CT-derived Biomechanical Metrics Improve Agreement Between Spirometry and Emphysema

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• 作者：Surya P. Bhatt ; MD^a ; ^b ; ^&dagger ; ; ^{spbhatt@uab.edu" class="auth_mail" title="E-mail the corresponding author} ; Sandeep Bodduluri ; MS^c ; ^&dagger ; ; John D. Newell ; MD^c ; Eric A. Hoffman ; PhD^c ; Jessica C. Sieren ; PhD^c ; Meilan K. Han ; MD ; MS^d ; Mark T. Dransfield ; MD^a ; ^b ; Joseph M. Reinhardt ; PhD^c ; for the COPDGene Investigators
• 关键词：Emphysema ; spirometry ; COPD ; discordance
• 刊名：Academic Radiology
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：23
• 期：10
• 页码：1255-1263
• 全文大小：561 K

文摘

Many patients with chronic obstructive pulmonary disease (COPD) have marked discordance between forced expiratory volume in 1 second (FEV₁) and degree of emphysema on computed tomography (CT). Biomechanical differences between these patients have not been studied. We aimed to identify reasons for the discordance between CT and spirometry in some patients with COPD.

Materials and Methods

Subjects with Global initiative for chronic Obstructive Lung Disease stages I–IV from a large multicenter study (The Genetic Epidemiology of COPD) were arranged by percentiles of %predicted FEV₁ and emphysema on CT. Three categories were created using differences in percentiles: Cat_spir with predominant airflow obstruction/minimal emphysema, Cat_CT with predominant emphysema/minimal airflow obstruction, and Cat_matched with matched FEV₁ and emphysema. Image registration was used to derive Jacobian determinants, a measure of lung elasticity, anisotropy, and strain tensors, to assess biomechanical differences between groups. Regression models were created with the previously mentioned categories as outcome variable, adjusting for demographics, scanner type, quantitative CT-derived emphysema, gas trapping, and airway thickness (model 1), and after adding biomechanical CT metrics (model 2).

Results

Jacobian determinants, anisotropy, and strain tensors were strongly associated with FEV₁. With Cat_matched as control, model 2 predicted Cat_spir and Cat_CT better than model 1 (Akaike information criterion 255.8 vs. 320.8). In addition to demographics, the strongest independent predictors of FEV₁ were Jacobian mean (β = 1.60,95%confidence intervals [CI] = 1.16 to 1.98; P < 0.001), coefficient of variation (CV) of Jacobian (β = 1.45,95%CI = 0.86 to 2.03; P < 0.001), and CV of strain (β = 1.82,95%CI = 0.68 to 2.95; P = 0.001). CVs of Jacobian and strain are both potential markers of biomechanical lung heterogeneity.

Conclusions

CT-derived measures of lung mechanics improve the link between quantitative CT and spirometry, offering the potential for new insights into the linkage between regional parenchymal destruction and global decrement in lung function in patients with COPD.