Silva Mario, Milanese Gianluca, Seletti Valeria, Ariani Alarico, Sverzellati Nicola
1 Department of Medicine and Surgery (DiMeC), Section of Radiology, Unit of Surgical Sciences, University of Parma , Parma , Italy.
2 Department of Medicine, Internal Medicine and Rheumatology Unit, University Hospital of Parma , Parma , Italy.
Br J Radiol. 2018 Feb;91(1083):20170644. doi: 10.1259/bjr.20170644. Epub 2018 Jan 12.
The frenetic development of imaging technology-both hardware and software-provides exceptional potential for investigation of the lung. In the last two decades, CT was exploited for detailed characterization of pulmonary structures and description of respiratory disease. The introduction of volumetric acquisition allowed increasingly sophisticated analysis of CT data by means of computerized algorithm, namely quantitative CT (QCT). Hundreds of thousands of CTs have been analysed for characterization of focal and diffuse disease of the lung. Several QCT metrics were developed and tested against clinical, functional and prognostic descriptors. Computer-aided detection of nodules, textural analysis of focal lesions, densitometric analysis and airway segmentation in obstructive pulmonary disease and textural analysis in interstitial lung disease are the major chapters of this discipline. The validation of QCT metrics for specific clinical and investigational needs prompted the translation of such metrics from research field to patient care. The present review summarizes the state of the art of QCT in both focal and diffuse lung disease, including a dedicated discussion about application of QCT metrics as parameters for clinical care and outcomes in clinical trials.
成像技术(包括硬件和软件)的迅猛发展为肺部研究提供了巨大潜力。在过去二十年中,CT被用于详细表征肺部结构和描述呼吸系统疾病。容积采集技术的引入使得通过计算机算法(即定量CT,QCT)对CT数据进行越来越复杂的分析成为可能。为了表征肺部的局灶性和弥漫性疾病,已经对数以十万计的CT进行了分析。开发了几种QCT指标,并针对临床、功能和预后描述符进行了测试。计算机辅助结节检测、局灶性病变的纹理分析、密度测定分析以及阻塞性肺病中的气道分割和间质性肺病中的纹理分析是该学科的主要内容。针对特定临床和研究需求对QCT指标进行验证,促使这些指标从研究领域转化为患者护理应用。本综述总结了QCT在局灶性和弥漫性肺病中的最新进展,包括专门讨论将QCT指标用作临床试验中临床护理和结果参数的应用情况。