在计算机断层扫描上对内脏动脉瘤的自动检测 血管扫描 使用人工智能 基于血管系统的细分
Fabien Lareyre1,2, Caroline Caradu3, Arindam Chaudhuri4
1Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, France.
EJVES vascular forum
|July 3, 2023
概括
这项研究开发了一种人工智能 (AI) 方法,用于在CT血管图扫描中自动检测内脏动脉动脉瘤 (VAA). 人工智能系统有望改善VAA查和早期检测.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 血管外科 血管外科
背景情况:
- 内脏动脉动脉瘤 (VAA) 很少见,通常无症状,导致诊断不足和治疗延迟.
- 计算机断层扫描血管造影 (CTA) 对于VAA诊断至关重要,但手动解释可能耗时.
- 人工智能 (AI) 为增强医疗图像分析和疾病检测提供了机会.
研究的目的:
- 开发和评估一种基于人工智能的方法,用于在CTA扫描中自动检测VAA.
- 评估AI系统在细分腹部血管树和识别动脉瘤方面的性能.
- 探索AI在改善查和早期发现危及生命的VAAs方面的潜力.
主要方法:
- 采用了混合人工智能方法,结合了基于特征的专家系统和深度学习卷积神经网络.
- 该系统对腹部血管树进行了自动细分,计算了动脉中心线和参考直径.
- 与参考部分相比,VAAs被确定为明显的直径增加,结果与33个CTA扫描中的专家注释得到验证.
主要成果:
- 人工智能系统准确地检测了43个专家识别的VAA中的40个,达到0.93.3的灵敏度.
- 该系统显示了0.51的积极预测值,平均每次扫描标记了3.5个区域进行专家审查.
- 对标记的VAA区域的专家审查每次CTA扫描需要不到30秒.
结论:
- 开发的AI方法显示了改善查和检测内脏动脉动脉瘤的巨大潜力.
- 虽然特异性需要增强,但人工智能系统可以有效地突出可疑的血管扩张,帮助临床注意.
- 这种人工智能驱动的方法为早期VAA诊断和管理提供了有希望的工具.
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