PURPOSE: To construct a tumor voxel dose response matrix (DRM) and dose prescription function (DPF) for adaptive dose painting by number (DPbN) based on treatment feedback of fluoro-2-deoxyglucose (FGD) positron emission tomography (PET)/computed tomography (CT) imaging. METHODS AND MATERIALS: FDG-PET/CT images obtained before and after chemoradiation therapy and at weekly chemoradiation therapy sessions for each of 18 patients with head and neck cancer, as well as the treatment outcomes, were used in the modeling. All weekly and posttreatment PET/CT images were registered voxel-to-voxel to the corresponding pretreatment baseline PET/CT image. Tumor voxel DRM was created using serial FDG-PET imaging of each patient with respect to the baseline standardized uptake value (SUV0). A tumor voxel control probability (TVCP) lookup table was created using the maximum likelihood estimation on the tumor voxel (SUV0, DRM) domain of all tumors. Tumor voxel DPF was created from the TVCP lookup table and used as the objective function for DPbN-based inverse planning optimization. RESULTS: Large intertumoral and intratumoral variations on both tumor voxels (SUV0, DRM) were identified. Tumor voxel dose resistance did not show correlation with its baseline SUV0 value and was the major cause of the tumor local failures. Tumor voxel DPF as the function of tumor voxel (SUV0, DRM) values also showed a very large intertumoral and intratumoral heterogeneity. Most human papillomavirus-negative tumors require a treatment dose >100 Gy to certain local tumor regions. These treatment doses, which are most unlikely to be implementable in conventional radiation therapy, can be achieved using adaptive DPbN treatment. Clinical feasibility was evaluated by comparing the adaptive DPbN treatment plan with the conventional intensity modulated radiation therapy plan. CONCLUSIONS: Tumor voxel (SUV0, DRM) provides an intratumoral prognostic map to target tumor locoregional-resistant regions. The corresponding TVCP or DPF provides a quantitative objective to optimize the intratumoral dose distribution for the individuals. The adaptive DPbN with FDG-PET/CT imaging feedback is feasible to implement in clinics.
PURPOSE: To construct a tumor voxel dose response matrix (DRM) and dose prescription function (DPF) for adaptive dose painting by number (DPbN) based on treatment feedback of fluoro-2-deoxyglucose (FGD) positron emission tomography (PET)/computed tomography (CT) imaging. METHODS AND MATERIALS: FDG-PET/CT images obtained before and after chemoradiation therapy and at weekly chemoradiation therapy sessions for each of 18 patients with head and neck cancer, as well as the treatment outcomes, were used in the modeling. All weekly and posttreatment PET/CT images were registered voxel-to-voxel to the corresponding pretreatment baseline PET/CT image. Tumor voxel DRM was created using serial FDG-PET imaging of each patient with respect to the baseline standardized uptake value (SUV0). A tumor voxel control probability (TVCP) lookup table was created using the maximum likelihood estimation on the tumor voxel (SUV0, DRM) domain of all tumors. Tumor voxel DPF was created from the TVCP lookup table and used as the objective function for DPbN-based inverse planning optimization. RESULTS: Large intertumoral and intratumoral variations on both tumor voxels (SUV0, DRM) were identified. Tumor voxel dose resistance did not show correlation with its baseline SUV0 value and was the major cause of the tumor local failures. Tumor voxel DPF as the function of tumor voxel (SUV0, DRM) values also showed a very large intertumoral and intratumoral heterogeneity. Most human papillomavirus-negative tumors require a treatment dose >100 Gy to certain local tumor regions. These treatment doses, which are most unlikely to be implementable in conventional radiation therapy, can be achieved using adaptive DPbN treatment. Clinical feasibility was evaluated by comparing the adaptive DPbN treatment plan with the conventional intensity modulated radiation therapy plan. CONCLUSIONS:Tumor voxel (SUV0, DRM) provides an intratumoral prognostic map to target tumor locoregional-resistant regions. The corresponding TVCP or DPF provides a quantitative objective to optimize the intratumoral dose distribution for the individuals. The adaptive DPbN with FDG-PET/CT imaging feedback is feasible to implement in clinics.
Authors: Chunyan Duan; W Art Chaovalitwongse; Fangyun Bai; Daniel S Hippe; Shouyi Wang; Phawis Thammasorn; Larry A Pierce; Xiao Liu; Jianxin You; Robert S Miyaoka; Hubert J Vesselle; Paul E Kinahan; Ramesh Rengan; Jing Zeng; Stephen R Bowen Journal: Phys Med Biol Date: 2020-10-07 Impact factor: 3.609
Authors: Weisi Yan; Mohammad K Khan; Xiaodong Wu; Charles B Simone; Jiajin Fan; Eric Gressen; Xin Zhang; Charles L Limoli; Houda Bahig; Slavisa Tubin; Waleed F Mourad Journal: Clin Transl Radiat Oncol Date: 2019-10-22
Authors: E J Her; A Haworth; H M Reynolds; Y Sun; A Kennedy; V Panettieri; M Bangert; S Williams; M A Ebert Journal: Radiat Oncol Date: 2020-07-13 Impact factor: 3.481