Comparison of the Manual, Semiautomatic, and Automatic Selection and Leveling of Hot Spots in Whole Slide Images for Ki-67 Quantification in Meningiomas

Background. This paper presents the study concerning hot-spot selection in the assessment of whole slide images of tissue sections collected from meningioma patients. The samples were immunohistochemically stained to determine theKi-67/MIB-1 proliferation index used for prognosis and treatment planning. Objective. The observer performance was examined by comparing results of the proposed method of automatic hot-spot selection in whole slide images, results of traditional scoring under a microscope, and results of a pathologist's manual hot-spot selection. Methods. The results of scoring the Ki-67 index using optical scoring under a microscope, software for Ki-67 index quantification based on hot spots selected by two pathologists (resp., once and three times), and the same software but on hot spots selected by proposed automatic methods were compared using Kendall's tau-b statistics. Results. Results show intra-and interobserver agreement. The agreement between Ki-67 scoring with manual and automatic hotspot selection is high, while agreement between Ki-67 index scoring results in whole slide images and traditional microscopic examination is lower. Conclusions. The agreement observed for the three scoring methods shows that automation of area selection is an effective tool in supporting physicians and in increasing the reliability of Ki-67 scoring in meningioma.