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动态高时间分辨率 MRI 对呼吸模式的定量特征分析,以心肺症状负担对急性新冠后患者进行分层。

Quantitative Characterization of Respiratory Patterns on Dynamic Higher Temporal Resolution MRI to Stratify Postacute Covid-19 Patients by Cardiopulmonary Symptom Burden.

机构信息

Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, New York, USA.

Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.

出版信息

J Magn Reson Imaging. 2024 Dec;60(6):2459-2469. doi: 10.1002/jmri.29352. Epub 2024 Mar 14.

Abstract

BACKGROUND

Postacute Covid-19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking.

PURPOSE

To evaluate if quantitative characterization of respiratory pattern on free-breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden.

STUDY TYPE

Prospective analysis of retrospectively acquired data.

SUBJECTS

A total of 37 postacute Covid-19 patients (25 male; median [interquartile range (IQR)] age: 58 [42-64] years; median [IQR] days from acute infection: 335 [186-449]).

FIELD STRENGTH/SEQUENCE: 0.55 T/two-dimensional coronal true fast imaging with steady-state free precession (trueFISP) at higher temporal resolution.

ASSESSMENT

Patients were stratified into three groups based on presence of no (N = 11), 1 (N = 14), or ≥2 (N = 14) cardiopulmonary symptoms, assessed using a standardized symptom inventory within 1 month of MRI. An automated lung postprocessing workflow segmented each lung in each trueFISP image (temporal resolution 0.2 seconds) and respiratory curves were generated. Quantitative parameters were derived including tidal lung area, rates of inspiration and expiration, lung area coefficient of variability (CV), and respiratory incoherence (departure from sinusoidal pattern) were. Pulmonary function tests were recorded if within 1 month of MRI. Qualitative assessment of respiratory pattern and lung opacity was performed by three independent readers with 6, 9, and 23 years of experience.

STATISTICAL TESTS

Analysis of variance to assess differences in demographic, clinical, and quantitative MRI parameters among groups; univariable analysis and multinomial logistic regression modeling to determine features predictive of patient symptom status; Akaike information criterion to compare the quality of regression models; Cohen and Fleiss kappa (κ) to quantify inter-reader reliability. Two-sided 5% significance level was used.

RESULTS

Tidal area and lung area CV were significantly higher in patients with two or more symptoms than in those with one or no symptoms (area: 15.4 cm vs. 12.9 cm vs. 12.8 cm; CV: 0.072, 0.067, and 0.058). Respiratory incoherence was significantly higher in patients with two or more symptoms than in those with one or no symptoms (0.05 vs. 0.043 vs. 0.033). There were no significant differences in patient age (P = 0.19), sex (P = 0.88), lung opacity severity (P = 0.48), or pulmonary function tests (P = 0.35-0.97) among groups. Qualitative reader assessment did not distinguish between groups and showed slight inter-reader agreement (κ = 0.05-0.11).

DATA CONCLUSION

Quantitative respiratory pattern measures derived from dynamic higher-temporal resolution MRI have potential to stratify patients by symptom burden in a postacute Covid-19 cohort.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 3.

摘要

背景

急性新冠病毒感染后患者常出现呼吸系统症状,但缺乏一种非侵入性的呼吸模式定量分析影像学方法。

目的

评估自由呼吸下更高时间分辨率 MRI 上呼吸模式的定量特征是否可根据心肺症状负担对患者进行分层。

研究类型

回顾性数据分析前瞻性研究。

受试者

共纳入 37 例急性新冠病毒感染后患者(25 名男性;中位[四分位间距(IQR)]年龄:58[42-64]岁;中位[IQR]自急性感染后时间:335[186-449]天)。

磁场强度/序列:0.55T/二维冠状位真实稳态自由进动(trueFISP)高时间分辨率。

评估

在 MRI 后 1 个月内,使用标准化症状清单评估患者是否存在无(N=11)、1(N=14)或≥2 种(N=14)心肺症状,并根据该评分将患者分为三组。自动肺后处理工作流程对每个 trueFISP 图像(时间分辨率 0.2 秒)中的每个肺进行分割,并生成呼吸曲线。生成的定量参数包括潮气量、吸气和呼气率、肺面积变异系数(CV)和呼吸不规则(偏离正弦模式)。如果在 MRI 后 1 个月内记录了肺功能检查。三位具有 6、9 和 23 年经验的独立读者对呼吸模式和肺不张的质量进行了定性评估。

统计学方法

方差分析用于评估组间人口统计学、临床和定量 MRI 参数的差异;单变量分析和多项逻辑回归模型用于确定预测患者症状状态的特征;赤池信息量准则用于比较回归模型的质量;Cohen 和 Fleiss κ(κ)用于量化读者间的可靠性。采用双侧 5%显著水平。

结果

存在 2 种或以上症状的患者的潮气量和肺面积 CV 明显高于存在 1 种或无症状的患者(面积:15.4cm 比 12.9cm 比 12.8cm;CV:0.072、0.067 和 0.058)。存在 2 种或以上症状的患者的呼吸不规则明显高于存在 1 种或无症状的患者(0.05 比 0.043 比 0.033)。组间患者年龄(P=0.19)、性别(P=0.88)、肺不张严重程度(P=0.48)或肺功能检查(P=0.35-0.97)无显著差异。定性读者评估未能区分组间差异,且显示出轻微的读者间一致性(κ=0.05-0.11)。

数据结论

急性新冠病毒感染后患者自由呼吸下更高时间分辨率 MRI 上的呼吸模式定量分析可能有潜力根据心肺症状负担对患者进行分层。

证据水平

3 级技术功效:3 级。

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Breathing patterns recognition: A functional data analysis approach.呼吸模式识别:一种功能数据分析方法。
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