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The quantification of ischaemic myocardial burden has been the cornerstone guiding clinical decision making in patients with stable coronary artery disease (CAD). This has traditionally been assessed using non-invasive functional testing, which although effective in identifying per-territory or per-patient ischaemia, often fails to identify the lesion responsible for symptoms or an appropriate target for coronary revascularisation.1 Invasive fractional flow reserve (FFR) has filled that void in being a well-validated technique to identify lesion-specific ischaemia. Clinical trials have established the role of FFR in contemporary clinical decision making, with FFR-guided revascularisation associated with improved outcomes and healthcare costs.2 Subsequently, advances in computational fluid dynamics and artificial intelligence have given rise to a non-invasive alternative in the form of FFR derived from a standard CT coronary angiogram (FFRCT).3
There is increasing evidence supporting the accuracy of FFRCT in identifying ischaemic lesions, predicting clinical outcomes, and guiding downstream testing in real-world practice.4–7 Recent data also demonstrate that the numeric value of FFRCT represents a risk continuum, with lower FFRCT values associated with a higher rate of clinical events.6 FFRCT represents one of the many emerging biomarkers that augment the anatomical assessment of CAD on CT coronary angiography (CTCA). The assessment of atherosclerotic plaque morphology and plaque biomechanics also provides incremental clinical value beyond coronary stenosis or traditional population-based cardiovascular risk scores.8 Although CTCA provides accurate assessment of total left ventricular myocardial mass, there is limited validation of techniques to quantify fractional myocardial mass or ischaemic myocardial burden from a standard CTCA. Furthermore, on its own, myocardial mass has limited utility in guiding clinical practice over established non-invasive techniques. Therefore, the role of CT-derived myocardial mass may lie in the integration with other emerging biomarkers such as FFRCT. The potential …
Contributors SLS and ARI wrote the mansucript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests SLS is supported by fellowships from the Canadian Institutes of Health Research and the Michael Smith Foundation for Health Research. ARI has received consulting honorarium from Boston Scientific and Canon Medical.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Patient consent for publication Not required.
Provenance and peer review Commissioned; internally peer reviewed.
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