Homeyer André, Nasr Patrik, Engel Christiane, Kechagias Stergios, Lundberg Peter, Ekstedt Mattias, Kost Henning, Weiss Nick, Palmer Tim, Hahn Horst Karl, Treanor Darren, Lundström Claes
Fraunhofer MEVIS, Am Fallturm 1, 28359, Bremen, Germany.
Department of Medical and Health Sciences, Linköping University, 581 83, Linköping, Sweden.
Diagn Pathol. 2017 Nov 13;12(1):80. doi: 10.1186/s13000-017-0671-y.
Steatosis is routinely assessed histologically in clinical practice and research. Automated image analysis can reduce the effort of quantifying steatosis. Since reproducibility is essential for practical use, we have evaluated different analysis methods in terms of their agreement with stereological point counting (SPC) performed by a hepatologist.
The evaluation was based on a large and representative data set of 970 histological images from human patients with different liver diseases. Three of the evaluated methods were built on previously published approaches. One method incorporated a new approach to improve the robustness to image variability.
The new method showed the strongest agreement with the expert. At 20× resolution, it reproduced steatosis area fractions with a mean absolute error of 0.011 for absent or mild steatosis and 0.036 for moderate or severe steatosis. At 10× resolution, it was more accurate than and twice as fast as all other methods at 20× resolution. When compared with SPC performed by two additional human observers, its error was substantially lower than one and only slightly above the other observer.
The results suggest that the new method can be a suitable automated replacement for SPC. Before further improvements can be verified, it is necessary to thoroughly assess the variability of SPC between human observers.
在临床实践和研究中,脂肪变性通常通过组织学方法进行评估。自动图像分析可以减少量化脂肪变性的工作量。由于可重复性对于实际应用至关重要,我们根据不同分析方法与肝病专家进行的体视学点计数(SPC)的一致性,对这些方法进行了评估。
评估基于来自不同肝病患者的970张组织学图像的大型代表性数据集。其中三种评估方法基于先前发表的方法构建。一种方法采用了新方法以提高对图像变异性的鲁棒性。
新方法与专家的一致性最强。在20倍分辨率下,对于无或轻度脂肪变性,其再现的脂肪变性面积分数平均绝对误差为0.011;对于中度或重度脂肪变性为0.036。在10倍分辨率下,它比所有其他20倍分辨率的方法更准确,速度快两倍。与另外两名人类观察者进行的SPC相比,其误差明显低于其中一名观察者,仅略高于另一名观察者。
结果表明,新方法可以作为SPC合适的自动替代方法。在进一步改进得到验证之前,有必要彻底评估人类观察者之间SPC的变异性。