Circulation: Cardiovascular Imaging最新文献

Background: The prognostic utility of quantitative positron emission tomography (PET) with myocardial blood flow (MBF) measurements in patients with prior coronary artery bypass grafting remains unestablished. We evaluated PET-derived myocardial flow reserve (MFR) and coronary vascular resistance (CVR) for risk stratification in patients who have undergone coronary artery pass grafting.

Methods: This retrospective study included consecutive patients undergoing Rubidium-82 PET myocardial perfusion imaging between May 2017 and November 2023. MFR and CVR were defined as the ratio of stress to rest myocardial blood flow and mean arterial pressure divided by stress myocardial blood flow, respectively. The primary end point was major adverse cardiovascular events (MACE), defined as a composite of cardiac mortality and nonfatal myocardial infarction. The secondary end point (expanded MACE) included MACE plus hospitalization for unstable angina or heart failure. Associations were assessed using multivariable Cox proportional hazards models after adjusting for clinical variables and PET parameters.

Results: A total of 556 patients (median age 72 years, 79% male) were included. Over a median follow-up of 676 (482-1077) days, 39 patients (7.0%) experienced MACE, and 74 (13.3%) experienced expanded MACE. Receiver operating characteristic analysis identified optimal cutoff values of 2.05 for MFR and 66.4 mm Hg·min·g/mL for CVR. Impaired MFR and CVR were each significantly associated with increased rates of MACE and expanded MACE (all P<0.001). Stratification by combined MFR and CVR status demonstrated significant differences in event rates across groups (all P<0.001). In multivariable analysis, MFR (≤2.05), CVR (≥66.4 mm Hg·min·g/mL), and their combination were all independently associated with MACE, with adjusted hazard ratio of 2.954 ([95% CI, 1.287-6.780]; P=0.011), 2.356 ([95% CI, 1.075-5.161]; P=0.032), and 5.437 ([95% CI, 2.700-10.950]: P<0.001), respectively.

Conclusions: PET-derived MFR and CVR provide independent and incremental prognostic value in coronary artery bypass grafting patients, enhancing risk stratification beyond conventional perfusion and function parameters.

Background: Myocardial late gadolinium enhancement (LGE) using cardiac magnetic resonance imaging has been described in older endurance athletes, particularly at the ventricular hinge point. However, data on young, elite athletes are lacking. We therefore quantified the prevalence of hinge point LGE (HP-LGE) in young elite-level athletes.

Methods: We investigated 309 (40% women; median age 25.1 [21.9-29.5] years) asymptomatic athletes included in the ELITE prospective cohort (Evaluation of Lifetime Participation in Intensive Top-level Sports and Exercise cohort), investigating cardiovascular screenings of elite (national-, international-, Olympic-, or Paralympic-) level athletes, including cardiac magnetic resonance imaging with short-axis cine imaging, LGE, and T1-mapping.

Results: A total of 124 (40%) athletes had HP-LGE, with a higher prevalence in men compared with women (47% versus 30%; P=0.004). When indexed for body surface area, athletes with HP-LGE had greater left ventricle end-systolic volumes (53±11 mL/m² versus 51±11 mL/m²; P=0.037), right ventricle end-systolic volumes (56±12 mL/m² versus 53±11 mL/m²; P=0.020), lower left ventricle ejection fraction (55.5±5.0% versus 56.7±4.6%; P=0.035), lower right ventricle ejection fraction (53.9±5.0% versus 55.2±4.4%; P=0.021), and smaller estimated global left ventricle extracellular volumes (24.45±2.52% versus 25.27±2.59%; P=0.015). In multivariable regression analyses, male sex was strongly associated with HP-LGE (odds ratio, 3.07 [95% CI, 1.32-7.32]; P=0.010).

Conclusions: HP-LGE is a common finding in asymptomatic, elite athletes and is strongly associated with sex. Lower left ventricle ejection fraction is moderately associated with HP-LGE. Our study's HP-LGE prevalence indicates that HP-LGE should be interpreted as a feature of the athlete's heart.

Background: Assessment of the systemic right ventricle (RV) is critical for patients with hypoplastic left heart syndrome (HLHS). Traditional imaging metrics fail to capture the RV's complex geometry and remodeling in HLHS, limiting risk stratification. We aimed to apply statistical shape modeling to a large multicenter cohort of cardiac magnetic resonance data sets to define RV shape variants and evaluate associations with clinical outcomes.

Methods: Cardiac magnetic resonance from the FORCE (Fontan Outcomes Registry Using CMR Examinations) was analyzed for patients with HLHS post-Fontan. Three-dimensional RV models were segmented at end-diastole and processed using statistical shape modeling (ShapeWorks). Shape modes were extracted via principal component analysis and correlated with RV function, tricuspid regurgitation, remnant left ventricular morphology, and clinical outcomes, including mortality, transplant, and a composite adverse outcome including heart failure.

Results: The mean RV shape template of 329 patients with HLHS (mean age, 14.7±6.3 years) depicted a circumferentially dilated RV with loss of septal concavity. RV end-diastolic volume was independently associated with composite adverse outcome (odds ratio, 6.50; P=0.001). Distinct shape modes were identified, including an apical bulge phenotype that was independently associated with composite adverse outcome (odds ratio, 2.45; P=0.047) and mortality/transplant (odds ratio, 4.24; P=0.004). This variant also correlated with RV dilation, hypertrophy, and impaired regional strain. A spheroidal shape was associated with ≥moderate tricuspid regurgitation and tricuspid annular dilation. Remnant left ventricular morphology influenced RV shape and function but not transplant-free survival.

Conclusions: Our statistical shape modeling analyses provide novel insights into RV geometric remodeling in HLHS and identify specific shape phenotypes associated with dysfunction and adverse outcomes. Shape-based metrics offer additive prognostic value beyond conventional volumetric analysis, with potential implications for risk stratification and surgical decision-making in single-ventricle physiology.

Background: Current atherosclerotic cardiovascular disease risk prediction tools based on traditional risk factors and the coronary artery calcium score have limitations.

Methods: The CREATION study includes patients with suspected coronary artery disease who underwent coronary computed tomography angiography (CCTA) at Fuwai Hospital between 2016 and 2019. The primary outcome was major adverse cardiac events defined as a composite end point of all-cause death, acute myocardial infarction, coronary revascularization, or stroke. Six machine learning survival models were used to create an atherosclerotic cardiovascular disease prediction model.

Results: Overall, 8431 participants with analyzable CCTA data were included with a median follow-up of 3.68 years, and 319 major adverse cardiac events (3.8%) occurred (mean age: 54.73±10.21 years, 48.2% were male, 50.9% with symptomatic chest pain). Among 6 machine learning models trained with 48 CCTA parameters, XGBoost showed the best performance and was selected for model development. In the training cohort (n=5901, 70%), the XGBoost model significantly outperformed the clinical risk factors and coronary artery calcium score model (area under the curve, 0.903 versus 0.830; P<0.001). Testing cohort showed similar performance (area under the curve, 0.899 versus 0.753; P<0.001). The CCTA model demonstrates consistent predictive performance across sex (female or male), onset-age (early onset or late-onset), and symptom (asymptomatic or symptomatic) subgroup analysis. The final CCTA model included diameter stenosis, lipid plaque burden and volume, total plaque volume, high-risk plaque, and vessel volume as the most important features. Lipid plaque burden was most strongly associated with major adverse cardiac event (adjusted hazard ratio per 5% increase: 2.524 [95% CI, 2.157-2.996]; P<0.001). The incremental value of machine learning CCTA features was consistent across different time points throughout the 1- to 5-year follow-up period. The findings remained unchanged when restricted to a secondary composite end point (death, myocardial infarction, or stroke).

Conclusions: The machine learning model incorporating CCTA plaque quantification, characterization, and stenosis assessment significantly enhanced the predictive capacity for major adverse cardiac events. It provides direct visualization of coronary atherosclerosis and outperforms the traditional risk factors and the coronary artery calcium score model recommended in clinical practice.

Background: Elevated blood pressure (BP) is a major contributor to coronary artery disease. We explored the impact of life-course BP on later-life normalized stress myocardial blood flow (sMBF_N) and perfusion reserve by cardiovascular magnetic resonance.

Methods: MyoFit46 (URL: https://www.clinicaltrials.gov; Unique identifier: NCT05455125) prospectively recruited ≈500 National Survey of Health and Development 1946 birth cohort participants aged ≈77 years to undergo stress perfusion and late gadolinium enhancement cardiovascular magnetic resonance. Systolic (SBPs) and diastolic BPs (DBPs) were recorded at 36, 43, 53, 63, 69, and 77 years. For each participant, annual rates of BP change (steepness) and area under the BP trajectory curve (cumulative burden) were derived using mixed-effects models. BP cardiovascular magnetic resonance perfusion associations were tested using generalized models, adjusted for antihypertensive use, demographics, lifestyle, and comorbidities. Cross-sectional associations between major adverse cardiovascular events (myocardial infarction, stroke, and heart failure) were also tested. Mediation analyses explored mechanistic pathways.

Results: Among 459 participants, each 10 mm Hg higher SBP at 36 to 69 years was associated with 3% to 6% lower sMBF_N at 77 years. At 43 to 63 years, as SBPs rose from 120 to 140 mm Hg, sMBF_N was 18% to 24% lower. Having a sustained higher SBP by 10 mm Hg from 36 to 77 years was associated with 11% (95% CI, 8-14) lower sMBF_N. Each 1 mm Hg/y steeper SBP rise during age intervals 36 to 43, 43 to 53, 53 to 63, and 63 to 69 is associated with 2% to 5% lower sMBF_N at 77 years, association not conditional on baseline or final BPs in each interval. Associations may be clinically relevant as each 1% lower sMBF_N is associated with 3% higher major adverse cardiovascular event odds. sMBF_N mediated 20% to 40% of the life-course SBPs late gadolinium enhancement associations. Results were similar for diastolic BP, myocardial perfusion reserve, or sMBF.

Conclusions: Higher life-course BPs, steeper increases, and greater cumulative burden associate with lower myocardial perfusion at 77 years, which can be linked with higher major adverse cardiovascular event odds and fibrosis burden. This underscores the importance of early life screening and guiding treatment based on BP trajectories.