Automated detection of Kaposi sarcoma-associated herpesvirus infected cells in immunohistochemical images of skin biopsies.

Immunohistochemical (IHC) staining for the antigen of Kaposi sarcoma-associated herpesvirus (KSHV), latency-associated nuclear antigen (LANA), is helpful in diagnosing Kaposi sarcoma (KS). A challenge, however, lies in distinguishing anti-LANA-positive cells from morphologically similar brown counterparts. In this work, we demonstrate a framework for automated localization and quantification of LANA positivity in whole slide images (WSI) of skin biopsies, leveraging weakly supervised multiple instance learning (MIL) while reducing false positive predictions by introducing a novel morphology-based slide aggregation method.

LAMP-enabled diagnosis of Kaposi's sarcoma for sub-Saharan Africa.

Kaposi's sarcoma (KS) is an endothelial cancer caused by the Kaposi's sarcoma-associated herpesvirus (KSHV) and is one of the most common cancers in sub-Saharan Africa. In limited-resource settings, traditional pathology infrastructure is often insufficient for timely diagnosis, leading to frequent diagnoses at advanced-stage disease where survival is poor. In this study, we investigate molecular diagnosis of KS performed in a point-of-care device to circumvent the limited infrastructure for traditional diagnosis.