用于评估计算机断层扫描灌注脑缺血半影区/核心梗死的人工智能软件:真实世界准确性研究。

IF 1.4 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING World journal of radiology Pub Date : 2024-08-28 DOI:10.4329/wjr.v16.i8.329
Zhu-Qin Li, Wu Liu, Wei-Liang Luo, Su-Qin Chen, Yu-Ping Deng
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引用次数: 0

摘要

背景:目的:研究人工智能诊断软件(Shukun)对大血管闭塞所致急性缺血性卒中患者缺血性半影/核心梗死评估的准确性:方法:纳入2021年11月至2022年3月期间连续接受舒坤人工智能半影评估后机械取栓术(MT)的大血管闭塞急性脑卒中患者。计算机断层扫描血管造影(CTA)和灌注检查由人工智能进行分析,并由资深神经介入专家进行审查。如果三位专家意见不一致,则进行讨论以得出最终结论。如果人工智能的结果与神经介入专家的诊断不一致,则认为人工智能的诊断不准确:研究共纳入了 22 名患者。血管再通率为 90.9%,在 3 个月的随访中,63.6% 的患者改良兰金量表评分为 0-2。3名患者的计算机断层扫描(CT)灌注诊断被证实无效(不准确率:13.6%):结论:AI(Shukun)在评估缺血半影方面存在局限性。整合临床和成像数据(CT、CTA 甚至磁共振成像)对于 MT 决策至关重要。
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Artificial intelligence software for assessing brain ischemic penumbra/core infarction on computed tomography perfusion: A real-world accuracy study.

Background: With the increasingly extensive application of artificial intelligence (AI) in medical systems, the accuracy of AI in medical diagnosis in the real world deserves attention and objective evaluation.

Aim: To investigate the accuracy of AI diagnostic software (Shukun) in assessing ischemic penumbra/core infarction in acute ischemic stroke patients due to large vessel occlusion.

Methods: From November 2021 to March 2022, consecutive acute stroke patients with large vessel occlusion who underwent mechanical thrombectomy (MT) post-Shukun AI penumbra assessment were included. Computed tomography angiography (CTA) and perfusion exams were analyzed by AI, reviewed by senior neurointerventional experts. In the case of divergences among the three experts, discussions were held to reach a final conclusion. When the results of AI were inconsistent with the neurointerventional experts' diagnosis, the diagnosis by AI was considered inaccurate.

Results: A total of 22 patients were included in the study. The vascular recanalization rate was 90.9%, and 63.6% of patients had modified Rankin scale scores of 0-2 at the 3-month follow-up. The computed tomography (CT) perfusion diagnosis by Shukun (AI) was confirmed to be invalid in 3 patients (inaccuracy rate: 13.6%).

Conclusion: AI (Shukun) has limits in assessing ischemic penumbra. Integrating clinical and imaging data (CT, CTA, and even magnetic resonance imaging) is crucial for MT decision-making.

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来源期刊
World journal of radiology
World journal of radiology RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
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8.00%
发文量
35
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