Can quantitative assessment of coronary artery disease (CAD) open the door to greater reproducibility and diagnostic accuracy than qualitative methods?
In a recent review, researchers from the Cardiovascular Imaging Department at the Monzino Cardiology Centre in Milan, Italy, set out to explore the conduction of quantitative assessment of CAD, and its advantages over traditional, qualitative methods. The drawbacks of qualitative techniques were highlighted as limited sensitivity, low reproducibility, and the use of a binary approach to ischemia.
The review provided an overview of how myocardial perfusion can be used to assess CAD, as well as indications, challenges, and opportunities to improve patient management.
Superior performance of CMR?
The review highlighted the three “robust techniques” used for myocardial perfusion in clinical practice as single-photon emission CT (SPECT), positron emission tomography (PET), and cardiovascular magnetic resonance (CMR). Of the three techniques, CMR and PET had demonstrated superior diagnostic accuracy in most meta-analyses. A fourth method, CT perfusion, has emerged more recently, but the review pointed out that there is less literature containing evidence of this technique’s effectiveness than the first three methods.
The limitations of a qualitative approach
A comparison of CMR and SPECT in women with suspected CAD from the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease (CE-MARC) Trial found that qualitative assessment of ischemia with CMR had greater sensitivity than SPECT in both males and females. However, another study showed that adding semi-quantitative CMR to qualitative stress magnetic resonance myocardial perfusion could produce higher sensitivity, especially in left circumflex lesions detection.
There is more evidence to suggest that qualitative perfusion may be insufficient for future clinical practice. The Dan-NICAD study compared the diagnostic accuracy of myocardial perfusion (with visually-assessed SPECT and CMR) against invasive coronary angiography (ICA) with fractional flow reserve (FFR) in patients with suspected CAD by coronary computed tomography angiography (CCTA). It was found that the sensitivity of both CMR and SPECT, which were visually assessed, was low compared with FFR, questioning whether the diagnostic accuracy of qualitative perfusion is sufficient for future clinical needs.
Advantages of absolute quantification
The review identified the main advantages of the three quantification techniques – which are the dual-bolus protocol, pre-bolus technique, and single bolus with a dual sequence – as being “improved reproducibility and diagnostic accuracy”.
It highlighted the findings of a study by researchers from King’s College London which demonstrated that, compared with visual assessment, quantitative perfusion analysis techniques had a higher accuracy for correctly identifying the presence of coronary microvascular dysfunction. Research demonstrating that the capacity to detect functionally significant coronary stenosis is incrementally improved by the successive addition of coronary flow reserve, stress myocardial blood flow (MBF), and relative flow reserve to relative perfusion defect assessments was also presented, along with the CE-MARC trial’s establishment of CMR’s superior diagnostic accuracy over SPECT in CAD.
An insufficient level of training has been picked out as the main determinant of the diagnostic accuracy of visual assessment.
Using myocardial perfusion to assess CAD
The review’s authors stated that in their own experience, as a first-line test in symptomatic patients with a previous history of revascularisation, CMR offered higher cost-effectiveness compared to anatomical assessment with CCTA.
The Dan-NICAD study has identified a “huge need” for quantitative perfusion in the setting of obstructive CAD, as the sensitivity of qualitative perfusion alone is not sufficient. Based on this finding and to increase diagnostic accuracy, the authors of the review have begun clinical examinations with quantitative perfusion on top of anatomical assessment with CT and will start assessments using quantitative perfusion with CMR.
Improving CAD patient management with absolute quantification
Absolute quantification with CMR improves the management of patients with CAD, the review explained. It does this by delineating different levels of ischemia, rather than producing the binary result of qualitative techniques; i.e. a result that is either positive or negative for ischemia. This allows clinicians to differentiate between patients with a mild, moderate, or severe reduction of stress myocardial blood flow (MBF), and also to distinguish between patients with a lower or higher volume of myocardial mass. It is hoped that in the future, quantitative perfusion will be able to identify “an optimal threshold that can be used in clinical practice to distinguish between patients with CAD who require medical therapy and the minority of patients with CAD who require revascularisation”.
In terms of diagnosis, the review highlighted research that showed automatically generated, fully quantitative CMR MBF pixel maps to have high diagnostic performance for detecting significant CAD. A study of patients with known or suspected CAD revealed that a strong, independent predictor of adverse cardiovascular outcomes was provided by the automatic measurement of reduced MBF and myocardial perfusion reserve using artificial intelligence quantification of CMR perfusion mapping.
Indications for quantitative assessment
The authors believe that the first indication for quantitative assessment in patients with a positive CT, and the second indication in patients with complex coronary artery anatomy, “for whom CT is not a useful examination” - is recommended that functional testing with stress CMR is used for these patients. Quantitative assessment is also used by the authors for the prognostic stratification of patients with heart muscle diseases.
Challenges and conclusion
Among the challenges cited by the review were “a lack of reference values” with “many confounders that can influence MBF thresholds, such as cardiovascular risk factors”. The “cost and lack of availability of perfusion CMR in all centers” were also highlighted.
It is concluded that data suggests “quantitative perfusion could be a solution” to the “puzzle” of CAD diagnosis. The authors propose that now “quantitative perfusion has started to be used in a large number of patients, their data must be entered into large registries that track outcomes,” before artificial intelligence is used to establish “robust MBF thresholds that are related to patient outcomes”.
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