preliminary study with a silicon microdosimeter for future applications … 2 microdosimetry 18 ......

CORSO DI LAUREA MAGISTRALE IN FISICA

Preliminary study with a silicon microdosimeterfor future applications in

Proton Boron Capture Therapy

Tesi di Laurea

Relatori:Prof. G. CuttoneCorrelatori:Dr. G.A.P. CirroneDr.ssa G. Petringa

Candidato:

Cinzia Gigliuto

Anno Accademico 2018/2019

Ai miei genitori e a mia sorella,

da sempre la mia forza

Contents

Introduction 1

1 Radiation therapy with heavy charged particles 3

1.1 Hadrontherapy . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2 Physical and Biological Aspects of radiation therapy . . . . . . . 4

1.2.1 Absorbed Dose . . . . . . . . . . . . . . . . . . . . . . . 5

1.2.2 Linear Energy Transfer (LET) . . . . . . . . . . . . . . . 6

1.2.3 Limitations of absorbed dose and LET . . . . . . . . . . 8

1.2.4 The Relative Biological Effectiveness (RBE) . . . . . . . 9

1.3 Proton Boron Capture Therapy . . . . . . . . . . . . . . . . . . 12

1.3.1 Physical considerations on the PBCT . . . . . . . . . . . 14

1.3.2 Experimental proof of PBCT . . . . . . . . . . . . . . . 15

2 Microdosimetry 18

2.1 Microdosimetric quantities . . . . . . . . . . . . . . . . . . . . . 18

2.1.1 Graphical representation of a microdosimetric spectrum . 21

2.2 Experimental methods in microdosimetry . . . . . . . . . . . . . 23

2.2.1 Proportional Counter Microdosimetry . . . . . . . . . . . 23

2.2.2 Solid state microdosimeters based on silicon devices . . . 27

3 MicroPlus probe and calibration 38

3.1 MicroPlus Probe (Mushroom microdosimeter) . . . . . . . . . . 38

3.1.1 Mushroom microdosimeter . . . . . . . . . . . . . . . . . 38

3.1.2 Probe and pulse-processing electronics . . . . . . . . . . 41

3.1.3 PMMA sheath . . . . . . . . . . . . . . . . . . . . . . . 43

3.2 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

3.2.1 Calibrated pulse generator . . . . . . . . . . . . . . . . . 44

3.2.2 Measurements with alpha sources and carbon ion beams 45

ii

CONTENTS

3.2.3 Comparison between measured and pulse calibrated energy 47

3.2.4 Gain MEDIUM and gain HIGH . . . . . . . . . . . . . . 49

4 Measurements with a 62 AMeV proton beam at the CATANA

facility 52

4.1 Experimental set-up . . . . . . . . . . . . . . . . . . . . . . . . 53

4.1.1 The CATANA prontontherapy facility . . . . . . . . . . 53

4.1.2 The irradiation set-up . . . . . . . . . . . . . . . . . . . 55

4.2 Monte Carlo Simulations . . . . . . . . . . . . . . . . . . . . . . 56

4.3 Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

4.3.1 Tissue equivalence correction and lineal energy . . . . . . 58

4.3.2 Microdosimetric spectra and uncertainties . . . . . . . . 59

4.4 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . 60

4.5 Comparison between simulation and experimental results . . . . 66

4.6 Measurements with a boron target . . . . . . . . . . . . . . . . 72

4.6.1 Experimental set-up . . . . . . . . . . . . . . . . . . . . 73

4.6.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

Conclusions 78

Bibliography 80

iii

Introduction

In the last 60 years, hadrontherapy has made great advances, going from a

stage of pure research to the consolidation of a standard treatment modal-

ity for solid tumours. This is particularly true for proton therapy, which has

emerged as the most rapidly expanding hadron therapy approach, counting

more than 80 facilities worldwide and totaling over 170,000 treated patients

[2]. The fast-growing interest in the use and development of particle therapy

stems from the urgent need to improve the precision of radiotherapy and its

biological effectiveness, reducing the risk of damaging healthy tissues and max-

imizing its effect in the cancerous regions [1].

The use of proton beams for cancer treatment can be more effective in com-

parison to conventional radiotherapy. This is due to the physical behaviour

and high ballistic precision of the heavy charged particles, which can deposit

energy far more selectively than photons, thanks to the inverted depth dose

profile described by the Bragg curve. However, one of the shortcomings of

proton therapy is its limited ability to treat radioresistant cancers [3]. While

this limit is partially overcome by densely ionizing heavier particles such as 12C

ions, the complications due to the fragmentation from the primary particle and

the high costs of the technology hamper its widespread adoption. Therefore,

new strategies are being developed with the aim of achieving a localized in-

crease in the relative biological effectiveness (RBE) of the protons.

A newly proposed approach based on a nuclear reaction triggered by the pro-

tons will be presented in this study. This approach is based on the use of

p+11B → 3α in order to enhance the biological effectiveness of the protons

limited to the region of the tumour, through the generation of short-range,

high LET alpha particles. The first experimental results [27], briefly reviewed

in Chapter 1, clearly illustrate the radiobiological effects caused by injecting

boron atoms in a biological sample. However, it turns out that the entity of

1

Introduction

the increase in the number of dead cells cannot be quantitatively justified by

the excess of dose that one would expect on the basis of the calculated number

of alpha-particles yielded for the reaction cross section at the given proton

energies. Therefore, in order to explain the phenomenon, one must look for

other concurring physical and/or biological factors. A more accurate analysis

is needed.

Macroscopic concepts like the absorbed dose or the average LET distribution

merely describe the radiobiological effect at the DNA level in a global, approx-

imate fashion. A more detailed knowledge of the interactions at the local level

can be achieved by exploiting the methodologies and instruments provided by

microdosimetry and nanodosimetry. The former aims at characterizing the sta-

tistical fluctuations of the local energy imparted at the micrometric level, while

the latter is devoted to the description of the pattern of particle interactions

at the nanometric level. In particular, microdosimetry studies the microscopic

physical properties of ionizing radiations, their interactions and their patterns

of energy deposition, with particular emphasis on the inhomogeneities and

stochastic nature of the interactions [28] (Chapter 2).

The aim of this work is to study a new silicon microdosimeter, the MicroPlus

probe, developed by the Centre for Medical Radiation Physics (CMRP) at the

Wollongong University for future applications in Proton Boron Capture Ther-

apy. The structure of the MicroPlus probe is based on the Silicon-On-Insulator

technology and consists of 3D cylindrical Sensitive Volumes (SVs) fabricated

on a 10 µm thick SOI substrate, the properties of which are described in

Chapter 3 together with the calibration procedure. The response of this new

silicon microdosimeter was investigated along the 62 MeV proton beam Spread

Out Bragg Peak (SOBP) at the “Centro di AdroTerapia e Applicazioni Nucle-

ari Avanzate” (CATANA) facility of the Istituto Nazionale di Fisica Nucleare

(INFN) - Laboratori Nazionali del Sud (LNS) in Catania, Italy. In Chapter 4,

the outcome of the measurements at the entrance, mid and distal SOBP using

the MicroPlus probe model #705 and #592 (the latter in collaboration with

the CMRP researchers) is reported. The experimental results were compared

with Monte Carlo simulations performed with the Geant4 toolkit. Finally,

in order to investigate the p+11B → 3α reaction, a set of measurements was

performed along the distal part of SOBP by placing a B4C target in front of

the detector. The results were then compared to those performed at the same

positions without the boron target.

2

Chapter 1

Radiation therapy with heavy

charged particles

1.1 Hadrontherapy

Radiation therapy is the treatment of malignant tumours by means of ionizing

radiation. Among the different treatments in radiation oncology, hadronther-

apy is an innovative therapeutic procedure for localized solid tumours, which

are difficult to treat with conventional radiotherapy [1]. Conventional radio-

therapy treats the tumours with high energy photons and electrons, while in

hadrontherapy protons and heavier ions like Carbon are used.

The idea of using protons for cancer treatment was first proposed in 1946

by the physicist Robert Wilson [4], while he was investigating the depth-dose

characteristics of proton beams, primarily for shielding purposes. He was the

first to recognise and investigate the potential benefits of using proton beams

[4]. The first patients were treated in the 1950s in nuclear physics research

facilities by means of non-dedicated accelerators [5]. Initially, the clinical ap-

plications were limited to few parts of the body, as the accelerators were not

powerful enough to allow the protons to penetrate deep in tissues. In the late

1970s, improvements in accelerator technology, together with advances in med-

ical imaging and computing, made protontherapy a viable option for routine

medical applications. However, it was not before the beginning of the 1990s

that proton facilities were established in clinical settings, the first one being in

Loma Linda, USA [6].

At the end of 2016, nearly 70 centres were in operation worldwide, and 63

3

1.2 Physical and Biological Aspects of radiation therapy

more are under construction or in the planning stage (Fig. 1.1).

Most of these are proton centres. Globally there is a huge momentum in parti-

cle therapy, especially for what concerns the treatment with protons. By 2021,

there will be 130 centres operating in almost 30 different countries.

Figure 1.1: Hadrontherapy facilities in operation, under construction and in

the planning stage worldwide at the end of 2016. From the Particle Therapy

Co-Operative Group (PTCOG).

1.2 Physical and Biological Aspects of radia-

tion therapy

The aim of radiotherapy is to deliver a dose to the tumour while sparing the

healthy tissue surrounding it.

Photons and electrons lose energy exponentially as they penetrate tissues (see

Fig. 1.2). Due to the nature of their interaction with matter, in order to

deliver a certain amount of dose to the tumour, part of the radiation dose will

be absorbed by the tissues that surround the target volume. Therefore, to

maximise the dose and to spread out the unwanted entrance dose, the strategy

used in conventional radiation therapy is to use beams crossing from many

angles. On the other hand, hadrons deposit almost all of their energy in a

sharp peak called the Bragg peak at the end of their path. According to the

4


Bethe formula1, the energy lost by charged particles is inversely proportional

to the square of their velocity. As a consequence, a peak occurs just before the

particle comes to a complete stop. Thanks to the Bragg peak it is possible to

target a well-defined cancerous region at a depth that can be tuned by adjust-

ing the kinetic energy of the incident beam. The strength of hadrontherapy

lies in these unique physical and radiobiological properties of heavy charged

particles. These features make it possible to obtain a better dose conforma-

tion and a more selective tailoring of the biological area to be treated. Such

an increase in precision is essential in the cases where a target tumour is close

to sensitive healthy tissues. A comparison of depth-dose profiles for photons,

electrons and ions is shown in Fig. 1.2.

Figure 1.2: The energy deposition of different particles in matter. For ions the

Bragg peak appears clearly.

1.2.1 Absorbed Dose

In radiation therapy, dosimetry is adopted to quantify the deposited energy

in a biological sample and to evaluate the radiation-induced effects (physical,

chemical, and/or biological). Several quantities and units have been defined by

the International Commission of Radiation Units and Measurements (ICRU

1 Bethe formula: −dEdx = 4πQ2e2nZmβ2c2

[ln(

2mc2γ2β2

I− β2

)], where m is the rest mass of the

electron, β equals to v/c – the particle velocity divided by the speed of light – γ is the

Lorentz factor of the particle, Q is the particle’s charge, Z is the atomic number of the

medium and n is the number density of the atoms in the medium.

5


Report 60) for describing the radiation sources and the amount of energy they

may deposit in different media [7].

In this framework, the fundamental quantity is the so-called absorbed dose,

expressed in gray (Gy) and defined as the quotient:

D =dE

dm(1.1)

where dE is the mean energy imparted to an amount of matter of mass dm.

Radiobiological and clinical effects are directly related to the absorbed dose,

and are strictly connected to the radiation quality. Radiation quality is a quan-

tity related to the type of particle and its energy spectrum. For equal absorbed

doses, radiations of different quality produce different levels of biological and

clinical effects, and may lead to important differences in the degree of harm

for a specific biological endpoint. For this reason, in many practical situations

the absorbed dose is not an appropriate measure.

1.2.2 Linear Energy Transfer (LET)

The pioneering experiments by Zirkle (1935) [9] and a multitude of subsequent

studies have established that the biological effectiveness of a radiation depends

not only on the amount of energy absorbed, but also on the spatial distribu-

tion of energy deposition. Since the energy is imparted in or near the tracks of

charged particles, it has been considered convenient to express the heterogene-

ity of energy deposition in terms of the linear density of energy loss in these

tracks [10].

The term Linear Energy Transfer (LET) has been coined by Zirkle et al. (1952)

and since its introduction it is adopted to describe the radiation quality. The

LET measures the average ionization density of a charged particle along its

path direction. Following ICRU (2011) [8] the linear energy transfer or re-

stricted linear electronic stopping power, L∆, of a material, for charged par-

ticles of a given type and energy, is the quotient of dE∆ by dl, where dE∆ is

the mean energy lost by the charged particles due to electronic interactions in

traversing a distance dl, minus the mean sum of the kinetic energies in excess

of ∆ of all the electrons released by the charged particles:

6


L∆ =dE∆

dl(1.2)

It is usually measured in keV/µm. If no energy cut-off is imposed, the unre-

stricted LET is equivalent to the linear electronic stopping power. L∆ specifies

the amount of local energy imparted to the target. It has been observed that

high-LET radiations like charged ions are in general more effective in caus-

ing biological damages than the low-LET ones (i.e. photons and electrons).

The greater biological effectiveness of densely ionizing radiation is a direct

consequence of the physical pattern of energy deposition events along and

around its tracks. Low-LET ionizing radiations induce sparse ionizations and

mainly damage cells through short-lived bursts of free radicals (e.g. reactive

oxygen species) generated by their interactions with the intracellular environ-

ment. This causes isolated lesions at the DNA level. Instead, the much denser

thread of ionization events specific to track-structured high-LET particle ra-

diations results in many closely spaced clusters of multiply DNA damaged

sites, comprising DSBs together with single-strand breaks and damaged bases,

which cause irreparable damages and cell killing. A schematic description of

low-LET and high LET radiation is displayed in Fig. 1.3.

Figure 1.3: Comparison of Low-LET and High-LET radiation fields, distin-

guishing sparsely from densely ionizing radiation fields.

7


1.2.3 Limitations of absorbed dose and LET

Medical dosimetry based on absorbed dose is a well-developed concept, but it

has known limitations, summarized as follows:

• The absorbed dose is independent of radiation quality; therefore, a sys-

tem of dose weighting factors is necessary, especially when radiation fields

with components of high linear energy transfer (LET) are used and the

biological effect is to be determined.

• It becomes meaningless if the sensitive measurement volume is very

small. Indeed, on the microscopic level, energy deposition – especially

when high-LET particles are involved – becomes inhomogeneous and the

energy imparted varies over several orders of magnitude.

• The absorbed dose averaged over a larger volume does not necessarily

represent the risk associated with very low doses, especially when the

radiation dose is delivered by a few particles of high LET (for example

in space radiation, alpha particle, or low-fluence neutron exposures).

As well as the dose, LET also is an average quantity and therefore it too has

several limitations [30].

Firstly, the delta ray energy distribution and its relationship to the spatial

dose distribution are not adequately taken into account. The particle velocity

largely determines the energy distribution of delta rays, but particles with

different velocities and charge can have the same LET. In microscopic volumes,

the delta rays distribution may be a significant factor in the spatial distribution

of energy, especially at high ion energies and small site sizes.

A second limitation is due to the short range of low-energy particles, which

may stop within the volume of interest or change their LET significantly as

they pass through it.

Finally LET, being a non stochastic average quantity, does not account for the

random fluctuations in the energy deposition along the tracks, which manifest

themselves in the clustering of energy deposition and in range straggling. At

high ion energies and small site sizes, the variance due to straggling may exceed

the path length variations.

8


1.2.4 The Relative Biological Effectiveness (RBE)

The specific biological effects of charged particle radiation have been recognized

as early as 1935 (Zirkle, 1935) [9]. However, systematic studies have been per-

formed only after the accelerators became an important tool for nuclear physics

studies and could then also be used as radiation sources for radiobiological ap-

plications. Cultured cells, plant seedlings, healthy and tumor-bearing animals

were irradiated and an endpoint, such as cell survival, chromosomal aberra-

tions, histological changes, LD50, etc. was examined. The central subject of

these experiments was the biological effectiveness of the accelerated ions in

comparison to the effect caused by the same physical dose of a reference radia-

tion, mostly 250 kV X-rays or 60Co γ-rays. For the X-rays or 60Co γ-rays, the

biological response is a non-linear function of the dose and for doses up to a

few gray cell inactivation can be approximated with good accuracy by a linear

quadratic expression in the dose D:

S = S0 exp (αD + βD2) (1.3)

where S is the fraction of surviving cells [18]. For particle radiation of increas-

ing linear energy transfer (LET) the beta term is small, so that the radiation

response is given by a pure linear dose relationship [19].

The Relative Biological Effectiveness (RBE) is defined as the ratio of X-ray

(or 60Co gamma ray) dose DX to particle dose Dparticle required to yield the

same biological endpoint (Fig. 1.4) [20]:

RBE =DX

Dparticle

(1.4)

The RBE depends on several parameters: the type and energy of the radiation,

the type of cell or tissue, the dose, the dose rate and fractionation. Due to

the large numbers of parameters, RBE values are not easily accessible; there-

fore various models have been proposed to estimate RBE values from physical

measurements.

In first approximation the RBE is related to the LET. The first RBE-LET re-

lation obtained by Barendsen [11] for alphas and deuterons showed an increase

of RBE with LET until a maximum (100 KeV/um) was reached, followed by

a decrease attributed to cell overkilling.

9


This trend was confirmed later in many other experiments using different type

of cells [12, 13, 14].

Figure 1.4: Definition of the Relative Biological Effectiveness, illustrated for

cell survival curves.

In general, these experiments show that the height of the RBE maximum

decreases continuously with increasing atomic number, while the position of

the RBE maximum is shifted to greater LET values. The experimental findings

can be explained with the assumption that the local distribution of ionization

density inside the particle track is as important as the total energy. The value

of LET gives the total dose released, while the radial distribution of said dose

depends on the projectile energy. By consequence, the RBE is not a unique

function of the LET, but rather a combination of the two parameters: LET

and energy determine the RBE and its position in the LET spectrum (Fig.

1.5). Moreover, the LET changes with the depth travelled in tissue and so

does the RBE, making any RBE-value assumption inaccurate.

In proton therapy a RBE value of 1.1 is currently adopted, while the average

RBE for carbon ions is much higher, estimated to be 2.5-3. However, more

refined studies show that low-energy (< 1 MeV) and very high-energy (> 1

GeV) protons can reach an RBE of 2 or more, depending on the studied

radiobiological endpoint.

10


Figure 1.5: Relative biological effectiveness (RBE) of different ions as a func-

tion of linear energy transfer (LET). The RBE maximum is shifted to higher

LET for heavier particles; the shift corresponds to a shift to higher energies.

11

1.3 Proton Boron Capture Therapy


The advent of hadrontherapy has allowed to study and develop new non-

invasive therapeutic modalities. In this framework, the use of binary ther-

apeutic systems based on nuclear capture and fission reactions has been in-

vestigated. The Boron Neutron Capture Therapy (BNCT) is one of the most

famous binary approaches already applied in clinical practice [22].

The BNCT is a technique that selectively aims to treat tumour cells while

sparing the normal cells by using boron compounds. Gordon Locher was the

first one to advance the principle of BNCT in 1936. He hypothesized that

if boron could be selectively concentrated in a tumour mass, and the volume

then be exposed to thermal neutrons, a higher radiation dose to the tumour

compared to adjacent normal tissue would be produced [15].

This technique is based on the nuclear reaction that occurs when 10B is irra-

diated with low-energy thermal neutrons to yield high linear energy transfer

α particles and recoiling 7Li nuclei.

The cross sections for the 10B(n,α)7Li reaction is 3837 barn at neutron thermal

energies (Q-value= 2.790 MeV) [21]. The 7Li ion and alpha particle provide

high energy along their very brief pathway (< 10 µm). Hence, their energy

deposition is limited to the diameter of a single cell and only neoplastic cells

with 10B are ravaged following thermal neutron irradiation.

In light of this, a new binary approach has recently been investigated to en-

hance the biological effectiveness of protons, since in the clinical energy range

their LET is too low to achieve a cell killing significantly greater than that

of conventional radiotherapy. The main concept in this new technique is the

use of nuclear reactions triggered by the protons themselves which are able to

generate short-range high-LET particles inside the tumours, causing a highly

localized DNA-damaging action. Specifically, this approach allows to exploit

the 11B(p, α)8Be nuclear fusion reaction channel through which three alpha

particles are emitted [16], idea theoretically proposed by Do-Kun Y et al. in

[17].

A schematic representation of conventional radiotherapy by low-LET proton

beams illustrating the rationale of boron-enhanced protontherapy is shown in

Fig. 1.6.

12


Figure 1.6: Schematic representation of conventional radiotherapy by low-LET

proton beams and the rationale of boron-enhanced protontherapy. Whereas in

conventional radiotherapy the incident proton beam mainly produces isolated,

mostly repairable DNA breaks, the extremely localized emission of high-LET

radiation produced by the proton-boron fusion in the Bragg peak region causes

irreparable clustered DNA damage, hence the expected increase in the effec-

tiveness of tumour cell killing.

13


1.3.1 Physical considerations on the PBCT

The considered proton-boron nuclear reaction is formalized as p+11B→ 3α. It

has a positive Q-value (8.7 MeV) and is referred to as a proton-boron fusion

reaction. This reaction has gathered interest since the 1930s [23, 24] because

of its ability to produce large numbers of alpha particles in an exothermic reac-

tion. According to the literature, the p-B nuclear fusion reaction shows three

resonant energies (0.162 MeV, 0.675 MeV, 2.64 MeV) and can be described as

a two-step reaction in which three alphas are produced. First of all, a proton

interacting with a 11B nucleus induces the formation of a 12C∗ compound nu-

cleus in the 2− or 3− excited state. 12C∗ then decays in one alpha particle and

one 8Be that, in turn, immediately decays in two secondary alpha particles.

In particular, if the 12C∗ nucleus is formed in its 2− state, it will decay to the

first 2+ state of 8Be by emitting one alpha-particle with angular momentum

l = 3 [16]. If the 12C∗ nucleus is formed in its 3− state, then the primary alpha

particle can be emitted either with l = 1 from the decay to the first 2+ 8Be

excited state, or with l = 3 from the decay to the 0+ ground state of 8Be. In

both cases (2+ or 0+), the resulting 8Be nucleus immediately decays into two

secondary alpha particles with l = 2. The alpha particles emitted in the first

stage present a well-defined energy distribution and are commonly referred to

as α0 and α1 respectively if the 8Be 2+ or 0+ states are populated.

Some authors [16, 26] report a very unlikely fourth channel where 12C∗, skip-

ping the intermediate 8Be stage, directly breaks into three α particles which

show a continuous energy distribution. This channel is characterized by a

maximum cross section of 10 µb in the 2.0-2.7 MeV energy range.

The total cross section for the most probable α1 channel decay is displayed

in Fig. 1.7, showing the resonance at 675 keV [25]. The maximum cross sec-

tion occurs at low proton energy, corresponding to the tumour region where

the incident proton beams lows down. This maximises the alpha particle pro-

duction around the proton Bragg peak region and in principle eliminates the

constraint of a differential uptake of the carrier between normal and cancer

cells, bypassing the main drawbacks of BNCT.

14


Figure 1.7: p+11B total reaction cross section for the most probable α1 channel

decay (from the EXFOR database).

1.3.2 Experimental proof of PBCT

The first experimental test of the p+11B→ 3α nuclear fusion reaction aimed at

enhancing the biological effectiveness of protons was performed at INFN-LNS

[27]. Cells from human prostate cancer line DU145 were irradiated with graded

doses at the middle position of the 62 MeV clinical Spread-Out Bragg Peak of

the INFN-LNS protontherapy ocular facility. Irradiations were performed in

presence of two concentrations of sodium borocaptate (Na2B12H11SH or BSH).

The BSH is a common agent clinically used in BNCT in its 10B-enriched form

to selectively deliver given boron concentrations in cancer cells. In this experi-

ment, in order to maximize the fusion rate, the considered BSH concentrations

were equivalent to 40 ppm and 80 ppm of 11B. These values were chosen on

the basis of what is done for the 10B-enriched BSH used in BNCT. The boron

treatment enhanced the proton biological effectiveness: the cells that were ir-

radiated after pre-treatment with, and in the presence of, boron-containing

BSH exhibited a greater radiosensitivity in comparison with cells exposed to

radiation alone.

15


In Fig. 1.8 the clonogenic dose response curves of prostate cancer cells DU145

irradiated with therapeutic protons in the presence or absence of BSH at mid-

SOBP is reported. The BSH-treated cells yield a much steeper dose-response

curve than those irradiated in the BSH-free medium.

Figure 1.8: Boron-mediated increase in proton irradiation-induced cell death.

Clonogenic dose response curves of prostate cancer cells DU145 irradiated with

therapeutic protons in the presence or absence of BSH at mid-SOBP.

In order to verify that the pB nuclear reaction depends on the incident proton

energy, the induction of cell killing in the presence of the boron compound at

the concentration of 80 ppm 11B was investigated by irradiating the cancer

DU145 cell line at the beam entrance (position P1), at the middle (position

P2) and at the distal (position P3) of the SOBP as reported in Fig. 1.9.

Fig. 1.10 shows the clonogenic survival dose-response curves derived from the

three positions along the SOBP in the absence and in the presence of BSH.

The enhancement of cell killing due to the presence of the boron compound

is null at the beam entrance (highest proton mean energy) and reaches its

maximum at the distal end of the SOBP (lowest mean proton energies).

16


These experimental results confirm that the enhancement of the biological

effectiveness is caused by the occurrence of pB nuclear fusion events, which

have a higher cross section at the end of the protons’ range.

Figure 1.9: Measured dose and calculated LET profile for cellular irradiation

at different positions along the clinical proton SOBP at INFN-LNS, Catania,

Italy. The cells were irradiated in the three positions displayed above.

Figure 1.10: Clonogenic survival dose-response curves obtained at positions

P1, P2 and P3 as indicated along the clinical proton SOBP.

17

Chapter 2

Microdosimetry

Microdosimetry could be defined as “the study of the physical microscopic

properties of ionizing radiations, their interactions and their pattern of depo-

sition, with particular emphasis on the inhomogeneities and stochastic nature

of the interactions” [28].

The concept of microdosimetry originated when Harald H. Rossi, the founder

of this new approach, developed a conceptual framework as well as correspond-

ing experimental methods for the analysis of the microscopic distribution of

energy deposition in irradiated matter [29, 30]. Its principal application has

been in the field of radiobiology, even if the microdosimetric concepts are also

applied in several other fields, such as radiation chemistry, radiation protec-

tion, radiation therapy and dosimetry [29]. This new approach contrasts with

conventional dosimetry, which is based on average macroscopic quantities as

the absorbed dose. Like other macroscopic quantities (e.g. temperature and

pressure), the absorbed dose describes the average state of the system; it ap-

plies only to macro-states near equilibrium and is inadequate to describe the

effects of radiation in small domains of cellular and sub-cellular dimensions.

The limitations of the absorbed dose and LET lead to the formulation of a set

of stochastic quantities which provide the fundamental basis for the description

of the energy-deposition events in microscopic structures.

2.1 Microdosimetric quantities

The formal definitions of the relevant microdosimetric quantities are reported

in ICRU report 36 [30]. The difference between stochastic and non-stochastic

18


quantities is central to microdosimetry. In brief, stochastic quantities are quan-

tities which are subject to random fluctuations. On the other hand, a non-

stochastic quantity is the expectation value of a stochastic quantity, and is

therefore an average quantity.

An elementary stochastic quantity is the energy deposit εi. It is introduced

for the description of the inchoate spatial distribution of energy in charged

particle tracks and is the energy deposited in a single interaction i:

εi = Tin − Tout +Q∆m (2.1)

where Tin and Tout are respectively the kinetic energy of the incident ionizing

particle and the sum of the kinetic energies of all ionizing particles leaving

the interaction and Q∆m is the change in the rest mass energy of the particles

involved in the reaction. εi is usually measured in eV or multiples thereof.

The energy imparted ε to the matter contained in a volume is defined as the

sum of all energy deposit events in that volume:

ε =∑i

εi (2.2)

The quotient of ε by m, where m is the mass of the matter contained in a

volume, gives the (imparted) specific energy z, that is

z =ε

m(2.3)

z is measured in gray (Gy) and it is a stochastic quantity.

In microdosimetry, it is useful to consider the frequency probability density

f(z) associated to z; f(z) is the derivative of the distribution function F (z)

with respect to z. The expectation value of z, given by

z =

∫ ∞0

zf(z)dz (2.4)

is called the mean specific energy. Being an average, it is a non-stochastic

quantity. In the limit of a large number of events in the site volume, the distri-

bution of specific energy shows small fluctuations around its mean value, and

the average of the multi-event value of the specific energy can be interpreted

as the absorbed dose D:

D ≈ z =

∫ ∞0

zf(z)dz (2.5)

19


The lineal energy is the quotient of the energy ε imparted to the volume due

to a single event by the mean chord length l in that volume:

y =ε

l(2.6)

y has the dimensions of an energy divided by a length and is most commonly

measured in keV/µm. The mean chord length in a volume is the mean length

of randomly oriented chords in that volume [36]. According to a theorem by

Cauchy [32], for a convex body l = 4VS

where V is its volume and S is its

surface area.

This parameter is introduced to take into account the geometry of the inter-

action, since the paths of energy deposition can intersect the site in a variety

of chord lengths.

The lineal energy is a stochastic quantity. The frequency probability density

associated to a single event is given by

f(y) =dF (y)

dy(2.7)

where F (y), the distribution function, represents the probability that the lineal

energy is equal to or less than y. f(y) is the frequency probability density of

having one event with lineal energy within the interval [y, y + dy]. It is also

called the lineal energy distribution and is independent of the absorbed dose or

dose rate. The expectation value of y (first moment of the f(y) distribution)

is

yF =

∫ ∞0

yf(y)dy (2.8)

yF is called the frequency-mean lineal energy and is a non-stochastic quantity.

It is also useful to consider the dose distribution D(y) of lineal energy and its

corresponding dose probability density d(y). The relation between d(y) and

f(y) is

d(y) =y

yFf(y) (2.9)

The expectation value of y with respect to d(y) (i.e. the second moment of the

f(y) distribution) is the dose-mean lineal energy :

yD =

∫ ∞0

yd(y)dy =1

yF

∫ ∞0

y2f(y)dy (2.10)

20


By definition the probability density functions are normalized to unity:∫ ∞0

f(y)dy =

∫ ∞0

d(y)dy = 1 (2.11)

2.1.1 Graphical representation of a microdosimetric spec-

trum

Most of the microdosimetric distributions span a rather large spectrum of val-

ues. To deal with this large range of energies and to compare results obtained

under different experimental conditions, the conventional approach consists in

dividing the lineal energy axis into equal logarithmic intervals, while presenting

the frequency or dose distributions on a linear axis. In the frequency distribu-

tion spectrum, equal areas represent equal fractions of observed events, while

in the dose distribution spectrum equal areas between different lineal energy

values represent equal fractions of dose imparted by those events (Fig. 2.1).

Figure 2.1: Dose distribution: in the yd(y) vs. log y representation, equal areas

under the curve represent equal fractional doses.

21


In order to preserve the probabilistic meaning of the areas displayed in the

semi-logarithmic spectra, the yf(y) vs. log(y) and yd(y) vs. log(y) represen-

tations are adopted. In fact, the normalization in equation 2.11 is unchanged

if:

∫ y2

y1

f(y)dy =

∫ y2

y1

yf(y)d(ln y) = ln 10

∫ y2

y1

[yf(y)]d(log y)

(2.12)∫ y2

y1

d(y)dy =

∫ y2

y1

yd(y)d(ln y) = ln 10

∫ y2

y1

[yd(y)]d(log y)

therefore the area delimited by y1 and y2 maintains the same information. The

same considerations hold for the dose distributions representation d(y); when

presented in this way, equal areas under different regions of the function yd(y)

correspond to equal doses. When the spectrum is presented in its standard

semi-log form, care must be taken to perform the correct normalization for

a logarithmically binned histogram, as discussed in Appendix B of ICRU 36

[30].

By definition, the distribution d(y) is normalized to unity (eq. 2.11). This

normalization should remain unchanged when plotted in the logarithmic scale

of y by using the logarithmic binning.

The logarithmic scale of y is subdivided into B increments per decade such

that the ith value of y is

yi = y0 · 10iB (2.13)

Using eqq. 2.11 and 2.12, the following relationship must be verified:∫ ∞0

yd(y)d(ln y) ≈ ln 10

B

∞∑i=0

yid(yi) = 1 (2.14)

The approximation in 2.14 is valid when the number B of increments per

decade is large enough that the difference between d(log y) and ∆(log y) can

be neglected:

d(log y) ≈ ∆(log y) =1

B(2.15)

22

2.2 Experimental methods in microdosimetry


Microdosimetric measurements consist in evaluating experimental quantities

closely related to the imparted energy ε.

Different types of detectors are used to perform these measurements: the gas-

filled Tissue Equivalent Proportional Counters (TEPC) and solid-state detec-

tors are the most common ones. In the next sections these detectors will be

briefly described, specifying the advantages and limitations of each detector

when microdosimetric spectra are investigated.

2.2.1 Proportional Counter Microdosimetry

The Tissue Equivalent Proportional Counters are the benchmark and most

commonly used microdosimetric devices. TEPCs consist of a spherical or a

cylindrical gas chamber with a central anode wire electrically isolated from the

surrounding chamber walls. A proportional counter operates in pulse mode

and provides an electrical signal which is proportional to the number of ion

pairs resulting from an energy-deposition event. If a sufficiently high electric

field is applied between the anode and the conductive wall, the number of ions

is amplified in magnitude by gas multiplication. In particular, the electrons

generated in the ionization process of the gas molecules by the radiation field

drift towards the anode wire under the effect of the voltage difference between

the electrodes. In this region, called avalanche region (or multiplication zone),

each ion or electron acquires enough energy to produce secondary and higher

generation ions through collisions with the gas molecules [35].

Simulation principle

The simulation of a micrometric volume of tissue of 1 g/cm3 is obtained by

replacing the volume with a larger cavity filled with a tissue equivalent gas of

lower density. In order to obtain the simulation of energy deposition in small

tissue volumes, the energy lost by a charged particle in the counter gas must

be the same as that lost on an equivalent trajectory in the tissue volume.

For a tissue sphere of diameter dt, density ρt and mass stopping power (S/ρ)t

and a gas sphere with dg, ρg and (S/ρ)g, the required condition of equivalent

energy loss is:

23


∆Et = (S/ρ)tρtdt = (S/ρ)gρgdg = ∆Eg (2.16)

where ∆Et and ∆Eg are the mean energy losses from the charged particle

in the tissue and gas. If the tissue and the gas have an identical atomic

composition and the mass stopping powers are independent of density, so that

(S/ρ)t = (S/ρ)g, equation 2.16 becomes

ρtdt = ρgdg (2.17)

Thus, if the ratio of gas to tissue diameter is kgt, then the density of the

gas must be reduced from that of tissue by the same factor. It should be

noted that the mass of gas in the counter is much greater than that in the

simulated tissue volume, by the factor k2gt. Therefore, more interactions will

occur in the counter for a given absorbed dose, but the energy deposition from

individual interactions will be correctly simulated because the energy loss along

corresponding trajectories will be equivalent.

In order to properly simulate the tissue volume, the density variation at the

interface between the counter walls and the filling gas should not affect the

energy deposition from the primary particle.

As stated by Fano’s theorem, in a medium of constant atomic composition,

the fluence of secondary particles is constant if the fluence of primary particles

is constant. Under this condition, the fluence is independent of the density

variations. For ensuring the condition of this theorem the atomic composition

of the wall and the gas must be identical. For this reason, the proportional

counters conventionally applied in microdosimetry have walls made of tissue-

equivalent (TE) plastic (generally A-150 TE plastic) and are filled with tissue-

equivalent gases (propane-based or methane-based). However, the condition

cannot always be met in practice. The requirement that the mass stopping

powers are independent of density is not always fulfilled due to polarization

effects in solids (with fast charged particles) [34].

24


Limitations of TEPCs

In the TEPCs, it is fundamental that the multiplication zone is confined near

the anode wire: if the avalanche region is small enough, the gas multiplication

does not depend on the point of formation of the primary ion/electron pairs.

However, by decreasing the gas pressure to simulate very small site sizes us-

ing conventional TEPCs, the amplification region increases so that the counter

output ceases to be independent of the spatial distribution of primary ion pairs

in the sensitive volume. In order to keep the amplification region confined, the

voltage must be reduced; this in turn decreases the gain. At lower pressure

charged particles lose less energy in the counter and the amplitude of the signal

from the TEPC becomes too low to be detected. Thus, at low pressures the

electronic gain must be significantly increased to provide a detectable signal.

Nevertheless, any attempt to increment the gas gain leads to a significant en-

largement of the electronic avalanche. The consequence of this effect is a loss

of resolution of the system. For this reason there is a limit on the pressure or,

equivalently, the size that can be simulated. The generally accepted limit on

the simulated diameter due to the expansion of the gas multiplication region

is around 0.3 µm, although a well defined limit does not exist because this de-

pends on the criterion used for the maximum tolerable spectrum deterioration

as well as on the applied electric field and gas pressure [30].

The quality of a microdosimetric measurement performed with a TEPC strongly

depends on the atomic composition and on the pressure stability of the fill-

ing gas. For this reason, it is important to avoid any contamination. This is

particularly difficult, since the walls in tissue equivalent plastic adsorb the TE

filling gas and release electronegative gases (including oxygen). The best way

of ensuring constant composition and pressure is to employ a gas flow system.

However, the need of a continuous tissue-equivalent gas flow system induces

practical difficulties and additional costs in the management and the mainte-

nance of the detection system. Even if the wall and TE gas have the same

atomic composition, density differences between the cavity and the wall can

lead to the scattering of the primary particle, and branches of secondaries and

tertiaries will be generated departing from the primary particle track. This

effect is called wall-effect and causes an increase in energy imparted by super-

position of energy deposition events that would not simultaneously occur in a

medium of uniform density.

25


Figure 2.2: Schematic representation of a wall effect: a track in the high density

(a) and low density (b) materials, distorted as it penetrates from the high to

the low density media (c). [29]

The result is a distortion in the experimental microdosimetric distributions

[30]. The wall-effects are more significant for electrons (more subject to de-

flections in the medium). They become even more relevant with increasing

cavity size and depend on the particle “quality” (namely nuclear charge, ve-

locity and mass). Rossi [36] was the first to suggest such effects with a detailed

theoretical treatment subsequently given by Kellerer [37]. An example of wall

effect is shown in Fig. 2.2, where a curved track experiments distortions at

the interface between two materials with different densities.

A complete classification and description of the wall-effects is reported in [30].

The wall-effects are minimized by wall-less TEPCs, exploiting material grids

or field-shaping electrodes to delineate the sensitive volume boundaries.

Mini-Tissue Equivalent Proportional Counters (Mini-TEPCs)

TEPCs are characterized by an optimum tissue-equivalence, and their response

to primary and secondary charged particles is accurate over a wide energy

range. In order to improve the physical description of the hadron treatment

fields and therefore to increase the accuracy of the treatment itself, miniatur-

ized counters named mini-TEPCs were developed (Fig. 2.3) [38, 39].

26


The small size allows to obtain a high spatial precision and to reduce the pile-

up effects that arise when high-rate particle beams are inspected, due to the

small number of intercepted particles.

This technique can measure not only the usual dose distributions, but also the

local fluctuations of the imparted energy, which can be useful for a more com-

prehensive knowledge of the physical process leading to the biological effects.

Figure 2.3: Scheme of the Mini-TEPC, the green part represents the sensitive

volume, the red part is the cathode and the yellow part is the insulating plastic.

On the right the pipes for the gas entrance and exit are indicated.

2.2.2 Solid state microdosimeters based on silicon de-

vices

The limitations of the TEPCs raise the need for alternative methods to perform

microdosimetric measurements. Solid state microdosimetry based on silicon

detectors is a good candidate for clinical quality assessment in hadron therapy,

especially due to the low cost and easy accessible silicon technology.

Semiconductor detectors have become widespread in radiation detection appli-

cations thanks to their high resolution, fast timing characteristics and compact

size. The use of semiconductor devices for microdosimetry has been investi-

gated since 1980 [40]. The first device employed for this purpose was a 7 µm

thick Si(Li) detector irradiated with a beam of negative pions. Since then,

several devices (mainly silicon diodes) were investigated thanks to their ability

of performing microdosimetric measurements in various fields, such as cosmic

radiation and radiation protection [41, 42, 43, 44].

27


Physical principles of semiconductor detectors

In semiconductor detectors, the fundamental information carriers are electron-

hole pairs, which are produced along the path taken by the charged particle

(primary or secondary) through the detector. In the absence of thermal exci-

tation, the semiconductor exhibits a valence band filled with electrons and an

empty conduction band. An electron can be promoted from the valence band

to the conduction band through thermal excitation or by ionizing radiation.

The excitation process not only creates an electron in the otherwise empty con-

duction band, but it also leaves a vacancy (called hole) in the otherwise full

valence band. The electron-hole pair is roughly the solid-state analogue of the

ion pair in gases. In silicon the energy gap between the conduction and valence

band is Eg = 1.12 eV at room temperature. The concentration of electrons

and holes (n and p) is equal to the intrinsic concentration ni = 1.45 · 1010cm−3

(at 300 K).

One of the most-important properties of a semiconductor is that it can be

doped with different types and concentrations of impurities to vary its resis-

tivity. Also, when these impurities are ionized and the carriers are depleted,

they leave behind a charge density that results in an electric field and some-

times a potential barrier inside the semiconductor. Pentavalent atoms like

phosphorous provide an electron that is not used in the bonds with the sur-

rounding silicon atoms. The energy necessary to promote this electron to the

conduction band is 0.045 eV; thus, at room temperature, practically all P

atoms present in the crystal contribute with one electron to the conduction

band. The phosphorus atoms, referred to as donors, sit in the silicon lattice

as fixed positive charges. Silicon with an excess of electrons in the conduction

band is called n-type silicon. The electrons are the majority carriers in n-type

silicon. By adding trivalent atoms to the silicon crystal, like boron, the oppo-

site effect is obtained. The boron atoms lack one electron to form the bonds

with the four surrounding silicon atoms; therefore an electron is transferred to

boron from a silicon atom. This results in a hole in the valence band. The

boron atoms sit in the silicon crystal as fixed negative charges and are referred

to as acceptors. Silicon with an excess of holes in the valence band is called

p-type silicon. The usefulness of semiconductors as circuit elements and for

radiation measurement stems from the special properties created at a junction

where n and p type semiconductors are brought into contact (Fig. 2.4).

28


Figure 2.4: Illustration of the p-n junction. (a) energy band diagram for ptype

and n-type silicon, (b) energy band diagram showing the generation of the

contact potential.

When the n- and p-type silicon are brought into contact, the free electrons of

the n-type silicon diffuse into the p-type, hereby annihilating holes, and vice-

versa. The result is a region (called the space charge region, SRC) of silicon

where no free charge carriers are present and the fixed charge of the dopants

is not compensated. The diffusion goes on until the electric field in the space

charge region produces a potential difference (built-in voltage) that stops the

diffusion process.

29


When an external voltage is applied to the pn-junction with the higher poten-

tial applied to the n-type silicon and the lower potential to the p-type (reverse

bias), the space charge region, also called the depletion region, becomes larger

and the contribution of majority carriers to the current traversing the junction

is heavily suppressed. This reduces the current enough to allow a practical

operation of silicon detectors at room temperature [35] .

Advantages, disadvantages and limitations of silicon microdosime-

ters

The growing interest in silicon microdosimetry is due not only to practical

criteria as the ease of use and technological accessibility of silicon devices, but

also to their performance. One of the most significant features of silicon micro-

dosimeters consists in the possibility of constructing devices with micrometric

dimensions. The energy resolution depends on the silicon device capacitance

and on the preamplifier noise. In silicon devices the contribution due to the

preamplifier noise is more significant to the overall resolution than for the pro-

portional counters, for which the theoretical contributions, such as the Fano

factor and gas multiplication, dominate. At higher energies the theoretical

contributions to the energy resolution are dominant, while the preamplifier

noise is a less significant factor. Since the theoretical contributions are lower

with respect to TEPCs, silicon microdosimeters show a better resolution at

higher energies. On the contrary, TEPCs offer better performance at lower

energies, especially in terms of low energy sensitivity since they are capable of

single ionization detection.

Features such as the excellent spatial resolution, the capability of in-vivo oper-

ation and the pile-up robustness, make silicon detectors remarkably adequate

for hadrontherapy applications. In addition, their compactness, low cost, abil-

ity of multiple shape manufacturing, transportability and low power consump-

tion make silicon devices a viable alternative to the TEPCs. However, other

problems are encountered when using silicon devices. First of all, silicon is

not a tissue-equivalent material and has to be corrected for tissue equivalence.

A second important issue in silicon microdosimetry is the poorly defined sen-

sitive volume. A well-defined sensitive volume is one of the most important

requirements in microdosimetry.

30


In silicon devices this condition cannot be easily fulfilled since often charge

collection is not limited to the inside of the depletion region.

One reason for this is the field funnelling effect [45], a local distortion of the

electric field in the sensitive zone, induced by high-LET particles, which leads

to charge collection outside the depletion region. In addition to these effects,

the moderate radiation hardness of silicon devices can also affect the charge

collection process.

The main properties of the TEPCs and silicon microdosimeters are summa-

rized in Tab. 2.1. The last decade of research has been aimed at improving the

silicon microdosimeters. If the reported problems are adequately addressed,

the many advantages of silicon microdosimetry may prove useful in future and

current applications.

Category Parameter TEPC Silicon microdosimeter

Energy Resolution Moderate Moderate

Low energy

sensitivity

Excellent, Single Ionizations,

Minimum y = 0.05 keV/mm

Moderate,

Minimum y = 0.4 keV/mm

Sensitive volume

definitionGood Moderate

Tissue Equivalence Good Moderate

Radiation Hardness Excellent Moderate

Spatial ResolutionPoor, 2.5 cm. 0.5 mm best

caseExcellent, 1 um

Wall effect Immunity Poor Excellent

Model cell array No Yes

Detector

performance

Shape design

flexibilityModerate Moderate

Calibration Simple Simple

Cost High Low

Portability Moderate Excellent

System ComplexityPoor: Requires HV supply and

gas supply

Good: only requires low voltage

supply.

In-vivo use No Yes

Ease of Use

Integration Poor Excellent

Table 2.1: Comparison between the proportional counter and the silicon mi-

crodosimeter [46].

31


Correction for tissue equivalence

In silicon microdosimetry the spectra have to be corrected for tissue equiv-

alence. Silicon microdosimeters require a tissue equivalent converter on top

of the device when measurements are performed outside a tissue equivalent

phantom. Ideally, the secondary particles produced by particles that directly

interact with silicon should be absent, or at least they should have a negligible

contribution in comparison those generated in the tissue equivalent area that

precedes the detector.

The amount of the energy imparted by stoppers (particles generated outside

the volume and completely stopped within it) within the sensitive volume can

be considered to be independent of the detector material (except for border

effects) since for these particles the detector can be though of as an absorber of

infinite thickness. On the contrary, the energy imparted by crossers (particles

produced outside the volume which cross it) must be corrected for tissue-

equivalence. The correction can be done by scaling the energy imparted in

silicon εSi by the ratio R:

R =ST issue(E)

SSi(E)(2.18)

where ST issue(E) and SSi(E) are the stopping powers of the particle in tissue

and Silicon respectively [47].

Hence, the energy imparted εtissue in an analogous tissue equivalent detector

εT issue is:

εT issue = εSi ·R(E) = εSi ·ST issue(E)

SSi(E)(2.19)

The ratio R(E) depends on the energy of the incident particle. When no

information about the energy of the incident particle is available, εTissue is

scaled with a constant ζ, obtained by averaging the ratio R(E) over the energy

interval of interest:

ζ =

∫ Emax

EminR(E)dE

Emax − Emin

=

∫ Emax

Emin

STissue(E)SSi(E)

dE

Emax − Emin

(2.20)

where Emin and Emax are the minimum and maximum energy of the impinging

particles.

32


State of the art of silicon microdosimeters

In order to resolve the issues mentioned above, several devices based on differ-

ent technologies (telescope detectors, silicon on insulator detectors, arrays of

cylindrical p-n junctions with internal amplification, etc.) have been proposed

as silicon microdosimeters [50] .

The Centre for Medical Radiation Physics (CMRP) of the University of Wol-

longong has demonstrated the possibility of a solid state microdosimeter on a

single Sensitive Volume (SV) using a small area reverse biased p-n junction of

the source diode in the MOSFET transistor [48]. They proposed a first prac-

tical solid state microdosimeter that tried to address the above shortcomings

of the TEPC.

A silicon microdosimeter is based on an array of micron sized silicon SVs that

mimic an array of biological cells, instead of the single cell simulated by the gas

volume of a TEPC. In order to minimize the field funneling effect the array of

silicon SVs was fabricated on Silicon On Insulator (SOI) substrates. By using

SOI technology charge collection beneath the active SOI layer is precluded.

This design creates a sensitive volume of well-defined thickness and is a major

advantage of using SOI technology for microdosimetry applications.

Five generations of SOI detectors have been developed, fabricated and inves-

tigated by CMRP researchers [50, 51, 52, 53].

• The first generation of SOI microdosimeters was based on a 2D 30 µm

× 30 µm diode array of elongated parallelepiped shaped micron sized

SVs adjacent to each other (Fig. 2.5). The main shortcoming of these

microdosimeters was the poorly defined charge collection volume [54, 55].

Figure 2.5: (a) Size and layout of the 1st generation silicon microdosimeter

arrays, (b) basic SOI diode array structure.

33


• The second generation of microdosimeter arrays was developed and fab-

ricated on high resistivity p-SOI with 2.5 and 10 µm thick layers of active

silicon (Fig. 2.6). To eliminate the possibility of lateral diffused charge

being collected outside the SV, an etching process that created raised

mesa SV structures was carried out such that each mesa was physically

isolated from the surrounding material [52].

Figure 2.6: 2nd generation microdosimeter with: a) a simple ring (or defined

guard ring) around the outer collector and b) guard electrode covering all

areas (or guard ring everywhere) that are not part of the SV. Top image:

single cylindrical SV fragment structure without oxide and Al metalisation;

bottom image: topology fragment of dopant diffused single planar SV [52].

• The devices of the third generation were based on array of planar 6 µm

and 10 µm in diameter sensitive volumes fabricated on a high resistivity

(3 kΩ cm) n-type SOI substrate of thickness 10 µm (Fig. 2.7). The main

limit of these devices was the charge sharing between the SVs, which

leads to excessive deposition of low energy events [53].

34


Figure 2.7: (a) Single cell simplified topology of the 3rd generation n-SOI

microdosimeter device; (b) top view of a single SV.

• The fourth generation microdosimeters are a fundamental step towards

fully freestanding 3D SVs. Based on experience with planar and mesa

SOI microdosimeters, the researchers concluded that freestanding-on-

silicon oxide 3D SVs is an optimal solution to avoid charge sharing and

lateral charge collecting outside of an SV. They developed a 3D mesa

“bridge” microdosimeter where the surrounding silicon was fully etched

to a depth of 10 µm using the deep reactive ion etching (DRIE) technique,

that produces a straight parallelepiped shape for the SVs whilst leaving

a thin silicon bridge between the SVs to support the aluminium tracks.

The “bridge” microdosimeter was based on an array of 4248 30 µm × 30

µm × 10 µm SVs fabricated on a high resistivity n-SOI active layer 10

µm thick, and a low resistivity supporting wafer (Fig. 2.8).

This technology provides a well-defined geometry of micron-sized 3D SVs

[56]. However, some lateral charge collection was still observed from the

bridge regions attached to the SV, due to the high resistivity of n-SOI

silicon.

• An improved version of the bridge microdosimeter is the fifth genera-

tion microdosimeter called “mushroom”. This SOI microdosimeter with

freestanding and true 3D SVs was developed in order to overcome the

problems mentioned above [57].

The properties of the mushroom microdosimeters will be described in detail in

the next chapters.

35


Figure 2.8: Schematic of the design of the SOI bridge microdosimeter. (a) 3D

view; (b) a cross-section of the microdosimeter behind the silicon bridge.

Another device providing charge confinement inside a micrometric sensitive

volume is the monolithic silicon telescope. The monolithic ∆E-E telescope

manufactured at STMicroelectronics (Catania, Italy) consists of a 1.8 µm ∆E

and a 500 µm E thick stage fabricated on a single silicon substrate and sep-

arated by a deeply implanted p+ cathode [58, 59]. This highly-doped p+

cathode acts as a watershed separating charge collection between the two

stage-detectors. The different thicknesses of the two stages with an almost

zero thick dead layer between them provides information on the nature of the

radiation beam and enables any nuclear secondaries produced to be identi-

fied. The ∆E stage acts as a microdosimeter while the residual energy E stage

provides information on the energy and type of the incident radiation. This

detector can provide microdosimetric spectra with sub-millimetre spatial res-

olution similar to an SOI microdosimeter. However, the drawback of using it

for microdosimetry is that it is not accurate in the isotropic field and results

in errors in the microdosimetric measurements, due to its mean chord length

being much greater than 1.8 µm. Starting from this configuration, an innova-

tive device characterized by a ∆E stage segmented in a matrix of micrometric

diodes was designed and tested.

36


It was constituted by cylindrical elements about 2 µm thick and 9 µm in diam-

eter, coupled to a single E stage (500 mm thick). The ∆E SVs pitch was about

41 µm and each element was surrounded by a 14 µm diameter guard ring that

confines the charge collection within the lateral surface of the sensitive volume

(Fig. 2.9) [60, 61].

Figure 2.9: Optical image and schematic of the pixelated ∆E-E telescope.

37

Chapter 3

MicroPlus probe and calibration

The purpose of this experiments is the study of a silicon microdosimeter de-

veloped at CMRP. The experimental activities were performed at INFN-LNS.

In the following sections the detector features and calibration procedures will

be described.

3.1 MicroPlus Probe (Mushroom microdosime-

ter)

The fifth generation of the detector developed at CMRP is the MicroPlus probe

with mushroom microdosimeter. This device is designed for microdosimetry

and RBE derivation in proton and 12C ion therapy. It has an extremely high

space resolution (∼ 10 µm), an easy to use low voltage biasing and a high

degree of portability.

3.1.1 Mushroom microdosimeter

The manufacturing of a fully 3D SV (Sensitive Volume) array microdosimeter

was made possible thanks to the improvements in micro-machining and stan-

dard VLSI (Very Large Scale Integration) technologies, together with advanced

deep reactive ion etching (DRIE) with high depth-to-width ratios [67].

The structure of the microdosimeter used in this experiment (model #705) is

based on an array of 3D cylindrical SVs with diameter of 30 µm and distance

between two SVs (core to core) of 50 µm (Fig. 3.1), placed on a high resistivity

38

3.1 MicroPlus Probe (Mushroom microdosimeter)

p-SOI (Silicon-On-Insulator) with a 10 µm thick active layer bonded to a low

resistivity supporting wafer and 2 µm silicon oxides in between [68].

Figure 3.1: Array of 3D “mushroom” microdosimeter (left). Detail of two

mushrooms (right).

Figure 3.2: Geometry of the sensitive volume.

39


The structure of a single 3D cylindrical sensitive volume is schematically dis-

played in Fig. 3.2. This structure is known as trenched 3D and consists of

cylindrical SVs with a core column of air and n+ doping in the inner core walls

of the SV center. Each SV is surrounded with a trench of air with p+ doping

on the outer wall, designed to physically eliminate the possibility of charge

generated outside the SV being collected. In this structure, the p+ trench and

n+ column of the SV are not filled with polysilicon; therefore the trench cannot

be a closed cylinder. In order to electrically connect the SVs in a single array,

two half-moon trenches were made leaving some silicon to allow passage for

the metal contacting the inner n+ electrode. Outer Al buses were connected

to p+ outer electrodes of the 3D SVs. Scanning Electron Microscope (SEM)

images clearly showing the structure of the microdosimeter are shown in Fig.

3.3 (right side).

Figure 3.3: Scanning Electron Microscopy (SEM) images of trench 3D mush-

room microdosimeter with air filled n+ column and p+ trench filled with air.

On the left, an array of SVs. On the right, a single SV.

In Fig. 3.4, the microdosimeter is shown in its actual size (left) and at the

optical microscope (right). The SVs are separated into odd and even arrays

(Fig. 3.3, on the right). A P-stop layer has been deposited everywhere on

device and under the pad to avoid the metal-oxide semiconductor (MOS) build

up charge effect under the metal buses [68]. This microdosimeter has been

designed to possess low depletion voltage and capacitance and 100% charge

collection.

40


Figure 3.4: Microdosimeter in its actual size (left). An image at the optical

microscope (right).

3.1.2 Probe and pulse-processing electronics

The probe is the green printed circuit board that houses the microdosimeter

and pre-amplifier (Fig. 3.5). The microdosimeter is mounted on a 20-pin DIL

package (an electronic component package with a rectangular housing and two

parallel rows of electrical connecting pins, Fig. 3.6) and is connected to the

probe using a 20-pin IC socket.

Figure 3.5: Microdosimeter housed on the probe.

Figure 3.6: Microdosimeter mounted on a 20-pin DIL package.

41


In order to optimise the noise properties, the connected arrays can be config-

ured using the jumpers on the probe. The arrays can be enabled or disabled by

moving the jumpers. An array is enabled if the jumper is placed over the two

pins corresponding to that array, as labelled on the probe, whereas to disable

it the jumper must be placed on the left pin corresponding to that array (Fig.

3.7).

Figure 3.7: On the left, all arrays are disconnected. On the right, array odd 3

is connected.

The output pulse from the SV is processed by low noise front-end electronics

on MicroPlus probe, followed by a pulse-shaping amplifier.

The shaping amplifier box is attached to the MicroPlus Probe using a D9 con-

nector. Its function is to shape the signals that will be sent to a Multi-Channel

Analyzer (MCA). In order to cover the full dynamic range, the amplifier has

three different gains:

• gain low can measure energies from 0 MeV to 15 MeV;

• gain medium from 0 MeV to 4.5 MeV;

• gain high from 0 MeV to 1.5 MeV.

The gain is set inside the shaper amplifier box by placing a jumper over the

two pins that select the desired gain.

The MCA measures the pulse heights, bins them into channels and provides a

histogram of the pulse heights. The Ortec Easy-MCA 8k was used to perform

the measurements. The 8K model’s successive-approximation 8192-channel

ADC offers gain settings from 256 to 8192 [62]. In this study, the MCA settings

were chosen so that 8192 channels span a 0-10 V range.

42


The pre-amplifier and the shaper amplifier are supplied with a voltage of 12 V.

The microdosimeter is supplied with a voltage of 9.5 V in reverse bias. This is

achieved by using a 6 pin DIN connector. It is extremely important to protect

the microdosimeter from light when biased. Saturation of the device will occur

immediately if it is exposed to normal indoor lights when the device is biased.

In order to protect the microdosimeter, an opaque polyethylene film has been

placed over the DIL package.

3.1.3 PMMA sheath

Once the microdosimeter is placed on the probe, it is inserted into a PMMA

sheath. In order to eliminate stray radio frequencies, the PMMA sheath is

tightly wrapped in an aluminium tape that acts as a Faraday cage (Fig. 3.8).

A small opening window in the Al foil over the sensitive region of the micro-

dosimeter allows the beam to pass through. The design of the PMMA sheath

includes a thin PMMA window 0.5 mm in thickness. This creates a 5 mm

cavity where different media can be placed very close to the microdosimeter.

The PMMA sheath has been manufactured to be waterproof in order to allow

it to be used in a dosimetric water tank.

Figure 3.8: PMMA sheath wrapped in aluminium tape in order to reduce radio

frequency interference.

In order to reduce the problem related to the window’s offset, an identical

PMMA sheath, without the PMMA window, was manufactured at INFN-LNS.

43

3.2 Calibration

3.2 Calibration

3.2.1 Calibrated pulse generator

The following calibration procedure refers to the probe assembled with the

microdosimeter model #705. The calibration of the MCA channel number to

energy was performed by using a calibrated pulse generator. The pulse gener-

ator was calibrated to a thick silicon Hamamatsu PIN diode [63] in response

to the conversion electrons of a 137Cs source. 137Cs has a half-life of about

30.17 years [71]. About 94.6% of the times it decays through beta emission to

a metastable nuclear isomer of barium: 137mBa. For the remainder it directly

populates the ground state of 137Ba, which is stable. 137mBa has a half-life

of about 153 seconds and is responsible for all the gamma-ray emissions in

samples of 137Cs. Metastable barium decays to the ground state by emitting

gamma rays of energy 0.662 MeV. These gammas can interact with one of the

atomic electrons and the electron can be ejected from the atom (electron con-

version). The expelled electron inherits the gamma energy minus the atomic

binding energy (Fig. 3.9).

Figure 3.9: An excited nucleus emits a gamma ray (a). The photon interacts

with one of the inner electrons of the atom (b), most likely with an electron

of the K shell. The gamma is absorbed and the electron is ejected from the

atom, creating a hole in the shell. The atom then reorganizes: an outermore

electron, here belonging to the L shell, fills the hole (c). An X-ray is emitted.

44

3.2 Calibration

The internal conversion probability is the largest for electrons belonging to the

innermost K shell. The K-shell electron used for the calibration has an energy

of 624.2 KeV.

The pulser is calibrated by injecting a pulse (43.7 mV) equal to the pulse

generated by the electrons in the thick silicon PIN diode. Operationally, the

injected pulse was tuned until its corresponding peak, visualized on the MCA

software, overlapped with the peak generated by the electrons. This way the

pulse in mV and the corresponding MCA channel peak are related to the

energy and, provided that the system is linear, each channel can be assigned

to the corresponding energy. Moreover, if the injected charge is known, then

the test capacity can be indirectly measured by using the following formula:

CTEST =Q

VTEST

=E [eV] · e

3.62 eV · VTEST

(3.1)

Here E is the energy of the particle injected, e is the charge of the electron,

3.62 eV is the energy required to create an electron/hole pair and VTEST is the

pulse amplitude. The measured test capacity is approximately 0.6 pF.

The pulse generator simulates the charge injected by the particles and, there-

fore, the calibrated pulse generator can be used to generate different energy

peaks for calibration. Since this calibration method assumes the linearity of

the MicroPlus probe, it is important to test the response of the latter. This

test was performed with two different alpha sources (241Am and 148Gd) and

carbon ions beams.

3.2.2 Measurements with alpha sources and carbon ion

beams

In order to test the calibration method described in the previous section, we

performed dedicated irradiation with helium and carbon ion beams acceler-

ated at the INFN-LNS Tandem accelerator. 5.486 MeV and 3.18 MeV alpha

particles from 241Am and 148Gd respectively, and 7.3 MeV and 9.7 MeV carbon

ions were used.

For these measurements the detector was placed in vacuum using the PMMA

sheath without the windows. The shaping amplifier was set on low gain.

45

3.2 Calibration

In Figg. 3.10 and 3.11 we report the experimental set-up of the measurements

with alpha sources and carbon ions, respectively.

Figure 3.10: Experimental set-up for the measurements performed with alpha

sources (before placing the MicroPlus probe inside the vacuum chamber).

Figure 3.11: Experimental set-up for the measurements performed with carbon

ions accelerated by the tandem accelerator.

46

3.2 Calibration

The alpha particles traverse the detector, and the energy released inside the

10 µm thick active layer of the SOI was calculated with the LISE software

[64]. On the contrary, the energy of the carbon ions was chosen so that the

particles should stop in the detector. It is important to keep in mind that the

microdosimeter also has a passive layer of SiO2, so that the energy released

inside the active layer is actually lower than the nominal one. The energy lost

to the passive layer and the energy released in the 10 µm silicon active layer

are reported in Tab. 3.2.

Nominal energy

(KeV)

Energy lost in

402 nm SiO2 (LISE)

(KeV)

Energy lost in

10 µm Si

(KeV)

α (148Gd) 3.18 85.60 2543

α (241Am) 5.48 60.79 152112C 7.30 52.79 677512C 9.70 493.07 9207

Table 3.2: Energy lost in the 402 nm SiO2 passive layer and in the 10 µm

silicon active layer.

Each energy value was correlated to a MCA channel and then compared with

the energy value that was obtained for the same channel by the calibrated

pulse generator.

3.2.3 Comparison between measured and pulse calibrated

energy

In order to produce the MCA channel peaks in the same positions as those

obtained with the alpha particles and carbon ions, a specific charge was in-

jected in the microdosimeter using the pulse generator. The energy calibrated

with the pulse generator, the energy obtained by LISE calculation and their

relative difference are reported in Tab. 3.3. The same data are also shown in

Fig. 3.12.

47

3.2 Calibration

Channel

Pulse calibrated

energy

(KeV)

Calculated

energy (LISE)

(KeV)

Relative

difference

(%)

528 1534 1521 0.85

842 2447 2543 3.77

2843 8264 6775 18.02

3952 11488 9207 19.86

Table 3.3: Comparison between the energies calibrated with the pulse genera-

tor and the energies obtained by the LISE calculation.

Figure 3.12: Comparison between measured data and data obtained with the

calibrated pulse generator.

The vertical error bars in Fig. 3.12 are the uncertainties in energy, calculated

by taking into account the uncertainty on the silicon active layer thickness

for the alpha particles, and the fluctuations in the energy of the beam for

the carbon ions. The horizontal bars are the Full Width at Half Maximum

(FWHM) of the peak distributions.

48

3.2 Calibration

In light of what we saw, we can conclude that the calibration curve of the pulser

deviates from the experimental measures. The coefficients of the calibration

curve y [Energy] = a · x [Channel] + b were determined through the calibrated

pulse generator to be a = 2.907 ± 0.001 keV/channel and b = 0.009 ± 0.639

keV. They can be regarded as valid only in a certain energy range – to be

specific, up to energies of about 4 MeV. The reasons for this behaviour are

still under investigation.

3.2.4 Gain MEDIUM and gain HIGH

The results obtained for the gain “low” can be used to calibrate the electronic

chain with the shaping amplifier set to medium or high gain. For each gain,

different test pulses were injected and then correlated with the corresponding

MCA channel (Fig. 3.13).

The test capacity and the calibration curve are known, so that each pulse can

be related to the energy by means of eq. 3.1, or alternatively each channel

can be related to the energy by means of the calibration curve. In Tabb. 3.4

and 3.5 we report the injected test pulses, the corresponding output pulses

(measured with the oscilloscope), the channels and the energies for the gains

medium and high, respectively. The uncertainties on the energy values have

been computed by propagating the errors of the calibration curve parameters.

VTest

(mV)

VOut

(mV)MCA Channel

Energy

(KeV)

14.8 396.0 311 210.5±4.6

28.0 756.0 591 399.0 ±4.6

48.4 1310.0 1029 695.7±4.6

67.2 1830.0 1413 958.2±4.6

134.0 3640.0 2828 1908.7 ±4.6

202.0 5480.0 4243 2862.0±4.7

266.0 7320.0 5661 3819.3±4.7

332.0 9080.0 7068 4764.7±4.8

Table 3.4: Injected test pulses and the corresponding output pulses (measured

with the oscilloscope), channels and energies for medium gain.

49

3.2 Calibration

VTest

(mV)

VOut

(mV)MCA Channel

Energy

(KeV)

6.8 556 439 98.2±4.6

14.8 1190 921 210.5±4.6

28.0 2250 1751 399.0 ±4.6

48.4 3900 3050 695.7 ±4.6

58.0 4680 3645 830.8±4.6

67.2 5360 4187 958.2±4.6

82.2 6480 5030 1146.0±4.6

100.0 8040 6281 1431.4 ±4.6

114.0 9160 7129 1624.6 ±4.6

Table 3.5: Injected test pulses and the corresponding output pulses (measured

with the oscilloscope), channels and energies for high gain.

Figure 3.13: MCA Channel as a function of the different injected VTEST for

low, medium and high gain.

50

3.2 Calibration

According to the information contained in Tabb. 3.4 and 3.5, the calibration

curve is given by y [Energy] = (0.674 ± 0.001) keV/Channel · x [Channel] +

(2.173± 2.693) keV (Fig. 3.14) for the gain medium and y [Energy] = (0.228±0.001) keV/Channel · x [Channel] + (−0.070± 2.458) keV for the gain high.

Figure 3.14: Calibration curve for medium gain.

Figure 3.15: Calibration curve for high gain.

51

Chapter 4

Measurements with a 62 AMeV

proton beam at the CATANA

facility

As mentioned in Chapter 1, the first experimental proof of the radiobiolog-

ical enhancement obtained by exploiting the p-B reaction was performed by

irradiating prostate cancer cells (DU145) and nontumorigenic breast epithelial

MCF-10A cell lines along a 62 MeV clinical proton spread out Bragg peak

(SOBP) at the Italian ocular proton therapy facility of INFN-LNS, Catania,

Italy [27]. Both clonogenic dose response curves and complex type chromoso-

mal aberration analyses clearly showed that the presence of boron nuclei results

in an increase in the radiobiological effectiveness of the proton beam. Besides

the advantage of using a neutron-free nuclear fusion reaction, the relevance of

this method stems from the fact that the reaction cross-section becomes sig-

nificantly high at relatively low incident proton energy, i.e., around the Bragg

peak region. Assuming that a given concentration of 11B nuclei is present

preferably, but not exclusively, in the tumor volume, the incoming slow pro-

tons can trigger fusion reaction events and generate highly DNA-damaging

alpha particles. The observed radiobiological enhancement reported in [27],

even if confirmed in four experimental sessions, still cannot be explained by

making simple use of the knowledge about the reaction cross-sections and/or

of analytical considerations based on the classical concepts of dose, LET, and

RBE. Therefore, in order to explain the phenomenon, one must look for other

concurring physical and/or biological factors.

52

4.1 Experimental set-up

The average LET distribution and absorbed doses are macroscopic concepts

and merely describe the radiobiological effect at the DNA level in a global, ap-

proximate fashion. A more detailed knowledge of the interactions at the local

level can be achieved by exploiting the methodologies and instruments pro-

vided by microdosimetry. A microdosimetric approach may give experimental

information about the number and quality of high-LET particles produced, and

may also take into account the biological effects of large local dose deposits

which could be able to explain part of the discrepancy.

In this chapter we will present the experimental measurements performed at

the CATANA facility with the new microdosimeter, the MicroPlus Probe. The

measurements were performed in the same positions where the cells were irra-

diated (entrance, mid and distal SOBP). In particular, two different models of

MicroPlus were used. The microdosimeter model #705 described in Chapter

3 was employed to perform the measurements at the distal and mid SOBP. A

second model (#592) was used for a second set of measurements, performed

at the entrance, mid and distal SOBP, in collaboration with the researchers of

the Wollongong University. The experimental results obtained for each set of

measurements were compared with Monte Carlo simulations performed with

Geant4. Finally, we present some measurements performed by placing a boron

converter in front of the detector; these were made in order to investigate the

p+11B reaction and its effects.


4.1.1 The CATANA prontontherapy facility

Irradiations were performed using the 62-MeV proton beam generated by the

superconducting cyclotron clinically used at the CATANA (Centro di AdroTer-

apia ed Applicazioni Nucleari Avanzate), eye proton therapy facility of the

INFN-LNS. CATANA was the first Italian protontherapy facility dedicated to

the treatment of ocular neoplastic pathologies. In operation at the INFN-LNS

since 2002, to date 520 patients have been successfully treated [65].

The CATANA facility is based on a passive transport system of a 62 MeV

proton beam. The proton maximal range, at the irradiation point, is about 30

mm, ideal for the treatment of eye tumors. A picture of the real beam line is

53


displayed in Fig. 4.1. Accelerated protons exit in air through a 50 µm Kapton

window. Upstream the exit window, a first thin (15 µm) tantalum scattering

foil is placed in vacuum, where it performs a first broadening of the beam.

After the Kapton window, in air, a second, thicker (25 µm), tantalum foil,

equipped with a brass stopper 4 mm in diameter, is used to perform the sec-

ond beam scattering. This double foil scattering system is designed to obtain

an optimal homogeneity of the final proton beam in terms of lateral dose dis-

tribution, while at the same time minimizing the energy losses. Range shifters

and modulator wheels are positioned downstream the scattering system.

A modulator wheel is made of different steps of varying thickness able to re-

produce pristine peaks of different energies to finally achieve a SOBP [66]. The

radiation field is simulated using a diffused light field. Two transmission mon-

itor ionization chambers, providing the on-line control of the dose delivered to

the patient, represent the key elements of the patient dosimetry system.

The beam line ends with a brass collimator.

Figure 4.1: The CATANA beamline.

54


4.1.2 The irradiation set-up

The response of the MicroPlus probe was investigated along the 62 MeV proton

beam SOBP, at the entrance, mid and distal regions of the latter. PMMA slabs

were placed in front of the microdosimeter in order to reproduce the different

positions. Each PMMA slab has a water equivalent thickness equal to 356

µm; the positional uncertainty was about 300 µm. The experimental set-up is

shown in Fig. 4.2.

Figure 4.2: Experimental set-up.

For the first set of measurements the microdosimeter model #705, described

in Chapter 3, was employed; the measurements were performed at the mid and

distal SOBP. For the measurements at the distal SOBP, the sheath without

the PMMA window was used, the opaque polyethylene film placed over the

microdosimeter on the DIL package was removed and a Mylar film was placed

on the sheath opening in order to protect the microdosimeter from light when

biased. We chose to use this sheath at the distal SOBP in order to have a

55

4.2 Monte Carlo Simulations

higher spatial resolution than that obtained with the sheath with the PMMA

windows. For this measurement a low gain was set and the acquisition time

was approximately thirty minutes.

At the mid SOBP, the LET of the protons is lower than that in the distal (Fig.

4.3), hence in the shaping amplifier the medium gain was chosen in order to

amplify the output pulse signal of the pre-amplifier.

Figure 4.3: Monte Carlo simulation of the total LET dose and the primary

LET dose of protons.

The response of the microdosimeter model #592 was studied at the entrance,

mid and distal part of SOBP. For this set of measurements the PMMA sheath

with the 0.5 mm PMMA windows was used and the medium gain was set.


Simulations were carried out using the Geant4 (GEometry ANd Tracking)

toolkit [72], version 10.05, and the official Geant4 advanced example Hadron-

therapy [73]. This example is an application specifically developed for dosi-

metric and radiobiological studies with proton and ion beams [74].

56


It is able to simulate each element of the CATANA beamline, where the exper-

imental campaigns reported in [27] were performed. The simulated geometry

incorporates all the transport elements, included the specific energy modulator

for generating the SOBP and the diagnostic elements.

Since the 1950s many strategies were developed to estimated the LET with the

highest possible precision. Nowadays, several Monte Carlo-based algorithms

able to do so are known [75].

The researchers of the LNS proposed new strategies to obtain the highest

precision with the lowest possible dependence from Monte Carlo parameters

such as the voxel size and the secondaries production cut threshold. These

parameters are intrinsic to any condensed-history Monte Carlo simulation tool

and have an impact in clinical practice.

The average LET can be retrieved by considering only the primary proton

spectra along the SOBP (Fig. 4.4) and using the formula

LD =

∑Ni=1 Liεi∑Ni=1 εi

(4.1)

where Li is the ratio between the energy deposited by the incident proton with

energy εi and a step length of li. Taking into account the contribution due to

the secondary particles, equation 4.1 becomes

LTotalD =

∑nj=1[∑N

i=1 Liεi]j∑nj=1[∑N

i=1 εi]j(4.2)

Similarly, the LET track is calculated using the following formula:

LT =

∑Ni=1 Lili∑Ni=1 li

(4.3)

Here, the average of Li is weighted by the track length of the charged primary

particle li. Taking into account the contribution due to the secondary particles

equation 4.3 becomes

LTotalT =

∑nj=1[∑N

i=1 Lili]j∑nj=1[∑N

i=1 li]j(4.4)

57

4.3 Data analysis

Figure 4.4: Proton energy spectra at various depths inside a water tank.

4.3 Data analysis

4.3.1 Tissue equivalence correction and lineal energy

The calibrated output of the MCA yields a plot of number of events on the

y-axis versus energy deposited on the x-axis. For each measurement, the plot

displays the spectrum of the events. In order to determine the microdosimetric

quantities from this output, the x-axis was first of all converted into lineal

energy. As discussed in Chapter 2, the lineal energy (eq. 2.6) is the ratio

between the deposited energy and the mean chord length. For the MicroPlus

probe, it is assumed that all protons travel in straight trajectories passing

perpendicularly through the SV, so that the mean path length is 10 µm in

silicon. Using GEANT4, CMRP determined that the average chord length

in tissue is equal to the average chord length in silicon divided by a factor of

0.58 [70]. Hence, the corresponding tissue equivalent mean path length is 17.24

µm. The energy deposition distribution was calculated first in the silicon SV by

means Geant4 and then again in the same radiation field conditions with tissue

58

4.3 Data analysis

equivalent material filling the SV [69] [70]. The size of the tissue-equivalent

volume was adjusted to reproduce the same energy deposition spectrum as the

one of the silicon SV. The best agreement between the response in the silicon

SV and in the tissue equivalent SV was quantified by comparing the energy

deposition spectra in silicon and tissue equivalent material by means of the χ2

test. This way a tissue scaling factor was determined. In particular, the tissue

equivalence correction factor k was defined as the ratio of lSi (the thickness of

the silicon SV) to lTE (the thickness of the tissue equivalent SV) for which the

best equivalent response to silicon was obtained.

The lineal energy was obtained by dividing the energy of the x-axis of the

MCA output by the tissue-equivalent mean chord length.

4.3.2 Microdosimetric spectra and uncertainties

For each measurement the microdosimetric spectrum was reconstructed. Fol-

lowing Chapter 2, the spectra were logarithmically rebinned. The number of

decades was set to 5 and the number B of increments to 60. As explained be-

fore, f(yi) is the probability density of the occurrence of the lineal energy yi,

by definition normalized to 1. f(yi) was calculated by the following expression:

f(yi) =n(yi)∑

i ∆yi n(yi)(4.5)

where the ni are the number of counts in each logarithmic interval and the ∆yi

are the widths of the logarithmic intervals.

A similar calculation provides the dose distribution: the dose probability den-

sity of the yi value is given by

d(yi) =yi n(yi)∑i ∆yi n(yi)

(4.6)

The probability distribution was used to calculate the microdosimetric quanti-

ties yF , the frequency-weighted mean lineal energy, and yD, the dose-weighted

mean lineal energy.

For the visualization of the microdosimetric distributions, the microdosimetric

spectra were plotted using the standard representation yd(y) vs. log(y). The

errors for yF and yD were determined by propagating the statistical uncertainty

due to the number of counts.

59

4.4 Experimental results


In this section we report the experimental results obtained along the 62 AMeV

proton beam SOPB. For each set of measurements the microdosimetric spectra

are shown and the corresponding yF and yD are calculated as a function of

depth. In Figg. 4.5 and 4.6 the microdosimetric spectra are displayed for each

position of the distal SOBP. As widely explained before, each distribution is

normalized to 1 and equal areas of the graph correspond to equal doses.

Figure 4.5: Microdosimetric distributions obtained for different positions of

the distal SOBP.

60


The frequency-weighted mean lineal energy and the dose-weighted mean lineal

energy for each distribution are reported in Tab. 4.1 and 4.2, respectively.

As expected, the values of yF and yD increase with depth. In particular, the

analysis performed at the end of the distal SOBP shows an increase of yF

from 5.966 KeV/µm at a depth of 28.45 mm to 16.619 KeV/µm at a depth of

30.94 mm (Tab. 4.1). On the other hand, the value of yD increases from 7.617

KeV/µm at 28.45 mm to 20.795 KeV/µm at 30.94 mm (Tab. 4.2).

Figure 4.6: Comparison of the microdosimetric spectra in the distal SOBP

positions.

The main feature of the microdosimetric spectra shown in Fig. 4.6 is the

presence of the proton edge at the end of the distal SOBP. This is a cut-off

that represents the maximum energy that can be deposited by the proton. The

proton edge is clearly visible at the depths of 30.58 mm and 30.94 mm. At the

depth of 28.45 mm the microdosimetric spectrum is not totally reconstructed.

This is due to the electronic noise, as clearly signaled by the peak in the

spectrum. A better discrimination of the signal from the electronic noise can

be obtained by changing the gain in the shaping amplifier, as was done for the

measurements performed at the mid SOBP.

61


Position

(mm)

yF

(KeV/µm)

Statistical error

(KeV/µm)

Relative error

(%)

13.30 1.786 0.0004 0.024

18.28 2.248 0.0005 0.022

19.70 2.464 0.0006 0.025

22.24 2.704 0.0007 0.024

24.33 3.172 0.0008 0.024

26.46 3.919 0.0009 0.024

28.45 5.966 0.004 0.061

29.16 7.872 0.005 0.065

29.87 11.720 0.004 0.036

30.58 15.097 0.009 0.059

30.94 16.619 0.020 0.121

Table 4.1: Measurement results for yF as a function of depth with associated

statistical and relative uncertainties at mid and distal SOBP, performed with

the MicroPlus probe #705.

Position

(mm)

yD

(KeV/µm)

Statistical error

(KeV/µm)

Relative error

(%)

13.30 3.096 0.037 1.19

18.28 3.598 0.024 0.67

19.70 4.355 0.023 0.53

22.24 4.518 0.018 0.40

24.33 4.995 0.015 0.31

26.46 5.748 0.009 0.15

28.45 7.617 0.018 0.234

29.16 10.374 0.016 0.153

29.87 15.516 0.008 0.054

30.58 19.189 0.015 0.076

30.94 20.795 0.056 0.269

Table 4.2: Measurement results for yD as function of depth with associated

statistical and relative uncertainties at mid and distal SOBP, performed with


62


The values of yF and yD for the measurements performed in the mid position

of the SOBP with medium gain are listed in Tabb. 4.1 and 4.2 respectively,

while the microdosimetric spectra are displayed in Fig. 4.7.

Figure 4.7: Comparison of the microdosimetric spectra in the mid SOBP po-

sitions.

The value of yF increases from 1.786 KeV/µm at a depth of 13.30 mm to 3.919

KeV/µm at 26.46 mm (Tab. 4.1), while yD goes from 3.096 KeV/µm to 5.748

KeV/µm.

As the above tables show, the relative errors associated to the values of yF and

yD are very small both at the distal and mid SOBP. We reiterate that these are

statistical errors associated to the Poisson distribution of the number of counts;

as such, they decrease as√N as the number of counts N increases. Thus the

smallness of the errors is explained by the very high number of counts recorded

in the measurements. Declaring the statistical error is the standard practice

in microdosimetry. Further studies will improve the estimation of errors by

taking into account any other relevant contribution (such as that due to the

calibration).

63


In Fig. 4.8 we present the spectra obtained both for the measurements at mid

and distal SOBP. These clearly show the typical trend of the microdosimetric

spectra: as the depth increases, so does the LET of the particles, and the

spectra tend to shift to higher lineal energies until they reach the limit position

(proton edge).

Figure 4.8: Microdosimetric spectra obtained for the measurements performed

both at mid and distal SOBP.

The general considerations that we made previously also apply to the set of

measurements performed with the MicroPlus probe model #592. The micro-

dosimetric spectra obtained at the different depths along the SOBP are shown

in Fig. 4.9.

The values of yF and yD are listed in Tabb. 4.3 and 4.4, respectively. For this

set of measurements the statistical errors are higher than those of the previous

one, due to the lower acquisition time and resulting lower number of counts.

64


Figure 4.9: Microdosimetric spectra obtained with the MicroPlus probe #592.

The value of yF at the entrance region is 0.945 KeV/µm, increasing to 11.093

KeV/µm at a depth of 29.29 mm; that of yD at the entrance is 2.664 KeV/µm,

increasing to 16.531 KeV/µm at 29.29 mm.

Position

(mm)

yF

(KeV/µm)

Statistical error

(KeV/µm)

Relative error

(%)

1.43 0.945 0.008 0.851

18.03 2.139 0.019 0.891

22.78 2.973 0.025 0.842

28.27 5.006 0.041 0.826

28.91 6.635 0.054 0.810

29.29 11.093 0.123 1.109

Table 4.3: Measurement results for yF as a function of depth with associated

statistical and relative uncertainties for the 62 MeV proton beam, performed

with the MicroPlus probe #592.

65

4.5 Comparison between simulation and experimental results

Position

(mm)

yD

(KeV/µm)

Statistical error

(KeV/µm)

Relative error

(%)

1.43 2.664 0.543 20.388

18.03 3.887 0.171 4.411

22.78 5.150 0.322 6.259

28.27 7.759 0.130 1.673

28.91 14.671 0.181 1.233

29.29 16.531 0.261 1.577

Table 4.4: Measurement results for yD as a function of depth with associated

statistical and relative uncertainties for the 62 MeV proton beam, performed

with the MicroPlus probe #592.

For both set of measurements, the microdosimetric spectra and the values of

yF and yD measured with the MicroPlus probe are in agreement with the ex-

pected trends: the measured microdosimetric spectra shift to higher values of

lineal energy with increasing depth. This shift of the spectra to higher linear

energies is expected towards the end of the proton range, where the proton

deposit more energy in the SV.

4.5 Comparison between simulation and ex-

perimental results

For comparison with our measured yD and yF , the dose average LET (LD)

and the track average LET (LT ) as functions of depth in the same proton

fields used for the measurements were calculated via Geant4 Monte Carlo sim-

ulations. As explained before, the simulations presented here were performed

using the Geant4 example “Hadrontherapy”. The new algorithm developed by

researchers of the LNS was used both for the absorbed dose average LET and

the track average LET.

In Fig. 4.10 the measured yD compared with the primary LET dose and total

LET dose for the measurements performed with the MicroPlus probe #705 is

displayed.

66


The measured yF compared with the primary LET track and total LET track

is shown in Fig. 4.11.

The simulated dose and the experimental dose measured with the Markus

chamber are also shown in the figures.

Figure 4.10: Measured yD (black dots) at the mid and distal SOBP, obtained

with the MicroPlus probe #705, compared to the total LET dose and primary

LET dose simulation.

In Tab. 4.5 we report the relative difference between the measured yD and the

total LET dose at each position. On average, there is a 18.66% difference. The

maximum difference between the measured yD and simulated total LET dose

is 30.50% at 18.28 mm depth, while the lower is 14.76% at 26.46 depth (Tab.

4.5). In general, the measured values of yD are lower than the simulated ones.

67


Position

(mm)

yD

(KeV/µm)

Total LET dose

(KeV/µm)

Relative difference

(%)

13.30 3.096 2.493 -19.46

18.28 3.598 5.177 30.50

19.70 4.355 6.631 34.33

22.24 4.518 5.884 23.22

24.33 4.995 7.175 30.39

26.46 5.748 6.743 14.76

28.45 7.617 9.091 16.17

29.16 10.374 12.684 18.18

29.87 15.516 19.110 18.79

30.58 19.189 24.472 21.54

30.94 20.795 25.003 16.82

Table 4.5: Measured yD compared to the LET dose total simulated with

Geant4 for the measurement performed at the distal and mid SOBP with


Figure 4.11: Measured yF (black squares) at mid and distal SOBP, obtained

with the MicroPlus probe #705, compared to the total LET track and primary

LET track simulation.

68


A better agreement is found between the measured values of yF and the simu-

lated total LET track. On average there is a 4.42% difference. The maximum

difference is 14.63% at 30.58 mm depth, while the lower is 0.11% at 19.70 mm

(Tab. 4.6).

Position

(mm)

yF

(KeV/µm)

Total LET Track

(KeV/µm)

Relative difference

(%)

13.30 1.786 1.687 -5.54

18.28 2.248 2.305 2.46

19.70 2.464 2.467 0.11

22.24 2.704 2.802 3.50

24.33 3.172 3.249 2.38

26.46 3.919 4.050 3.23

28.45 5.966 5.865 1.70

29.16 7.872 8.399 6.27

29.87 11.720 12.762 8.16

30.58 15.098 17.684 14.63

30.94 16.619 18.822 11.70

Table 4.6: Measured yF at the distal and mid SOBP obtained with the Mi-

croPlus probe #705, compared to the LET track total simulated with Geant4.

The results obtained with the microdosimeter model #592 were also compared

with the simulations. In Fig. 4.12 the measured yD compared with the primary

LET dose and total LET dose is displayed.

On average there is a 0.97% difference between the measured yD and the total

LET dose simulated. The lower difference is at the entrance (0.71%), while

the higher is 28.90% at 28.91 mm in depth. In the distal, the measured values

of yD are higher than the simulated ones.

All the results are reported in Tab. 4.7.

69


Figure 4.12: Measured yD (black diamonds) compared to the total LET dose

and primary LET dose simulation (MicroPlus probe #592).

Position

(mm)

yD

(KeV/µm)

LET Dose Total

(KeV/µm)

Relative difference

(%)

1.43 2.663 2.683 0.71

18.03 3.887 4.709 17.46

22.78 5.150 6.269 17.85

28.27 7.758 8.366 7.26

28.91 14.671 10.434 -28.90

29.29 16.531 13.188 -20.22

Table 4.7: Measured yD values compared to the LET dose total simulated with

Geant4 (MicroPlus Probe #592).

The comparison between the measured values of yF and the simulated total

LET track is reported in Fig. 4.13 and in Tab. 4.8. At variance with what

we have seen before, for the value of yD at the entrance there is the maximum

difference (26.23%) between the measured value and the simulated one. The

lower difference is 1.77% at 22.78 mm. On average, there is a 5.86 % difference.

70


Figure 4.13: Measured yF (black diamonds) compared to the total LET track

and primary LET track simulation (MicroPlus probe #592).

Position

(mm)

yF

(KeV/µm)

LET track Total

(KeV/µm)

Relative difference

(%)

1.43 0.945 1.281 26.23

18.03 2.139 2.222 3.71

22.78 2.973 2.921 -1.77

28.27 5.006 5.662 11.58

28.91 6.635 7.352 9.76

29.29 11.093 9.499 -14.37

Table 4.8: Measured yF values compared to the LET track total simulated

with Geant4 (MicroPlus probe #592).

The overall conclusions are as follows. Both the microdosimeters deviate from

the simulated values, especially at the distal SOBP. The values of the micro-

dosimetric quantities measured through model #705 are generally lower than

their simulated counterpart; those measured through model #592 are often

higher.

71

4.6 Measurements with a boron target

In order to provide an overview of the results, in Fig. 4.14 we report the

simulated LET dose primary and LET dose total, and the values of yD obtained

with different microdosimeters along the 62 MeV proton beam SOPB at the

CATANA facility. In particular, we report the values of yD obtained with a

Mini-TEPC (red circles) and with a Silicon Telescope (purple triangles). There

seems to be good agreement between the simulations and the experimental

measures of the values of yD at the distal SOBP obtained with the Mini-

TEPC, the Silicon Telescope and also the MicroPlus probe #592. On the

contrary, as we have seen, the values of yD at higher depths measured with the

MicroPlus probe #705 are underestimated.

Figure 4.14: Comparison between the values of yD obtained with different

microdosimeters (Mini-TEPC, Silicon Telescope and MicroPlus probe) and

the simulated total LET dose and primary LET dose.


The MicroPlus probe was also employed to study the p+11B reaction. The mi-

crodosimetric spectra were evaluated at the distal SOBP, at the same depths

chosen for the measurements performed with the MicroPlus probe #705. The

aim of this measurements is to evaluate the microdosimetric quantities in the

presence of a boron converter that triggers alpha production through the re-

action p+11B. The alphas are high LET particles, hence a certain number of

events should appear at higher lineal energies in the microdosimetric spectra.

72


Moreover, as explained in Chapter 1, the maximum cross section for such a

reaction occurs at low proton energy, corresponding to the region of the tu-

mour where the incident proton beam slows down. For this reason, we chose to

perform the first measurements with the boron converter at the distal SOBP.

4.6.1 Experimental set-up

The measurements were performed under the same experimental conditions as

those employed at the distal SOBP for the measurements without the boron

target, in order to be able to compare the results. Since the number of al-

phas produced by the p+11B reaction, as well as the reaction cross section,

is very low, in order to have more statistic it was necessary to increase the

acquisition time. A preliminary PMMA foil containing boron was designed

and manufactured. This was produced by depositing a thin layer (tens of µm)

of boron carbide (B4C) on a 50 µm PMMA foil through a chemical procedure

(Fig. 4.15, on the left). The thickness of the deposited boron was optimized

to minimize the yield of alpha particles undergoing self-absorption inside the

converter (the aim was to maximize the yield of detectable alpha particles).

As for the first set of measurements, the sheath without the PMMA windows

was used. In order to leave a small layer of air preventing the target from

touching the microdosimeter and damaging it (or its bonding contacts), the

boron target was placed over a PMMA foil holed in correspondence with the

sensitive region of the microdosimeter (Fig. 4.15, on the right).

Figure 4.15: On the left, the boron target. On the right, the boron target

placed on the MicroPlus probe.

73


4.6.2 Results

The experimental data was analysed with the same method of the previous

sections. Microdosimetric spectra were obtained for each position (Fig. 4.16).

The values of yF and yD together with their statistical error are reported in

Tabb. 4.9 and 4.10, respectively. As for the spectra obtained without the

boron converter, we observed the proton edge at 30.58 mm and 30.94 mm

depth; we also observed a peak caused by noise at 28.45 mm.

Figure 4.16: Microdosimetric spectra obtained with a boron target in front of

the microdosimeter.

Position

(mm)

yF

(KeV/µm)

Statistical error

(KeV/µm)

Relative error

(%)

28.45 6.024 0.004 0.06

29.16 8.281 0.005 0.07

29.87 12.652 0.004 0.03

30.58 16.023 0.017 0.08

30.94 16.783 0.044 0.26

Table 4.9: Measurement results for the value of yF as a function of depth, with

associated statistical and relative uncertainties, with a boron target placed in

front of the detector.

74


Position

(mm)

yD

(KeV/µm)

Statistical error

(KeV/µm)

Relative error

(%)

28.45 7.618 0.023 0.28

29.16 10.959 0.019 0.17

29.87 16.597 0.008 0.05

30.58 20.108 0.021 0.11

30.94 21.235 0.097 0.45

Table 4.10: Measurement results for the value of yD as a function of depth, with

associated statistical and relative uncertainties, with a boron target placed in

front of the detector.

In order to study the effect of the presence of the boron converter, the mi-

crodosimetric spectra obtained with boron were compared with the analogues

obtained in its absence (Fig. 4.17).

Figure 4.17: Comparison between the microdosimetric spectra obtained with

and without the boron target at a depth of 28.45 mm, 26.16 mm, 29.87 mm,

30.58 mm and 30.94 mm.

75


The relative difference is reported for the values of yF and yD in Tabb. 4.11

and 4.12.

Position

(mm)

yF Boron

(KeV/µm)

yF w/o Boron

(KeV/µm)

Relative difference

(%)

28.45 6.024 5.966 0.95

29.16 8.281 7.872 4.94

29.87 12.652 11.720 7.36

30.58 16.023 15.097 5.77

30.94 16.783 16.619 0.98

Table 4.11: Comparison between the values of yF obtained with and without

the boron target.

Position

(mm)

yD Boron

(KeV/µm)

yD w/o Boron

(KeV/µm)

Relative difference

(%)

28.45 7.6180 7.617 0.01

29.16 10.959 10.374 5.33

29.87 16.597 15.516 6.51

30.58 20.108 19.189 4.57

30.94 21.235 20.795 2.10

Table 4.12: Comparison between the values of yD obtained with and without

the boron target.

Both for yF and yD the maximum relative difference between the values mea-

sured with and without the boron converter is observed at a depth of 29.87

mm, with percentages of 7.36% and 6.51% respectively. To be specific, the

effects of the presence of boron are apparent at the depths of 29.16 mm, 29.87

mm and 30.58 mm, both for yF and yD. This is the region where the protons

slow down and the cross section of the p+11B reaction increases. On the other

hand, no effect is evident at 28.45 mm.

There is a clear correlation between the presence of boron and the increase

in the microdosimetric quantities. However, since a target of natural boron

76


(19,9% 10B, 80.1% 11B) was used for the measurements, we could not determine

to what extent the increase in yF and yD was due to the p+11B reaction, as

compared to the more common n+10B. In principle, we cannot exclude that

the latter makes a relevant contribution. Further investigation is needed in

order to distinguish the alphas produced in the p+11B reaction from those

produced in the n+10B reaction.

77

Conclusions

The p+11B inelastic reactions triggered by energetic protons as they slow down

across a clinical SOBP seem to produce an enhancement in the proton radiobi-

ological effectiveness. The experimental results obtained by irradiating human

prostate cancer cells, even if well-corroborated by repeated experimental cam-

paigns [27], seem to fall short of an immediate justification by estimations

merely based on analytical and Monte Carlo evaluations of classical dosimet-

ric quantities such as integral dose, LET and RBE. This prompts us to adopt

a microdosimetric approach, through which experimental information on the

number and quality of high-LET particles produced in the reaction can be

obtained.

In this context, the response of the MicroPlus probe, the new silicon micro-

dosimeter developed by the CMRP at the Wollongong University, was investi-

gated along the 62 MeV proton beam SOBP of the CATANA facility (INFN-

LNS). The aim was to obtain a first microdosimetric characterization of the

CATANA 62 MeV clinical proton SOBP, with and without a boron converter,

through the MicroPlus probe. This study is part of a new INFN project called

NEPTUNE (Nuclear process-driven Enhancement of Proton Therapy UNrav-

Eled), whose aim is to consolidate and explain the promising results of PBCT.

The measurements without the boron converter were performed using the Mi-

croPlus Probe models #705 and #592 in different positions of the SOBP. Lin-

eal energy distributions and the corresponding microdosimetric quantities were

calculated for each position and then compared with Monte Carlo simulations

of the LET. From the analysis we concluded that both the microdosimeters

deviate from the simulated values, especially at the distal SOBP. The values

of the microdosimetric quantities measured through model #705 are generally

lower than their simulated counterpart, while those measured through model

#592 are often higher. On the other hand, there seems to be good agreement

78

Conclusions

between the experimental measures of the dose-weighted mean lineal energy

obtained at the distal SOBP with the the MicroPlus probe #592 and that

obtained with a Mini-TEPC and a Silicon Telescope.

The response of the MicroPlus probe was also investigated by placing a boron

converter in front of the microdosimeter. The measurements were performed

at the distal SOBP, in the same positions as those chosen for the measurements

without boron. We found that there is a clear correlation between the presence

of boron and the increase in the microdosimetric quantities. However, we were

unable to evaluate to what extent this effect is due to the p+11B reaction,

rather than to the more common n+10B. To be specific, since both the isotopes

are present in the natural boron target, we could not distinguish the alphas

produced in the p+11B reaction from those produced in the n+10B reaction.

In order to shed light on this issue, the next step will be to perform the

measurements in the same positions using both a 10B-enriched and a 11B-

enriched boron target.

79

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