The value of phase-resolved functional lung MRI in the quantitative assessment of pulmonary perfusion and ventilation defects in restrictive ventilatory dysfunction
10.3760/cma.j.cn112149-20250205-00065
- VernacularTitle:相位分辨功能性肺MRI定量评估限制性通气功能障碍肺灌注/通气缺损的价值
- Author:
Tao OUYANG
1
;
Hongjie CAO
1
;
Qi YANG
1
Author Information
1. 首都医科大学附属北京朝阳医院放射介入影像中心，北京100020
- Publication Type:Journal Article
- Keywords:
Magnetic resonance imaging;
Lung diseases;
Restrictive ventilatory dysfunction;
Perfusion defects;
Ventilation defects
- From:
Chinese Journal of Radiology
2025;59(7):757-764
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the value of phase-resolved functional lung MRI (PREFUL-MRI) in identifying pulmonary perfusion and ventilation defects in patients with restrictive ventilatory dysfunction (RVD).Methods:This study was a cross-sectional study. Participants were prospectively enrolled from March 2023 to July 2024 at Beijing Chaoyang Hospital, Capital Medical University, where they underwent pulmonary function testing [indicators including first second forced expiratory volume (FEV 1), forced vital capacity(FVC), FVC percent predicted(FVC%pred), FEV 1 percent predicted(FEV 1%pred),et al] and low-dose CT examinations. Based on pulmonary function results, all participants were divided into an RVD group and a control group. The RVD group was further subdivided into a mild RVD subgroup (FEV 1%pred≥70%) and a moderate-to-severe RVD subgroup (FEV 1%pred<70%). All participants underwent PREFUL-MRI examination. Quantitative lung perfusion parameters were measured, including perfusion quantified (Q Quantified) and perfusion defect percentage (QDP). Ventilation parameters were also acquired, including regional ventilation (RVent), flow-volume loop correlation metric (FVL-CM), and ventilation defect percentages (VDP RVent and VDP FVL-CM). Comparisons of continuous variables between groups were performed using the Mann-Whitney U test, while categorical variables were compared using the χ2 test or Fisher′s exact test. Spearman correlation analysis was used to assess the relationships between pulmonary function parameters and lung perfusion and ventilation parameters. Variables showing statistically significant differences between the RVD and control groups, or between the mild and moderate-to-severe RVD subgroups in univariate analyses, were included in multivariate binary logistic regression analysis to identify independent risk factors for the occurrence of RVD and moderate-to-severe RVD, and predictive models were constructed. The predictive performance of the models was evaluated using receiver operating characteristic curves and the area under the curve (AUC). Results:A total of 37 patients were included in the RVD group (23 males and 14 females), with a median age of 59 (52, 75)years. Among them, 18 had mild RVD and 19 had moderate-to-severe RVD. The control group consisted of 49 individuals (39 males and 10 females), with a median age of 55(46.5, 60) years. The RVD group had lower FEV 1%pred, FVC%pred, and Q Quantified, and higher RVent and QDP compared to the control group ( P<0.05). The moderate-to-severe RVD subgroup had lower FEV 1%pred, FVC%pred, and Q Quantified, and higher RVent and QDP than the mild RVD subgroup ( P<0.05). In the RVD group, FEV 1%pred and FVC%pred showed significant positive correlations with RVent and Q Quantified, and significant negative correlations with QDP ( P<0.05). The FEV 1/FVC ratio was positively correlated with RVent and FVL-CM, and negatively correlated with VDP RVent, VDP FVL-CM, and QDP ( P<0.05). Logistic regression analysis revealed that Q Quantified ( OR=0.97, 95% CI 0.94-0.99, P=0.005) and QDP ( OR=1.23, 95% CI 1.07-1.41, P=0.003) were independent predictors of RVD, and the AUC of the predictive model was 0.823. QDP ( OR=1.23, 95% CI 1.07-1.41, P=0.003) was identified as an independent predictor of moderate-to-severe RVD, with the model achieving an AUC of 0.825. Conclusions:PREFUL-MRI facilitates the noninvasive assessment of pulmonary perfusion abnormalities in RVD. The quantitative perfusion parameter serves as a valuable biomarker for detecting RVD and evaluating its severity, offering a novel tool for both pathophysiological research and clinical assessment.
