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

BACKGROUND: People with 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 (ECV, 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, total 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 71.3% failed to achieve persistent viral suppression (42.2% with peak viral load < 200 cp/mL). Overall, WWH showed higher nT1 than women without HIV (WWOH) after full adjustment. This higher nT1 was more pronounced in those with antecedent or current viremia or nadir CD4+ count < 200 cells/µL, the latter also associated with higher ECV. 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 WWOH, 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.

Multi-Ethnic Study of Atherosclerosis: Relationship between Left Ventricular Shape at Cardiac MRI and 10-year Outcomes.

Background Left ventricular (LV) subclinical remodeling is associated with adverse outcomes and indicates mechanisms of disease development. Standard metrics such as LV mass and volumes may not capture the full range of remodeling. Purpose To quantify the relationship between LV three-dimensional shape at MRI and incident cardiovascular events over 10 years. Materials and Methods In this retrospective study, 5098 participants from the Multi-Ethnic Study of Atherosclerosis who were free of clinical cardiovascular disease underwent cardiac MRI from 2000 to 2002. LV shape models were automatically generated using a machine learning workflow. Event-specific remodeling signatures were computed using partial least squares regression, and random survival forests were used to determine which features were most associated with incident heart failure (HF), coronary heart disease (CHD), and cardiovascular disease (CVD) events over a 10-year follow-up period. The discrimination improvement of adding LV shape to traditional cardiovascular risk factors, coronary artery calcium scores, and N-terminal pro-brain natriuretic peptide levels was assessed using the index of prediction accuracy and time-dependent area under the receiver operating characteristic curve (AUC). Kaplan-Meier survival curves were used to illustrate the ability of remodeling signatures to predict the end points. Results Overall, 4618 participants had sufficient three-dimensional MRI information to generate patient-specific LV models (mean age, 60.6 years ± 9.9 [SD]; 2540 women). Among these participants, 147 had HF, 317 had CHD, and 455 had CVD events. The addition of LV remodeling signatures to traditional cardiovascular risk factors improved the mean AUC for 10-year survival prediction and achieved better performance than LV mass and volumes; HF (AUC, 0.83 ± 0.01 and 0.81 ± 0.01, respectively; P < .05), CHD (AUC, 0.77 ± 0.01 and 0.75 ± 0.01, respectively; P < .05), and CVD (AUC, 0.78 ± 0.0 and 0.76 ± 0.0, respectively; P < .05). Kaplan-Meier analysis demonstrated that participants with high-risk HF remodeling signatures had a 10-year survival rate of 56% compared with 95% for those with low-risk scores. Conclusion Left ventricular event-specific remodeling signatures were more predictive of heart failure, coronary heart disease, and cardiovascular disease events over 10 years than standard mass and volume measures and enable an automatic personalized medicine approach to tracking remodeling. © RSNA, 2022 Online supplemental material is available for this article.

Vascular aneurysms in Ehlers-Danlos syndrome subtypes: A systematic review.

Aneurysmal lesions are commonly seen in Ehlers-Danlos Syndrome (EDS). To better identify the regional and vessel-specific spectrum of aneurysms in different subtypes of EDS, we performed a systematic review. We searched Medline for relevant studies from 1963 to April 2022. Studies providing a report of any EDS subtype by genetic diagnosis, histologic analysis, or clinical criteria were included. A total of 448 patients from 220 studies were included. 720 vessel-specific aneurysms were reported: 386 in the abdominopelvic area, 165 in the intracranial region, 98 in the thorax, 2 in the extremities, and 6 in the venous system. In 27 out of the 65 patients with ruptured aneurysms, the ruptured aneurysm was the initial presentation. Multiple aneurysms were present in 163 out of 249 patients who had been systematically evaluated for other locations of aneurysms. The head and neck and abdominopelvic regions are two potential foci for aneurysm formation in patients with EDS. The aneurysm development in EDS is not confined to arteries; the venous system and cardiac septa may also be affected. Many patients develop multiple aneurysms, either at the time of the initial presentation or throughout their lifetime and aneurysm formation or rupture may be the first presentation of EDS.

Thoracic Aortic Volume as a Predictor of Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: It is unclear whether thoracic aortic volume (TAV) is useful for cardiovascular (CV) disease prognosis and risk assessment. PURPOSE: This study evaluated cross-sectional associations of TAV with CV risk factors, and longitudinal association with incident CV events in the multiethnic study of atherosclerosis. STUDY TYPE: Retrospective cohort analysis of prospective data. POPULATION: 1182 participants (69 ± 9 years, 54% female, 37% Caucasian, 18% Chinese, 31% African American, 14% Hispanic, 60% hypertensive, and 20% diabetic) without prior CV disease. FIELD STRENGTH AND SEQUENCES: Axial black-blood turbo spin echo or bright blood steady-state free precession images on 1.5T scanners. ASSESSMENT: TAV was calculated using Simpson's method from axial images, and included the ascending arch and descending segments. Traditional CV risk factors were assessed at the time of MRI. CV outcomes over a 9-year follow-up period were recorded and represented a composite of stroke, stroke death, coronary heart disease (CHD), CHD death, atherosclerotic death, and CVD death. STATISTICAL TESTS: Multivariable linear regression models adjusted for height and weight were used to determine the relationship (ß coefficient) between TAV and CV risk factors. Cox regression models assessed the association of TAV and incident CV events. A P-value of <0.05 was deemed statistically significant. RESULTS: Mean TAV was = 139 ± 41 mL. In multivariable regression, TAV was directly associated with age (ß = 1.6), male gender (ß = 23.9), systolic blood pressure (ß = 0.1), and hypertension medication use (ß = 7.9); and inversely associated with lipid medication use (ß = -5.3) and treated diabetes (ß = -8.9). Compared to Caucasians, Chinese Americans had higher TAV (ß = 11.4), while African Americans had lower TAV (ß = -7.0). Higher TAV was independently associated with incident CV events (HR: 1.057 per 10 mL). CONCLUSION: Greater TAV is associated with incident CV events, increased age, and hypertension in a large multiethnic population while treated diabetes and lipid medication use were associated with lower TAV. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Multivariate longitudinal data for survival analysis of cardiovascular event prediction in young adults: insights from a comparative explainable study.

BACKGROUND: Multivariate longitudinal data are under-utilized for survival analysis compared to cross-sectional data (CS - data collected once across cohort). Particularly in cardiovascular risk prediction, despite available methods of longitudinal data analysis, the value of longitudinal information has not been established in terms of improved predictive accuracy and clinical applicability. METHODS: We investigated the value of longitudinal data over and above the use of cross-sectional data via 6 distinct modeling strategies from statistics, machine learning, and deep learning that incorporate repeated measures for survival analysis of the time-to-cardiovascular event in the Coronary Artery Risk Development in Young Adults (CARDIA) cohort. We then examined and compared the use of model-specific interpretability methods (Random Survival Forest Variable Importance) and model-agnostic methods (SHapley Additive exPlanation (SHAP) and Temporal Importance Model Explanation (TIME)) in cardiovascular risk prediction using the top-performing models. RESULTS: In a cohort of 3539 participants, longitudinal information from 35 variables that were repeatedly collected in 6 exam visits over 15 years improved subsequent long-term (17 years after) risk prediction by up to 8.3% in C-index compared to using baseline data (0.78 vs. 0.72), and up to approximately 4% compared to using the last observed CS data (0.75). Time-varying AUC was also higher in models using longitudinal data (0.86-0.87 at 5 years, 0.79-0.81 at 10 years) than using baseline or last observed CS data (0.80-0.86 at 5 years, 0.73-0.77 at 10 years). Comparative model interpretability analysis revealed the impact of longitudinal variables on model prediction on both the individual and global scales among different modeling strategies, as well as identifying the best time windows and best timing within that window for event prediction. The best strategy to incorporate longitudinal data for accuracy was time series massive feature extraction, and the easiest interpretable strategy was trajectory clustering. CONCLUSION: Our analysis demonstrates the added value of longitudinal data in predictive accuracy and epidemiological utility in cardiovascular risk survival analysis in young adults via a unified, scalable framework that compares model performance and explainability. The framework can be extended to a larger number of variables and other longitudinal modeling methods. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00005130, Registration Date: 26/05/2000.

Change in Left Atrioventricular Coupling Index to Predict Incident Atrial Fibrillation: The Multi-Ethnic Study of Atherosclerosis (MESA).

Background Left atrial (LA) and left ventricular (LV) structural and functional parameters have independent prognostic values as predictors of atrial fibrillation (AF). Purpose To investigate the prognostic value of a left atrioventricular coupling index (LACI) and average annualized change in LACI (hereafter, ΔLACI) measured by cardiac MRI to predict incident AF in a population-based sample from the Multi-Ethnic Study of Atherosclerosis (MESA). Materials and Methods In a secondary analysis of the prospective MESA, 1911 study participants without clinically recognized AF and cardiovascular disease at baseline had LACI assessed with cardiac MRI at baseline (examination 1, 2000-2002) and 10 years later (examination 5, 2010-2012). LACI was defined as the ratio of LA to LV end-diastolic volumes. Univariable and multivariable Cox proportional hazard models were used to evaluate the associations of LACI and average ΔLACI with incident AF. Results Among the 1911 participants (mean age, 59 years ± 9 [standard deviation]; 907 men), 87 incident AF events occurred over 3.9 years ± 0.9 after the second imaging (examination 5). After adjustment for traditional risk factors, greater LACI and ΔLACI were independently associated with AF (hazard ratio, 1.69 [95% CI: 1.46, 1.96] and 1.71 [95% CI: 1.50, 1.94], respectively; both P < .001). Adjusted models for LACI and ΔLACI showed improvement in model discrimination compared with currently used AF risk score (Cohort for Heart and Aging Research in Genomic Epidemiology-Atrial Fibrillation, or CHARGE-AF, score) model (area under receiver operating characteristic curve [AUC], 0.78 vs 0.74; and AUC, 0.80 vs 0.74, respectively; both P < .001); and to the final model including individual LA or LV parameters for predicting AF incidence (AUC, 0.78 vs 0.76; and AUC, 0.80 vs 0.78, respectively; both P < .001). Conclusion Atrioventricular coupling (left atrioventricular coupling index [LACI]) and coupling change (annual change in LACI) were strong predictors for atrial fibrillation (AF) in a multiethnic population. Both had incremental prognostic value for predicting AF over traditional risk factors, and superior discrimination compared with the Cohort for Heart and Aging Research in Genomic Epidemiology-Atrial Fibrillation, or CHARGE-AF, score and to individual left atrial or left ventricular parameters. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Leiner in this issue.

Deep Learning-based Automated Aortic Area and Distensibility Assessment: the Multi-Ethnic Study of Atherosclerosis (MESA).

This study details application of deep learning for automatic segmentation of the ascending and descending aorta from 2D phase-contrast cine magnetic resonance imaging for automatic aortic analysis on the large MESA cohort with assessment on an external cohort of thoracic aortic aneurysm (TAA) patients. This study includes images and corresponding analysis of the ascending and descending aorta at the pulmonary artery bifurcation from the MESA study. Train, validation, and internal test sets consisted of 1123 studies (24,282 images), 374 studies (8067 images), and 375 studies (8069 images), respectively. The external test set of TAAs consisted of 37 studies (3224 images). CNN performance was evaluated utilizing a dice coefficient and concordance correlation coefficients (CCC) of geometric parameters. Dice coefficients were as high as 97.55% (CI: 97.47-97.62%) and 93.56% (CI: 84.63-96.68%) on the internal and external test of TAAs, respectively. CCC for maximum and minimum and ascending aortic area were 0.969 and 0.950, respectively, on the internal test set and 0.997 and 0.995, respectively, for the external test. The absolute differences between manual and deep learning segmentations for ascending and descending aortic distensibility were 0.0194 × 10-4 ± 9.67 × 10-4 and 0.002 ± 0.001 mmHg-1, respectively, on the internal test set and 0.44 × 10-4 ± 20.4 × 10-4 and 0.002 ± 0.001 mmHg-1, respectively, on the external test set. We successfully developed a U-Net-based aortic segmentation and analysis algorithm in both MESA and in external cases of TAA.

Integrating baseline MR imaging biomarkers into BCLC and CLIP improves overall survival prediction of patients with hepatocellular carcinoma (HCC).

OBJECTIVES: We aimed to evaluate the independent predictive role of baseline imaging biomarkers for overall survival (OS) and transplant-free survival (TFS) in patients with HCC and assess the incremental value of these biomarkers to current staging systems. METHODS: In this retrospective IRB approved study, the clinical, laboratory, and imaging parameters of 304 HCC patients were collected. Cox regression model was utilized to identify the potential predictors of survival. Recursive partitioning test was utilized to identify the optimal ADC cutoff for stratifying patients' OS. Patients were stratified based on Barcelona Clinic Liver Cancer (BCLC) and Cancer of the Liver Italian Program (CLIP). Binary ADC value (above vs. below the cutoff) and tumor margin (well- vs. ill-defined) were integrated into BCLC and CLIP. OS and TFS was compared for patients based on standard criteria with and without imaging biomarkers. RESULTS: At baseline, patients with low tumor ADC and well-defined tumor margin (favorable imaging biomarkers) had longer survival, as compared to those with high ADC and ill-defined tumor margin (unfavorable imaging biomarkers) (median OS of 43 months vs. 7 months, respectively) (p < 0.001). Tumor ADC and tumor margin remained strong independent predictors of survival after adjustment for demographics, BCLC and CLIP staging, and tumor burden. Incorporating ADC and tumor margin improved performance of OS prediction by 9% in BCLC group and 6% in CLIP group. CONCLUSION: Incorporating ADC and tumor margin to current staging systems for HCC significantly improve prediction of OS and TFS of these criteria. KEY POINTS: • ADC and tumor margin are predictors of overall survival in HCC patients, independent of clinical, laboratory, and other imaging variables. • Adding ADC and tumor margin improved the prognostic value of BCLC and CLIP criteria by 9% and 6%, respectively. • High ADC and ill-defined tumor margin at baseline predicted poor survival, regardless of patient's liver function and general health status.

Extracellular volume-guided late gadolinium enhancement analysis for non-ischemic cardiomyopathy: The Women's Interagency HIV Study.

BACKGROUND: Quantification of non-ischemic myocardial scar remains a challenge due to the patchy diffuse nature of fibrosis. Extracellular volume (ECV) to guide late gadolinium enhancement (LGE) analysis may achieve a robust scar assessment. METHODS: Three cohorts of 80 non-ischemic-training, 20 non-ischemic-validation, and 10 ischemic-validation were prospectively enrolled and underwent 3.0 Tesla cardiac MRI. An ECV cutoff to differentiate LGE scar from non-scar was identified in the training cohort from the receiver-operating characteristic curve analysis, by comparing the ECV value against the visually-determined presence/absence of the LGE scar at the highest signal intensity (SI) area of the mid-left ventricle (LV) LGE. Based on the ECV cutoff, an LGE semi-automatic threshold of n-times of standard-deviation (n-SD) above the remote-myocardium SI was optimized in the individual cases ensuring correspondence between LGE and ECV images. The inter-method agreement of scar amount in comparison with manual (for non-ischemic) or full-width half-maximum (FWHM, for ischemic) was assessed. Intra- and inter-observer reproducibility were investigated in a randomly chosen subset of 40 non-ischemic and 10 ischemic cases. RESULTS: The non-ischemic groups were all female with the HIV positive rate of 73.8% (training) and 80% (validation). The ischemic group was all male with reduced LV function. An ECV cutoff of 31.5% achieved optimum performance (sensitivity: 90%, specificity: 86.7% in training; sensitivity: 100%, specificity: 81.8% in validation dataset). The identified n-SD threshold varied widely (range 3 SD-18 SD), and was independent of scar amount (ß = -0.01, p = 0.92). In the non-ischemic cohorts, results suggested that the manual LGE assessment overestimated scar (%) in comparison to ECV-guided analysis [training: 4.5 (3.2-6.4) vs. 0.92 (0.1-2.1); validation: 2.5 (1.2-3.7) vs. 0.2 (0-1.6); P < 0.01 for both]. Intra- and inter-observer analyses of global scar (%) showed higher reproducibility in ECV-guided than manual analysis with CCC = 0.94 and 0.78 versus CCC = 0.86 and 0.73, respectively (P < 0.01 for all). In ischemic validation, the ECV-guided LGE analysis showed a comparable scar amount and reproducibility with the FWHM. CONCLUSIONS: ECV-guided LGE analysis is a robust scar quantification method for a non-ischemic cohort. Trial registration ClinicalTrials.gov; NCT00000797, retrospectively-registered 2 November 1999; NCT02501811, registered 15 July 2015.

Natural Selection on Genes Related to Cardiovascular Health in High-Altitude Adapted Andeans.

The increase in red blood cell mass (polycythemia) due to the reduced oxygen availability (hypoxia) of residence at high altitude or other conditions is generally thought to be beneficial in terms of increasing tissue oxygen supply. However, the extreme polycythemia and accompanying increased mortality due to heart failure in chronic mountain sickness most likely reduces fitness. Tibetan highlanders have adapted to high altitude, possibly in part via the selection of genetic variants associated with reduced polycythemic response to hypoxia. In contrast, high-altitude-adapted Quechua- and Aymara-speaking inhabitants of the Andean Altiplano are not protected from high-altitude polycythemia in the same way, yet they exhibit other adaptive features for which the genetic underpinnings remain obscure. Here, we used whole-genome sequencing to scan high-altitude Andeans for signals of selection. The genes showing the strongest evidence of selection-including BRINP3, NOS2, and TBX5-are associated with cardiovascular development and function but are not in the response-to-hypoxia pathway. Using association mapping, we demonstrated that the haplotypes under selection are associated with phenotypic variations related to cardiovascular health. We hypothesize that selection in response to hypoxia in Andeans could have vascular effects and could serve to mitigate the deleterious effects of polycythemia rather than reduce polycythemia itself.

Association of right atrial structure with incident atrial fibrillation: a longitudinal cohort cardiovascular magnetic resonance study from the Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: While studies of the left atrium (LA) have demonstrated associations between volumes and emptying fraction with atrial fibrillation (AF), the contribution of right atrial (RA) abnormalities to incident AF remains poorly understood. OBJECTIVES: Assess the association between RA structure and function with incident AF using feature-tracking cardiovascular magnetic resonance (CMR). METHODS: This is a prospective cohort study of all participants in the Multi-Ethnic Study of Atherosclerosis with baseline CMR, sinus rhythm, and free of clinical cardiovascular disease at study initiation. RA volume, strain, and emptying fraction in participants with incident AF (n = 368) were compared against AF-free (n = 2779). Cox proportional-hazards models assessed association between variables. RESULTS: Participants were aged 60 ± 10 yrs., 55% female, and followed an average 11.2 years. Individuals developing AF had higher baseline RA maximum volume index (mean ± standard deviation [SD]: 24 ± 9 vs 22 ± 8 mL/m2, p = 0.002) and minimum volume index (13 ± 7 vs 12 ± 6 mL/m2, p < 0.001), and lower baseline RA emptying fraction (45 ± 15% vs 47 ± 15%, p = 0.02), peak global strain (34 ± 17% vs 36 ± 19%, p < 0.001), and peak free-wall strain (40 ± 23% vs 42 ± 26%, p = 0.049) compared with the AF-free population. After adjusting for traditional cardiovascular risk factors and LA volume and function, we found RA maximum volume index (hazards ratio [HR]: 1.13 per SD, p = 0.041) and minimum volume index (HR: 1.12 per SD, p = 0.037) were independently associated with incident AF. CONCLUSIONS: In a large multiethnic population, higher RA volume indices were independently associated with incident AF after adjustment for conventional cardiovascular risk factors and LA parameters. It is unclear if this predictive value persists when additional adjustment is made for ventricular parameters.

Reference ranges ("normal values") for cardiovascular magnetic resonance (CMR) in adults and children: 2020 update.

Cardiovascular magnetic resonance (CMR) enables assessment and quantification of morphological and functional parameters of the heart, including chamber size and function, diameters of the aorta and pulmonary arteries, flow and myocardial relaxation times. Knowledge of reference ranges ("normal values") for quantitative CMR is crucial to interpretation of results and to distinguish normal from disease. Compared to the previous version of this review published in 2015, we present updated and expanded reference values for morphological and functional CMR parameters of the cardiovascular system based on the peer-reviewed literature and current CMR techniques. Further, databases and references for deep learning methods are included.

Non-contrast coronary magnetic resonance angiography: current frontiers and future horizons.

Coronary magnetic resonance angiography (coronary MRA) is advantageous in its ability to assess coronary artery morphology and function without ionizing radiation or contrast media. However, technical limitations including reduced spatial resolution, long acquisition times, and low signal-to-noise ratios prevent it from clinical routine utilization. Nonetheless, each of these limitations can be specifically addressed by a combination of novel technologies including super-resolution imaging, compressed sensing, and deep-learning reconstruction. In this paper, we first review the current clinical use and motivations for non-contrast coronary MRA, discuss currently available coronary MRA techniques, and highlight current technical developments that hold unique potential to optimize coronary MRA image acquisition and post-processing. In the final section, we examine the various research-based coronary MRA methods and metrics that can be leveraged to assess coronary stenosis severity, physiological function, and atherosclerotic plaque characterization. We specifically discuss how such technologies may contribute to the clinical translation of coronary MRA into a robust modality for routine clinical use.

Reproducibility and Changes in Vena Caval Blood Flow by Using 4D Flow MRI in Pulmonary Emphysema and Chronic Obstructive Pulmonary Disease (COPD): The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Substudy.

BackgroundChronic obstructive pulmonary disease (COPD) is associated with hemodynamic changes in the pulmonary vasculature. However, cardiac effects are not fully understood and vary by phenotype of chronic lower respiratory disease.PurposeTo use four-dimensional (4D) flow MRI for comprehensive assessment of the right-sided cardiovascular system, assess its interrater and intraobserver reproducibility, and examine associations with venous return to the right heart in individuals with chronic COPD and emphysema.Materials and MethodsThe Multi-Ethnic Study of Atherosclerosis COPD substudy prospectively recruited participants who smoked and who had COPD and nested control participants from population-based samples. Electrocardiography and respiratory gated 4D flow 1.5-T MRI was performed at three sites with full volumetric coverage of the thoracic vessels in 2014-2017 with postbronchodilator spirometry and inspiratory chest CT to quantify percent emphysema. Net flow, peak velocity, retrograde flow, and retrograde fraction were measured on 14 analysis planes. Interrater reproducibility was assessed by two independent observers, and the principle of conservation of mass was employed to evaluate the internal consistency of flow measures. Partial correlation coefficients were adjusted for age, sex, race/ethnicity, height, weight, and smoking status.ResultsAmong 70 participants (29 participants with COPD [mean age, 73.5 years ± 8.1 {standard deviation}; 20 men] and 41 control participants [mean age, 71.0 years ± 6.1; 22 men]), the interrater reproducibility of the 4D flow MRI measures was good to excellent (intraclass correlation coefficient range, 0.73-0.98), as was the internal consistency. There were no statistically significant differences in venous flow parameters according to COPD severity (P > .05). Greater percent emphysema at CT was associated with greater regurgitant flow in the superior and inferior caval veins and tricuspid valve (adjusted r = 0.28-0.55; all P < .01), particularly in the superior vena cava.ConclusionFour-dimensional flow MRI had good-to-excellent observer variability and flow consistency. Percent emphysema at CT was associated with statistically significant differences in retrograde flow, greatest in the superior vena cava.© RSNA, 2019Online supplemental material is available for this article.See also the editorial by Choe in this issue.

Regional abnormalities on cardiac magnetic resonance imaging and arrhythmic events in patients with cardiac sarcoidosis.

BACKGROUND: Patients with cardiac sarcoidosis (CS) may present with arrhythmic events (AE): atrioventricular block (AVB) and/ or ventricular arrhythmias (VA). We sought to: (a) use regional analysis of cardiac magnetic resonance imaging (CMR) to describe anatomic and functional phenotypes of patients with CS and AE; (b) Assess the association of regional CMR abnormalities with the combined endpoint of death, heart transplantation (HT) and AE; and (c) use machine learning (ML) to predict the combined endpoint based on CMR features. METHODS: we included 76 patients with CS and CMR. We analyzed cine images to determine regional longitudinal (LS) and radial strain (RS); and late gadolinium enhancement imaging to determine regional scar burden (%scar). RESULTS: Patients with AVB (n = 7), compared with those without, had higher %scar in the anterior (21.8 ± 27.4 vs 5.1 ± 8.9; P = 0.0005) and anteroseptal (19.3 ± 24.5 vs 3.5 ± 5.5; P < .0001) walls. Patients with VA (n = 12), compared with those without, had higher %scar in the basal inferoseptum (20.4 ± 30.8 vs 8.3 ± 13.4; P = .03). During mean follow-up of 4.4 ± 3.3 years, four patients died or underwent HT; eight had VA; and zero developed AVB. Multiple regional abnormalities were associated with the combined endpoint, including scar in the anteroseptal wall (HR 1.06 [1.02-1.09] per 1%scar increase, P = .002). The ML algorithm predicted the combined endpoint with a C-statistic of 0.91. CONCLUSION: Regional CMR abnormalities are associated with AE in patients with CS.

Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of Atherosclerosis.

RATIONALE: Machine learning may be useful to characterize cardiovascular risk, predict outcomes, and identify biomarkers in population studies. OBJECTIVE: To test the ability of random survival forests, a machine learning technique, to predict 6 cardiovascular outcomes in comparison to standard cardiovascular risk scores. METHODS AND RESULTS: We included participants from the MESA (Multi-Ethnic Study of Atherosclerosis). Baseline measurements were used to predict cardiovascular outcomes over 12 years of follow-up. MESA was designed to study progression of subclinical disease to cardiovascular events where participants were initially free of cardiovascular disease. All 6814 participants from MESA, aged 45 to 84 years, from 4 ethnicities, and 6 centers across the United States were included. Seven-hundred thirty-five variables from imaging and noninvasive tests, questionnaires, and biomarker panels were obtained. We used the random survival forests technique to identify the top-20 predictors of each outcome. Imaging, electrocardiography, and serum biomarkers featured heavily on the top-20 lists as opposed to traditional cardiovascular risk factors. Age was the most important predictor for all-cause mortality. Fasting glucose levels and carotid ultrasonography measures were important predictors of stroke. Coronary Artery Calcium score was the most important predictor of coronary heart disease and all atherosclerotic cardiovascular disease combined outcomes. Left ventricular structure and function and cardiac troponin-T were among the top predictors for incident heart failure. Creatinine, age, and ankle-brachial index were among the top predictors of atrial fibrillation. TNF-α (tissue necrosis factor-α) and IL (interleukin)-2 soluble receptors and NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) levels were important across all outcomes. The random survival forests technique performed better than established risk scores with increased prediction accuracy (decreased Brier score by 10%-25%). CONCLUSIONS: Machine learning in conjunction with deep phenotyping improves prediction accuracy in cardiovascular event prediction in an initially asymptomatic population. These methods may lead to greater insights on subclinical disease markers without apriori assumptions of causality. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00005487.