title: Development of an inverse optimization package to plan nonuniform dose distributions based on spatially inhomogeneous radiosensitivity extracted from biological images.
abstract: An inverse optimization package which is capable of generating nonuniform dose distribution with subregional dose escalation is developed to achieve maximum equivalent uniform dose (EUD) for target while keeping the critical structure doses as low as possible. Relative cerebral blood volume (rCBV) maps obtained with a dynamic susceptibility contrast-enhanced MRI technique were used to delineate spatial radiosensitivity distributions. The voxel rCBV was converted to voxel radiosensitivity parameters (e.g., alpha and alpha/beta) based on previously reported correlations between rCBV, tumor grade, and radiosensitivity. A software package, DOSEPAINT, developed using MATLAB, optimizes the beamlet weights to achieve maximum EUD for target while limiting doses to critical structures. Using DOSEPAINT, we have generated nonuniform 3D-dose distributions for selected patient cases. Depending on the variation of the pixel radiosensitivity, the subregional dose escalation can be as high as 35% of the uniform dose as planned conventionally. The target dose escalation comes from both the inhomogeneous radiosensitivities and the elimination of integral target dose constraint. The target EUDs are found to be higher than those for the uniform dose planned ignoring the spatial inhomogeneous radiosensitivity. The EUDs for organs at risk are found to be approximately equal to or lower than those for the uniform dose plans. In conclusion, we have developed a package that is capable of generating nonuniform dose distributions optimized for spatially inhomogeneous radiosensitivity. Subregional dose escalation may lead to increased treatment effectiveness as indicated by higher EUDs. The current development will impact biological image guided radiotherapy.
authors.affiliation: Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA.
authors.forename: Guang-Pei
authors.initials: GP
authors.lastname: Chen
authors.forename: Ergun
authors.initials: E
authors.lastname: Ahunbay
authors.forename: Christopher
authors.initials: C
authors.lastname: Schultz
authors.forename: X Allen
authors.initials: XA
authors.lastname: Li
mesh_terms: D000465:Algorithms; D016880:Anisotropy; D001932:Brain Neoplasms / Q000503:physiopathology / Q000532:radiotherapy*; D019583:Dose Fractionation, Radiation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009928:Organ Specificity; D011836:Radiation Tolerance; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods*; D012984:Software