Radiomics in early detection of bilio-pancreatic lesions: A narrative review

IF 3.2 3区医学 Q2 GASTROENTEROLOGY & HEPATOLOGY

Best Practice & Research Clinical Gastroenterology Pub Date : 2025-02-01 DOI:10.1016/j.bpg.2025.101997

Calogero Casà , Daniel Portik , Ahmed Nadeem Abbasi , Francesco Miccichè

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引用次数: 0

Abstract

Radiomics is transforming the field of early detection of bilio-pancreatic lesions, offering significant advancements in diagnostic accuracy and personalized treatment planning. By extracting high-dimensional data from medical images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), radiomics reveals complex patterns that remain undetectable through traditional imaging evaluation. This review synthesizes recent developments in radiomics, particularly its application to early detection of pancreatic cancer (PC) and biliary duct cancer (BDC). It highlights the role of machine learning algorithms and multi-parametric models in improving diagnostic performance and discusses challenges such as standardization, reproducibility, and the need for larger, multicenter datasets. The integration of radiomics with genomic data and liquid biopsies also presents future opportunities for more individualized patient care.

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放射组学在胆道-胰腺病变早期检测中的应用综述

放射组学正在改变胆道胰腺病变的早期检测领域，在诊断准确性和个性化治疗计划方面取得了重大进展。通过从计算机断层扫描（CT）、磁共振成像（MRI）和正电子发射断层扫描（PET）等医学图像中提取高维数据，放射组学揭示了传统成像评估无法检测到的复杂模式。本文综述了放射组学的最新进展，特别是其在胰腺癌（PC）和胆管癌（BDC）早期检测中的应用。它强调了机器学习算法和多参数模型在提高诊断性能方面的作用，并讨论了标准化、可重复性以及对更大、多中心数据集的需求等挑战。放射组学与基因组数据和液体活检的整合也为未来更加个性化的患者护理提供了机会。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Best Practice & Research Clinical Gastroenterology 医学-胃肠肝病学

CiteScore

5.50

自引率

0.00%

发文量

审稿时长

69 days

期刊介绍： Each topic-based issue of Best Practice & Research Clinical Gastroenterology will provide a comprehensive review of current clinical practice and thinking within the specialty of gastroenterology.