BACKGROUND Accurate assessment of hepatic steatosis is a key to grade disease severity in non-alcoholic fatty liver disease (NAFLD). METHODS We developed a digital automated quantification of steatosis on whole-slide images (WSIs) of liver tissue and performed a validation study. Hematoxylin-eosin stained liver tissue slides were digitally scanned, and steatotic areas were manually annotated. We identified thresholds for size and roundness parameters by logistic regression to discriminate steatosis from surrounding liver tissue. The resulting algorithm produces a steatosis proportionate area (SPA; ratio of steatotic area to total tissue area described as percentage). The software can be implemented as a Java plug-in in FIJI, in which digital WSI can be processed automatically using the Pathomation extension. RESULTS We obtained liver tissue specimens from 61 NAFLD patients and 18 controls. The area under the curve of correctly classified steatosis by the algorithm was 0.970 (95% CI 0.968-0.973), P < 0.001. Accuracy of the algorithm was 91.9%, with a classification error of 8.1%. SPA correlated significantly with steatosis grade (Rs = 0.845, CI: 0.749-0.902, P < 0.001) and increased significantly with each individual steatosis grade, except between Grade 2 and 3. CONCLUSIONS We have developed a novel digital analysis algorithm that accurately quantifies steatosis on WSIs of liver tissue. This algorithm can be incorporated when quantification of steatosis is warranted, such as in clinical trials studying efficacy of new therapeutic interventions in NAFLD. © 2019 The Authors. Cytometry Part B: Clinical Cytometry published by Wiley Periodicals, Inc. on behalf of International Clinical Cytometry Society.

中文翻译：

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一种新颖的自动数字算法，可准确量化组织病理学全幻灯片图像上NAFLD中的脂肪变性。

背景技术准确评估肝脂肪变性是在非酒精性脂肪肝疾病（NAFLD）中分级疾病严重程度的关键。方法我们在肝脏组织的全张图像（WSI）上开发了脂肪变性的数字自动量化方法，并进行了一项验证研究。对苏木精-伊红染色的肝组织玻片进行数字扫描，并手动注释脂肪变性区域。我们通过逻辑回归确定大小和圆度参数的阈值，以区分脂肪变性与周围肝脏组织。生成的算法将产生脂肪变性比例区域（SPA；脂肪变性面积与总组织面积之比，以百分比表示）。该软件可以实现为FIJI中的Java插件，其中可以使用Pathomation扩展自动处理数字WSI。结果我们从61名NAFLD患者和18名对照中获得了肝组织标本。通过该算法正确分类的脂肪变性曲线下面积为0.970（95％CI 0.968-0.973），P <0.001。该算法的准确度为91.9％，分类误差为8.1％。SPA与脂肪变性等级显着相关（Rs = 0.845，CI：0.749-0.902，P <0.001），并且每个脂肪变性等级均显着增加（除了2级和3级之间）。结论我们开发了一种新型数字分析算法，可以精确地量化脂肪变性。肝组织的WSIs。当需要对脂肪变性进行定量时，例如在研究NAFLD中新的治疗性干预措施的疗效的临床试验中，可以合并该算法。©2019作者。细胞计数法B部分：由Wiley Periodicals出版的临床细胞计数法，