Same‐Day Repeatability and 28‐Day Reproducibility of Xenon MRI Ventilation in Children With Cystic Fibrosis in a Multi‐Site Trial

IF 3.3 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Journal of Magnetic Resonance Imaging Pub Date : 2024-09-11 DOI:10.1002/jmri.29605
Laura L. Walkup, David J. Roach, Joseph W. Plummer, Matthew M. Willmering, Brandon Zanette, Giles Santyr, Sean B. Fain, Michael J. Rock, Jaime Mata, Deborah Froh, Sanja Stanojevic, Zackary I. Cleveland, Felix Ratjen, Jason C. Woods
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Abstract

BackgroundMRI with xenon‐129 gas (Xe MRI) can assess airflow obstruction and heterogeneity in lung diseases. Specifically, Xe MRI may represent a sensitive modality for future therapeutic trials of cystic fibrosis (CF) therapies. The reproducibility of Xe MRI has not yet been assessed in the context of a multi‐site study.PurposeTo determine the same‐day repeatability and 28‐day reproducibility of Xe MRI in children with CF.Study TypeFour‐center prospective, longitudinal.PopulationThirty‐eight children (18 females, 47%), median interquartile range (IQR) age 12 (9–14) years old, with mild CF (forced expiratory volume in 1 second (FEV1) ≥85% predicted).Field Strength/Sequence3‐T, two‐dimensional (2D) gradient‐echo (GRE) sequence.AssessmentXe MRI, FEV1, and nitrogen multiple‐breath wash‐out for lung‐clearance index (LCI2.5) were performed. To assess same‐day reproducibility, Xe MRI was performed twice within the first visit, and procedures were repeated at 28 days. Xe hypoventilation was quantified using ventilation‐defect percentage (VDP) and reader‐defect volume (RDV). For VDP, hypoventilated voxels from segmented images were identified using a threshold of <60% mean whole‐lung signal and expressed as a percentage of the lung volume. For RDV, hypoventilation was identified by two trained readers and expressed as a percentage.Statistical TestsInter‐site comparisons were conducted using Kruskal–Wallis nonparametric tests with Dunn's multiple‐comparisons tests. Differences for individuals were assessed using Wilcoxon matched‐pairs tests. Bland–Altman tests were used to evaluate same‐day repeatability, 28‐day reproducibility, and inter‐reader agreement. A P‐value ≤0.05 was considered significant.ResultsMedian FEV1 %‐predicted was 96.8% (86%–106%), and median LCI2.5 was 6.6 (6.3–7.4). Xe MRI had high same‐day reproducibility (mean VDP difference 0.12%, 95% limits of agreement [−3.2, 3.4]; mean RDV difference 0.42% [−2.5, 3.3]). At 28 days, 26/31 participants (84%) fell within the same‐day 95% limits of agreement.Data ConclusionXe MRI may offer excellent same‐day and short‐term reproducibility.Evidence Level2Technical EfficacyStage 2
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多站点试验中囊性纤维化儿童氙磁共振通气的当日重复性和 28 天重复性
背景使用氙-129 气体进行磁共振成像(Xe MRI)可评估肺部疾病的气流阻塞和异质性。具体来说,Xe MRI可能是未来囊性纤维化(CF)治疗试验的一种敏感模式。研究类型四个中心的前瞻性纵向研究。研究对象38名儿童(18名女性,47%),中位数四分位数(IQR)年龄为12(9-14)岁,患有轻度CF(1秒内用力呼气容积(FEV1)≥85%预测值)。评估方法进行Xe MRI、FEV1和氮气多次呼吸冲洗肺通气指数(LCI2.5)。为了评估当天的可重复性,在首次就诊时进行了两次 Xe MRI,并在 28 天后重复了这些程序。Xe通气不足采用通气缺陷百分比(VDP)和阅读器缺陷体积(RDV)进行量化。对于 VDP,使用平均全肺信号 60% 的阈值从分割图像中识别通气不足的体素,并以肺容积的百分比表示。统计检验采用 Kruskal-Wallis 非参数检验和 Dunn's 多重比较检验进行站间比较。个体差异采用 Wilcoxon 配对检验进行评估。使用 Bland-Altman 检验来评估同日重复性、28 天重复性和读数者之间的一致性。结果中位 FEV1 预测值为 96.8%(86%-106%),中位 LCI2.5 为 6.6(6.3-7.4)。Xe MRI 的当日重现性很高(平均 VDP 差异为 0.12%,95% 的一致性范围 [-3.2, 3.4];平均 RDV 差异为 0.42% [-2.5, 3.3])。28 天时,26/31 名参与者(84%)的数据在当天 95% 的一致性范围内。
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来源期刊
CiteScore
9.70
自引率
6.80%
发文量
494
审稿时长
2 months
期刊介绍: The Journal of Magnetic Resonance Imaging (JMRI) is an international journal devoted to the timely publication of basic and clinical research, educational and review articles, and other information related to the diagnostic applications of magnetic resonance.
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Editorial for "Assessment the Impact of IDH Mutation Status on MRI Assessments of White Matter Integrity in Glioma Patients: Insights From Peak Width of Skeletonized Mean Diffusivity and Free Water Metrics". On the Origin of fMRI Species. Seizure Burden and Clinical Risk Factors in Glioma-Related Epilepsy: Insights From MRI Voxel-Based Lesion-Symptom Mapping. Issue Information Assessing the Performance of Artificial Intelligence Assistance for Prostate MRI: A Two-Center Study Involving Radiologists With Different Experience Levels.
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