DOI: 10.3390/diagnostics16162622 ISSN: 2075-4418

Diffusion-Weighted Imaging in the Musculoskeletal System: Evolving Role in Modern Imaging Practice

Ankit Tandon, Gurukrishna Bindhumadhavan

Diffusion-weighted imaging (DWI) has evolved from a niche research sequence into an increasingly valuable adjunct to conventional magnetic resonance imaging (MRI) in musculoskeletal (MSK) radiology. By providing qualitative and quantitative information on tissue microstructure through assessment of water diffusion and apparent diffusion coefficient (ADC) mapping, DWI offers functional insights beyond conventional morphological imaging. We aim to present the current evidence for DWI in MSK imaging organised around established applications and emerging applications, with particular emphasis on composition-related interpretive pitfalls relevant to differentiating tumours and other pathologies, and to review the technique’s evolving role in routine practice. This narrative review synthesises the current literature on the clinical utility of DWI in MSK imaging. It is structured in four parts: foundations and the tissue composition signal framework, including the basis of qualitative and quantitative assessment; established applications; emerging applications; and assessment of tissue composition-related interpretive as well as technical pitfalls, including those arising due to myxoid matrix, chondroid matrix, blood degradation products, organising thrombus, crystalline or mineralised material, keratinaceous debris, purulent content, cellular haematopoietic marrow, by using original cases from the authors’ institution, which have been confirmed either histologically or surgically. Applications are stratified by strength of evidence. Established applications of DWI include soft tissue abscess detection, differentiation of malignant from benign soft tissue tumours, differentiation of malignant from benign vertebral compression fractures, and myeloma staging and response assessment, as well as treatment response in soft tissue and bone sarcomas. Whole-body MRI with DWI for staging and response assessment in multiple myeloma is guideline-endorsed and supported by prospective multicentre data. Soft tissue abscess detection, soft tissue and bone tumour characterisation, and characterisation of vertebral compression fractures are supported by consistent evidence from multiple independent cohorts, although no universally transferable ADC threshold exists. The emerging applications, which are promising adjuncts supported by small, single-centre or heterogeneous studies with thresholds that have not been externally validated, include ADC ghost sign in osteomyelitis (high specificity but sensitivity of only 20%), peripheral nerve sheath tumour characterisation and surveillance in NF1 patients, peripheral neuropathy and plexopathy, predisposing conditions such as Li Fraumeni syndrome in paediatric cancers, inflammatory myopathy, and postsurgical assessment of residual disease, as well as opportunistic detection of venous thrombosis. Radiomics and machine learning approaches remain experimental. Recent technical advances, including reduced field-of-view imaging, multi-shot acquisition and improved fat suppression, have mitigated but not eliminated historical limitations of susceptibility artefacts and limited spatial resolution. DWI has become an important functional imaging technique that complements conventional MRI across a broad range of musculoskeletal disorders. Understanding the relationship between tissue composition and the diffusion signal is central to both interpreting DWI correctly and avoiding its characteristic pitfalls. DWI is best regarded not as a stand-alone technique but as one component of a multiparametric assessment, in which its functional information is integrated with conventional morphological imaging. Ongoing technical improvement and expanding clinical evidence are expected to further support its integration into routine MSK imaging and its development as a quantitative biomarker for diagnosis, prognostication, and treatment monitoring.

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