As the population of adults with congenital heart disease (ACHD) grows, there also grows an expanded need for non-invasive surveillance methods to guide management and intervention. A multimodal imaging approach layers complementary insights from echocardiography, computed tomography (CT), magnetic resonance imaging (MRI), and other modalities into a clinician's view of patient physiology. Merely applying strategies from acquired adult cardiac disease would be inadequate and potentially misleading. As data amasses in this small but growing population, investigators in the field of ACHD have discovered population-specific imaging biomarkers that identify deterioration and pivotal time points where intervention may reduce morbidity and mortality. Moreover, due to the variety of physiologies and the modest number of ACHD patients relative to that of adults with acquired heart disease, multicenter registries will be key in advancing research. The integration of well-defined imaging variables into these databases can help identify important biomarkers. Emerging technologies like computational fluid dynamics (CFD) and artificial intelligence (AI) are also primed to enhance imaging capabilities and clinical workflows, though require careful adaption as ACHD patients are not meaningfully represented in the training data for these technologies. Ultimately, a multimodal imaging approach is essential for optimizing care for ACHD patients, enabling personalized medicine where interventions can be performed before clinical deterioration occurs.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11707463 | PMC |
http://dx.doi.org/10.21037/cdt-24-363 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!