Heart Scans That Count Blood Flow Predict Who Faces Serious Cardiac Events, Study of 1,007 Patients Shows

For decades, cardiologists have relied on images of the heart to tell them whether a patient’s heart muscle is getting enough blood. The pictures reveal bright and dim patches, and a dim patch during exercise or drug-induced stress has traditionally signaled a blocked coronary artery. But a new study from Taiwan suggests that the real prognostic power lies not in how the images look, but in the numbers that can now be extracted from them. Researchers at Far Eastern Memorial Hospital found that absolute measurements of myocardial blood flow and myocardial flow reserve, obtained with a specialized cadmium-zinc-telluride gamma camera, independently predicted which patients would go on to suffer major adverse cardiovascular events over nearly four years of follow-up.

The study, published in the European Journal of Nuclear Medicine and Molecular Imaging, followed 1,007 consecutive patients with suspected ischemic heart disease who underwent dynamic technetium-99m sestamibi myocardial perfusion imaging on a CZT D-SPECT camera between June 2018 and May 2021. The investigators deliberately excluded patients who underwent early revascularization within 90 days of the scan, a design choice that removes the circularity of counting procedures prompted by the test itself. During a median follow-up of 49 months, 191 patients, or 19 percent of the cohort, experienced a major adverse cardiovascular event, defined as a composite of cardiovascular death, non-fatal myocardial infarction, non-fatal stroke, hospitalization for heart failure, or late coronary revascularization.

The technology at the heart of the study represents a quiet revolution in nuclear cardiology. Conventional single-photon emission computed tomography produces static images of relative perfusion, essentially a comparison of one region of heart muscle against another. That approach can miss disease that is diffuse rather than focal, because when blood flow is uniformly reduced across the heart, no single region stands out as abnormal. Cadmium-zinc-telluride detectors changed the equation by dramatically improving sensitivity and count efficiency, making it feasible to track a radioactive tracer bolus as it moves through the bloodstream and into the heart muscle. By fitting kinetic models to that dynamic data, the scanner can calculate absolute myocardial blood flow in milliliters per gram of tissue per minute, a true physiological measurement rather than a visual impression.

The Taiwanese team quantified flow using Corridor 4DM software with a net retention model, generating two key parameters for each patient. Stress myocardial blood flow measures how much blood the heart receives when the coronary vessels are dilated by a pharmacological stressor, approximating the demands of exercise. Resting myocardial blood flow captures baseline perfusion, and the myocardial flow reserve, the ratio between the two, reflects how much the coronary circulation can ramp up delivery when the heart demands more. A healthy coronary system can multiply its flow severalfold; a diseased or dysfunctional microvasculature cannot. Using maximally selected rank statistics, a method that searches data for the cut point that best separates outcomes, the researchers determined optimal thresholds of 1.96 mL/g/min for stress flow and 1.98 for flow reserve.

The statistical signal was striking. Patients whose flow measurements fell below these thresholds had significantly worse survival free of major adverse events, with abnormal flow status associated with a chi-square value of 87.2 and a p-value below 0.001. But the more important test was whether these measurements added anything beyond what clinicians already know. In multivariable analysis, the investigators adjusted for clinical risk factors, stress left ventricular ejection fraction, and the stress total perfusion deficit, a quantitative measure of the static perfusion image itself. Even after all of that adjustment, myocardial flow reserve and resting myocardial blood flow remained independent predictors of adverse outcomes, indicating that the flow numbers carried prognostic information that no conventional variable could supply.

Perhaps the most clinically consequential finding concerned patients whose conventional scans looked reassuring. When the researchers restricted the analysis to patients with a stress total perfusion deficit below 15 percent, meaning their static perfusion images showed little or no obvious abnormality, quantitative flow assessment still provided incremental risk stratification. In other words, a patient whose pictures appear normal but whose measured flow reserve is low is not actually at low risk. This addresses one of the most persistent anxieties in cardiology: the well-documented phenomenon of false-negative perfusion images in patients with balanced ischemia or predominantly microvascular disease, where the static image underestimates the true extent of ischemic burden.

The result also illuminates the biology of coronary disease in a broader sense. Angiography, the traditional gold standard, visualizes the large epicardial arteries, but cardiovascular events often arise from disease distributed across the vessel wall or from dysfunction in the thousands of tiny arterioles that regulate perfusion. Quantitative flow imaging interrogates the entire delivery system, from the proximal stenosis to the distal microvasculature, in a single integrated measurement. Prior research with positron emission tomography has established that impaired flow reserve predicts outcomes even in patients without obstructive coronary disease, including those with ischemia and no obstructive coronary arteries, a condition once dismissed as a paradox but now understood as a major source of preventable events.

What makes the new study notable is the platform. Quantitative flow has long been considered the province of PET, which uses short-lived tracers such as rubidium-82, nitrogen-13 ammonia, or oxygen-15 water to perform kinetic imaging with high accuracy. PET cameras, however, are expensive, concentrated in large academic centers, and logistically demanding because of cyclotron-produced tracers. CZT-based SPECT cameras are more widely available and already perform millions of conventional perfusion studies worldwide. Validation work over the past decade, including head-to-head comparisons with nitrogen-13 ammonia PET and with invasive fractional flow reserve, has built the case that dynamic CZT-SPECT can approach PET-grade flow quantification using routine technetium tracers. This study extends that case from diagnostic accuracy to hard outcomes: it demonstrates that the numbers generated on these cameras actually mean something for a patient’s future.

There are caveats worth keeping in view. The analysis was retrospective and conducted at a single institution, and the cohort, drawn from patients referred for clinical perfusion imaging, may not generalize perfectly to screening populations. The researchers used a net retention model rather than full compartmental kinetic modeling, and threshold values such as 1.96 mL/g/min and 1.98 are derived from this specific camera, software, and protocol, so they may require recalibration on other platforms. The authors also note that patients who underwent early revascularization within 90 days were excluded precisely to avoid counting procedures triggered by the scan, and dataset access is available from the corresponding author on reasonable request. Still, the size of the cohort, the length of follow-up, and the rigor of the adjustment analysis place this among the strongest demonstrations yet that SPECT-derived flow quantification carries independent prognostic weight.

The practical implication is that the same scan that already tells a cardiologist whether part of the heart looks under-perfused can now, with dynamic acquisition and appropriate software, also report absolute flow and reserve, refining risk stratification at little added burden to the patient. For the roughly one in five patients in this cohort who went on to experience a cardiovascular death, heart attack, stroke, heart failure admission, or late revascularization, the difference between a normal-looking image and a low flow measurement may determine whether aggressive prevention is initiated in time. As CZT cameras proliferate and quantification software matures, the study suggests that the future of cardiac nuclear imaging will be measured not in shades of gray on a screen, but in milliliters per gram per minute, numbers that translate directly into forecasts of who lives free of cardiovascular catastrophe and who does not.

Subject of Research: Prognostic value of quantitative myocardial blood flow and flow reserve measured by dynamic CZT-SPECT for predicting major adverse cardiovascular events in suspected ischemic heart disease

Article Title: The prognostic value of quantitative myocardial blood flow and flow reserve by dynamic CZT-SPECT for major adverse cardiovascular events

Article References: The prognostic value of quantitative myocardial blood flow and flow reserve by dynamic CZT-SPECT for major adverse cardiovascular events. (n.d.). https://doi.org/10.1007/s00259-026-08195-5

Image Credits: AI Generated

DOI: 10.1007/s00259-026-08195-5

Keywords: CZT-SPECT, myocardial blood flow, myocardial flow reserve, major adverse cardiovascular events, myocardial perfusion imaging, ischemic heart disease, coronary artery disease, nuclear cardiology, prognosis, risk stratification, technetium-99m sestamibi, coronary microvascular dysfunction