David D Yang, Leslie K Lee, James M G Tsui, Jonathan E Leeman, Heather M McClure, Atchar Sudhyadhom, Christian V Guthier, Mary-Ellen Taplin, Quoc-Dien Trinh, Kent W Mouw, Neil E Martin, Peter F Orio, Paul L Nguyen, Anthony V D'Amico, Kee-Young Shin, Katie N Lee, Martin T King
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{"title":"多参数磁共振成像的 AI 导出肿瘤体积与局部前列腺癌的预后","authors":"David D Yang, Leslie K Lee, James M G Tsui, Jonathan E Leeman, Heather M McClure, Atchar Sudhyadhom, Christian V Guthier, Mary-Ellen Taplin, Quoc-Dien Trinh, Kent W Mouw, Neil E Martin, Peter F Orio, Paul L Nguyen, Anthony V D'Amico, Kee-Young Shin, Katie N Lee, Martin T King","doi":"10.1148/radiol.240041","DOIUrl":null,"url":null,"abstract":"<p><p>Background An artificial intelligence (AI)-based method for measuring intraprostatic tumor volume based on data from MRI may provide prognostic information. Purpose To evaluate whether the total volume of intraprostatic tumor from AI-generated segmentations (V<sub>AI</sub>) provides independent prognostic information in patients with localized prostate cancer treated with radiation therapy (RT) or radical prostatectomy (RP). Materials and Methods For this retrospective, single-center study (January 2021 to August 2023), patients with cT1-3N0M0 prostate cancer who underwent MRI and were treated with RT or RP were identified. Patients who underwent RT were randomly divided into cross-validation and test RT groups. An AI segmentation algorithm was trained to delineate Prostate Imaging Reporting and Data System (PI-RADS) 3-5 lesions in the cross-validation RT group before providing segmentations for the test RT and RP groups. Cox regression models were used to evaluate the association between V<sub>AI</sub> and time to metastasis and adjusted for clinical and radiologic factors for combined RT (ie, cross-validation RT and test RT) and RP groups. Areas under the receiver operating characteristic curve (AUCs) were calculated for V<sub>AI</sub> and National Comprehensive Cancer Network (NCCN) risk categorization for prediction of 5-year metastasis (RP group) and 7-year metastasis (combined RT group). Results Overall, 732 patients were included (combined RT group, 438 patients; RP group, 294 patients). Median ages were 68 years (IQR, 62-73 years) and 61 years (IQR, 56-66 years) for the combined RT group and the RP group, respectively. V<sub>AI</sub> was associated with metastasis in the combined RT group (median follow-up, 6.9 years; adjusted hazard ratio [AHR], 1.09 per milliliter increase; 95% CI: 1.04, 1.15; <i>P</i> = .001) and the RP group (median follow-up, 5.5 years; AHR, 1.22; 95% CI: 1.08, 1.39; <i>P</i> = .001). AUCs for 7-year metastasis for the combined RT group for V<sub>AI</sub> and NCCN risk category were 0.84 (95% CI: 0.74, 0.94) and 0.74 (95% CI: 0.80, 0.98), respectively (<i>P</i> = .02). Five-year AUCs for the RP group for V<sub>AI</sub> and NCCN risk category were 0.89 (95% CI: 0.80, 0.98) and 0.79 (95% CI: 0.64, 0.94), respectively (<i>P</i> = .25). Conclusion The volume of AI-segmented lesions was an independent, prognostic factor for localized prostate cancer. © RSNA, 2024 <i>Supplemental material is available for this article.</i></p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"313 1","pages":"e240041"},"PeriodicalIF":12.1000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI-derived Tumor Volume from Multiparametric MRI and Outcomes in Localized Prostate Cancer.\",\"authors\":\"David D Yang, Leslie K Lee, James M G Tsui, Jonathan E Leeman, Heather M McClure, Atchar Sudhyadhom, Christian V Guthier, Mary-Ellen Taplin, Quoc-Dien Trinh, Kent W Mouw, Neil E Martin, Peter F Orio, Paul L Nguyen, Anthony V D'Amico, Kee-Young Shin, Katie N Lee, Martin T King\",\"doi\":\"10.1148/radiol.240041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Background An artificial intelligence (AI)-based method for measuring intraprostatic tumor volume based on data from MRI may provide prognostic information. Purpose To evaluate whether the total volume of intraprostatic tumor from AI-generated segmentations (V<sub>AI</sub>) provides independent prognostic information in patients with localized prostate cancer treated with radiation therapy (RT) or radical prostatectomy (RP). Materials and Methods For this retrospective, single-center study (January 2021 to August 2023), patients with cT1-3N0M0 prostate cancer who underwent MRI and were treated with RT or RP were identified. Patients who underwent RT were randomly divided into cross-validation and test RT groups. An AI segmentation algorithm was trained to delineate Prostate Imaging Reporting and Data System (PI-RADS) 3-5 lesions in the cross-validation RT group before providing segmentations for the test RT and RP groups. Cox regression models were used to evaluate the association between V<sub>AI</sub> and time to metastasis and adjusted for clinical and radiologic factors for combined RT (ie, cross-validation RT and test RT) and RP groups. Areas under the receiver operating characteristic curve (AUCs) were calculated for V<sub>AI</sub> and National Comprehensive Cancer Network (NCCN) risk categorization for prediction of 5-year metastasis (RP group) and 7-year metastasis (combined RT group). Results Overall, 732 patients were included (combined RT group, 438 patients; RP group, 294 patients). Median ages were 68 years (IQR, 62-73 years) and 61 years (IQR, 56-66 years) for the combined RT group and the RP group, respectively. V<sub>AI</sub> was associated with metastasis in the combined RT group (median follow-up, 6.9 years; adjusted hazard ratio [AHR], 1.09 per milliliter increase; 95% CI: 1.04, 1.15; <i>P</i> = .001) and the RP group (median follow-up, 5.5 years; AHR, 1.22; 95% CI: 1.08, 1.39; <i>P</i> = .001). AUCs for 7-year metastasis for the combined RT group for V<sub>AI</sub> and NCCN risk category were 0.84 (95% CI: 0.74, 0.94) and 0.74 (95% CI: 0.80, 0.98), respectively (<i>P</i> = .02). Five-year AUCs for the RP group for V<sub>AI</sub> and NCCN risk category were 0.89 (95% CI: 0.80, 0.98) and 0.79 (95% CI: 0.64, 0.94), respectively (<i>P</i> = .25). Conclusion The volume of AI-segmented lesions was an independent, prognostic factor for localized prostate cancer. © RSNA, 2024 <i>Supplemental material is available for this article.</i></p>\",\"PeriodicalId\":20896,\"journal\":{\"name\":\"Radiology\",\"volume\":\"313 1\",\"pages\":\"e240041\"},\"PeriodicalIF\":12.1000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1148/radiol.240041\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1148/radiol.240041","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
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