Gated metabolic myocardial imaging, a surrogate for dual perfusion-metabolism imaging by positron emission tomography

Acknowledgments The authors are grateful for the help from Dr H Ali and Dr A Dawson. Funding: This study was performed using a research grant from the Aberdeen Royal Hospitals Trust's Endowment Fund, with further support from the Department of Medical Physics at the University of Aberdeen, for which the authors express their gratitude.Peer reviewedPublisher PD

Mixed Valvular Disease Following Transcatheter Aortic Valve Replacement: Quantification and Systematic Differentiation Using Clinical Measurements and Image-Based Patient‐Specific In Silico Modeling

Background: Mixed valvular disease (MVD), mitral regurgitation (MR) from pre‐existing disease in conjunction with paravalvular leak (PVL) following transcatheter aortic valve replacement (TAVR), is one of the most important stimuli for left ventricle (LV) dysfunction, associated with cardiac mortality. Despite the prevalence of MVD, the quantitative understanding of the interplay between pre‐existing MVD, PVL, LV, and post‐TAVR recovery is meager. Methods and Results: We quantified the effects of MVD on valvular‐ventricular hemodynamics using an image‐based patient‐specific computational framework in 72 MVD patients. Doppler pressure was reduced by TAVR (mean, 77%; N=72; P<0.05), but it was not always accompanied by improvements in LV workload. TAVR had no effect on LV workload in 22 patients, and LV workload post‐TAVR significantly rose in 32 other patients. TAVR reduced LV workload in only 18 patients (25%). PVL significantly alters LV flow and increases shear stress on transcatheter aortic valve leaflets. It interacts with mitral inflow and elevates shear stresses on mitral valve and is one of the main contributors in worsening of MR post‐TAVR. MR worsened in 32 patients post‐TAVR and did not improve in 18 other patients. Conclusions: PVL limits the benefit of TAVR by increasing LV load and worsening of MR and heart failure. Post‐TAVR, most MVD patients (75% of N=72; P<0.05) showed no improvements or even worsening of LV workload, whereas the majority of patients with PVL, but without that pre‐existing MR condition (60% of N=48; P<0.05), showed improvements in LV workload. MR and its exacerbation by PVL may hinder the success of TAVR

Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation

In cardiac magnetic resonance imaging, fully-automatic segmentation of the heart enables precise structural and functional measurements to be taken, e.g. from short-axis MR images of the left-ventricle. In this work we propose a recurrent fully-convolutional network (RFCN) that learns image representations from the full stack of 2D slices and has the ability to leverage inter-slice spatial dependences through internal memory units. RFCN combines anatomical detection and segmentation into a single architecture that is trained end-to-end thus significantly reducing computational time, simplifying the segmentation pipeline, and potentially enabling real-time applications. We report on an investigation of RFCN using two datasets, including the publicly available MICCAI 2009 Challenge dataset. Comparisons have been carried out between fully convolutional networks and deep restricted Boltzmann machines, including a recurrent version that leverages inter-slice spatial correlation. Our studies suggest that RFCN produces state-of-the-art results and can substantially improve the delineation of contours near the apex of the heart.Comment: MICCAI Workshop RAMBO 201

A multiscale model for collagen alignment in wound healing

It is thought that collagen alignment plays a significant part in scar tissue formation during dermal wound healing. We present a multiscale model for collagen deposition and alignment during this process. We consider fibroblasts as discrete units moving within an extracellular matrix of collagen and fibrin modelled as continua. Our model includes flux induced alignment of collagen by fibroblasts, and contact guidance of fibroblasts by collagen fibres. We can use the model to predict the effects of certain manipulations, such as varying fibroblast speed, or placing an aligned piece of tissue in the wound. We also simulate experiments which alter the TGF-β concentrations in a healing dermal wound and use the model to offer an explanation of the observed influence of this growth factor on scarring

Obese Subjects Show Sex-Specific Differences in Right Ventricular Hypertrophy

As right ventricular (RV) remodeling in obesity remains underinvestigated, and the impact of left ventricular (LV) diastolic dysfunction on RV hypertrophy is unknown, we aimed to investigate whether (1) sex-specific patterns of RV remodeling exist in obesity and (2) LV diastolic dysfunction in obesity is related to RV hypertrophy.Seven hundred thirty-nine subjects (women, n=345; men, n=394) without identifiable cardiovascular risk factors (body mass index [BMI], 15.3-59.2 kg/m2) underwent cardiovascular magnetic resonance (1.5 T) to measure RV mass (g), RV end-diastolic volume (mL), RV mass/volume ratio, and LV diastolic peak filling rate (mL/s). All subjects were normotensive (average, 119±11/73±8 mm Hg), normoglycaemic (4.8±0.5 mmol/L), and normocholesterolaemic (4.8±0.9 mmol/L) at the time of scanning. Across both sexes, there was a moderately strong positive correlation between BMI and RV mass (men, +0.8 g per BMI point increase; women, +1.0 g per BMI point increase; both P&lt;0.001). Whereas women exhibited RV cavity dilatation (RV end-diastolic volume, +1.0 mL per BMI point increase; P&lt;0.001), BMI was not correlated with RV end-diastolic volume in men (R=0.04; P=0.51). Concentric RV remodeling was present in both sexes, with RV mass/volume ratio being positively correlated to BMI (men, R=0.41; women, R=0.51; both P&lt;0.001). Irrespective of sex, the LV peak filling rate was negatively correlated with both RV mass (men, R=-0.43; women, R=-0.44; both P&lt;0.001) and RV mass/volume ratio (men, R=-0.37; women, R=-0.35; both P&lt;0.001).A sex difference in RV remodeling exists in obesity. Whereas men exhibit concentric RV remodeling, women exhibit a mixed pattern of eccentric and concentric remodeling. Regardless of sex, reduced LV diastolic function is associated with concentric RV remodeling

Left ventricular heart failure and pulmonary hypertension

In patients with left ventricular heart failure (HF), the development of pulmonary hypertension (PH) and right ventricular (RV) dysfunction are frequent and have important impact on disease progression, morbidity, and mortality, and therefore warrant clinical attention. Pulmonary hypertension related to left heart disease (LHD) by far represents the most common form of PH, accounting for 65–80% of cases. The proper distinction between pulmonary arterial hypertension and PH-LHD may be challenging, yet it has direct therapeutic consequences. Despite recent advances in the pathophysiological understanding and clinical assessment, and adjustments in the haemodynamic definitions and classification of PH-LHD, the haemodynamic interrelations in combined post- and pre-capillary PH are complex, definitions and prognostic significance of haemodynamic variables characterizing the degree of pre-capillary PH in LHD remain suboptimal, and there are currently no evidence-based recommendations for the management of PH-LHD. Here, we highlight the prevalence and significance of PH and RV dysfunction in patients with both HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF), and provide insights into the complex pathophysiology of cardiopulmonary interaction in LHD, which may lead to the evolution from a ‘left ventricular phenotype’ to a ‘right ventricular phenotype’ across the natural history of HF. Furthermore, we propose to better define the individual phenotype of PH by integrating the clinical context, non-invasive assessment, and invasive haemodynamic variables in a structured diagnostic work-up. Finally, we challenge current definitions and diagnostic short falls, and discuss gaps in evidence, therapeutic options and the necessity for future developments in this context

Cancer modelling: Getting to the heart of the problem

Paradoxically, improvements in healthcare that have enhanced the life expectancy of humans in the Western world have, indirectly, increased the prevalence of certain types of cancer such as prostate and breast. It remains unclear whether this phenomenon should be attributed to the ageing process itself or the cumulative effect of prolonged exposure to harmful environmental stimuli such as ultraviolet light, radiation and carcinogens (Franks and Teich, 1988). Equally, there is also compelling evidence that certain genetic abnormalities can predispose individuals to specific cancers (Ilyas et al., 1999). The variety of factors that have been implicated in the development of solid tumours stems, to a large extent, from the fact that ‘cancer’ is a generic term, often used to characterize a series of disorders that share common features. At this generic level of description, cancer may be viewed as a cellular disease in which controls that usually regulate growth and maintain homeostasis are disrupted. Cancer is typically initiated by genetic mutations that lead to enhanced mitosis of a cell lineage and the formation of an avascular tumour. Since it receives nutrients by diffusion from the surrounding tissue, the size of an avascular tumour is limited to several millimeters in diameter. Further growth relies on the tumour acquiring the ability to stimulate the ingrowth of a new, circulating blood supply from the host vasculature via a process termed angiogenesis (Folkman, 1974). Once vascularised, the tumour has access to a vast nutrient source and rapid growth ensues. Further, tumour fragments that break away from the primary tumour, on entering the vasculature, may be transported to other organs in which they may establish secondary tumours or metastases that further compromise the host. Invasion is another key feature of solid tumours whereby contact with the tissue stimulates the production of enzymes that digest the tissue, liberating space into which the tumour cells migrate. Thus, cancer is a complex, multiscale process. The spatial scales of interest range from the subcellular level, to the cellular and macroscopic (or tissue) levels while the timescales may vary from seconds (or less) for signal transduction pathways to months for tumour doubling times The variety of phenomena involved, the range of spatial and temporal scales over which they act and the complex way in which they are inter-related mean that the development of realistic theoretical models of solid tumour growth is extremely challenging. While there is now a large literature focused on modelling solid tumour growth (for a review, see, for example, Preziosi, 2003), existing models typically focus on a single spatial scale and, as a result, are unable to address the fundamental problem of how phenomena at different scales are coupled or to combine, in a systematic manner, data from the various scales. In this article, a theoretical framework will be presented that is capable of integrating a hierarchy of processes occurring at different scales into a detailed model of solid tumour growth (Alarcon et al., 2004). The model is formulated as a hybrid cellular automaton and contains interlinked elements that describe processes at each spatial scale: progress through the cell cycle and the production of proteins that stimulate angiogenesis are accounted for at the subcellular level; cell-cell interactions are treated at the cellular level; and, at the tissue scale, attention focuses on the vascular network whose structure adapts in response to blood flow and angiogenic factors produced at the subcellular level. Further coupling between the different spatial scales arises from the transport of blood-borne oxygen into the tissue and its uptake at the cellular level. Model simulations will be presented to illustrate the effect that spatial heterogeneity induced by blood flow through the vascular network has on the tumour’s growth dynamics and explain how the model may be used to compare the efficacy of different anti-cancer treatment protocols