Feature Tracking Cardiac Magnetic Resonance via Deep Learning and Spline Optimization

Feature tracking Cardiac Magnetic Resonance (CMR) has recently emerged as an area of interest for quantification of regional cardiac function from balanced, steady state free precession (SSFP) cine sequences. However, currently available techniques lack full automation, limiting reproducibility. We propose a fully automated technique whereby a CMR image sequence is first segmented with a deep, fully convolutional neural network (CNN) architecture, and quadratic basis splines are fitted simultaneously across all cardiac frames using least squares optimization. Experiments are performed using data from 42 patients with hypertrophic cardiomyopathy (HCM) and 21 healthy control subjects. In terms of segmentation, we compared state-of-the-art CNN frameworks, U-Net and dilated convolution architectures, with and without temporal context, using cross validation with three folds. Performance relative to expert manual segmentation was similar across all networks: pixel accuracy was ~97%, intersection-over-union (IoU) across all classes was ~87%, and IoU across foreground classes only was ~85%. Endocardial left ventricular circumferential strain calculated from the proposed pipeline was significantly different in control and disease subjects (-25.3% vs -29.1%, p = 0.006), in agreement with the current clinical literature.Comment: Accepted to Functional Imaging and Modeling of the Heart (FIMH) 201

Demonstration of Patient-Specific Simulations to Assess Left Atrial Appendage Thrombogenesis Risk

Atrial fibrillation (AF) alters left atrial (LA) hemodynamics, which can lead to thrombosis in the left atrial appendage (LAA), systemic embolism and stroke. A personalized risk-stratification of AF patients for stroke would permit improved balancing of preventive anticoagulation therapies against bleeding risk. We investigated how LA anatomy and function impact LA and LAA hemodynamics, and explored whether patient-specific analysis by computational fluid dynamics (CFD) can predict the risk of LAA thrombosis. We analyzed 4D-CT acquisitions of LA wall motion with an in-house immersed-boundary CFD solver. We considered six patients with diverse atrial function, three with either a LAA thrombus (removed digitally before running the simulations) or a history of transient ischemic attacks (LAAT/TIA-pos), and three without a LAA thrombus or TIA (LAAT/TIA-neg). We found that blood inside the left atrial appendage of LAAT/TIA-pos patients had marked alterations in residence time and kinetic energy when compared with LAAT/TIA-neg patients. In addition, we showed how the LA conduit, reservoir and booster functions distinctly affect LA and LAA hemodynamics. Finally, fixed-wall and moving-wall simulations produced different LA hemodynamics and residence time predictions for each patient. Consequently, fixed-wall simulations risk-stratified our small cohort for LAA thrombosis worse than moving-wall simulations, particularly patients with intermediate LAA residence time. Overall, these results suggest that both wall kinetics and LAA morphology contribute to LAA blood stasis and thrombosis.This work was partially supported by the Comunidad de Madrid (Sinergias Y2018/BIO-4858 PREFI-CM), Cátedra Excelencia UC3M-Santander, Ministry of Education of Spain (Salvador de Madariaga program), the US NHLBI (NCAI-UCCAI-2017-06-6), the United States American Heart Association (AHA 20POST35200401), and the 2019 UCSD GEM Program. Computational time provided by XSEDE (Comet) and RES (Altamira) is gratefully acknowledged

Left Atrial structure and function in hypertrophic cardiomyopathy sarcomere mutation carriers with and without left ventricular hypertrophy

Background: Impaired left atrial (LA) function is an early marker of cardiac dysfunction and predictor of adverse cardiac events. Herein, we assess LA structure and function in hypertrophy in hypertrophic cardiomyopathy (HCM) sarcomere mutation carriers with and without left ventricular hypertrophy (LVH). Method Seventy-three participants of the HCMNet study who underwent cardiovascular magnetic resonance (CMR) imaging were studied, including mutation carriers with overt HCM (n = 34), preclinical mutation carriers without HCM (n = 24) and healthy, familial controls (n = 15). Results: LA volumes were similar between preclinical, control and overt HCM cohorts after covariate adjustment. However, there was evidence of impaired LA function with decreased LA total emptying function in both preclinical (64 ± 8%) and overt HCM (59 ± 10%), compared with controls (70 ± 7%; p = 0.002 and p = 0.005, respectively). LA passive emptying function was also decreased in overt HCM (35 ± 11%) compared with controls (47 ± 10%; p = 0.006). Both LAtotal emptying function and LA passive emptying function were inversely correlated with the extent of late gadolinium enhancement (LGE; p = 0.005 and p < 0.05, respectively), LV mass (p = 0.02 and p < 0.001) and interventricular septal thickness (p < 0.001 for both) and serum NT-proBNP levels (p < 0.001 for both). Conclusion: LA dysfunction is detectable by CMR in preclinical HCM mutation carriers despite non-distinguishable LV wall thickness and LA volume. LA function appears most impaired in subjects with overt HCM and a greater extent of LV fibrosis. Electronic supplementary material The online version of this article (10.1186/s12968-017-0420-0) contains supplementary material, which is available to authorized users

DMSO and Betaine Greatly Improve Amplification of GC-Rich Constructs in De Novo Synthesis

In Synthetic Biology, de novo synthesis of GC-rich constructs poses a major challenge because of secondary structure formation and mispriming. While there are many web-based tools for codon optimizing difficult regions, no method currently exists that allows for potentially phenotypically important sequence conservation. Therefore, to overcome these limitations in researching GC-rich genes and their non-coding elements, we explored the use of DMSO and betaine in two conventional methods of assembly and amplification. For this study, we compared the polymerase (PCA) and ligase-based (LCR) methods for construction of two GC-rich gene fragments implicated in tumorigenesis, IGF2R and BRAF. Though we found no benefit in employing either DMSO or betaine during the assembly steps, both additives greatly improved target product specificity and yield during PCR amplification. Of the methods tested, LCR assembly proved far superior to PCA, generating a much more stable template to amplify from. We further report that DMSO and betaine are highly compatible with all other reaction components of gene synthesis and do not require any additional protocol modifications. Furthermore, we believe either additive will allow for the production of a wide variety of GC-rich gene constructs without the need for expensive and time-consuming sample extraction and purification prior to downstream application

Quantification of regional cardiac function: clinically-motivated algorithm development and application to cardiac magnetic resonance and computed tomography

Techniques described to date for the reproducible and noninvasive quantification of regional cardiac function have been largely relegated to research settings due to time-consuming and cumbersome image acquisition and analysis. In this thesis, feature tracking algorithms are developed for 2-D+Time cardiac magnetic resonance (CMR) and 3-D+Time cardiac computed tomography (CCT) image sequences that are easily acquired clinically, while emphasising reproducibility and automation in their design. First, a commercially-implemented CMR feature tracking algorithm for the analysis of steady state free precession (SSFP) cine series is evaluated in patients with hypertrophic cardiomyopathy (HCM) and arrhythmogenic right ventricular cardiomyopathy (ARVC), which primarily affect the left ventricle (LV) and right ventricle (RV), respectively, and functional impairment compared with control populations is found in both cases. The limitations of this implementation are then used to guide development of an automated algorithm for the same purpose, making use of fully convolutional neural networks (CNN) for segmentation and spline registration across all frames simultaneously for tracking. This study is performed in the subjects with HCM, and functional impairment is again identified in disease subjects. Finally, as myocardial contraction is inherently a 3-D phenomenon, a technique is developed for quantification of regional function from 3-D+Time functional CCT studies using simultaneous registration of automatically generated Loop subdivision surface models for tracking. This study is performed in canine mongrels, and compared with the current state of the art technique for CCT functional analysis. This work demonstrates the feasibility of automated, reproducible cardiac functional analysis from CMR and CCT image sequences. While work remains to be done in extending the principles demonstrated and modular components described to fully automated whole-heart analysis, it is hoped that this thesis will accelerate the clinical adoption of regional functional analysis.</p

Quantification of regional cardiac function: clinically-motivated algorithm development and application to cardiac magnetic resonance and computed tomography

Techniques described to date for the reproducible and noninvasive quantification of regional cardiac function have been largely relegated to research settings due to time-consuming and cumbersome image acquisition and analysis. In this thesis, feature tracking algorithms are developed for 2-D+Time cardiac magnetic resonance (CMR) and 3-D+Time cardiac computed tomography (CCT) image sequences that are easily acquired clinically, while emphasising reproducibility and automation in their design. First, a commercially-implemented CMR feature tracking algorithm for the analysis of steady state free precession (SSFP) cine series is evaluated in patients with hypertrophic cardiomyopathy (HCM) and arrhythmogenic right ventricular cardiomyopathy (ARVC), which primarily affect the left ventricle (LV) and right ventricle (RV), respectively, and functional impairment compared with control populations is found in both cases. The limitations of this implementation are then used to guide development of an automated algorithm for the same purpose, making use of fully convolutional neural networks (CNN) for segmentation and spline registration across all frames simultaneously for tracking. This study is performed in the subjects with HCM, and functional impairment is again identified in disease subjects. Finally, as myocardial contraction is inherently a 3-D phenomenon, a technique is developed for quantification of regional function from 3-D+Time functional CCT studies using simultaneous registration of automatically generated Loop subdivision surface models for tracking. This study is performed in canine mongrels, and compared with the current state of the art technique for CCT functional analysis. This work demonstrates the feasibility of automated, reproducible cardiac functional analysis from CMR and CCT image sequences. While work remains to be done in extending the principles demonstrated and modular components described to fully automated whole-heart analysis, it is hoped that this thesis will accelerate the clinical adoption of regional functional analysis

Vascular Landmark-Based Method for Highly Reproducible Measurement of Left Atrial Appendage Volume in Computed Tomography.

BackgroundModern computed tomographic scanning can produce 4-dimensional images of the left atrial appendage (LAA). LAA function and morphology can then be measured, to plan interventions such as occlusion and to evaluate LAA flow for thrombogenic risk analysis. A current problem here is defining a reproducible boundary between the LAA and the left atrium.MethodsThis study used retrospectively gated 4-dimensional computed tomographic data from 25 implantation and coronary artery imaging patients. In each patient, the LAA ostium was defined at multiple time points during the RR interval. To examine the reproducibility of the definition of the LAA ostium, 3 observers analyzed all time frames in each patient 3 times. Five nonconsecutive time frames from each patient were then compared using intraclass correlation coefficients to quantify the precision of the method across patients. The correlation of LAA volumes for each time frame of each patient was determined across the different observers (interobserver) and within each observer's own data sets (intraobserver).ResultsThe method was successful in 92% of patients. Two-way random-effect, absolute-agreement, single-measurement intraclass correlation coefficients for interobserver measurements were 0.984, 0.990, and 0.988, with intraobserver intraclass correlation coefficients of 0.989, 0.989, and 0.995. The intraclass correlation coefficient of all observations was 0.988.ConclusionsClassification of the LAA ostium using a stepwise procedure identifying the coumadin ridge and 2 vascular landmarks in ECG-gated computed tomography provides a viable method of establishing a highly reproducible boundary between the atrium and LAA needed to obtain LAA metrics useful for procedure planning and measuring LAA function

M-SiSSR: Regional Endocardial Function Using Multilabel Simultaneous Subdivision Surface Registration.

Quantification of regional cardiac function is a central goal of cardiology. Multiple methods, such as Coherent Point Drift (CPD) and Simultaneous Subdivision Surface Registration (SiSSR), have been used to register meshes to the endocardial surface. However, these methods do not distinguish between cardiac chambers during registration, and consequently the mesh may "slip" across the interface between two structures during contraction, resulting in inaccurate regional functional measurements. Here, we present Multilabel-SiSSR (M-SiSSR), a novel method for registering a "labeled" cardiac mesh (with each triangle assigned to a cardiac structure). We compare our results to the original, label-agnostic version of SiSSR and find both a visual and quantitative improvement in tracking of the mitral valve plane

Regional dynamics of fractal dimension of the left ventricular endocardium from cine computed tomography images.

We present a method to leverage the high fidelity of computed tomography (CT) to quantify regional left ventricular function using topography variation of the endocardium as a surrogate measure of strain. 4DCT images of 10 normal and 10 abnormal subjects, acquired with standard clinical protocols, are used. The topography of the endocardium is characterized by its regional values of fractal dimension ( F D ), computed using a box-counting algorithm developed in-house. The average F D in each of the 16 American Heart Association segments is calculated for each subject as a function of time over the cardiac cycle. The normal subjects show a peak systolic percentage change in F D of 5.9 % ± 2 % in all free-wall segments, whereas the abnormal cohort experiences a change of 2 % ± 1.2 % ( p &lt; 0.00001 ). Septal segments, being smooth, do not undergo large changes in F D . Additionally, a principal component analysis is performed on the temporal profiles of F D to highlight the possibility for unsupervised classification of normal and abnormal function. The method developed is free from manual contouring and does not require any feature tracking or registration algorithms. The F D values in the free-wall segments correlated well with radial strain and with endocardial regional shortening measurements