the growth of tumor masses g. dattoli enea frascati

31
The growth of tumor masses G. Dattoli ENEA FRASCATI The point of view of a laser physicist (a theoritician)

Upload: shay-kim

Post on 31-Dec-2015

12 views

Category:

Documents


1 download

DESCRIPTION

The growth of tumor masses G. Dattoli ENEA FRASCATI. The point of view of a laser physicist (a theoritician). Power laws. Math. Formulation Self- Symilarity (Invariance under Scale trasformation, Kallan-Szymanzik). TAYLOR-”Law”. Bode-law. Distance of planets from the sun - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: The growth of tumor masses G. Dattoli ENEA FRASCATI

The growth of tumor massesG. Dattoli

ENEA FRASCATIThe point of view of a laser physicist

(a theoritician)

Page 2: The growth of tumor masses G. Dattoli ENEA FRASCATI

Power laws

Math. Formulation

• Self- Symilarity (Invariance under • Scale trasformation, Kallan-Szymanzik)

,)(1

),log()log())(log()(

00

kk

k

x

xxy

xa

xkaxyxaxy

)()( xyxyxx k

Page 3: The growth of tumor masses G. Dattoli ENEA FRASCATI

TAYLOR-”Law”

5

12

)(

tE

tR

Page 4: The growth of tumor masses G. Dattoli ENEA FRASCATI

Bode-law

• Distance of planets from the sun

• n=n-th planet

1.0

)(

,73.1

,,44

),()(

amplitudewith

noffunctionyoscillatorweakn

b

unitsondependingbuta

nband n

Page 5: The growth of tumor masses G. Dattoli ENEA FRASCATI

Astrophysics1.2rM

Page 6: The growth of tumor masses G. Dattoli ENEA FRASCATI

Biology& EchologyThe New fronteer

• Volterra-Lotka, Malthus, Gompertz, Damouth, Kleiber…

Page 7: The growth of tumor masses G. Dattoli ENEA FRASCATI

Echology: Damouth-law

25.2lP

Page 8: The growth of tumor masses G. Dattoli ENEA FRASCATI

Biology & Ecology: the Paradise of the scaling law

• Kleiber:mass- metabolyc rate

4

3

MkR

Page 9: The growth of tumor masses G. Dattoli ENEA FRASCATI

)/(90

,

4

3

4

3

Kgscalk

MkR

Page 10: The growth of tumor masses G. Dattoli ENEA FRASCATI

Kleiber-Law 18-orders of magnitude!!!!!

Page 11: The growth of tumor masses G. Dattoli ENEA FRASCATI

…3/4 ???

Card.rate -1/4

Card. period 1/4

Life Duration

1/4

Diam, Aorta 3/4

Mass. Brain 3/4

Consumption O(ml/s)

3/4

Gluc

mg/m

3/4

const

MTRE

cL

,

Page 12: The growth of tumor masses G. Dattoli ENEA FRASCATI

Kleiber and dynamics…

• Rate eq. (West, Brown, Enquist (1997))

ratemetabolyctotalB

cellperEnergyE

rateMetabolycCellB

cellsofNumberN

td

NdEBNB

c

c

c

cccc

.

.

,

,

Page 13: The growth of tumor masses G. Dattoli ENEA FRASCATI

Eq. Di evoluzione

0

4

30

4

3

0

0

,

)(

,)(

,

mm

mE

Bm

E

mB

td

md

mBmB

mE

BmB

E

m

td

md

mNm

td

NdEBNB

c

c

c

c

c

c

c

c

cc

cccc

Page 14: The growth of tumor masses G. Dattoli ENEA FRASCATI

Living body Evolution

Von-Bartalanffy- Quantitative laws in metabolism and growth-Quarterly review on Biology 32, 217-231 (1957).

.....,..

)(

.)(,

,0

,

0

4

30

FELOttavianiLPGD

stransitionphaseLandauGinzburgh

BiolyBartalanffVonmbmadt

md

mm

mE

Bm

E

mB

td

md

c

c

c

c

Page 15: The growth of tumor masses G. Dattoli ENEA FRASCATI

Logistic-function,Gompertz….

• The solutions of the Eq.

• Is a logistic type

0

4

30

0

,

mm

mE

Bm

E

mB

td

md

c

c

c

c

)1ln(4

,

4

1

0

4

0

M

m

B

ET

B

mBM

c

c

c

c

4

3

00

04

mB

nET cc

c

c

tt

B

E

eeM

mMtm

4

,1)(

1

4

4 0 11

Page 16: The growth of tumor masses G. Dattoli ENEA FRASCATI

Analisi dei dati West & Brown)

Page 17: The growth of tumor masses G. Dattoli ENEA FRASCATI

Growth of tumor masses

Prostate cancer

0 100 200 300

200

400

600

800

Mass (grams) of the human prostate cancer vs. time (days) using the WBE equation and the parameters

./1094.2)0(

,/10753.1)0(,103,101.2

4

33

0

695

dayJgB

dayJBgmJE

t

tccc

Page 18: The growth of tumor masses G. Dattoli ENEA FRASCATI

Prostate and breast cancer andenergetic

• age 40 years

0 50 100 150 200

200

400

600

800

0 2 4 6 8 101

10

100

1 103

1 104

1 105

1 106

WdayJBgWdaygB

daytJEM

mBB

m

aEBmBP

E

tPE

E

tPE

t

m

MEE

s

e

s

t

m

MEdttmBE

tc

t

ct

tc

c

ctc

tc

c

c

c

c

c

c

ts

s

s

c

ct

t

1164

324

33

0

4

4

00

4

3

03

4

4

3

4

4

4

3

10

4

3

0

102/10753.1,104.3/1094.2

))((85.0][,,,,4

1

,)(

4

1

,

,13

)1(4')'(

Page 19: The growth of tumor masses G. Dattoli ENEA FRASCATI

Tumor cell evolution

33

ccmnr

0.01 0.1 1 10 100 1 103

1 104

1

10

100

1 103

1 104

1 105

1 106

1 107

1 108

1 109

1 1010

1 1011

1 1012

n t 1 1( )

n t 4 1( )

n t 12 1( )

107

109

1011

t

Evolution of the tumor cell number vs time, final mass 671 g, different evolution times

days121

days481

days1441

Page 20: The growth of tumor masses G. Dattoli ENEA FRASCATI

Tumor and host organ

• Human prostate cancer mass in grams (continuous line) and cancer metabolic rate in (continuous line), vs time in days (the dash curve refers to the average human metabolic rate). The cancer power density has been calculated assuming that the tumour has a spherical shape with a density comparable to that of the water.

0 20 40 60 80 1000

200

400

600

Page 21: The growth of tumor masses G. Dattoli ENEA FRASCATI

Required Power

• • For a practically vanishing initial tumour mass

and at small times we can evaluate the power associated to the tumour evolution, during its early stages is given by

• while the energy used to generate the corresponding tumour mass is

4

3

0 )()( tmBtP

4

3

0

33

4

3,

4

1

cc

c

cT

mBP

tE

PP

3

4

4

)(

4

1

c

c

E

tPE

Page 22: The growth of tumor masses G. Dattoli ENEA FRASCATI

Carrying Capacity and critical times for methastases spreading

O

T

P

PC 3

4*

c

O

c

c

P

P

P

Et

3

4

0

*

B

Pm O

0.1 1 10 100 1 1031 10

3

0.01

0.1

1

10

100

1 103

1 104

1 105

1 106

P t( )

86400 2

10

86400

10

t

Page 23: The growth of tumor masses G. Dattoli ENEA FRASCATI

Tumor and methastases

• Statistical model, Poissonian distribution

• Il parametro is, along with the growth time, a measure of the tumour aggressivity

))(exp(

!

)()( tn

s

tntp

s

Page 24: The growth of tumor masses G. Dattoli ENEA FRASCATI

Evolution of methastasis• Probability vs. time (days) that s-malignant cells leaves the primary tumour • s=10 cells (solid line), s=50 cells (dash line), s=130 cells (dot line)• for M=671 g and

days120,10 13

1 10 100 1 103

1 104

1 109

1 108

1 107

1 106

1 105

1 104

1 103

0.01

0.1

1

10

1 10 100 1 103

1 104

1 105

1 109

1 108

1 107

1 106

1 105

1 104

1 103

0.01

0.1

1

10

years5.6,10 16

Page 25: The growth of tumor masses G. Dattoli ENEA FRASCATI

Probability of spreading

• Probability of colony formation vs. time (days) for a tumour with days and 1 colony (solid line), 10 colonies (dot line), 50 colonies (dash line), number of cells normalized to the saturation number (dash-dot), the parallel line corresponds to the clinical level (cells)

1 10 100 1 103

1 104

1 104

1 103

0.01

0.1

1

10

Page 26: The growth of tumor masses G. Dattoli ENEA FRASCATI

Angiogenesis

Page 27: The growth of tumor masses G. Dattoli ENEA FRASCATI

Conclusions

• Biol. Evolution relies on complex mechanisms• Simple mathematical models are welcome• The same applies to tumor mass evolution • Concepts like carrying capacity e methastases

spreading could be understoo in enegetic terms• The Kleiber “law” should be considered as the

manifestation of a more general LAW • The dependence on the temperature should be

included

• Tk

Ei

eMTMB

4

3

),(

Page 28: The growth of tumor masses G. Dattoli ENEA FRASCATI

…Conclusions

• E=6 eV typical value of biochemical reactions

TK

Ei

eMcl

4

1

1

Page 29: The growth of tumor masses G. Dattoli ENEA FRASCATI

Frattali e legge di Kleiber

Page 30: The growth of tumor masses G. Dattoli ENEA FRASCATI

….Fractal dimensions

Page 31: The growth of tumor masses G. Dattoli ENEA FRASCATI