Durom Eveline, Yang Chanwoo, Mozaffaripour Ali, Matheson Alexander M, Eddy Rachel L, Svenningsen Sarah, Parraga Grace
Robarts Research Institute, Western University, London, Canada (E.D., C.Y., A.M., A.M.M., G.P.); School of Biomedical Engineering, Western University, London, Canada (E.D., A.M., G.P.).
Robarts Research Institute, Western University, London, Canada (E.D., C.Y., A.M., A.M.M., G.P.).
Acad Radiol. 2025 Aug;32(8):4893-4902. doi: 10.1016/j.acra.2025.04.030. Epub 2025 May 5.
Hyperpolarized Xe magnetic resonance imaging (MRI) provides a way to quantify ventilation heterogeneity as ventilation defect percent (VDP), calculated as the volume of unventilated lung volume normalized to the thoracic cavity volume. Currently used methods for quantifying VDP include (1) binary signal-intensity thresholds (Binary-threshold, BT), (2) Gaussian transformation of signal-intensity histogram with standard deviation thresholds or Gaussian-linear-binning (GLB), and (3) iterative centroid-based clustering of the signal-intensity histogram (k-means). These methods have not been directly compared in patients with asthma and chronic obstructive pulmonary disease (COPD), in whom ventilation defects are hallmark findings. Our objective was to quantify and compare VDP using these four different methods.
Data from 175 participants (n=42 healthy, n=43 COPD, n=90 asthma) were retrospectively evaluated using a CNN co-registration and segmentation pipeline and GLB, GLB, (slice-wise evaluation of GLB) BT and k-means VDP quantification methods. Linear-regression and Bland-Altman plots were used to quantify inter-method correlations and agreement.
VDP was significantly different using GLB (Asthma: 6±9%, COPD: 7±7%, p<.001) and BT (Asthma: 6±7%, COPD: 10±8%, p<.001) methods compared to GLB (Asthma: 12±13%, COPD: 16±15%, p<.001) and k-means (Asthma: 12±12%, COPD: 25±17%, p<.001). VDP calculated using GLB (R=.64, p<.001), GLB (R=.84, p<.001) and BT (R=.84, p<.001) was significantly correlated with k-means VDP. Bland-Altman plots revealed wide 95% confidence intervals of agreement for k-means with GLB/GLB (COPD -6%/-1%: 42%/23%; asthma -5%/-10%:16%/10%) and BT (COPD -4%:36%; asthma -6%:19%).
VDP differences in patients with asthma and COPD calculated using four methods are important to consider for multi-center studies.
超极化氙磁共振成像（MRI）提供了一种量化通气异质性的方法，即通气缺陷百分比（VDP），计算方法为未通气肺体积与胸腔体积的归一化比值。目前用于量化VDP的方法包括：（1）二元信号强度阈值法（Binary-threshold，BT）；（2）信号强度直方图的高斯变换，采用标准差阈值或高斯线性分箱法（Gaussian-linear-binning，GLB）；（3）基于信号强度直方图的迭代质心聚类法（k均值法）。在哮喘和慢性阻塞性肺疾病（COPD）患者中，通气缺陷是标志性表现，但这些方法尚未在这类患者中进行直接比较。我们的目的是使用这四种不同方法对VDP进行量化和比较。
使用CNN配准和分割流程以及GLB、GLB（GLB的逐切片评估）、BT和k均值VDP量化方法，对175名参与者（n = 42名健康者，n = 43名COPD患者，n = 90名哮喘患者）的数据进行回顾性评估。采用线性回归和布兰德 - 奥特曼图来量化方法间的相关性和一致性。
与GLB（哮喘：12±13%，COPD：16±15%，p <.001）和k均值法（哮喘：12±12%，COPD：25±17%，p <.001）相比，使用GLB（哮喘：6±9%，COPD：7±7%，p <.001）和BT（哮喘：6±7%，COPD：10±8%，p <.001）方法时，VDP有显著差异。使用GLB（R =.64，p <.001）、GLB（R =.84，p <.001）和BT（R =.84，p <.001）计算的VDP与k均值VDP显著相关。布兰德 - 奥特曼图显示，k均值法与GLB/GLB（COPD -6%/-1%：42%/23%；哮喘 -5%/-10%：16%/10%）和BT（COPD -4%：36%；哮喘 -6%：19%）的一致性95%置信区间较宽。
对于多中心研究，考虑哮喘和COPD患者使用四种方法计算的VDP差异很重要。
