脏活检中的慢性性参数的可复制性和预后能力 - 在数字病理学中比较显微镜和人工智能的全面评估
Rajesh Nachiappa Ganesh1, Edward A Graviss2, Duc Nguyen3
1Department of Pathology and Genomic Medicine, The Houston Methodist Hospital and Research Institute, Houston, TX, USA.
Human pathology
|April 19, 2024
概括
对于疾病预后的脏活检评分是可靠的,尽管病理学家的变化. 计算机化方法显示出希望,但人工智能 (AI) 算法需要标准化以进行一致的量化.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 数字病理学数字病理学
- 医学成像分析 医学成像分析
背景情况:
- 活检的半定量评分对于评估病活动和预后至关重要.
- 手动评分的观察者间的变化引起了人们对其预测可靠性的担忧,需要客观的量化方法.
研究的目的:
- 评估脏活检中半定量慢性性得分的预后效用.
- 将手动评分与计算机化和基于人工智能的算法进行比较,用于间歇性纤维化 (IF) 的量化.
- 评估不同评分方法与功能和移植结果的相关性.
主要方法:
- 分析了94名脏活检患者 (45名本地患者,49名移植患者).
- 慢性得分由四名病理学家使用标准化图表进行评估.
- 间歇性纤维化 (IF) 使用五种不同的计算机化和人工智能算法对三色和PAS染料进行量化.
主要成果:
- 病理学家得分显示适度一致,但与功能和移植结果的预后相关性很强.
- 两种计算机算法与活检时估计的淋巴细胞过率 (eGFR) 相相关,但在随访时没有.
- 基于人工智能的平台在不同算法之间显示出不良一致性.
结论:
- 在活检中慢性性得分仍然是一个强大的预后工具,即使在观察者之间存在差异.
- 计算机化量化提供了潜力,但人工智能算法需要标准化,以克服硬件和软件的变化,以便可靠地使用.
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