Clinical trials

During the last decades hematologists have excelled at improving and refining the classification, diagnosis, and thus ultimately the therapeutic decision-making process for their patients. This continuous evolution proceeded in parallel to seminal discoveries in basic science such as FISH, PCR and NGS. So far, the current WHO classification serves as reference to diagnostic decision making and is largely based on 5 diagnostic pillars: cytomorphology of peripheral blood and/or bone marrow smears, histology and immunohistochemistry of bone marrow trephine biopsies or lymph nodes, immunophenotyping, chromosome banding analysis supplemented by FISH analysis, molecular genetics including PCR and targeted panel sequencing via NGS. This leads to a swift diagnosis in 90 % of all cases. The leftover 10 % remain a challenge for hematopathologists and clinicians alike and are resolved through interdisciplinary teams in the context of specialized boards. With the advent of high throughput sequencing (mainly WGS and WTS) the possibility of a comprehensive and detailed portrait of the genetic alterations - specifically in challenging cases - has become a realistic alternative to classical methods. In SIRIUS the investigators will prospectively challenge this hypothesis to address the question of how often a better or final diagnosis can be delivered by WGS and/or WTS and if unclear cases can be efficiently resolved.

To the best of our knowledge, BELUGA will be the first prospective trial investigating the usefulness of deep learning-based hematologic diagnostic algorithms. Taking advantage of an unprecedented collection of diagnostic samples consisting of flow cytometry datapoints and digitalized blood-smears, categorization of yet undiagnosed patient samples will prospectively be compared to current state-of-the-art diagnosis at the Munich Leukemia Laboratory (hereafter MLL). In total, a collection of 25,000 digitalized blood smears and 25,000 flow cytometry datapoints will be prospectively used to train an AI-based deep neuronal network for correct categorization. Subsequently, the superiority will be challenged for the primary endpoints: sensitivity and specificity of diagnosis, most probable diagnosis, and time to diagnose. The secondary endpoints will compare the consequences regarding further diagnostic work-up and, thus, clinical decision making between routine diagnosis and AI guided diagnostics. BELUGA will set the stage for the introduction of AI-based hematologic diagnostics in a real-world setting.