Differentiating small (< 2 cm) pancreatic ductal adenocarcinoma from neuroendocrine tumors with multiparametric MRI-based radiomic features.

IF 4.7 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
European Radiology Pub Date : 2024-12-01 Epub Date: 2024-06-13 DOI:10.1007/s00330-024-10837-x
Keren Shen, Weijie Su, Chunmiao Liang, Dan Shi, Jihong Sun, Risheng Yu
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引用次数: 0

Abstract

Objectives: To assess MR-based radiomic analysis in preoperatively discriminating small (< 2 cm) pancreatic ductal adenocarcinomas (PDACs) from neuroendocrine tumors (PNETs).

Methods: A total of 197 patients (146 in the training cohort, 51 in the validation cohort) from two centers were retrospectively collected. A total of 7338 radiomics features were extracted from T2-weighted, diffusion-weighted, T1-weighted, arterial phase, portal venous phase and delayed phase imaging. The optimal features were selected by the Mann-Whitney U test, Spearman's rank correlation test and least absolute shrinkage and selection operator method and used to construct the radiomic score (Rad-score). Conventional radiological and clinical features were also assessed. Multivariable logistic regression was used to construct a radiological model, a radiomic model and a fusion model.

Results: Nine optimal features were identified and used to build the Rad-score. The radiomic model based on the Rad-score achieved satisfactory results with AUCs of 0.905 and 0.930, sensitivities of 0.780 and 0.800, specificities of 0.906 and 0.952 and accuracies of 0.836 and 0.863 for the training and validation cohorts, respectively. The fusion model, incorporating CA19-9, tumor margins, pancreatic duct dilatation and the Rad-score, exhibited the best performance with AUCs of 0.977 and 0.941, sensitivities of 0.914 and 0.852, specificities of 0.954 and 0.950, and accuracies of 0.932 and 0.894 for the training and validation cohorts, respectively.

Conclusions: The MR-based Rad-score is a novel image biomarker for discriminating small PDACs from PNETs. A fusion model combining radiomic, radiological and clinical features performed very well in differentially diagnosing these two tumors.

Clinical relevance statement: A fusion model combining MR-based radiomic, radiological, and clinical features could help differentiate between small pancreatic ductal adenocarcinomas and pancreatic neuroendocrine tumors.

Key points: Preoperatively differentiating small pancreatic ductal adenocarcinomas (PDACs) and pancreatic neuroendocrine tumors (PNETs) is challenging. Multiparametric MRI-based Rad-score can be used for discriminating small PDACs from PNETs. A fusion model incorporating radiomic, radiological, and clinical features differentiated small PDACs from PNETs well.

Abstract Image

利用基于多参数磁共振成像的放射学特征区分小型(< 2 厘米)胰腺导管腺癌和神经内分泌肿瘤。
目的评估基于核磁共振成像的放射学分析在术前鉴别小(方法:回顾性收集两个中心的 197 例患者(146 例为训练队列,51 例为验证队列)。从 T2 加权、弥散加权、T1 加权、动脉期、门静脉期和延迟期成像中提取了共 7338 个放射组学特征。通过曼-惠特尼 U 检验、斯皮尔曼秩相关检验、最小绝对收缩和选择算子法筛选出最佳特征,用于构建放射组学评分(Rad-score)。此外,还对常规放射学和临床特征进行了评估。多变量逻辑回归用于构建放射学模型、放射学模型和融合模型:结果:确定了九个最佳特征,并将其用于建立 Rad 评分。基于 Rad 评分的放射学模型取得了令人满意的结果,训练组和验证组的 AUC 分别为 0.905 和 0.930,灵敏度分别为 0.780 和 0.800,特异度分别为 0.906 和 0.952,准确度分别为 0.836 和 0.863。融合了CA19-9、肿瘤边缘、胰管扩张和Rad-score的融合模型表现最佳,训练组和验证组的AUC分别为0.977和0.941,灵敏度分别为0.914和0.852,特异性分别为0.954和0.950,准确度分别为0.932和0.894:结论:基于磁共振的Rad-score是一种新的图像生物标志物,可用于区分小型PDAC和PNET。结合放射学、放射学和临床特征的融合模型在区分诊断这两种肿瘤方面表现出色:基于 MR 的放射学、影像学和临床特征的融合模型有助于区分小型胰腺导管腺癌和胰腺神经内分泌肿瘤:要点:术前区分小胰腺导管腺癌(PDAC)和胰腺神经内分泌肿瘤(PNET)具有挑战性。基于 MRI 的多参数 Rad-score 可用于区分小型 PDAC 和 PNET。一个融合了放射学、放射学和临床特征的模型能很好地区分小型 PDAC 和 PNET。
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来源期刊
European Radiology
European Radiology 医学-核医学
CiteScore
11.60
自引率
8.50%
发文量
874
审稿时长
2-4 weeks
期刊介绍: European Radiology (ER) continuously updates scientific knowledge in radiology by publication of strong original articles and state-of-the-art reviews written by leading radiologists. A well balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes ER an indispensable source for current information in this field. This is the Journal of the European Society of Radiology, and the official journal of a number of societies. From 2004-2008 supplements to European Radiology were published under its companion, European Radiology Supplements, ISSN 1613-3749.
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