Radiomics for the Diagnosis and Differentiation of Pancreatic Cystic Lesions

Radiomics, also known as quantitative imaging or texture analysis, involves extracting a large number of features traditionally unmeasured in conventional radiological cross-sectional images and converting them into mathematical models. This review describes this approach and its use in the evaluation of pancreatic cystic lesions (PCLs). This discipline has the potential of more accurately assessing, classifying, risk stratifying, and guiding the management of PCLs. Existing studies have provided important insight into the role of radiomics in managing PCLs. Although these studies are limited by the use of retrospective design, single center data, and small sample sizes, radiomic features in combination with clinical data appear to be superior to the current standard of care in differentiating cyst type and in identifying mucinous PCLs with high-grade dysplasia. Combining radiomic features with other novel endoscopic diagnostics, including cyst fluid molecular analysis and confocal endomicroscopy, can potentially optimize the predictive accuracy of these models. There is a need for multicenter prospective studies to elucidate the role of radiomics in the management of PCLs.

影像组学，也称为定量成像或纹理分析，包括提取大量传统上在常规放射学横断面图像中未测量的特征，并将它们转化为数学模型。这篇综述描述了这种方法及其在胰腺囊性病变（PCLs）评估中的应用。该学科有可能更准确地对PCLs进行评估、分类、风险分层以及指导其治疗。现有研究对影像组学在PCLs管理中的作用提供了重要见解。尽管这些研究受到回顾性设计、单中心数据和小样本量的限制，但影像组学特征结合临床数据似乎在区分囊肿类型以及识别伴有高度异型增生的黏液性PCLs方面优于当前的标准治疗方法。将影像组学特征与其他新的内镜诊断方法（包括囊液分子分析和共聚焦内镜显微术）相结合，可能会优化这些模型的预测准确性。需要多中心前瞻性研究来阐明影像组学在PCLs管理中的作用。