cancer therapy and imaging cancer therapy and imaging rob edgecock stfc rutherford appleton...

Cancer Therapy and ImagingCancer Therapy and Imaging

Rob EdgecockSTFC Rutherford Appleton Laboratory

Imaging and DosimetryImaging and Dosimetry

• What else do we need to know for radiotherapy?

Where the tumour is (exactly)

The structure of the patient

Optimum treatment

Correct dose is delivered

Imaging

Imaging

Treatment planning

Dosimetry

ImagingImaging

• Four main techniques

X-rays

ImagingImaging

• Four main techniques

X-rays

More absorption by denser objects, e.g. bones- appear lighter

Less absorption by less dense objects- appear darker

ImagingImaging

• Four main techniques

CT Scan: Computerised (Axial) Tomography

X-rays source and detector rotate

Thousands of images taken

3Dish image built by computer

Very common technique as very fast

ImagingImaging

• Four main techniques

CT Scan: Computerised (Axial) Tomography

Much bigger dose than X-rays!

ImagingImaging

• Four main techniques

Molecular imaging: PET and SPECT

Load tumour/organ with radiopharmaceutical.

Detect products from decay.

Positron Emission Tomography

Single Photon Emission Computed Tomography

ImagingImaging

• Four main techniques

PET Scan:

Most accurate tumour location

Not so good for surroundings

ImagingImaging

• Four main techniques

SPECT: uses a gamma emitter directly

Gamma detectors rotate.

Make 2D images.

3D reconstructed offline.

Resolution not as good as PET.

ImagingImaging

• Four main techniques

MRI Scan: Magnetic Resonance Imaging

Magnetic field lines up atoms.

Different atoms absorb different RF frequencies.

Very good for soft tissues (exploits hydrogen in water).

ImagingImaging

• Four main techniques are (sort of) complementary

• None is ideal

• Can lead to incorrectly defined margins

Results from 11 student oncologists.

Areas inside lines would be treated.

ImagingImaging

• Situation is improved by combining techniques

• E.g. CT + PET

• Still significant room for improvement

Results from 11 student oncologists.

Areas inside lines would be treated.

Treatment PlanningTreatment Planning

• Takes images, etc

• Uses software to determine best treatment plan

• Best position, angle, no. of fields, energies, etc

• Depends on image quality, knowledge of tissue, etc

• Tumour motion

Timescale Effect Possible solution

Seconds Breathing Gating; averaging

Minutes Patient motion Markers

Day Patient position; food & liquid Markers; re-scan

Week “ “ “ “ Markers; re-scan

• Reduced precision of beam delivery – larger area

DosimetryDosimetry

• Verify correct dose delivered to tumour

• ”In-vivo” dosimetry preferred.....but not actually in-vivo!

Catheter dosimeterWireless dosimeter

Contributions from Particle Contributions from Particle PhysicsPhysics

• Improved accelerators for radiotherapy

hard to improve on linacs for X-rays

but..........

Laptop

1MeV electron prototype

Big sister being tested

Contributions from Particle Contributions from Particle PhysicsPhysics

Fixed Field Alternating Gradient accelerator

Cyclotron-like

Synchrotron-like

• Combines features of cyclotrons and synchrotrons

• Interesting for X-ray radiotherapy

• But.....particularly interesting for hadron therapy.....

• .....plus particle physics, power generation, etc

Hadron TherapyHadron Therapy

• Requirements

Proton up to carbon beams; 250 MeV to 400MeV/u

Rapid cycling: ~500-1000Hz

Rapid energy variation from accelerator

Gantries

Reliability

“Small” cost

Small size

• Used currently:

Cyclotrons: protons; SC understudy for carbon

Synchrotrons: protons and carbon

RequirementsRequirements

Cyclotron Synchrotron FFAG

Protons & carbon Yes(ish) Yes Yes

Rapid cycling Yes No Yes

Variable energy No Yes Yes

Cost and size – S/C Yes No Yes

Gantries Yes Yes Yes

Reliability Yes No(ish) Yes

• FFAGs very interesting

• Most interesting type – no machine ever built

• So we’ve built one – called EMMA

EMMAEMMA

EMMA = proof-of-principle machine

Electrons from 10 to 20MeV

Use ALICE as injector

42 magnetic “cells”

Built on 7 girders

EMMAEMMA

Works!Full experimental programme started.

First results published in Nature Physics.

PAMELAPAMELA

PAMELAPAMELA

PAMELAPAMELA

Recondensing cryocooler

Insulating vacuum chamber

4k Helium vessel

Magnets

Magnet support structure

40k Radiation shield

40k Inner radiation shield

D FF

Next step: prototyping of main components:- ring magnets- RF cavities- extraction magnets

Positive funding signs

Contributions from Particle Contributions from Particle PhysicsPhysics

• Improved PET imaging:

better tumour location

verification that treatment in correct place

ToF PETToF PET

• Standard PET:

best tumour locator

but essentially 2D

software required

worse resolution &long time

• ToF PET

3D

better image & shorter time

Conventional

Detector

Tomograph Ring

Time-of-Flight

ToF PETToF PET

Conventional

500 ps

1.2 ns

300 ps700 ps

Phantom(1:2:3 body:liver:tumor)

• PP techniques being tried

• Target ~50ps, but v. difficult

• Projects to improve other techniques underway

Achieved

Commercially available

Contributions from Particle Contributions from Particle PhysicsPhysics

• In-vivo dosimetry

smaller device - possible to leave in?

lower power consumption

additional functionality at later date

RFUNIT

PWRUNIT

RADUNIT

RF receiver

RadiationSource

Implantable micro unit

Concept of in-vivo dosimetry

Contributions from Particle Contributions from Particle PhysicsPhysics

• In-vivo dosimetry

smaller device - possible to leave in?

lower power consumption

additional functionality at later date

Low power electronic

Radiation Sensor Antenna

1000μm

Thin film battery on the back side

Silicon chip

Contributions from Particle Contributions from Particle PhysicsPhysics

• Data storage and analysis:

creating framework for clinical data

including long term follow-up

help strengthen case

provide info for improvements

• Patient modelling

no two patients the same treatment planning includes modelling of beam

PP techniques and codes being tried

PP measurements of interactions for models

ConclusionsConclusions

• Knowledge from PP being applied in various areas

• Strong priority in the UK

• One discussed here

• Cancer therapy

data storage and analysis

modelling

detector development

accelerator design