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Automated Image Analysis For Placental Villi In Histological Sections
Home ‹ 2012 Abstracts ‹ Automated Image Analysis For Placental Villi In Histological Sections

Background: diagnostic pathology is based on morphologic analysis of histologic pattern in tissue sections. The patterns are highly variable and interpretation is subjective. Automated image analysis is not widely used in diagnostic pathology.

Histologic sections of placenta consist of bi-dimensional complex array of villi. The size, shape and distance between villi discriminate normal appearing villi (N) from distal villous hypoplasia (DVH) and delayed villous maturation (DVM). It reflect on the pathophysiology. Could automated image analysis separate normal villi from DVH and DVM? To our knowledge, the question was not previously addressed.

Materials and methods: the perinatal autopsy files of Meir Hospital were searched for cases of antepartum fetal death at term. According to description of placenta and placental villi, cases with N, DVH and DVM (5 cases per each group) were selected for this study. Photographs of histologic section in 3 designated areas were taken at X100 manification, (DP70 digital camera, Olympus, Japan). Blob analysis for various morphologic features of placental villi was performed, using ImageJ free software.

Results: The average number of villi per image, average size and % area occupied by villi are shown in table 1 and graph 1. Each group has distinct numerical values, significantly different from other groups.

Discussion: Automated image analysis of placental villi rapidly generates numerous numerical results. The results clearly distinguish normal villi from DVM and DVH. The addition quantitative characterization of placental villi by automated image analysis to histologic evaluation of placenta may improve standardization and reproducibility of histologic diagnosis.

Table 1: Numerical descriptors of placental villi by automated image analysis, by group:

automated1

automated2

 

Authors

Debora Kidron1, Jouly Eidel1 and Rami Aviram2

1Department of Pathology, 2Obstetrics and Gynecology, Meir Hospital, Kfar Saba

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