Better Leukemia Diagnostics Through AI (BELUGA)

Summary

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.

Eligibility

Inclusion Criteria:

* Patients having been diagnosed with a suspected hematological disorder
* The suspected diagnoses constitute a primary diagnosis
* Only samples of patients min.18 years of age will be used
* Samples must suffice quality attributes which are denoted in "Exclusion Criteria"

Exclusion Criteria:

* The sample is not fit for state-of-the-art diagnosis or fails initial quality control. For quality insurance, we will exclude samples in heparin- instead of EDTA. Samples with damage due to atmospheric reasons (freeze-thaw damage or elevated temperature) will be excluded.
* Samples with too scarce material jeopardizing routine gold-standard diagnosis will be excluded.
* Bone marrow aspirates without sufficient material to assess malignant or healthy hematopoiesis.

Conditions6

Browse More Trials