Circulation: Cardiovascular Imaging最新文献

Background: Racial and ethnic differences have been reported for aortic valve calcium (AVC) and long-term aortic stenosis (AS). Whether these differences are due to differing risk factor profiles or the burden of AVC is unknown.

Methods: Baseline AVC was quantified using the Agatston method among 6812 MESA (Multi-Ethnic Study of Atherosclerosis) participants. AVC scores were not reported to participants. The primary outcome of long-term moderate or severe AS was adjudicated using standard clinical criteria. We calculated multivariable Cox proportional hazards with log-transformed AVC as a continuous variable for each race and ethnicity.

Results: The mean age was 62 years, and 47% of participants were women. Over a median follow-up of 16.7 years, 140 participants were diagnosed with moderate (n=56) and severe AS (n=84). The prevalence of baseline AVC >0 by self-reported race and ethnicity was White (15.8%), Hispanic (13.3%), Black (12.3%), and Chinese (8.3%). The rate of long-term incident moderate-severe AS was highest for White participants (2.1/1000 person-years) and lowest for Chinese participants (0.5/1000 person-years). The association of AVC with moderate-severe AS was significant for all race and ethnicity groups: White hazard ratio, 1.82 (95% CI, 1.62-2.03); Hispanic hazard ratio, 2.18 (95% CI, 1.82-2.62); Black hazard ratio, 2.28 (95% CI, 1.78-2.93); and Chinese hazard ratio, 3.65 (95% CI, 1.05-12.71) per 1 unit higher log transformed AVC. There was no interaction by race and ethnicity (P=0.26) when modeling Black versus non-Black participants.

Conclusions: The racial and ethnic groups with a higher baseline prevalence of AVC had a higher long-term incidence of moderate-severe AS, but a similar relative association between AVC and moderate-severe AS regardless of baseline atherosclerotic cardiovascular disease risk. Our findings suggest that differences in AS by race and ethnicity may likely be explained by the burden of AVC.

Background: Accurate aortic stenosis (AS) phenotyping requires multimodality imaging which has limited availability. The digital aortic stenosis severity index (DASSi), an artificial intelligence biomarker of AS-related remodeling on single-view 2-dimensional echocardiography, predicts AS progression independent of Doppler measurements. We sought to evaluate the ability of DASSi to define personalized AS progression profiles and to validate its performance as a scalable alternative to multimodality imaging features of functional, structural, and biological AS severity.

Methods: In the SALTIRE-2 trial (Study Investigating the Effect of Drugs Used to Treat Osteoporosis on the Progression of Calcific Aortic Stenosis 2) of participants with mild or moderate AS, we performed blinded DASSi measurements (probability of severe AS, 0-1) on baseline transthoracic echocardiograms. We evaluated the association between baseline DASSi and (1) disease severity by hemodynamic (peak aortic valve velocity), structural (computed tomography-derived aortic valve calcium score), and biological features ([¹⁸F]sodium fluoride uptake on positron emission tomography-computed tomography); (2) longitudinal disease progression (absolute change in peak aortic valve velocity and aortic valve calcium score); and (3) incident aortic valve replacement. We used generalized linear mixed or Cox models adjusted for risk factors and aortic valve area.

Results: We analyzed 134 participants (72 [interquartile range, 69-78] years; 27 [20.1%] women) with a mean baseline DASSi of 0.51 (SD, 0.19). DASSi was independently associated with cross-sectional disease severity: each SD increase was associated with higher peak aortic valve velocity (+0.21 [95% CI, 0.12-0.30] m/s), aortic valve calcium score (+284 [95% CI, 101-467] Agatston units), and [¹⁸F]sodium fluoride target-to-background ratio_max (+0.17 [95% CI, 0.04-0.31]). Higher DASSi was also associated with disease progression by Doppler (peak aortic valve velocity) and computed tomography (aortic valve calcium score) at 24 months (P interaction for DASSi × time<0.001), and future aortic valve replacement (75 events over 5.5 [interquartile range, 2.4-7.2] years, adjusted hazard ratio, 1.42 [95% CI, 1.11-1.84] per SD).

Conclusions: DASSi is associated with functional, structural and biological features of AS severity and predicts disease progression and adverse outcomes. DASSi-enhanced echocardiography may provide an accessible alternative to multimodality AS imaging and serve as a predictive enrichment biomarker in clinical trials.

Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02132026.

Background: Myocardial flow reserve (MFR), measured by positron emission tomography (PET) myocardial perfusion imaging, provides valuable information on epicardial coronary disease, diffuse atherosclerosis, and microvascular function. Despite its routine use, the prognostic efficacy of ¹³N-ammonia PET MFR remains unconfirmed in larger multicenter cohorts of patients with suspected or known coronary artery disease.

Methods: We considered patients from 5 sites in the REFINE PET (Registry of Fast Myocardial Perfusion Imaging With Next Generation PET) registry who underwent ¹³N-ammonia PET myocardial perfusion imaging for coronary artery disease. Clinical and imaging data were collected at the time of myocardial perfusion imaging. MFR was quantified as the ratio of stress to rest myocardial blood flow, using QPET software (Cedars-Sinai Medical Center, Los Angeles, CA). The primary outcome was all-cause mortality. Survival analyses were performed using Kaplan-Meier and Cox regression models adjusted for clinical and imaging covariates.

Results: In total, 6277 patients were included (median age of 65 years, 56% male). Median follow-up time was 3.8 years. There were 1895 patients with MFR ≤2 and 4382 with MFR >2. Patients with MFR ≤2 had significantly higher mortality than those with MFR >2 (n=701 [37.0%] versus n=537 [12.3%], respectively; P<0.001). Annualized all-cause mortality rates by MFR and summed stress score ranged from 1.7 to 15.8. In multivariable analysis, MFR ≤2 was independently associated with increased all-cause mortality in the overall population (hazard ratio, 2.70 [95% CI, 2.41-3.03]; P<0.001), even among patients with no perfusion defects (hazard ratio, 2.36 [95% CI, 1.93-2.89]; P<0.001). Mortality risk decreased across increasing MFR deciles, ranging from hazard ratio, 2.73 (95% CI, 2.39-3.11) to hazard ratio, 0.35 (95% CI, 0.25-0.50).

Conclusions: In this large multicenter cohort, MFR derived from ¹³N-ammonia PET myocardial perfusion imaging is a strong, independent predictor of all-cause mortality, even in patients with normal perfusion. An MFR of ≤2.0 identifies elevated risk, while higher values are associated with improved survival. These findings support the routine integration of MFR to enhance risk stratification in patients with suspected or known coronary artery disease.

Background: Depression is linked to major adverse cardiac events (MACE), yet the role of stress-related neural activity-previously implicated in stress and anxiety in mediating this association remains unclear. Because anxiety and depression frequently co-occur and share neurobiological pathways, we hypothesized that the relationship between depression, anxiety, and their co-occurrence with MACE is partially mediated by increased stress-related neural activity and related autonomic-immune mechanisms.

Methods: Data were obtained from participants enrolled in the Mass General Brigham Biobank (2010-2020). A subset underwent ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography imaging to assess stress-related neural activity, defined as the ratio of amygdala to background prefrontal cortical activity. Heart rate variability and CRP (C-reactive protein) served as indicators of autonomic activity and systemic inflammation. Depression and anxiety were determined at enrollment, and MACE was identified during follow-up using International Classification of Diseases codes. Each exposure (depression, anxiety, or concurrent anxiety plus depression) was modeled separately against study outcomes using linear and Cox regressions.

Results: Of 85 551 study subjects, 3078 (3.6%) participants developed MACE, over a median 3.4 years follow-up (interquartile range, 1.9-4.8). Depression was associated with higher MACE risk (hazard ratio, 1.24 [95% CI, 1.14-1.34]; P<0.001), with stronger associations for concurrent anxiety plus depression (hazard ratio, 1.35 [1.23-1.49]; P<0.001) and remained significant after adjustment for demographics, lifestyle, cardiovascular, and socioeconomic factors. In subsamples with available imaging (N=1123) or biomarkers (heart rate variability, N=7862; CRP, N=12 906), depression was linked to higher amygdala-to-cortex activity ratio (β=0.16; P=0.006), lower heart rate variability (β=-0.20; P<0.001), and higher CRP (β=0.14; P<0.001). Mediation analyses showed indirect effects of amygdala-to-cortex activity ratio, heart rate variability, and CRP on the depression-MACE relationship (log odds ratios, 0.04, 0.04, and 0.02, respectively; all P<0.05). Similar associations were observed for anxiety or concurrent anxiety plus depression.

Conclusions: Depression and anxiety independently associate with increased MACE risk, partly mediated by heightened stress-related neural activity and autonomic-immune dysregulation. The risk is greatest among those with both conditions, underscoring shared stress-related pathophysiology.

Percutaneous coronary intervention outcomes rely heavily on accurate lesion assessment and procedural planning. Invasive tools, such as fractional flow reserve, nonhyperemic pressure ratios, intravascular ultrasound, and optical coherence tomography, provide essential physiological and anatomic insights but are resource-intensive, prolong procedures, and increase contrast and radiation exposure. Coronary computed tomography (CT) angiography has emerged as a noninvasive modality with high diagnostic accuracy for coronary artery disease, capable of detailing plaque composition, lesion length, and vessel geometry. With the integration of CT-derived fractional flow reserve and CT myocardial perfusion imaging, coronary CT angiography now offers both anatomic and functional evaluation, bridging diagnostic and interventional decision-making. Despite guideline endorsement for coronary artery disease diagnosis, its role in guiding percutaneous coronary intervention strategies remains underutilized and absent from revascularization recommendations. This review outlines a practical, step-by-step framework for integrating coronary CT angiography into contemporary percutaneous coronary intervention planning, covering acquisition protocols, software platforms, lesion assessment, and stent strategy optimization. It also explores emerging intraprocedural applications, including fusion imaging, augmented and virtual reality, and holographic visualization. By synthesizing current evidence and identifying gaps, this review positions coronary CT angiography as a promising adjunct in precision-based percutaneous coronary intervention.