Robust, Standardized Quantification of Pulmonary Emphysema in Low Dose CT Exams

RATIONALE AND OBJECTIVES: The aim of this study was to present and evaluate a fully automated system for emphysema quantification on low-dose computed tomographic images. The platform standardizes emphysema measurements against changes in the reconstruction algorithm and slice thickness. MATERIALS AND METHODS: Emphysema was quantified in 149 patients using a fully automatic, in-house developed software (the Robust Automatic On-Line Pulmonary Helper). The accuracy of the system was evaluated against commercial software, and its reproducibility was assessed using pairs of volume-corrected images taken 1 year apart. Furthermore, to standardize quantifications, the effect of changing the reconstruction parameters was modeled using a nonlinear fit, and the inverse of the model function was then applied to the data. The association between quantifications and pulmonary function testing was also evaluated. The accuracy of the in-house software compared to that of commercial software was measured using Spearman's rank correlation coefficient, the mean difference, and the intrasubject variability. Agreement between the methods was studied using Bland-Altman plots. To assess the reproducibility of the method, intraclass correlation coefficients and Bland-Altman plots were used. The statistical significance of the differences between the standardized data and the reference data (soft-tissue reconstruction algorithm B40f; slice thickness, 1 mm) was assessed using a paired two-sample t test. RESULTS: The accuracy of the method, measured as intrasubject variability, was 3.86 mL for pulmonary volume, 0.01% for emphysema index, and 0.39 Hounsfield units for mean lung density. Reproducibility, assessed using the intraclass correlation coefficient, was >0.95 for all measurements. The standardization method applied to compensate for variations in the reconstruction algorithm and slice thickness increased the intraclass correlation coefficients from 0.87 to 0.97 and from 0.99 to 1.00, respectively. The correlation of the standardized measurements with pulmonary function testing parameters was similar to that of the reference (for the emphysema index and the obstructive subgroup: forced expiratory volume in 1 second, -0.647% vs -0.615%; forced expiratory volume in 1 second/forced vital capacity, -0.672% vs -0.654%; and diffusing capacity for carbon monoxide adjusted for hemoglobin concentration, -0.438% vs -0.523%). CONCLUSIONS: The new emphysema quantification method presented in this report is accurate and reproducible and, thanks to its standardization method, robust to changes in the reconstruction parameters

Pulmonary Structure and Function in Chronic Obstructive Pulmonary Disease Evaluated using Hyperpolarized Noble Gas Magnetic Resonance Imaging

Chronic obstructive pulmonary disease (COPD) is the 4th leading cause of death worldwide and accounts for the highest rate of hospital admissions in Canada. The need for sensitive regional and surrogate measurements of lung structure and function in COPD continues to motivate the development of non-radiation based and sensitive imaging approaches, such as hyperpolarized helium-3 (3He) and xenon-129 (129Xe) magnetic resonance imaging (MRI). The static ventilation images acquired using these approaches allows us to directly visualize lung regions accessed by the hyperpolarized gas during a breath-hold, as well as quantify the regions without signal referred to as the percentage of the thoracic cavity occupied by ventilation defects (VDP). The lung micro-structure can also be probed using diffusion-weighted imaging which takes advantage of the rapid diffusion of 3He and 129Xe atoms to generate surrogate measurements of alveolar size, referred to as the apparent diffusion coefficient (ADC). Here we evaluated COPD lung structure and function using hyperpolarized gas MRI measurements longitudinally, following treatment and in early disease. In COPD ex-smokers, we demonstrated 3He VDP and ADC worsened significantly in only 2 years although there was no change in age-matched healthy volunteers, suggestive of disease progression. We also evaluated COPD ex-smokers pre- and post-bronchodilator and showed regional improvements in gas distribution following bronchodilator therapy regardless of spirometry-based responder classification; the ADC measured in these same COPD ex-smokers also revealed significant reductions in regional gas trapping post-bronchodilator. Although 3He MRI has been more widely used, the limited global quantities necessitates the transition to hyperpolarized 129Xe, and therefore we directly compared 3He and 129Xe MRI in the same COPD ex-smokers and showed significantly greater gas distribution abnormalities for 129Xe compared to 3He MRI that were spatially and significantly related to lung regions with elevated ADC. Finally, we demonstrated that ex-smokers with normal spirometry but abnormal diffusion capacity of the lung for carbon monoxide (DLCO) had significantly worse symptoms, exercise capacity and 3He ADC than ex-smokers with normal DLCO. These important findings indicate that hyperpolarized gas MRI can be used to improve our understanding of lung structural and functional changes in COPD

Quantitative CT analysis in ILD and use of artificial intelligence on imaging of ILD

Advances in computer technology over the past decade, particularly in the field of medical image analysis, have permitted the identification, characterisation and quantitation of abnormalities that can be used to diagnose disease or determine disease severity. On CT imaging performed in patients with ILD, deep-learning computer algorithms now demonstrate comparable performance with trained observers in the identification of a UIP pattern, which is associated with a poor prognosis in several fibrosing ILDs. Computer tools that quantify individual voxel-level CT features have also come of age and can predict mortality with greater power than visual CT analysis scores. As these tools become more established, they have the potential to improve the sensitivity with which minor degrees of disease progression are identified. Currently, PFTs are the gold standard measure used to assess clinical deterioration. However, the variation associated with pulmonary function measurements may mask the presence of small but genuine functional decline, which in the future could be confirmed by computer tools. The current chapter will describe the latest advances in quantitative CT analysis and deep learning as related to ILDs and suggest potential future directions for this rapidly advancing field