RecruitingNCT04466059

Better Leukemia Diagnostics Through AI (BELUGA)

A Case-Control Study To Determine The Suitability Of Artificial Intelligence For Leukemia Diagnostics


Sponsor

Munich Leukemia Laboratory

Enrollment

25,000 participants

Start Date

Jan 5, 2020

Study Type

OBSERVATIONAL

Conditions

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

Min Age: 18 Years

Inclusion Criteria3

  • 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

Exclusion Criteria3

  • 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.

Interventions

DIAGNOSTIC_TESTAutomated AI-Guided Diagnosis of Hematological Malignancies

In BELUGA, we want to investigate whether the automated analysis of blood (from peripheral blood and bone marrow aspirates) smears and flow-cytometry-based analyses can provide a benefit for diagnostic quality and, ultimately, patient care.


Locations(1)

MLL Munich Leukemia Laboratory

Munich, Bavaria, Germany

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NCT04466059


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