基于mri的风险分层预测胰腺导管腺癌的总生存期。

IF 4.5 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Insights into Imaging Pub Date : 2025-09-24 DOI:10.1186/s13244-025-02088-1

Haitao Sun, Jianbo Li, Lei Li, Peng Wang, Qiying Tang, Tianyu Lu, Jun Han, Zongyu Xie, Yiheng Zhou, Kai Liu, Mengsu Zeng, Minping Hong, Yaolin Xu, Jianjun Zhou

{"title":"基于mri的风险分层预测胰腺导管腺癌的总生存期。","authors":"Haitao Sun, Jianbo Li, Lei Li, Peng Wang, Qiying Tang, Tianyu Lu, Jun Han, Zongyu Xie, Yiheng Zhou, Kai Liu, Mengsu Zeng, Minping Hong, Yaolin Xu, Jianjun Zhou","doi":"10.1186/s13244-025-02088-1","DOIUrl":null,"url":null,"abstract":"Purpose: To develop and validate a magnetic resonance imaging (MRI)-based pancreatic risk stratification model (M-PRiSM) for prognosis prediction and therapy guidance in pancreatic ductal adenocarcinoma (PDAC).Materials and methods: In this retrospective multicenter study, a total of 540 patients with PDAC were enrolled. A Cox proportional hazards model was used to identify significant clinical-radiological predictors and develop an M-PRiSM risk score system. The performance of the model was assessed using Harrell's C-index, time-dependent area under the curve (AUC), and calibration curves, and was compared with existing clinical prediction metrics, including the 8th American Joint Committee on Cancer (AJCC) staging and CA19-9 levels.Results: 540 PDAC patients were split into a development cohort (n = 282) and an internal validation cohort (n = 122), with 136 patients forming external cohort A (n = 80) and B (n = 56). The model, incorporating CA19-9 (hazard ratio (HR), 1.604, p = 0.047), margin (HR, 1.918, p = 0.001), tumor size (HR, 1.308, p = 0.003), and venous enhancement ratio (VER) (HR, 0.605, p = 0.047), was developed, showing superior predictive accuracy for OS with C-indexes of 0.73, 0.70, and 0.70, and 0.68 across four cohorts. The model outperformed the 8th AJCC staging and CA19-9 alone across validation cohorts (p < 0.001). High-risk patients exhibit the worst overall survival (OS) and a higher frequency of adverse pathological features, but benefited significantly from adjuvant therapy, with improved survival outcomes.Conclusion: The M-PRiSM model effectively predicts postoperative OS and identifies PDAC patients likely to benefit from adjuvant treatment.Critical relevance statement: The M-PRiSM model, utilizing MRI and clinical features, enables preoperative risk stratification for overall survival in pancreatic ductal adenocarcinoma, offering a generalizable tool to guide personalized adjuvant therapy and enhance prognostic assessment.Key points: The M-PRiSM model can effectively predict pancreatic ductal adenocarcinoma survival. The M-PRiSM model showed strong generalizability in external validations. The M-PRiSM model stratifies patients for guiding adjuvant therapy for improved outcomes.","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"205"},"PeriodicalIF":4.5000,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12460861/pdf/","citationCount":"0","resultStr":"{\"title\":\"MRI-based risk stratification for predicting overall survival in pancreatic ductal adenocarcinoma.\",\"authors\":\"Haitao Sun, Jianbo Li, Lei Li, Peng Wang, Qiying Tang, Tianyu Lu, Jun Han, Zongyu Xie, Yiheng Zhou, Kai Liu, Mengsu Zeng, Minping Hong, Yaolin Xu, Jianjun Zhou\",\"doi\":\"10.1186/s13244-025-02088-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose: To develop and validate a magnetic resonance imaging (MRI)-based pancreatic risk stratification model (M-PRiSM) for prognosis prediction and therapy guidance in pancreatic ductal adenocarcinoma (PDAC).Materials and methods: In this retrospective multicenter study, a total of 540 patients with PDAC were enrolled. A Cox proportional hazards model was used to identify significant clinical-radiological predictors and develop an M-PRiSM risk score system. The performance of the model was assessed using Harrell's C-index, time-dependent area under the curve (AUC), and calibration curves, and was compared with existing clinical prediction metrics, including the 8th American Joint Committee on Cancer (AJCC) staging and CA19-9 levels.Results: 540 PDAC patients were split into a development cohort (n = 282) and an internal validation cohort (n = 122), with 136 patients forming external cohort A (n = 80) and B (n = 56). The model, incorporating CA19-9 (hazard ratio (HR), 1.604, p = 0.047), margin (HR, 1.918, p = 0.001), tumor size (HR, 1.308, p = 0.003), and venous enhancement ratio (VER) (HR, 0.605, p = 0.047), was developed, showing superior predictive accuracy for OS with C-indexes of 0.73, 0.70, and 0.70, and 0.68 across four cohorts. The model outperformed the 8th AJCC staging and CA19-9 alone across validation cohorts (p < 0.001). High-risk patients exhibit the worst overall survival (OS) and a higher frequency of adverse pathological features, but benefited significantly from adjuvant therapy, with improved survival outcomes.Conclusion: The M-PRiSM model effectively predicts postoperative OS and identifies PDAC patients likely to benefit from adjuvant treatment.Critical relevance statement: The M-PRiSM model, utilizing MRI and clinical features, enables preoperative risk stratification for overall survival in pancreatic ductal adenocarcinoma, offering a generalizable tool to guide personalized adjuvant therapy and enhance prognostic assessment.Key points: The M-PRiSM model can effectively predict pancreatic ductal adenocarcinoma survival. The M-PRiSM model showed strong generalizability in external validations. The M-PRiSM model stratifies patients for guiding adjuvant therapy for improved outcomes.\",\"PeriodicalId\":13639,\"journal\":{\"name\":\"Insights into Imaging\",\"volume\":\"16 1\",\"pages\":\"205\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12460861/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Insights into Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s13244-025-02088-1\",\"RegionNum\":2,\"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":"Insights into Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13244-025-02088-1","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}

引用次数: 0

摘要

目的：建立并验证基于磁共振成像（MRI）的胰腺风险分层模型（M-PRiSM），用于胰腺导管腺癌（PDAC）的预后预测和治疗指导。材料和方法：在这项回顾性多中心研究中，共入组540例PDAC患者。Cox比例风险模型用于识别重要的临床放射学预测因子，并开发M-PRiSM风险评分系统。采用Harrell’s c指数、曲线下随时间变化的面积（AUC）和校准曲线对模型的性能进行评估，并与现有的临床预测指标（包括第8届美国癌症联合委员会（AJCC）分期和CA19-9水平）进行比较。结果：540例PDAC患者被分为发展队列（n = 282）和内部验证队列（n = 122），其中136例患者组成外部队列a （n = 80）和B （n = 56）。该模型纳入了CA19-9（风险比（HR）， 1.604, p = 0.047）、边缘（HR, 1.918, p = 0.001）、肿瘤大小（HR, 1.308, p = 0.003）和静脉增强比（VER）（HR, 0.605, p = 0.047），在4个队列中，c指数分别为0.73、0.70、0.70和0.68，显示出较好的OS预测准确性。该模型在验证队列中的表现优于第8期AJCC分期和单独CA19-9 (p)结论：M-PRiSM模型可有效预测术后OS并识别可能从辅助治疗中获益的PDAC患者。关键相关性声明：M-PRiSM模型利用MRI和临床特征，实现了胰腺导管腺癌的术前总生存风险分层，为指导个性化辅助治疗和增强预后评估提供了一种通用工具。重点：M-PRiSM模型能有效预测胰腺导管腺癌患者的生存。M-PRiSM模型在外部验证中表现出较强的泛化性。M-PRiSM模型对患者进行分层，以指导辅助治疗以改善预后。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

MRI-based risk stratification for predicting overall survival in pancreatic ductal adenocarcinoma.

Purpose: To develop and validate a magnetic resonance imaging (MRI)-based pancreatic risk stratification model (M-PRiSM) for prognosis prediction and therapy guidance in pancreatic ductal adenocarcinoma (PDAC).

Materials and methods: In this retrospective multicenter study, a total of 540 patients with PDAC were enrolled. A Cox proportional hazards model was used to identify significant clinical-radiological predictors and develop an M-PRiSM risk score system. The performance of the model was assessed using Harrell's C-index, time-dependent area under the curve (AUC), and calibration curves, and was compared with existing clinical prediction metrics, including the 8^th American Joint Committee on Cancer (AJCC) staging and CA19-9 levels.

Results: 540 PDAC patients were split into a development cohort (n = 282) and an internal validation cohort (n = 122), with 136 patients forming external cohort A (n = 80) and B (n = 56). The model, incorporating CA19-9 (hazard ratio (HR), 1.604, p = 0.047), margin (HR, 1.918, p = 0.001), tumor size (HR, 1.308, p = 0.003), and venous enhancement ratio (VER) (HR, 0.605, p = 0.047), was developed, showing superior predictive accuracy for OS with C-indexes of 0.73, 0.70, and 0.70, and 0.68 across four cohorts. The model outperformed the 8th AJCC staging and CA19-9 alone across validation cohorts (p < 0.001). High-risk patients exhibit the worst overall survival (OS) and a higher frequency of adverse pathological features, but benefited significantly from adjuvant therapy, with improved survival outcomes.

Conclusion: The M-PRiSM model effectively predicts postoperative OS and identifies PDAC patients likely to benefit from adjuvant treatment.

Critical relevance statement: The M-PRiSM model, utilizing MRI and clinical features, enables preoperative risk stratification for overall survival in pancreatic ductal adenocarcinoma, offering a generalizable tool to guide personalized adjuvant therapy and enhance prognostic assessment.

Key points: The M-PRiSM model can effectively predict pancreatic ductal adenocarcinoma survival. The M-PRiSM model showed strong generalizability in external validations. The M-PRiSM model stratifies patients for guiding adjuvant therapy for improved outcomes.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Insights into Imaging Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

7.30

自引率

4.30%

发文量

182

审稿时长

13 weeks

期刊介绍： Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere! I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe. Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy. A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field. I³ is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly. The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members. The journal went open access in 2012, which means that all articles published since then are freely available online.