A Rare Case of Post-orchidectomy Arterial Injury With Rapidly Enlarging Scrotal Hematoma Treated With Coil Embolization.

Testicular cancer is the most common solid tumor in young adult males. Radical inguinal orchidectomy is the gold standard for the diagnosis and treatment of testicular cancer, which is confined to the scrotum and is generally well tolerated. An uncommon, but known, complication of radical orchidectomy is scrotal hematoma. Scrotal hematoma from radical orchidectomy is commonly self-limited and typically self-resolving. We present a rare case of metastatic testicular malignancy diagnosed with radical inguinal orchidectomy complicated by a rapidly enlarging scrotal hematoma, successfully treated with surgical evacuation and image-guided arterial embolization.

Brainhack: Developing a culture of open, inclusive, community-driven neuroscience.

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress.

Temporal and geospatial variations among the interventional radiology physician workforce in the United States.

OBJECTIVE: To analyze the temporal trends and state-wide geospatial variations in Vascular and Interventional Radiology (VIR) workforce in the United States. METHODS: The State Physician Workforce Data from the AAMC website was accessed for years 2015, 2017, and 2019. The variables collected for each state included total number of active physicians, total number of physicians per specialty and total number of female physicians in VIR. Comparative data was obtained for vascular surgery (VS), diagnostic radiology (DR), and radiation oncology (RO). The annual growth rate for total physicians and sub-analysis of female physicians in each state was computed for each specialty. RESULTS: From 2015 to 2019, the total number of active physicians in the United States grew by 1.8% per year. Growth of active physicians in VIR grew by 8.3%, DR 0.06%, VS 4.4%, and RO 1.9% per year. Colorado and Minnesota had the highest growth rate for VIR physicians (15%). VIR physicians per 100,000 people increased from 0.84 (2015) to 1.10 (2019) in the US. In comparison, VS physicians increased from 0.99 (2015) to 1.14 (2019), DR physicians decreased from 8.61 (2015) to 8.43 (2019), and RO physicians grew from 1.48 (2015) to 1.56 (2019). Women represented 6.8% of the VIR workforce in the US in 2019 and increased by a rate of 16% annually in the US from 2015 to 2019. In comparison, the number of women in VS has grown by 21%, DR by 2%, and RO by 2.4% during the same period. The state of Maryland has the highest proportion of women in VIR at 18%. CONCLUSION: The number of VIR physicians is increasing at a higher rate than the national overall physician growth, and while female VIR physicians makeup a small fraction of the VIR workforce, their numbers have increased at a faster rate than overall VIR physicians.

Algebraic relationship between the structural network's Laplacian and functional network's adjacency matrix is preserved in temporal lobe epilepsy subjects.

The relationship between anatomic and resting state functional connectivity of large-scale brain networks is a major focus of current research. In previous work, we introduced a model based on eigen decomposition of the Laplacian which predicts the functional network from the structural network in healthy brains. In this work, we apply the eigen decomposition model to two types of epilepsy; temporal lobe epilepsy associated with mesial temporal sclerosis, and MRI-normal temporal lobe epilepsy. Our findings show that the eigen relationship between function and structure holds for patients with temporal lobe epilepsy as well as normal individuals. These results suggest that the brain under TLE conditions reconfigures and rewires the fine-scale connectivity (a process which the model parameters are putatively sensitive to), in order to achieve the necessary structure-function relationship.

Individual susceptibility to TMS affirms the precuneal role in meta-memory upon recollection.

A recent virtual-lesion study using inhibitory repetitive transcranial magnetic stimulation (rTMS) confirmed the causal behavioral relevance of the precuneus in the evaluation of one's own memory performance (aka mnemonic metacognition). This study's goal is to elucidate how these TMS-induced neuromodulatory effects might relate to the neural correlates and be modulated by individual anatomical profiles in relation to meta-memory. In a within-subjects design, we assessed the impact of 20-min rTMS over the precuneus, compared to the vertex, across three magnetic resonance imaging (MRI) neuro-profiles on 18 healthy subjects during a memory versus a perceptual task. Task-based functional MRI revealed that BOLD signal magnitude in the precuneus is associated with variation in individual meta-memory efficiency. Moreover, individuals with higher resting-state functional connectivity (rs-fcMRI) between the precuneus and the hippocampus, or smaller gray matter volume in the stimulated precuneal region exhibit considerably higher vulnerability to the TMS effect. These effects were not observed in the perceptual domain. Thus, we provide compelling evidence in outlining a possible circuit encompassing the precuneus and its mnemonic midbrain neighbor the hippocampus at the service of realizing our meta-awareness during memory recollection of episodic details.

Multi-branch convolutional neural network for multiple sclerosis lesion segmentation.

In this paper, we present an automated approach for segmenting multiple sclerosis (MS) lesions from multi-modal brain magnetic resonance images. Our method is based on a deep end-to-end 2D convolutional neural network (CNN) for slice-based segmentation of 3D volumetric data. The proposed CNN includes a multi-branch downsampling path, which enables the network to encode information from multiple modalities separately. Multi-scale feature fusion blocks are proposed to combine feature maps from different modalities at different stages of the network. Then, multi-scale feature upsampling blocks are introduced to upsize combined feature maps to leverage information from lesion shape and location. We trained and tested the proposed model using orthogonal plane orientations of each 3D modality to exploit the contextual information in all directions. The proposed pipeline is evaluated on two different datasets: a private dataset including 37 MS patients and a publicly available dataset known as the ISBI 2015 longitudinal MS lesion segmentation challenge dataset, consisting of 14 MS patients. Considering the ISBI challenge, at the time of submission, our method was amongst the top performing solutions. On the private dataset, using the same array of performance metrics as in the ISBI challenge, the proposed approach shows high improvements in MS lesion segmentation compared with other publicly available tools.

Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure.

How structural connectivity (SC) gives rise to functional connectivity (FC) is not fully understood. Here we mathematically derive a simple relationship between SC measured from diffusion tensor imaging, and FC from resting state fMRI. We establish that SC and FC are related via (structural) Laplacian spectra, whereby FC and SC share eigenvectors and their eigenvalues are exponentially related. This gives, for the first time, a simple and analytical relationship between the graph spectra of structural and functional networks. Laplacian eigenvectors are shown to be good predictors of functional eigenvectors and networks based on independent component analysis of functional time series. A small number of Laplacian eigenmodes are shown to be sufficient to reconstruct FC matrices, serving as basis functions. This approach is fast, and requires no time-consuming simulations. It was tested on two empirical SC/FC datasets, and was found to significantly outperform generative model simulations of coupled neural masses.

Bilateral effects of unilateral cerebellar lesions as detected by voxel based morphometry and diffusion imaging.

Over the last decades, the importance of cerebellar processing for cortical functions has been acknowledged and consensus was reached on the strict functional and structural cortico-cerebellar interrelations. From an anatomical point of view strictly contralateral interconnections link the cerebellum to the cerebral cortex mainly through the middle and superior cerebellar peduncle. Diffusion MRI (dMRI) based tractography has already been applied to address cortico-cerebellar-cortical loops in healthy subjects and to detect diffusivity alteration patterns in patients with neurodegenerative pathologies of the cerebellum. In the present study we used dMRI-based tractography to determine the degree and pattern of pathological changes of cerebellar white matter microstructure in patients with focal cerebellar lesions. Diffusion imaging and high-resolution volumes were obtained in patients with left cerebellar lesions and in normal controls. Middle cerebellar peduncles and superior cerebellar peduncles were reconstructed by multi fiber diffusion tractography. From each tract, measures of microscopic damage were assessed, and despite the presence of unilateral lesions, bilateral diffusivity differences in white matter tracts were found comparing patients with normal controls. Consistently, bilateral alterations were also evidenced in specific brain regions linked to the cerebellum and involved in higher-level functions. This could be in line with the evidence that in the presence of unilateral cerebellar lesions, different cognitive functions can be affected and they are not strictly linked to the side of the cerebellar lesion.

MRI Analysis of White Matter Myelin Water Content in Multiple Sclerosis: A Novel Approach Applied to Finding Correlates of Cortical Thinning.

A novel lesion-mask free method based on a gamma mixture model was applied to myelin water fraction (MWF) maps to estimate the association between cortical thickness and myelin content, and how it differs between relapsing-remitting (RRMS) and secondary-progressive multiple sclerosis (SPMS) groups (135 and 23 patients, respectively). It was compared to an approach based on lesion masks. The gamma mixture distribution of whole brain, white matter (WM) MWF was characterized with three variables: the mode (most frequent value) m1 of the gamma component shown to relate to lesion, the mode m2 of the component shown to be associated with normal appearing (NA) WM, and the mixing ratio (λ) between the two distributions. The lesion-mask approach relied on the mean MWF within lesion and within NAWM. A multivariate regression analysis was carried out to find the best predictors of cortical thickness for each group and for each approach. The gamma-mixture method was shown to outperform the lesion-mask approach in terms of adjusted R2, both for the RRMS and SPMS groups. The predictors of the final gamma-mixture models were found to be m1 (ß = 1.56, p < 0.005), λ (ß = -0.30, p < 0.0005) and age (ß = -0.0031, p < 0.005) for the RRMS group (adjusted R2 = 0.16), and m2 (ß = 4.72, p < 0.0005) for the SPMS group (adjusted R2 = 0.45). Further, a DICE coefficient analysis demonstrated that the lesion mask had more overlap to an ROI associated with m1, than to an ROI associated with m2 (p < 0.00001), and vice versa for the NAWM mask (p < 0.00001). These results suggest that during the relapsing phase, focal WM damage is associated with cortical thinning, yet in SPMS patients, global WM deterioration has a much stronger influence on secondary degeneration. Through these findings, we demonstrate the potential contribution of myelin loss on neuronal degeneration at different disease stages and the usefulness of our statistical reduction technique which is not affected by the typical bias associated with approaches based on lesion masks.

Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation.

Transcranial electric stimulation aims to stimulate the brain by applying weak electrical currents at the scalp. However, the magnitude and spatial distribution of electric fields in the human brain are unknown. We measured electric potentials intracranially in ten epilepsy patients and estimated electric fields across the entire brain by leveraging calibrated current-flow models. When stimulating at 2 mA, cortical electric fields reach 0.8 V/m, the lower limit of effectiveness in animal studies. When individual whole-head anatomy is considered, the predicted electric field magnitudes correlate with the recorded values in cortical (r = 0.86) and depth (r = 0.88) electrodes. Accurate models require adjustment of tissue conductivity values reported in the literature, but accuracy is not improved when incorporating white matter anisotropy or different skull compartments. This is the first study to validate and calibrate current-flow models with in vivo intracranial recordings in humans, providing a solid foundation to target stimulation and interpret clinical trials.

Impact of cerebellar atrophy on cortical gray matter and cerebellar peduncles as assessed by voxel-based morphometry and high angular resolution diffusion imaging.

In recent years the cerebellum has been attributed amore important role in higher-level functions than previously believed. We examined a cohort of patients suffering from cerebellar atrophy resulting in ataxia, with two main objectives: first to investigate which regions of the cerebrum were affected by the cerebellar degeneration, and second to assess whether diffusion magnetic resonance imaging (dMRI) metrics within the medial (MCP) and superior cerebellar peduncle (SCP) - namely fractional anisotropy (FA) and radial diffusivity (RD) - could be used as a biomarker in patients with this condition. Structural and dMRI data of seven patients with cerebellar atrophy (2 with spinocerebellar atrophy type 2, 1 with Friedreich's ataxia, 4 with idiopathic cerebellar ataxia) and no visible cortical lesions or cortical atrophy were investigated with Freesurfer and voxel-based morphometry (VBM) of gray matter (GM) as well as MCP and SCP FA maps. Correlations of MCP and SCP mean FA with ataxia scores and subscores were also evaluated. Freesurfer showed that patients had significantly reduced volume of the thalamus, ventral diencephalon and pallidum. VBM also demonstrated significantly lower local GM volumes in patients, notably in the head of the caudate nucleus, posterior cingulate gyrus and orbitofrontal cortex bilaterally, as well as in Broca's area in the left hemisphere, and a significant increase in RD in the MCP and SCP of both hemispheres. A significant correlation was found between MCP mean FA and total ataxia score (R=-0.7, p=0.03), and subscores for kinetic functions (R=-0.74, p=0.03) and oculomotor disorders (R=-0.70, p=0.04). The regions of the cerebrum found to have significantly lower local GM volumes have been described to be involved in higher-level cerebellar functions such as initiation of voluntary movements, emotional control, memory retrieval and general cognition. Our findings corroborate recent research pointing to a more extensive corticocerebellar system than previously thought. The significant difference in the MCP and SCP dMRI metrics between patients and controls as well as the significant correlation with ataxia total score and subscores support the use of dMRI metrics as an imaging biomarker for cerebellar degeneration and ataxia.

Profilometry: A new statistical framework for the characterization of white matter pathways, with application to multiple sclerosis.

AIMS: describe a new "profilometry" framework for the multimetric analysis of white matter tracts, and demonstrate its application to multiple sclerosis (MS) with radial diffusivity (RD) and myelin water fraction (MWF). METHODS: A cohort of 15 normal controls (NC) and 141 MS patients were imaged with T1, T2 FLAIR, T2 relaxometry and diffusion MRI (dMRI) sequences. T1 and T2 FLAIR allowed for the identification of patients having lesion(s) on the tracts studied, with a special focus on the forceps minor. T2 relaxometry provided MWF maps, while dMRI data yielded RD maps and the tractography required to compute MWF and RD tract profiles. The statistical framework combined a multivariate analysis of covariance (MANCOVA) and a linear discriminant analysis (LDA) both accounting for age and gender, with multiple comparison corrections. RESULTS: In the single-case case study the profilometry visualization showed a clear departure of MWF and RD from the NC normative data at the lesion location(s). Group comparison from MANCOVA demonstrated significant differences at lesion locations, and a significant age effect in several tracts. The follow-up LDA analysis suggested MWF better discriminates groups than RD. DISCUSSION AND CONCLUSION: While progress has been made in both tract-profiling and metrics for white matter characterization, no single framework for a joint analysis of multimodality tract profiles accounting for age and gender is known to exist. The profilometry analysis and visualization appears to be a promising method to compare groups using a single score from MANCOVA while assessing the contribution of each metric with LDA.

Tractography of the optic radiation: a repeatability and reproducibility study.

Our main objective was to evaluate the repeatability and reproducibility of optic radiation (OR) reconstruction from diffusion MRI (dMRI) data. 14 adults were scanned twice with the same 60-direction dMRI sequence. Peaks in the diffusion profile were estimated with the single tensor (ST), Q-ball (QSH) and persistent angular structure (PAS) methods. Segmentation of the OR was performed by two experimenters with probabilistic tractography based on a manually drawn region-of-interest (ROI) protocol typically employed for OR segmentation, with both standard and extended sets of ROIs. The repeatability and reproducibility were assessed by calculating the intra-class correlation coefficient (ICC) of intra- and inter-rater experiments, respectively. ICCs were calculated for commonly used dMRI metrics (FA, MD, AD, RD) and anatomical dimensions of the optic radiation (distance from Meyer's loop to the temporal pole, ML-TP), as well as the Dice similarity coefficient (DSC) between the raters' OR segmentation. Bland-Altman plots were also calculated to investigate bias and variability in the reproducibility measurements. The OR was successfully reconstructed in all subjects by both raters. The ICC was found to be in the good to excellent range for both repeatability and reproducibility of the dMRI metrics, DSC and ML-TP distance. The Bland-Altman plots did not show any apparent systematic bias for any quantities. Overall, higher ICC values were found for the multi-fiber methods, QSH and PAS, and for the standard set of ROIs. Considering the good to excellent repeatability and reproducibility of all the quantities investigated, these findings support the use of multi-fiber OR reconstruction with a limited number of manually drawn ROIs in clinical applications utilizing either OR microstructure characterization or OR dimensions, as is the case in neurosurgical planning for temporal lobectomy.

The role of iron in gray matter degeneration in Huntington's disease: a magnetic resonance imaging study.

In Huntington's disease, iron accumulation in basal ganglia accompanies neuronal loss. However, if iron content changes with disease progression and how it relates to gray matter atrophy is not clear yet. We explored iron content in basal ganglia and cortex and its relationship with gray matter volume in 77 mutation carriers [19 presymptomatic, 8 with soft symptoms (SS), and 50 early-stage patients) and 73 matched-controls by T2*relaxometry and T1-weighted imaging on a 3T scanner. The ANCOVA model showed that iron accumulates in the caudate in presymptomatic subjects (P = 0.004) and remains relatively stable along disease stages in this nucleus; while increases in putamen and globus pallidus (P < 0.05). Volume instead decreases in basal ganglia, starting from the caudate (P < 0.0001) and extending to the putamen and globus pallidus (P ≤ 0.001). The longer the disease duration and the higher the CAG repeats, the higher the iron accumulation and the smaller the volume. In the cortex, iron decreases in parieto-occipital areas in SS (P < 0.027); extending to premotor and parieto-temporo-occipital areas in patients (P < 0.003); while volume declines in frontoparietal and temporal areas in presymptomatic (P < 0.023) and SS (P < 0.045), and extends throughout the cortex, with the exception of anterior frontal regions, in patients (P < 0.023). There is an inverse correlation between volume and iron levels in putamen, globus pallidus and the anterior cingulate; and a direct correlation in cortical structures (SMA-sensoriomotor and temporo-occipital). Iron homeostasis is affected in the disease; however, there appear to be differences in the role played by iron in basal ganglia and in cortex.

Optic radiation structure and anatomy in the normally developing brain determined using diffusion MRI and tractography.

The optic radiation (OR) is a component of the visual system known to be myelin mature very early in life. Diffusion tensor imaging (DTI) and its unique ability to reconstruct the OR in vivo were used to study structural maturation through analysis of DTI metrics in a cohort of 90 children aged 5-18 years. As the OR is at risk of damage during epilepsy surgery, we measured its position relative to characteristic anatomical landmarks. Anatomical distances, DTI metrics and volume of the OR were investigated for age, gender and hemisphere effects. We observed changes in DTI metrics with age comparable to known trajectories in other white matter tracts. Left lateralization of DTI metrics was observed that showed a gender effect in lateralization. Sexual dimorphism of DTI metrics in the right hemisphere was also found. With respect to OR dimensions, volume was shown to be right lateralised and sexual dimorphism demonstrated for the extent of the left OR. The anatomical results presented for the OR have potentially important applications for neurosurgical planning.

Consensus between pipelines in structural brain networks.

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks. Furthermore, the choice of which connections are considered important is unclear. In this study, we assessed the similarity between structural networks obtained using two independent state-of-the-art reconstruction pipelines. We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines. Similarity of network connections was compared between pipelines employing different atlases by merging parcels to a common and equivalent node scale. We found a high agreement between the networks across a range of fiber density thresholds. In addition, we identified a robust core of highly connected regions coinciding with a peak in similarity across network density thresholds, and replicated these results with atlases at different node scales. The binary network properties of these core connections were similar between pipelines but showed some differences in atlases across node scales. This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study.

Principal networks.

Graph representations of brain connectivity have attracted a lot of recent interest, but existing methods for dividing such graphs into connected subnetworks have a number of limitations in the context of neuroimaging. This is an important problem because most cognitive functions would be expected to involve some but not all brain regions. In this paper we outline a simple approach for decomposing graphs, which may be based on any measure of interregional association, into coherent "principal networks". The technique is based on an eigendecomposition of the association matrix, and is closely related to principal components analysis. We demonstrate the technique using cortical thickness and diffusion tractography data, showing that the subnetworks which emerge are stable, meaningful and reproducible. Graph-theoretic measures of network cost and efficiency may be calculated separately for each principal network. Unlike some other approaches, all available connectivity information is taken into account, and vertices may appear in none or several of the subnetworks. Subject-by-subject "scores" for each principal network may also be obtained, under certain circumstances, and related to demographic or cognitive variables of interest.