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This study aims to compare ethnic difference in proximal aortic pulse wave velocity (PWV) and characteristic impedance (Zc).Increased aortic stiffness is an independent predictor of target organ damage, incident hypertension, and all-cause mortality. However, previous studies have not directly assessed proximal aortic function in Blacks, the ethnic population with disproportionately high risk for incident hypertension and target organ complications.We evaluated the multiethnic, population-based DHS (Dallas Heart Study) participants (N = 2,544, 54.2% women, 49.7% Black) who underwent cardiac magnetic resonance at 1.5-T. Aortic stiffness and Zc were determined from aortic arch PWV and lumen area measurements. Linear regression was used to evaluate ethnic differences in proximal aortic wall stiffness using aortic arch PWV and Zc as dependent variables with and without adjustment for traditional cardiovascular risk factors. Because cardiac output was significantly higher in Blacks compared to Whites and Hispanics, additional comparisons of PWV and Zc were performed after adjustment for cardiac output and peripheral vascular resistance.Compared with Whites, both Blacks and Hispanics had higher levels of aortic arch PWV (4.25, 95% confidence interval [CI]: 4.15 to 4.35 m/s, vs. 4.72, 95% CI: 4.64 to 4.81 m/s, vs. 4.48, 95% CI: 4.33 to 4.63 m/s, respectively, both p 0.05 vs. White), and Zc (64.9, 95% CI: 63.3 to 66.6 dyne·s/cmIn a multiethnic population-based-sample, Blacks and Hispanics had higher proximal aortic stiffness compared with Whites independent of blood pressure and relevant risk factors.

To assess if fully automated localization of the aorta can be achieved using phase contrast (PC) MR images.PC cardiac-gated MR images were obtained as part of a large population-based study. A fully automated process using the Hough transform was developed to localize the ascending aorta (AAo) and descending aorta (DAo). The study was designed to validate this technique by determining: (i) its performance in localizing the AAo and DAo; (ii) its accuracy in generating AAo flow volume and DAo flow volume; and (iii) its robustness on studies with pathological abnormalities or imaging artifacts.The algorithm was applied successfully on 1884 participants. In the randomly selected 50-study validation set, linear regression shows an excellent correlation between the automated (A) and manual (M) methods for AAo flow (r = 0.99) and DAo flow (r = 0.99). Bland-Altman difference analysis demonstrates strong agreement with minimal bias for: AAo flow (mean difference [A-M] = 0.47 ± 2.53 mL), and DAo flow (mean difference [A-M] = 1.74 ± 2.47 mL).A robust fully automated tool to localize the aorta and provide flow volume measurements on phase contrast MRI was validated on a large population-based study.

Purpose: Multiple biomarkers have been associated with total brain atrophy. However, little is known about their relationship to segmental atrophy in a large, multi-ethnic, population-based sample. Materials and Methods: 3D-MPRAGE brain images obtained at 3T from 2082 participants of the Dallas Heart Study (DHS) 2 were analyzed with Freesurfer and outlier analysis was performed. Divisive eigenvalue clustering of 89 brain segments yielded 24 groups with linked atrophy patterns. Plasma C-reactive protein (CRP), IL-18, homocsysteine and B-type natriuretic peptide (BNP) obtained 7 years prior during DHS 1 were available for 1343, 840, 1333 and 1331 participants, respectively. Multivariate linear regression analysis with adjustments for age, ethnicity, and gender were used to demonstrate associations between biomarkers and atrophy clusters. Results: Nine atrophy clusters were associated with CRP, three atrophy clusters were associated with IL-18, and six atrophy clusters were associated with BNP (Table 1). Homocysteine did not have any significant correlations. Conclusions: The markers studied had associations with distinct patterns of segmental atrophy indicating they may have unique interactions in different brain regions. This suggests that distinct inflammatory and other pathways may be at work in specific regions of the brain and that their localized effects may be obscured by approaches evaluating solely total brain volumes. Table 1

Introduction: White Matter Hyperintensities (WMH) have been implicated as a risk factor for motor and cognitive decline, dementia and stroke. A standard for use in clinical settings is needed to identify which cases are advanced or meet thresholds with implications for degree of impairment. The system of Fazekas is a promising candidate due to its simplicity and strong correlation with outcomes. The original Fazekas categorized deep and periventricular WMH separately. Advanced periventricular and deep WMH were later shown to have equivalent pathology and etiology. Subsequent work by De Carli showed the classification of deep and periventricular WMH on axial images to be arbitrary and suggested a common etiology for lesser degrees of WMH as well. We therefore adapted the Fazekas criteria to consider deep and periventricular WMH jointly. Questions persist about low reproducibility of grading systems. In a preliminary analysis we found frequent disagreement classifying lesions less than 3mm in diameter and decided to incorporate this threshold into our criteria to determine the effect on reproducibility and correlation of our final model with automated volumes. Hypothesis: Modification of the Fazekas grading system to consider deep and periventricular WMH jointly is less arbitrary. Simple modifications of such a system will result in a high degree of reproducibility and high correlation with automated WMH volumes. Methods: Axial 3T FLAIR MR images of the brain were obtained from community dwelling subjects. Grading measurements were applied to diameter of deep WMH and thickness of periventricular WMH. The initial system defined Grade 0 as no WMH, Grade 1 as < 10mm, Grade 2 as >=10mm but =20mm. 52 studies were read separately by 2 reviewers. We then revised grade 0 to include intensities < 3mm and grade 1 as >=3mm but Results: After modifications, inter-rater agreement for Fazekas white matter score increased from 72% to 89% with kappa increased from 0.45 to 0.78. There was good correlation of grade and automated volume (ANOVA R-Square: 0.52 P Conclusion: Advances in understanding of White Matter Hyperintensities suggest periventricular and deep lesions should be rated jointly. This modification was applied to the Fazekas system with excellent reproducibility after implementation of a 3mm size threshold as well as high agreement with automated volumes ammong community dwelling subjects.