Exploring major trends in cardiac MRI
Cardiac magnetic resonance imaging (MRI) is advancing beyond its established role in structure and function assessments, with improvements in tissue characterization, myocardial blood flow quantification and automated image analysis helping clinicians better diagnose cardiovascular disease, assess risk and guide treatment decisions.
Amit Patel, MD, secretary of the Society for Cardiovascular Magnetic Resonance (SCMR) and director of cardiac imaging with the University of Virginia Health System in Charlottesville, outlined four key areas where cardiac MRI is expanding its clinical value. He added that the growing role of artificial intelligence (AI) is making advanced imaging techniques more practical for routine clinical use.
Cardiac MR tissue characterization guides diagnosis and treatment
One of the most significant developments in this field is the increasing use of tissue characterization techniques, including T1 mapping, T2 mapping and extracellular volume fraction measurements. These tools help clinicians better identify underlying myocardial disease and establish more specific diagnoses, Patel said. Improved characterization of heart muscle abnormalities can help physicians select targeted treatments and, in some conditions, monitor how patients respond to therapy.
"These developments are allowing us, once we make a specific diagnosis, to really use targeted treatments to treat the patient," Patel told Cardiovascular Business. "Beyond that, in certain diseases like amyloidosis, we are able to track treatment response and potentially change our treatment if we have progression of disease, or add a second therapeutic to it."
Quantifying blood flow reveals overlooked disease
A second major trend in this field is the ability to quantify myocardial blood flow during stress MRI examinations. Beyond identifying ischemia, quantitative measurements can help diagnose coronary microvascular dysfunction, a condition that can cause chest pain and is frequently overlooked, particularly in women.
Patel said randomized controlled trials have demonstrated that patients who undergo quantitative stress MRI and receive a diagnosis of coronary microvascular dysfunction can experience improved symptoms and quality of life.
The findings highlight how advanced MRI techniques can help close diagnostic gaps and provide more actionable information for managing patients with chest pain.
Scar assessment could improve cardiac arrest risk stratification
Cardiac MRI also has an established role in identifying myocardial scarring through late gadolinium enhancement (LGE). Emerging evidence is strengthening the case for using the extent of scarring to guide clinical decisions.
Patel pointed to data from the large HCMR registry, which examined patients with hypertrophic cardiomyopathy. The findings support the importance of LGE as an independent risk factor for sudden cardiac death. Quantifying scar burden could therefore help physicians determine which patients may benefit from an implantable cardioverter-defibrillator (ICD), improving risk stratification beyond conventional clinical assessments.
MRI offers another tool for evaluating valve disease
A fourth area of growing interest is the assessment of valvular heart disease. Cardiac MRI can accurately quantify valve regurgitation and measure the heart's remodeling in response to the abnormal blood flow.
These measurements may help clinicians identify patients who would benefit from valve surgery, while also identifying others who can safely continue to be monitored before undergoing any intervention.
AI helps make advanced cardiac MRI more practical
Despite the clinical potential of these techniques, workflow demands have historically limited their use. AI is increasingly helping address those challenges by improving patient selection, streamlining examinations, reducing scan times and automating image analysis and reporting.
"AI is playing a huge role in the field of cardiac magnetic resonance. It is really helping identify which patients are more likely to benefit from getting the MRI exam as well, and it is really helping make the MRI exam occur more efficiently by allowing us to reduce scan times while maintaining image quality through noise reduction algorithms," Patel explained.
He said automated tools are also increasingly doing more of the measurements of cardiac chamber size, myocardial tissue characteristics and scar burden, which saves a significant amount of staff time.
Patel cited quantitative myocardial blood flow as an example of the change. Previously, segmenting the heart and identifying the information needed to calculate blood flow could require nearly an hour of manual work. Automated analysis can now generate the measurements almost immediately after image acquisition. That reduction in processing time could make advanced quantitative techniques more feasible for routine clinical practice, allowing centers to expand the the information from each exam without adding increasing staff time.
Dave Fornell has covered healthcare for more than 17 years, with a focus in cardiology and radiology. Fornell is a 5-time winner of a Jesse H. Neal Award, the most prestigious editorial honors in the field of specialized journalism. The wins included best technical content, best use of social media and best COVID-19 coverage. Fornell was also a three-time Neal finalist for best range of work by a single author. He produces more than 100 editorial videos each year, most of them interviews with key opinion leaders in medicine. He also writes technical articles, covers key trends, conducts video hospital site visits, and is very involved with social media. E-mail: [email protected]