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CT 血管造影中 Viz LVO 与 Rapid LVO 对急性脑卒中大血管闭塞的检测。

Viz LVO versus Rapid LVO in detection of large vessel occlusion on CT angiography for acute stroke.

机构信息

Emergency Medicine, HCA Houston, Kingwood, Texas, USA.

Internal Medicine, HCA Houston, Kingwood, Texas, USA.

出版信息

J Neurointerv Surg. 2024 May 21;16(6):599-602. doi: 10.1136/jnis-2023-020445.

Abstract

BACKGROUND

Endovascular thrombectomy improves outcomes and reduces mortality for large vessel occlusion (LVO) and is time-sensitive. Computer automation may aid in the early detection of LVOs, but false values may lead to alarm desensitization. We compared Viz LVO and Rapid LVO for automated LVO detection.

METHODS

Data were retrospectively extracted from Rapid LVO and Viz LVO running concurrently from January 2022 to January 2023 on CT angiography (CTA) images compared with a radiologist interpretation. We calculated diagnostic accuracy measures and performed a McNemar test to look for a difference between the algorithms' errors. We collected demographic data, comorbidities, ejection fraction (EF), and imaging features and performed a multiple logistic regression to determine if any of these variables predicted the incorrect classification of LVO on CTA.

RESULTS

360 participants were included, with 47 large vessel occlusions. Viz LVO and Rapid LVO had a specificity of 0.96 and 0.85, a sensitivity of 0.87 and 0.87, a positive predictive value of 0.75 and 0.46, and a negative predictive value of 0.98 and 0.97, respectively. A McNemar test on correct and incorrect classifications showed a statistically significant difference between the two algorithms' errors (P=0.00000031). A multiple logistic regression showed that low EF (Viz P=0.00125, Rapid P=0.0286) and Modified Woodcock Score >1 (Viz P=0.000198, Rapid P=0.000000975) were significant predictors of incorrect classification.

CONCLUSION

Rapid LVO produced a significantly larger number of false positive values that may contribute to alarm desensitization, leading to missed alarms or delayed responses. EF and intracranial atherosclerosis were significant predictors of incorrect predictions.

摘要

背景

血管内血栓切除术改善了大血管闭塞(LVO)患者的预后并降低了死亡率,且对时间敏感。计算机自动化可能有助于早期检测 LVO,但错误的数值可能导致报警脱敏。我们比较了 Viz LVO 和 Rapid LVO 用于自动 LVO 检测。

方法

我们回顾性地从 2022 年 1 月至 2023 年 1 月在 CT 血管造影(CTA)图像上同时运行的 Rapid LVO 和 Viz LVO 中提取数据,并与放射科医生的解释进行比较。我们计算了诊断准确性测量值,并进行了 McNemar 检验,以寻找算法错误之间的差异。我们收集了人口统计学数据、合并症、射血分数(EF)和影像学特征,并进行了多因素逻辑回归分析,以确定这些变量中是否有任何一个可以预测 CTA 上 LVO 的不正确分类。

结果

共纳入 360 例患者,其中 47 例为大血管闭塞。Viz LVO 和 Rapid LVO 的特异性分别为 0.96 和 0.85,敏感性分别为 0.87 和 0.87,阳性预测值分别为 0.75 和 0.46,阴性预测值分别为 0.98 和 0.97。对正确和错误分类的 McNemar 检验显示,两种算法的错误之间存在统计学显著差异(P=0.00000031)。多因素逻辑回归显示,低 EF(Viz P=0.00125,Rapid P=0.0286)和改良 Woodcock 评分>1(Viz P=0.000198,Rapid P=0.000000975)是不正确分类的显著预测因素。

结论

Rapid LVO 产生了大量的假阳性值,可能导致报警脱敏,导致漏报或反应延迟。EF 和颅内动脉粥样硬化是不正确预测的显著预测因素。

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