Zhou Xingyu, Ye Chen, Iwao Yuma, Okamoto Takayuki, Kawata Naoko, Shimada Ayako, Haneishi Hideaki
Graduate School of Science and Engineering, Chiba University, Chiba 263-8522, Japan.
School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
Diagnostics (Basel). 2023 Oct 20;13(20):3261. doi: 10.3390/diagnostics13203261.
Chronic obstructive pulmonary disease (COPD) typically causes airflow blockage and breathing difficulties, which may result in the abnormal morphology and motion of the lungs or diaphragm. This study aims to quantitatively evaluate respiratory diaphragm motion using a thoracic sagittal magnetic resonance imaging (MRI) series, including motion asynchronization and limitations. First, the diaphragm profile is extracted using a deep-learning-based field segmentation approach. Next, by measuring the motion waveforms of each position in the extracted diaphragm profile, obvious differences in the independent respiration cycles, such as the period and peak amplitude, are verified. Finally, focusing on multiple breathing cycles, the similarity and amplitude of the motion waveforms are evaluated using the normalized correlation coefficient (NCC) and absolute amplitude. Compared with normal subjects, patients with severe COPD tend to have lower NCC and absolute amplitude values, suggesting motion asynchronization and limitation of their diaphragms. Our proposed diaphragmatic motion evaluation method may assist in the diagnosis and therapeutic planning of COPD.
慢性阻塞性肺疾病(COPD)通常会导致气流阻塞和呼吸困难,这可能会导致肺部或膈肌的形态和运动异常。本研究旨在使用胸部矢状面磁共振成像(MRI)系列定量评估呼吸膈肌运动,包括运动不同步和运动受限情况。首先,使用基于深度学习的场分割方法提取膈肌轮廓。接下来,通过测量提取的膈肌轮廓中每个位置的运动波形,验证独立呼吸周期中存在的明显差异,如周期和峰值幅度。最后,聚焦于多个呼吸周期,使用归一化相关系数(NCC)和绝对幅度评估运动波形的相似性和幅度。与正常受试者相比,重度COPD患者的NCC和绝对幅度值往往较低,提示其膈肌运动不同步和受限。我们提出的膈肌运动评估方法可能有助于COPD的诊断和治疗规划。