Multimodal diagnostic imaging for early mitral valve disease: integration of current and emerging modalities—a narrative review

Background and Objective: Mitral valve disease (MVD) is a major contributor to global cardiovascular morbidity and mortality. Early identification is critical to prevent progression to heart failure, atrial fibrillation, and irreversible myocardial remodeling. Existing reviews have largely focused on advanced MVD, individual imaging modalities, or guideline summaries, with limited emphasis on early, asymptomatic disease, quantitative diagnostic thresholds, comparative multimodal imaging, and recent innovations. This narrative review uniquely synthesizes evidence published between 2020 and 2025 to provide an updated, modality-integrated overview of early-stage MVD, emphasizing emerging technologies, global accessibility considerations, and a practical multimodal diagnostic framework. Methods: A comprehensive literature search was conducted using PubMed, Scopus, and Google Scholar from January 2020 to August 2025. Original studies, meta-analyses, high-quality narrative or state-of-the-art reviews, and consensus statements addressing early diagnosis of MVD were included. Non-English publications, case reports, and studies focusing exclusively on advanced disease were excluded. Study selection and data extraction were performed by the author, and alternative available versions were retrieved when full texts were unavailable. Key Content and Findings: Echocardiography remains the cornerstone of early MVD assessment due to its accessibility, dynamic evaluation capabilities, and cost-effectiveness. Cardiac magnetic resonance (CMR) offers high precision for quantifying regurgitant volume, myocardial fibrosis, and early remodeling. Computed tomography (CT) provides superior spatial resolution for anatomical assessment and preprocedural planning, while positron emission tomography (PET) contributes metabolic and inflammatory insights, especially in prosthetic valve disease. Emerging innovations, such as artificial intelligence (AI), machine learning (ML), fusion imaging, and four-dimensional (4D) flow CMR, enhance diagnostic precision and prognostication. In resource-limited settings, strategies including tele-echocardiography, portable ultrasound, and global training initiatives are improving accessibility. Integration of imaging with clinical, functional, and patient-reported outcomes promotes a holistic, patient-centered approach. Conclusions: Advances in multimodal cardiovascular imaging are transforming early MVD detection and management. A patient-centered, AI-enhanced imaging strategy, incorporating echocardiography, CMR, CT, and PET, can significantly improve diagnostic accuracy, optimize intervention timing, and enhance long-term outcomes. Broader implementation of telemedicine, standardized training, and cost-effective imaging technologies will be essential for equitable global adoption.