Automated Analysis of Corpora Callosa

Abstract. This report describes and evaluates the steps needed to perform modern model-based interpretation of the corpus callosum in MRI. The process is discussed from the initial landmark-free contours to fullfledged statistical models based on the Active Appearance Models framework. Topics treated include landmark placement, background modelling and multi-resolution analysis. Preliminary quantitative and qualitative validation in a cross-sectional study show that fully automated analysis and segmentation of the corpus callosum are feasible.

Hypertrophic cardiomyopathy: insights from extracellular volume mapping

Hypertrophic cardiomyopathy (HCM) is a genetic cardiac disease characterized by myocardial hypertrophy and fibrosis. The phenotypic expression ranges from asymptomatic patients to heart failure and sudden death.1 Disease progression and relationship between hypertrophy and fibrosis are not well understood. Extracellular volume fraction (ECV) mapping on cardiovascular magnetic resonance (CMR) can demonstrate pixel-by-pixel ECV elevation (focal or diffuse fibrosis) or reduction (cellular hypertrophy).2 Furthermore, it has been shown that physical training induces remodelling of both heart and vasculature.3,4 In particular, it has been shown that hypertrophied myocardium in athletes has lower ECV, suggesting that cardiac athletic adaptation is an adaptive one caused predominantly by cellular rather than interstitial expansion.4 Hypothesizing that ECV mapping can reveal both differential responses of left ventricular hypertrophy (LVH), we explored the distribution of ECV in HCM

Fractal dimension (df) as a new structural biomarker of clot microstructure in different stages of lung cancer

Venous thromboembolism (VTE) is common in cancer patients, and is the second commonest cause of death associated with the disease. Patients with chronic inflammation, such as cancer, have been shown to have pathological clot structures with modulated mechanical properties. Fractal dimension (df) is a new technique which has been shown to act as a marker of the microstructure and mechanical properties of blood clots, and can be performed more readily than current methods such as scanning electron microscopy (SEM). We measured df in 87 consecutive patients with newly diagnosed lung cancer prior to treatment and 47 matched-controls. Mean group values were compared for all patients with lung cancer vs controls and for limited disease vs extensive disease. Results were compared with conventional markers of coagulation, fibrinolysis and SEM images. Significantly higher values of df were observed in lung cancer patients compared with controls and patients with extensive disease had higher values than those with limited disease (p< 0.05), whilst conventional markers failed to distinguish between these groups. The relationship between df of the incipient clot and mature clot microstructure was confirmed by SEM and computational modelling: higher df was associated with highly dense clots formed of smaller fibrin fibres in lung cancer patients compared to controls. This study demonstrates that df is a sensitive technique which quantifies the structure and mechanical properties of blood clots in patients with lung cancer. Our data suggests that df has the potential to identify patients with an abnormal clot micro-structure and greatest VTE risk

The Effects of Temperature on Clot Microstructure and Strength in Healthy Volunteers

BACKGROUND: Anesthesia, critical illness, and trauma are known to alter thermoregulation, which can potentially affect coagulation and clinical outcome. This in vitro preclinical study explores the relationship between temperature change and hemostasis using a recently validated viscoelastic technique. We hypothesize that temperature change will cause significant alterations in the microstructural properties of clot. METHODS: We used a novel viscoelastic technique to identify the gel point of the blood. The gel point identifies the transition of the blood from a viscoelastic liquid to a viscoelastic solid state. Furthermore, identification of the gel point provides 3 related biomarkers: the elastic modulus at the gel point, which is a measure of clot elasticity; the time to the gel point (TGP), which is a measure of the time required to form the clot; and the fractal dimension of the clot at the gel point, df, which quantifies the microstructure of the clot. The gel point measurements were performed in vitro on whole blood samples from 136 healthy volunteers over a temperature range of 27°C to 43°C. RESULTS: There was a significant negative correlation between increases in temperature, from 27°C to 43°C, and TGP (r = −0.641, P 37°C. CONCLUSIONS: This study demonstrates that the gel point technique can identify alterations in clot microstructure because of changes in temperature. This was demonstrated in slower-forming clots with less structural complexity as temperature is decreased. We also found that significant changes in clot microstructure occurred when the temperature was ≤32°C

Precision measurement of cardiac structure and function in cardiovascular magnetic resonance using machine learning

BACKGROUND: Measurement of cardiac structure and function from images (e.g. volumes, mass and derived parameters such as left ventricular (LV) ejection fraction [LVEF]) guides care for millions. This is best assessed using cardiovascular magnetic resonance (CMR), but image analysis is currently performed by individual clinicians, which introduces error. We sought to develop a machine learning algorithm for volumetric analysis of CMR images with demonstrably better precision than human analysis. METHODS: A fully automated machine learning algorithm was trained on 1923 scans (10 scanner models, 13 institutions, 9 clinical conditions, 60,000 contours) and used to segment the LV blood volume and myocardium. Performance was quantified by measuring precision on an independent multi-site validation dataset with multiple pathologies with n = 109 patients, scanned twice. This dataset was augmented with a further 1277 patients scanned as part of routine clinical care to allow qualitative assessment of generalization ability by identifying mis-segmentations. Machine learning algorithm ('machine') performance was compared to three clinicians ('human') and a commercial tool (cvi42, Circle Cardiovascular Imaging). FINDINGS: Machine analysis was quicker (20 s per patient) than human (13 min). Overall machine mis-segmentation rate was 1 in 479 images for the combined dataset, occurring mostly in rare pathologies not encountered in training. Without correcting these mis-segmentations, machine analysis had superior precision to three clinicians (e.g. scan-rescan coefficients of variation of human vs machine: LVEF 6.0% vs 4.2%, LV mass 4.8% vs. 3.6%; both P < 0.05), translating to a 46% reduction in required trial sample size using an LVEF endpoint. CONCLUSION: We present a fully automated algorithm for measuring LV structure and global systolic function that betters human performance for speed and precision

Study protocol: MyoFit46-the cardiac sub-study of the MRC National Survey of Health and Development

BACKGROUND: The life course accumulation of overt and subclinical myocardial dysfunction contributes to older age mortality, frailty, disability and loss of independence. The Medical Research Council National Survey of Health and Development (NSHD) is the world's longest running continued surveillance birth cohort providing a unique opportunity to understand life course determinants of myocardial dysfunction as part of MyoFit46-the cardiac sub-study of the NSHD. METHODS: We aim to recruit 550 NSHD participants of approximately 75 years+ to undertake high-density surface electrocardiographic imaging (ECGI) and stress perfusion cardiovascular magnetic resonance (CMR). Through comprehensive myocardial tissue characterization and 4-dimensional flow we hope to better understand the burden of clinical and subclinical cardiovascular disease. Supercomputers will be used to combine the multi-scale ECGI and CMR datasets per participant. Rarely available, prospectively collected whole-of-life data on exposures, traditional risk factors and multimorbidity will be studied to identify risk trajectories, critical change periods, mediators and cumulative impacts on the myocardium. DISCUSSION: By combining well curated, prospectively acquired longitudinal data of the NSHD with novel CMR-ECGI data and sharing these results and associated pipelines with the CMR community, MyoFit46 seeks to transform our understanding of how early, mid and later-life risk factor trajectories interact to determine the state of cardiovascular health in older age. TRIAL REGISTRATION: Prospectively registered on ClinicalTrials.gov with trial ID: 19/LO/1774 Multimorbidity Life-Course Approach to Myocardial Health- A Cardiac Sub-Study of the MCRC National Survey of Health and Development (NSHD)

Microstructural and Microvascular Phenotype of Sarcomere Mutation Carriers and Overt Hypertrophic Cardiomyopathy

BACKGROUND: In hypertrophic cardiomyopathy (HCM), myocyte disarray and microvascular disease (MVD) have been implicated in adverse events, and recent evidence suggests that these may occur early. As novel therapy provides promise for disease modification, detection of phenotype development is an emerging priority. To evaluate their utility as early and disease-specific biomarkers, we measured myocardial microstructure and MVD in 3 HCM groups-overt, either genotype-positive (G+LVH+) or genotype-negative (G-LVH+), and subclinical (G+LVH-) HCM-exploring relationships with electrical changes and genetic substrate. METHODS: This was a multicenter collaboration to study 206 subjects: 101 patients with overt HCM (51 G+LVH+ and 50 G-LVH+), 77 patients with G+LVH-, and 28 matched healthy volunteers. All underwent 12-lead ECG, quantitative perfusion cardiac magnetic resonance imaging (measuring myocardial blood flow, myocardial perfusion reserve, and perfusion defects), and cardiac diffusion tensor imaging measuring fractional anisotropy (lower values expected with more disarray), mean diffusivity (reflecting myocyte packing/interstitial expansion), and second eigenvector angle (measuring sheetlet orientation). RESULTS: Compared with healthy volunteers, patients with overt HCM had evidence of altered microstructure (lower fractional anisotropy, higher mean diffusivity, and higher second eigenvector angle; all P<0.001) and MVD (lower stress myocardial blood flow and myocardial perfusion reserve; both P<0.001). Patients with G-LVH+ were similar to those with G+LVH+ but had elevated second eigenvector angle (P<0.001 after adjustment for left ventricular hypertrophy and fibrosis). In overt disease, perfusion defects were found in all G+ but not all G- patients (100% [51/51] versus 82% [41/50]; P=0.001). Patients with G+LVH- compared with healthy volunteers similarly had altered microstructure, although to a lesser extent (all diffusion tensor imaging parameters; P<0.001), and MVD (reduced stress myocardial blood flow [P=0.015] with perfusion defects in 28% versus 0 healthy volunteers [P=0.002]). Disarray and MVD were independently associated with pathological electrocardiographic abnormalities in both overt and subclinical disease after adjustment for fibrosis and left ventricular hypertrophy (overt: fractional anisotropy: odds ratio for an abnormal ECG, 3.3, P=0.01; stress myocardial blood flow: odds ratio, 2.8, P=0.015; subclinical: fractional anisotropy odds ratio, 4.0, P=0.001; myocardial perfusion reserve odds ratio, 2.2, P=0.049). CONCLUSIONS: Microstructural alteration and MVD occur in overt HCM and are different in G+ and G- patients. Both also occur in the absence of hypertrophy in sarcomeric mutation carriers, in whom changes are associated with electrocardiographic abnormalities. Measurable changes in myocardial microstructure and microvascular function are early-phenotype biomarkers in the emerging era of disease-modifying therapy

Electrophysiological characterization of subclinical and overt hypertrophic cardiomyopathy by magnetic resonance imaging-guided electrocardiography

Background: Ventricular arrhythmia in hypertrophic cardiomyopathy (HCM) relates to adverse structural change and genetic status. Cardiovascular magnetic resonance (CMR)–guided electrocardiographic imaging (ECGI) noninvasively maps cardiac structural and electrophysiological (EP) properties. Objectives: The purpose of this study was to establish whether in subclinical HCM (genotype [G]+ left ventricular hypertrophy [LVH]−), ECGI detects early EP abnormality, and in overt HCM, whether the EP substrate relates to genetic status (G+/G−LVH+) and structural phenotype. Methods: This was a prospective 211-participant CMR-ECGI multicenter study of 70 G+LVH−, 104 LVH+ (51 G+/53 G−), and 37 healthy volunteers (HVs). Local activation time (AT), corrected repolarization time, corrected activation-recovery interval, spatial gradients (GAT/GRTc), and signal fractionation were derived from 1,000 epicardial sites per participant. Maximal wall thickness and scar burden were derived from CMR. A support vector machine was built to discriminate G+LVH− from HV and low-risk HCM from those with intermediate/high-risk score or nonsustained ventricular tachycardia. Results: Compared with HV, subclinical HCM showed mean AT prolongation (P = 0.008) even with normal 12-lead electrocardiograms (ECGs) (P = 0.009), and repolarization was more spatially heterogenous (GRTc: P = 0.005) (23% had normal ECGs). Corrected activation-recovery interval was prolonged in overt vs subclinical HCM (P &lt; 0.001). Mean AT was associated with maximal wall thickness; spatial conduction heterogeneity (GAT) and fractionation were associated with scar (all P &lt; 0.05), and G+LVH+ had more fractionation than G−LVH+ (P = 0.002). The support vector machine discriminated subclinical HCM from HV (10-fold cross-validation accuracy 80% [95% CI: 73%-85%]) and identified patients at higher risk of sudden cardiac death (accuracy 82% [95% CI: 78%-86%]). Conclusions: In the absence of LVH or 12-lead ECG abnormalities, HCM sarcomere gene mutation carriers express an aberrant EP phenotype detected by ECGI. In overt HCM, abnormalities occur more severely with adverse structural change and positive genetic status