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Better Leukemia Diagnostics Through AI (BELUGA)

NCT04466059 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 25000

Last updated 2024-12-17

No results posted yet for this study

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.

Conditions

Interventions

DIAGNOSTIC_TEST

Automated 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.

Sponsors & Collaborators

  • Munich Leukemia Laboratory

    lead INDUSTRY

Principal Investigators

  • Wolfgang Kern, Prof. Dr. · MLL Munich Leukemia Laboratory

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-01-05
Primary Completion
2025-07-31
Completion
2025-07-31

Countries

  • Germany

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04466059 on ClinicalTrials.gov