Yeon-Koo Kang, Seunggyun Ha, Ji Bong Jeong, So Won Oh
{"title":"PET/CT 放射组学在预测胰腺导管腺癌患者生存结果方面的价值。","authors":"Yeon-Koo Kang, Seunggyun Ha, Ji Bong Jeong, So Won Oh","doi":"10.1038/s41598-024-77022-4","DOIUrl":null,"url":null,"abstract":"<p><p>Pancreatic ductal adenocarcinoma (PDAC) is associated with poor prognosis even without distant metastases, necessitating in-depth characterization of primary tumors for survival prediction. We assessed the feasibility of using FDG-PET/CT radiomics to predict overall survival (OS) in PDAC. This retrospective study included PDAC patients without distant metastasis who underwent FDG-PET/CT for initial staging. Primary tumors were segmented from FDG-PET/CT images, extracting 222 radiomics features. A radiomics-based risk score (Rad-score) was developed using Cox proportional hazards regression with LASSO to predict OS. The prognostic performance of the Rad-score was compared with a clinical model (demographics, disease stage, laboratory results) using Harrell's concordance index (C-index) and bootstrapping. 140 patients were included, with a mortality rate was 72.9% during follow-up (total population, 19.5 ± 19.2 months; survivors, 34.4 ± 28.8 months). Eleven radiomics features were significant for survival prediction. The Rad-score predicted OS with a C-index of 0.681 [95% CI, 0.632-0.731]. A model integrating clinical parameters and Rad-score outperformed the clinical-only model in predicting OS (C-index 0.740 [0.715-0.816] vs. 0.673 [0.650-0.766]; C-index difference 0.067 [0.014-0.113]; P < 0.001). These findings suggest that incorporating FDG-PET/CT radiomics into preexisting prognotic stratification paradiagm may enhance survival prediction in PDAC, warranting large-scale studies to confirm its applicability in clinical practice.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"14 1","pages":"28958"},"PeriodicalIF":3.8000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The value of PET/CT radiomics for predicting survival outcomes in patients with pancreatic ductal adenocarcinoma.\",\"authors\":\"Yeon-Koo Kang, Seunggyun Ha, Ji Bong Jeong, So Won Oh\",\"doi\":\"10.1038/s41598-024-77022-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Pancreatic ductal adenocarcinoma (PDAC) is associated with poor prognosis even without distant metastases, necessitating in-depth characterization of primary tumors for survival prediction. We assessed the feasibility of using FDG-PET/CT radiomics to predict overall survival (OS) in PDAC. This retrospective study included PDAC patients without distant metastasis who underwent FDG-PET/CT for initial staging. Primary tumors were segmented from FDG-PET/CT images, extracting 222 radiomics features. A radiomics-based risk score (Rad-score) was developed using Cox proportional hazards regression with LASSO to predict OS. The prognostic performance of the Rad-score was compared with a clinical model (demographics, disease stage, laboratory results) using Harrell's concordance index (C-index) and bootstrapping. 140 patients were included, with a mortality rate was 72.9% during follow-up (total population, 19.5 ± 19.2 months; survivors, 34.4 ± 28.8 months). Eleven radiomics features were significant for survival prediction. The Rad-score predicted OS with a C-index of 0.681 [95% CI, 0.632-0.731]. A model integrating clinical parameters and Rad-score outperformed the clinical-only model in predicting OS (C-index 0.740 [0.715-0.816] vs. 0.673 [0.650-0.766]; C-index difference 0.067 [0.014-0.113]; P < 0.001). These findings suggest that incorporating FDG-PET/CT radiomics into preexisting prognotic stratification paradiagm may enhance survival prediction in PDAC, warranting large-scale studies to confirm its applicability in clinical practice.</p>\",\"PeriodicalId\":21811,\"journal\":{\"name\":\"Scientific Reports\",\"volume\":\"14 1\",\"pages\":\"28958\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Reports\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41598-024-77022-4\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-024-77022-4","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
The value of PET/CT radiomics for predicting survival outcomes in patients with pancreatic ductal adenocarcinoma.
Pancreatic ductal adenocarcinoma (PDAC) is associated with poor prognosis even without distant metastases, necessitating in-depth characterization of primary tumors for survival prediction. We assessed the feasibility of using FDG-PET/CT radiomics to predict overall survival (OS) in PDAC. This retrospective study included PDAC patients without distant metastasis who underwent FDG-PET/CT for initial staging. Primary tumors were segmented from FDG-PET/CT images, extracting 222 radiomics features. A radiomics-based risk score (Rad-score) was developed using Cox proportional hazards regression with LASSO to predict OS. The prognostic performance of the Rad-score was compared with a clinical model (demographics, disease stage, laboratory results) using Harrell's concordance index (C-index) and bootstrapping. 140 patients were included, with a mortality rate was 72.9% during follow-up (total population, 19.5 ± 19.2 months; survivors, 34.4 ± 28.8 months). Eleven radiomics features were significant for survival prediction. The Rad-score predicted OS with a C-index of 0.681 [95% CI, 0.632-0.731]. A model integrating clinical parameters and Rad-score outperformed the clinical-only model in predicting OS (C-index 0.740 [0.715-0.816] vs. 0.673 [0.650-0.766]; C-index difference 0.067 [0.014-0.113]; P < 0.001). These findings suggest that incorporating FDG-PET/CT radiomics into preexisting prognotic stratification paradiagm may enhance survival prediction in PDAC, warranting large-scale studies to confirm its applicability in clinical practice.
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