Spherical convolutional neural networks can improve brain microstructure estimation from diffusion MRI data.

Diffusion magnetic resonance imaging is sensitive to the microstructural properties of brain tissue. However, estimating clinically and scientifically relevant microstructural properties from the measured signals remains a highly challenging inverse problem that machine learning may help solve. This study investigated if recently developed rotationally invariant spherical convolutional neural networks can improve microstructural parameter estimation. We trained a spherical convolutional neural network to predict the ground-truth parameter values from efficiently simulated noisy data and applied the trained network to imaging data acquired in a clinical setting to generate microstructural parameter maps. Our network performed better than the spherical mean technique and multi-layer perceptron, achieving higher prediction accuracy than the spherical mean technique with less rotational variance than the multi-layer perceptron. Although we focused on a constrained two-compartment model of neuronal tissue, the network and training pipeline are generalizable and can be used to estimate the parameters of any Gaussian compartment model. To highlight this, we also trained the network to predict the parameters of a three-compartment model that enables the estimation of apparent neural soma density using tensor-valued diffusion encoding.

Fibre orientation atlas guided rapid segmentation of white matter tracts.

Fibre tract delineation from diffusion magnetic resonance imaging (MRI) is a valuable clinical tool for neurosurgical planning and navigation, as well as in research neuroimaging pipelines. Several popular methods are used for this task, each with different strengths and weaknesses making them more or less suited to different contexts. For neurosurgical imaging, priorities include ease of use, computational efficiency, robustness to pathology and ability to generalise to new tracts of interest. Many existing methods use streamline tractography, which may require expert neuroimaging operators for setting parameters and delineating anatomical regions of interest, or suffer from as a lack of generalisability to clinical scans involving deforming tumours and other pathologies. More recently, data-driven approaches including deep-learning segmentation models and streamline clustering methods have improved reproducibility and automation, although they can require large amounts of training data and/or computationally intensive image processing at the point of application. We describe an atlas-based direct tract mapping technique called 'tractfinder', utilising tract-specific location and orientation priors. Our aim was to develop a clinically practical method avoiding streamline tractography at the point of application while utilising prior anatomical knowledge derived from only 10-20 training samples. Requiring few training samples allows emphasis to be placed on producing high quality, neuro-anatomically accurate training data, and enables rapid adaptation to new tracts of interest. Avoiding streamline tractography at the point of application reduces computational time, false positives and vulnerabilities to pathology such as tumour deformations or oedema. Carefully filtered training streamlines and track orientation distribution mapping are used to construct tract specific orientation and spatial probability atlases in standard space. Atlases are then transformed to target subject space using affine registration and compared with the subject's voxel-wise fibre orientation distribution data using a mathematical measure of distribution overlap, resulting in a map of the tract's likely spatial distribution. This work includes extensive performance evaluation and comparison with benchmark techniques, including streamline tractography and the deep-learning method TractSeg, in two publicly available healthy diffusion MRI datasets (from TractoInferno and the Human Connectome Project) in addition to a clinical dataset comprising paediatric and adult brain tumour scans. Tract segmentation results display high agreement with established techniques while requiring less than 3 min on average when applied to a new subject. Results also display higher robustness than compared methods when faced with clinical scans featuring brain tumours and resections. As well as describing and evaluating a novel proposed tract delineation technique, this work continues the discussion on the challenges surrounding the white matter segmentation task, including issues of anatomical definitions and the use of quantitative segmentation comparison metrics.

Lesion detection in epilepsy surgery: Lessons from a prospective evaluation of a machine learning algorithm.

AIM: To evaluate a lesion detection algorithm designed to detect focal cortical dysplasia (FCD) in children undergoing stereoelectroencephalography (SEEG) as part of their presurgical evaluation for drug-resistant epilepsy. METHOD: This was a prospective, single-arm, interventional study (Idea, Development, Exploration, Assessment, and Long-Term Follow-Up phase 1/2a). After routine SEEG planning, structural magnetic resonance imaging sequences were run through an FCD lesion detection algorithm to identify putative clusters. If the top three clusters were not already sampled, up to three additional SEEG electrodes were added. The primary outcome measure was the proportion of patients who had additional electrode contacts in the SEEG-defined seizure-onset zone (SOZ). RESULTS: Twenty patients (median age 12 years, range 4-18 years) were enrolled, one of whom did not undergo SEEG. Additional electrode contacts were part of the SOZ in 1 out of 19 patients while 3 out of 19 patients had clusters that were part of the SOZ but they were already implanted. A total of 16 additional electrodes were implanted in nine patients and there were no adverse events from the additional electrodes. INTERPRETATION: We demonstrate early-stage prospective clinical validation of a machine learning lesion detection algorithm used to aid the identification of the SOZ in children undergoing SEEG. We share key lessons learnt from this evaluation and emphasize the importance of robust prospective evaluation before routine clinical adoption of such algorithms. WHAT THIS PAPER ADDS: The focal cortical dysplasia detection algorithm collocated with the seizure-onset zone (SOZ) in 4 out of 19 patients. The algorithm changed the resection boundaries in 1 of 19 patients undergoing stereoelectroencephalography for drug-resistant epilepsy. The patient with an altered resection due to the algorithm was seizure-free 1 year after resective surgery. Overall, the algorithm did not increase the proportion of patients in whom SOZ was identified.

The incidence of movement disorder increases with age and contrasts with subtle and limited neuroimaging abnormalities in argininosuccinic aciduria.

Argininosuccinate lyase (ASL) is integral to the urea cycle detoxifying neurotoxic ammonia and the nitric oxide (NO) biosynthesis cycle. Inherited ASL deficiency causes argininosuccinic aciduria (ASA), a rare disease with hyperammonemia and NO deficiency. Patients present with developmental delay, epilepsy and movement disorder, associated with NO-mediated downregulation of central catecholamine biosynthesis. A neurodegenerative phenotype has been proposed in ASA. To better characterise this neurodegenerative phenotype in ASA, we conducted a retrospective study in six paediatric and adult metabolic centres in the UK in 2022. We identified 60 patients and specifically looked for neurodegeneration-related symptoms: movement disorder such as ataxia, tremor and dystonia, hypotonia/fatigue and abnormal behaviour. We analysed neuroimaging with diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) in an individual with ASA with movement disorders. We assessed conventional and DTI MRI alongside single photon emission computer tomography (SPECT) with dopamine analogue radionuclide 123 I-ioflupane, in Asl-deficient mice treated by hASL mRNA with normalised ureagenesis. Movement disorders in ASA appear in the second and third decades of life, becoming more prevalent with ageing and independent from the age of onset of hyperammonemia. Neuroimaging can show abnormal DTI features affecting both grey and white matter, preferentially basal ganglia. ASA mouse model with normalised ureagenesis did not recapitulate these DTI findings and showed normal 123 I-ioflupane SPECT and cerebral dopamine metabolomics. Altogether these findings support the pathophysiology of a late-onset movement disorder with cell-autonomous functional central catecholamine dysregulation but without or limited neurodegeneration of dopaminergic neurons, making these symptoms amenable to targeted therapy.

Extent of piriform cortex resection in children with temporal lobe epilepsy.

OBJECTIVE: A greater extent of resection of the temporal portion of the piriform cortex (PC) has been shown to be associated with higher likelihood of seizure freedom in adults undergoing anterior temporal lobe resection (ATLR) for drug-resistant temporal lobe epilepsy (TLE). There have been no such studies in children, therefore this study aimed to investigate this association in a pediatric cohort. METHODS: A retrospective, neuroimaging cohort study of children with TLE who underwent ATLR between 2012 and 2021 was undertaken. The PC, hippocampal and amygdala volumes were measured on the preoperative and postoperative T1-weighted MRI. Using these volumes, the extent of resection per region was compared between the seizure-free and not seizure-free groups. RESULTS: In 50 children (median age 9.5 years) there was no significant difference between the extent of resection of the temporal PC in the seizure-free (median = 50%, n = 33/50) versus not seizure-free (median = 40%, n = 17/50) groups (p = 0.26). In a sub-group of 19 with ipsilateral hippocampal atrophy (quantitatively defined by ipsilateral-to-contralateral asymmetry), the median extent of temporal PC resection was greater in children who were seizure-free (53%) versus those not seizure-free (19%) (p = 0.009). INTERPRETATION: This is the first study demonstrating that, in children with TLE and hippocampal atrophy, more extensive temporal PC resection is associated with a greater chance of seizure freedom-compatible with an adult series in which 85% of patients had hippocampal sclerosis. In a combined group of children with and without hippocampal atrophy, the extent of PC resection was not associated with seizure outcome, suggesting different epileptogenic networks within this cohort.

Accuracy of robot-assisted stereotactic MRI-guided laser ablation in children with epilepsy.

OBJECTIVE: Robot-assisted (RA) stereotactic MRI-guided laser ablation has been reported to be a safe and effective technique for the treatment of epileptogenic foci in children and adults. In this study the authors aimed to assess the accuracy of RA stereotactic MRI-guided laser fiber placement in children and to identify factors that might increase the risk of misplacement. METHODS: A retrospective single-institution review of all children from 2019 to 2022 who underwent RA stereotactic MRI-guided laser ablation for epilepsy was undertaken. Placement error was calculated at the target by measuring the Euclidean distance between the implanted laser fiber position and the preoperatively planned position. Collected data included age at surgery, sex, pathology, date of robot calibration, number of catheters, entry position, entry angle, extracranial soft-tissue thickness, bone thickness, and intracranial catheter length. A systematic review of the literature was also performed using Ovid Medline, Ovid Embase, and the Cochrane Central Register of Controlled Trials. RESULTS: In 28 children with epilepsy, the authors assessed 35 RA stereotactic MRI-guided laser ablation fiber placements. Twenty (71.4%) children had undergone ablation for hypothalamic hamartoma, 7 children (25.0%) for presumed insular focal cortical dysplasia, and 1 patient (3.6%) for periventricular nodular heterotopia. Nineteen children were male (67.9.%) and 9 were female (32.1%). The median age at the time of the procedure was 7.67 years (IQR 4.58-12.26 years). The median target point localization error (TPLE) was 1.27 mm (IQR 0.76-1.71 mm). The median offset error between the planned and actual trajectories was 1.04° (IQR 0.73°-1.46°). Patient age, sex, pathology and the time interval between date of surgery and robot calibration, entry position, entry angle, soft-tissue thickness, bone thickness, and intracranial length were not associated with the placement accuracy of the implanted laser fibers. However, the number of catheters placed did correlate with the offset angle error on univariate analysis (ρ = 0.387, p = 0.022). There were no immediate surgical complications. Meta-analysis indicated that the overall pooled mean TPLE was 1.46 mm (95% CI -0.58 to 3.49 mm). CONCLUSIONS: RA stereotactic MRI-guided laser ablation for epilepsy in children is highly accurate. These data will aid surgical planning.

Paediatric subarachnoid haemorrhage and severe vasospasm secondary to traumatic pseudoaneurysm of a fenestrated vertebral artery: a case report and review of the literature.

Paediatric intracranial aneurysms are rare entities accounting for less than 5% of all age intracranial aneurysms. Traumatic aneurysms are more common in children and have an association with anatomical variations such as arterial fenestrations. Here, we present a case of a child initially presenting with traumatic subarachnoid haemorrhage who returned to baseline and was discharged home only to return within 2 weeks with diffuse subarachnoid and intraventricular re-haemorrhage. A dissecting aneurysm of a duplicated (fenestrated) V4 vertebral artery segment was identified as a rare cause of rebleeding. We describe a course complicated by severe vasospasm delaying aneurysm detection and treatment. Dissecting aneurysms in children should be considered in all cases of delayed post-traumatic cranial rebleeding, particularly where there is anomalous arterial anatomy.

Implications of leg length for metabolic health and fitness.

Background and objectives: Several studies have linked longer legs with favorable adult metabolic health outcomes and greater offspring birth weight. A recent Mendelian randomization study suggested a causal link between height and cardiometabolic risk; however, the underlying reasons remain poorly understood. Methodology: Using a cross-sectional design, we tested in a convenience sample of 70 healthy young women whether birth weight and tibia length as markers of early-life conditions associated more strongly with metabolically beneficial traits like organ size and skeletal muscle mass (SMM) than a statistically derived height-residual variable indexing later, more canalized growth. Results: Consistent with the 'developmental origins of health and disease' hypothesis, we found relatively strong associations of tibia length-but not birth weight-with adult organ size, brain size, SMM and resting energy expenditure measured by magnetic resonance imaging (MRI), dual-energy X-ray absorptiometry and indirect calorimetry, respectively. Conclusions and implications: Building on prior work, these results suggest that leg length is a sensitive marker of traits directly impacting metabolic and reproductive health. Alongside findings in the same sample relating tibia length and height-residual to MRI-measured pelvic dimensions, we suggest there may exist a degree of coordination in the development of long bone, lean mass and pelvic traits, possibly centered on early, pre-pubertal growth periods. Such phenotypic coordination has important implications for fitness, serving to benefit both adult health and the health of offspring in subsequent generations.

Amygdalar Functional Connectivity Differences Associated With Reduced Pain Intensity in Pediatric Peripheral Neuropathic Pain.

Background: There is evidence of altered corticolimbic circuitry in adults with chronic pain, but relatively little is known of functional brain mechanisms in adolescents with neuropathic pain (NeuP). Pediatric NeuP is etiologically and phenotypically different from NeuP in adults, highlighting the need for pediatric-focused research. The amygdala is a key limbic region with important roles in the emotional-affective dimension of pain and in pain modulation. Objective: To investigate amygdalar resting state functional connectivity (rsFC) in adolescents with NeuP. Methods: This cross-sectional observational cohort study compared resting state functional MRI scans in adolescents aged 11-18 years with clinical features of chronic peripheral NeuP (n = 17), recruited from a tertiary clinic, relative to healthy adolescents (n = 17). We performed seed-to-voxel whole-brain rsFC analysis of the bilateral amygdalae. Next, we performed post hoc exploratory correlations with clinical variables to further explain rsFC differences. Results: Adolescents with NeuP had stronger negative rsFC between right amygdala and right dorsolateral prefrontal cortex (dlPFC) and stronger positive rsFC between right amygdala and left angular gyrus (AG), compared to controls (P FDR <0.025). Furthermore, lower pain intensity correlated with stronger negative amygdala-dlPFC rsFC in males (r = 0.67, P = 0.034, n = 10), and with stronger positive amygdala-AG rsFC in females (r = -0.90, P = 0.006, n = 7). These amygdalar rsFC differences may thus be pain inhibitory. Conclusions: Consistent with the considerable affective and cognitive factors reported in a larger cohort, there are rsFC differences in limbic pain modulatory circuits in adolescents with NeuP. Findings also highlight the need for assessing sex-dependent brain mechanisms in future studies, where possible.

Drug-resistant focal epilepsy in children is associated with increased modal controllability of the whole brain and epileptogenic regions.

Network control theory provides a framework by which neurophysiological dynamics of the brain can be modelled as a function of the structural connectome constructed from diffusion MRI. Average controllability describes the ability of a region to drive the brain to easy-to-reach neurophysiological states whilst modal controllability describes the ability of a region to drive the brain to difficult-to-reach states. In this study, we identify increases in mean average and modal controllability in children with drug-resistant epilepsy compared to healthy controls. Using simulations, we purport that these changes may be a result of increased thalamocortical connectivity. At the node level, we demonstrate decreased modal controllability in the thalamus and posterior cingulate regions. In those undergoing resective surgery, we also demonstrate increased modal controllability of the resected parcels, a finding specific to patients who were rendered seizure free following surgery. Changes in controllability are a manifestation of brain network dysfunction in epilepsy and may be a useful construct to understand the pathophysiology of this archetypical network disease. Understanding the mechanisms underlying these controllability changes may also facilitate the design of network-focussed interventions that seek to normalise network structure and function.

Proportion of resected seizure onset zone contacts in pediatric stereo-EEG-guided resective surgery does not correlate with outcome.

OBJECTIVE: We aimed to determine whether the proportion of putative seizure onset zone (SOZ) contacts resected associates with seizure outcome in a cohort of children undergoing stereoelectroencephalography (SEEG)-guided resective epilepsy surgery. METHODS: Patients who underwent SEEG-guided resective surgery over a six-year period were included. The proportion of SOZ contacts resected was determined by co-registration of pre- and post-operative imaging. Outcome was classified as seizure free (SF, Engel class I) or not seizure-free (NSF, Engel class II-IV) at last clinical follow-up. RESULTS: Twenty-nine patients underwent resection of whom 22 had sufficient imaging data for analysis (median age at surgery of 10 years, range 5-18). Fifteen (68.2%) were SF at median follow-up of 19.5 months (range 12-46). On univariate analysis, histopathology, was the only significant factor associated with SF (p < 0.05). The percentage of defined SOZ contacts resected ranged from 25-100% and was not associated with SF (p = 0.89). In a binary logistic regression model, it was highly likely that histology was the only independent predictor of outcome. CONCLUSIONS: The percentage of SOZ contacts resected was not associated with SF in children undergoing SEEG-guided resective epilepsy surgery. SIGNIFICANCE: Factors such as spatial organisation of the epileptogenic zone, neurophysiological biomarkers and the prospective identification of pathological tissue may therefore play an important role.

IDEAL approach to the evaluation of machine learning technology in epilepsy surgery: protocol for the MAST trial.

Epilepsy and epilepsy surgery lend themselves well to the application of machine learning (ML) and artificial intelligence (AI) technologies. This is evidenced by the plethora of tools developed for applications such as seizure detection and analysis of imaging and electrophysiological data. However, few of these tools have been directly used to guide patient management. In recent years, the Idea, Development, Exploration, Assessment, Long-Term Follow-Up (IDEAL) collaboration has formalised stages for the evaluation of surgical innovation and medical devices, and, in many ways, this pragmatic framework is also applicable to ML/AI technology, balancing innovation and safety. In this protocol paper, we outline the preclinical (IDEAL stage 0) evaluation and the protocol for a prospective (IDEAL stage 1/2a) study to evaluate the utility of an ML lesion detection algorithm designed to detect focal cortical dysplasia from structural MRI, as an adjunct in the planning of stereoelectroencephalography trajectories in children undergoing intracranial evaluation for drug-resistant epilepsy.

High-resolution microscopic diffusion anisotropy imaging in the human hippocampus at 3T.

PURPOSE: Several neurological conditions are associated with microstructural changes in the hippocampus that can be observed using DWI. Imaging studies often use protocols with whole-brain coverage, imposing limits on image resolution and worsening partial-volume effects. Also, conventional single-diffusion-encoding methods confound microscopic diffusion anisotropy with size variance of microscopic diffusion environments. This study addresses these issues by implementing a multidimensional diffusion-encoding protocol for microstructural imaging of the hippocampus at high resolution. METHODS: The hippocampus of 8 healthy volunteers was imaged at 1.5-mm isotropic resolution with a multidimensional diffusion-encoding sequence developed in house. Microscopic fractional anisotropy (µFA) and normalized size variance (CMD ) were estimated using q-space trajectory imaging, and their values were compared with DTI metrics. The overall scan time was 1 hour. The reproducibility of the protocol was confirmed with scan-rescan experiments, and a shorter protocol (14 minutes) was defined for situations with time constraints. RESULTS: Mean µFA (0.47) was greater than mean FA (0.20), indicating orientation dispersion in hippocampal tissue microstructure. Mean CMD was 0.17. The reproducibility of q-space trajectory imaging metrics was comparable to DTI, and microstructural metrics in the healthy hippocampus are reported. CONCLUSION: This work shows the feasibility of high-resolution microscopic anisotropy imaging in the human hippocampus at 3 T and provides reference values for microstructural metrics in a healthy hippocampus.

Planning stereoelectroencephalography using automated lesion detection: Retrospective feasibility study.

OBJECTIVE: This retrospective, cross-sectional study evaluated the feasibility and potential benefits of incorporating deep-learning on structural magnetic resonance imaging (MRI) into planning stereoelectroencephalography (sEEG) implantation in pediatric patients with diagnostically complex drug-resistant epilepsy. This study aimed to assess the degree of colocalization between automated lesion detection and the seizure onset zone (SOZ) as assessed by sEEG. METHODS: A neural network classifier was applied to cortical features from MRI data from three cohorts. (1) The network was trained and cross-validated using 34 patients with visible focal cortical dysplasias (FCDs). (2) Specificity was assessed in 20 pediatric healthy controls. (3) Feasibility of incorporation into sEEG implantation plans was evaluated in 34 sEEG patients. Coordinates of sEEG contacts were coregistered with classifier-predicted lesions. sEEG contacts in seizure onset and irritative tissue were identified by clinical neurophysiologists. A distance of <10 mm between SOZ contacts and classifier-predicted lesions was considered colocalization. RESULTS: In patients with radiologically defined lesions, classifier sensitivity was 74% (25/34 lesions detected). No clusters were detected in the controls (specificity = 100%). Of the total 34 sEEG patients, 21 patients had a focal cortical SOZ, of whom eight were histopathologically confirmed as having an FCD. The algorithm correctly detected seven of eight of these FCDs (86%). In patients with histopathologically heterogeneous focal cortical lesions, there was colocalization between classifier output and SOZ contacts in 62%. In three patients, the electroclinical profile was indicative of focal epilepsy, but no SOZ was localized on sEEG. In these patients, the classifier identified additional abnormalities that had not been implanted. SIGNIFICANCE: There was a high degree of colocalization between automated lesion detection and sEEG. We have created a framework for incorporation of deep-learning-based MRI lesion detection into sEEG implantation planning. Our findings support the prospective evaluation of automated MRI analysis to plan optimal electrode trajectories.

Estimating brain volume loss after radiation therapy in children treated for posterior fossa tumors (Corpus callosum and whole brain volume changes following radiotherapy in children).

BACKGROUND: More than half of pediatric tumors of central nervous system (CNS) primarily originate in the posterior fossa and are conventionally treated with radiation therapy (RT). OBJECTIVES: The objective of this study was to establish whether corpus callosum volumes (CCV) and whole brain volumes (WBV) are correlated and to determine the impact of whole-brain lowvs high-dose RT on brain parenchymal volume loss as assessed using each technique. MATERIAL AND METHODS: Of the 30 identified children (6-12 years) with newly diagnosed posterior fossa tumors treated with cranial RT, including focal and whole-brain RT, suitable imaging was obtained for 23. Radiotherapy regimens were the following: no whole-brain RT (Group 1, n = 7), low-dose whole-brain RT (<30 Gy, Group 2, n = 9) and high-dose whole-brain RT (>30 Gy, Group 3, n = 7) in addition to focal boost. Magnetic resonance images (MRIs) were analyzed at baseline and follow-up (median 14 months). The CCVs were manually segmented on midline sagittal slice (n = 23), while WBVs were segmented semi-automatically using Freesurfer (n = 15). This was done twice (6-month interval) for all baseline CCV measurements and 5 randomly selected WBV measurements to establish measurement reproducibility. Correlations between CCV and WBV were investigated and percentage of children demonstrating reduction in CCV or WBV noted. RESULTS: Correlation between baseline CCV and WBV was not significant (p = 0.37). Measurement reproducibility was from 6% to -9% for CCV and from 4.8% to -1.2% for WBV. Among the children studied, 30.4% (7/23) had >9% reduction in CCV at follow-up, while 33.3% (5/15) had >1.2% reduction in WBV. Five of 7 patients with CCV loss were not picked up by WBV measurements. Similarly, 3 of 5 patients with WBV loss were not picked up by CCV measurements. CONCLUSIONS: The CCV and the WBV are unrelated and may indicate different brain parenchymal losses following RT. Up to a third of posterior fossa tumors treated with RT have measurable CCV or WBV loss; incidence was equivalent in lowvs high-dose whole-brain RT.

The feasibility and acceptability of research magnetic resonance imaging in adolescents with moderate-severe neuropathic pain.

INTRODUCTION: Multimodal characterisation with questionnaires, Quantitative Sensory Testing (QST), and neuroimaging will improve understanding of neuropathic pain (NeuP) in adolescents. Magnetic resonance imaging (MRI) data in adolescents with NeuP are limited, and the perceived practical or ethical burden of scanning may represent a barrier to research. OBJECTIVE: To determine the feasibility of MRI scanning in adolescents with moderate-severe NeuP, with respect to consent rate, postscan acceptability, and data quality. METHODS: This prospective cohort study evaluating questionnaires and QST recruited adolescents aged 10 to 18 years with clinically diagnosed NeuP from a tertiary clinic. Eligible adolescents aged 11 years and older could additionally agree/decline an MRI scan. After the scan, families rated discomfort, perceived risk, and acceptability of current and future MRI scans (0-10 numerical rating scales). Head motion during scanning was compared with healthy controls to assess data quality. RESULTS: Thirty-four families agreed to MRI (72% recruitment), and 21 adolescents with moderate-severe pain (average last week 6.7 ± 1.7; mean ± SD) and with neuropathic QST profiles were scanned. Three adolescents reported positional or noise-related discomfort during scanning. Perceived risk was low, and acceptability of the current scan was high for parents (range [median]: 7 to 10/10 [10]) and adolescents (8-10/10 [10]). Willingness to undergo a future research scan was high for parents (7-10/10 [10]) and adolescents (5-10/10 [10]) and did not differ from future scans for clinical purposes. Mean head motion during resting state functional MRI did not differ from control adolescents. CONCLUSION: Research MRI is feasible and acceptable for many adolescents with moderate-severe NeuP.

Accuracy of robot-assisted versus optical frameless navigated stereoelectroencephalography electrode placement in children.

OBJECTIVE The aim of this study was to compare the accuracy of optical frameless neuronavigation (ON) and robot-assisted (RA) stereoelectroencephalography (SEEG) electrode placement in children, and to identify factors that might increase the risk of misplacement. METHODS The authors undertook a retrospective review of all children who underwent SEEG at their institution. Twenty children were identified who underwent stereotactic placement of a total of 218 electrodes. Six procedures were performed using ON and 14 were placed using a robotic assistant. Placement error was calculated at cortical entry and at the target by calculating the Euclidean distance between the electrode and the planned cortical entry and target points. The Mann-Whitney U-test was used to compare the results for ON and RA placement accuracy. For each electrode placed using robotic assistance, extracranial soft-tissue thickness, bone thickness, and intracranial length were measured. Entry angle of electrode to bone was calculated using stereotactic coordinates. A stepwise linear regression model was used to test for variables that significantly influenced placement error. RESULTS Between 8 and 17 electrodes (median 10 electrodes) were placed per patient. Median target point localization error was 4.5 mm (interquartile range [IQR] 2.8­6.1 mm) for ON and 1.07 mm (IQR 0.71­1.59) for RA placement. Median entry point localization error was 5.5 mm (IQR 4.0­6.4) for ON and 0.71 mm (IQR 0.47­1.03) for RA placement. The difference in accuracy between Stealth-guided (ON) and RA placement was highly significant for both cortical entry point and target (p < 0.0001 for both). Increased soft-tissue thickness and intracranial length reduced accuracy at the target. Increased soft-tissue thickness, bone thickness, and younger age reduced accuracy at entry. There were no complications. CONCLUSIONS RA stereotactic electrode placement is highly accurate and is significantly more accurate than ON. Larger safety margins away from vascular structures should be used when placing deep electrodes in young children and for trajectories that pass through thicker soft tissues such as the temporal region. ABBREVIATIONS CTA = CT angiography; IQR = interquartile range; MEG = magnetoencephalography; ON = optical frameless neuronavigation; RA = robot-assisted; SEEG = stereoelectroencephalography.

Metabolic rate of major organs and tissues in young adult South Asian women.

BACKGROUND/OBJECTIVES: Major organ-specific and tissue-specific metabolic rate (Ki) values were initially estimated using in vivo methods, and values reported by Elia (Energy metabolism: tissue determinants and cellular corollaries, Raven Press, New York, 1992) were subsequently supported by statistical analysis. However, the majority of work to date on this topic has addressed individuals of European descent, whereas population variability in resting energy metabolism has been reported. We aimed to estimate Ki values in South Asian females. SUBJECTS/METHODS: This cross-sectional study recruited 70 healthy young women of South Asian ancestry. Brain and organs were measured using magnetic resonance imaging, skeletal muscle mass by dual-energy X-ray absorptiometry, fat mass by the 4-component model, and whole-body resting energy expenditure by indirect calorimetry. Organ and tissue Ki values were estimated indirectly using regression analysis through the origin. Preliminary analysis suggested overestimation of heart mass, hence the modeling was repeated with a literature-based 22.5% heart mass reduction. RESULTS: The pattern of derived Ki values across organs and tissues matched that previously estimated in vivo, but the values were systematically lower. However, adjusting for the overestimation of heart mass markedly improved the agreement. CONCLUSIONS: Our results support variability in Ki values among organs and tissues, where some are more metabolically "expensive" than others. Initial findings suggesting lower organ/tissue Ki values in South Asian women were likely influenced by heart mass estimation bias. The question of potential ethnic variability in organ-specific and tissue-specific energy metabolism requires further investigation.

Natural biological variation of white matter microstructure is accentuated in Huntington's disease.

Huntington's disease (HD) is a monogenic neurodegenerative disorder caused by a CAG-repeat expansion in the Huntingtin gene. Presence of this expansion signifies certainty of disease onset, but only partly explains age at which onset occurs. Genome-wide association studies have shown that naturally occurring genetic variability influences HD pathogenesis and disease onset. Investigating the influence of biological traits in the normal population, such as variability in white matter properties, on HD pathogenesis could provide a complementary approach to understanding disease modification. We have previously shown that while white matter diffusivity patterns in the left sensorimotor network were similar in controls and HD gene-carriers, they were more extreme in the HD group. We hypothesized that the influence of natural variation in diffusivity on effects of HD pathogenesis on white matter is not limited to the sensorimotor network but extends to cognitive, limbic, and visual networks. Using tractography, we investigated 32 bilateral pathways within HD-related networks, including motor, cognitive, and limbic, and examined diffusivity metrics using principal components analysis. We identified three independent patterns of diffusivity common to controls and HD gene-carriers that predicted HD status. The first pattern involved almost all tracts, the second was limited to sensorimotor tracts, and the third encompassed cognitive network tracts. Each diffusivity pattern was associated with network specific performance. The consistency in diffusivity patterns across both groups coupled with their association with disease status and task performance indicates that naturally-occurring patterns of diffusivity can become accentuated in the presence of the HD gene mutation to influence clinical brain function.

Altered White-Matter Microstructure in Conduct Disorder Is Specifically Associated with Elevated Callous-Unemotional Traits.

Adolescents with conduct disorder (CD) and elevated callous-unemotional (CU) traits have been reported to present with a more severe and persistent pattern of antisocial behaviour than those with low levels of CU traits. However, relatively few studies have investigated whether there are differences in brain structure between these subgroups.We acquired diffusion tensor imaging data and used tract-based spatial statistics (TBSS) to compare adolescents with CD and high levels of CU traits (CD/CU+; n = 18, CD and low levels of CU traits (CD/CU-; n = 17) and healthy controls (HC; n = 32) on measures of fractional anisotropy (FA), axial (AD), radial (RD) and mean (MD) diffusivity. Compared to CD/CU- adolescents, those with CD/CU+ presented increased FA and reduced RD and MD (lower diffusivity) in several tracts including: body and splenium of the corpus callosum, right inferior longitudinal fasciculus, ILF; right inferior fronto-occipital fasciculus, IFOF; left superior longitudinal fasciculus, SLF; left cerebral peduncle, bilateral internal capsule, left superior and posterior corona radiata, bilateral thalamic radiation and left external capsule. In addition, relative to CD/CU- individuals, adolescents with CD/CU+ showed lower diffusivity (indexed by reduced RD and MD) in left uncinate fasciculus and bilateral fornix. Finally, relative to healthy controls, CD/CU+ individuals showed lower diffusivity (reduced RD) in the genu and body of the corpus callosum and left anterior corona radiata. These results suggest that CD/CU+ individuals present with white-matter microstructural abnormalities compared to both CD/CU- individuals and age-matched healthy controls. This finding is consistent with emerging evidence suggesting that CD/CU+ represents a distinct subtype of CD, and illustrates the importance of accounting for heterogeneity within CD populations.