hMRI - A toolbox for quantitative MRI in neuroscience and clinical research

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.

A single fast radio burst localized to a massive galaxy at cosmological distance

Fast radio bursts (FRBs) are brief radio emissions from distant astronomical sources. Some are known to repeat, but most are single bursts. Nonrepeating FRB observations have had insufficient positional accuracy to localize them to an individual host galaxy. We report the interferometric localization of the single-pulse FRB 180924 to a position 4 kiloparsecs from the center of a luminous galaxy at redshift 0.3214. The burst has not been observed to repeat. The properties of the burst and its host are markedly different from those of the only other accurately localized FRB source. The integrated electron column density along the line of sight closely matches models of the intergalactic medium, indicating that some FRBs are clean probes of the baryonic component of the cosmic web.

Characterization of a temporoparietal junction subtype of Alzheimer's disease

Alzheimer's disease (AD) subtypes have been described according to genetics, neuropsychology, neuropathology, and neuroimaging. Thirty-one patients with clinically probable AD were selected based on perisylvian metabolic decrease on FDG-PET. They were compared to 25 patients with a typical pattern of decreased posterior metabolism. Tree-based machine learning was used on those 56 images to create a classifier that was subsequently applied to 207 Alzheimer's Disease Neuroimaging Initiative (ADNI) patients with AD. Machine learning was also used to discriminate between the two ADNI groups based on neuropsychological scores. Compared to AD patients with a typical precuneus metabolic decrease, the new subtype showed stronger hypometabolism in the temporoparietal junction. The classifier was able to distinguish the two groups in the ADNI population. Both groups could only be distinguished cognitively by Trail Making Test-A scores. This study further confirms that there is more than a typical metabolic pattern in probable AD with amnestic presentation.

EEG-BIDS, an extension to the brain imaging data structure for electroencephalography

The Brain Imaging Data Structure (BIDS) project is a rapidly evolving effort in the human brain imaging research community to create standards allowing researchers to readily organize and share study data within and between laboratories. Here we present an extension to BIDS for electroencephalography (EEG) data, EEG-BIDS, along with tools and references to a series of public EEG datasets organized using this new standard.

Development and validation of the EUROFORGEN NAME (North African and Middle Eastern) ancestry panel

Inference of biogeographic origin is an important factor in clinical, population and forensic genetics. The information provided by AIMs (Ancestry Informative Markers) can allow the differentiation of major continental population groups, and several AIM panels have been developed for this purpose. However, from these major population groups, Eurasia covers a wide area between two continents that is difficult to differentiate genetically. These populations display a gradual genetic cline from West Europe to South Asia in terms of allele frequency distribution. Although differences have been reported between Europe and South Asia, Middle East populations continue to be a target of further investigations due to the lack of genetic variability, therefore hampering their genetic differentiation from neighboring populations. In the present study, a custom-built ancestry panel was developed to analyze North African and Middle Eastern populations, designated the 'NAME' panel. The NAME panel contains 111 SNPs that have patterns of allele frequency differentiation that can distinguish individuals originating in North Africa and the Middle East when combined with a previous set of 126 Global AIM-SNPs.

Multiparameter MRI quantification of microstructural tissue alterations in multiple sclerosis

Objectives

Conventional MRI is not sensitive to many pathological processes underpinning multiple sclerosis (MS) ongoing in normal appearing brain tissue (NABT). Quantitative MRI (qMRI) and a multiparameter mapping (MPM) protocol are used to simultaneously quantify magnetization transfer (MT) saturation, transverse relaxation rate R2* (1/T2*) and longitudinal relaxation rate R1 (1/T1), and assess differences in NABT microstructure between MS patients and healthy controls (HC).

Methods

This prospective cross-sectional study involves 36 MS patients (21 females, 15 males; age range 22–63 years; 15 relapsing-remitting MS - RRMS; 21 primary or secondary progressive MS - PMS) and 36 age-matched HC (20 females, 16 males); age range 21–61 years). The qMRI maps are computed and segmented in lesions and 3 normal appearing cerebral tissue classes: normal appearing cortical grey matter (NACGM), normal appearing deep grey matter (NADGM), normal appearing white matter (NAWM). Individual median values are extracted for each tissue class and MR parameter. MANOVAs and stepwise regressions assess differences between patients and HC.

Results

MS patients are characterized by a decrease in MT, R2* and R1 within NACGM (p < .0001) and NAWM (p < .0001). In NADGM, MT decreases (p < .0001) but R2* and R1 remain normal. These observations tend to be more pronounced in PMS. Quantitative MRI parameters are independent predictors of clinical status: EDSS is significantly related to R1 in NACGM and R2* in NADGM; the latter also predicts motor score. Cognitive score is best predicted by MT parameter within lesions.

Conclusions

Multiparametric data of brain microstructure concord with the literature, predict clinical performance and suggest a diffuse reduction in myelin and/or iron content within NABT of MS patients.

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We revisit microstructural alterations of NABT in MS patients by simultaneously quantifying three MRI parameters.

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Data suggest reduction of MT/R2*/R1 in NABT of MS patients, suggesting a reduction in myelin and/or iron content.

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Quantitative MRI parameters in NABT are independent predictors of clinical status.

Increased cerebral responses to salient transitions between alternating stimuli in chronic migraine with medication overuse headache and during migraine attacks

Introduction

In a previous study exploring central pain modulation with heterotopic stimuli in healthy volunteers, we found that transitions between sustained noxious and innocuous thermal stimulations on the foot activated the “salience matrix”. Knowing that central sensory processing is abnormal in migraine, we searched in the present study for possible abnormalities of these salient transitional responses in different forms of migraine and at different time points of the migraine cycle.

Methods

Participants of both sexes, mostly females, took part in a conditioned pain modulation experiment: Migraineurs between (n = 14) and during attacks (n = 5), chronic migraine patients with medication overuse headache (n = 7) and healthy volunteers (n = 24). To evoke the salience response, continuous noxious cold or innocuous warm stimulations were alternatively applied on the right foot. Cerebral blood oxygenation level dependent responses were recorded with fMRI.

Results

Switching between the two stimulations caused a significant transition response in the “salience matrix” in all subject groups (effect of the condition). Moreover, some group effects appeared on subsequent post-hoc analyses. Augmented transitional blood oxygenation level dependent responses in the motor cortex and superior temporal sulcus were found in two patient groups compared to healthy controls: chronic migraine with medication overuse headache patients and migraineurs recorded during an attack. In chronic migraine with medication overuse headache patients, salience-related responses were moreover greater in the premotor cortex, supplementary motor area, lingual gyrus and dorso-medial prefrontal cortex and other “salience matrix” areas, such as the anterior cingulate and primary somatosensory cortices.

Conclusion

This study shows salience-related hyperactivation of affective and motor control areas in chronic migraine with medication overuse headache patients and, to a lesser extent, in episodic migraine patients during an attack. The greater extension of exaggerated blood oxygenation level dependent responses to unspecific salient stimuli in chronic migraine with medication overuse headache than during a migraine attack could be relevant for headache chronification.

Skull Base 3D Modeling of Rigid Buttress for Gasket-Seal Closure Using Operative Endoscopic Imaging: Cadaveric Feasibility

Surgical defect closure following endonasal transsphenoidal tumor resection is a critical component of procedural success. Three-dimensional (3D) modeling of relevant skull base anatomy during resection can potentially facilitate design of a custom rigid buttress for gasket-seal closure; however, access to conventional cross-sectional imaging intraoperatively is limited and cumbersome. Endoscopic imaging, by contrast, is always available. This work demonstrates the feasibility of 3D modeling of the visible skull base through structure-from-motion photogrammetric postprocessing techniques, providing a suitable template to design a gasket-seal buttress. Additionally, endoscopic 3D reconstruction of skull base surface anatomy may represent a more robust depiction of the surgical defect than is available by conventional 3D modeling with computed tomography, which suboptimally recapitulates very thin bones and mucosal surfaces typical of this regional anatomy.

Soil and water bioengineering: Practice and research needs for reconciling natural hazard control and ecological restoration

Soil and water bioengineering is a technology that encourages scientists and practitioners to combine their knowledge and skills in the management of ecosystems with a common goal to maximize benefits to both man and the natural environment. It involves techniques that use plants as living building materials, for: (i) natural hazard control (e.g., soil erosion, torrential floods and landslides) and (ii) ecological restoration or nature-based re-introduction of species on degraded lands, river embankments, and disturbed environments. For a bioengineering project to be successful, engineers are required to highlight all the potential benefits and ecosystem services by documenting the technical, ecological, economic and social values. The novel approaches used by bioengineers raise questions for researchers and necessitate innovation from practitioners to design bioengineering concepts and techniques. Our objective in this paper, therefore, is to highlight the practice and research needs in soil and water bioengineering for reconciling natural hazard control and ecological restoration. Firstly, we review the definition and development of bioengineering technology, while stressing issues concerning the design, implementation, and monitoring of bioengineering actions. Secondly, we highlight the need to reconcile natural hazard control and ecological restoration by posing novel practice and research questions.

Cost-effectiveness of yoga for managing musculoskeletal conditions in the workplace

Background

Back pain and musculoskeletal conditions negatively affect the health-related quality of life (HRQL) of employees and generate substantial costs to employers.

Aims

To assess the cost-effectiveness of yoga for managing musculoskeletal conditions.

Methods

A randomized controlled trial evaluated an 8-week yoga programme, with a 6-month follow-up, for National Health Service (NHS) employees. Effectiveness in managing musculoskeletal conditions was assessed using repeated-measures generalized linear modelling for the Roland-Morris Disability Questionnaire (RDQ) and the Keele STarT Back Screening Tool. Cost-effectiveness was determined using area-under-the-curve linear regression for assessing HRQL from healthcare and societal perspectives. The incremental cost per quality-adjusted life year (QALY) was also calculated. Sickness absence was measured using electronic staff records at 6 months.

Results

There were 151 participants. At 6 months, mean differences between groups favouring yoga were observed for RDQ [-0.63 (95% CI, -1.78, 0.48)], Keele STarT [-0.28 (95% CI, -0.97, 0.07)] and HRQL (0.016 QALY gain). From a healthcare perspective, yoga yielded an incremental cost-effectiveness ratio of £2103 per QALY. Given a willingness to pay for an additional QALY of £20 000, the probability of yoga being cost-effective was 95%. From a societal perspective, yoga was the dominant treatment compared with usual care. At 6 months, electronic staff records showed that yoga participants missed a total of 2 working days due to musculoskeletal conditions compared with 43 days for usual care participants.

Conclusions

Yoga for NHS employees may enhance HRQL, reduce disability associated with back pain, lower sickness absence due to musculoskeletal conditions and is likely to be cost-effective.

Critical care usage after major gastrointestinal and liver surgery: a prospective, multicentre observational study

BACKGROUND

Patient selection for critical care admission must balance patient safety with optimal resource allocation. This study aimed to determine the relationship between critical care admission, and postoperative mortality after abdominal surgery.

METHODS

This prespecified secondary analysis of a multicentre, prospective, observational study included consecutive patients enrolled in the DISCOVER study from UK and Republic of Ireland undergoing major gastrointestinal and liver surgery between October and December 2014. The primary outcome was 30-day mortality. Multivariate logistic regression was used to explore associations between critical care admission (planned and unplanned) and mortality, and inter-centre variation in critical care admission after emergency laparotomy.

RESULTS

Of 4529 patients included, 37.8% (n=1713) underwent planned critical care admissions from theatre. Some 3.1% (n=86/2816) admitted to ward-level care subsequently underwent unplanned critical care admission. Overall 30-day mortality was 2.9% (n=133/4519), and the risk-adjusted association between 30-day mortality and critical care admission was higher in unplanned [odds ratio (OR): 8.65, 95% confidence interval (CI): 3.51-19.97) than planned admissions (OR: 2.32, 95% CI: 1.43-3.85). Some 26.7% of patients (n=1210/4529) underwent emergency laparotomies. After adjustment, 49.3% (95% CI: 46.8-51.9%, P<0.001) were predicted to have planned critical care admissions, with 7% (n=10/145) of centres outside the 95% CI.

CONCLUSIONS

After risk adjustment, no 30-day survival benefit was identified for either planned or unplanned postoperative admissions to critical care within this cohort. This likely represents appropriate admission of the highest-risk patients. Planned admissions in selected, intermediate-risk patients may present a strategy to mitigate the risk of unplanned admission. Substantial inter-centre variation exists in planned critical care admissions after emergency laparotomies.

Electrical impedance tomography for non-invasive assessment of stroke volume variation in health and experimental lung injury

BACKGROUND

Functional imaging by thoracic electrical impedance tomography (EIT) is a non-invasive approach to continuously assess central stroke volume variation (SVV) for guiding fluid therapy. The early available data were from healthy lungs without injury-related changes in thoracic impedance as a potentially influencing factor. The aim of this study was to evaluate SVV measured by EIT (SVV_EIT) against SVV from pulse contour analysis (SVV_PC) in an experimental animal model of acute lung injury at different lung volumes.

METHODS

We conducted a randomized controlled trial in 30 anaesthetized domestic pigs. SVV_EIT was calculated automatically analysing heart-lung interactions in a set of pixels representing the aorta. Each initial analysis was performed automatically and unsupervised using predefined frequency domain algorithms that had not previously been used in the study population. After baseline measurements in normal lung conditions, lung injury was induced either by repeated broncho-alveolar lavage (n=15) or by intravenous administration of oleic acid (n=15) and SVV_EIT was remeasured.

RESULTS

The protocol was completed in 28 animals. A total of 123 pairs of SVV measurements were acquired. Correlation coefficients (r) between SVV_EIT and SVV_PC were 0.77 in healthy lungs, 0.84 after broncho-alveolar lavage, and 0.48 after lung injury from oleic acid.

CONCLUSIONS

EIT provides automated calculation of a dynamic preload index of fluid responsiveness (SVV_EIT) that is non-invasively derived from a central haemodynamic signal. However, alterations in thoracic impedance induced by lung injury influence this method.

Random Forests Based Group Importance Scores and Their Statistical Interpretation: Application for Alzheimer's Disease

Machine learning approaches have been increasingly used in the neuroimaging field for the design of computer-aided diagnosis systems. In this paper, we focus on the ability of these methods to provide interpretable information about the brain regions that are the most informative about the disease or condition of interest. In particular, we investigate the benefit of group-based, instead of voxel-based, analyses in the context of Random Forests. Assuming a prior division of the voxels into non overlapping groups (defined by an atlas), we propose several procedures to derive group importances from individual voxel importances derived from Random Forests models. We then adapt several permutation schemes to turn group importance scores into more interpretable statistical scores that allow to determine the truly relevant groups in the importance rankings. The good behaviour of these methods is first assessed on artificial datasets. Then, they are applied on our own dataset of FDG-PET scans to identify the brain regions involved in the prognosis of Alzheimer's disease.