Quantitative Computed Tomography Imaging of Interstitial Lung Diseases
Quantitative Computed Tomography Imaging of Interstitial Lung Diseases
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DOI：
10.1097/rti.0b013e3182a21969
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发表时间：
2013-09-01
影响因子：
3.3
通讯作者：
Robb, Richard A.
中科院分区：
文献类型：
--
作者：
Bartholmai, Brian J.;Raghunath, Sushravya;Robb, Richard A.
目的：高分辨率胸部CT(HRCT)对间质性肺疾病的定性诊断具有重要意义。某些疾病的HRCT表现可作为诊断依据。HRCT纵向监测可以评估间质性肺疾病的进展；然而，异常体积和特征的细微变化可能很难评估。诊断的准确性取决于放射科医生、病理学家或临床医生的专业知识和经验。胸部HRCT的定量分析有可能重复性地确定疾病的程度，分类异常类型，并使诊断过程自动化。材料和方法：利用直方图特征来表征肺实质的新型软件被用于分析胸部HRCT数据，包括对临床CT扫描和来自肺组织研究联盟的研究数据的回顾处理。其他信息包括生理学、病理学和半定量的放射科医生评估，以允许将定量结果与疾病的目测估计、生理参数和疾病结果的测量进行比较。结果：定量分析结果以区域体积提供，用于统计分析和图形表示。这些结果表明，HRCT定量分析可以作为一种具有生理、病理和预后意义的生物标志物。结论：HRCT定量分析有可能在临床实践中作为一种辅助手段，帮助确定可能的诊断，对早期疾病进行预后分层，并一致地判断疾病的进展或治疗反应。进一步优化定量技术和对特征明确的受试者进行纵向分析将有助于验证这些方法。
Purpose: High-resolution chest computed tomography (HRCT) is essential in the characterization of interstitial lung disease. The HRCT features of some diseases can be diagnostic. Longitudinal monitoring with HRCT can assess progression of interstitial lung disease; however, subtle changes in the volume and character of abnormalities can be difficult to assess. Accuracy of diagnosis can be dependent on expertise and experience of the radiologist, pathologist, or clinician. Quantitative analysis of thoracic HRCT has the potential to determine the extent of disease reproducibly, classify the types of abnormalities, and automate the diagnostic process.Materials and Methods: Novel software that utilizes histogram signatures to characterize pulmonary parenchyma was used to analyze chest HRCT data, including retrospective processing of clinical CT scans and research data from the Lung Tissue Research Consortium. Additional information including physiological, pathologic, and semiquantitative radiologist assessment was available to allow comparison of quantitative results, with visual estimates of the disease, physiological parameters, and measures of disease outcome.Results: Quantitative analysis results were provided in regional volumetric quantities for statistical analysis and a graphical representation. These results suggest that quantitative HRCT analysis can serve as a biomarker with physiological, pathologic, and prognostic significance.Conclusions: It is likely that quantitative analysis of HRCT can be used in clinical practice as a means to aid in identifying a probable diagnosis, stratifying prognosis in early disease, and consistently determining progression of the disease or response to therapy. Further optimization of quantitative techniques and longitudinal analysis of well-characterized subjects would be helpful in validating these methods.