在急性缺血性中风后的随访非对比CT上,血液变化的自动细分
Jiacheng Sun1,2, Freda Werdiger3,4, Christopher Blair1,2,5
1Sydney Brain Centre, The Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia.
Frontiers in neuroinformatics
|May 1, 2024
概括
这项研究介绍了一种快速的,半自动化的工具,用于在中风治疗后对脑出血进行细分. 该算法准确量化出血,有助于预测患者在内血管血栓切除术后的结果.
科学领域:
- 医学成像分析 医学成像分析
- 神经学 神经学
- 人工智能在医学中的应用
背景情况:
- 出血转化 (HT) 是急性缺血性中风再注射疗法后的一个重要并发症.
- 准确的分段和定量出血对于患者的评估和预后至关重要.
- 当前的方法可能需要大量的数据或计算资源.
研究的目的:
- 开发和评估一个半自动算法,用于对随访非对比头部CT (NCCT) 的出血区域进行细分.
- 评估算法在中风患者治疗内血管血栓切除术 (EVT) 的表现.
- 为改善中风患者的预后预测提供一个工具.
主要方法:
- 使用了51名接受EVT治疗的中风患者的多中心数据集.
- 提出了一种采用自适应值方法的半自动化方法.
- 使用子相似系数 (DSC) 和林的一致性相关系数 (Lin's CCC) 评估了性能.
主要成果:
- 该算法实现了0.66±0.17的平均DSC,与出血性心脏病发作 (HI2) 病例 (DSC0.61±0.18) 相比,对帕伦基马性血液瘤 (PH) 病例 (DSC0.73±0.14) 的表现优越,与出血性心脏病发作 (HI2) 病例 (DSC0.61) 相比.
- 林的CCC表示与基本真相 (0.88;95%CI 0.79-0.93) 强烈一致.
- 该算法展示了快速处理,平均每案2.7秒.
结论:
- 这项研究介绍了急性中风患者治疗后出血的首次自动细分,根据放射性严重程度进行评估.
- 开发的工具是快速,有效的,并且需要最小的培训数据.
- 它有可能有助于预测中风患者在EVT后经历HT的预后.
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