Adiposity related brain plasticity induced by bariatric surgery

Previous magnetic resonance imaging (MRI) studies revealed structural-functional brain reorganization 12 months after gastric-bypass surgery, encompassing cortical and subcortical regions of all brain lobes as well as the cerebellum. Changes in the mean of cluster-wise gray/white matter density (GMD/WMD) were correlated with the individual loss of body mass index (BMI), rendering the BMI a potential marker of widespread surgery-induced brain plasticity. Here, we investigated voxel-by-voxel associations between surgery-induced changes in adiposity, metabolism and inflammation and markers of functional and structural neural plasticity. We re-visited the data of patients who underwent functional and structural MRI, 6 months (n = 27) and 12 months after surgery (n = 22), and computed voxel-wise regression analyses. Only the surgery-induced weight loss was significantly associated with brain plasticity, and this only for GMD changes. After 6 months, weight loss overlapped with altered GMD in the hypothalamus, the brain’s homeostatic control site, the lateral orbitofrontal cortex, assumed to host reward and gustatory processes, as well as abdominal representations in somatosensory cortex. After 12 months, weight loss scaled with GMD changes in right cerebellar lobule VII, involved in language-related/cognitive processes, and, by trend, with the striatum, assumed to underpin (food) reward. These findings suggest time-dependent and weight-loss related gray matter plasticity in brain regions involved in the control of eating, sensory processing and cognitive functioning

Roux-en-Y gastric bypass surgery progressively alters radiologic measures of hypothalamic inflammation in obese patients

There is increased interest in whether bariatric surgeries such as Roux-en-Y gastric bypass (RYGB) achieve their profound weight-lowering effects in morbidly obese individuals through the brain. Hypothalamic inflammation is a well-recognized etiologic factor in obesity pathogenesis and so represents a potential target of RYGB, but clinical evidence in support of this is limited. We therefore assessed hypothalamic T2-weighted signal intensities (T2W SI) and fractional anisotropy (FA) values, 2 validated radiologic measures of brain inflammation, in relation to BMI and fat mass, as well as circulating inflammatory (C-reactive protein; CrP) and metabolic markers in a cohort of 27 RYGB patients at baseline and 6 and 12 months after surgery. We found that RYGB progressively increased hypothalamic T2W SI values, while it progressively decreased hypothalamic FA values. Regression analyses further revealed that this could be most strongly linked to plasma CrP levels, which independently predicted hypothalamic FA values when adjusting for age, sex, fat mass, and diabetes diagnosis. These findings suggest that RYGB has a major time-dependent impact on hypothalamic inflammation status, possibly by attenuating peripheral inflammation. They also suggest that hypothalamic FA values may provide a more specific radiologic measure of hypothalamic inflammation than more commonly used T2W SI values

Search for new loci and low-frequency variants influencing glioma risk by exome-array analysis

To identify protein-altering variants (PAVs) for glioma, we analysed Illumina HumanExome BeadChip exome-array data on 1882 glioma cases and 8079 controls from three independent European populations. In addition to single-variant tests we incorporated information on the predicted functional consequences of PAVs and analysed sets of genes with a higher likelihood of having a role in glioma on the basis of the profile of somatic mutations documented by large-scale sequencing initiatives. Globally there was a strong relationship between effect size and PAVs predicted to be damaging (P=2.29 × 10−49); however, these variants which are most likely to impact on risk, are rare (MAFT, p.(Lys3326Ter), which has been shown to influence breast and lung cancer risk (odds ratio (OR)=2.3, P=4.00 × 10−4 for glioblastoma (GBM)) and IDH2:c.782G>A, p.(Arg261His) (OR=3.21, P=7.67 × 10−3, for non-GBM). Additionally, gene burden tests revealed a statistically significant association for HARS2 and risk of GBM (P=2.20 × 10−6). Genome scans of low-frequency PAVs represent a complementary strategy to identify disease-causing variants compared with scans based on tagSNPs. Strategies to lessen the multiple testing burden by restricting analysis to PAVs with higher priors affords an opportunity to maximise study power

Infant Brain Atlases from Neonates to 1- and 2-Year-Olds

Background: Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. Methodology: To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-yearold, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between agespecific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. Conclusions: We expect that the proposed infant 0–1–2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website

Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI Segmentation

Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study

Effect of surgical experience and spine subspecialty on the reliability of the {AO} Spine Upper Cervical Injury Classification System

OBJECTIVE The objective of this paper was to determine the interobserver reliability and intraobserver reproducibility of the AO Spine Upper Cervical Injury Classification System based on surgeon experience (< 5 years, 5–10 years, 10–20 years, and > 20 years) and surgical subspecialty (orthopedic spine surgery, neurosurgery, and "other" surgery). METHODS A total of 11,601 assessments of upper cervical spine injuries were evaluated based on the AO Spine Upper Cervical Injury Classification System. Reliability and reproducibility scores were obtained twice, with a 3-week time interval. Descriptive statistics were utilized to examine the percentage of accurately classified injuries, and Pearson’s chi-square or Fisher’s exact test was used to screen for potentially relevant differences between study participants. Kappa coefficients (κ) determined the interobserver reliability and intraobserver reproducibility. RESULTS The intraobserver reproducibility was substantial for surgeon experience level (< 5 years: 0.74 vs 5–10 years: 0.69 vs 10–20 years: 0.69 vs > 20 years: 0.70) and surgical subspecialty (orthopedic spine: 0.71 vs neurosurgery: 0.69 vs other: 0.68). Furthermore, the interobserver reliability was substantial for all surgical experience groups on assessment 1 (< 5 years: 0.67 vs 5–10 years: 0.62 vs 10–20 years: 0.61 vs > 20 years: 0.62), and only surgeons with > 20 years of experience did not have substantial reliability on assessment 2 (< 5 years: 0.62 vs 5–10 years: 0.61 vs 10–20 years: 0.61 vs > 20 years: 0.59). Orthopedic spine surgeons and neurosurgeons had substantial intraobserver reproducibility on both assessment 1 (0.64 vs 0.63) and assessment 2 (0.62 vs 0.63), while other surgeons had moderate reliability on assessment 1 (0.43) and fair reliability on assessment 2 (0.36). CONCLUSIONS The international reliability and reproducibility scores for the AO Spine Upper Cervical Injury Classification System demonstrated substantial intraobserver reproducibility and interobserver reliability regardless of surgical experience and spine subspecialty. These results support the global application of this classification system

ICAR: endoscopic skull‐base surgery

n/

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries