Kazuma Kobayashi1,2,3, Naoya Murakami4, Kana Takahashi4, Koji Inaba4, Hiroshi Igaki4, Ryuji Hamamoto5,2,3, Jun Itami4. 1. Division of Molecular Modification and Cancer Biology, National Cancer Center Research Institute, Tokyo, Japan; kazumkob@ncc.go.jp. 2. Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan. 3. Department of NCC Cancer Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan. 4. Department of Radiation Oncology, National Cancer Center Hospital, Tokyo, Japan. 5. Division of Molecular Modification and Cancer Biology, National Cancer Center Research Institute, Tokyo, Japan.
Abstract
BACKGROUND/AIM: We established a data-driven method for extracting spatial patterns of dose distribution associated with radiation injuries, based on patients with prostate cancer who underwent iodine-125 (I-125) seed implantation. PATIENTS AND METHODS: Seventy-five patients underwent I-125 seed implantation for prostate cancer. We modeled the severity of lower urinary tract symptoms (LUTS) to be estimated using a linear model, which is formulated as an inner product between the dose distribution D and voxel-wise radiosensitivity B inside the prostate. For the estimation, tensor regression based on a low-rank decomposition with generalized fused lasso penalty was applied. RESULTS: The spatial distribution of B was visually assessed. Positive parameters appeared dominantly in the region close to the urethra and the prostate base. CONCLUSION: Our tensor regression-based model can predict intra-organ radiosensitivity in a data-driven manner, providing a compelling parameter distribution associated with the development of LUTS after I-125 seed implantation for prostate cancer. Copyright
BACKGROUND/AIM: We established a data-driven method for extracting spatial patterns of dose distribution associated with radiation injuries, based on patients with prostate cancer who underwent iodine-125 (I-125) seed implantation. PATIENTS AND METHODS: Seventy-five patients underwent I-125 seed implantation for prostate cancer. We modeled the severity of lower urinary tract symptoms (LUTS) to be estimated using a linear model, which is formulated as an inner product between the dose distribution D and voxel-wise radiosensitivity B inside the prostate. For the estimation, tensor regression based on a low-rank decomposition with generalized fused lasso penalty was applied. RESULTS: The spatial distribution of B was visually assessed. Positive parameters appeared dominantly in the region close to the urethra and the prostate base. CONCLUSION: Our tensor regression-based model can predict intra-organ radiosensitivity in a data-driven manner, providing a compelling parameter distribution associated with the development of LUTS after I-125 seed implantation for prostate cancer. Copyright
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