Topographic Analysis of Low-Grade Myeloid Neoplasms By Multiparametric in Situ Imaging of Human Bone Marrow Core Biopsy Tissues

Diagnosis of low-grade myelodysplastic syndromes (LG-MDS) is one of the most challenging in hematopathology as it relies predominantly on morphologic assessment of dysplasia. Prior studies have demonstrated poor interobserver agreement among pathologists. Histomorphological evaluation of bone marrow core biopsy samples remains the gold standard for diagnostic workup of LG-MDS, including myelodysplastic syndromes (MDS) and other myeloid neoplasms. However, this approach may be subjective, and cannot quantitatively assess subtle differences in marrow topography and the cellular microenvironment. Multiparametric in situ imaging (MISI) through various techniques enables multiple biomarker detection in a single tissue. BostonGene has developed an AI-based image analysis platform to reveal spatial information and subtle histomorphologic features in an objective, quantitative fashion. Here, we demonstrate the potential for automated AI-based imaging analysis of MISI to assist in the differentiation of LG-MDS samples from normal marrow tissues (NBM).