用超极化 129Xenon 磁共振成像量化多种肺部疾病中通气缺陷的空间分布。

IF 4.3 3区材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-10-22 DOI:10.1002/jmri.29627

Abdullah S Bdaiwi, Matthew M Willmering, Jason C Woods, Laura L Walkup, Zackary I Cleveland

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引用次数: 0

摘要

背景：超极化129Xe磁共振成像评估肺通气，通常使用通气缺陷百分比（VDP）。与 VDP 不同，缺陷分布指数（DDI）可量化缺陷的空间集群。目的：使用 DDI 量化 129Xe 通气缺陷在不同肺部疾病中的空间分布：研究类型：回顾性研究：研究对象： 421 名受试者（年龄 = 23.1 ± 17.1，女性=230），包括健康对照组（N=60）和患有阻塞性疾病（哮喘[N=25]，支气管炎闭塞综合征[BOS，N=18]，囊性纤维化[CF，N=90]，淋巴管瘤病[LAM，N=50]）、限制性疾病（博来霉素治疗的癌症幸存者[BLEO，N=14]；纤维化肺病 [FLD，N = 92]）、骨髓移植（BMT，N = 53）和支气管肺发育不良（BPD，N = 19）。场强/序列：3T，二维多层梯度回波：从 DDI 图中提取全肺平均 DDI；与 VDP（像素百分比 1）、FVC 和 FEV1/FVC 相关。对不同疾病的 DDI 和 DDI/VDP （缺陷集群的标记）进行比较：皮尔逊相关分析和 Kruskal-Wallis 检验。P 结果与对照组（1.8 ± 3.1）相比，DDI在BMT（8.3 ± 11.5）、BOS（30.1 ± 57.5）、BPD（16.0 ± 46.8）、CF（15.4 ± 27.2）和LAM（12.6 ± 34.2）中明显升高。除 BLEO 外，DDI 与所有组的 VDP 都有明显相关性（r ≥ 0.56），与 CF、FLD 和 LAM 的 PFTs 也有明显相关性（r ≥ 0.56）。阻塞性组的平均 DDI（14.0 ± 32.0）明显高于对照组（1.8 ± 3.0）和限制性组（4.0 ± 12.0）。限制性组的 DDI/VDP（0.6 ± 0.6）明显低于对照组（0.8 ± 0.6）和阻塞性组（1.0 ± 1.0）：数据结论：DDI可帮助了解通气缺陷在不同疾病中的分布情况。

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Quantifying Spatial Distribution of Ventilation Defects in Multiple Pulmonary Diseases With Hyperpolarized ¹²⁹Xenon MRI.

Background: Hyperpolarized ¹²⁹Xe MRI assesses lung ventilation, often using the ventilation defect percentage (VDP). Unlike VDP, defect distribution index (DDI) quantifies spatial clustering of defects.

Purpose: To quantify spatial distribution of ¹²⁹Xe ventilation defects using DDI across pulmonary diseases.

Study type: Retrospective.

Subjects: Four hundred twenty-one subjects (age = 23.1 ± 17.1, female = 230), comprising healthy controls (N = 60) and subjects with obstructive conditions (asthma [N = 25], bronchiolitis obliterans syndrome [BOS, N = 18], cystic fibrosis [CF, N = 90], lymphangioleiomyomatosis [LAM, N = 50]), restrictive conditions (bleomycin-treated cancer survivors [BLEO, N = 14]; fibrotic lung diseases [FLD, N = 92]), bone marrow transplantation (BMT, N = 53), and bronchopulmonary dysplasia (BPD, N = 19).

Field strength/sequence: 3 T, two-dimensional multi-slice gradient echo.

Assessment: Whole-lung mean DDI was extracted from DDI maps; correlated with VDP (percent of pixels <60% of whole-lung mean signal intensity) and pulmonary function tests (PFTs) including FEV₁, FVC, and FEV₁/FVC. DDI and DDI/VDP, a marker of defect clustering, were compared across diseases.

Statistical tests: Pearson correlation analysis and Kruskal-Wallis tests. P < 0.0056 for disease groups, P < 0.0125 for categories.

Results: DDI was significantly elevated in BMT (8.3 ± 11.5), BOS (30.1 ± 57.5), BPD (16.0 ± 46.8), CF (15.4 ± 27.2), and LAM (12.6 ± 34.2) compared to controls (1.8 ± 3.1). DDI correlated significantly with VDP in all groups (r ≥ 0.56) except BLEO, and with PFTs in CF, FLD, and LAM (r ≥ 0.56). Obstructive groups had significantly higher mean DDI (14.0 ± 32.0) than controls (1.8 ± 3.0) and restrictive groups (4.0 ± 12.0). DDI/VDP was significantly lower in the restrictive group (0.6 ± 0.6) than controls (0.8 ± 0.6) and obstructive group (1.0 ± 1.0).

Data conclusion: DDI may provide insights into the distribution of ventilation defects across diseases.

Evidence level: 3 TECHNICAL EFFICACY: Stage 2.

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