Ketone ester supplementation suppresses cardiac inflammation and improves cardiac energetics in a swine model of acute myocardial infarction.

BACKGROUND: Myocardial infarction (MI) is a major risk factor for the development of heart failure with reduce ejection fraction (HFrEF). While previous studies have focused on HFrEF, the cardiovascular effects of ketone bodies in acute MI are unclear. We examined the effects of oral ketone supplementation as a potential treatment strategy in a swine acute MI model. METHODS: Farm pigs underwent percutaneous balloon occlusion of the LAD for 80 min followed by 72 h reperfusion period. Oral ketone ester or vehicle was administered during reperfusion and continued during the follow-up period. RESULTS: Oral KE supplementation induced ketonemia 2-3 mmol/l within 30 min after ingestion. KE increased ketone (ßHB) extraction in healthy hearts without affecting glucose and fatty acid (FA) consumption. During reperfusion, the MI hearts consumed less FA with no change in glucose consumption, whereas hearts from MI-KE-fed animals consumed more ßHB and FA, as well as improved myocardial ATP production. A significant elevation of infarct T2 values indicative of inflammation was found only in untreated MI group compared to sham. Concordantly, cardiac expression of inflammatory markers, oxidative stress, and apoptosis were reduced by KE. RNA-seq analysis identified differentially expressed genes related to mitochondrial energy metabolism and inflammation. CONCLUSIONS: Oral KE supplementation induced ketosis and enhanced myocardial ßHB extraction in both healthy and infarcted hearts. Acute oral supplementation with KE favorably altered cardiac substrate uptake and utilization, improved cardiac ATP levels, and reduced cardiac inflammation following MI.

Contrast-Enhanced Cardiac Magnetic Resonance Imaging With a Manganese-Based Alternative to Gadolinium for Tissue Characterization of Acute Myocardial Infarction.

Background Late gadolinium enhancement cardiac magnetic resonance imaging is an effective and reproducible method for characterizing myocardial infarction. However, gadolinium-based contrast agents are contraindicated in patients with acute and chronic renal insufficiency. In addition, several recent studies have noted tissue deposition of free gadolinium in patients who have undergone serial contrast-enhanced magnetic resonance imaging. There is a clinical need for alternative forms of magnetic resonance imaging contrast agents that are acceptable in the setting of renal insufficiency. Methods and Results Three days after 80 minutes of ischemia/reperfusion of the left anterior descending coronary artery, cardiac magnetic resonance imaging was performed to assess myocardial lesion burden using both contrast agents. Late gadolinium enhancement cardiac magnetic resonance imaging was examined 10 and 15 minutes after contrast injection. Contrast agents were administered in alternating manner with a 2- to 3-hour washout period between contrast agent injections. Lesion evaluation and image processing were performed using Segment Medviso software. Mean infarct size and transmurality, measured using RVP-001, were not different compared with those measured using late gadolinium enhancement images. Bland-Altman analysis demonstrated a nominal bias of 0.13 mL (<1% of average total lesion volume) for RVP-001 in terms of gross infarct size measurement. Conclusions The experimental manganese-based contrast agent RVP-001 appears to be an effective agent for assessment of myocardial infarction location, size, and transmurality, and it may be useful as an alternative to gadolinium-based agents.

Single breath-hold CINE imaging with combined simultaneous multislice and region-optimized virtual coils.

PURPOSE: To investigate the feasibility of combining simultaneous multislice (SMS) and region-optimized virtual coils (ROVir) for single breath-hold CINE imaging. METHOD: ROVir is a recent virtual coil approach that allows reduced-field of view (FOV) imaging by localizing the signal from a region-of-interest (ROI) and/or suppressing the signal from unwanted spatial regions. In this work, ROVir is used for reduced-FOV SMS bSSFP CINE imaging, which enables whole heart CINE with a single breath-hold acquisition. RESULTS: Reduced-FOV CINE with either SMS-only or ROVir-only resulted in significant aliasing, with severely reduced image quality when compared to the full FOV reference CINE, while the visual appearance of aliasing was substantially reduced with the proposed SMS+ROVir. The end diastolic volume, end systolic volume, and ejection fraction obtained using the proposed approach were similar to the clinical reference (correlations of 0.92, 0.94, and 0.88, respectively with p < 0 . 05 $$ p<0.05 $$ in each case, and biases of 0.1, 1.6 mL, and - 0 . 6 % $$ -0.6\% $$ , respectively). No statistically significant differences for these parameters were found with a Wilcoxon rank test (p = 0.96, 0.20, and 0.40, respectively). CONCLUSION: We demonstrated that reduced-FOV CINE imaging with SMS+ROVir enables single breath-hold whole-heart imaging without compromising visual image quality or quantitative cardiac function parameters.

Accelerated and quantitative three-dimensional molecular MRI using a generative adversarial network.

PURPOSE: To substantially shorten the acquisition time required for quantitative three-dimensional (3D) chemical exchange saturation transfer (CEST) and semisolid magnetization transfer (MT) imaging and allow for rapid chemical exchange parameter map reconstruction. METHODS: Three-dimensional CEST and MT magnetic resonance fingerprinting (MRF) datasets of L-arginine phantoms, whole-brains, and calf muscles from healthy volunteers, cancer patients, and cardiac patients were acquired using 3T clinical scanners at three different sites, using three different scanner models and coils. A saturation transfer-oriented generative adversarial network (GAN-ST) supervised framework was then designed and trained to learn the mapping from a reduced input data space to the quantitative exchange parameter space, while preserving perceptual and quantitative content. RESULTS: The GAN-ST 3D acquisition time was 42-52 s, 70% shorter than CEST-MRF. The quantitative reconstruction of the entire brain took 0.8 s. An excellent agreement was observed between the ground truth and GAN-based L-arginine concentration and pH values (Pearson's r > 0.95, ICC > 0.88, NRMSE < 3%). GAN-ST images from a brain-tumor subject yielded a semi-solid volume fraction and exchange rate NRMSE of 3 . 8 ± 1 . 3 % $$ 3.8\pm 1.3\% $$ and 4 . 6 ± 1 . 3 % $$ 4.6\pm 1.3\% $$ , respectively, and SSIM of 96 . 3 ± 1 . 6 % $$ 96.3\pm 1.6\% $$ and 95 . 0 ± 2 . 4 % $$ 95.0\pm 2.4\% $$ , respectively. The mapping of the calf-muscle exchange parameters in a cardiac patient, yielded NRMSE < 7% and SSIM > 94% for the semi-solid exchange parameters. In regions with large susceptibility artifacts, GAN-ST has demonstrated improved performance and reduced noise compared to MRF. CONCLUSION: GAN-ST can substantially reduce the acquisition time for quantitative semi-solid MT/CEST mapping, while retaining performance even when facing pathologies and scanner models that were not available during training.

Pocket CLARITY enables distortion-mitigated cardiac microstructural tissue characterization of large-scale specimens.

Molecular phenotyping by imaging of intact tissues has been used to reveal 3D molecular and structural coherence in tissue samples using tissue clearing techniques. However, clearing and imaging of cardiac tissue remains challenging for large-scale (>100 mm3) specimens due to sample distortion. Thus, directly assessing tissue microstructural geometric properties confounded by distortion such as cardiac helicity has been limited. To combat sample distortion, we developed a passive CLARITY technique (Pocket CLARITY) that utilizes a permeable cotton mesh pocket to encapsulate the sample to clear large-scale cardiac swine samples with minimal tissue deformation and protein loss. Combined with light sheet auto-fluorescent and scattering microscopy, Pocket CLARITY enabled the characterization of myocardial microstructural helicity of cardiac tissue from control, heart failure, and myocardial infarction in swine. Pocket CLARITY revealed with high fidelity that transmural microstructural helicity of the heart is significantly depressed in cardiovascular disease (CVD), thereby revealing new insights at the tissue level associated with impaired cardiac function.

A soft robotic sleeve mimicking the haemodynamics and biomechanics of left ventricular pressure overload and aortic stenosis.

Preclinical models of aortic stenosis can induce left ventricular pressure overload and coarsely control the severity of aortic constriction. However, they do not recapitulate the haemodynamics and flow patterns associated with the disease. Here we report the development of a customizable soft robotic aortic sleeve that can mimic the haemodynamics and biomechanics of aortic stenosis. By allowing for the adjustment of actuation patterns and blood-flow dynamics, the robotic sleeve recapitulates clinically relevant haemodynamics in a porcine model of aortic stenosis, as we show via in vivo echocardiography and catheterization studies, and a combination of in vitro and computational analyses. Using in vivo and in vitro magnetic resonance imaging, we also quantified the four-dimensional blood-flow velocity profiles associated with the disease and with bicommissural and unicommissural defects re-created by the robotic sleeve. The design of the sleeve, which can be adjusted on the basis of computed tomography data, allows for the design of patient-specific devices that may guide clinical decisions and improve the management and treatment of patients with aortic stenosis.

Measurement of magnetostimulation thresholds in the porcine heart.

PURPOSE: Powerful MRI gradient systems can surpass the International Electrotechnical Commission (IEC) 60601-2-33 limit for cardiac stimulation (CS), which was determined by simple electromagnetic simulations and electrode stimulation experiments. Only a few canine studies measured magnetically induced CS thresholds in vivo and extrapolating them to human safety limits can be challenging. METHODS: We measured cardiac magnetostimulation thresholds in 10 healthy, anesthetized pigs using capacitors discharged into a flat spiral coil to produce damped sinusoidal waveforms with effective stimulus duration ts,eff  = 0.45 ms. Electrocardiography (ECG), blood pressure, and peripheral oximetry signals were recorded to determine threshold coil currents yielding cardiac capture. Dixon and CINE MR volumes from each animal were segmented to generate porcine-specific electromagnetic models to calculate dB/dt and E-field values in the porcine heart at threshold. For comparison, we also simulated maximum dB/dt and E-field values created by three MRI gradient systems in the heart of a human body model. RESULTS: The average dB/dt threshold estimated in the porcine heart was 1.66 ± 0.23 kT/s, which is 11-fold greater than the IEC dB/dt limit at ts,eff  = 0.45 ms, and 31-fold greater than the maximum value created by the investigated MRI gradients in the human heart. The average E-field threshold estimated in the porcine heart was 92.9 ± 13.5 V/m, which is 6-fold greater than the IEC E-field limit at ts,eff  = 0.45 ms and 37-fold greater than the maximum gradient-induced E-field in the human heart. CONCLUSION: This first measurement of cardiac magnetostimulation thresholds in pigs indicates that the IEC cardiac safety limit is conservative for the investigated stimulus duration (ts,eff  = 0.45 ms).

Exercise-induced CITED4 expression is necessary for regional remodeling of cardiac microstructural tissue helicity.

Both exercise-induced molecular mechanisms and physiological cardiac remodeling have been previously studied on a whole heart level. However, the regional microstructural tissue effects of these molecular mechanisms in the heart have yet to be spatially linked and further elucidated. We show in exercised mice that the expression of CITED4, a transcriptional co-regulator necessary for cardioprotection, is regionally heterogenous in the heart with preferential significant increases in the lateral wall compared with sedentary mice. Concordantly in this same region, the heart's local microstructural tissue helicity is also selectively increased in exercised mice. Quantification of CITED4 expression and microstructural tissue helicity reveals a significant correlation across both sedentary and exercise mouse cohorts. Furthermore, genetic deletion of CITED4 in the heart prohibits regional exercise-induced microstructural helicity remodeling. Taken together, CITED4 expression is necessary for exercise-induced regional remodeling of the heart's microstructural helicity revealing how a key molecular regulator of cardiac remodeling manifests into downstream local tissue-level changes.

Feasibility study of clinical target volume definition for soft-tissue sarcoma using muscle fiber orientations derived from diffusion tensor imaging.

Objective.Soft-tissue sarcoma spreads preferentially along muscle fibers. We explore the utility of deriving muscle fiber orientations from diffusion tensor MRI (DT-MRI) for defining the boundary of the clinical target volume (CTV) in muscle tissue.Approach.We recruited eight healthy volunteers to acquire MR images of the left and right thigh. The imaging session consisted of (a) two MRI spin-echo-based scans, T1- and T2-weighted; (b) a diffusion weighted (DW) spin-echo-based scan using an echo planar acquisition with fat suppression. The thigh muscles were auto-segmented using the convolutional neural network. DT-MRI data were used as a geometry encoding input to solve the anisotropic Eikonal equation with the Hamiltonian Fast-Marching method. The isosurfaces of the solution modeled the CTV boundary.Main results.The auto-segmented muscles of the thigh agreed with manually delineated with the Dice score ranging from 0.8 to 0.94 for different muscles. To validate our method of deriving muscle fiber orientations, we compared anisotropy of the isosurfaces across muscles with different anatomical orientations within a thigh, between muscles in the left and right thighs of each subject, and between different subjects. The fiber orientations were identified reproducibly across all comparisons. We identified two controlling parameters, the distance from the gross tumor volume to the isosurface and the eigenvalues ratio, to tailor the proposed CTV to the satisfaction of the clinician.Significance.Our feasibility study with healthy volunteers shows the promise of using muscle fiber orientations derived from DW MRI data for automated generation of anisotropic CTV boundary in soft tissue sarcoma. Our contribution is significant as it serves as a proof of principle for combining DT-MRI information with tumor spread modeling, in contrast to using moderately informative 2D CT planes for the CTV delineation. Such improvements will positively impact the cancer centers with a small volume of sarcoma patients.

Cine gastric MRI reveals altered Gut-Brain Axis in Functional Dyspepsia: gastric motility is linked with brainstem-cortical fMRI connectivity.

BACKGROUND: Functional dyspepsia (FD) is a disorder of gut-brain interaction, and its putative pathophysiology involves dysregulation of gastric motility and central processing of gastric afference. The vagus nerve modulates gastric peristalsis and carries afferent sensory information to brainstem nuclei, specifically the nucleus tractus solitarii (NTS). Here, we combine MRI assessment of gastric kinematics with measures of NTS functional connectivity to the brain in patients with FD and healthy controls (HC), in order to elucidate how gut-brain axis communication is associated with FD pathophysiology. METHODS: Functional dyspepsia and HC subjects experienced serial gastric MRI and brain fMRI following ingestion of a food-based contrast meal. Gastric function indices estimated from 4D cine MRI data were compared between FD and HC groups using repeated measure ANOVA models, controlling for ingested volume. Brain connectivity of the NTS was contrasted between groups and associated with gastric function indices. KEY RESULTS: Propagation velocity of antral peristalsis was significantly lower in FD compared to HC. The brain network defined by NTS connectivity loaded most strongly onto the Default Mode Network, and more strongly onto the Frontoparietal Network in FD. FD also demonstrated higher NTS connectivity to insula, anterior cingulate and prefrontal cortices, and pre-supplementary motor area. NTS connectivity was linked to propagation velocity in HC, but not FD, whereas peristalsis frequency was linked with NTS connectivity in patients with FD. CONCLUSIONS & INFERENCES: Our multi-modal MRI approach revealed lower peristaltic propagation velocity linked to altered brainstem-cortical functional connectivity in patients suffering from FD suggesting specific plasticity in gut-brain communication.

Spatiotemporal approximation of cardiac activation and recovery isochrones.

BACKGROUND: The sequence of myocardial activation and recovery can be studied in detail by invasive catheter recordings of cardiac electrograms (EGMs), or noninvasive inverse reconstructions thereof with electrocardiographic imaging (ECGI). Local activation and recovery times are obtained from a unipolar EGM by the moment of maximum downslope of the QRS complex or maximum upslope of the T wave, respectively. However, both invasive and noninvasive recordings of intracardiac EGMs may suffer from noise and fractionation, making reliable detection of these deflections nontrivial. METHODS: Here, we introduce a novel method that benefits from the spatial coupling of these processes, and incorporate not only the temporal EGM deflection, but also the spatial gradients. We validated this approach in computer simulations, in animal data with ECGI and invasive electrode recordings, and illustrated its use in a clinical case. RESULTS: In the simulated data, the spatiotemporal approach was able to incorporate spatial information to better select the correct deflection in artificially fractionated EGMs and outperformed the traditional temporal-only method. In experimental data, the accuracy of time estimation from ECGI compared to invasive recordings significantly increased from R = 0.73 (activation) and R = 0.58 (recovery) with the temporal-only method to R = 0.79 (activation) and R = 0.72 (recovery) with the novel approach. Localization of the pacing origin of paced beats improved significantly from 36 mm mean error with the temporal-only approach to 23 mm with the spatiotemporal approach. CONCLUSION: The spatiotemporal method to compute activation and recovery times from EGMs outperformed the traditional temporal-only approach in which spatial information was not taken into account.

Reconstruction of cardiac position using body surface potentials.

Electrocardiographic imaging (ECGI) is a noninvasive technique to assess the bioelectric activity of the heart which has been applied to aid in clinical diagnosis and management of cardiac dysfunction. ECGI is built on mathematical models that take into account several patient specific factors including the position of the heart within the torso. Errors in the localization of the heart within the torso, as might arise due to natural changes in heart position from respiration or changes in body position, contribute to errors in ECGI reconstructions of the cardiac activity, thereby reducing the clinical utility of ECGI. In this study we present a novel method for the reconstruction of cardiac geometry utilizing noninvasively acquired body surface potential measurements. Our geometric correction method simultaneously estimates the cardiac position over a series of heartbeats by leveraging an iterative approach which alternates between estimating the cardiac bioelectric source across all heartbeats and then estimating cardiac positions for each heartbeat. We demonstrate that our geometric correction method is able to reduce geometric error and improve ECGI accuracy in a wide range of testing scenarios. We examine the performance of our geometric correction method using different activation sequences, ranges of cardiac motion, and body surface electrode configurations. We find that after geometric correction resulting ECGI solution accuracy is improved and variability of the ECGI solutions between heartbeats is substantially reduced.

Manifold-based respiratory phase estimation enables motion and distortion correction of free-breathing cardiac diffusion tensor MRI.

PURPOSE: For in vivo cardiac DTI, breathing motion and B0 field inhomogeneities produce misalignment and geometric distortion in diffusion-weighted (DW) images acquired with conventional single-shot EPI. We propose using a dimensionality reduction method to retrospectively estimate the respiratory phase of DW images and facilitate both distortion correction (DisCo) and motion compensation. METHODS: Free-breathing electrocardiogram-triggered whole left-ventricular cardiac DTI using a second-order motion-compensated spin echo EPI sequence and alternating directionality of phase encoding blips was performed on 11 healthy volunteers. The respiratory phase of each DW image was estimated after projecting the DW images into a 2D space with Laplacian eigenmaps. DisCo and motion compensation were applied to the respiratory sorted DW images. The results were compared against conventional breath-held T2 half-Fourier single shot turbo spin echo. Cardiac DTI parameters including fractional anisotropy, mean diffusivity, and helix angle transmurality were compared with and without DisCo. RESULTS: The left-ventricular geometries after DisCo and motion compensation resulted in significantly improved alignment of DW images with T2 reference. DisCo reduced the distance between the left-ventricular contours by 13.2% ± 19.2%, P < .05 (2.0 ± 0.4 for DisCo and 2.4 ± 0.5 mm for uncorrected). DisCo DTI parameter maps yielded no significant differences (mean diffusivity: 1.55 ± 0.13 × 10-3 mm2 /s and 1.53 ± 0.13 × 10-3 mm2 /s, P = .09; fractional anisotropy: 0.375 ± 0.041 and 0.379 ± 0.045, P = .11; helix angle transmurality: 1.00% ± 0.10°/% and 0.99% ± 0.12°/%, P = .44), although the orientation of individual tensors differed. CONCLUSION: Retrospective respiratory phase estimation with LE-based DisCo and motion compensation in free-breathing cardiac DTI resulting in significantly reduced geometric distortion and improved alignment within and across slices.

Reducing Line-of-Block Artifacts in Cardiac Activation Maps Estimated Using ECG Imaging: A Comparison of Source Models and Estimation Methods.

OBJECTIVE: To investigatecardiac activation maps estimated using electrocardiographic imaging and to find methods reducing line-of-block (LoB) artifacts, while preserving real LoBs. METHODS: Body surface potentials were computed for 137 simulated ventricular excitations. Subsequently, the inverse problem was solved to obtain extracellular potentials (EP) and transmembrane voltages (TMV). From these, activation times (AT) were estimated using four methods and compared to the ground truth. This process was evaluated with two cardiac mesh resolutions. Factors contributing to LoB artifacts were identified by analyzing the impact of spatial and temporal smoothing on the morphology of source signals. RESULTS: AT estimation using a spatiotemporal derivative performed better than using a temporal derivative. Compared to deflection-based AT estimation, correlation-based methods were less prone to LoB artifacts but performed worse in identifying real LoBs. Temporal smoothing could eliminate artifacts for TMVs but not for EPs, which could be linked to their temporal morphology. TMVs led to more accurate ATs on the septum than EPs. Mesh resolution had anegligible effect on inverse reconstructions, but small distances were important for cross-correlation-based estimation of AT delays. CONCLUSION: LoB artifacts are mainly caused by the inherent spatial smoothing effect of the inverse reconstruction. Among the configurations evaluated, only deflection-based AT estimation in combination with TMVs and strong temporal smoothing can prevent LoB artifacts, while preserving real LoBs. SIGNIFICANCE: Regions of slow conduction are of considerable clinical interest and LoB artifacts observed in non-invasive ATs can lead to misinterpretations. We addressed this problem by identifying factors causing such artifacts.

Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study.

Cardiac diffusion tensor imaging (DTI) is an emerging technique for the in vivo characterisation of myocardial microstructure, and there is a growing need for its validation and standardisation. We sought to establish the accuracy, precision, repeatability and reproducibility of state-of-the-art pulse sequences for cardiac DTI among 10 centres internationally. Phantoms comprising 0%-20% polyvinylpyrrolidone (PVP) were scanned with DTI using a product pulsed gradient spin echo (PGSE; N = 10 sites) sequence, and a custom motion-compensated spin echo (SE; N = 5) or stimulated echo acquisition mode (STEAM; N = 5) sequence suitable for cardiac DTI in vivo. A second identical scan was performed 1-9 days later, and the data were analysed centrally. The average mean diffusivities (MDs) in 0% PVP were (1.124, 1.130, 1.113) x 10-3  mm2 /s for PGSE, SE and STEAM, respectively, and accurate to within 1.5% of reference data from the literature. The coefficients of variation in MDs across sites were 2.6%, 3.1% and 2.1% for PGSE, SE and STEAM, respectively, and were similar to previous studies using only PGSE. Reproducibility in MD was excellent, with mean differences in PGSE, SE and STEAM of (0.3 ± 2.3, 0.24 ± 0.95, 0.52 ± 0.58) x 10-5  mm2 /s (mean ± 1.96 SD). We show that custom sequences for cardiac DTI provide accurate, precise, repeatable and reproducible measurements. Further work in anisotropic and/or deforming phantoms is warranted.

Characterization of Exercise-Induced Myocardium Growth Using Finite Element Modeling and Bayesian Optimization.

Cardiomyocyte growth can occur in both physiological (exercised-induced) and pathological (e.g., volume overload and pressure overload) conditions leading to left ventricular (LV) hypertrophy. Studies using animal models and histology have demonstrated the growth and remodeling process at the organ level and tissue-cellular level, respectively. However, the driving factors of growth and the mechanistic link between organ, tissue, and cellular growth remains poorly understood. Computational models have the potential to bridge this gap by using constitutive models that describe the growth and remodeling process of the myocardium coupled with finite element (FE) analysis to model the biomechanics of the heart at the organ level. Using subject-specific imaging data of the LV geometry at two different time points, an FE model can be created with the inverse method to characterize the growth parameters of each subject. In this study, we developed a framework that takes in vivo cardiac magnetic resonance (CMR) imaging data of exercised porcine model and uses FE and Bayesian optimization to characterize myocardium growth in the transverse and longitudinal directions. The efficacy of this framework was demonstrated by successfully predicting growth parameters of 18 synthetic LV targeted masks which were generated from three LV porcine geometries. The framework was further used to characterize growth parameters in 4 swine subjects that had been exercised. The study suggested that exercise-induced growth in swine is prone to longitudinal cardiomyocyte growth (58.0 ± 19.6% after 6 weeks and 79.3 ± 15.6% after 12 weeks) compared to transverse growth (4.0 ± 8.0% after 6 weeks and 7.8 ± 9.4% after 12 weeks). This framework can be used to characterize myocardial growth in different phenotypes of LV hypertrophy and can be incorporated with other growth constitutive models to study different hypothetical growth mechanisms.

Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation.

Electrocardiographic imaging (ECGI) is an effective tool for noninvasive diagnosis of a range of cardiac dysfunctions. ECGI leverages a model of how cardiac bioelectric sources appear on the torso surface (the forward problem) and uses recorded body surface potential signals to reconstruct the bioelectric source (the inverse problem). Solutions to the inverse problem are sensitive to noise and variations in the body surface potential (BSP) recordings such as those caused by changes or errors in cardiac position. Techniques such as signal averaging seek to improve ECGI solutions by incorporating BSP signals from multiple heartbeats into an averaged BSP with a higher SNR to use when estimating the cardiac bioelectric source. However, signal averaging is limited when it comes to addressing sources of BSP variability such as beat to beat differences in the forward solution. We present a novel joint inverse formulation to solve for the cardiac source given multiple BSP recordings and known changes in the forward solution, here changes in the heart position. We report improved ECGI accuracy over signal averaging and averaged individual inverse solutions using this joint inverse formulation across multiple activation sequence types and regularization techniques with measured canine data and simulated heart motion. Our joint inverse formulation builds upon established techniques and consequently can easily be applied with many existing regularization techniques, source models, and forward problem formulations.

Skin strata delineation in reflectance confocal microscopy images using recurrent convolutional networks with attention.

Reflectance confocal microscopy (RCM) is an effective non-invasive tool for cancer diagnosis. However, acquiring and reading RCM images requires extensive training and experience, and novice clinicians exhibit high discordance in diagnostic accuracy. Quantitative tools to standardize image acquisition could reduce both required training and diagnostic variability. To perform diagnostic analysis, clinicians collect a set of RCM mosaics (RCM images concatenated in a raster fashion to extend the field view) at 4-5 specific layers in skin, all localized in the junction between the epidermal and dermal layers (dermal-epidermal junction, DEJ), necessitating locating that junction before mosaic acquisition. In this study, we automate DEJ localization using deep recurrent convolutional neural networks to delineate skin strata in stacks of RCM images collected at consecutive depths. Success will guide to automated and quantitative mosaic acquisition thus reducing inter operator variability and bring standardization in imaging. Testing our model against an expert labeled dataset of 504 RCM stacks, we achieved [Formula: see text] classification accuracy and nine-fold reduction in the number of anatomically impossible errors compared to the previous state-of-the-art.