Three Dimensional Quantification of Angiotensin II-Induced Murine Abdominal Aortic Aneurysms Using High Frequency Ultrasound

Abdominal aortic aneurysms (AAAs), a localized dilation of the vessel wall of 50% or more above normal, claims approximately 14,000 U.S. lives yearly due to aortic rupture. This commonly asymptomatic disease can only be treated by endovascular stent grafts or invasive surgery, usually after the AAA diameter reaches 5 cm. Because these treatment methods carry serious risk, stem cell therapy is being explored in order to provide a low risk option for managing smaller AAAs. To determine if stem cell therapy, once administered, could stabilize or reduce AAA growth, baseline 3D ultrasound measurements in a control group were first needed. High frequency ultrasound was used on apolipoprotein E-deficient (apoE-/-) mice given angiotensin II (AngII) from subcutaneously implanted osmotic mini pumps. This mouse model developed dissecting AAAs, containing a false and true lumen, which were clearly visualized and quantified using 3D ultrasound imaging. With this ultrasound technique, we found that aneurysm diameter, total volume, and false lumen volume all increased steadily over a period of 28 days once AAAs formed. These data suggest our noninvasive, 3D ultrasound technique can be used to monitor the progression of aneurysms that may be delayed once stem cell therapy is administered

Nonlinear Optical Microscopy of Murine Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is a cardiovascular disease characterized by dilation and weakening of the vessel wall. AAA rupture is responsible for approximately 14,000 deaths annually in the United States [1]. Nonlinear optical (NLO) microscopy presents new possibilities for analyzing AAA tissue samples from murine models. Common NLO techniques are two-photon excitation fluorescence (TPEF), which detects the intrinsic autofluorescent properties of elastin, and second-harmonic generation (SHG), which is specific for collagen fibrils. Elastin and collagen, two major extracellular matrix components, help the aortic wall withstand internal pressure. Murine AAAs were created through 1) subcutaneous continuous systemic infusion of angiotensin II (AngII) in hyperlipidemic apolipoprotein E-deficient mice and 2) by intraluminal infusion of elastase (low 0.5 U/ml and high 25 U/ml concentrations) into the infrarenal aorta of rats [2]. We imaged aneurysmal and control tissue using TPEF and SHG and compared the resulting images to sections stained with standard elastin and collagen markers. TPEF images revealed disorganized elastin sheets and SHG images indicated collagen turnover after aneurysm formation. We quantified the relative degree of elastin degradation and collagen content in the aortic media within a user-defined area on sections stained with Verhoeff-van Gieson (VVG) or Masson’s trichrome (MTC), as well as on TPEF and SHG images. Our analysis with VVG-stained sections shows that elastin content in AAA tissue is significantly decreased by 64% in AngII models (P=0.02), by 34% in low concentration elastase models (P=0.07), and by 99% in high concentration elastase models (P=0.03), relative to control aortic tissue

Posttraumatic Stress Disorder Prevalence and Risk of Recurrence in Acute Coronary Syndrome Patients: A Meta-analytic Review

BACKGROUND:Acute coronary syndromes (ACS; myocardial infarction or unstable angina) can induce posttraumatic stress disorder (PTSD), and ACS-induced PTSD may increase patients' risk for subsequent cardiac events and mortality. OBJECTIVE:To determine the prevalence of PTSD induced by ACS and to quantify the association between ACS-induced PTSD and adverse clinical outcomes using systematic review and meta-analysis. DATA SOURCES:Articles were identified by searching Ovid MEDLINE, PsycINFO, and Scopus, and through manual search of reference lists. METHODOLOGY/PRINCIPAL FINDINGS:Observational cohort studies that assessed PTSD with specific reference to an ACS event at least 1 month prior. We extracted estimates of the prevalence of ACS-induced PTSD and associations with clinical outcomes, as well as study characteristics. We identified 56 potentially relevant articles, 24 of which met our criteria (N = 2383). Meta-analysis yielded an aggregated prevalence estimate of 12% (95% confidence interval [CI], 9%-16%) for clinically significant symptoms of ACS-induced PTSD in a random effects model. Individual study prevalence estimates varied widely (0%-32%), with significant heterogeneity in estimates explained by the use of a screening instrument (prevalence estimate was 16% [95% CI, 13%-20%] in 16 studies) vs a clinical diagnostic interview (prevalence estimate was 4% [95% CI, 3%-5%] in 8 studies). The aggregated point estimate for the magnitude of the relationship between ACS-induced PTSD and clinical outcomes (ie, mortality and/or ACS recurrence) across the 3 studies that met our criteria (N = 609) suggested a doubling of risk (risk ratio, 2.00; 95% CI, 1.69-2.37) in ACS patients with clinically significant PTSD symptoms relative to patients without PTSD symptoms. CONCLUSIONS/SIGNIFICANCE:This meta-analysis suggests that clinically significant PTSD symptoms induced by ACS are moderately prevalent and are associated with increased risk for recurrent cardiac events and mortality. Further tests of the association of ACS-induced PTSD and clinical outcomes are needed

Machine Learning Driven Contouring of High-Frequency Four-Dimensional Cardiac Ultrasound Data

Automatic boundary detection of 4D ultrasound (4DUS) cardiac data is a promising yet challenging application at the intersection of machine learning and medicine. Using recently developed murine 4DUS cardiac imaging data, we demonstrate here a set of three machine learning models that predict left ventricular wall kinematics along both the endo- and epi-cardial boundaries. Each model is fundamentally built on three key features: (1) the projection of raw US data to a lower dimensional subspace, (2) a smoothing spline basis across time, and (3) a strategic parameterization of the left ventricular boundaries. Model 1 is constructed such that boundary predictions are based on individual short-axis images, regardless of their relative position in the ventricle. Model 2 simultaneously incorporates parallel short-axis image data into their predictions. Model 3 builds on the multi-slice approach of model 2, but assists predictions with a single ground-truth position at end-diastole. To assess the performance of each model, Monte Carlo cross validation was used to assess the performance of each model on unseen data. For predicting the radial distance of the endocardium, models 1, 2, and 3 yielded average R2 values of 0.41, 0.49, and 0.71, respectively. Monte Carlo simulations of the endocardial wall showed significantly closer predictions when using model 2 versus model 1 at a rate of 48.67%, and using model 3 versus model 2 at a rate of 83.50%. These finding suggest that a machine learning approach where multi-slice data are simultaneously used as input and predictions are aided by a single user input yields the most robust performance. Subsequently, we explore the how metrics of cardiac kinematics compare between ground-truth contours and predicted boundaries. We observed negligible deviations from ground-truth when using predicted boundaries alone, except in the case of early diastolic strain rate, providing confidence for the use of such machine learning models for rapid and reliable assessments of murine cardiac function. To our knowledge, this is the first application of machine learning to murine left ventricular 4DUS data. Future work will be needed to strengthen both model performance and applicability to different cardiac disease models

Application of 4-D ultrasound-derived regional strain and proteomics analysis in

The comprehensive characterization of cardiac structure and function is critical to better understanding various murine models of cardiac disease. We demonstrate here a multimodal analysis approach using high-frequency four-dimensional ultrasound (4DUS) imaging and proteomics to explore the relationship between regional function and tissue composition in a murine model of metabolic cardiomyopathy (Nkx2-5183P/ þ ). The presented 4DUS analysis outlines a novel approach to mapping both circumfer- ential and longitudinal strain profiles through a standardized framework. We then demonstrate how this approach allows for spa- tiotemporal comparisons of cardiac function and improved localization of regional left ventricular dysfunction. Guided by observed trends in regional dysfunction, our targeted Ingenuity Pathway Analysis (IPA) results highlight metabolic dysregulation in the Nkx2-5183P/ þ model, including altered mitochondrial function and energy metabolism (i.e., oxidative phosphorylation and fatty acid/lipid handling). Finally, we present a combined 4DUS-proteomics z-score-based analysis that highlights IPA canonical pathways showing strong linear relationships with 4DUS biomarkers of regional cardiac dysfunction. The presented multimodal analysis methods aim to help future studies more comprehensively assess regional structure-function relationships in other pre- clinical models of cardiomyopathy

High-Frequency 4-Dimensional Ultrasound (4DUS): A Reliable Method for Assessing Murine Cardiac Function

In vivo imaging has provided a unique framework for studying pathological progression in various mouse models of cardiac disease. Although conventional short-axis motion-mode (SAX MM) ultrasound and cine magnetic resonance imaging (MRI) are two of the most prevalent strategies used for quantifying cardiac function, there are few notable limitations including imprecision, inaccuracy, and geometric assumptions with ultrasound, or large and costly systems with substantial infrastructure requirements with MRI. Here we present an automated 4-dimensional ultrasound (4DUS) technique that provides comparable information to cine MRI through spatiotemporally synced imaging of cardiac motion. Cardiac function metrics derived from SAX MM, cine MRI, and 4DUS data show close agreement between cine MRI and 4DUS but overestimations by SAX MM. The inclusion of a mouse model of cardiac hypertrophy further highlights the precision of 4DUS compared with that of SAX MM, with narrower groupings of cardiac metrics based on health status. Our findings suggest that murine 4DUS can be used as a reliable, accurate, and cost-effective technique for longitudinal studies of cardiac function and disease progression

Loss of cardiac carnitine palmitoyltransferase 2 results in rapamycin-resistant, acetylation-independent hypertrophy

Cardiac hypertrophy is closely linked to impaired fatty acid oxidation, but the molecular basis of this link is unclear. Here, we investigated the loss of an obligate enzyme in mitochondrial long-chain fatty acid oxidation, carnitine palmitoyltransferase 2 (CPT2), on muscle and heart structure, function, and molecular signatures in a muscle- and heart-specific CPT2-deficient mouse (Cpt2M/) model. CPT2 loss in heart and muscle reduced complete oxidation of long-chain fatty acids by 87 and 69%, respectively, without altering body weight, energy expenditure, respiratory quotient, or adiposity. Cpt2M/ mice developed cardiac hypertrophy and systolic dysfunction, evidenced by a 5-fold greater heart mass, 60 –90% reduction in blood ejection fraction relative to control mice, and eventual lethality in the absence of cardiac fibrosis. The hypertrophy-inducing mammalian target of rapamycin complex 1 (mTORC1) pathway was activated in Cpt2M/ hearts; however, daily rapamycin exposure failed to attenuate hypertrophy in Cpt2M/ mice. Lysine acetylation was reduced by 50% in Cpt2M/ hearts, but trichostatin A, a histone deacetylase inhibitor that improves cardiac remodeling, failed to attenuate Cpt2M/ hypertrophy. Strikingly, a ketogenic diet increased lysine acetylation in Cpt2M/ hearts 2.3-fold compared with littermate control mice fed a ketogenic diet, yet it did not improve cardiac hypertrophy. Together, these results suggest that a shift away from mitochondrial fatty acid oxidation initiates deleterious hypertrophic cardiac remodeling independent of fibrosis. The data also indicate that CPT2-deficient hearts are impervious to hypertrophy attenuators, that mitochondrial metabolism regulates cardiac acetylation, and that signals derived from alterations in mitochondrial metabolism are the key mediators of cardiac hypertrophic growth.Fil: Pereyra, Andrea Soledad. Purdue University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Hasek, Like Y.. Purdue University; Estados UnidosFil: Harris, Kate L.. Purdue University; Estados UnidosFil: Berman, Alycia G.. Purdue University; Estados UnidosFil: Damen, Frederick W.. Purdue University; Estados UnidosFil: Goergen, Craig J.. Purdue University; Estados UnidosFil: Ellis, Jessica M.. Purdue University; Estados Unido

<i>In Vivo</i> Multiscale and Spatially-Dependent Biomechanics Reveals Differential Strain Transfer Hierarchy in Skeletal Muscle

Biological tissues have a complex hierarchical architecture that spans organ to subcellular scales and comprises interconnected biophysical and biochemical machinery. Mechanotransduction, gene regulation, gene protection, and structure–function relationships in tissues depend on how force and strain are modulated from macro to microscales, and <i>vice versa</i>. Traditionally, computational and experimental techniques have been used in common model systems (e.g., embryos), and simple strain measures were applied. However, the hierarchical transfer of mechanical parameters like strain in mammalian systems is largely unexplored <i>in vivo</i>. Here, we experimentally probed complex strain transfer processes in mammalian skeletal muscle tissue over multiple biological scales using complementary <i>in vivo</i> ultrasound and optical imaging approaches. An iterative hyperelastic warping technique quantified the spatially dependent strain distributions in tissue, matrix, and subcellular (nuclear) structures, and revealed a surprising increase in strain magnitude and heterogeneity in active muscle as the spatial scale also increased. The multiscale strain heterogeneity indicates tight regulation of mechanical signals to the nuclei of individual cells in active muscle and an emergent behavior appearing at larger (e.g., tissue) scales characterized by dramatically increased strain complexity