Jonathan D. Suever

Cellular Encapsulation Enhances Cardiac Repair

Background Stem cells for cardiac repair have shown promise in preclinical trials, but lower than expected retention, viability, and efficacy. Encapsulation is one potential strategy to increase viable cell retention while facilitating paracrine effects. Methods and Results Human mesenchymal stem cells (hMSC) were encapsulated in alginate and attached to the heart with a hydrogel patch in a rat myocardial infarction (MI) model. Cells were tracked using bioluminescence (BLI) and cardiac function measured by transthoracic echocardiography (TTE) and cardiac magnetic resonance imaging (CMR). Microvasculature was quantified using von Willebrand factor staining and scar measured by Massons Trichrome. Post‐MI ejection fraction by CMR was greatly improved in encapsulated hMSC‐treated animals (MI: 34±3%, MI+Gel: 35±3%, MI+Gel+hMSC: 39±2%, MI+Gel+encapsulated hMSC: 56±1%; n=4 per group; P<0.01). Data represent mean±SEM. By TTE, encapsulated hMSC‐treated animals had improved fractional shortening. Longitudinal BLI showed greatest hMSC retention when the cells were encapsulated (P<0.05). Scar size at 28 days was significantly reduced in encapsulated hMSC‐treated animals (MI: 12±1%, n=8; MI+Gel: 14±2%, n=7; MI+Gel+hMSC: 14±1%, n=7; MI+Gel+encapsulated hMSC: 7±1%, n=6; P<0.05). There was a large increase in microvascular density in the peri‐infarct area (MI: 121±10, n=7; MI+Gel: 153±26, n=5; MI+Gel+hMSC: 198±18, n=7; MI+Gel+encapsulated hMSC: 828±56 vessels/mm2, n=6; P<0.01). Conclusions Alginate encapsulation improved retention of hMSCs and facilitated paracrine effects such as increased peri‐infarct microvasculature and decreased scar. Encapsulation of MSCs improved cardiac function post‐MI and represents a new, translatable strategy for optimization of regenerative therapies for cardiovascular diseases.

Framework to Co-register Longitudinal Virtual Histology-Intravascular Ultrasound Data in the Circumferential Direction

Considerable efforts have been directed at identifying prognostic markers for rapidly progressing coronary atherosclerotic lesions that may advance into a high-risk (vulnerable) state. Intravascular ultrasound (IVUS) has become a valuable clinical tool to study the natural history of coronary artery disease (CAD). While prospectively IVUS studies have provided tremendous insight on CAD progression, and its association with independent markers (e.g., wall shear stress), they are limited by the inability to examine the focal association between spatially heterogeneous variables (in both circumferential and axial directions). Herein, we present a framework to automatically co-register longitudinal (in-time) virtual histology-intravascular ultrasound (VH-IVUS) imaging data in the circumferential direction (i.e., rotate follow-up image so circumferential basis coincides with corresponding baseline image). Multivariate normalized cross correlation was performed on paired images (n = 636) from five patients using three independent VH-IVUS defined parameters: artery thickness, VH-IVUS defined plaque constituents, and VH-IVUS perivascular imaging data. Results exhibited high correlation between co-registration rotation angles determined automatically versus manually by an expert reader (r2 = 0.90). Furthermore, no significant difference between automatic and manual co-registration angles was observed (91.31 ±1.04° and 91.07 ±1.04°, respectively; p = 0.48) and Bland-Altman analysis yielded excellent agreement (bias = 0.24°, 95% CI +/- 16.33°). In conclusion, we have developed, verified, and validated an algorithm that automatically co-registers VH-IVUS imaging data that will allow for the focal examination of CAD progression.

Biomechanical modeling and morphology analysis indicates plaque rupture due to mechanical failure unlikely in atherosclerosis-prone mice

Spontaneous plaque rupture in mouse models of atherosclerosis is controversial, although numerous studies have discussed so-called vulnerable plaque phenotypes in mice. We compared the morphology and biomechanics of two acute and one chronic murine model of atherosclerosis to human coronaries of the thin-cap fibroatheroma (TCFA) phenotype. Our acute models were apolipoprotein E-deficient (ApoE(-/-)) and LDL receptor-deficient (LDLr(-/-)) mice, both fed a high-fat diet for 8 wk with simultaneous infusion of angiotensin II (ANG II), and our chronic mouse model was the apolipoprotein E-deficient strain fed a regular chow diet for 1 yr. We found that the mouse plaques from all three models exhibited significant morphological differences from human TCFA plaques, including the plaque burden, plaque thickness, eccentricity, and amount of the vessel wall covered by lesion as well as significant differences in the relative composition of plaques. These morphological differences suggested that the distribution of solid mechanical stresses in the walls may differ as well. Using a finite-element analysis computational solid mechanics model, we computed the relative distribution of stresses in the walls of murine and human plaques and found that although human TCFA plaques have the highest stresses in the thin fibrous cap, murine lesions do not have such stress distributions. Instead, local maxima of stresses were on the media and adventitia, away from the plaque. Our results suggest that if plaque rupture is possible in mice, it may be driven by a different mechanism than mechanics.

Reproducibility of Pulse Wave Velocity Measurements with Phase Contrast Magnetic Resonance and Applanation Tonometry

Increased aortic pulse wave velocity (PWV) results from loss of arterial compliance and is associated with unfavorable outcomes. Applanation tonometry (AT) is the most frequently applied method to assess PWV and deduce aortic compliance. The goal of this study was to compare the reproducibility of PWV measurements obtained with: (1) cross-correlation analysis of phase contrast magnetic resonance (PCMR) velocity data, and (2) applanation tonometry (AT). PWV was measured twice with each modality in 13 normal young volunteers (controls) and 9 older patients who had undergone a CT exam to evaluate coronary artery calcium. The coefficient of variation (CoV) between measurements was computed for each modality. There was no significant difference in PWV values obtained with AT and PCMR in controls or patients. The inter-scan reproducibility of PCMR was superior to AT in the controls (CoV: 3.4xa0±xa02.3% vs. 6.3xa0±xa04.0%, Pxa0=xa00.03) but not in the older patients (7.4xa0±xa08.0% vs. 9.9xa0±xa09.6%, Pxa0=xa00.32). PWV values were higher in patients than controls (5.6xa0±xa01.2 vs. 9.7xa0±xa02.8, Pxa0=xa00.002). PCMR and AT yielded similar values for PWV in patients and volunteers. PCMR showed a superior reproducibility in young subjects but not in older patients.

Method to create regional mechanical dyssynchrony maps from short-axis cine steady-state free-precession images

To develop a robust method to assess regional mechanical dyssynchrony from cine short‐axis MR images. Cardiac resynchronization therapy (CRT) is an effective treatment for patients with heart failure and evidence of left‐ventricular (LV) dyssynchrony. Patient response to CRT is greatest when the LV pacing lead is placed in the most dyssynchronous segment. Existing techniques for assessing regional dyssynchrony require difficult acquisition and/or postprocessing. Our goal was to develop a widely applicable and robust method to assess regional mechanical dyssynchrony.

Relationship between mechanical dyssynchrony and intra-operative electrical delay times in patients undergoing cardiac resynchronization therapy

BackgroundIt is important to understand the relationship between electrical and mechanical ventricular activation in CRT patients. By measuring local electrical activation at multiple locations within the coronary veins and myocardial contraction at the same locations in the left ventricle, we determined the relationship between electrical and mechanical activation at potential left ventricular pacing locations.MethodsIn this study, mechanical contraction times were computed using high temporal resolution cine cardiovascular magnetic resonance (CMR) data, while electrical activation times were derived from intra-procedural local electrograms.ResultsIn our cohort, there was a strong correlation between electrical and mechanical delay times within each patient (R2u2009=u20090.78u2009±u20090.23). Additionally, the latest electrically activated location corresponded with the latest mechanically contracting location in 91% of patients.ConclusionsThis study provides initial evidence that our method of obtaining non-invasive mechanical activation patterns accurately reflects the underlying electromechanical substrate of intraventricular dyssynchrony.

Prediction of response to cardiac resynchronization therapy using left ventricular pacing lead position and cardiovascular magnetic resonance derived wall motion patterns: a prospective cohort study

BackgroundDespite marked benefits in many heart failure patients, a considerable proportion of patients treated with cardiac resynchronization therapy (CRT) fail to respond appropriately. Recently, a “U-shaped” (type II) wall motion pattern identified by cardiovascular magnetic resonance (CMR) has been associated with improved CRT response compared to a homogenous (type I) wall motion pattern. There is also evidence that a left ventricular (LV) lead localized to the latest contracting LV site predicts superior response, compared to an LV lead localized remotely from the latest contracting LV site.MethodsWe prospectively evaluated patients undergoing CRT with pre-procedural CMR to determine the presence of type I and type II wall motion patterns and pre-procedural echocardiography to determine end systolic volume (ESV). We assessed the final LV lead position on post-procedural fluoroscopic images to determine whether the lead was positioned concordant to or remote from the latest contracting LV site. CRT response was defined as au2009≥u200915xa0% reduction in ESV on a 6xa0month follow-up echocardiogram.ResultsThe study included 33 patients meeting conventional indications for CRT with a mean New York Heart Association class of 2.8u2009±u20090.4 and mean LV ejection fraction of 28u2009±u20099xa0%. Overall, 55xa0% of patients were echocardiographic responders by ESV criteria. Patients with both a type II pattern and an LV lead concordant to the latest contracting site (T2CL) had a response rate of 92xa0%, compared to a response rate of 33xa0% for those without T2CL (pu2009=u20090.003). T2CL was the only independent predictor of response on multivariate analysis (odds ratio 18, 95xa0% confidence interval 1.6-206; pu2009=u20090.018). T2CL resulted in significant incremental improvement in prediction of echocardiographic response (increase in the area under the receiver operator curve from 0.69 to 0.84; pu2009=u20090.038).ConclusionsThe presence of a type II wall motion pattern on CMR and a concordant LV lead predicts superior CRT response. Improving patient selection by evaluating wall motion pattern and targeting LV lead placement may ultimately improve the response rate to CRT.

Biomechanics and inflammation in atherosclerotic plaque erosion and plaque rupture: implications for cardiovascular events in women.

Objective Although plaque erosion causes approximately 40% of all coronary thrombi and disproportionally affects women more than men, its mechanism is not well understood. The role of tissue mechanics in plaque rupture and regulation of mechanosensitive inflammatory proteins is well established, but their role in plaque erosion is unknown. Given obvious differences in morphology between plaque erosion and rupture, we hypothesized that inflammation in general as well as the association between local mechanical strain and inflammation known to exist in plaque rupture may not occur in plaque erosion. Therefore, our objective was to determine if similar mechanisms underlie plaque rupture and plaque erosion. Methods and Results We studied a total of 74 human coronary plaque specimens obtained at autopsy. Using lesion-specific computer modeling of solid mechanics, we calculated the stress and strain distribution for each plaque and determined if there were any relationships with markers of inflammation. Consistent with previous studies, inflammatory markers were positively associated with increasing strain in specimens with rupture and thin-cap fibroatheromas. Conversely, overall staining for inflammatory markers and apoptosis were significantly lower in erosion, and there was no relationship with mechanical strain. Samples with plaque erosion most closely resembled those with the stable phenotype of thick-cap fibroatheromas. Conclusions In contrast to classic plaque rupture, plaque erosion was not associated with markers of inflammation and mechanical strain. These data suggest that plaque erosion is a distinct pathophysiological process with a different etiology and therefore raises the possibility that a different therapeutic approach may be required to prevent plaque erosion.

Time-resolved analysis of coronary vein motion and cross-sectional area†

To quantify periods of low motion and cross‐sectional area changes of the coronary veins during the cardiac cycle for planning magnetic resonance coronary venograms (MRCV).

Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration

Intracranial hemorrhage (ICH) requires prompt diagnosis to optimize patient outcomes. We hypothesized that machine learning algorithms could automatically analyze computed tomography (CT) of the head, prioritize radiology worklists and reduce time to diagnosis of ICH. 46,583 head CTs (~2 million images) acquired from 2007–2017 were collected from several facilities across Geisinger. A deep convolutional neural network was trained on 37,074 studies and subsequently evaluated on 9499 unseen studies. The predictive model was implemented prospectively for 3 months to re-prioritize “routine” head CT studies as “stat” on realtime radiology worklists if an ICH was detected. Time to diagnosis was compared between the re-prioritized “stat” and “routine” studies. A neuroradiologist blinded to the study reviewed false positive studies to determine whether the dictating radiologist overlooked ICH. The model achieved an area under the ROC curve of 0.846 (0.837–0.856). During implementation, 94 of 347 “routine” studies were re-prioritized to “stat”, and 60/94 had ICH identified by the radiologist. Five new cases of ICH were identified, and median time to diagnosis was significantly reduced (pu2009<u20090.0001) from 512 to 19u2009min. In particular, one outpatient with vague symptoms on anti-coagulation was found to have an ICH which was treated promptly with reversal of anticoagulation, resulting in a good clinical outcome. Of the 34 false positives, the blinded over-reader identified four probable ICH cases overlooked in original interpretation. In conclusion, an artificial intelligence algorithm can prioritize radiology worklists to reduce time to diagnosis of new outpatient ICH by 96% and may also identify subtle ICH overlooked by radiologists. This demonstrates the positive impact of advanced machine learning in radiology workflow optimization.A computer program that automatically analyzes brain images from patients undergoing CT scans of the head can reliably flag those with signs of hemorrhage. A team of researchers from Geisinger in Danville, Pennsylvania, USA, trained and tested a machine-learning algorithm using 46,583 computed tomography imaging studies of the head. Subsequently, they implemented the model into routine care for 3 months to help prioritize radiology worklists. Of 347 routine cases, the computer identified 94 as having an intracranial hemorrhage, two-thirds of which were confirmed by a radiologist, including five among patients who had a new diagnosis of a brain bleed. The algorithm reduced the average time in which a radiologist diagnosed these patients from around 8.5 h to just 19 min, demonstrating the positive impact of incorporating artificial intelligence into radiology workflow.