Dey, Damini

BACKGROUND: Aortic enlargement is a powerful predictor of dissection and rupture, yet it is rarely evaluated during routine myocardial perfusion imaging, despite the widespread availability of computed tomography (CT) attenuation correction scans. The aim of this study was to determine whether fully automated, opportunistically derived, artificial intelligence-based aortic measurements from myocardial perfusion imaging CT attenuation correction scans are associated with adverse outcomes in a large multicenter cohort. METHODS: CT attenuation correction scans from patients undergoing positron emission tomography/CT and single-photon emission CT/CT myocardial perfusion imaging across 10 centers were included. A deep learning model automatically segmented the thoracic aorta, and a postprocessing algorithm extracted maximum ascending and descending diameters. The aortic size index was calculated by indexing the diameter to body surface area. RESULTS: A total of 29 339 patients (56% men; median age, 66 years [interquartile range, 58–75 years]) were included. Over a median follow-up of 3.5 years (interquartile range, 1.9–5.0 years), 5083 (17.3%) patients died. Median ascending and descending aortic size index values were 1.8 cm/m 2 (interquartile range, 1.6–2.0) and 1.5 cm/m 2 (interquartile range, 1.4–1.6), respectively, with an increase with age and higher values in females. Elevated aortic size index thresholds (ascending >2.2 cm/m 2 ; descending >1.6 cm/m 2 ) were significantly associated with increased all-cause mortality (ascending: adjusted hazard ratio, 1.16 [95% CI, 1.07–1.26], P <0.001; descending: adjusted hazard ratio, 1.23 [95% CI, 1.14–1.31]; P <0.001). Notably, the prognostic value of an abnormal aortic size index persisted independent of age, sex, and perfusion abnormalities. CONCLUSIONS: Artificial intelligence can unlock previously unused information within routine myocardial perfusion imaging CT attenuation correction scans by rapidly and automatically quantifying aortic size at scale. Opportunistic aortic measurements derived from CT attenuation correction may serve as an adjunctive risk biomarker and could add prognostic value to standard myocardial perfusion imaging without additional imaging or radiation.

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 Aims Left bundle branch block (LBBB) is associated with mechanical dyssynchrony, heterogeneous perfusion, and adverse left ventricular (LV) remodelling. However, not all patients with LBBB develop cardiomyopathy, and dyssynchrony can occur without conduction defects. The role of microvascular dysfunction remains uncertain. We aimed to assess how mechanical dyssynchrony and perfusion heterogeneity relate to LV remodelling and function in patients with and without LBBB. Methods and results We analysed 233 patients with LBBB and 932 matched controls who underwent PET myocardial perfusion imaging, assessing mechanical dyssynchrony (phase entropy), LV volumes, and ejection fraction (EF); coronary vascular resistance (CVR), myocardial blood flow (MBF), myocardial flow reserve (MFR) as markers of microvascular function; and septal-to-lateral MBF ratio (SLR) as a measure of regional perfusion heterogeneity. Compared with controls, LBBB patients had greater dyssynchrony (56% vs. 40%), larger LV volumes, and lower EF (54% vs. 67%) (all P &lt; 0.001), as well as higher stress CVR (37 vs. 34 mmHg/mL·min−1·g−1), and lower MBF (2.4 vs. 2.6 mL/min/g), MFR (2.4 vs. 2.6), and SLR (0.95 vs. 1.00) (all P &lt; 0.05). Among patients with dyssynchrony, SLR &lt;1.0 identified greater remodelling. In multivariable regression, phase entropy and SLR independently predicted LV volumes and EF, with adverse effects of SLR reduction amplified in LBBB (interaction P &lt; 0.01). In Cox analysis, phase entropy (HR:1.02, P = 0.01), MFR (HR:0.62, P &lt; 0.001), and LVEF (HR:0.97, P &lt; 0.001) were independently associated with death or heart failure hospitalization, whereas LBBB was not. Conclusion Mechanical dyssynchrony and perfusion heterogeneity independently predict adverse LV remodelling, irrespective of LBBB. Integrated imaging improves cardiomyopathy stratification.

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 Low-dose colchicine (0.5 mg once daily) reduces the risk of major cardiovascular events in coronary disease, but its mechanism of action is not yet fully understood. We investigated whether low-dose colchicine is associated with changes in pericoronary inflammation and plaque composition in patients with chronic coronary disease. Methods We performed a cross-sectional, nationwide, subanalysis of the Low-Dose Colchicine 2 Trial (LoDoCo2, n=5522). CT angiography studies were performed in 151 participants randomised to colchicine or placebo after a median treatment duration of 28.2 months. Pericoronary adipose tissue (PCAT) attenuation measurements around proximal coronary artery segments and quantitative plaque analysis for the entire coronary tree were performed using artificial intelligence-enabled plaque analysis software. Results Median PCAT attenuation was not significantly different between the two groups (−79.5 Hounsfield units (HU) for colchicine versus −78.7 HU for placebo, p=0.236). Participants assigned to colchicine had a higher volume (169.6 mm 3 vs 113.1 mm 3 , p=0.041) and burden (9.6% vs 7.0%, p=0.035) of calcified plaque, and higher volume of dense calcified plaque (192.8 mm 3 vs 144.3 mm 3 , p=0.048) compared with placebo, independent of statin therapy. Colchicine treatment was associated with a lower burden of low-attenuation plaque in participants on a low-intensity statin, but not in those on a high-intensity statin (p interaction =0.037). Conclusions Pericoronary inflammation did not differ among participants who received low-dose colchicine compared with placebo. Low-dose colchicine was associated with a higher volume of calcified plaque, particularly dense calcified plaque, which is considered a feature of plaque stability.

ABSTRACTBackgroundPrior studies have documented that patients with colorectal cancer (CRC) are at an increased risk of cardiovascular disease (CVD).ObjectivesTo examine coronary artery calcium (CAC) as a marker of subclinical atherosclerosis and its association with major adverse cardiovascular events (MACE) in patients with CRC across the cancer treatment trajectory.MethodsAdults with newly diagnosed CRC were enrolled in the prospective ColoCare study from 2017 to 2024. CAC was measured from routine diagnostic computed tomography (CT) and positron emission tomography‐CT scans at CRC diagnosis until 5 years post‐diagnosis. Atherosclerosis was defined as the presence of CAC. We used multivariable‐adjusted Fine and Gray models to assess the association between CAC and MACE risk, accounting for competing risks.ResultsAmong 300 CRC patients, the most common CVD risk factors at cancer diagnosis were hypertension (37%), hyperlipidemia (24%), and diabetes (14%). During follow‐up (median = 5.3 years), 75 (25%) individuals experienced MACE: stroke (3%), new/worsening HF (9%), HF exacerbation requiring hospitalization (2%), coronary revascularization (3%), and death (19%). Among individuals with imaging at baseline (n = 101), 37 (36.6%) had CAC, and statins were not prescribed in 11 (55.0%) patients with moderate/high CAC. For those with serial imaging (n = 61), 31.1% showed worsening CAC and 3% developed new CAC. Baseline CAC conferred a higher risk of MACE (HR = 4.79; 95% CI: 1.05–21.75, p = 0.04) after accounting for cancer‐related deaths as a competing risk.ConclusionsSubclinical atherosclerosis and MACE are common among patients with CRC. Integrating CAC from routine cancer imaging can identify patients who may benefit from cardio‐preventive treatment.

BACKGROUND: Computed tomography (CT) attenuation correction scans are an intrinsic part of positron emission tomography (PET) myocardial perfusion imaging using PET/CT, but anatomic information is rarely derived from these ultralow-dose CT scans. We aimed to assess the association between deep learning-derived cardiac chamber volumes (right atrial, right ventricular, left ventricular, and left atrial) and mass (left ventricular) from these scans with myocardial flow reserve and heart failure hospitalization. METHODS: We included 18 079 patients with cardiac PET/CT from 6 sites. A deep learning model estimated cardiac chamber volumes and left ventricular mass from CT attenuation correction imaging. Associations between deep learning-derived CT mass and volumes with heart failure hospitalization and reduced myocardial flow reserve were assessed in a multivariable analysis. RESULTS: During a median follow-up of 4.3 years, 1721 (9.5%) patients experienced heart failure hospitalization. Patients with 3 or 4 abnormal chamber volumes were 7× more likely to be hospitalized for heart failure compared with patients with normal volumes. In adjusted analyses, left atrial volume (hazard ratio [HR], 1.25 [95% CI, 1.19–1.30]), right atrial volume (HR, 1.29 [95% CI, 1.23–1.35]), right ventricular volume (HR, 1.25 [95% CI, 1.20–1.31]), left ventricular volume (HR, 1.27 [95% CI, 1.23–1.35]), and left ventricular mass (HR, 1.25 [95% CI, 1.18–1.32]) were independently associated with heart failure hospitalization. In multivariable analyses, left atrial volume (odds ratio, 1.14 [95% CI, 1.0–1.19]) and ventricular mass (odds ratio, 1.12 [95% CI, 1.6–1.17]) were independent predictors of reduced myocardial flow reserve. CONCLUSIONS: Deep learning–derived chamber volumes and left ventricular mass from CT attenuation correction were predictive of heart failure hospitalization and reduced myocardial flow reserve in patients undergoing cardiac PET perfusion imaging. This anatomic data can be routinely reported along with other PET/CT parameters to improve risk prediction.

Abstract Background and Aims Positron emission tomography (PET)/computed tomography (CT) myocardial perfusion imaging (MPI) is a vital diagnostic tool, especially in patients with cardiometabolic syndrome. Low-dose CT scans are routinely performed with PET for attenuation correction and potentially contain valuable data about body tissue composition. Deep learning and image processing were combined to automatically quantify skeletal muscle (SM), bone and adipose tissue from these scans and then evaluate their associations with death or myocardial infarction (MI). Methods In PET MPI from three sites, deep learning quantified SM, bone, epicardial adipose tissue (EAT), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and intermuscular adipose tissue (IMAT). Sex-specific thresholds for abnormal values were established. Associations with death or MI were evaluated using unadjusted and multivariable models adjusted for clinical and imaging factors. Results This study included 10 085 patients, with median age 68 (interquartile range 59–76) and 5767 (57%) male. Body tissue segmentations were completed in 102 ± 4 s. Higher VAT density was associated with an increased risk of death or MI in both unadjusted [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.37–1.43] and adjusted (HR 1.24, 95% CI 1.19–1.28) analyses, with similar findings for IMAT, SAT, and EAT. Patients with elevated VAT density and reduced myocardial flow reserve had a significantly increased risk of death or MI (adjusted HR 2.49, 95% CI 2.23–2.77). Conclusions Volumetric body tissue composition can be obtained rapidly and automatically from standard cardiac PET/CT. This new information provides a detailed, quantitative assessment of sarcopenia and cardiometabolic health for physicians.