Quantitative Analysis for Lung Disease on Thin-Section CT

Abstract

Thin-section computed tomography (CT) is widely employed not only for assessing morphology but also for evaluating respiratory function. Three-dimensional images obtained from thin-section CT provide precise measurements of lung, airway, and vessel volumes. These volumetric indices are correlated with traditional pulmonary function tests (PFT). CT also generates lung histograms. The volume ratio of areas with low and high attenuation correlates with PFT results. These quantitative image analyses have been utilized to investigate the early stages and disease progression of diffuse lung diseases, leading to the development of novel concepts such as pre-chronic obstructive pulmonary disease (pre-COPD) and interstitial lung abnormalities. Quantitative analysis proved particularly valuable during the COVID-19 pandemic when clinical evaluations were limited. In this review, we introduce CT analysis methods and explore their clinical applications in the context of various lung diseases. We also highlight technological advances, including images with matrices of 1024 × 1024 and slice thicknesses of 0.25 mm, which enhance the accuracy of these analyses.

High-Resolution Computed Tomography in Diagnosing and Monitoring Various Interstitial Lung Diseases

“…The observations of Li et al [14], Doshi et al [15], and Ebner et al [17] are consistent with the distribution of HRCT patterns among various ILD categories. The HRCT results for RA, polymyositis and dermatomyositis, systemic sclerosis, Sjögren syndrome, mixed connective tissue disorder, and systemic lupus erythematosus were published by Li et al [14,[18][19][20][21][22]. Our analysis is consistent with these categories, offering a thorough understanding of HRCT trends among different ILD kinds.…”