3. What is radiation therapy (RT)? Cancer treatment Tumor versus normal tissues External photon beam RT

4. Intensity-modulated RT (IMRT) Brahme et al. 1982 –Fluence-modulated beams –Homogeneous, concave dose distributions Better target dose conformity and/or better sparing of organs at risk (OARs)

5. Imaging for RT

6. Anatomical imaging CT MRI

7. Biological imaging PET SPECT fMRI MRSI Brain Tumor

8. Tumor biology characterization RadiotracerCharacterization 18 F-FDGGlucose metabolism 18 F-FLTDNA synthesis 11 C-METProtein synthesis 60 Cu-ATSM, 18 F-FMISOHypoxia Radiolabeled Annexin VApoptosis Radiolabeled  V  3 integrin antagonists Angiogenesis Apisarnthanarax and Chao 2005

9. Biological imaging for RT Improvement of diagnostic and staging accuracy Guidance of target volume definition and dose prescription Evaluation of therapeutic response

10. Target volume definition Gross tumor volume (GTV) Clinical target volume (CTV) Planning target volume (PTV)

11. Biological target volume (BTV) Ling et al. 2000

12. Dose painting

13. Dose painting by contours

14. Dose painting by numbers

15. Biologically Conformal Radiation Therapy

16. Dose calculation algorithms Speed versus accuracy: –Broad beam –Pencil beam (PB) –Convolution/superposition (CS) –Monte Carlo (MC) Monte Carlo dose engine MCDE Reynaert et al. 2004 Accuracy ↑ Speed ↓

17. MC dose calculation accuracy Cross section data Treatment beam modeling Patient modeling –CT conversion –Electron disequilibrium –Conversion of dose to medium to dose to water Statistical uncertainties

20. Implementation of BCRT: Relationship between signal intensity and radiation dose Dose I low I high D low D high Signal intensity

21. Implementation of BCRT: Treatment planning strategy

22. Implementation of BCRT: Biology-based segmentation tool 2D segmentation grid in template beam’s eye view –Projection of targets (+) –Integration of signal intensities along rayline (+) –Projection of organs at risk (-) –Distance Segment contours from iso-value lines of segmentation grid

23. Implementation of BCRT: Objective function Optimization of segment weights and shapes (leaf positions) Expression of planning goals Biological: –Tumor control probability (TCP) –Normal tissue complication probability (NTCP) Physical: –Dose prescription

24. Implementation of BCRT: Treatment plan evaluation QVH

25. Implementation of BCRT: Example [ 18 F]FDG-PET guided BCRT for oropharyngeal cancer PTV dose prescription: D low = 2.16 Gy/fxD high = 2.5 and 3 Gy/fx I low = 0.25*I 95% I high = I 95%

26. Implementation of BCRT: Example

28. Implementation of BCRT: Conclusions Technical solution –Biology-based segmentation tool –Objective function Feasibility –Planning constraints OK –Best biological conformity for the lowest level of dose escalation

30. BCRT planning study: Set-up BCRT or dose painting-by-numbers (“voxel intensity-based IMRT”) versus dose painting (“contour-based IMRT”) 15 head and neck cancer patients Comparison of clinically relevant dose- volume characteristics –Between “cb 250 ” and “vib 216-250 ” –Between “vib 216-250 ” and “vib 216-300 ”

31. BCRT planning study: Target dose prescription “cb 250 ” (cGy/fx) “vib 216-250 ” (cGy/fx) “vib 216-300 ” (cGy/fx) PTV PET 250 PTV 69+PET 216 - 250216 - 300 PTV 69 216 PTV 66 206 PTV 62 194 PTV 56 175

32. BCRT planning study: “cb 250 ” (blue) versus “vib 216-250 ” (green)

33. BCRT planning study: “vib 216-250 ” (green) versus “vib 216-300 ” (orange)

34. BCRT planning study: Example

35. BCRT planning study: QF

36. BCRT planning study: Conclusions BCRT did not compromise the planning constraints for the OARs Best biological conformity was obtained for the lowest level of dose escalation Compared to dose painting by contours, improved target dose coverage was achieved using BCRT

37. MC dose calculations in the clinic Comparison of PB, CS and MCDE for lung IMRT Comparison of 6 MV and 18 MV photons for lung IMRT Conversion of CT numbers into tissue parameters: a multi-centre study Evaluation of uncertainty-based stopping criteria Feasibility of MC-based IMRT optimization

38. CT conversion: multi-centre study Stoichiometric calibration Dosimetrically equivalent tissue subsets Gammex RMI 465 tissue calibration phantom Patient dose calculations Conversion of dose to medium to dose to water

39. CT conversion: example

40. CT conversion: conclusions Accuracy of MC patient dose calculations Proposed CT conversion scheme: Air, lung, adipose, muscle, 10 bone bins Validated on phantoms Patient study: Multiple bone bins necessary if dose is converted to dose to water

42. Biologically conformal RT Technical solution –Bound-constrained linear model –Treatment plan optimization Biology-based segmentation tool Objective function –Treatment plan evaluation Feasibility of FDG-PET guided BCRT for head and neck cancer

43. MC dose calculations Individual patients may benefit from highly accurate MC dose calculations Improvement of MCDE –CT conversion –Uncertainty-based stopping criteria Feasibility of MC-based IMRT optimization MCDE is unsuitable for routine clinical use, but represents an excellent benchmarking tool

45. Adaptive RT: Inter-fraction tumor tracking Anatomical & biological changes during RT Re-imaging and re-planning Ghent University Hospital: phase I trial on adaptive FDG-PET guided BCRT in head and neck cancer

46. Summation of DVHs CT 1 Dose 1CT 2Dose 2 Registration Structure 1 Points P Doses TPoints TP Doses Total doses Total DVH Structure 2

47. Summation of QVHs CT 1 Dose 1CT 2Dose 2 Registration Structure 1 Points P Q-values TPoints TP Q-values Total Q-values Total QVH PET 1PET 2 Registration Disregard TPoints outside structure 2 Structure 2

48. Treatment planning and delivery Biological optimisation Adaptive RT Biological imaging Tracers Acquisition, reconstruction, quantification Clinical investigations Fundamental research in vitro, animal studies Treatment outcome