Multiple Myeloma: A Structured and Multidisciplinary Approach to Diagnosis.
Nourhan Ibrahim1, Daniel Rivera1, Janhavi Govande1
1Department of Pathology and Laboratory Medicine, The University of Texas Health Science Center at Houston, Houston, TX.
Seminars in Diagnostic Pathology
|December 27, 2025
Summary
Diagnosing multiple myeloma, a cancer of plasma cells, is complex. This review details advanced diagnostic tools like serum protein electrophoresis and AI imaging for earlier detection and better patient classification.
Area of Science:
- Hematology
- Oncology
- Immunology
Background:
- Multiple myeloma is a B-cell malignancy producing monoclonal immunoglobulin (M protein).
- Diagnosis is challenging due to varied symptoms, from asymptomatic to severe bone, kidney, and blood issues.
- Accurate characterization requires integrating imaging, lab tests, and bone marrow evaluation.
Purpose of the Study:
- To review current and emerging diagnostic strategies for multiple myeloma.
- To highlight the impact of these strategies on disease detection and classification.
- To provide an overview of diagnostic advancements in multiple myeloma.
Main Methods:
- Review of current literature on multiple myeloma diagnostics.
- Analysis of advancements in serum protein electrophoresis (SPEP) and immunofixation (IFE).
- Evaluation of free light chain (FLC) assays, next-generation sequencing (NGS), and AI-assisted imaging.
Main Results:
- New technologies refine diagnostic precision for multiple myeloma.
- Earlier detection and improved risk stratification are enabled by advanced assays.
- AI-assisted imaging shows promise in enhancing diagnostic accuracy.
Conclusions:
- Multimodal diagnostic approaches are crucial for accurate multiple myeloma characterization.
- Technological advancements are significantly improving the detection and classification of multiple myeloma.
- Continued evolution of diagnostic strategies is key to better patient outcomes in multiple myeloma.
