Sica Giacomo, D'Agnano Vito, Bate Simon Townend, Romano Federica, Viglione Vittorio, Franzese Linda, Scaglione Mariano, Tamburrini Stefania, Reginelli Alfonso, Perrotta Fabio
Radiology Unit, Monaldi Hospital, A.O. dei Colli, 80131 Naples, Italy.
Department of Translational Medical Sciences, University of Campania "L. Vanvitelli", 80131 Naples, Italy.
Diagnostics (Basel). 2025 Jan 24;15(3):278. doi: 10.3390/diagnostics15030278.
Interstitial lung diseases (ILDs) are a heterogeneous group of pulmonary disorders characterised by variable degrees of inflammation, interstitial thickening, and fibrosis leading to distortion of the pulmonary architecture and gas exchange impairment. There are approximately 200 different entities in this category. ILDs are commonly classified based on several criteria, including causes, clinical features, and radiological patterns. Chest HRCT is the gold standard for the recognition of lung alteration patterns underlying interstitial lung diseases (ILDs), diagnosing specific patterns, and evaluating radiologic progression. Methods based on artificial intelligence (AI) may be used in computational medicine, especially in image-based specialties such as radiology. The evolving field of radiomics offers a unique and non-invasive approach to extracting quantitative information from medical images, particularly high-resolution computed tomography (HRCT) scans. This comprehensive review explores the burgeoning role of radiomics in unravelling the intricacies of interstitial lung disease. It focuses on its potential applications in diagnosis, prognostication, and treatment response evaluation.
间质性肺疾病（ILDs）是一组异质性肺部疾病，其特征是不同程度的炎症、间质增厚和纤维化，导致肺结构扭曲和气体交换受损。这一类别中约有200种不同的疾病实体。ILDs通常根据多种标准进行分类，包括病因、临床特征和放射学模式。胸部高分辨率计算机断层扫描（HRCT）是识别间质性肺疾病（ILDs）潜在肺部改变模式、诊断特定模式以及评估放射学进展的金标准。基于人工智能（AI）的方法可用于计算医学，尤其是在放射学等基于图像的专业领域。不断发展的放射组学领域提供了一种独特的非侵入性方法，可从医学图像中提取定量信息，特别是高分辨率计算机断层扫描（HRCT）扫描。这篇综述探讨了放射组学在揭示间质性肺疾病复杂性方面日益重要的作用。它重点关注其在诊断、预后和治疗反应评估中的潜在应用。
