Chen Zhennong, Contijoch Francisco, Kahn Andrew M, Kligerman Seth, Narayan Hari K, Manohar Ashish, McVeigh Elliot
Departments of Bioengineering (Z.C., F.C., E.M.) and Mechanical and Aerospace Engineering (A.M.), UC San Diego School of Engineering, La Jolla, Calif; and Departments of Radiology (F.C., S.K., E.M.), Cardiology (A.M.K., E.M.), and Pediatrics (H.K.N.), UC San Diego School of Medicine, 9452 Medical Dr, La Jolla, CA 92037.
Radiol Cardiothorac Imaging. 2023 Mar 9;5(2):e220134. doi: 10.1148/ryct.220134. eCollection 2023 Apr.
To investigate whether endocardial regional shortening computed from four-dimensional (4D) CT angiography (RS) can be used as a decision classifier to detect the presence of left ventricular (LV) wall motion abnormalities (WMAs).
One hundred electrocardiographically gated cardiac 4D CT studies (mean age, 59 years ± 14 [SD]; 61 male patients) conducted between April 2018 and December 2020 were retrospectively evaluated. Three experts labeled LV wall motion in each of the 16 American Heart Association (AHA) segments as normal or abnormal; they also measured peak RS across one heartbeat in each segment. The data set was split evenly into training and validation groups. During training, interchangeability of RS thresholding with experts to detect WMA was assessed using the individual equivalence index (γ), and an optimal threshold of the peak RS (RS*) that achieved maximum agreement was identified. RS* was then validated using the validation group, and the effect of AHA segment-specific thresholds was evaluated. Agreement was assessed using κ statistics.
The optimal threshold, RS* of -0.19, when applied to all AHA segments, led to high agreement (agreement rate = 92.17%, κ = 0.82) and interchangeability with experts (γ = -2.58%). The same RS* also achieved high agreement in the validation group (agreement rate = 90.29%, κ = 0.76, γ = -0.38%). The use of AHA segment-specific thresholds (range: 0.16 to -0.23 across AHA segments) slightly improved agreement (1.79% increase).
RS thresholding was interchangeable with expert visual analysis in detecting segmental WMA from 4D CT and may be used as an objective decision classifier. CT, Left Ventricle, Regional Endocardial Shortening, Wall Motion Abnormality © RSNA, 2023.
研究从四维（4D）CT血管造影术计算得出的心内膜区域缩短率（RS）能否用作检测左心室（LV）壁运动异常（WMA）的决策分类器。
回顾性评估2018年4月至2020年12月期间进行的100项心电图门控心脏4D CT研究（平均年龄59岁±14[标准差]；61例男性患者）。三位专家将16个美国心脏协会（AHA）节段中的每个节段的LV壁运动标记为正常或异常；他们还测量了每个节段一次心跳中的峰值RS。数据集被均匀分为训练组和验证组。在训练期间，使用个体等效指数（γ）评估RS阈值与专家检测WMA的互换性，并确定达到最大一致性的峰值RS（RS*）的最佳阈值。然后使用验证组对RS*进行验证，并评估AHA节段特异性阈值的效果。使用κ统计量评估一致性。
当应用于所有AHA节段时，最佳阈值RS为-0.19，导致高度一致性（一致率=92.17%，κ=0.82）以及与专家的互换性（γ=-2.58%）。相同的RS在验证组中也达到了高度一致性（一致率=90.29%，κ=0.76，γ=-0.38%）。使用AHA节段特异性阈值（范围：跨AHA节段为0.16至-0.23）略微提高了一致性（提高了1.79%）。
在从4D CT检测节段性WMA方面，RS阈值与专家视觉分析具有互换性，并且可以用作客观的决策分类器。CT，左心室，区域心内膜缩短，壁运动异常 ©RSNA，2023。
