HIV, HIV-Specific Factors, and Myocardial Disease in Women.

BACKGROUND: People with human immunodeficiency virus (HIV) (PWH) have an increased risk of cardiovascular disease (CVD). Cardiac magnetic resonance (CMR) has documented higher myocardial fibrosis, inflammation, and steatosis in PWH, but studies have mostly relied on healthy volunteers as comparators and focused on men. METHODS: We investigated the associations of HIV and HIV-specific factors with CMR phenotypes in female participants enrolled in the Women's Interagency HIV Study's New York and San Francisco sites. Primary phenotypes included myocardial native (n) T1 (fibro-inflammation), extracellular volume fraction (fibrosis), and triglyceride content (steatosis). Associations were evaluated with multivariable linear regression, and results pooled or meta-analyzed across centers. RESULTS: Among 261 women with HIV (WWH, N = 362), 76.2% had undetectable viremia at CMR. For the 82.8% receiving continuous antiretroviral therapy (ART) in the preceding 5 years, adherence was 51.7%, and 69.4% failed to achieve persistent viral suppression (40.7% with peak viral load <200 cp/mL). Overall, WWH showed higher nT1 than women without HIV after full adjustment. This higher nT1 was more pronounced in those with antecedent or current viremia or nadir CD4+ count <200 cells/µL, with the latter also associated with higher extracellular volume fraction. WWH and current CD4+ count <200 cells/µL had less cardiomyocyte steatosis. Cumulative exposure to specific ART showed no associations. CONCLUSIONS: Compared with sociodemographically similar women without HIV, WWH on ART exhibit higher myocardial fibro-inflammation, which is more prominent with unsuppressed viremia or CD4+ lymphopenia. These findings support the importance of improved ART adherence strategies, along with better understanding of latent infection, to mitigate cardiac end-organ damage in this population.

Differential Stroke Volume between Left and Right Ventricles as a Predictor of Clinical Outcomes: The MESA Study.

Background Valvular heart disease and intracardiac shunts can disrupt the balance between left ventricular (LV) and right ventricular (RV) stroke volumes. However, the prognostic value of such imbalances has not been established among asymptomatic individuals. Purpose To assess the association between differential ventricular stroke volumes quantified using cardiac MRI and clinical outcomes in individuals without cardiovascular disease. Materials and Methods This secondary analysis of a prospective study included participants without cardiovascular disease at enrollment (July 2000 to July 2002) who underwent cardiac MRI. Differences in stroke volume were calculated as LV stroke volume minus RV stroke volume, and participants were categorized as having balanced (greater than or equal to -30 mL to ≤30 mL), negative (less than -30 mL), or positive (>30 mL) differential stroke volumes. Multivariable Cox proportional hazard regression models were used to test the association between differences in stroke volume and adverse outcomes. Results A cohort of 4058 participants (mean age, 61.4 years ± 10 [SD]; 2120 female) were included and followed up for a median of 18.4 years (IQR, 18.3-18.5 years). During follow-up, 1006 participants died, 235 participants developed heart failure, and 764 participants developed atrial fibrillation. Compared with participants who had a balanced differential stroke volume, those with an increased differential stroke volume showed a higher risk of mortality (hazard ratio [HR], 1.73 [95% CI: 1.12, 2.67]; P = .01), heart failure (HR, 2.40 [95% CI: 1.11, 5.20]; P = .03), and atrial fibrillation (HR, 1.89 [95% CI: 1.16, 3.08]; P = .01) in adjusted models. Participants in the negative group, with a decreased differential stroke volume, showed an increased risk of heart failure compared with those in the balanced group (HR, 2.09 [95% CI: 1.09, 3.99]; P = .03); however, this was no longer observed after adjusting for baseline LV function (P = .34). Conclusion Participants without cardiovascular disease at the time of study enrollment who had an LV stroke volume exceeding the RV stroke volume by greater than 30 mL had an increased risk of mortality, heart failure, and atrial fibrillation compared with those with balanced stroke volumes. ClinicalTrials.gov Identifier: NCT00005487 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Almeida in this issue.

Poor cardiac output reserve in pulmonary arterial hypertension is associated with right ventricular stiffness and impaired interventricular dependence.

BACKGROUND: Pulmonary arterial hypertension (PAH) is characterised by poor exercise tolerance. The contribution of right ventricular (RV) diastolic function to the augmentation of cardiac output during exercise is not known. This study leverages pressure-volume (P-V) loop analysis to characterise the impact of RV diastology on poor flow augmentation during exercise in PAH. METHODS: RV P-V loops were measured in 41 PAH patients at rest and during supine bike exercise. Patients were stratified by median change in cardiac index (CI) during exercise into two groups: high and low CI reserve. Indices of diastolic function (end-diastolic elastance (E ed)) and ventricular interdependence (left ventricular transmural pressure (LVTMP)) were compared at matched exercise stages. RESULTS: Compared to patients with high CI reserve, those with low reserve exhibited lower exercise stroke volume (36 versus 49 mL·m-2; p=0.0001), with higher associated exercise afterload (effective arterial elastance (E a) 1.76 versus 0.90 mmHg·mL-1; p<0.0001), RV stiffness (E ed 0.68 versus 0.26 mmHg·mL-1; p=0.003) and right-sided pressures (right atrial pressure 14 versus 8 mmHg; p=0.002). Higher right-sided pressures led to significantly lower LV filling among the low CI reserve subjects (LVTMP -4.6 versus 3.2 mmHg; p=0.0001). Interestingly, low exercise flow reserve correlated significantly with high afterload and RV stiffness, but not with RV contractility nor RV-PA coupling. CONCLUSIONS: Patients with poor exercise CI reserve exhibit poor exercise RV afterload, stiffness and right-sided filling pressures that depress LV filling and stroke work. High afterload and RV stiffness were the best correlates to low flow reserve in PAH. Exercise unmasked significant pathophysiological PAH differences unapparent at rest.

MRI-Based Breast Cancer Classification and Localization by Multiparametric Feature Extraction and Combination Using Deep Learning.

BACKGROUND: Deep learning (DL) have been reported feasible in breast MRI. However, the effectiveness of DL method in mpMRI combinations for breast cancer detection has not been well investigated. PURPOSE: To implement a DL method for breast cancer classification and detection using feature extraction and combination from multiple sequences. STUDY TYPE: Retrospective. POPULATION: A total of 569 local cases as internal cohort (50.2 ± 11.2 years; 100% female), divided among training (218), validation (73) and testing (278); 125 cases from a public dataset as the external cohort (53.6 ± 11.5 years; 100% female). FIELD STRENGTH/SEQUENCE: T1-weighted imaging and dynamic contrast-enhanced MRI (DCE-MRI) with gradient echo sequences, T2-weighted imaging (T2WI) with spin-echo sequences, diffusion-weighted imaging with single-shot echo-planar sequence and at 1.5-T. ASSESSMENT: A convolutional neural network and long short-term memory cascaded network was implemented for lesion classification with histopathology as the ground truth for malignant and benign categories and contralateral breasts as healthy category in internal/external cohorts. BI-RADS categories were assessed by three independent radiologists as comparison, and class activation map was employed for lesion localization in internal cohort. The classification and localization performances were assessed with DCE-MRI and non-DCE sequences, respectively. STATISTICAL TESTS: Sensitivity, specificity, area under the curve (AUC), DeLong test, and Cohen's kappa for lesion classification. Sensitivity and mean squared error for localization. A P-value <0.05 was considered statistically significant. RESULTS: With the optimized mpMRI combinations, the lesion classification achieved an AUC = 0.98/0.91, sensitivity = 0.96/0.83 in the internal/external cohorts, respectively. Without DCE-MRI, the DL-based method was superior to radiologists' readings (AUC 0.96 vs. 0.90). The lesion localization achieved sensitivities of 0.97/0.93 with DCE-MRI/T2WI alone, respectively. DATA CONCLUSION: The DL method achieved high accuracy for lesion detection in the internal/external cohorts. The classification performance with a contrast agent-free combination is comparable to DCE-MRI alone and the radiologists' reading in AUC and sensitivity. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Deep learning for automatic volumetric segmentation of left ventricular myocardium and ischaemic scar from multi-slice late gadolinium enhancement cardiovascular magnetic resonance.

AIMS: This study details application of deep learning for automatic volumetric segmentation of left ventricular (LV) myocardium and scar and automated quantification of myocardial ischaemic scar burden from late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR). METHODS AND RESULTS: We included 501 images and manual segmentations of short-axis LGE-CMR from over 20 multinational sites, from which 377 studies were used for training and 124 studies from unique participants for internal validation. A third test set of 52 images was used for external evaluation. Three models, U-Net, Cascaded U-Net, and U-Net++, were trained with a novel adaptive weighted categorical cross-entropy loss function. Model performance was evaluated using concordance correlation coefficients (CCCs) for LV mass and per cent myocardial scar burden. Cascaded U-Net was found to be the best model for the quantification of LV mass and scar percentage. The model exhibited a mean difference of -5 ± 23 g for LV mass, -0.4 ± 11.2 g for scar mass, and -0.8 ± 7% for per cent scar. CCC were 0.87, 0.77, and 0.78 for LV mass, scar mass, and per cent scar burden, respectively, in the internal validation set and 0.75, 0.71, and 0.69, respectively, in the external test set. For segmental scar mass, CCC was 0.74 for apical scar, 0.91 for mid-ventricular scar, and 0.73 for basal scar, demonstrating moderate to strong agreement. CONCLUSION: We successfully trained a convolutional neural network for volumetric segmentation and analysis of LV scar burden from LGE-CMR images in a large, multinational cohort of participants with ischaemic scar.

Left atrial diastasis strain slope is a marker of hemodynamic recovery in post-ST elevation myocardial infarction: the Laser Atherectomy for STemi, Pci Analysis with Scintigraphy Study (LAST-PASS).

Background: Left atrial (LA) mechanics are strongly linked with left ventricular (LV) filling. The LA diastasis strain slope (LADSS), which spans between the passive and active LA emptying phases, may be a key indicator of the LA-LV interplay during diastole. Aim: This study aimed to investigate the LA-LV interdependencies in post-ST elevation myocardial infarction (STEMI), with particular focus on the LADSS. Materials and methods: Patients with post-anterior STEMI who received primary percutaneous coronary intervention underwent contrast cardiac magnetic resonance imaging (MRI) during acute (5-9 days post-STEMI) and chronic (at 6 months) phases. The LADSS was categorized into three groups: Groups 1, 2, and 3 representing positive, flat, and negative slopes, respectively. Cross-sectional correlates of LADSS Group 2 or 3 compared to Group 1 were identified, adjusting for demographics, LA indices, and with or without LV indices. The associations of acute phase LADSS with the recovery of LV ejection fraction (LVEF) and scar amount were investigated. Results: Sixty-six acute phase (86.4% male, 63.1 ± 11.8 years) and 59 chronic phase cardiac MRI images were investigated. The distribution across LADSS Groups 1, 2, and 3 in the acute phase was 24.2%, 28.9%, and 47.0%, respectively, whereas in the chronic phase, it was 33.9%, 22.0%, and 44.1%, respectively. LADSS Group 3 demonstrated a higher heart rate than Group 1 in the acute phase (61.9 ± 8.7 vs. 73.5 ± 11.9 bpm, p < 0.01); lower LVEF (48.7 ± 8.6 vs. 41.8 ± 9.9%, p = 0.041) and weaker LA passive strain rate (SR) (-1.1 ± 0.4 vs. -0.7 [-1.2 to -0.6] s-1, p = 0.037) in the chronic phase. Chronic phase Group 3 exhibited weaker LA passive SR [relative risk ratio (RRR) = 8.8, p = 0.012] than Group 1 after adjusting for demographics and LA indices; lower LVEF (RRR = 0.85, p < 0.01), higher heart rate (RRR = 1.1, p = 0.070), and less likelihood of being male (RRR = 0.08, p = 0.058) after full adjustment. Acute phase LADSS Groups 2 and 3 predicted poor recovery of LVEF when adjusted for demographics and LA indices; LADSS Group 2 remained a predictor in the fully adjusted model (ß = -5.8, p = 0.013). Conclusion: The LADSS serves both as a marker of current LV hemodynamics and its recovery in post-anterior STEMI. The LADSS is an important index of LA-LV interdependency during diastole. Clinical Trial Registration: https://clinicaltrials.gov/, identifier NCT03950310.

Utility of multimodal longitudinal imaging data for dynamic prediction of cardiovascular and renal disease: the CARDIA study.

Background: Medical examinations contain repeatedly measured data from multiple visits, including imaging variables collected from different modalities. However, the utility of such data for the prediction of time-to-event is unknown, and only a fraction of the data is typically used for risk prediction. We hypothesized that multimodal longitudinal imaging data could improve dynamic disease prognosis of cardiovascular and renal disease (CVRD). Methods: In a multi-centered cohort of 5,114 CARDIA participants, we included 166 longitudinal imaging variables from five imaging modalities: Echocardiography (Echo), Cardiac and Abdominal Computed Tomography (CT), Dual-Energy x-ray Absorptiometry (DEXA), Brain Magnetic Resonance Imaging (MRI) collected from young adulthood to mid-life over 30 years (1985-2016) to perform dynamic survival analysis of CVRD events using machine learning dynamic survival analysis (Dynamic-DeepHit, LTRCforest, and Extended Cox for Time-varying Covariates). Risk probabilities were continuously updated as new data were collected. Model performance was assessed using integrated AUC and C-index and compared to traditional risk factors. Results: Longitudinal imaging data, even when being irregularly collected with high missing rates, improved CVRD dynamic prediction (0.03 in integrated AUC, up to 0.05 in C-index compared to traditional risk factors; best model's C-index = 0.80-0.83 up to 20 years from baseline) from young adulthood followed up to midlife. Among imaging variables, Echo and CT variables contributed significantly to improved risk estimation. Echo measured in early adulthood predicted midlife CVRD risks almost as well as Echo measured 10-15 years later (0.01 C-index difference). The most recent CT exam provided the most accurate prediction for short-term risk estimation. Brain MRI markers provided additional information from cardiac Echo and CT variables that led to a slightly improved prediction. Conclusions: Longitudinal multimodal imaging data readily collected from follow-up exams can improve CVRD dynamic prediction. Echocardiography measured early can provide a good long-term risk estimation, while CT/calcium scoring variables carry atherosclerotic signatures that benefit more immediate risk assessment starting in middle-age.

Association of Cardiovascular Fibrosis, Remodeling, and Dysfunction With Frailty, Prefrailty, and Functional Performance: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Cardiovascular disease is associated with higher incidence of frailty. However, the nature of the mechanisms underlying this association remains unclear. The purpose of this study is to identify cardiovascular phenotypes most associated with physical frailty and functional performance in the Multi-Ethnic Study of Atherosclerosis (MESA). METHODS: As part of the MESA study, 3 045 participants underwent cardiovascular magnetic resonance and computed tomography between 2010 and 2012. Of these, 1 743 completed a Six-Minute Walk test (6MWT) and questionnaires (follow-up exam: 2016-2018) which were used to generate a binary combined frail/prefrail versus robust score according to a modified FRAIL Scale (self-report questionnaire). Multivariable logistic (binary frail outcome) or linear (6MWT) regression assessed the association between frailty and cardiovascular structure and function, aortic stiffness, coronary artery calcium, and myocardial fibrosis (ECV, extracellular volume fraction). RESULTS: Participants were 66 ±â€…8 years, 52% female at the time of imaging, and 29.4% were classified as frail or prefrail. Older age and female gender were associated with greater odds of being in the frail/prefrail group. Concentric left ventricular remodeling (odds ratio [OR] 1.89, p = .008; Coef. -52.9, p < .001), increased ECV (OR 1.10, p = .002; Coef. -4.0, p = .001), and worsening left atrial strain rate at early diastole (OR 1.56, p ≤ .001; Coef. -22.75, p = .027) were found to be associated with a greater likelihood of being in a frail state and lower 6MWT distance (m). All associations with 6MWT performance were attenuated with adjustments for risk factors whereas ECV and LA strain rate remained independently associated with frailty. CONCLUSIONS: These findings suggest a significant overlap in pathways associated with subclinical cardiac dysfunction, cardiovascular fibrosis, and physical frailty.

Change in left atrial function and volume predicts incident heart failure with preserved and reduced ejection fraction: Multi-Ethnic Study of Atherosclerosis.

AIMS: The role of change in left atrial (LA) parameters prior to the onset of heart failure (HF) remains unclear. We used cardiac magnetic resonance (CMR) imaging to investigate the relationship between longitudinal change in LA function and incident HF in a multi-ethnic population with subclinical cardiovascular disease (CVD). METHODS AND RESULTS: In this prospective multi-ethnic cohort study, 2470 participants (60 ± 9 years, 47% males), free at baseline of clinical CVD, had LA volume and function assessed via multimodality tissue tracking on CMR imaging at baseline (2000-02) and a second study 9.4 ± 0.6 years later. Free of HF, 73 participants developed incident HF [HF with preserved ejection fraction (HFpEF), n = 39; reduced ejection fraction (HFrEF), n = 34] 7.1 ± 2.1 years after the second study. An annual decrease of 1 SD unit in peak LA strain (ΔLASmax) was most strongly associated with the risk of HFpEF [subdistribution hazard ratios (HR) = 2.56, 95% confidence interval (CI) (1.34-4.90), P = 0.004] and improved model reclassification and discrimination in predicting HFpEF [C-statistic = 0.84, 95% CI (0.79-0.90); net reclassification index (NRI) = 0.34, P = 0.01; and integrated discrimination index (IDI) = 0.02, P = 0.02], whilst an annual decrease of 1 mL/m2 of pre-atrial indexed LA volumes (ΔLAVipreA) was most strongly associated with the risk of HFrEF [subdistribution HR = 1.88, 95% CI (1.44-2.45), P < 0.001] and improved model reclassification and discrimination in predicting HFrEF [C-statistic = 0.81, 95% CI (0.72-0.90); NRI = 0.31, P = 0.03; and IDI = 0.01, P = 0.50] after adjusting for event-specific risk factors and baseline LA measures. CONCLUSION: ΔLASmax and ΔLAVipreA were associated with and incrementally predictive of HFpEF and HFrEF, after adjusting for risk factors and baseline LA measures in this population of subclinical CVD.

Deep phenotyping of dementia in a multi-ethnic cardiovascular cohort: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: Our understanding of the specific aspects of vascular contributions to dementia remains unclear. OBJECTIVES: We aim to identify the correlates of incident dementia in a multi-ethnic cardiovascular cohort. METHODS: A total of 6806 participants with follow-up data for incident dementia were included. Probable dementia diagnoses were identified using hospitalization discharge diagnoses according to the International Classification of Diseases Codes (ICD). We used Random Forest analyses to identify the correlates of incident dementia and cognitive function from among 198 variables collected at the baseline MESA exam entailing demographic risk factors, medical history, anthropometry, lab biomarkers, electrocardiograms, cardiovascular magnetic resonance imaging, carotid ultrasonography, coronary artery calcium and liver fat content. Death and stroke were considered competing events. RESULTS: Over 14 years of follow-up, 326 dementia events were identified. Beyond age, the top correlates of dementia included coronary artery calcification, high sensitivity troponin, common carotid artery intima to media thickness, NT-proBNP, physical activity, pulse pressure, tumor necrosis factor-α, history of cancer, and liver to spleen attenuation ratio from computed tomography. Correlates of cognitive function included income and physical activity, body size, serum glucose, glomerular filtration rate, measures of carotid artery stiffness, alcohol use, and inflammation indexed as IL-2 and TNF soluble receptors and plasmin-antiplasmin complex. CONCLUSION: In a deeply phenotyped cardiovascular cohort we identified the key correlates of dementia beyond age as subclinical atherosclerosis and myocyte damage, vascular function, inflammation, physical activity, hepatic steatosis, and history of cancer.

Subclinical vascular composites predict clinical cardiovascular disease, stroke, and dementia: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND AND AIMS: Subclinical cardiovascular disease (CVD) measures may reflect biological pathways that contribute to increased risk for coronary heart disease (CHD) events, stroke, and dementia beyond conventional risk scores. METHODS: The Multi-Ethnic Study of Atherosclerosis (MESA) followed 6814 participants (45-84 years of age) from baseline in 2000-2002 to 2018 over 6 clinical examinations and annual follow-up interviews. MESA baseline subclinical CVD procedures included: seated and supineblood pressure, coronary calcium scan, radial artery tonometry, and carotid ultrasound. Baseline subclinical CVD measures were transformed into z-scores before factor analysis to derive composite factor scores. Time to clinical event for all-cause CVD, CHD, stroke and ICD code-based dementia events were modeled using Cox proportional hazards models reported as area under the curve (AUC) with 95% Confidence Intervals (95%CI) at 10 and 15 years of follow-up. All models included all factor scores together, and adjustment for conventional risk scores for global CVD, stroke, and dementia. RESULTS: After factor selection, 24 subclinical measures aggregated into four distinct factors representing: blood pressure, atherosclerosis, arteriosclerosis, and cardiac factors. Each factor significantly predicted time to CVD events and dementia at 10 and 15 years independent of each other and conventional risk scores. Subclinical vascular composites of atherosclerosis and arteriosclerosis best predicted time to clinical events of CVD, CHD, stroke, and dementia. These results were consistent across sex and racial and ethnic groups. CONCLUSIONS: Subclinical vascular composites of atherosclerosis and arteriosclerosis may be useful biomarkers to inform the vascular pathways contributing to events of CVD, CHD, stroke, and dementia.