Functional Impairment in Small Airways Associated With the Breathlessness Symptoms in Long-Coronavirus Disease.

IF 2 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Journal of Thoracic Imaging Pub Date : 2024-03-01 Epub Date: 2023-10-09 DOI:10.1097/RTI.0000000000000748
Minsuok Kim, Jeongeun Hwang, James T Grist, Gabriele Abueid, Soon Ho Yoon, Vicente Grau, Emily Fraser, Fergus V Gleeson
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Abstract

Purpose: This study aimed to determine the association between functional impairment in small airways and symptoms of dyspnea in patients with Long-coronavirus disease (COVID), using imaging and computational modeling analysis.

Patients and methods: Thirty-four patients with Long-COVID underwent thoracic computed tomography and hyperpolarized Xenon-129 magnetic resonance imaging (HP Xe MRI) scans. Twenty-two answered dyspnea-12 questionnaires. We used a computed tomography-based full-scale airway network (FAN) flow model to simulate pulmonary ventilation. The ventilation distribution projected on a coronal plane and the percentage lobar ventilation modeled in the FAN model were compared with the HP Xe MRI data. To assess the ventilation heterogeneity in small airways, we calculated the fractal dimensions of the impaired ventilation regions in the HP Xe MRI and FAN models.

Results: The ventilation distribution projected on a coronal plane showed an excellent resemblance between HP Xe MRI scans and FAN models (structure similarity index: 0.87 ± 0.04). In both the image and the model, the existence of large clustered ventilation defects was not identifiable regardless of dyspnea severity. The percentage lobar ventilation of the HP Xe MRI and FAN model showed a strong correlation (ρ = 0.63, P < 0.001). The difference in the fractal dimension of impaired ventilation zones between the low and high dyspnea-12 score groups was significant (HP Xe MRI: 1.97 [1.89 to 2.04] and 2.08 [2.06 to 2.14], P = 0.005; FAN: 2.60 [2.59 to 2.64] and 2.64 [2.63 to 2.65], P = 0.056).

Conclusions: This study has identified a potential association of small airway functional impairment with breathlessness in Long-COVID, using fractal analysis of HP Xe MRI scans and FAN models.

小型航空公司的功能损害和长期冠状病毒疾病的呼吸困难症状有关。
目的:本研究旨在通过成像和计算建模分析,确定长期冠状病毒病(COVID)患者小气道功能损伤与呼吸困难症状之间的关系。患者和方法:34名Long COVID患者接受了胸部计算机断层扫描和超极化Xenon-129磁共振成像(HP Xe MRI)扫描。22人回答了12项运动障碍问卷。我们使用基于计算机断层扫描的全尺寸气道网络(FAN)流量模型来模拟肺通气。将冠状面上投影的通气分布和FAN模型中建模的肺叶通气百分比与HP Xe MRI数据进行比较。为了评估小气道的通气异质性,我们计算了HP Xe MRI和FAN模型中受损通气区域的分形维数。结果:投影在冠状面上的通气分布显示,HP Xe MRI扫描与FAN模型非常相似(结构相似指数:0.87±0.04)。在图像和模型中,无论呼吸困难的严重程度如何,都无法识别是否存在大型聚集性通气缺陷。HP Xe MRI和FAN模型的肺叶通气百分比显示出很强的相关性(ρ=0.63,P<0.001)。低和高呼吸困难12分组之间通气受损区的分形维数差异显著(HP Xe MRI:1.97[1.89至2.04]和2.08[2.06至2.14],P=0.005;FAN:2.60[2.59至2.64]和2.64[2.63至2.65],P=0.056)这项研究通过对HP Xe MRI扫描和FAN模型的分形分析,确定了长期新冠肺炎患者小气道功能损伤和呼吸困难的潜在关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Thoracic Imaging
Journal of Thoracic Imaging 医学-核医学
CiteScore
7.10
自引率
9.10%
发文量
87
审稿时长
6-12 weeks
期刊介绍: Journal of Thoracic Imaging (JTI) provides authoritative information on all aspects of the use of imaging techniques in the diagnosis of cardiac and pulmonary diseases. Original articles and analytical reviews published in this timely journal provide the very latest thinking of leading experts concerning the use of chest radiography, computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and all other promising imaging techniques in cardiopulmonary radiology. Official Journal of the Society of Thoracic Radiology: Japanese Society of Thoracic Radiology Korean Society of Thoracic Radiology European Society of Thoracic Imaging.
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