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

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

Imaging for RT

Anatomical imaging CT MRI

Biological imaging PET SPECT fMRI MRSI Brain Tumor

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

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

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

Biological target volume (BTV) Ling et al. 2000

Dose painting

Dose painting by contours

Dose painting by numbers

Biologically Conformal Radiation Therapy

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 Accuracy ↑ Speed ↓

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

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

Implementation of BCRT: Treatment planning strategy

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

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

Implementation of BCRT: Treatment plan evaluation QVH

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%

Implementation of BCRT: Example

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

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 ” –Between “vib ” and “vib ”

BCRT planning study: Target dose prescription “cb 250 ” (cGy/fx) “vib ” (cGy/fx) “vib ” (cGy/fx) PTV PET 250 PTV 69+PET PTV PTV PTV PTV

BCRT planning study: “cb 250 ” (blue) versus “vib ” (green)

BCRT planning study: “vib ” (green) versus “vib ” (orange)

BCRT planning study: Example

BCRT planning study: QF

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

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

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

CT conversion: example

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

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

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

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

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

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

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