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通过使用人工智能分析乙胆酶染色来诊断希尔什普朗格病

Yannick Braun¹, Florian Friedmacher¹, Till-Martin Theilen¹

¹Department of Pediatric Surgery and Pediatric Urology, University Hospital Frankfurt, Goethe-University, Frankfurt am Main, Germany.

Journal of pediatric gastroenterology and nutrition

|August 9, 2024

概括

对乙胆酶染色的软件分析通过检测胆性超内核变化,准确地识别了赫斯普隆病 (HD). 这种人工智能驱动的方法可以提高这种先天性疾病的诊断精度.

科学领域:

组织病理学和数字病理学
儿科手术儿科手术
胃肠病学胃肠病学

背景情况:

希尔施普朗格病 (HD) 诊断依赖于检查直肠活检显示的结膜炎和胆固醇过内核.
目前的诊断准确性受到样品质量和主观解释的限制.
需要客观的方法来改善希尔施普朗格病的诊断.

研究的目的:

在数字化组织病理学幻灯片中评估基于软件的胆固醇过激内核的识别,用于诊断希尔施普朗格病.
评估机器学习在分析乙胆酶 (AChE) 染色模式中的实用性.
为了提高希尔施普朗格病诊断的客观性和准确性.

主要方法:

使用数字成像软件 (HALO,QuPath) 来分析112名患者的190个直肠活检样本.
在肠道粘膜层中对乙胆化酶 (AChE) 阳性染色区域的量化.
机器学习算法的应用,以识别胆固醇过激内核的标志性模式.

主要成果:

与对照组相比,赫斯普隆病患者的ACHE阳性染色面积显著增加 (p < 0.0001).
人工智能在识别HD方面实现了高精度 (AUC0.96).
排除非直肠样本进一步提高了诊断准确度 (AUC 0.993).

结论:

软件辅助的机器学习分析ACHE染色有效帮助诊断希尔施普朗格病.
这种数字病理学方法提供了更好的诊断准确性和客观性.
这种方法有望提高希尔施普朗格病的临床诊断.

关键词:

这种疾病叫做aganglionosis.数字病理学数字病理学机器学习是机器学习.结肠直肠活检是什么意思

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