Al-Mallah, Mouaz H

BACKGROUND: Although the prognostic utility of positron emission tomography (PET) myocardial flow reserve (MFR) is well established, emerging data suggest that reduced subendocardial flows also predict adverse outcomes. However, the incremental value of subendocardial MFR (MFR SE ) beyond transmural MFR (MFR TM ) remains unclear. METHODS: We studied patients in a multicenter PET registry with normal perfusion on stress/rest Rb-82 PET, excluding those with a previous history of coronary artery bypass surgery, heart transplantation, or left ventricular ejection fraction <40%. The optimal MFR SE cutoff for predicting major adverse cardiovascular events (MACEs; death, myocardial infarction [MI], revascularization, or heart failure [HF] hospitalization) was determined using Youden’s index. Patients were stratified into 3 groups: concordant-normal (MFR TM ≥2.0; MFR SE ≥2.1), discordant (low-MFR SE , normal MFR TM ), and abnormal MFR TM . Clinical outcomes were compared by MFR groups. RESULTS: Among 6603 patients (normal N=4103; discordant N=885; abnormal N=1615) the mean age was 66.3±12.4 years, and 54% were women. Compared with the concordant-normal group, patients with discordant low-MFR SE were older and more likely to have hypertension, diabetes, peripheral artery disease, and previous percutaneous coronary intervention. The median MFR TM for normal, discordant, and abnormal groups were 2.86, 2.15, and 1.72, respectively. Over a median follow-up of 4.9 years, 1661 MACE events occurred. Discordant low-MFR SE patients had a higher risk of MACE (hazard ratio [HR], 1.41; 95% CI, 1.22–1.64) and all-cause mortality (HR, 1.36; 95% CI, 1.14–1.61) compared with concordant-normal patients. The discordant group had an intermediate absolute risk of MACE, with an adjusted annualized event rate of 5.79% (95% CI, 5.10–6.49) compared with 3.99% (95% CI, 3.67–4.30; P <0.001) in the concordant-normal group and 8.35% (95% CI, 7.71–9.00; P <0.001) in the abnormal MFR TM group. CONCLUSIONS: Subendocardial MFR reveals clinically meaningful risk heterogeneity among patients with preserved transmural flow reserve, helping refine risk stratification beyond traditional PET metrics.

ABSTRACT Background Anemia is an established marker of cardiovascular disease severity and risk which leads to elevations in resting myocardial blood flow (MBF) and impaired myocardial flow reserve (MFR) in patients without obstructive coronary artery disease (CAD). Anemia can potentially be detected opportunistically from blood pool density changes on computed tomography (CT) imaging. Objectives We evaluated relationships between chamber density measurements with hemoglobin, positron emission tomography (PET) findings, and cardiovascular events. Methods We included 33460 patients from 13 sites in the REFINE-PET who underwent PET and 24368 patients undergoing lung cancer screening chest CT. A deep learning model segmented cardiac chambers from CT images, then quantified chamber density. We evaluated the relationship between chamber density measures with resting MBF and MFR, as well as associations with death or myocardial infarction (MI). Results We included a total of 57,828 patients. A higher density in myocardium compared to left ventricle blood pool was associated with reduced MFR (adjusted odds ratio 3.02 per SD increase, 95% confidence interval[CI] 2.72 – 3.38) and an increased risk of death or MI in (adjusted hazard ratio[HR] 1.38 per SD increase, 95% CI 1.26-1.51). Having myocardial density higher than blood pool density was also associated with cardiovascular death in patients undergoing low-dose chest CT (adjusted HR 1.73, 95% CI 1.20-2.52). Conclusions In a large multimodality dataset, lower cardiac chamber density is associated with impaired MFR and independently associated with cardiovascular events. These biomarkers can be automatically extracted from CT to provide physiologic insights and potentially guide patient care. CONDENSED ABSTRACT Anemia is an important marker of cardiovascular disease severity and predictor of cardiovascular events. We utilized deep learning to measure cardiac chamber density on computed tomography imaging as a surrogate for anemia in 57,828 patients from two large multicenter studies. A higher density in myocardium compared to left ventricle blood pool was associated with reduced MFR and an increased risk of death or MI in patients undergoing positron emission tomography, and an increased risk of cardiovascular death in patients undergoing low-dose computed tomography. These biomarkers can provide additionally physiologic insights which could be used to guide patient care.

ABSTRACT Aims Exercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be used to estimate cardiorespiratory fitness. We developed a body composition “fitness” score, then validated its utility in two external populations. Methods and Results We included patients from four sites undergoing single photon emission computed tomography (SPECT) and twelve sites undergoing positron emission tomography (PET). We quantified body composition using deep learning. We evaluated associations between body composition and good exercise capacity (defined as completing ≥7 minutes on a Bruce protocol) then developed a body composition “fitness” score. We then assessed the associations of “fitness” score with exercise capacity and all-cause mortality in external populations. In total, 36471 patients were included with median age 67 (interquartile range 58 – 74). Median skeletal muscle density was higher among patients with good exercise capacity. In the external SPECT population, the body composition “fitness” score had higher prediction performance for good exercise capacity (AUC 0.771, 95% CI 0.752 – 0.789) than age (AUC 0.717, p<0.01). In the external PET population, high body composition “fitness” score was associated with lower cardiovascular death (adjusted hazard ratio 0.70, 95% CI 0.62 – 0.79, p<0.001). Conclusions We demonstrated that a comprehensive body composition “fitness” score could identify patients with good cardiorespiratory fitness. This approach transforms routinely acquired CT data into a surrogate marker of fitness which can be applied in patients undergoing PET, or other CT imaging, where exercise testing is not performed. Graphical Abstract Overview of study design. The overall population (n=36471) was split as outlined above. Body composition was analyzed from available computed tomography imaging. The distribution of body composition measures were analyzed in the combined single photon emission computed tomography (SPECT) populations. A body composition “fitness” score was derived to predict good exercise capacity in the internal population, with associations assessed in the two external testing populations.

ABSTRACT Introduction Positron emission tomography (PET) myocardial flow reserve (MFR) is a robust indicator of coronary vascular health and a strong predictor of cardiovascular risk. Clinical guidelines typically use fixed MFR thresholds (e.g., <2.0) to stratify risk, yet this approach overlooks individual variation, particularly by age and sex. We aimed to establish age- and sex-adjusted MFR percentiles and to evaluate their prognostic and predictive performance for cardiovascular risk assessment, in comparison with conventional fixed-threshold MFR approach. Methods Using data from the REFINE PET registry (24,820 patients from 12 sites), we measured PET MFR and derived age- and sex-adjusted MFR reference percentiles using quantile regression in patients without known coronary artery disease. All patients were categorized into percentile-based quartile groups. The primary outcome for prognostic and prediction analyses was major adverse cardiovascular events (MACE), defined as all-cause mortality, myocardial infarction, or heart-failure hospitalization. Time-to-event associations were evaluated using covariate-adjusted survival models, with cumulative incidence and hazard ratios (HR) estimated at 1 and 5 years in the derivation dataset, an independent but similar validation dataset A, and a high-risk validation dataset B. Predictive performance for MACE was assessed using discrimination, calibration, and reclassification metrics, comparing percentile-based models with models using a fixed MFR threshold (<2.0). Results Among participants (mean age 66.5 years; median follow-up 3.6 years), age- and sex-adjusted MFR quartile groups were strong independent predictors of MACE, with adjusted HR increasing stepwise across quartile groups at both early and later follow-up. At 1 year, HR (95% CI) comparing the lowest to the highest quartile group were 4.06 (3.41–4.82) in the derivation cohort, 3.31 (2.32–4.71) in validation cohort A, and 2.35 (2.05–2.70) in validation cohort B. At 5 years, the corresponding HR were 2.18 (1.86–2.56), 1.77 (1.31–2.40), and 1.59 (1.36–1.86). Percentile-based models demonstrated consistently higher discrimination, better calibration, and greater net reclassification for MACE at both time points compared with fixed-threshold MFR models. Although 67.2% of patients had preserved MFR (>2.0), cardiovascular risk increased steadily across MFR percentiles even within this range. Conclusion Age- and sex-adjusted MFR percentiles provide a reliable, clinically actionable measure of vascular health, improving cardiovascular risk stratification by better capturing age- and sex-related heterogeneity in vascular risk. Compared with traditional fixed-threshold approaches, MFR percentiles demonstrate improved predictive performance for cardiovascular risk assessment across diverse patient populations. CLINICAL PERSPECTIVE What is new? In a large, multinational real-world registry of more than 24,000 patients undergoing PET MPI, we derived age- and sex-adjusted myocardial flow reserve (MFR) percentiles, establishing a lifespan-based reference framework with age-specific reference values. Age- and sex-adjusted MFR percentiles showed a strong, graded association with 1- and 5-year cardiovascular risk and demonstrated improved prognostic and predictive performance compared with fixed MFR thresholds and models without MFR across independent derivation and validation datasets, including a higher-risk cohort. Lower adjusted MFR percentiles were consistently associated with higher risk of major adverse cardiovascular events, including all-cause mortality, myocardial infarction, and heart-failure hospitalization. What are the clinical implications? Age- and sex-adjusted MFR percentiles provide a personalized, dynamic measure of coronary vascular health that improves cardiovascular risk stratification by accounting for age- and sex-related heterogeneity. A percentile-based approach may help clinicians better identify patients at elevated cardiovascular risk who may warrant closer monitoring or intensified preventive strategies, while avoiding unnecessary intervention in lower-risk individuals. By integrating macrovascular and microvascular dysfunction, age- and sex-adjusted MFR percentiles offer a clinically interpretable marker of vascular aging that may inform future research on aging biomarkers, novel therapeutics and cardiovascular risk assessment across the spectrum of atherosclerotic and microvascular disease.

Background Coronary microvascular function and hemodynamics may play a role in coronary circulation and myocardial remodeling in patients with aortic stenosis (AS). We aimed to evaluate the relationship between myocardial blood flow and myocardial function in patients with AS, no AS, and aortic valve sclerosis. Methods and Results We included consecutive patients who had resting transthoracic echocardiography and clinically indicated positron emission tomography myocardial perfusion imaging to capture their left ventricular ejection fraction, global longitudinal strain (GLS), and myocardial flow reserve (MFR). The primary outcome was major adverse cardiovascular event (all‐cause mortality, myocardial infarction, or late revascularization). There were 2778 patients (208 with aortic sclerosis, 39 with prosthetic aortic valve, 2406 with no AS, and 54, 49, and 22 with mild, moderate, and severe AS, respectively). Increasing AS severity was associated with impaired MFR ( P <0.001) and GLS ( P <0.001), even when perfusion was normal. Statistically significant associations were noted between MFR and GLS, MFR and left ventricular ejection fraction, and MFR and left ventricular ejection fraction reserve. After a median follow‐up of 349 (interquartile range, 116–662) days, 4 (7.4%), 5 (10.2%), and 6 (27.3%) patients experienced a major adverse cardiovascular event in the mild, moderate, and severe AS groups, respectively. In a matched‐control analysis, patients with mild‐to‐moderate AS had higher rates of impaired MFR (52.9% versus 39.9%; P =0.048) and major adverse cardiovascular event (11.8% versus 3.0%; P =0.002). Conclusions Despite lack of ischemia, as severity of AS increased, MFR decreased and GLS worsened, reflecting worse coronary microvascular health and myocardial remodeling. Positron emission tomography–derived MFR showed a significant independent correlation with left ventricular ejection fraction and GLS. Patients with prosthetic aortic valve showed a high prevalence of impaired MFR.

Background: SARS-CoV-2 infects its target cells via angiotensin converting enzyme 2 receptor, a membrane-bound protein found on the surface of many human cells. Treatment with angiotensin converting enzyme inhibitors (ACEI) or angiotensin receptors blockers (ARB) has been shown to increase angiotensin converting enzyme 2 expression by up to 5-fold. Areas of uncertainty: These findings coupled with observations of the high prevalence and mortality among SARS-CoV-2-infected patients with underlying cardiovascular disease have led to a speculation that ACEIs/ARBs may predispose to higher risk of being infected with SARS-CoV-2. Therefore, we systematically reviewed the literature and performed a meta-analysis of the association between prior use of ACEIs and ARBs and the risk of SARS-CoV-2 infection or hospitalization due to COVID-19 disease. Data sources: We searched Ovid MEDLINE(R) and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Ovid Embase, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Web of Science, Scopus, and Medrxiv.org preprint server until June 18, 2020. Therapeutic advances: Ten studies (6 cohorts and 4 case control) that enrolled a total of 23,892 patients and 853,369 controls were eligible for inclusion in our meta-analysis. One study was excluded from the analysis because of high risk of bias. Prior use of ACEIs was not associated with an increased risk of acquiring SARS-CoV-2 or hospitalization due to COVID-19 disease, odds ratio 0.98, 95% confidence interval (0.91–1.05), I2 = 15%. Similarly, prior use of ARBs was not associated with an increased risk of acquiring SARS-CoV-2, odds ratio 1.04, 95% confidence interval (0.98–1.10), I2 = 0%. Conclusion: Cumulative evidence suggests that prior use of ACEIs or ARBs is not associated with a higher risk of COVID-19 or hospitalization due to COVID-19 disease. Our results provide a reassurance to the public not to discontinue prescribed ACEIs/ARBs because of fear of COVID-19.

AbstractAimsPioglitazone, a thiazolidinedione, was approved for treatment of Type 2 diabetes. However, several observational studies suggest an association of pioglitazone with an increased risk of bladder cancer in patients with diabetes. Therefore, we sought to perform a systematic review and meta‐analysis to evaluate the magnitude of this association and the quality of the supporting evidence.MethodsElectronic databases were queried to identify controlled studies of pioglitazone that measured the risk of bladder cancer.ResultsSix studies involving 215 142 patients using pioglitazone were included, with a median period of follow‐up of 44 months. The hazard of developing bladder cancer was significantly higher in patients using pioglitazone (hazard ratio 1.23; 95% CI 1.09–1.39; I2 = 0%) compared with control groups. The risk of bias was moderate across the six studies. Considering an incidence rate of 20.8 per 100 000 person years, the number needed to harm was five additional cases of bladder cancer per 100 000 person years.ConclusionsPatients treated with pioglitazone have a slight increased risk of bladder cancer compared to general population. Patient involvement and weighing treatment benefits versus risks should be discussed with patient toward shared decision. Patients with type 2 diabetes with risk factors, such as family history, smoking, or exposure to certain forms of chemotherapy may need to consider other anti‐hyperglycemic agents. Also, pioglitazone should be discontinued in type 2 diabetes patients with newly diagnosed bladder cancer.