Kidron Debora, Vainer Ifat, Fisher Yael, Sharony Reuven
Department of Pathology, Meir Hospital, Kfar Saba, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Department of Pathology, Meir Hospital, Kfar Saba, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Placenta. 2017 May;53:113-118. doi: 10.1016/j.placenta.2017.04.004. Epub 2017 Apr 8.
Delayed villous maturation and accelerated villous maturation diagnosed in histologic sections are morphologic manifestations of pathophysiological conditions. The inter-observer agreement among pathologists in assessing these conditions is moderate at best. We investigated whether automated image analysis of placental villi and syncytial knots could improve standardization in diagnosing these conditions.
Placentas of antepartum fetal death at or near term were diagnosed as normal, delayed or accelerated villous maturation. Histologic sections of 5 cases per group were photographed at ×10 magnification. Automated image analysis of villi and syncytial knots was performed, using ImageJ public domain software. Analysis of hundreds of histologic images was carried out within minutes on a personal computer, using macro commands.
Compared to normal placentas, villi from delayed maturation were larger and fewer, with fewer and smaller syncytial knots. Villi from accelerated maturation were smaller. The data were further analyzed according to horizontal placental zones and groups of villous size.
Normal placentas can be discriminated from placentas of delayed or accelerated villous maturation using automated image analysis. Automated image analysis of villi and syncytial knots is not equivalent to interpretation by the human eye. Each method has advantages and disadvantages in assessing the 2-dimensional histologic sections representing the complex, 3-dimensional villous tree. Image analysis of placentas provides quantitative data that might help in standardizing and grading of placentas for diagnostic and research purposes.
组织学切片中诊断出的绒毛成熟延迟和绒毛成熟加速是病理生理状况的形态学表现。病理学家在评估这些状况时,观察者之间的一致性充其量只是中等水平。我们研究了胎盘绒毛和合体结的自动图像分析是否能提高诊断这些状况的标准化程度。
将足月或接近足月的产前胎儿死亡的胎盘诊断为正常、绒毛成熟延迟或绒毛成熟加速。每组5例的组织学切片在×10放大倍数下拍照。使用ImageJ公共领域软件对绒毛和合体结进行自动图像分析。使用宏命令在个人计算机上几分钟内对数百张组织学图像进行分析。
与正常胎盘相比,成熟延迟的胎盘绒毛更大、数量更少,合体结更少、更小。成熟加速的胎盘绒毛更小。根据胎盘水平区域和绒毛大小组对数据进行进一步分析。
使用自动图像分析可以将正常胎盘与绒毛成熟延迟或加速的胎盘区分开来。绒毛和合体结的自动图像分析并不等同于肉眼解读。在评估代表复杂三维绒毛树的二维组织学切片时,每种方法都有优缺点。胎盘的图像分析提供了定量数据,这可能有助于在诊断和研究中对胎盘进行标准化和分级。