The Russell H. Morgan Department of Radiology and Radiological Sciences, The Johns Hopkins University, Baltimore, Maryland, USA.
Department of Radiology, The University of Maryland School of Medicine, Baltimore, Maryland, USA.
J Magn Reson Imaging. 2024 May;59(5):1612-1619. doi: 10.1002/jmri.28923. Epub 2023 Jul 28.
Intracranial vessel tortuosity is a key component of dolichoectasia and has been associated with atherosclerosis and adverse neurologic outcomes. However, the evaluation of tortuosity is mainly a descriptive assessment.
To compare the performance of three automated tortuosity metrics (angle metric [AM], distance metric [DM], and distance-to-axis metric [DTA]) for detection of dolichoectasia and presence of segment-specific plaques.
Observational, cross-sectional metric assessment.
1899 adults from the general population; mean age = 76 years, female = 59%, and black = 29%.
FIELD STRENGTH/SEQUENCE: 3-T, three-dimensional (3D) time-of-flight MRA and 3D vessel wall MRI.
Tortuosity metrics and mean luminal area were quantified for designated segments of the internal carotid artery, middle cerebral artery, anterior cerebral artery, posterior cerebral artery, vertebral artery, and entire length of basilar artery (BA). Qualitative interpretations of BA dolichoectasia were assessed based on Smoker's visual criteria.
Descriptive statistics (2-sample t-tests, Pearson chi-square tests) for group comparisons. Receiver operating characteristics area under the curve (AUC) for detection of BA dolichoectasia or segment-specific plaque. Model inputs included 1) tortuosity metrics, 2) mean luminal area, and 3) demographics (age, race, and sex).
Qualitative dolichoectasia was identified in 336 (18%) participants, and atherosclerotic plaques were detected in 192 (10%) participants. AM-, DM-, and DTA-calculated tortuosity were good individual discriminators of basilar dolichoectasia (AUCs: 0.76, 0.74, and 0.75, respectively), with model performance improving with the mean lumen area: (AUCs: 0.88, 0.87, and 0.87, respectively). Combined characteristics (tortuosity and mean luminal area) identified plaques with better performance in the anterior (AUCs ranging from 0.66 to 0.78) than posterior (AUCs ranging from 0.54 to 0.65) circulation, with all models improving by the addition of demographics (AUCs ranging from 0.62 to 0.84).
Quantitative vessel tortuosity metrics yield good diagnostic accuracy for the detection of dolichoectasia.
1 TECHNICAL EFFICACY STAGE: 2.
颅内血管迂曲是梭形扩张的一个关键组成部分，与动脉粥样硬化和不良神经结局有关。然而，迂曲的评估主要是一种描述性评估。
比较三种自动迂曲度量（角度度量[AM]、距离度量[DM]和距离到轴度量[DTA]）在检测梭形扩张和存在节段性斑块方面的性能。
观察性、横截面度量评估。
来自普通人群的 1899 名成年人；平均年龄=76 岁，女性=59%，黑种人=29%。
场强/序列：3T、三维（3D）时间飞跃 MRA 和 3D 血管壁 MRI。
为颈内动脉、大脑中动脉、大脑前动脉、大脑后动脉、椎动脉和基底动脉（BA）全长指定节段量化迂曲度量和平均管腔面积。根据 Smoker 的视觉标准评估 BA 梭形扩张的定性解释。
组间比较的描述性统计（2 样本 t 检验，Pearson 卡方检验）。用于检测 BA 梭形扩张或节段性斑块的接收者操作特征曲线（AUC）。模型输入包括 1）迂曲度量，2）平均管腔面积和 3）人口统计学（年龄、种族和性别）。
336 名（18%）参与者存在定性梭形扩张，192 名（10%）参与者存在动脉粥样硬化斑块。AM、DM 和 DTA 计算的迂曲性是基底动脉梭形扩张的良好个体鉴别指标（AUC：分别为 0.76、0.74 和 0.75），随着平均管腔面积的增加，模型性能得到改善：（AUC：分别为 0.88、0.87 和 0.87）。组合特征（迂曲性和平均管腔面积）在前循环（AUC 范围为 0.66 至 0.78）中比后循环（AUC 范围为 0.54 至 0.65）中识别斑块的性能更好，所有模型通过添加人口统计学数据都有所改善（AUC 范围为 0.62 至 0.84）。
定量血管迂曲度量对梭形扩张的检测具有良好的诊断准确性。
1 技术功效阶段：2。
