Community delivery of semiautomated fractal analysis tool in cardiac mr for trabecular phenotyping.

PURPOSE: To report the development of easy-to-use magnetic resonance imaging (MRI) fractal tools deployed on platforms accessible to all. The trabeculae of the left ventricle vary in health and disease but their measurement is difficult. Fractal analysis of cardiac MR images can measure trabecular complexity as a fractal dimension (FD). MATERIALS AND METHODS: This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the local Institutional Review Board. Participants provided written informed consent. The original MatLab implementation (region-based level set segmentation and box-counting algorithm) was recoded for two platforms (OsiriX and a clinical MR reporting platform [cvi42 , Circle Cardiovascular Imaging, Calgary, Canada]). For validation, 100 subjects were scanned at 1.5T and 20 imaged twice for interstudy reproducibility. Cines were analyzed by the three tools and FD variability determined. Manual trabecular delineation by an expert reader (R1) provided ground truth contours for validation of segmentation accuracy by point-to-curve (P2C) distance estimates. Manual delineation was repeated by R1 and a second reader (R2) on 15 cases for intra/interobserver variability. RESULTS: FD by OsiriX and the clinical MR reporting platform showed high correlation with MatLab values (correlation coefficients: 0.96 [95% CI: 0.95-0.97] and 0.96 [0.95-0.96]) and high interstudy and intraplatform reproducibility. Semiautomated contours in OsiriX and the clinical MR reporting platform were highly correlated with ground truth contours evidenced by low P2C errors: 0.882 ± 0.76 mm and 0.709 ± 0.617 mm. Validity of ground truth contours was inferred from low P2C errors between readers (R1-R1: 0.798 ± 0.718 mm; R1-R2: 0.804 ± 0.649 mm). CONCLUSION: This set of accessible fractal tools that measure trabeculation in the heart have been validated and released to the cardiac MR community (http://j.mp/29xOw3B) to encourage novel clinical applications of fractals in the cardiac imaging domain. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1082-1088.

Utility of Real Time 3D Echocardiography for the Assessment of Left Ventricular Mass in Patients with Hypertrophic Cardiomyopathy: Comparison with Cardiac Magnetic Resonance.

INTRODUCTION AND OBJECTIVES: Patients with hypertrophic cardiomyopathy (HCM) have irregular ventricular shapes with small and sometimes obliterated cavities at end-systole that affect the quantification of left ventricular mass (LVM) by conventional methods, such as M-mode or two-dimensional echocardiography. The goal of this study was to validate the use of real time three-dimensional echocardiography (RT3DE) to quantify LVM using cardiac magnetic resonance imaging (CMR) as a reference, in a large population of patients with different types of HCM. METHODS: Forty-eight consecutive patients with HCM had a complete transthoracic examination and CMR performed within 7 days. LVM was calculated by M-mode and RT3DE and compared to CMR that served as gold standard. RESULTS: Left ventricular mass calculated by RT3DE was 195 ± 41 g and 187 ± 49 g by CMR. The correlation between the two methods was moderate, with a Lin index of 0.63 and good linear correlation (r = 0.63, P < 0.0001). The correlation was high when RT3DE was of high or adequate image quality. The correlation between LVM by M-mode and CMR was poor. CONCLUSION: Three-dimensional echocardiography is an accurate method for the quantification of LVM in patients with different subtypes of HCM that is in better agreement with CMR reference values than M-mode measurements.

Fractal frontiers in cardiovascular magnetic resonance: towards clinical implementation.

Many of the structures and parameters that are detected, measured and reported in cardiovascular magnetic resonance (CMR) have at least some properties that are fractal, meaning complex and self-similar at different scales. To date however, there has been little use of fractal geometry in CMR; by comparison, many more applications of fractal analysis have been published in MR imaging of the brain.This review explains the fundamental principles of fractal geometry, places the fractal dimension into a meaningful context within the realms of Euclidean and topological space, and defines its role in digital image processing. It summarises the basic mathematics, highlights strengths and potential limitations of its application to biomedical imaging, shows key current examples and suggests a simple route for its successful clinical implementation by the CMR community.By simplifying some of the more abstract concepts of deterministic fractals, this review invites CMR scientists (clinicians, technologists, physicists) to experiment with fractal analysis as a means of developing the next generation of intelligent quantitative cardiac imaging tools.

Automatic cardiac LV segmentation in MRI using modified graph cuts with smoothness and interslice constraints.

PURPOSE: Magnetic resonance imaging (MRI), specifically late-enhanced MRI, is the standard clinical imaging protocol to assess cardiac viability. Segmentation of myocardial walls is a prerequisite for this assessment. Automatic and robust multisequence segmentation is required to support processing massive quantities of data. METHODS: A generic rule-based framework to automatically segment the left ventricle myocardium is presented here. We use intensity information, and include shape and interslice smoothness constraints, providing robustness to subject- and study-specific changes. Our automatic initialization considers the geometrical and appearance properties of the left ventricle, as well as interslice information. The segmentation algorithm uses a decoupled, modified graph cut approach with control points, providing a good balance between flexibility and robustness. RESULTS: The method was evaluated on late-enhanced MRI images from a 20-patient in-house database, and on cine-MRI images from a 15-patient open access database, both using as reference manually delineated contours. Segmentation agreement, measured using the Dice coefficient, was 0.81±0.05 and 0.92±0.04 for late-enhanced MRI and cine-MRI, respectively. The method was also compared favorably to a three-dimensional Active Shape Model approach. CONCLUSION: The experimental validation with two magnetic resonance sequences demonstrates increased accuracy and versatility.

Extracellular Volume Fraction by Computed Tomography Predicts Long-Term Prognosis Among Patients With Cardiac Amyloidosis.

BACKGROUND: Light chain (AL) and transthyretin (ATTR) amyloid fibrils are deposited in the extracellular space of the myocardium, resulting in heart failure and premature mortality. Extracellular expansion can be quantified by computed tomography, offering a rapid, cheaper, and more practical alternative to cardiac magnetic resonance, especially among patients with cardiac devices or on renal dialysis. OBJECTIVES: This study sought to investigate the association of extracellular volume fraction by computed tomography (ECVCT), myocardial remodeling, and mortality in patients with systemic amyloidosis. METHODS: Patients with confirmed systemic amyloidosis and varying degrees of cardiac involvement underwent electrocardiography-gated cardiac computed tomography. Whole heart and septal ECVCT was analyzed. All patients also underwent clinical assessment, electrocardiography, echocardiography, serum amyloid protein component, and/or technetium-99m (99mTc) 3,3-diphosphono-1,2-propanodicarboxylic acid scintigraphy. ECVCT was compared across different extents of cardiac infiltration (ATTR Perugini grade/AL Mayo stage) and evaluated for its association with myocardial remodeling and all-cause mortality. RESULTS: A total of 72 patients were studied (AL: n = 35, ATTR: n = 37; median age: 67 [IQR: 59-76] years, 70.8% male). Mean septal ECVCT was 42.7% ± 13.1% and 55.8% ± 10.9% in AL and ATTR amyloidosis, respectively, and correlated with indexed left ventricular mass (r = 0.426; P < 0.001), left ventricular ejection fraction (r = 0.460; P < 0.001), N-terminal pro-B-type natriuretic peptide (r = 0.563; P < 0.001), and high-sensitivity troponin T (r = 0.546; P < 0.001). ECVCT increased with cardiac amyloid involvement in both AL and ATTR amyloid. Over a mean follow-up of 5.3 ± 2.4 years, 40 deaths occurred (AL: n = 14 [35.0%]; ATTR: n = 26 [65.0%]). Septal ECVCT was independently associated with all-cause mortality in ATTR (not AL) amyloid after adjustment for age and septal wall thickness (HR: 1.046; 95% CI: 1.003-1.090; P = 0.037). CONCLUSIONS: Cardiac amyloid burden quantified by ECVCT is associated with adverse cardiac remodeling as well as all-cause mortality among ATTR amyloid patients. ECVCT may address the need for better identification and risk stratification of amyloid patients, using a widely accessible imaging modality.

The Medical Segmentation Decathlon.

International challenges have become the de facto standard for comparative assessment of image analysis algorithms. Although segmentation is the most widely investigated medical image processing task, the various challenges have been organized to focus only on specific clinical tasks. We organized the Medical Segmentation Decathlon (MSD)-a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities to investigate the hypothesis that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. MSD results confirmed this hypothesis, moreover, MSD winner continued generalizing well to a wide range of other clinical problems for the next two years. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to scientists that are not versed in AI model training.

Standardised computed tomographic assessment of left atrial morphology and tissue thickness in humans.

AIMS: Left atrial (LA) remodelling is a common feature of many cardiovascular pathologies and is a sensitive marker of adverse cardiovascular outcomes. The aim of this study was to establish normal ranges for LA parameters derived from coronary computed tomographic angiography (CCTA) imaging using a standardised image processing pipeline to establish normal ranges in a previously described cohort. METHODS: CCTA imaging from 193 subjects recruited to the Budapest GLOBAL twin study was analysed. Indexed LA cavity volume (LACVi), LA surface area (LASAi), wall thickness and LA tissue volume (LATVi) were calculated. Wall thickness maps were combined into an atlas. Indexed LA parameters were compared with clinical variables to identify early markers of pathological remodelling. RESULTS: LACVi is similar between sexes (31 ml/m2 v 30 ml/m2) and increased in hypertension (33 ml/m2 v 29 ml/m2, p = 0.009). LASAi is greater in females than males (47.8 ml/m2 v 45.8 ml/m2 male, p = 0.031). Median LAWT was 1.45 mm. LAWT was lowest at the inferior portion of the posterior LA wall (1.14 mm) and greatest in the septum (median = 2.0 mm) (p < 0.001). Conditions known to predispose to the development of AF were not associated with differences in tissue thickness. CONCLUSIONS: The reported LACVi, LASAi, LATVi and tissue thickness derived from CCTA may serve as reference values for this age group and clinical characteristics for future studies. Increased LASAi in females in the absence of differences in LACVi or LATVi may indicate differential LA shape changes between the sexes. AF predisposing conditions, other than sex, were not associated with detectable changes in LAWT.Clinical trial registration:http://www.ClinicalTrials.gov/NCT01738828.

Cardiac injuries in blunt chest trauma.

Blunt chest traumas are a clinical challenge, both for diagnosis and treatment. The use of cardiovascular magnetic resonance can play a major role in this setting. We present two cases: a 12-year-old boy and 45-year-old man. Late gadolinium enhancement imaging enabled visualization of myocardial damage resulting from the trauma.

Automatic rib cage unfolding with CT cylindrical projection reformat in polytraumatized patients for rib fracture detection and characterization: Feasibility and clinical application.

OBJECTIVES: To assess the use of CT with unfolded cylindrical projection (UCP) for rib fracture detection and characterization. METHODS: The images from 60 polytraumatized patients who underwent whole body CT were evaluated for the presence and characterization of rib fractures (displaced or not, single or multiple). Two readers independently evaluated conventional CT images and UCP images in two readout sessions at least one month apart. All readouts were timed. A gold standard was established by two radiologists with 12 and 22 years of clinical experience based on the combined analysis of conventional and UCP reformats. RESULTS: Using UCP, the mean evaluation time was 27%-54% shorter (P = 0.01 and <0.0001) while maintaining a comparable diagnostic performance (sensitivity and specificity of 68.4-79.1% and 99.5-99.6% for conventional reformats and 70.6-91.0% and 96.8-97.7% for UCP) and a good reproducibility (Kappa of 0.71). The multiple fracture detection ratio of UCP was similar to that of conventional reformats (>80%). There were more false positives and false negatives using UCP and displaced fractures were harder to characterize. CONCLUSION: UCP yielded a diagnostic performance similar to that of conventional reformats for the detection of rib fractures with a good reproducibility and a noticeable reduction in evaluation time.

Personalized computational modeling of left atrial geometry and transmural myofiber architecture.

Atrial fibrillation (AF) is a supraventricular tachyarrhythmia characterized by complete absence of coordinated atrial contraction and is associated with an increased morbidity and mortality. Personalized computational modeling provides a novel framework for integrating and interpreting the role of atrial electrophysiology (EP) including the underlying anatomy and microstructure in the development and sustenance of AF. Coronary computed tomography angiography data were segmented using a statistics-based approach and the smoothed voxel representations were discretized into high-resolution tetrahedral finite element (FE) meshes. To estimate the complex left atrial myofiber architecture, individual fiber fields were generated according to morphological data on the endo- and epicardial surfaces based on local solutions of Laplace's equation and transmurally interpolated to tetrahedral elements. The influence of variable transmural microstructures was quantified through EP simulations on 3 patients using 5 different fiber interpolation functions. Personalized geometrical models included the heterogeneous thickness distribution of the left atrial myocardium and subsequent discretization led to high-fidelity tetrahedral FE meshes. The novel algorithm for automated incorporation of the left atrial fiber architecture provided a realistic estimate of the atrial microstructure and was able to qualitatively capture all important fiber bundles. Consistent maximum local activation times were predicted in EP simulations using individual transmural fiber interpolation functions for each patient suggesting a negligible effect of the transmural myofiber architecture on EP. The established modeling pipeline provides a robust framework for the rapid development of personalized model cohorts accounting for detailed anatomy and microstructure and facilitates simulations of atrial EP.