Long-Term Safety and Efficacy of Mavacamten in Symptomatic Obstructive Hypertrophic Cardiomyopathy: Interim Results of the PIONEER-OLE Study

BACKGROUND

The phase 2 PIONEER-HCM (Phase 2 Open-label Pilot Study Evaluating Mavacamten in Subjects With Symptomatic Hypertrophic Cardiomyopathy and Left Ventricular Outflow Tract Obstruction) study showed that mavacamten improved left ventricular outflow tract gradients, exercise capacity, and symptoms in patients with obstructive hypertrophic cardiomyopathy (HCM), but the results of longer-term treatment are less well described. We report interim results from the PIONEER-OLE (PIONEER Open-Label Extension) study, the longest-term study of mavacamten in patients with symptomatic obstructive HCM.

METHODS AND RESULTS

Patients who previously completed PIONEER-HCM (n=20) were eligible to enroll in PIONEER-OLE. Patients received oral mavacamten, 5 mg once daily (starting dose), with individualized dose titration at week 6. Evaluations included serial monitoring of safety, echocardiography, Kansas City Cardiomyopathy Questionnaire-Overall Summary Score, and serum NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels. Thirteen patients enrolled and received mavacamten (median study duration at data cutoff, 201 weeks). Most patients (92.3%) received β-blockers concomitantly. Treatment-emergent adverse events were predominantly mild/moderate. One patient had an isolated reduction in left ventricular ejection fraction to 47%, which recovered and remained normal with continued treatment at a reduced dose. At week 180, mavacamten was associated with New York Heart Association class improvements from baseline (class II to I, n=9; class III to II, n=1; and unchanged, n=2), sustained reductions in left ventricular outflow tract gradients (mean [SD] change from baseline: resting, -50 [55] mm Hg; Valsalva, -70 [41] mm Hg), and serum NT-proBNP levels (median [interquartile range] change from baseline: -498 [-2184 to -76] ng/L), and improved Kansas City Cardiomyopathy Questionnaire-Overall Summary Score (mean [SD] change from baseline: +17 [16]).

CONCLUSIONS

This long-term analysis supports the continued safety and effectiveness of mavacamten for >3 years in obstructive HCM.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03496168.

Multi-task Learning for Motion Analysis and Segmentation in 3D Echocardiography

Characterizing left ventricular deformation and strain using 3D+time echocardiography provides useful insights into cardiac function and can be used to detect and localize myocardial injury. To achieve this, it is imperative to obtain accurate motion estimates of the left ventricle. In many strain analysis pipelines, this step is often accompanied by a separate segmentation step; however, recent works have shown both tasks to be highly related and can be complementary when optimized jointly. In this work, we present a multi-task learning network that can simultaneously segment the left ventricle and track its motion between multiple time frames. Two task-specific networks are trained using a composite loss function. Cross-stitch units combine the activations of these networks by learning shared representations between the tasks at different levels. We also propose a novel shape-consistency unit that encourages motion propagated segmentations to match directly predicted segmentations. Using a combined synthetic and in-vivo 3D echocardiography dataset, we demonstrate that our proposed model can achieve excellent estimates of left ventricular motion displacement and myocardial segmentation. Additionally, we observe strong correlation of our image-based strain measurements with crystal-based strain measurements as well as good correspondence with SPECT perfusion mappings. Finally, we demonstrate the clinical utility of the segmentation masks in estimating ejection fraction and sphericity indices that correspond well with benchmark measurements.

Multiaxial pressure-strain analysis of regional myocardial work in the setting of graded coronary stenoses and dobutamine stress

We present a detailed analysis of regional myocardial blood flow and work to better understand the effects of coronary stenoses and low-dose dobutamine stress. Our analysis is based on a unique open-chest model in anesthetized canines that features invasive hemodynamic monitoring, microsphere-based blood flow analysis, and an extensive three-dimensional (3-D) sonomicrometer array that provides multiaxial deformational assessments in the ischemic, border, and remote vascular territories. We use this model to construct regional pressure-strain loops for each territory and quantify the loop subcomponent areas that reflect myocardial work contributing to the ejection of blood and wasted work that does not. We demonstrate that reductions in coronary blood flow markedly alter the shapes and temporal relationships of pressure-strain loops, as well as the magnitudes of their total and subcomponent areas. Specifically, we show that moderate stenoses in the mid-left anterior descending coronary artery decrease regional midventricle myocardial work indices and substantially increase indices of wasted work. In the midventricle, these effects are most pronounced along the radial and longitudinal axes, with more modest effects along the circumferential axis. We further demonstrate that low-dose dobutamine can help to restore or even improve function, but often at the cost of increased wasted work. This detailed, multiaxial analysis provides unique insight into the physiology and mechanics of the heart in the presence of ischemia and low-dose dobutamine, with potential implications in many areas, including the detection and characterization of ischemic heart disease and the use of inotropic support for low cardiac output.NEW & NOTEWORTHY Our unique experimental model assesses cardiac pressure-strain relationships along multiple axes in multiple regions. We demonstrate that moderate coronary stenoses decrease regional myocardial work and increase wasted work and that low-dose dobutamine can help to restore myocardial function, but often with further increases in wasted work. Our findings highlight the significant directional variation of cardiac mechanics and demonstrate potential advantages of pressure-strain analyses over traditional, purely deformational measures, especially in characterizing physiological changes related to dobutamine.

Left Ventricular Systolic Dysfunction in Patients Diagnosed With Hypertrophic Cardiomyopathy During Childhood: Insights From the SHaRe Registry

BACKGROUND

The development of left ventricular systolic dysfunction (LVSD) in hypertrophic cardiomyopathy (HCM) is rare but serious and associated with poor outcomes in adults. Little is known about the prevalence, predictors, and prognosis of LVSD in patients diagnosed with HCM as children.

METHODS

Data from patients with HCM in the international, multicenter SHaRe (Sarcomeric Human Cardiomyopathy Registry) were analyzed. LVSD was defined as left ventricular ejection fraction <50% on echocardiographic reports. Prognosis was assessed by a composite of death, cardiac transplantation, and left ventricular assist device implantation. Predictors of developing incident LVSD and subsequent prognosis with LVSD were assessed using Cox proportional hazards models.

RESULTS

We studied 1010 patients diagnosed with HCM during childhood (<18 years of age) and compared them with 6741 patients with HCM diagnosed as adults. In the pediatric HCM cohort, median age at HCM diagnosis was 12.7 years (interquartile range, 8.0-15.3), and 393 (36%) patients were female. At initial SHaRe site evaluation, 56 (5.5%) patients with childhood-diagnosed HCM had prevalent LVSD, and 92 (9.1%) developed incident LVSD during a median follow-up of 5.5 years. Overall LVSD prevalence was 14.7% compared with 8.7% in patients with adult-diagnosed HCM. Median age at incident LVSD was 32.6 years (interquartile range, 21.3-41.6) for the pediatric cohort and 57.2 years (interquartile range, 47.3-66.5) for the adult cohort. Predictors of developing incident LVSD in childhood-diagnosed HCM included age <12 years at HCM diagnosis (hazard ratio [HR], 1.72 [CI, 1.13-2.62), male sex (HR, 3.1 [CI, 1.88-5.2), carrying a pathogenic sarcomere variant (HR, 2.19 [CI, 1.08-4.4]), previous septal reduction therapy (HR, 2.34 [CI, 1.42-3.9]), and lower initial left ventricular ejection fraction (HR, 1.53 [CI, 1.38-1.69] per 5% decrease). Forty percent of patients with LVSD and HCM diagnosed during childhood met the composite outcome, with higher rates in female participants (HR, 2.60 [CI, 1.41-4.78]) and patients with a left ventricular ejection fraction <35% (HR, 3.76 [2.16-6.52]).

CONCLUSIONS

Patients with childhood-diagnosed HCM have a significantly higher lifetime risk of developing LVSD, and LVSD emerges earlier than for patients with adult-diagnosed HCM. Regardless of age at diagnosis with HCM or LVSD, the prognosis with LVSD is poor, warranting careful surveillance for LVSD, especially as children with HCM transition to adult care.

Segmentation-Free PVC for Cardiac SPECT Using a Densely-Connected Multi-Dimensional Dynamic Network

In nuclear imaging, limited resolution causes partial volume effects (PVEs) that affect image sharpness and quantitative accuracy. Partial volume correction (PVC) methods incorporating high-resolution anatomical information from CT or MRI have been demonstrated to be effective. However, such anatomical-guided methods typically require tedious image registration and segmentation steps. Accurately segmented organ templates are also hard to obtain, particularly in cardiac SPECT imaging, due to the lack of hybrid SPECT/CT scanners with high-end CT and associated motion artifacts. Slight mis-registration/mis-segmentation would result in severe degradation in image quality after PVC. In this work, we develop a deep-learning-based method for fast cardiac SPECT PVC without anatomical information and associated organ segmentation. The proposed network involves a densely-connected multi-dimensional dynamic mechanism, allowing the convolutional kernels to be adapted based on the input images, even after the network is fully trained. Intramyocardial blood volume (IMBV) is introduced as an additional clinical-relevant loss function for network optimization. The proposed network demonstrated promising performance on 28 canine studies acquired on a GE Discovery NM/CT 570c dedicated cardiac SPECT scanner with a 64-slice CT using Technetium-99m-labeled red blood cells. This work showed that the proposed network with densely-connected dynamic mechanism produced superior results compared with the same network without such mechanism. Results also showed that the proposed network without anatomical information could produce images with statistically comparable IMBV measurements to the images generated by anatomical-guided PVC methods, which could be helpful in clinical translation.

Radiotracers to Address Unmet Clinical Needs in Cardiovascular Imaging, Part 2: Inflammation, Fibrosis, Thrombosis, Calcification, and Amyloidosis Imaging

Cardiovascular imaging is evolving in response to systemwide trends toward molecular characterization and personalized therapies. The development of new radiotracers for PET and SPECT imaging is central to addressing the numerous unmet diagnostic needs that relate to these changes. In this 2-part review, we discuss select radiotracers that may help address key unmet clinical diagnostic needs in cardiovascular medicine. Part 1 examined key technical considerations pertaining to cardiovascular radiotracer development and reviewed emerging radiotracers for perfusion and neuronal imaging. Part 2 covers radiotracers for imaging cardiovascular inflammation, thrombosis, fibrosis, calcification, and amyloidosis. These radiotracers have the potential to address several unmet needs related to the risk stratification of atheroma, detection of thrombi, and the diagnosis, characterization, and risk stratification of cardiomyopathies. In the first section, we discuss radiotracers targeting various aspects of inflammatory responses in pathologies such as myocardial infarction, myocarditis, sarcoidosis, atherosclerosis, and vasculitis. In a subsequent section, we discuss radiotracers for the detection of systemic and device-related thrombi, such as those targeting fibrin (e.g., ⁶⁴Cu-labeled fibrin-binding probe 8). We also cover emerging radiotracers for the imaging of cardiovascular fibrosis, such as those targeting fibroblast activation protein (e.g., ⁶⁸Ga-fibroblast activation protein inhibitor). Lastly, we briefly review radiotracers for imaging of cardiovascular calcification (¹⁸F-NaF) and amyloidosis (e.g., ^99mTc-pyrophosphate and ¹⁸F-florbetapir).

Radiotracers to Address Unmet Clinical Needs in Cardiovascular Imaging, Part 1: Technical Considerations and Perfusion and Neuronal Imaging

The development of new radiotracers for PET and SPECT is central to addressing unmet diagnostic needs related to systemwide trends toward molecular characterization and personalized therapies in cardiovascular medicine. In the following 2-part review, we discuss select emerging radiotracers that may help address important unmet diagnostic needs in central areas of cardiovascular medicine, such as heart failure, arrhythmias, valvular disease, atherosclerosis, and thrombosis. Part 1 examines key technical considerations pertaining to cardiovascular radiotracer development and reviews emerging radiotracers for perfusion and neuronal imaging. Highlights of this work include discussions on the development of ¹⁸F-flurpiridaz, an emerging PET perfusion tracer, and the development of ¹⁸F-based radiotracers for cardiovascular neuronal imaging, such as ¹⁸F-flubrobenguane. Part 2 of this review covers emerging radiotracers for the imaging of inflammation, fibrosis, thrombosis, calcification, and cardiac amyloidosis.

Prototype device for endoventricular beta-emitting radiotracer detection and molecularly-guided intervention

BACKGROUND

We have set out to develop a catheter-based theranostic system that: (a) identifies diseased and at-risk myocardium via endocardial detection of systemically delivered β-emitting radiotracers and (b) utilizes molecular signals to guide delivery of therapeutics to appropriate tissue via direct intramyocardial injection.

METHODS

Our prototype device consists of a miniature β-radiation detector contained within the tip of a flexible intravascular catheter. The catheter can be adapted to incorporate an injection port and retractable needle for therapeutic delivery. The performance of the β-detection catheter was assessed in vitro with various β-emitting radionuclides and ex vivo in hearts of pigs following systemic injection of 18F-fluorodeoxyglucose (18F-FDG) at 1-week post-myocardial infarction. Regional catheter-based endocardial measurements of 18F activity were compared to regional tissue activity from PET/CT images and gamma counting.

RESULTS

The β-detection catheter demonstrated sensitive in vitro detection of β-radiation from 22Na (β+), 18F (β+), and 204Tl (β-), with minimal sensitivity to γ-radiation. For 18F, the catheter demonstrated a sensitivity of 4067 counts/s/μCi in contact and a spatial resolution of 1.1 mm FWHM. Ex vivo measurements of endocardial 18F activity with the β-detection catheter in the chronic pig infarct model demonstrated good qualitative and quantitative correlation with regional tissue activity from PET/CT images and gamma counting.

CONCLUSION

The prototype β-detection catheter demonstrates sensitive and selective detection of β- and β+ emissions over a wide range of energies and enables high-fidelity ex vivo characterization of endocardial activity from systemically delivered 18F-FDG.

Feasibility study of PET dynamic imaging of [18F]DHMT for quantification of reactive oxygen species in the myocardium of large animals

OBJECTIVES

We aimed to develop a dynamic imaging technique for a novel PET superoxide tracer, [18F]DHMT, to allow for absolute quantification of myocardial reactive oxygen species (ROS) production in a large animal model.

METHODS

Six beagle dogs underwent a single baseline dynamic [18F]DHMT PET study, whereas one animal underwent three serial dynamic studies over the course of chronic doxorubicin administration (1 mg·kg-1·week-1 for 15 weeks). During the scans, sequential arterial blood samples were obtained for plasma metabolite correction. The optimal compartment model and graphical analysis method were identified for kinetic modeling. Values for the left ventricular (LV) net influx rate, Ki, were reported for all the studies and compared with the LV standard uptake values (SUVs) and the LV-to-blood pool SUV ratios from the 60 to 90 minute static images. Parametric images were also generated.

RESULTS

[18F]DHMT followed irreversible kinetics once oxidized within the myocardium in the presence of superoxide, as evidenced by the fitting generated by the irreversible two-tissue (2Ti) compartment model and the linearity of Patlak analysis. Myocardial Ki values showed a weak correlation with LV SUV (R2 = 0.27), but a strong correlation with LV-to-blood pool SUV ratio (R2 = 0.92). Generation of high-quality parametric images showed superior myocardial to blood contrast compared to static images.

CONCLUSIONS

A dynamic PET imaging technique for [18F]DHMT was developed with full and simplified kinetic modeling for absolute quantification of myocardial superoxide production in a large animal model.

Simultaneous Segmentation and Motion Estimation of Left Ventricular Myocardium in 3D Echocardiography Using Multi-task Learning

Motion estimation and segmentation are both critical steps in identifying and assessing myocardial dysfunction, but are traditionally treated as unique tasks and solved as separate steps. However, many motion estimation techniques rely on accurate segmentations. It has been demonstrated in the computer vision and medical image analysis literature that both these tasks may be mutually beneficial when solved simultaneously. In this work, we propose a multi-task learning network that can concurrently predict volumetric segmentations of the left ventricle and estimate motion between 3D echocardiographic image pairs. The model exploits complementary latent features between the two tasks using a shared feature encoder with task-specific decoding branches. Anatomically inspired constraints are incorporated to enforce realistic motion patterns. We evaluate our proposed model on an in vivo 3D echocardiographic canine dataset. Results suggest that coupling these two tasks in a learning framework performs favorably when compared against single task learning and other alternative methods.

Learning-Based Regularization for Cardiac Strain Analysis via Domain Adaptation

Reliable motion estimation and strain analysis using 3D+ time echocardiography (4DE) for localization and characterization of myocardial injury is valuable for early detection and targeted interventions. However, motion estimation is difficult due to the low-SNR that stems from the inherent image properties of 4DE, and intelligent regularization is critical for producing reliable motion estimates. In this work, we incorporated the notion of domain adaptation into a supervised neural network regularization framework. We first propose a semi-supervised Multi-Layered Perceptron (MLP) network with biomechanical constraints for learning a latent representation that is shown to have more physiologically plausible displacements. We extended this framework to include a supervised loss term on synthetic data and showed the effects of biomechanical constraints on the network's ability for domain adaptation. We validated the semi-supervised regularization method on in vivo data with implanted sonomicrometers. Finally, we showed the ability of our semi-supervised learning regularization approach to identify infarct regions using estimated regional strain maps with good agreement to manually traced infarct regions from postmortem excised hearts.

SHAPE-REGULARIZED UNSUPERVISED LEFT VENTRICULAR MOTION NETWORK WITH SEGMENTATION CAPABILITY IN 3D+TIME ECHOCARDIOGRAPHY

Accurate motion estimation and segmentation of the left ventricle from medical images are important tasks for quantitative evaluation of cardiovascular health. Echocardiography offers a cost-efficient and non-invasive modality for examining the heart, but provides additional challenges for automated analyses due to the low signal-to-noise ratio inherent in ultrasound imaging. In this work, we propose a shape regularized convolutional neural network for estimating dense displacement fields between sequential 3D B-mode echocardiography images with the capability of also predicting left ventricular segmentation masks. Manually traced segmentations are used as a guide to assist in the unsupervised estimation of displacement between a source and a target image while also serving as labels to train the network to additionally predict segmentations. To enforce realistic cardiac motion patterns, a flow incompressibility term is also incorporated to penalize divergence. Our proposed network is evaluated on an in vivo canine 3D+t B-mode echocardiographic dataset. It is shown that the shape regularizer improves the motion estimation performance of the network and our overall model performs favorably against competing methods.

A Semi-supervised Joint Network for Simultaneous Left Ventricular Motion Tracking and Segmentation in 4D Echocardiography

This work presents a novel deep learning method to combine segmentation and motion tracking in 4D echocardiography. The network iteratively trains a motion branch and a segmentation branch. The motion branch is initially trained entirely unsupervised and learns to roughly map the displacements between a source and a target frame. The estimated displacement maps are then used to generate pseudo-ground truth labels to train the segmentation branch. The labels predicted by the trained segmentation branch are fed back into the motion branch and act as landmarks to help retrain the branch to produce smoother displacement estimations. These smoothed out displacements are then used to obtain smoother pseudo-labels to retrain the segmentation branch. Additionally, a biomechanically-inspired incompressibility constraint is implemented in order to encourage more realistic cardiac motion. The proposed method is evaluated against other approaches using synthetic and in-vivo canine studies. Both the segmentation and motion tracking results of our model perform favorably against competing methods.

Computed Tomographic Angiography Assessment of Epicardial Coronary Vasoreactivity for Early Detection of Doxorubicin-Induced Cardiotoxicity

Background

The vascular endothelium is a novel target for the detection, management, and prevention of doxorubicin (DOX)-induced cardiotoxicity.

Objectives

The study aimed to: 1) develop a methodology by computed tomography angiography (CTA) to evaluate stress-induced changes in epicardial coronary diameter; and 2) apply this to a chronic canine model of DOX-induced cardiotoxicity to assess vascular toxicity.

Methods

To develop and validate quantitative methods, sequential retrospectively gated coronary CTAs were performed in 16 canines. Coronary diameters were measured at prespecified distances during rest, adenosine (ADE) (280 μg/kg/min), rest 30 min post-ADE, and dobutamine (DOB) (5 μg/kg/min). A subgroup of 8 canines received weekly intravenous DOX (1 mg/kg) for 12 to 15 weeks, followed by rest-stress CTA at cumulative doses of ∼4-mg/kg (3 to 5 mg/kg), ∼8-mg/kg (7 to 9 mg/kg), and ∼12-mg/kg (12 to 15 mg/kg) of DOX. Echocardiograms were performed at these timepoints to assess left ventricular ejection fraction and global longitudinal strain.

Results

Under normal conditions, epicardial coronary arteries reproducibly dilated in response to ADE (left anterior descending coronary artery [LAD]: 12 ± 2%, left circumflex coronary artery [LCx]: 13 ± 2%, right coronary artery [RCA]: 14 ± 2%) and DOB (LAD: 17 ± 3%, LCx: 18 ± 2%, RCA: 15 ± 3%). With DOX, ADE vasodilator responses were impaired after ∼4-mg/kg (LAD: –3 ± 1%, LCx: 0 ± 2%, RCA: –5 ± 2%) and ∼8-mg/kg (LAD: –3 ± 1%, LCx: 0 ± 1%, RCA: –2 ± 2%). The DOB dilation response was preserved at ∼4-mg/kg of DOX (LAD: 18 ± 4%, LCx: 11 ± 3%, RCA: 11 ± 2%) but tended to decrease at ∼8-mg/kg of DOX (LAD: 4 ± 2%, LCx: 8 ± 3%, RCA: 3 ± 2%). A significant left ventricular ejection fraction reduction was observed only at 12 to 15 mg/kg DOX (baseline: 63 ± 2%, 12-mg/kg: 45 ± 3%). Global longitudinal strain was abnormal at ∼4-mg/kg of DOX (p = 0.011).

Conclusions

CTA can reliably assess epicardial coronary diameter in response to pharmacological stressors, providing a noninvasive functional index of coronary vasoreactivity. Impaired epicardial vasodilation occurs early in DOX-induced cardiotoxicity.

A SEMI-SUPERVISED JOINT LEARNING APPROACH TO LEFT VENTRICULAR SEGMENTATION AND MOTION TRACKING IN ECHOCARDIOGRAPHY

Accurate interpretation and analysis of echocardiography is important in assessing cardiovascular health. However, motion tracking often relies on accurate segmentation of the myocardium, which can be difficult to obtain due to inherent ultrasound properties. In order to address this limitation, we propose a semi-supervised joint learning network that exploits overlapping features in motion tracking and segmentation. The network simultaneously trains two branches: one for motion tracking and one for segmentation. Each branch learns to extract features relevant to their respective tasks and shares them with the other. Learned motion estimations propagate a manually segmented mask through time, which is used to guide future segmentation predictions. Physiological constraints are introduced to enforce realistic cardiac behavior. Experimental results on synthetic and in vivo canine 2D+t echocardiographic sequences outperform some competing methods in both tasks.

Unsupervised Motion Tracking of Left Ventricle in Echocardiography

Accurate motion tracking of the left ventricle is critical in detecting wall motion abnormalities in the heart after an injury such as a myocardial infarction. We propose an unsupervised motion tracking framework with physiological constraints to learn dense displacement fields between sequential pairs of 2-D B-mode echocardiography images. Current deep-learning motion-tracking algorithms require large amounts of data to provide ground-truth, which is difficult to obtain for in vivo datasets (such as patient data and animal studies), or are unsuccessful in tracking motion between echocardiographic images due to inherent ultrasound properties (such as low signal-to-noise ratio and various image artifacts). We design a U-Net inspired convolutional neural network that uses manually traced segmentations as a guide to learn displacement estimations between a source and target image without ground-truth displacement fields by minimizing the difference between a transformed source frame and the original target frame. We then penalize divergence in the displacement field in order to enforce incompressibility within the left ventricle. We demonstrate the performance of our model on synthetic and in vivo canine 2-D echocardiography datasets by comparing it against a non-rigid registration algorithm and a shape-tracking algorithm. Our results show favorable performance of our model against both methods.

Regional myocardial strain analysis via 2D speckle tracking echocardiography: validation with sonomicrometry and correlation with regional blood flow in the presence of graded coronary stenoses and dobutamine stress

Background

Quantitative regional strain analysis by speckle tracking echocardiography (STE) may be particularly useful in the assessment of myocardial ischemia and viability, although reliable measurement of regional strain remains challenging, especially in the circumferential and radial directions. We present an acute canine model that integrates a complex sonomicrometer array with microsphere blood flow measurements to evaluate regional myocardial strain and flow in the setting of graded coronary stenoses and dobutamine stress. We apply this unique model to rigorously evaluate a commercial 2D STE software package and explore fundamental regional myocardial flow-function relationships.

Methods

Sonomicrometers (16 crystals) were implanted in epicardial and endocardial pairs across the anterior myocardium of anesthetized open chest dogs (n = 7) to form three adjacent cubes representing the ischemic, border, and remote regions, as defined by their relative locations to a hydraulic occluder on the mid-left anterior descending coronary artery (LAD). Additional cardiac (n = 3) and extra-cardiac (n = 3) reference crystals were placed to define the cardiac axes and aid image registration. 2D short axis echocardiograms, sonometric data, and microsphere blood flow data were acquired at baseline and in the presence of mild and moderate LAD stenoses, both before and during low-dose dobutamine stress (5 μg/kg/min). Regional end-systolic 2D STE radial and circumferential strains were calculated with commercial software (EchoInsight) and compared to those determined by sonomicrometry and to microsphere blood flow measurements. Post-systolic indices (PSIs) were also calculated for radial and circumferential strains.

Results

Low-dose dobutamine augmented both strain and flow in the presence of mild and moderate stenoses. Regional 2D STE strains correlated moderately with strains assessed by sonomicrometry (R_radial = 0.56, p < 0.0001; R_circ = 0.55, p < 0.0001) and with regional flow quantities (R_radial = 0.61, R_circ = 0.63). Overall, correspondence between 2D STE and sonomicrometry was better in the circumferential direction (Bias ± 1.96 SD: − 1.0 ± 8.2% strain, p = 0.06) than the radial direction (5.7 ± 18.3%, p < 0.0001). Mean PSI values were greatest in low flow conditions and normalized with low-dose dobutamine.

Conclusions

2D STE identifies changes in regional end-systolic circumferential and radial strain produced by mild and moderate coronary stenoses and low-dose dobutamine stress. Regional 2D STE end-systolic strain measurements correlate modestly with regional sonomicrometer strain and microsphere flow measurements.

Mycoplasma Pneumoniae Pericarditis

Mycoplasma pneumoniae is an atypical bacterium that is frequently implicated in respiratory infections, but uncommonly identified as a cause of pericarditis. We report 2 cases of pericarditis attributed to M. pneumoniae that were characterized by prolonged respiratory prodromes, pericardial, and pleural effusions, elevated inflammatory markers, and relapsing clinical courses. In conclusion, our experience suggests that M. pneumoniae should be considered as a potential cause in cases of pericarditis associated with upper respiratory symptoms, pneumonia, pleural effusions, arthralgia, and/or a recurrent/refractory clinical course. The availability of effective antibiotic treatment makes this an important diagnosis to make.

Quantification of intramyocardial blood volume with 99mTc-RBC SPECT-CT imaging: A preclinical study

BACKGROUND

Currently, there is no established non-invasive imaging approach to directly evaluate myocardial microcirculatory function in order to diagnose microvascular disease independent of co-existing epicardial disease. In this work, we developed a methodological framework for quantification of intramyocardial blood volume (IMBV) as a novel index of microcirculatory function with SPECT/CT imaging of 99mTc-labeled red blood cells (RBCs).

METHODS

Dual-gated myocardial SPECT/CT equilibrium imaging of 99mTc-RBCs was performed on twelve canines under resting conditions. Five correction schemes were studied: cardiac gating with no other corrections (CG), CG with attenuation correction (CG + AC), CG + AC with scatter correction (CG + AC + SC), dual cardiorespiratory gating with AC + SC (DG + AC + SC), and DG + AC + SC with partial volume correction (DG + AC + SC + PVC). Quantification of IMBV using each approach was evaluated in comparison to those obtained from all corrections. The in vivo SPECT estimates of IMBV values were validated against those obtained from ex vivo microCT imaging of the casted hearts.

RESULTS

The estimated IMBV with all corrections was 0.15 ± 0.03 for the end-diastolic phase and 0.11 ± 0.03 for the end-systolic phase. The cycle-dependent change in IMBV (ΔIMBV) with all corrections was 23.9 ± 8.6%. Schemes that applied no correction or partial correction resulted in significant over-estimation of IMBV and significant under-underestimation of ΔIMBV. Estimates of IMBV and ΔIMBV using all corrections were consistent with values reported in the literature using invasive techniques. In vivo SPECT estimates of IMBV strongly correlated (R2 ≥ 0.70) with ex vivo measures for the various correction schemes, while the fully corrected scheme yielded the smallest bias.

CONCLUSIONS

Non-invasive quantification of IMBV is feasible using 99mTc-RBCs SPECT/CT imaging, however, requires full compensation of physical degradation factors.

Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT

Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine ^99mTc-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.

Nanoparticles for Cardiovascular Imaging and Therapeutic Delivery, Part 2: Radiolabeled Probes

Nanoparticulate imaging agents and therapeutics have proven to be valuable tools in preclinical cardiovascular disease research. Because of their distinct properties and significant functional versatility, nanoparticulate imaging agents afford certain capabilities that are typically not provided by traditional small molecule agents. This review is the second in a two-part series covering nanoparticulate imaging agents and theranostics. It highlights current examples of radiolabeled nanoparticulate probes in preclinical cardiovascular research and demonstrates their utility in applications such as blood pool imaging and molecular imaging of ischemia, angiogenesis, atherosclerosis, and inflammation. These agents provide valuable insight into the molecular and cellular mechanisms of cardiovascular disease and illustrate both the limitations and the significant potential of nanoparticles in diagnostic and therapeutic applications. Further technologic development to improve performance, address safety concerns, and fulfil regulatory obligations is required for clinical translation of these emergent technologies.

Nanoparticles for Cardiovascular Imaging and Therapeutic Delivery, Part 1: Compositions and Features

Imaging agents made from nanoparticles are functionally versatile and have unique properties that may translate to clinical utility in several key cardiovascular imaging niches. Nanoparticles exhibit size-based circulation, biodistribution, and elimination properties different from those of small molecules and microparticles. In addition, nanoparticles provide versatile platforms that can be engineered to create both multimodal and multifunctional imaging agents with tunable properties. With these features, nanoparticulate imaging agents can facilitate fusion of high-sensitivity and high-resolution imaging modalities and selectively bind tissues for targeted molecular imaging and therapeutic delivery. Despite their intriguing attributes, nanoparticulate imaging agents have thus far achieved only limited clinical use. The reasons for this restricted advancement include an evolving scope of applications, the simplicity and effectiveness of existing small-molecule agents, pharmacokinetic limitations, safety concerns, and a complex regulatory environment. This review describes general features of nanoparticulate imaging agents and therapeutics and discusses challenges associated with clinical translation. A second, related review to appear in a subsequent issue of JNM highlights nuclear-based nanoparticulate probes in preclinical cardiovascular imaging.

Massive interventricular septal aneurysm and stroke in a healthy young patient: guilt by association?

Aneurysm of the membranous interventricular septum is an uncommon cardiac defect that is, on rare occasions, associated with embolic stroke. We describe here the case of an otherwise healthy, 41-year-old man who presented to the hospital with acute-onset confusion and left-sided body weakness attributed to a right middle cerebral artery ischemic stroke. He experienced a nearly complete resolution of deficits following systemic thrombolytic therapy. After an extensive workup, the presumed mechanism of stroke was a thromboembolus that originated in a massive aneurysm of the patient's membranous interventricular septum. Due to a perceived risk of surgical morbidity, the patient was managed conservatively with anticoagulation. He denied further events and reported nearly full function at follow-up.

Extracellular matrix in pancreatic islets: relevance to scaffold design and transplantation

Intrahepatic islet transplantation provides a potentially more benign alternative to pancreatic transplantation. However, islet transplants are associated with limited engraftment potential. This inefficiency is likely at least partially attributable to the isolation process, which removes islets from their native environment. Isolation not only disrupts the internal vascularization and innervation of islets, but also fundamentally changes interactions between islet cells and macromolecules of the extracellular matrix (ECM). Signaling interactions between islet cells and ECM are known to regulate multiple aspects of islet physiology, including survival, proliferation, and insulin secretion. Although it is highly likely that disruptions to these interactions during isolation significantly affect transplant outcomes, the true implications of these conditions are not well understood. The following article reviews current understandings and uncertainties in islet-ECM interactions and explains their potential impact on posttransplant engraftment. Topics covered include matrix and receptor compositions in native islets, effects of isolation and culture on islet-ECM interactions, and potential for postisolation restoration of islet-ECM interactions. Greater understanding in these areas may help to reduce isolation and transplantation stresses and improve islet engraftment.

Self-assembling peptide amphiphile nanofiber matrices for cell entrapment

We have developed a class of peptide amphiphile (PA) molecules that self-assemble into three-dimensional nanofiber networks under physiological conditions in the presence of polyvalent metal ions. The assembly can be triggered by adding PA solutions to cell culture media or other synthetic physiological fluids containing polyvalent metal ions. When the fluids contain suspended cells, PA self-assembly entraps cells in the nanofibrillar matrix, and the cells survive in culture for at least three weeks. We also show that entrapment does not arrest cell proliferation and motility. Biochemical and ultrastructural analysis by electron microscopy indicate that entrapped cells internalize the nanofibers and possibly utilize PA molecules in their metabolic pathways. These results demonstrate that PA nanofibrillar matrices have the potential to be used for cell transplantation or other tissue engineering applications.

Modification of fibrous poly(l-lactic acid) scaffolds with self-assembling triblock molecules

Molecular self-assembly offers an effective method to modify the surface properties of common biomaterials by presenting biologically relevant chemistry in a controlled, ordered fashion. This work reports on self-assembling triblock molecules containing rigid cholesteryl segments followed by flexible oligomers of L-(lactic acid) and second generation L-lysine dendrons. Second harmonic generation and small angle X-ray scattering indicate these molecules self-assemble into multilayer polar structures when cast from ethyl acetate solutions and segregate into polar polydomains when annealed. These self-assembled layers significantly improve water wettability when coated onto poly(L-lactic acid) fibers. Scaffolds formed from fibers modified by self-assembly enhance adhesion of 3T3 mouse calvaria cells and produce greater population growth rates. These results demonstrate the use of self-assembly to present biologically relevant chemistry on surfaces of biomaterials. Applications of this technology include the modification of substrates for cell culture, tissue engineering, and cell transplantation.