Multiple myeloma is a heterogeneous plasma cell malignancy that primarily affects older adults, with a median age of diagnosis between 65 and 69 years. It is preceded by asymptomatic precursor conditions, including monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM), which require careful differentiation from active disease to guide clinical management. MGUS progresses to multiple myeloma at a rate of ∼1 % per year, while SMM has a higher transformation rate of 10 % annually in the first five years.1

The challenge in diagnosing multiple myeloma lies in accurately distinguishing these precursor states from symptomatic disease and detecting cases with atypical presentations, such as extramedullary disease (EMD), non-secretory myeloma, and plasma cell leukemia.2

The diagnosis of multiple myeloma is based on a multidisciplinary evaluation incorporating biochemical, histopathologic, and imaging studies. Serum and urine protein electrophoresis, immunofixation, and free light chain assays remain the primary tools for detecting monoclonal gammopathy. Bone marrow biopsy with immunophenotyping, cytogenetics, and molecular profiling provides crucial diagnostic and prognostic insights. Advances in imaging—particularly whole-body low-dose CT, PET-CT, and whole-body MRI—have significantly improved lesion detection and disease staging, especially in cases with minimal bone marrow involvement. Additionally, emerging technologies such as mass spectrometry for monoclonal protein detection and AI-driven imaging algorithms, are shaping the future of multiple myeloma diagnostics.3 This review explores the evolving landscape of multiple myeloma diagnostics, emphasizing recent advancements, novel biomarkers, and ongoing challenges in integrating cutting-edge technologies into routine clinical practice.4