从基线 CT 图像中提取的放射组学特征在预测非手术治疗的胰腺导管腺癌患者总生存期中的价值：将放射组学评分纳入多参数命定图以预测一年总生存期。

IF 2.2 3区医学 Q3 GASTROENTEROLOGY & HEPATOLOGY

Journal of Gastrointestinal Surgery Pub Date : 2025-02-01 DOI:10.1016/j.gassur.2024.101882

Seyedeh Panid Madani , Mohammad Mirza-Aghazadeh-Attari , Alireza Mohseni , Shadi Afyouni , Ghazal Zandieh , Haneyeh Shahbazian , Ali Borhani , Iman Yazdani Nia , Daniel Laheru , Timothy M. Pawlik , Ihab R. Kamel

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引用次数: 0

摘要

目的：确定基线 CT 扫描和容积测量得出的放射组学特征对预测接受 FOLFIRINOX 治疗的非手术胰腺导管腺癌（PDAC）患者总生存期的价值：在这项回顾性单机构研究中，纳入了2012年12月至2021年11月期间接受FOLFIRINOX新辅助化疗的131例非手术治疗PDAC患者。所有患者在纳入前均进行了治疗前对比增强 CT 成像检查。原发肿瘤的轮廓由具有 25 年经验的放射科专家绘制。从肿瘤总体积中总共提取了 845 个放射组学特征，包括一阶、二阶和高阶特征。特征缩减管道用于降低数据的维度。所选特征用于生成基于 LASSO 系数的放射组学评分。根据放射组学评分以及其他定量和语义成像结果生成高维 Cox 模型：结果：在提取的 845 个放射组学特征中，有 45 个特征在三元组之间存在显著差异。放射组学评分公式如下：=小面积强调⁎-66.87801+大依赖性强调⁎-0.2345916。放射组学评分在三组放射组学特征之间存在显著差异（P = 0.034）。三组的总生存率差异显著（P = 0.02）。提名图显示出良好的校准性，并在将患者分为三等分时显示出显著差异（P 结论：放射组学方法具有预测非手术治疗的胰腺导管腺癌患者总生存期的潜力，纳入语义成像结果和病理数据可进一步提高 PDAC 患者的预后。

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Value of radiomics features extracted from baseline computed tomography images in predicting overall survival in patients with nonsurgical pancreatic ductal adenocarcinoma: incorporation of a radiomics score to a multiparametric nomogram to predict 1-year overall survival

Purpose

This study aimed to determine the value of radiomics features derived from baseline computed tomography (CT) scans and volumetric measurements to predict overall survival (OS) in patients with nonsurgical pancreatic ductal adenocarcinoma (PDAC) treated with a chemotherapy combination regimen of 5-fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX).

Methods

In this retrospective single-institution study, 131 patients with nonsurgical PDAC who received FOLFIRINOX neoadjuvant chemotherapy between December 2012 and November 2021 were included. Pretreatment contrast-enhanced CT images were obtained for all patients before inclusion. The primary tumor was contoured by an expert radiologist with 25 years of experience. A total of 845 radiomics features, including first-, second-, and higher-order features, were extracted from the total tumor volume. A feature reduction pipeline was used to reduce the dimensionality of the data. The selected features were used to generate a radiomics score based on the Least Absolute Shrinkage and Selection Operator coefficients. A high-dimensional Cox model was generated on the basis of the radiomics score and other quantitative and semantic imaging findings.

Results

From the 845 radiomics features extracted, 45 were significantly different between the tertiles. The following equation was used to generate a radiomics score: radiomics score = SmallAreaEmphasis (−66.87801 + LargeDependenceEmphasis) − 0.2345916. The radiomics score was significantly different among the 3 groups of the radiomics features (P = .034). The overall difference in survival was significant among the 3 groups (P = .02). The nomogram showed good calibration and showed significant differences among the patients when they were classified as tertiles (P < .00).

Conclusion

Radiomics approaches have the potential to predict OS in nonsurgical patients with PDAC, and the inclusion of semantic imaging findings and pathologic data could further enhance prognostication in patients with PDAC.

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来源期刊

Journal of Gastrointestinal Surgery 医学-外科

CiteScore

5.50

自引率

3.10%

发文量

319

审稿时长

2 months

期刊介绍： The Journal of Gastrointestinal Surgery is a scholarly, peer-reviewed journal that updates the surgeon on the latest developments in gastrointestinal surgery. The journal includes original articles on surgery of the digestive tract; gastrointestinal images; "How I Do It" articles, subject reviews, book reports, editorial columns, the SSAT Presidential Address, articles by a guest orator, symposia, letters, results of conferences and more. This is the official publication of the Society for Surgery of the Alimentary Tract. The journal functions as an outstanding forum for continuing education in surgery and diseases of the gastrointestinal tract.