In the current issue of Polish Archives of Internal Medicine, Borodzicz‑Jażdżyk et al¹ present compelling findings from a retrospective analysis evaluating 2 distinct cardiovascular magnetic resonance (CMR) approaches for assessing myocardial ischemia. The study compares conventional qualitative visual assessment (QA) of first‑pass perfusion images—interpreted in grayscale—with a quantitative method using pixel‑wise perfusion (QP) mapping. The analysis was conducted in a cohort of patients referred for stress CMR (n = 101), offering valuable insights into the evolving role of quantitative techniques in routine clinical practice. CMR perfusion techniques tailored to a quantitative assessment of myocardial blood flow (MBF) were used, utilizing a dual‑bolus protocol for administration of gadolinium‑based contrast agents.¹ This approach was coupled with a postprocessing framework based on well‑established principles for MBF quantification and clinically plausible definitions of myocardial ischemia (MBF <⁠1.83 ml/min/g), enhancing the methodological rigor and translational relevance of the findings. QP mapping identified a substantially higher number of ischemic coronary territories than QA, with 46% vs 17% of the territories classified as ischemic, respectively (P <⁠0.001). At the patient level, QP analysis detected myocardial ischemia in 63% of the participants (n = 64), whereas QA did so in only 40% (n = 40; P <⁠0.001). Notably, QA identified ischemia that was not confirmed by QP mapping in a small subset of patients (7%; QA+/QP−), whereas QP analysis newly identified myocardial ischemia in 31% of the patients who had been classified as nonischemic by QA (QA−/QP+). Additionally, QP mapping diagnosed 2‑vessel or 3‑vessel disease / global ischemia more frequently than QA (2‑vessel disease, 14% vs 4%; P = 0.02; 3‑vessel disease / global ischemia 31% vs 4%; P <⁠0.001). If the higher number of segments with abnormal MBF were to actually reflect a higher number of true positive results with QP mapping, as compared with QA, then QP analysis may afford a higher sensitivity for detection of ischemia than QA. At the treating clinician’s discretion and based in part on the information from the QA, but not the QP analysis, 37 patients underwent invasive coronary angiography (ICA) with a per vessel analysis. For this subset, the authors showed a trend toward a more accurate classification of vessels using QP analysis, as compared with QA. This could support the clinical utility of QP imaging for uncovering myocardial ischemia that may go undetected with conventional visual interpretation. Importantly, this real‑world study contributes valuable data to the current literature, reinforcing the practical applicability of quantitative perfusion in routine clinical settings and underscoring its relevance for everyday patient care.

It is important to emphasize that QP mapping has been rigorously investigated across multiple clinical contexts, and has consistently demonstrated superior diagnostic accuracy for detection of obstructive coronary artery disease (CAD), as compared with visual or semiquantitative assessment methods.^2-7 In patients with obstructive CAD, QP analysis consistently revealed significantly reduced stress MBF and myocardial perfusion reserve (MPR), with MBF values typically ranging from 1.4 to 2.5 ml/min/g and MPR values between 1.6 and 2.1. A fully automated, pixel‑wise QP threshold of up to 2.01 ml/min/g has been shown to identify obstructive CAD with sensitivity of 90% and specificity of 89% (area under the curve [AUC] = 0.95),⁵ while an MPR cutoff of up to 1.86 yielded excellent diagnostic performance at the coronary territory level (AUC = 0.93).⁴ Importantly, QP mapping adds significant clinical value in evaluating multivessel disease, a scenario in which qualitative analysis frequently underestimates the ischemic burden. In a prospective study of 151 patients undergoing both stress CMR and ICA with fractional flow reserve (FFR) measurement, QP analysis identified inducible ischemia in 100% of the individuals with angiographically confirmed 3‑vessel disease, as compared with only 56% of those diagnosed based on visual assessment alone (P <⁠0.001).² Recent evidence has demonstrated the prognostic utility of QP CMR across a broad spectrum of patients with CAD. In a prospective study by Sammut et al,⁸ reduced MPR assessed by fully quantitative CMR was strongly associated with major adverse cardiovascular events, offering independent and incremental prognostic value beyond traditional imaging and clinical risk factors. Knott et al⁹ demonstrated that both global stress MBF and MPR were powerful predictors of mortality and cardiovascular outcomes, using an automated pixel‑wise perfusion mapping approach in a large, well‑characterized cohort. Importantly, Seraphim et al¹⁰ extended these findings to patients with prior coronary artery bypass grafting, a population often excluded from perfusion studies, confirming that quantitative perfusion remains a robust predictor of outcomes even in complex, surgically treated cases. Collectively, these studies support the clinical utility of QP, particularly in patients with multivessel or complex CAD, where it can improve ischemia detection and contribute to more informed risk stratification and clinical decision making. However, it is essential to note that much of the existing evidence has been derived from controlled research settings. In this context, the current study stands out by offering real‑world data, highlighting the feasibility and potential impact of QP CMR in routine clinical practice. This adds a valuable and practical dimension to the growing body of literature in the field.

Although the present study offers innovative and clinically relevant data, demonstrating that the use of QP CMR is feasible in a real‑world setting, several important limitations warrant careful consideration. A thorough understanding of these limitations is essential to interpret the present study’s findings appropriately and to assess their potential implications for routine clinical practice. One of the primary concerns is the lack of information regarding the pretest probability of CAD and the clinical profile of the referred patients, particularly the presence, type, and characteristics of chest pain. This represents a significant limitation, as current guidelines recommend investigating myocardial ischemia based on well‑established criteria that incorporate both symptom characteristics and pretest probability of CAD. Without this context, it is challenging to assess the appropriateness of referrals and generalize the findings across broader patient populations. Additionally, the small number of patients who underwent ICA is a significant constraint. After necessary exclusions—including prior coronary artery bypass grafting, acute coronary syndromes, and coronary dissection—only 37 patients and 111 coronary vessels were available for analysis. This limited sample size, inherently linked to the retrospective design of the study, reduces the power to draw robust conclusions. More importantly, the absence of a consistent invasive reference standard, such as FFR, in the majority of patients limits the ability to determine whether myocardial ischemia detected by QA or QP mapping truly reflected physiologically significant CAD. Neither positive nor negative QP findings were systematically validated against a reference standard, limiting the ability to determine whether these results represent true positives or negatives. Moreover, the clinical indication for ICA was left to the discretion of the referring physician and may have been influenced by the QA findings, potentially introducing a significant referral bias. From a technical standpoint, while the study reports both rest and stress MBF and MPR values, it remains unclear whether rest MBF values were corrected by the rate‑pressure product. This adjustment has been shown to be useful in distinguishing physiologic from pathologic increases in resting perfusion, particularly in the cases of elevated myocardial workload.⁸ The lack of clarity on this point may impact the interpretation of perfusion metrics, especially in borderline or ambiguous cases. Finally, an absence of longitudinal follow‑up or outcome data poses another key limitation. While QP analysis identified a greater number of patients with ischemia than QA, it is unknown whether this led to meaningful changes in clinical management or improved patient outcomes. Conversely, it also remains unclear whether this higher sensitivity could increase the risk of unnecessary downstream testing or interventions.

In conclusion, the study by Borodzicz‑Jażdżyk and colleagues¹ offers real‑world insights into the clinical application of QP CMR. By demonstrating the feasibility and superior sensitivity of QP mapping over conventional QA, particularly in identifying myocardial ischemia that may be missed by visual interpretation, the authors contribute to a growing body of evidence supporting the value of quantitative imaging in routine cardiology practice. These findings are consistent with prior studies showing the diagnostic superiority of QP analysis in detecting obstructive CAD, especially in complex and multivessel disease, where visual analysis often underestimates the ischemic burden. However, it is important to acknowledge the study’s limitations, which temper the strength of its conclusions. The lack of detailed clinical characterization—such as symptom type and pretest probability of CAD—limits the ability to contextualize the findings. Furthermore, the relatively small number of patients undergoing ICA and the absence of widespread use of FFR as a physiologic reference standard restrict definitive validation of the ischemic territories identified by QP mapping. Despite these constraints, this study makes a valuable contribution by bridging controlled research and real‑world clinical practice. As quantitative CMR continues to evolve, future prospective studies with comprehensive clinical and outcome data will be essential to fully establish the role of QP analysis in guiding patient management and improving cardiovascular outcomes.