An amino-domino model described by a cross-peptide-bond Ramachandran plot defines amino acid pairs as local structural units.

Protein structure, both at the global and local level, dictates function. Proteins fold from chains of amino acids, forming secondary structures, α-helices and ß-strands, that, at least for globular proteins, subsequently fold into a three-dimensional structure. Here, we show that a Ramachandran-type plot focusing on the two dihedral angles separated by the peptide bond, and entirely contained within an amino acid pair, defines a local structural unit. We further demonstrate the usefulness of this cross-peptide-bond Ramachandran plot by showing that it captures ß-turn conformations in coil regions, that traditional Ramachandran plot outliers fall into occupied regions of our plot, and that thermophilic proteins prefer specific amino acid pair conformations. Further, we demonstrate experimentally that the effect of a point mutation on backbone conformation and protein stability depends on the amino acid pair context, i.e., the identity of the adjacent amino acid, in a manner predictable by our method.

Testing quantitative magnetization transfer models with membrane lipids.

PURPOSE: Quantitative magnetization transfer (qMT) models aim to quantify the contributions of lipids and macromolecules to the MRI signal. Hence, a model system that relates qMT parameters and their molecular sources may improve the interpretation of the qMT parameters. Here we used membrane lipid phantoms as a meaningful tool to study qMT models. By controlling the fraction and type of membrane lipids, we could test the accuracy, reliability, and interpretability of different qMT models. METHODS: We formulated liposomes with various lipid types and water-to-lipids fractions and measured their signals with spoiled gradient-echo MT. We fitted three known qMT models and estimated six parameters for every model. We tested the accuracy and reproducibility of the models and compared the dependency among the qMT parameters. We compared the samples' qMT parameters with their water-to-lipid fractions and with a simple MTnorm (= MTon/MToff) calculation. RESULTS: We found that the three qMT models fit the membrane lipids signals well. We also found that the estimated qMT parameters are highly interdependent. Interestingly, the estimated qMT parameters are a function of the membrane lipid type and also highly related to the water-to-lipid fraction. Finally, we find that most of the lipid sample's information can be captured using the common and easy to estimate MTnorm analysis. CONCLUSION: qMT parameters are sensitive to both the water-to-lipid fraction and to the lipid type. Estimating the water-to-lipid fraction can improve the characterization of membrane lipids' contributions to qMT parameters. Similar characterizations can be obtained using the MTnorm analysis.

Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis.

Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically meaningful terms, handling the presence of unknown medical conditions, and transparency regarding the system's limitations, both in terms of statistical performance as well as recognizing situations for which the system's predictions are irrelevant. We articulate these unmet clinical needs as machine-learning (ML) problems and systematically address them with cutting-edge ML techniques. We focus on electrocardiogram (ECG) analysis as an example domain in which AI has great potential and tackle two challenging tasks: the detection of a heterogeneous mix of known and unknown arrhythmias from ECG and the identification of underlying cardio-pathology from segments annotated as normal sinus rhythm recorded in patients with an intermittent arrhythmia. We validate our methods by simulating a screening for arrhythmias in a large-scale population while adhering to statistical significance requirements. Specifically, our system 1) visualizes the relative importance of each part of an ECG segment for the final model decision; 2) upholds specified statistical constraints on its out-of-sample performance and provides uncertainty estimation for its predictions; 3) handles inputs containing unknown rhythm types; and 4) handles data from unseen patients while also flagging cases in which the model's outputs are not usable for a specific patient. This work represents a significant step toward overcoming the limitations currently impeding the integration of AI into clinical practice in cardiology and medicine in general.

Spatial profiles provide sensitive MRI measures of the midbrain micro- and macrostructure.

The midbrain is the rostral-most part of the brainstem. It contains numerous nuclei and white matter tracts, which are involved in motor, auditory and visual processing, and changes in their structure and function have been associated with aging, as well as neurodegenerative disorders. Current tools for estimating midbrain subregions and their structure with MRI require high resolution and multi-parametric quantitative MRI measures. We propose an approach that relies on morphology to calculate profiles along the midbrain and show these profiles are sensitive to the underlying macrostructure of the midbrain. First, we show that the midbrain structure can be sampled, within subject space, along three main axes of the left and right midbrain, producing profiles that are similar across subjects. We use two data sets with different field strengths, that contain R1, R2* and QSM maps and show that the profiles are highly correlated both across subjects and between datasets. Next, we compare profiles of the midbrain that sample ROIs, and show that the profiles along the first two axes sample the midbrain in a way that reliably separates the main structures, i.e., the substantia nigra, the red nucleus, and periaqueductal gray. We further show that age differences which are localized to specific nuclei, are reflected in the profiles. Finally, we generalize the same approach to calculate midbrain profiles on a third clinically relevant dataset using HCP subjects, with metrics such as the diffusion tensor and semi-quantitative data such as T1w/T2w maps. Our results suggest that midbrain profiles, both of quantitative and semi-quantitative estimates are sensitive to the underlying macrostructure of the midbrain. The midbrain profiles are calculated in native space, and rely on simple measurements. We show that it is robust and can be easily expanded to different datasets, and as such we hope that it will be of great use to the community and to the study of the midbrain in particular.

White matter properties underlying reading abilities differ in 8-year-old children born full term and preterm: A multi-modal approach.

Many diffusion magnetic resonance imaging (dMRI) studies document associations between reading skills and fractional anisotropy (FA) within brain white matter, suggesting that efficient transfer of information across the brain contributes to individual differences in reading. Use of complementary imaging methods can determine if these associations relate to myelin content of white matter tracts. Compared to children born at term (FT), children born preterm (PT) are at risk for reading deficits. We used two MRI methods to calculate associations of reading and white matter properties in FT and PT children. Participants (N=79: 36 FT and 43 PT) were administered the Gray's Oral Reading Test at age 8. We segmented three dorsal (left arcuate and bilateral superior longitudinal fasciculus) and four ventral (bilateral inferior longitudinal fasciculus and bilateral uncinate) tracts and quantified (1) FA from dMRI and (2) R1 from quantitative T1 relaxometry. We examined correlations between reading scores and these metrics along the trajectories of the tracts. Reading positively correlated with FA in segments of left arcuate and bilateral superior longitudinal fasciculi in FT children; no FA associations were found in PT children. Reading positively correlated with R1 in segments of the left superior longitudinal, right uncinate, and left inferior longitudinal fasciculi in PT children; no R1 associations were found in FT children. Birth group significantly moderated the associations of reading and white matter metrics. Myelin content of white matter may contribute to individual differences in PT but not FT children.

Subdividing the superior longitudinal fasciculus using local quantitative MRI.

The association fibers of the superior longitudinal fasciculus (SLF) connect parietal and frontal cortical regions in the human brain. The SLF comprises of three distinct sub-bundles, each presenting a different anatomical trajectory, and specific functional roles. Nevertheless, in vivo studies of the SLF often consider the entire SLF complex as a single entity. In this work, we suggest a data-driven approach that relies on microstructure measurements for separating SLF-III from the rest of the SLF. We apply the SLF-III separation procedure in three independent datasets using parameters of diffusion MRI (fractional anisotropy), as well as relaxometry-based parameters (T1, T2, T2* and T2-weighted/T1-weighted). We show that the proposed procedure is reproducible across datasets and tractography algorithms. Finally, we suggest that differential crossing with different white-matter tracts is the source of the distinct MRI signatures of SLF-II and SLF-III.

Conduction delays in the visual pathways of progressive multiple sclerosis patients covary with brain structure.

In developed countries, multiple sclerosis (MS) is the leading cause of non-traumatic neurological disability in young adults. MS is a chronic demyelinating disease of the central nervous system, in which myelin is attacked, changing white matter structure and leaving lesions. The demyelination has a direct effect on white matter conductivity. This effect can be examined in the visual system, where damage is highly prevalent in MS, leading to substantial delays in conduction, commonly measured with visual evoked potentials (VEPs). The structural damage to the visual system in MS is often estimated with MRI measurements in the white matter. Recent developments in quantitative MRI (qMRI) provide improved sensitivity to myelin content and new structural methods allow better modeling of the axonal structure, leading researchers to link white matter microstructure to conduction properties of action potentials along fiber tracts. This study attempts to explain the variance in conduction latencies down the visual pathway using structural measurements of both the retina and the optic radiation (OR). Forty-eight progressive MS patients, participants in a longitudinal stem-cell therapy clinical trial, were included in this study, three and six months post final treatment. Twenty-seven patients had no history of optic neuritis, and were the main focus of this study. All participants underwent conventional MRI scans, as well as diffusion MRI and qMRI sequences to account for white matter microstructure. Optical coherence tomography scans were also obtained, and peripapillary retinal nerve fiber layer (pRNFL) thickness and macular volume measurements were extracted. Finally, latencies of recorded VEPs were estimated. Our results show that in non-optic neuritis progressive MS patients there is a relationship between the VEP latency and both retinal damage and OR lesion load. In addition, we find that qMRI values, sampled along the OR, are also correlated with VEP latency. Finally, we show that combining these parameters using PCA we can explain more than 40% of the inter-subject variance in VEP latency. In conclusion, this study contributes to understanding the relationship between the structural properties and conduction in the visual system in disease. We focus on the visual system, where the conduction latencies can be estimated, but the conclusions could be generalized to other brain systems where the white matter structure can be measured. It also highlights the importance of having multiple parameters when assessing the clinical stages of MS patients, which could have major implications for future studies of other white matter diseases.

A phantom system for assessing the effects of membrane lipids on water proton relaxation.

Quantitative MRI (qMRI) is a method for the non-invasive study of brain-structure-associated changes expressed with measurable units. The qMRI-derived parameters have been shown to reflect brain tissue composition such as myelin content. Nevertheless, it remains a major challenge to identify and quantify the contributions of specific molecular components to the MRI signal. Here, we describe a phantom system that can be used to evaluate the contribution of membrane lipids to qMRI-derived parameters. We used a hydration-dehydration dry film technique to formulate liposomes that can be used as a model of the bilayer lipid membrane. The liposomes were comprised of the most abundant types of lipid found in the human brain. We then applied clinically available qMRI techniques with adjusted bias corrections in order to test the ability of the phantom system to estimate multiple qMRI parameters such as proton density (PD), T1 , T2 , T2 * and magnetization transfer. In addition, we accurately measured the phantom sample water fraction (normalized PD). A similar protocol was also applied to the human brain in vivo. The phantom system allows for a reliable estimation of qMRI parameters for phantoms composed of various lipid types using a clinical MRI scanner. We also found a comparable reproducibility between the phantom and in vivo human brain qMRI estimations. To conclude, we have successfully created a biologically relevant liposome phantom system whose lipid composition can be fully controlled. Our lipid system and analysis can be used to measure the contributions to qMRI parameters of membrane lipids found in the human brain under scanning conditions that are relevant to in vivo human brain scans. Such a model system can be used to test the contributions of lipidomic changes in normal and pathological brain states.

Associations of Reading Efficiency with White Matter Properties of the Cerebellar Peduncles in Children.

Reading in children has been associated with microstructural properties of the cerebellar peduncles, the white matter pathways connecting the cerebellum to the cerebrum. In this study, we used two independent neuroimaging modalities to assess which features of the cerebellar peduncles would be associated with reading. Twenty-three 8-year-old children were evaluated on word reading efficiency and imaged using diffusion MRI (dMRI) and quantitative T1 relaxometry (qT1). We segmented the superior (SCP), middle, and inferior cerebellar peduncles and extracted two metrics: fractional anisotropy (FA) from dMRI and R1 from qT1. Tract-FA was significantly correlated with tract-R1 in left and right SCPs (left: rP(21) = .63, right: rP(21) = .76, p ≤ .001) suggesting that FA of these peduncles, at least in part, indexed myelin content. Tract-FA and tract R1 were not correlated in the other cerebellar peduncles. Reading efficiency negatively correlated with tract-FA of the left (rP(21) = - .43, p = .040) and right SCP (rP(21) = - .37, p = .079). Reading efficiency did not correlate with tract-R1 in the SCPs. The negative association of reading efficiency with tract-FA and the lack of association of reading efficiency with tract-R1 implicate properties other than myelin content as relevant to the information flow between the cerebellum and the cerebrum for individual differences in reading skills in children.

Tractography delineation of the vertical occipital fasciculus using quantitative T1 mapping.

The vertical occipital fasciculus (VOF) is a white-matter tract that connects the ventral and dorsal visual streams. The precise borders of the VOF have been a matter of dispute since its discovery in the 19th century. The presence of an adjacent vertical pathway, the posterior arcuate fasciculus, makes it especially hard to determine the anterior extent of the VOF. By integrating diffusion MRI tractography with quantitative T1 mapping we found that the vertical streamlines originating in the ventral occipito-temporal cortex show a pattern of lower T1 in more posterior streamlines. We used this pattern to develop an automatic procedure for VOF identification based on a sharp increase in the streamline T1 signature along the posterior-anterior axis. We studied the cortical endpoints of the VOF and their relation to known cytoarchitectonic and functional divisions of the cortex. These results show that multi-modal MRI information, which characterizes local tissue microstructure such as myelination, can be used to delineate white-matter tracts in vivo.

Evaluating arcuate fasciculus laterality measurements across dataset and tractography pipelines.

The arcuate fasciculi are white-matter pathways that connect frontal and temporal lobes in each hemisphere. The arcuate plays a key role in the language network and is believed to be left-lateralized, in line with left hemisphere dominance for language. Measuring the arcuate in vivo requires diffusion magnetic resonance imaging-based tractography, but asymmetry of the in vivo arcuate is not always reliably detected in previous studies. It is unknown how the choice of tractography algorithm, with each method's freedoms, constraints, and vulnerabilities to false-positive and -negative errors, impacts findings of arcuate asymmetry. Here, we identify the arcuate in two independent datasets using a number of tractography strategies and methodological constraints, and assess their impact on estimates of arcuate laterality. We test three tractography methods: a deterministic, a probabilistic, and a tractography-evaluation (LiFE) algorithm. We extract the arcuate from the whole-brain tractogram, and compare it to an arcuate bundle constrained even further by selecting only those streamlines that connect to anatomically relevant cortical regions. We test arcuate macrostructure laterality, and also evaluate microstructure profiles for properties such as fractional anisotropy and quantitative R1. We find that both tractography choice and implementing the cortical constraints substantially impact estimates of all indices of arcuate laterality. Together, these results emphasize the effect of the tractography pipeline on estimates of arcuate laterality in both macrostructure and microstructure.

Evaluating g-ratio weighted changes in the corpus callosum as a function of age and sex.

Recent years have seen a growing interest in relating MRI measurements to the structural-biophysical properties of white matter fibers. The fiber g-ratio, defined as the ratio between the inner and outer radii of the axon myelin sheath, is an important structural property of white matter, affecting signal conduction. Recently proposed modeling methods that use a combination of quantitative-MRI signals, enable a measurement of the fiber g-ratio in vivo. Here we use an MRI-based g-ratio estimation to observe the variance of the g-ratio within the corpus callosum, and evaluate sex and age related differences. To estimate the g-ratio we used a model (Stikov et al., 2011; Duval et al., 2017) based on two different WM microstructure parameters: the relative amounts of myelin (myelin volume fraction, MVF) and fibers (fiber volume fraction, FVF) in a voxel. We derived the FVF from the fractional anisotropy (FA), and estimated the MVF by using the lipid and macromolecular tissue volume (MTV), calculated from the proton density (Mezer et al., 2013). In comparison to other methods of estimating the MVF, MTV represents a stable parameter with a straightforward route of acquisition. To establish our model, we first compared histological MVF measurements (West et al., 2016) with the MRI derived MTV. We then implemented our model on a large database of 92 subjects (44 males), aged 7 to 81, in order to evaluate age and sex related changes within the corpus callosum. Our results show that the MTV provides a good estimation of MVF for calculating g-ratio, and produced values from the corpus callosum that correspond to those found in animals ex vivo and are close to the theoretical optimum, as well as to published in vivo data. Our results demonstrate that the MTV derived g-ratio provides a simple and reliable in vivo g-ratio-weighted (GR*) measurement in humans. In agreement with theoretical predictions, and unlike other tissue parameters measured with MRI, the g-ratio estimations were found to be relatively stable with age, and we found no support for a significant sexual dimorphism with age.

Tractography optimization using quantitative T1 mapping in the human optic radiation.

Diffusion MRI tractography is essential for reconstructing white-matter projections in the living human brain. Yet tractography results miss some projections and falsely identify others. A challenging example is the optic radiation (OR) that connects the thalamus and the primary visual cortex. Here, we tested whether OR tractography can be optimized using quantitative T1 mapping. Based on histology, we proposed that myelin-sensitive T1 values along the OR should remain consistently low compared with adjacent white matter. We found that complementary information from the T1 map allows for increasing the specificity of the reconstructed OR tract by eliminating falsely identified projections. This T1-filtering outperforms other, diffusion-based tractography filters. These results provide evidence that the smooth microstructural signature along the tract can be used as constructive input for tractography. Finally, we demonstrate that this approach can be applied in a case of multiple sclerosis, and generalized to the HCP-available MRI measurements. We conclude that multimodal MRI microstructural information can be used to eliminate spurious tractography results in the case of the OR.

Aortic Valve Gradient and Clinical Outcome in Patients Undergoing Transcatheter Aortic Valve Implantation for Severe Aortic Stenosis.

OBJECTIVES: To explore the relation between the baseline aortic valve gradient (AVG) as a continuous variable and clinical outcomes following transcatheter aortic valve implantation (TAVI) in general and specifically in patients with high-gradient aortic stenosis (AS). METHODS: We reviewed 317 consecutive patients who underwent TAVI at our institution. We investigated the relation between AVG as a continuous/categorical variable and outcome among all patients and in patients without low-flow low-gradient AS, using the Cox proportional hazard model adjusting for multiple prognostic variables. RESULTS: Patients had a peak AVG of 79.9 ± 22.8 mm Hg (mean 50.5 ±15.7). During a mean follow-up of 2.7 years, AVG was inversely associated with mortality and mortality or cardiac hospitalization. Every 10-mm-Hg increase in peak AVG was associated with 18% reduction in mortality (p = 0.003) and 19% reduction in mortality/cardiac hospitalization (p < 0.001). Every 10-mm-Hg increase in mean AVG was associated with a 24% reduction in both outcomes (p = 0.005 and p < 0.001). Subgroup analysis of patients with left-ventricular ejection fraction >40% or peak AVG >64 mm Hg yielded similar results. CONCLUSIONS: Mean and peak baseline AVGs are directly associated with improved outcomes after TAVI; AVG can be used to select the patients most likely to benefit from TAVI.

Type of Atrial Fibrillation and Clinical Outcomes in Patients Undergoing Transcatheter Aortic Valve Replacement.

BACKGROUND: There are limited data available regarding the relationship between atrial fibrillation (AF) clinical type, oral anticoagulation (OAC) treatment, and clinical outcome after transcatheter aortic valve replacement (TAVR). The study was designed to evaluate this relationship. METHODS: We analyzed data from the Rabin Medical Center TAVR registry, including 319 consecutive patients who underwent TAVR from 2008 to 2014. Patients were divided into three groups based on their history of AF: sinus rhythm (SR), paroxysmal AF (PAF), or nonparoxysmal AF (NPAF). RESULTS: There were 211 (66%), 56 (18%), and 52 (16%) patients in the SR, PAF, and NPAF groups, respectively. The cumulative risk for stroke or death at 2 years was highest among patients with NPAF (38%), but similarly low in PAF (15%) and SR patients (16%, P < 0.001). By multivariate analysis, patients with NPAF demonstrated a significantly higher risk of stroke or death (HR = 2.76, 95% CI 1.63-4.66, P < 0.001), as compared with SR. In contrast, patients with PAF had a similar risk of stroke or death compared with SR (HR = 0.80, P = 0.508). Patients with NPAF not treated with OAC demonstrated an 8.3-fold (P < 0.001) increased risk of stroke or death, whereas patients with PAF not treated with OAC had a similar risk of stroke or death compared with the SR group (HR = 1.25, P = 0.569). CONCLUSION: History of NPAF, but not PAF, is associated with a significant increased risk of stroke or death compared with sinus rhythm in patients undergoing TAVR.

A dataset of alternately located segments in protein crystal structures.

Protein Data Bank (PDB) files list the relative spatial location of atoms in a protein structure as the final output of the process of fitting and refining to experimentally determined electron density measurements. Where experimental evidence exists for multiple conformations, atoms are modelled in alternate locations. Programs reading PDB files commonly ignore these alternate conformations by default leaving users oblivious to the presence of alternate conformations in the structures they analyze. This has led to underappreciation of their prevalence, under characterisation of their features and limited the accessibility to this high-resolution data representing structural ensembles. We have trawled PDB files to extract structural features of residues with alternately located atoms. The output includes the distance between alternate conformations and identifies the location of these segments within the protein chain and in proximity of all other atoms within a defined radius. This dataset should be of use in efforts to predict multiple structures from a single sequence and support studies investigating protein flexibility and the association with protein function.

Primary diffuse large B-cell lymphoma of the breast: looking at pathogenesis, clinical issues and therapeutic options.

Primary breast lymphoma is a rare form of non-Hodgkin lymphoma with some distinct clinical features. The most common histopathological type is diffuse large B-cell lymphoma (DLBCL), but other less frequent subtypes are also encountered. In this review, we describe the characteristics of primary breast DLBCL, with emphasis on pathogenesis, staging, risk stratification and prognosis. In addition, key issues regarding therapy and various available therapeutic modalities are addressed, as well as the role of rituximab in therapy and whether central nervous system prophylaxis is still routinely required. There are very few prospective clinical studies addressing therapy, and available data rely mostly on retrospective case series involving small numbers of patients. Our conclusions and proposed recommendations are therefore not offered as formal guidelines. This review attempts to represent an unbiased analysis of the published data and is intended as a useful aid for clinicians treating this uncommon type of extra nodal lymphoma.

Non-invasive assessment of normal and impaired iron homeostasis in the brain.

Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissue's iron homeostasis remains a challenge. We present a magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2* relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron ions. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors' iron homeostasis, and enhances the distinction between tumor tissue and non-pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains.

Exergaming in patients with a left ventricular assist device: a feasibility study.

AIMS: Exercise games (exergames) have been recently proposed as a mode of facilitating physical activity in patients with chronic diseases. Although patients supported with left ventricular assist devices (LVADs) benefit from physical activity, specific LVAD-related issues hinder their ability to exercise properly. The objective of this study was to assess the feasibility and safety of exergaming in LVAD-supported patients. METHODS AND RESULTS: Eleven LVAD-supported patients were enrolled in a 4 week exergaming programme using Nintendo Wii console with five sport games. Patients were instructed to play for 30 min a day, 5 days a week. Data on exercise capacity and exergaming were collected by using the 6 min walk test (6MWT) and a daily self-report diary, respectively. Feasibility of using the console and its safety was assessed by a semi-structured patient interview. Quality of life was assessed by the Minnesota Living with Heart failure Questionnaire (MLHFQ) and the Cantril's Ladder of Life. Safety was assessed by patient's report in interview and diary. The study group consisted of 10 male patients and 1 female patient, mean age of 67 ± 7 years, of whom 10 were supported with the HeartMate 3 LVAD for a median of 10 (interquartile range 3, 21) months. Baseline exercise capacity assessed by the 6MWT ranged from 240 to 570 m (mean 448 ± 112). After 4 weeks of exergaming, 6MWT distance increased from a mean of 448 ± 112 (evaluated in six patients) to 472 ± 113 m (P = 0.023). Patients' Cantril's Ladder of Life score improved numerically from an average of 6.13 to 7.67, as did their MLHFQ score from 45.9 ± 27 to 38.7 ± 18, with higher and lower scores, respectively, reflecting higher quality of life. No specific LVAD-related safety issues regarding exergaming were reported. CONCLUSIONS: Exergaming was found to be a safe and feasible mode for encouraging physical activity in LVAD-supported patients and carries a potential for improving exercise capacity and quality of life in these patients. Larger scale studies are warranted to further investigate the effect of exergaming in this patient population.