Utilisation of brain MRI for the diagnosis of dementia in low and middle-income countries: systematic review and meta-analysis

OBJECTIVES: To synthesise the prevalence and patterns of dementia-relevant structural brain MRI abnormalities in adults with suspected or confirmed dementia in low- and middle-income countries (LMICs), and to summarise MRI protocols and the incremental diagnostic contribution of MRI beyond cognitive screening. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed, EMBASE, Web of Science and PsycINFO (January 1990-27 January 2025), plus reference list screening and targeted manual searches. ELIGIBILITY CRITERIA: Observational or diagnostic-accuracy studies from World Bank-defined LMICs including adults (≥50 years) with suspected or confirmed dementia who underwent brain MRI as part of diagnostic evaluation. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened, extracted data and assessed risk of bias using ROBINS-I. Random-effects models pooled prevalence of dementia-relevant MRI abnormalities; diagnostic-accuracy outcomes were synthesised narratively due to heterogeneous reference standards and incomplete reporting. RESULTS: 39 LMIC studies were included; 23 studies (2513 participants) contributed to the meta-analysis. Dementia-relevant MRI abnormalities (defined as ≥1 clinically relevant structural abnormality per study definition) were present in 1248/2513 participants. The pooled prevalence of dementia-relevant MRI abnormalities was 58% (95% CI 43% to 72%), with substantial heterogeneity (I²=95%) and a wide prediction interval (8-96%), indicating marked between-study variability; this estimate should be interpreted as a descriptive summary of study-level proportions rather than a precise population parameter. CONCLUSIONS: Brain MRI frequently demonstrates dementia-relevant pathology in LMIC clinical cohorts, usually with mixed neurodegenerative-vascular patterns. Structured visual ratings may add aetiologic specificity beyond cognitive screening, but pooled estimates should be interpreted as summaries of heterogeneous study-level findings rather than precise population parameters, given high heterogeneity and risk of bias. PROSPERO REGISTRATION NUMBER: CRD42024510241.