Chau Ngan-Khanh, Park Eun-Kee, Choi Sanghun
School of Mechanical Engineering and IEDT, Kyungpook National University, Daegu, Republic of Korea.
An Giang University, Vietnam National University - Ho Chi Minh City, Ho Chi Minh, Vietnam.
Front Physiol. 2025 May 30;16:1578058. doi: 10.3389/fphys.2025.1578058. eCollection 2025.
Pneumoconiosis, caused by prolonged exposure to mineral dust, leads to progressive structural and functional lung alterations. Quantitative computed tomography (qCT) has emerged as a critical tool for assessing these changes, yet there is limited research on the longitudinal patterns in pneumoconiosis patients.
This study examined a cohort of 31 former coal workers with pneumoconiosis over a 1-year period. Inspiratory qCT images were enhanced using a deep learning-based super-resolution model and then processed to extract lung functional and airway structural metrics. A non-rigid image registration process was performed with baseline images as fixed and follow-up images as moving. Registration-derived metrics, including anisotropic deformation index (ADI), slab rod index (SRI), and Jacobian (J), were extracted to quantify regional deformation longitudinally. Pulmonary function tests, including forced expiratory volume in one second (FEV) and forced vital capacity (FVC), were recorded at both time points to assess functional decline.
The study identified significant airway changes in angles, diameters, and geometry, with a decrease in normal lung tissue in the right upper lobe. Blood vessel volumes declined, indicating vascular remodeling. Registration metrics revealed regional heterogeneity, with higher ADI and SRI values and localized volume loss (J) in the lower lobes. FEV/FVC progression correlated positively with tracheal angle, emphysema, and consolidation but negatively with normal lung tissue, semi-consolidation, and fibrosis. ADI, SRI, and J were associated with structural deformation, airway remodeling, and parenchymal loss, linking these changes to lung function decline.
qCT imaging and registration metrics effectively monitor structural and functional lung changes in pneumoconiosis. Registering baseline and follow-up inspiration images offers additionally valuable insights into disease progression.
长期接触矿物粉尘导致的尘肺病会引起肺部结构和功能的渐进性改变。定量计算机断层扫描(qCT)已成为评估这些变化的关键工具,但关于尘肺病患者纵向变化模式的研究有限。
本研究对31名患有尘肺病的 former coal workers 进行了为期1年的队列研究。吸气qCT图像使用基于深度学习的超分辨率模型进行增强,然后进行处理以提取肺功能和气道结构指标。以基线图像为固定图像、随访图像为移动图像进行非刚性图像配准。提取配准衍生指标,包括各向异性变形指数(ADI)、平板杆指数(SRI)和雅可比行列式(J),以纵向量化区域变形。在两个时间点记录肺功能测试,包括一秒用力呼气量(FEV)和用力肺活量(FVC),以评估功能下降情况。
该研究发现气道在角度、直径和几何形状方面有显著变化,右上叶正常肺组织减少。血管容积下降,表明血管重塑。配准指标显示区域异质性,下叶的ADI和SRI值较高且存在局部容积损失(J)。FEV/FVC进展与气管角度、肺气肿和实变呈正相关,但与正常肺组织、半实变和纤维化呈负相关。ADI、SRI和J与结构变形、气道重塑和实质损失相关,将这些变化与肺功能下降联系起来。
qCT成像和配准指标可有效监测尘肺病患者肺部的结构和功能变化。对基线和随访吸气图像进行配准可提供有关疾病进展的额外有价值的见解。