Computer-Aided Assessment of Melanocytic Lesions by Means of a Mitosis Algorithm.

An increasing number of pathology laboratories are now fully digitised, using whole slide imaging (WSI) for routine diagnostics. WSI paves the road to use artificial intelligence (AI) that will play an increasing role in computer-aided diagnosis (CAD). In melanocytic skin lesions, the presence of a dermal mitosis may be an important clue for an intermediate or a malignant lesion and may indicate worse prognosis.

Validation of Whole-slide Digitally Imaged Melanocytic Lesions: Does Z-Stack Scanning Improve Diagnostic Accuracy?

Background: Accurate diagnosis of melanocytic lesions is challenging, even for expert pathologists. Nowadays, whole-slide imaging (WSI) is used for routine clinical pathology diagnosis in several laboratories. One of the limitations of WSI, as it is most often used, is the lack of a multiplanar focusing option.

The evaluation of colon biopsies using virtual microscopy is reliable.

Aims: Virtual microscopy offers major advantages for pathology practice, separating slide evaluation from slide production. The aim of this study was to investigate the reliability of using whole slide images as compared with routine glass slides for diagnostic purposes.

Methods And Results: Colon biopsies (n = 295) were assessed using both glass slides and whole slide images by four pathologists and two residents.

Interobserver variability and the effect of education in the histopathological diagnosis of differentiated vulvar intraepithelial neoplasia.

No published data concerning intraobserver and interobserver variability in the histopathological diagnosis of differentiated vulvar intraepithelial neoplasia (DVIN) are available, although it is widely accepted to be a subtle and difficult histopathological diagnosis. In this study, the reproducibility of the histopathological diagnosis of DVIN is evaluated. Furthermore, we investigated the possible improvement of the reproducibility after providing guidelines with histological characteristics and tried to identify histological characteristics that are most important in the recognition of DVIN.