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Cardiosphere-derived cells (CDCs) are progenitor cells derived from heart tissue and have shown promising results in preclinical models. APOSEC, the secretome of irradiated peripheral blood mononuclear cells, has decreased infarct size in acute and chronic experimental myocardial infarction (MI). We enhanced the effect of CDCs with APOSEC preconditioning (apoCDC) and investigated the reparative effect in a translational pig model of reperfused MI. Supernatants of CDCs, assessed by proteomic analysis, revealed reduced production of extracellular matrix proteins after in vitro APOSEC preconditioning. In a porcine model of catheter-based reperfused anterior acute MI (AMI), CDCs with (apoCDC, n = 8) or without APOSEC preconditioning (CDC, n = 6) were infused intracoronary, 15 min after the start of reperfusion. Untreated AMI animals (n = 7) and sham procedures (n = 5) functioned as controls. 2-deoxy-2-(18 F)-fluoro-D-glucose-positron emission tomography-magnetic resonance imaging ([18F]FDG-PET-MRI), with late enhancement after 1 month, showed reduced scar volume and lower transmurality of the infarcted area in CDC and apoCDC compared to AMI controls. Segmental quantitative PET images displayed indicated more residual viability in apoCDC. The left-ventricle (LV) ejection fraction was improved nonsignificantly to 45.8% ± 8.6% for apoCDC and 43.5% ± 7.1% for CDCs compared to 38.5% ± 4.4% for untreated AMI. Quantitative hybrid [18F]FDG-PET-MRI demonstrated improved metabolic and functional recovery after CDC administration, whereas apoCDCs induced preservation of viability of the infarcted area.

Magnetic resonance imaging (MRI) has become an essential diagnostic modality for congenital disorders of the central nervous system. Recent advancements have transformed foetal MRI into a clinically feasible tool, and in an effort to find predictors of clinical outcomes in spinal dysraphism, foetal MRI began to unveil its potential. The purpose of our review is to introduce MRI techniques to experts with diverse backgrounds, who are involved in the management of spina bifida. We introduce advanced foetal MRI postprocessing potentially improving the diagnostic work-up. Importantly, we discuss how postprocessing can lead to a more efficient utilisation of foetal or neonatal MRI data to depict relevant anatomical characteristics. We provide a critical perspective on how structural, diffusion and metabolic MRI are utilised in an endeavour to shed light on the correlates of impaired development. We found that the literature is consistent about the value of MRI in providing morphological cues about hydrocephalus development, hindbrain herniation or outcomes related to shunting and motor functioning. MRI techniques, such as foetal diffusion MRI or diffusion tractography, are still far from clinical use; however, postnatal studies using these methods revealed findings that may reflect early neural correlates of upstream neuronal damage in spinal dysraphism.

Funding Acknowledgements Type of funding sources: None. Purpose We sought to retrospectively evaluate the feasibility of identifying the fetal cardiac and thoracic vascular structures with non-gated dynamic balanced steady-state free precession MRI sequences. Methods We retrospectively assessed the visibility of cardiovascular anatomy in 66 fetuses without suspicion of congenital heart defect (mean gestational age 27+/- 4, range 21-38 weeks). Non-gated dynamic balanced steady-state free precession (SSFP) sequences were acquired in three planes (axial, coronal and sagittal) of the fetal thorax (slice thickness 4-5mm, FOV 400, FA 60°, matrix 256x256). The images were analysed following a segmental approach in consensus reading by an experienced paediatric cardiologist and radiologist. An imaging score was defined by giving one point to each visualized structure. Basic diagnostic structures included the atria, ventricles, systemic veins, right and left ventricular outflow tracts (RVOT/LVOT), aortic arch, descending aorta (DAO), ductus arteriosus and thymus (12 points); advanced diagnostic features included the atrioventricular (AV) valves, pulmonary arteries and veins, supraaortic arteries and trachea, yielding a maximum score of 21 points. Image quality was rated from 0 (poor) to 2 (good). The influence of gestational age (GA), field strength, placenta position, and maternal panniculus on image quality and imaging score were tested. Results 34 scans were performed at 1.5 T, 32 at 3 T. Heart position, atria and ventricles could be seen in all 66 fetuses. Basic diagnosis (>12 points) was achieved in 60 (90%) cases, with visualization of the IVC and SVC in 65 (98%) and 63 (95%), RVOT in 62 (94%), LVOT in 61 (92%), aortic arch in 60 (91%), DAO in 64 (97%), ductus arteriosus in 59 (89%) and thymus in 50 (76%) fetuses. The AV valves were recognised in 55 (83%), the pulmonary arteries in 35 (53%), at least one pulmonary vein in 46 (70%), the supraaortic arteries in 42 (64%), and the trachea in 59 (89%) fetuses. The mean imaging score was 16.8 +/- 3.7. Maternal panniculus (r -0.3; p 0.01) and gestational age (r 0.6; p < 0.001) correlated with imaging score. Field strength influenced image quality, with 1.5 T being better than 3T images (p 0.04), but not the total imaging score. Imaging score or quality were independent from placenta position. Conclusions Fetal heart MRI with a non-gated SSFP sequence in multiple planes enables recognition of basic cardiovascular anatomy. Advanced diagnostics may be limited by thick maternal panniculus, lower GA and higher field strength.

It is critical to quantitatively analyse the developing human fetal brain in order to fully understand neurodevelopment in both normal fetuses and those with congenital disorders. To facilitate this analysis, automatic multi-tissue fetal brain segmentation algorithms are needed, which in turn requires open datasets of segmented fetal brains. Here we introduce a publicly available dataset of 50 manually segmented pathological and non-pathological fetal magnetic resonance brain volume reconstructions across a range of gestational ages (20 to 33 weeks) into 7 different tissue categories (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, deep grey matter, brainstem/spinal cord). In addition, we quantitatively evaluate the accuracy of several automatic multi-tissue segmentation algorithms of the developing human fetal brain. Four research groups participated, submitting a total of 10 algorithms, demonstrating the benefits the dataset for the development of automatic algorithms., Scientific Data, 8 (1), ISSN:2052-4463

Inhibition abilities are often impaired in children born very preterm. In typically-developing individuals, inhibition has been associated with structural brain connectivity (SC). As SC is frequently altered following preterm birth, this study investigated whether aberrant SC underlies inhibition deficits in school-aged children born very preterm. In a group of 67 very preterm participants aged 8–13 years and 69 term-born peers, inhibition abilities were assessed with two tasks. In a subgroup of 50 very preterm and 62 term-born participants, diffusion tensor imaging (DTI) data were collected. Using network-based statistics (NBS), mean fractional anisotropy (FAmean) was compared between groups. Associations of FAmean and inhibition abilities were explored through linear regression. The composite score of inhibition abilities was lower in the very preterm group (M ​= ​−0.4, SD ​= ​0.8) than in the term-born group (M ​= ​0.0, SD ​= ​0.8) but group differences were not significant when adjusting for age, sex and socio-economic status (β ​= ​−0.13, 95%-CI [-0.30, 0.04], p ​= ​0.13). In the very preterm group, FAmean was significantly lower in a network comprising thalamo-frontal, thalamo-temporal, frontal, cerebellar and intra-hemispheric connections than in the term-born group (t ​= ​5.21, lowest p-value ​= ​0.001). Irrespective of birth status, a network comprising parietal, cerebellar and subcortical connections was positively associated with inhibition abilities (t ​= ​4.23, lowest p-value ​= ​0.02). Very preterm birth results in long-term alterations of SC at network-level. As networks underlying inhibition abilities do not overlap with those differing between the groups, FAmean may not be adequate to explain inhibition problems in very preterm children. Future studies should combine complementary measures of brain connectivity to address neural correlates of inhibition abilities.

Background In utero intravoxel incoherent motion magnetic resonance imaging (IVIM-MRI) provides a novel method for examining microvascular perfusion fraction and diffusion in the developing human fetus. Purpose To characterize gestational changes in the microvascular perfusion fraction of the placenta, fetal liver, and lungs using IVIM-MRI. Study type Retrospective, cross-sectional study. Subjects Fifty-five datasets from 33 singleton pregnancies were acquired (17-36 gestational weeks). Field strength/sequence In utero diffusion-weighted echo-planar imaging at 1.5T and 3.0T with b-factors ranging from 0 to 900 s/mm2 in 16 steps. Assessment Using the IVIM principle, microvascular perfusion fraction (f), pseudodiffusion (D*), and diffusion coefficients (d) were estimated for the placenta, liver, and lungs with a biexponential model. A free-form nonlinear deformation algorithm was used to correct for the frame-by-frame motion of the fetal organs and the placenta. The IVIM parameters were then compared to a Doppler ultrasound-based assessment of the umbilical artery resistance index. Statistical tests Pearson product-moment correlation coefficient (PMCC) to reveal outlier corrected correlations between Doppler and IVIM parameters. Gestational age-related changes were assessed using linear regression analysis (LR). Results Placental f (0.29 ± 0.08) indicates high blood volume in the microvascular compartment, moderately increased during gestation (LR, R = 0.338), and correlated negatively with the umbilical artery resistance index (PMCC, R = -0.457). The f of the liver decreased sharply during gestation (LR, R = -0.436). Lung maturation was characterized by increasing perfusion fraction (LR, R = 0.547), and we found no gestational changes in d and D* values (LR, R = -0.013 and R = 0.051, respectively). The Doppler measurements of the umbilical artery and middle cerebral artery did not correlate with the IVIM parameters of the lungs and liver. Data conclusion Gestational age-associated changes of the placental, liver, and lung IVIM parameters likely reflect changes in placental and fetal circulation, and characterize the trajectory of microstructural and functional maturation of the fetal vasculature. Level of evidence 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017.

Developmental pathoconnectomics is an emerging field that aims to unravel the events leading to and outcome from disrupted brain connectivity development. Advanced magnetic resonance imaging (MRI) technology enables the portrayal of human brain connectivity before birth and has the potential to offer novel insights into normal and pathological human brain development. This review gives an overview of the currently used MRI techniques for connectomic imaging, with a particular focus on recent studies that have successfully translated these to the in utero or postmortem fetal setting. Possible mechanisms of how pathologies, maternal, or environmental factors may interfere with the emergence of the connectome are considered. The review highlights the importance of advanced image post processing and the need for reproducibility studies for connectomic imaging. Further work and novel data-sharing efforts would be required to validate or disprove recent observations from in utero connectomic studies, which are typically limited by low case numbers and high data drop out. Novel knowledge with regard to the ontogenesis, architecture, and temporal dynamics of the human brain connectome would lead to the more precise understanding of the etiological background of neurodevelopmental and mental disorders. To achieve this goal, this review considers the growing evidence from advanced fetal connectomic imaging for the increased vulnerability of the human brain during late gestation for pathologies that might lead to impaired connectome development and subsequently interfere with the development of neural substrates serving higher cognition.

Background The disturbance of cardiac energy substrate metabolism has a decisive role in the pathogenesis of adverse cardiac remodeling and heart failure. Under normoxic conditions, the free fatty acid metabolism is the predominant pathway by providing the highest energy per substrate molecule. Severe myocardial hypoxia leads to a switch from beta-oxidation to glucose metabolism to increase the ATP production per oxygen molecule. This metabolic disorder appears as perfusion-metabolism mismatch in 18F-fluorodeoxyglucose (18F-FDG) PET images, as increased 18F-FDG uptake in the under-perfused hypoxic myocardial area. Purpose The aim of our study was to evaluate the simultaneous perfusion, metabolism and function of the ischemic heart by hybrid 18F-FDG-PET-cMRI with late enhancement images in a translation animal model of heart failure. Methods Under general anesthesia, closed chest reperfused acute myocardial infarction (AMI) was induced in 36 domestic pigs by 90 min occlusion of the mid left anterior descending artery with a percutaneous intracoronary balloon, followed by reperfusion. Three days and 1 month after AMI, after 12h fasting, 18F-FDG-PET-cMRI were performed by using standardized acquisition protocols (n=30). Cardiac functional parameter, such as ejection fraction (EF), end-diastolic volume (EDV), infarct size, and mean tracer uptake of the infarcted area were quantitatively assessed. Six animals were euthanized after the 3-day 18F-FDG-PET-cMRI images to elaborate the differences in gene expression patterns in animals with perfusion-metabolic mismatch by using next generation sequencing (NGS) and pathway network analyses. Results Eight (group Mismatch) of the 30 animals (group Match) with 1-month follow-up showed high 18F-FDG uptake in the infarcted area (perfusion-metabolism mismatch) at the 3-day 18F-FDG-PET-cMRI-LE images (Figure). The animals in the Mismatch group had significantly lower EF at 3 days (34±8.8 vs 42±3%) and at the 1-month follow-up (35.8±6 vs 43±6.6%) and larger infarct size at day 3 (26.6±6.6 vs 22.1±4.4%) and 1 month (28±5.4 vs 20.3±4.3%) with higher EDV at 1 month. Mean tracer uptake of the infarcted area was significantly reduced in the Mismatch group at 1 month (56±23.1 vs 64.7±13.2%). NGS revealed downregulation of the cholesterol metabolism pathway, and upregulation of carbohydrate derivative catabolism pathway with highly activated innate immune system and genes responsible for cytokine activation in the infarcted area 3 days post-AMI in the Mismatch group, which explains the paradox high 18F-FDG tracer uptake in the infarction zone. Accordingly, the high energy demand of the severe hypoxic area led to “glucose steel phenomenon” at the molecular level, subtracting the 18F-FDG from the normally perfused non-ischemic myocardial regions. Conclusions 18F-FDG-glucose perfusion-metabolism mismatch early after AMI visualized by hybrid 18F-FDG-PET-MRI images predict development of LV adverse remodeling. Acknowledgement/Funding Fibrotarget EU Grant Nr 602904

Children with congenital heart disease (CHD) remain at risk for neurodevelopmental impairment despite improved peri- and intraoperative care. Our prospective cohort study aimed to determine the relationship between perioperative brain volumes and neurodevelopmental outcome in neonates with severe CHD. Pre- and postoperative cerebral MRI was acquired in term born neonates with CHD undergoing neonatal cardiopulmonary bypass surgery. Brain volumes were measured using an atlas prior based automated method. One-year outcome was assessed with the Bayley-III. CHD infants (n=77) had lower pre- and postoper-ative total and regional brain volumes compared to controls (n=44, all p

Intravoxel incoherent motion (IVIM) imaging allows contrast-agent free in vivo perfusion quantification with magnetic resonance imaging (MRI). However, its use is limited by typically low accuracy due to low signal-to-noise ratio (SNR) at large gradient encoding magnitudes as well as dephasing artefacts caused by subject motion, which is particularly challenging in fetal MRI. To mitigate this problem, we propose an implicit IVIM signal acquisition model with which we learn full posterior distribution of perfusion parameters using artificial neural networks. This posterior then encapsulates the uncertainty of the inferred parameter estimates, which we validate herein via numerical experiments with rejection-based Bayesian sampling. Compared to state-of the-art IVIM estimation method of segmented least-squares fitting, our proposed approach improves parameter estimation accuracy by 65% on synthetic anisotropic perfusion data. On paired rescans of in vivo fetal MRI, our method increases repeatability of parameter estimation in placenta by 46%.

Congenital heart defects are the most common congenital anomalies, accounting for a third of all congenital anomaly cases. While surgical correction dramatically improved survival rates, the lag behind normal neurodevelopment appears to persist. Deficits in higher cognitive functions are particularly common, including developmental delay in communication and oral-motor apraxia. It remains unclear whether the varying degree of cognitive developmental delay is reflected in variability in brain growth patterns. To answer this question, we aimed to investigate whether the rate of regional brain growth is correlated with later life neurodevelopment. Forty-four newborns were included in our study, of whom 33 were diagnosed with dextro-transposition of the great arteries and 11 with other forms of severe congenital heart defects. During the first month of life, neonates underwent corrective or palliative cardiovascular bypass surgery, pre- and post-operative cerebral MRI were performed 18.7 ± 7.03 days apart. MRI was performed in natural sleep on a 3.0 T scanner using an 8-channel head coil, fast spin-echo T2-weighted anatomical sequences were acquired in three planes. Based on the principles of deformation-based morphometry, we calculated brain growth rate maps reflecting average daily growth occurring between pre- and post-operative brain images. An explorative, whole-brain, threshold-free cluster enhancement analysis revealed strong correlation between the growth rate of the Heschl's gyrus, anterior planum temporale and language score at 12 months of age, corrected for demographic variables (P= 0.018, t = 5.656). No significant correlation was found between brain growth rates and motor or cognitive scores. Post hoc analysis showed that the length of hospitalization interacted with this correlation, longer hospitalization resulted in faster enlargement of the internal CSF spaces. Our longitudinal cohort study provides evidence for the early importance of left-dominant perisylvian regions in auditory and language development before direct postnatal exposure to native language. In congenital heart disease patients, the perioperative period results in a critical variability of brain growth rate in this region, which is a reliable neural correlate of language development at 1 year of age.

Background Our purpose was to test the within-subject (test–retest) reproducibility of the perfusion fraction, diffusion coefficient, and pseudo-diffusion coefficient measurements in various foetus organs and in the placenta based on the intra-voxel incoherent motion (IVIM) principle. Methods In utero diffusion-weighted IVIM magnetic resonance imaging (MRI) was performed in 15 pregnant women (pregnancy age 21–36 weeks) on 1.5-T and 3.0-T clinical scanners with b-factors in the range of 0–900 s/mm2 in 16 steps. A bi-exponential model was fitted on the volume-averaged diffusion values. Perfusion fraction (f), diffusion coefficient (d), and pseudo-diffusion coefficient (D*) were calculated. Within-subject reproducibility was evaluated as test–retest variability (VAR %) of the IVIM parameters in the foetal frontal cortex, frontal white matter, cerebellum, lungs, kidneys, liver, and in the placenta. Results For the foetal lungs, liver and the placenta, test–retest variability was in the range of 14–20% for f, 12–14% for d, and 17–25% for D*. The diffusion coefficients of the investigated brain regions were moderately to highly reproducible (VAR 5–15%). However, f and D* showed inferior reproducibility compared to corresponding measures for the lungs, liver, and placenta. The IVIM parameters of the foetal kidney were revealed to be highly variable across scans. Conclusions IVIM MRI potentially provides a novel method for examining microvascular perfusion and diffusion in the developing human foetus. However, reproducibility of perfusion and diffusion parameters depends greatly upon data quality, foetal and maternal movements, and foetal-specific image post-processing.

Our purpose was to test the within-subject repeatability of the perfusion fraction, diffusion coefficient and pseudo diffusion coefficient measurements in various fetal organs and in the placenta based on the intra-voxel incoherent motion imaging principle. In utero diffusion-weighted magnetic resonance imaging was performed on 1.5T and 3.0T clinical scanners with b-factors ranging from 0 to 900 s/mm2 in 16 steps and a tetrahedral diffusion-weighting encoding scheme. Data from 16 pregnant women (maternal age: 34 ± 4.9 years, range: 24.6 −40.8) were included in this pilot study. For 15 cases, IVIM was repeated (maternal age: 33.7 ± 5.2 years, range: 24.6 – 40.8). A bi-exponential model was fitted on the volume-averaged diffusion values and the perfusion fraction (f), diffusion coefficient (d) and pseudo diffusion coefficient (D*) were calculated. Within-subject repeatability was given as the test-retest variability of the IVIM parameters in the fetal frontal cortex, frontal white matter, cerebellum, lungs, kidneys, liver and in the placenta. An in-house developed image processing script was utilized to remove the image frames with excessive motion, and to perform motion correction by using non-linear freeform deformations. For the fetal lungs, liver and the placenta, within-subject variability ranged from 14.4% to 20.4% for f, 12.2% to 14.1% for d and 16.8% to 25.3% for D*. The diffusion coefficients of the investigated brain regions were moderately to highly reproducible (4.8% to 15.2%), however, f and D* showed inferior reproducibility compared to corresponding measures derived for the lungs, liver and placenta. The IVIM-based parameters of the fetal kidney were revealed to be highly variable across scans. Our results indicate that in utero intra-voxel incoherent motion magnetic resonance imaging potentially provides a novel method for examining microvascular perfusion and diffusion in the developing human fetus. The reproducible quantification of the perfusion and diffusion parameters depend greatly upon data quality, fetal and maternal movements, and image post processing to detect and remove corrupted data before calculating the IVIM model.

OBJECTIVE The long-term (5-year) outcome of early (3-6 weeks after acute myocardial infarction [AMI], BM-MNC Early group) and late (3-4 months after AMI, BM-MNC Late group) combined (percutaneous intramyocardial and intracoronary) delivery of autologous bone marrow mononuclear cells (BM-MNCs) was evaluated in patients with ejection fractions (EF) between 30-45% post-AMI. METHODS Major adverse cardiac and cerebrovascular events (MACCE) and hospitalization were recorded. Left (LV) and right (RV) ventricular function were measured by transthoracic echocardiography. Cardiac magnetic resonance imaging (MRI) and myocardial single photon emission computed tomography was performed in a subgroup of patients. Pre-cell therapy myocardial voltage values of treated areas (assessed by NOGA mapping) were correlated with clinical outcome. RESULTS Five-year MACCE incidences (7.4%. vs 24.1%) and the composite of all adverse events (11.1% vs 27.6%) were not different between the Early and Late treatment groups. The significant LV-EF increase at 1-year follow-up was preserved at the 5-year control (from baseline to 5-year: 5.3%, 95% CI:0.5-10.1, and 5.7%, 95% CI:1.7-9.6, p

In utero magnetic resonance imaging (MRI) has significantly increased our knowledge on early fetal brain development. Especially the possibility to expand standard clinical applications of imaging structure to functional imaging has increased the opportunities but also introduced major challenges in the field regarding motion artifacts, group analysis, and generating structural templates. This chapter gives an overview on fetal functional imaging from stimulation to resting-state studies and discusses critical challenges in data analysis. Fetal functional MRI is a powerful approach investigating brain development in utero and has the potential of generating biomarkers for developmental prognosis in the future.

Variations in the shape and appearance of anatomical structures in medical images are often relevant radiological signs of disease. Automatic tools can help automate parts of this manual process. A cloud-based evaluation framework is presented in this paper including results of benchmarking current state-of-the-art medical imaging algorithms for anatomical structure segmentation and landmark detection: the VISCERAL Anatomy benchmarks. The algorithms are implemented in virtual machines in the cloud where participants can only access the training data and can be run privately by the benchmark administrators to objectively compare their performance in an unseen common test set. Overall, 120 computed tomography and magnetic resonance patient volumes were manually annotated to create a standard Gold Corpus containing a total of 1295 structures and 1760 landmarks. Ten participants contributed with automatic algorithms for the organ segmentation task, and three for the landmark localization task. Different algorithms obtained the best scores in the four available imaging modalities and for subsets of anatomical structures. The annotation framework, resulting data set, evaluation setup, results and performance analysis from the three VISCERAL Anatomy benchmarks are presented in this article. Both the VISCERAL data set and Silver Corpus generated with the fusion of the participant algorithms on a larger set of non-manually-annotated medical images are available to the research community. QC 20170104

The recent technological advancement of fast magnetic resonance imaging (MRI) sequences allowed the inclusion of diffusion tensor imaging, functional MRI, and proton MR spectroscopy in prenatal imaging protocols. These methods provide information beyond morphology and hold the key to improving several fields of human neuroscience and clinical diagnostics. Our review introduces the fundamental works that enabled these imaging techniques, and also highlights the most recent contributions to this emerging field of prenatal diagnostics, such as the structural and functional connectomic approach. We introduce the advanced image processing approaches that are extensively used to tackle fetal or maternal movement−related image artifacts, and which are necessary for the optimal interpretation of such imaging data.

Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1–2 mm and with 10–50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named “MIDA”. The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community., PLoS ONE, 10 (4), ISSN:1932-6203

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been shown to reduce some of the symptoms of advanced, levodopa-responsive Parkinson's disease that are not adequately controlled with medication. However, the precise mechanism of the therapeutic action of DBS is still unclear. Stimulation-induced side effects are not uncommon and require electrical "dose" adjustments. Quantitative methods are needed to fully characterize the electric field in the deep brain region that surrounds the electrodes in order to help with adjustments and maximize the efficacy of the device. Herein we report a magnetic resonance imaging (MRI)-based head model proposed for analysis of fields generated by deep brain stimulation (DBS). The model was derived from multimodal image data at 0.5mm isotropic spatial resolution and distinguishes 142 anatomical structures, including the basal ganglia and 38 nuclei of the thalamus. Six bipolar electrode configurations (1-2, 1-3, 1-4, 2-3, 2-4, 3-4) were modeled in order to assess the effects of the inter-electrode distance of the electric field. Increasing the distance between the electrodes results in an attenuated stimulation, with up to 25% reduction in electric field amplitude delivered (2-3 vs. 1-4). The map of the deep brain structures provided a highly precise anatomical detail which is useful for the quantitative assessment of current spread around the electrode and a better evaluation of the stimulation setting for the treatment optimization.

OBJECTIVES: We compared the accuracy of NOGA endocardial mapping for delineating transmural and non-transmural infarction to the results of cardiac magnetic resonance imaging (cMRI) with late gadolinium enhancement (LE) for guiding intramyocardial reparative substance delivery using data from experimental myocardial infarction studies. METHODS: Sixty domestic pigs underwent diagnostic NOGA endocardial mapping and cMRI-LE 60 days after induction of closed-chest reperfused myocardial infarction. The infarct size was determined by LE of cMRI and by delineation of the infarct core on the unipolar voltage polar map. The sizes of the transmural and non-transmural infarctions were calculated from the cMRI transmurality map using signal intensity (SI) cut-offs of>75% and>25% and from NOGA bipolar maps using bipolar voltage cut-off values of

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26–29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity., Seventh Framework Programme (European Commission) (KHRESMOI Project)

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients - manually annotated by up to four raters - and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%-85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously. Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource., National Center for Research Resources (U.S.) (P41-RR14075), National Institute of Biomedical Imaging and Bioengineering (U.S.) (R01EB013565), National Institute of Biomedical Imaging and Bioengineering (U.S.) (U54-EB005149), National Institutes of Health (U.S.) (P41-RR13218), National Institute of Biomedical Imaging and Bioengineering (U.S.) (P41-EB-015902), National Cancer Institute (U.S.) (R15CA115464)

Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that “resting-state” fMRI-based brain connectivity conclusions may be erroneous when motion artifacts have a differential effect on fMRI BOLD signals for between group comparisons. A potential explanation could be that in-scanner displacement, due to rotational components, is not spatially constant in the whole brain. However, this localized nature of motion artifacts is poorly understood and is rarely considered in brain connectivity studies. In this study, we initially demonstrate the local correspondence between head displacement and the changes in the resting-state fMRI BOLD signal. Than, we investigate how connectivity strength is affected by the population-level variation in the spatial pattern of regional displacement. We introduce Regional Displacement Interaction (RDI), a new covariate parameter set for second-level connectivity analysis and demonstrate its effectiveness in reducing motion related confounds in comparisons of groups with different voxel-vise displacement pattern and preprocessed using various nuisance regression methods. The effect of using RDI as second-level covariate is than demonstrated in autism-related group comparisons. The relationship between the proposed method and some of the prevailing subject-level nuisance regression techniques is evaluated. Our results show that, depending on experimental design, treating in-scanner head motion as a global confound may not be appropriate. The degree of displacement is highly variable among various brain regions, both within and between subjects. These regional differences bias correlation-based measures of brain connectivity. The inclusion of the proposed second-level covariate into the analysis successfully reduces artifactual motion-related group differences and preserves real neuronal differences, as demonstrated by the autism-related comparisons.

The aim of this work was to use probabilistic diffusion tractography to examine the organization of the human insular cortex based on the similarities of its remote projections. Forty right-handed healthy subjects (33.8 ± 12.7 years old) with no history of neurological injury were included in the study. After the spatial standardization of diffusion tensor images, insular cortical masks were delineated based on the Harvard–Oxford Cortical Atlas and were used to initiate fibertracking. Cluster analysis by the k-means algorithm was employed to partition the insular voxels into two groups that featured the most distinct distribution of connections. In order to perform volumetric comparisons, the assigned label maps were transformed back to space of the subjects’ native anatomical MR images. The outlines of the change in connectivity profile did not respect the known cytoarchitectural subdivisions and were shown to be independent from the gyral anatomy. Interhemispheric asymmetry in the volumes of connectivity-based subdivisions was observed putatively marking a leftward functional dominance of the anterior insula and its reciprocally interconnected targets which influences the size of insular area where similar connections are represented. The fractional anisotropy values were not significantly different between the hemipsheres or connectivity-based clusters; however, the mean diffusivity was higher in the anterior insula in both hemispheres.

We report on a female patient with blepharophimosis mental retardation syndrome of Say/Barber/Biesecker/Young-Simpson (SBBYS) type. Main findings in her were marked developmental delay, blepharophimosis, ptosis, cleft palate, external auditory canal stenosis, small and malformed teeth, hypothyroidism, hearing impairment, and joint limitations. We performed diffusion tensor magnetic resonance imaging (MRI) and tractography of the brain which showed inappropriate myelination and disturbed white matter integrity. Cytogenetic analysis, subtelomeric fluorescence in situ hybridization and comparative genomic hybridization failed to identify an abnormality. It remains uncertain whether the MRI findings are specific to the present patient or form part of the SBBYS syndrome.

The quantity of cells with paracrine effects for use in myocardial regeneration therapy is limited. This study investigated the effects of catheter-based endomyocardial delivery of secretome of 2.5 × 109 apoptotic peripheral blood mononuclear cells (APOSEC) on porcine chronic post-myocardial infarction (MI) left ventricular (LV) dysfunction and on gene expression. Closed-chest reperfused MI was induced in pigs by 90-min occlusion followed by reperfusion of the mid-LAD (day 0). At day 30, animals were randomized to receive porcine APOSEC (n = 8) or medium solution (control; n = 8) injected intramyocardially into the MI border zone using 3D NOGA guidance. At day 60, cardiac MRI with late enhancement and diagnostic NOGA (myocardial viability) were performed. Gene expression profiling of the infarct core, border zone, and normal myocardium was performed using microarray analysis and confirmed by quantitative real-time PCR. Injection of APOSEC significantly decreased infarct size (p