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Royston Group - AI-based Analysis of the Bone Marrow; Integrating Spatial Transcriptomics & Multiplexed Imaging To Improve the Assessment of Blood Cancer (Funding Available)
The diagnosis of blood cancer requires integration of clinical, pathological, immunophenotypic and genetic / molecular findings. Accurate and consistent interpretation of bone marrow trephines (BMT) is particularly important for distinguishing between important blood cancer subtypes. Such distinction guides patient management and informs risk stratification. In response, our group have developed pioneering artificial intelligence (AI) approaches to accurately capture important tissue features of the bone marrow in blood cancer. This includes the development of automated and quantitative approaches to detect cellular and stromal changes present on routinely prepared diagnostic samples. We are now developing strategies to combine these approaches with newly developed advanced spatial transcriptomic and IHC / IF multiplexing strategies for patient-derived bone marrow biopsies.