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
AIM: To develop a population-based statistical model in order to find a spatial pattern of dose distribution which is related to lower urinary tract symptoms (LUTS) after iodine-125 (125I) seed implantation for prostate cancer. PATIENTS AND METHODS: A total of 75 patients underwent 125I seed implantation for prostate cancer. Principal component analysis was applied to the standardized dose array and for each patient dose distribution was uniquely characterized by a combination of weighted eigenvectors. The correlation between eigenvectors and the severity of LUTS was investigated with linear regression analysis. RESULTS: Eight eigenvectors were identified as being significantly associated with the severity of LUTS (p<0.05). Multivariate regression model identified that intraprostatic parameters, which were positively associated with the severity of LUTS, were distributed around a portion of the urethral base and a peripheral region of the prostate. CONCLUSION: We established a population-based statistical model that may indicate a significant dose pattern associated with the severity of radiation toxicity. Copyright
AIM: To develop a population-based statistical model in order to find a spatial pattern of dose distribution which is related to lower urinary tract symptoms (LUTS) after iodine-125 (125I) seed implantation for prostate cancer. PATIENTS AND METHODS: A total of 75 patients underwent 125I seed implantation for prostate cancer. Principal component analysis was applied to the standardized dose array and for each patient dose distribution was uniquely characterized by a combination of weighted eigenvectors. The correlation between eigenvectors and the severity of LUTS was investigated with linear regression analysis. RESULTS: Eight eigenvectors were identified as being significantly associated with the severity of LUTS (p<0.05). Multivariate regression model identified that intraprostatic parameters, which were positively associated with the severity of LUTS, were distributed around a portion of the urethral base and a peripheral region of the prostate. CONCLUSION: We established a population-based statistical model that may indicate a significant dose pattern associated with the severity of radiation toxicity. Copyright
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