دورية أكاديمية
CT-Derived Deep Learning- Based Quantification of Body Composition Associated with Disease Severity in Chronic Obstructive Pulmonary Disease
| العنوان: | CT-Derived Deep Learning- Based Quantification of Body Composition Associated with Disease Severity in Chronic Obstructive Pulmonary Disease |
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| المؤلفون: | Jae Eun Song, So Hyeon Bak, Myoung-Nam Lim, Eun Ju Lee, Yoon Ki Cha, Hyun Jung Yoon, Woo Jin Kim |
| المصدر: | Journal of the Korean Society of Radiology, Vol 84, Iss 5, Pp 1123-1133 (2023) |
| بيانات النشر: | The Korean Society of Radiology, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Medical physics. Medical radiology. Nuclear medicine |
| مصطلحات موضوعية: | multidetector computed tomography, chronic obstructive pulmonary disease, deep learning, muscle, Medical physics. Medical radiology. Nuclear medicine, R895-920 |
| الوصف: | Purpose Our study aimed to evaluate the association between automated quantified body composition on CT and pulmonary function or quantitative lung features in patients with chronic obstructive pulmonary disease (COPD). Materials and Methods A total of 290 patients with COPD were enrolled in this study. The volume of muscle and subcutaneous fat, area of muscle and subcutaneous fat at T12, and bone attenuation at T12 were obtained from chest CT using a deep learning-based body segmentation algorithm. Parametric response mapping-derived emphysema (PRMemph), PRM-derived functional small airway disease (PRMfSAD), and airway wall thickness (AWT)-Pi10 were quantitatively assessed. The association between body composition and outcomes was evaluated using Pearson’s correlation analysis. Results The volume and area of muscle and subcutaneous fat were negatively associated with PRMemph and PRMfSAD (p < 0.05). Bone density at T12 was negatively associated with PRMemph (r = -0.1828, p = 0.002). The volume and area of subcutaneous fat and bone density at T12 were positively correlated with AWT-Pi10 (r = 0.1287, p = 0.030; r = 0.1668, p = 0.005; r = 0.1279, p = 0.031). However, muscle volume was negatively correlated with the AWT-Pi10 (r = -0.1966, p = 0.001). Muscle volume was significantly associated with pulmonary function (p < 0.001). Conclusion Body composition, automatically assessed using chest CT, is associated with the phenotype and severity of COPD. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English Korean |
| تدمد: | 2951-0805 |
| Relation: | https://doaj.org/toc/2951-0805 |
| DOI: | 10.3348/jksr.2022.0152 |
| URL الوصول: | https://doaj.org/article/40df6999195d4b6cbdc92572d36b10ae |
| رقم الأكسشن: | edsdoj.40df6999195d4b6cbdc92572d36b10ae |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 29510805 |
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| DOI: | 10.3348/jksr.2022.0152 |