Inclusion of Biological Information in Treatment Planning Optimization Dag Rune Olsen

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1 Inclusion of Biological Information in Treatment Planning Optimization Dag Rune Olsen Institute for Cancer Research, Norwegian Radium Hospital, University of Oslo

2 Theragnostics biological conformality Tumors are often spatially and temporally heterogeneous uniform tumor dose vs non-uniform tumor dose? Treatment optimization guided by biological images of the tumor

3 Theragnostics biological conformality The hypothesis is that non-invasive biological imaging may provide the pertinent information to guide the painting or sculpting of the optimal dose distribution. C.C. Ling, Int. J. Radiat. Oncol. Biol. Phys. 47: , 2000.

4 Theragnostics biological conformality Sir William Osler: The principles and practice of Medicine, 1892 If it were not for the great variability among individuals, medicine might as well be a science and not an art

5 Theragnostics Challenge 1: How to obtain relevant and valid biological information applicable to treatment plan optimization?

6 Theragnostics

7 Theragnostics A): Metabolism (FDG) B): proliferation (FLT) C): hypoxia (Cu-ATSM) D): angiogenesis (MMP) Apisarnthanaraxa & Chao, RADIATION RESEARCH 163, 1 25, 2005.

8 Theragnostics Molecular markers and tracers in PET Mechanism of FDG in functional imaging D. Heron, et al. Medical Dosimetry, 31(1):3-11, 2005.

9 Theragnostics Dynamic contrast enhances MRI: Perfusion, oxygenation Diffusion MRI: Cellular integrity, cell death MRSi: metabolism dce-mri

10 dce- MRI & tumor hypoxia Frequency (%) po 2 (mm Hg) probe MR C i ( t ) = K t Ki ( t u ) trans ν e, i i Ca( u )e 0 trans du E PERF K (ml / (g min) ) trans po 2 (mm Hg)

11 dce- MRI & tumor hypoxia po 2, calc 1: > 20 mm Hg 2: 5-20 mm Hg 3: mm Hg Compartmentization 4: < 0.5 mm Hg

12 Optimization Challenge 2: How to utilize the information in dose distribution optimization? Image of a relevant biological parameters Ideal dose map Planned dose map

13 Optimization Dose modifying factor: D i =OER i (p i ) * D ox

14 Optimization Constraint: - maintaining the mean dose to the target volume: - iso-biological effect in each voxel of the target volume: TCP = TCP [ V, ρ, α(oer),β(oer), γ ] volume density radiosensitivity repopulation rate

15 Optimization where f i (d) is the normalized dose distribution for compartment i, and the integration over N i (d)f i (d) yields the expected number of surviving clonogens in the given compartment. The total TCP is given by the product of the probabilities for controlling each compartment and is obtained by integrating the product over a distribution of radiation sensitivities g(α O ):

16 Optimization For a tumour with a non-uniform distribution of radiation sensitivity, the optimal dose distribution for a given mean dose is the distribution which gives a uniform density ρ of surviving clonogens in the tumour:

17 Optimization

18 Optimization Prescribed compartmental doses and calculated TCP for a uniform and nonuniform prescription scheme.

19 Optimization TCP for a non-uniform and a uniform dose distribution of equal mean dose for four cases. TCP for varying numbers of dose prescription compartments for cases 2 and 3.

20 Optimization

21 Dynamics Challenge 3: How to deal with and systematic and random errors, and spatial and temporal changes? Treatment fraction K trans

22 Dynamics A B Systematic and random errors: The effect on the TCP by randomly (A) or systematically (B) assigning voxels to other tumour compartments.

23 Dynamics Fraction 1 Fraction 2 Fraction 3 Fraction 4 Fraction 5 Fraction 7 Fraction 9 Fraction 10 Spatial distribution of po 2 segmented into four compartments, on 16 of the 18 treatment fractions. Fraction 11 Fraction 12 2 Fraction 13 Fraction Fraction 15 Fraction 16 Fraction 17 Fraction 18

24 Dynamics Hypoxic volume fractions (A) and corresponding optimal dose per treatment fraction (B) for different compartments for each of the treatment fractions.

25 Dynamics 40% reoxygenation TCP as a function of dose per fraction to the normoxic compartment for: no reoxygenation ( ) 10% reoxygenation ( ) 20% reoxygenation( ) 30% reoxygenation( ) 40% reoxygenation ( ) no reoxygenation The dose per fraction to the normoxic compartment was kept constant.

26 Dynamics uniforme dose TCP drops with increasing fraction of acute hypoxic cells, and is lowest appying a uniform dose as compared to non-uinform dose. TCP increases with increasing fraction of the chronic hypoxic celles that receive the intended dose

27 Dynamics

28 Multi-parametric optimization Challenge 4: How to deal with multiple parameters/ information?

29 The Pareto principle: for many events, 80% of the effects come from 20% of the causes. Does this apply to radiation oncology optimization? Can we identify the critical 20% component? Wilfried Fritz Pareto

30 Thank you for your attention!