评估人工智能在诊断头部和部动脉瘤方面的临床应用价值
Yi Shen1, Chao Zhu1,2, Bingqian Chu1
1Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, 230022, China.
BMC medical imaging
|October 1, 2024
概括
这项研究表明,人工智能 (AI) 软件在检测脑动脉瘤和测量其大小方面表现良好. 与标准方法相比,人工智能系统还提供了优越的图像质量和更快的处理时间.
科学领域:
- 神经辐射学神经辐射学
- 医疗成像医学成像
- 人工智能在医学中的应用
背景情况:
- 大脑动脉瘤构成重大风险,需要准确的检测和表征.
- 计算机断层扫描血管造影 (CTA) 是诊断脑动脉瘤的关键成像方式.
- 半自动化人工智能 (AI) 工具提供了改善诊断工作流程的潜力.
研究的目的:
- 评估CerebralDoc®人工智能系统用于检测脑动脉瘤的性能.
- 评估人工智能系统在测量动脉瘤形态特征方面的准确性.
- 将人工智能驱动的图像后处理质量和时间与传统方法进行比较.
主要方法:
- 对354个CTA病例的回顾性分析,包括DSA组中的102个和非DSA组中的178个.
- 对动脉瘤的存在,位置和形态与数字减去血管学 (DSA) 和放射科医生的发现进行AI性能评估.
- 将人工智能产生的图像质量和处理时间与标准软件和放射科医生评估进行比较.
主要成果:
- 在DSA组中,AI的灵敏度为88.24%,准确度为81.97% (与放射科医生相比:95.10%的灵敏度,84.43%的准确度).
- 在非DSA组中,AI获得了81.46%的灵敏度和76.29%的准确度.
- 人工智能在子宽度和最大直径测量方面表现出卓越的可靠性 (ICC>0.80),图像质量优越,处理时间缩短.
结论:
- 人工智能系统在检测脑动脉瘤方面表现强.
- 人工智能提取的形态参数与放射科医生的评估高度一致.
- 人工智能软件对神经血管成像中的临床应用具有重大前景.
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