Atlas-based assessment of hypomyelination: Quantitative MRI in Pelizaeus-Merzbacher disease.

Pelizaeus-Merzbacher disease (PMD) is a rare childhood hypomyelinating leukodystrophy. Quantification of the pronounced myelin deficit and delineation of subtle myelination processes are of high clinical interest. Quantitative magnetic resonance imaging (qMRI) techniques can provide in vivo insights into myelination status, its spatial distribution, and dynamics during brain maturation. They may serve as potential biomarkers to assess the efficacy of myelin-modulating therapies. However, registration techniques for image quantification and statistical comparison of affected pediatric brains, especially those of low or deviant image tissue contrast, with healthy controls are not yet established. This study aimed first to develop and compare postprocessing pipelines for atlas-based quantification of qMRI data in pediatric patients with PMD and evaluate their registration accuracy. Second, to apply an optimized pipeline to investigate spatial myelin deficiency using myelin water imaging (MWI) data from patients with PMD and healthy controls. This retrospective single-center study included five patients with PMD (mean age, 6 years ± 3.8) who underwent conventional brain MRI and diffusion tensor imaging (DTI), with MWI data available for a subset of patients. Three methods of registering PMD images to a pediatric template were investigated. These were based on (a) T1-weighted (T1w) images, (b) fractional anisotropy (FA) maps, and (c) a combination of T1w, T2-weighted, and FA images in a multimodal approach. Registration accuracy was determined by visual inspection and calculated using the structural similarity index method (SSIM). SSIM values for the registration approaches were compared using a t test. Myelin water fraction (MWF) was quantified from MWI data as an assessment of relative myelination. Mean MWF was obtained from two PMDs (mean age, 3.1 years ± 0.3) within four major white matter (WM) pathways of a pediatric atlas and compared to seven healthy controls (mean age, 3 years ± 0.2) using a Mann-Whitney U test. Our results show that visual registration accuracy estimation and computed SSIM were highest for FA-based registration, followed by multimodal, and T1w-based registration (SSIMFA = 0.67 ± 0.04 vs. SSIMmultimodal = 0.60 ± 0.03 vs. SSIMT1 = 0.40 ± 0.14). Mean MWF of patients with PMD within the WM pathways was significantly lower than in healthy controls MWFPMD = 0.0267 ± 0.021 vs. MWFcontrols = 0.1299 ± 0.039. Specifically, MWF was measurable in brain structures known to be myelinated at birth (brainstem) or postnatally (projection fibers) but was scarcely detectable in other brain regions (commissural and association fibers). Taken together, our results indicate that registration accuracy was highest with an FA-based registration pipeline, providing an alternative to conventional T1w-based registration approaches in the case of hypomyelinating leukodystrophies missing normative intrinsic tissue contrasts. The applied atlas-based analysis of MWF data revealed that the extent of spatial myelin deficiency in patients with PMD was most pronounced in commissural and association and to a lesser degree in brainstem and projection pathways.

Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by improved inter-scanner stability.

OBJECTIVES: To develop an automatic method for accurate and robust thalamus segmentation in T1w-MRI for widespread clinical use without the need for strict harmonization of acquisition protocols and/or scanner-specific normal databases. METHODS: A three-dimensional convolutional neural network (3D-CNN) was trained on 1975 T1w volumes from 170 MRI scanners using thalamus masks generated with FSL-FIRST as ground truth. Accuracy was evaluated with 18 manually labeled expert masks. Intra- and inter-scanner test-retest stability were assessed with 477 T1w volumes of a single healthy subject scanned on 123 MRI scanners. The sensitivity of 3D-CNN-based volume estimates for the detection of thalamus atrophy was tested with 127 multiple sclerosis (MS) patients and a normal database comprising 4872 T1w volumes from 160 scanners. The 3D-CNN was compared with a publicly available 2D-CNN (FastSurfer) and FSL. RESULTS: The Dice similarity coefficient of the automatic thalamus segmentation with manual expert delineation was similar for all tested methods (3D-CNN and FastSurfer 0.86 ± 0.02, FSL 0.87 ± 0.02). The standard deviation of the single healthy subject's thalamus volume estimates was lowest with 3D-CNN for repeat scans on the same MRI scanner (0.08 mL, FastSurfer 0.09 mL, FSL 0.15 mL) and for repeat scans on different scanners (0.28 mL, FastSurfer 0.62 mL, FSL 0.63 mL). The proportion of MS patients with significantly reduced thalamus volume was highest for 3D-CNN (24%, FastSurfer 16%, FSL 11%). CONCLUSION: The novel 3D-CNN allows accurate thalamus segmentation, similar to state-of-the-art methods, with considerably improved robustness with respect to scanner-related variability of image characteristics. This might result in higher sensitivity for the detection of disease-related thalamus atrophy. KEY POINTS: • A three-dimensional convolutional neural network was trained for automatic segmentation of the thalamus with a heterogeneous sample of T1w-MRI from 1975 patients scanned on 170 different scanners. • The network provided high accuracy for thalamus segmentation with manual segmentation by experts as ground truth. • Inter-scanner variability of thalamus volume estimates across different MRI scanners was reduced by more than 50%, resulting in increased sensitivity for the detection of thalamus atrophy.

Infratentorial lesions in multiple sclerosis patients: intra- and inter-rater variability in comparison to a fully automated segmentation using 3D convolutional neural networks.

OBJECTIVE: Automated quantification of infratentorial multiple sclerosis lesions on magnetic resonance imaging is clinically relevant but challenging. To overcome some of these problems, we propose a fully automated lesion segmentation algorithm using 3D convolutional neural networks (CNNs). METHODS: The CNN was trained on a FLAIR image alone or on FLAIR and T1-weighted images from 1809 patients acquired on 156 different scanners. An additional training using an extra class for infratentorial lesions was implemented. Three experienced raters manually annotated three datasets from 123 MS patients from different scanners. RESULTS: The inter-rater sensitivity (SEN) was 80% for supratentorial lesions but only 62% for infratentorial lesions. There was no statistically significant difference between the inter-rater SEN and the SEN of the CNN with respect to the raters. For supratentorial lesions, the CNN featured an intra-rater intra-scanner SEN of 0.97 (R1 = 0.90, R2 = 0.84) and for infratentorial lesion a SEN of 0.93 (R1 = 0.61, R2 = 0.73). CONCLUSION: The performance of the CNN improved significantly for infratentorial lesions when specifically trained on infratentorial lesions using a T1 image as an additional input and matches the detection performance of experienced raters. Furthermore, for infratentorial lesions the CNN was more robust against repeated scans than experienced raters. KEY POINTS: • A 3D convolutional neural network was trained on MRI data from 1809 patients (156 different scanners) for the quantification of supratentorial and infratentorial multiple sclerosis lesions. • Inter-rater variability was higher for infratentorial lesions than for supratentorial lesions. The performance of the 3D convolutional neural network (CNN) improved significantly for infratentorial lesions when specifically trained on infratentorial lesions using a T1 image as an additional input. • The detection performance of the CNN matches the detection performance of experienced raters.

Single-subject analysis of regional brain volumetric measures can be strongly influenced by the method for head size adjustment.

PURPOSE: Total intracranial volume (TIV) is often a nuisance covariate in MRI-based brain volumetry. This study compared two TIV adjustment methods with respect to their impact on z-scores in single subject analyses of regional brain volume estimates. METHODS: Brain parenchyma, hippocampus, thalamus, and TIV were segmented in a normal database comprising 5059 T1w images. Regional volume estimates were adjusted for TIV using the residual method or the proportion method. Age was taken into account by regression with both methods. TIV- and age-adjusted regional volumes were transformed to z-scores and then compared between the two adjustment methods. Their impact on the detection of thalamus atrophy was tested in 127 patients with multiple sclerosis. RESULTS: The residual method removed the association with TIV in all regions. The proportion method resulted in a switch of the direction without relevant change of the strength of the association. The reduction of physiological between-subject variability was larger with the residual method than with the proportion method. The difference between z-scores obtained with the residual method versus the proportion method was strongly correlated with TIV. It was larger than one z-score point in 5% of the subjects. The area under the ROC curve of the TIV- and age-adjusted thalamus volume for identification of multiple sclerosis patients was larger with the residual method than with the proportion method (0.84 versus 0.79). CONCLUSION: The residual method should be preferred for TIV and age adjustments of T1w-MRI-based brain volume estimates in single subject analyses.

Individual odor hedonic perception is coded in temporal joint network activity.

INTRO: The human sense of smell is highly individual and characterized by a strong variability in the perception and evaluation of olfactory stimuli, depending on cultural imprint and current physiological conditions. Since this individual perspective has often been neglected in fMRI studies on olfactory hedonic coding, this study focuses on the neuronal activity and connectivity patterns resulting from subject-specific olfactory stimulation. METHODS: Thirty-one normosmic participants took part in a fMRI block designed paradigm consisting of three olfactory stimulation sessions. The most pleasant and unpleasant odors were individually specified during a pre-test for each participant and validated in the main experiment. Mean activation and functional connectivity analysis focusing on the right and left piriform cortex were performed for the predefined olfactory regions-of-interest (ROIs) and compared between the three olfactory conditions. RESULTS: Individual unpleasant olfactory stimulation as compared to pleasant or neutral did not alter mean BOLD activation in the predefined olfactory ROIs but led to a change in connectivity pattern in the right piriform cortex. CONCLUSION: Our data suggests that the individual pleasantness of odors is not detectable by average BOLD magnitude changes in primary or secondary olfactory brain areas, but reflected in temporal patterns of joint activation that create a network between the right piriform cortex, the left insular cortex, the orbitofrontal cortex, and the precentral gyrus. This network may serve the evolutionary defense mechanism of olfaction by preparing goal-directed action.

Aberrancies of Brain Network Structures in Patients with Anosmia.

Patients with anosmia exhibit structural and functional brain abnormalities. The present study explored changes in brain white matter (WM) in non-neurodegenerative anosmia using diffusion-tensor-based network analysis. Twenty patients with anosmia and sixteen healthy controls were recruited in the cross-sectional, case-control study. Participants underwent olfactory tests (orthonasal and retronasal), neuropsychological assessment (cognitive function and depressive symptoms) and diffusion tensor imaging measurement. Tract-Based Spatial Statistics, graph theoretical analysis and Network-Based Statistics were used to explore the white matter. There was no significant difference in fractional anisotropy (FA) between patients and controls. In global network topological properties comparisons, patients exhibited higher γ and λ levels than controls, and both groups satisfied the criteria of small-world (σ > 1). In local network topological properties, patients had reduced betweenness, degree and efficiency (global and local), as well as increased shortest path length and cluster coefficient in olfactory-related brain areas (anterior cingulum, lenticular nucleus, putamen, hippocampus, amygdala, caudate nucleus, orbito-frontal gyrus). Olfactory threshold scores and the retronasal score were negatively correlated with γ and λ, and the retronasal score was positively correlated with FA values in certain WM tracts, i.e. middle cerebellar peduncle, right inferior cerebellar peduncle, left inferior cerebellar peduncle, right cerebral peduncle, left cerebral peduncle, left cingulum (cingulate gyrus), right cingulum (hippocampus), superior fronto-occipital fasciculus, and, left tapetum. Patients with anosmia demonstrated relevant WM network dysfunction though their structural integrity remained intact. Their retronasal olfaction deficits revealed to be more strongly associated with WM alterations compared with orthonasal olfactory scores.

Parcellation of the Subthalamic Nucleus in Parkinson's Disease: A Retrospective Analysis of Atlas- and Diffusion-Based Methods.

BACKGROUND: Deep brain stimulation (DBS) is an established method of treatment for Parkinson's disease (PD). A stimulation sweet spot at the interface between the motor and associative clusters of the subthalamic nucleus (STN) has recently been postulated. The aim of this study was to analyze the available clustering methods for the STN and their correlation to outcome. METHODS: This is a retrospective analysis of a group of 20 patients implanted with a DBS device for PD. Atlas-based and diffusion tractography-based parcellation of the STN was performed. The distances of the electrode to the obtained clusters were compared to each other and to outcome parameters, which included levodopa equivalent dose (LED) reduction, Unified Parkinson's Disease Rating Scale (UPDRS)-III scores, and reduction in scores for items 32 and 36 of the UPDRS-IV. RESULTS: The implanted electrodes were located nearest to the motor clusters of the STN. The following significant associations with postoperative LED reduction were found: (1) distance of the electrode to the motor cluster in the Accolla and DISTAL atlases (p < 0.01) and (2) distance of the electrode to the supplementary motor area cluster (p = 0.02). There was no association with either the UPDRS-III or the UPDRS-IV score. CONCLUSIONS: The results of this study suggest the possibility that atlas-based clustering, as well as diffusion tractography-based parcellation, can be useful in estimating the stimulation target ("sweet spot") for STN-DBS in PD patients. Atlas-based as well as diffusion-based clustering might become a useful tool in DBS trajectory planning.

Somatosensory functional MRI tractography for individualized targeting of deep brain stimulation in patients with chronic pain after brachial plexus injury.

BACKGROUND: The optimal targets for deep brain stimulation (DBS) in patients with refractory chronic pain are not clearly defined. We applied sensory functional MRI (fMRI)- and diffusion tensor imaging (DTI)-based DBS in chronic pain patients into 3 different targets to ascertain the most beneficial individual stimulation site. METHODS: Three patients with incapacitating chronic pain underwent DBS into 3 targets (periventricular gray (PVG), ventroposterolateral thalamus (VPL), and posterior limb of the internal capsule according to fMRI and DTI (PLIC). The electrodes were externalized and double-blinded tested for several days. Finally, the two electrodes with the best pain reduction were kept for permanent stimulation. The patients were then followed up for 12 months. Outcome measures comprised the numerical rating scale (NRS), short-form McGill's score (SF-MPQ), and health-related quality of life (SF-36). RESULTS: Continuous pain (mean NRS 6.6) was reduced to NRS 3.6 after 12 months. Only with stimulation of the PLIC pain attacks, that occurred at least 3 times a week (mean NRS 9.6) resolved in 2 patients and improved in one patient concerning both intensity (NRS 5) and frequency (twice a month). The mean SF-MPQ decreased from 92.7 to 50. The health-related quality of life improved considerably. CONCLUSION: fMRI- and DTI-based DBS to the PLIC was the only target with a significant effect on pain attacks and seems to be the most promising target in chronic pain patients after brachial plexus injury. The combination with PVG or VPL can further improve patients' outcome especially in terms of reducing the continuous pain.

Enhancing tumor apparent diffusion coefficient histogram skewness stratifies the postoperative survival in recurrent glioblastoma multiforme patients undergoing salvage surgery.

Objective To determine the value of apparent diffusion coefficient (ADC) histogram parameters for the prediction of individual survival in patients undergoing surgery for recurrent glioblastoma (GBM) in a retrospective cohort study. Methods Thirty-one patients who underwent surgery for first recurrence of a known GBM between 2008 and 2012 were included. The following parameters were collected: age, sex, enhancing tumor size, mean ADC, median ADC, ADC skewness, ADC kurtosis and fifth percentile of the ADC histogram, initial progression free survival (PFS), extent of second resection and further adjuvant treatment. The association of these parameters with survival and PFS after second surgery was analyzed using log-rank test and Cox regression. Results Using log-rank test, ADC histogram skewness of the enhancing tumor was significantly associated with both survival (p = 0.001) and PFS after second surgery (p = 0.005). Further parameters associated with prolonged survival after second surgery were: gross total resection at second surgery (p = 0.026), tumor size (0.040) and third surgery (p = 0.003). In the multivariate Cox analysis, ADC histogram skewness was shown to be an independent prognostic factor for survival after second surgery. Conclusion ADC histogram skewness of the enhancing lesion, enhancing lesion size, third surgery, as well as gross total resection have been shown to be associated with survival following the second surgery. ADC histogram skewness was an independent prognostic factor for survival in the multivariate analysis.

Multi-parametric ultrasound criteria for internal carotid artery disease-comparison with CT angiography.

INTRODUCTION: The German Society of Ultrasound in Medicine (known by its acronym DEGUM) recently proposed a novel multi-parametric ultrasound approach for comprehensive and accurate assessment of extracranial internal carotid artery (ICA) steno-occlusive disease. We determined the agreement between duplex ultrasonography (DUS) interpreted by the DEGUM criteria and CT angiography (CTA) for grading of extracranial ICA steno-occlusive disease. METHODS: Consecutive patients with acute cerebral ischemia underwent DUS and CTA. Internal carotid artery stenosis was graded according to the DEGUM-recommended criteria for DUS. Independent readers manually performed North American Symptomatic Carotid Endarterectomy Trial-type measurements on axial CTA source images. Both modalities were compared using Spearman's correlation and Bland-Altman analyses. RESULTS: A total of 303 acute cerebral ischemia patients (mean age, 72 ± 12 years; 58 % men; median baseline National Institutes of Health Stroke Scale score, 4 [interquartile range 7]) provided 593 DUS and CTA vessel pairs for comparison. There was a positive correlation between DUS and CTA (r s = 0.783, p < 0.001) with mean difference in degree of stenosis measurement of 3.57 %. Bland-Altman analysis further revealed widely varying differences (95 % limits of agreement -29.26 to 22.84) between the two modalities. CONCLUSION: Although the novel DEGUM criteria showed overall good agreement between DUS and CTA across all stenosis ranges, potential for wide incongruence with CTA underscores the need for local laboratory validation to avoid false screening results.

Deficient MWF mapping in multiple sclerosis using 3D whole-brain multi-component relaxation MRI.

Recent multiple sclerosis (MS) MRI research has highlighted the need to move beyond the lesion-centric view and to develop and validate new MR imaging strategies that quantify the invisible burden of disease in the brain and establish much more sensitive and specific surrogate markers of clinical disability. One of the most promising of such measures is myelin-selective MRI that allows the acquisition of myelin water fraction (MWF) maps, a parameter that is correlated to brain white matter (WM) myelination. The aim of our study was to apply the newest myelin-selective MRI method, multi-component Driven Equilibrium Single Pulse Observation of T1 and T2 (mcDESPOT) in a controlled clinical MS pilot trial. This study was designed to assess the capabilities of this new method to explain differences in disease course and degree of disability in subjects spanning a broad spectrum of MS disease severity. The whole-brain isotropically-resolved 3D acquisition capability of mcDESPOT allowed for the first time the registration of 3D MWF maps to standard space, and consequently a formalized voxel-based analysis of the data. This approach combined with image segmentation further allowed the derivation of new measures of MWF deficiency: total deficient MWF volume (DV) in WM, in WM lesions, in diffusely abnormal white matter and in normal appearing white matter (NAWM). Deficient MWF volume fraction (DVF) was derived from each of these by dividing by the corresponding region volume. Our results confirm that lesion burden does not correlate well with clinical disease activity measured with the extended disability status scale (EDSS) in MS patients. In contrast, our measurements of DVF in NAWM correlated significantly with the EDSS score (R2=0.37; p<0.001). The same quantity discriminated clinically isolated syndrome patients from a normal control population (p<0.001) and discriminated relapsing-remitting from secondary-progressive patients (p<0.05); hence this new technique may sense early disease-related myelin loss and transitions to progressive disease. Multivariate analysis revealed that global atrophy, mean whole-brain myelin water fraction and white matter atrophy were the three most important image-derived parameters for predicting clinical disability (EDSS). Overall, our results demonstrate that mcDESPOT-defined measurements in NAWM show great promise as imaging markers of global clinical disease activity in MS. Further investigation will determine if this measure can serve as a risk factor for the conversion into definite MS and for the secondary transition into irreversible disease progression.

Exploring in vivo lesion myelination dynamics: Longitudinal Myelin Water Imaging in early Multiple Sclerosis.

BACKGROUND: Multiple Sclerosis (MS) lesions are pathologically heterogeneous and the temporal behavior in terms of growth and myelination status of individual lesions is highly variable, especially in the early phase of the disease. Thus, monitoring the development of individual lesion myelination by using quantitative magnetic resonance myelin water imaging (MWI) could be valuable to capture the variability of disease pathology and get an individual insight into the subclinical disease activity. OBJECTIVE: The goal of this work was (1) to observe the variation and longitudinal change of in vivo lesion myelination by means of MWI and its parameter Myelin Water Fraction (MWF), and, (2) to identify individual lesion myelination patterns in early MS. METHODS: In this study n = 12 patients obtained conventional MRI and quantitative MWI derived from multi-component driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) within four weeks after presenting a clinically isolated syndrome and remained within the study if clinically definitive MS was diagnosed within the 12 months study period. Four MRI sessions were acquired at baseline, 3, 6, and 12 months. The short-term and long-term variability of MWF maps was evaluated by scan-rescan measures and the coefficient of variation was determined in four healthy controls. Tracking of individual lesions was performed using the Automatic Follow-up of Individual Lesions (AFIL) algorithm. Lesion volume and MWF were evaluated for every individual lesion in all patients. Median lesion MWF change was used to define lesion categories as decreasing, varying, increasing and invariant for MWF variation. RESULTS: In total n = 386 T2 lesions were detected with a subset of n = 225 permanent lesions present at all four time-points. Among those, a heterogeneous lesion MWF reduction was found, with the majority of lesions bearing only mild MWF reduction, approximately a third with an intermediate MWF decrease and highest MWF reduction in acute-inflammatory active lesions. A moderate negative correlation was determined between individual lesion volumes and median MWF consistent across all time-points. Permanent lesions featured variable temporal dynamics with the majority of varying MWF (58 %), however decreasing (16 %), increasing (15 %) and invariant (11 %) subgroups could be identified resembling demyelinating activity and post-demyelinating inactivity known from histopathology studies. Inflammatory-active enhancing lesions showed a distinct pattern of MWF reduction followed by partial recovery after 3 months. This was similar in new enhancing lesions and those with a non-enhancing precursor lesion. CONCLUSION: This work provides in vivo evidence for an individual evolution of early demyelinated MS lesions measured by means of MWF imaging. Our results support the hypothesis, that MS lesions undergo multiple demyelination and remyelination episodes in the early acute phase. The in vivo MRI surrogate of myelin turnover bears capacity as a novel biomarker to select and potentially monitor personalized MS treatment.

Acquired olfactory loss alters functional connectivity and morphology.

Removing function from a developed and functional sensory system is known to alter both cerebral morphology and functional connections. To date, a majority of studies assessing sensory-dependent plasticity have focused on effects from either early onset or long-term sensory loss and little is known how the recent sensory loss affects the human brain. With the aim of determining how recent sensory loss affects cerebral morphology and functional connectivity, we assessed differences between individuals with acquired olfactory loss (duration 7-36 months) and matched healthy controls in their grey matter volume, using multivariate pattern analyses, and functional connectivity, using dynamic connectivity analyses, within and from the olfactory cortex. Our results demonstrate that acquired olfactory loss is associated with altered grey matter volume in, among others, posterior piriform cortex, a core olfactory processing area, as well as the inferior frontal gyrus and angular gyrus. In addition, compared to controls, individuals with acquired anosmia displayed significantly stronger dynamic functional connectivity from the posterior piriform cortex to, among others, the angular gyrus, a known multisensory integration area. When assessing differences in dynamic functional connectivity from the angular gyrus, individuals with acquired anosmia had stronger connectivity from the angular gyrus to areas primary responsible for basic visual processing. These results demonstrate that recently acquired sensory loss is associated with both changed cerebral morphology within core olfactory areas and increase dynamic functional connectivity from olfactory cortex to cerebral areas processing multisensory integration.

Video-Oculography-Assisted Head Impulse Test and Caloric Testing for Detecting Stroke in Acute Vertigo Patients via Modified HINTS Plus.

BACKGROUND: We assessed whether detection of stroke underlying acute vertigo using HINTS plus (head-impulse test, nystagmus type, test of skew, hearing loss) can be improved by video-oculography for automated head-impulse test (V-HIT) analysis. METHODS: We evaluated patients with acute vestibular syndrome (AVS) presenting to the emergency room using HINTS plus and V-HIT-assisted HINTS plus in a randomized sequence followed by cranial MRI and caloric testing. Image-confirmed posterior circulation stroke or vertebrobasilar TIA were the reference standards to calculate diagnostic accuracy. We repeated statistical analysis for a third protocol that was composed post hoc by replacing the head-impulse test with caloric testing in the HINTS plus protocol. RESULTS: We included 30 AVS patients (ages 55.4 ± 17.2 years, 14 females). Of these, 11 (36.7%) had posterior circulation stroke (n = 4) or TIA (n = 7). Acute V-HIT-assisted HINTS plus was feasible and displayed tendentially higher accuracy than conventional HINTS plus (sensitivity: 81.8%, 95% CI 48.2-97.7%; specificity 31.6%, 95% CI 12.6-56.6% vs. sensitivity 72.7%, 95% CI 39.0-94.0%; specificity 36.8%, 95% CI 16.3-61.6%). The new caloric-supported algorithm showed high accuracy (sensitivity 100%, 95% CI 66.4-100%; specificity 66.7%, 95% CI 41-86.7%). CONCLUSIONS: Our study provides pilot data on V-HIT-assisted HINTS plus for acute AVS assessment and indicates the diagnostic value of integrated acute caloric testing.

CT Angiography Manual Multiplanar Vessel Diameter Measurement vs. Semiautomated Perpendicular Area Minimal Caliber Computation of Internal Carotid Artery Stenosis.

Objective: To determine the diagnostic agreement of CT angiography (CTA) manual multiplanar reformatting (MPR) stenosis diameter measurement and semiautomated perpendicular stenosis area minimal caliber computation of extracranial internal carotid artery (ICA) stenosis. Methods: We analyzed acute cerebral ischemia CTA at our tertiary stroke center in a 12-month period. Prospective NASCET-type stenosis grading for each ICA was independently performed using (1) MPR to manually determine diameters and (2) perpendicular stenosis area with minimal caliber semiautomated computation to grade luminal constriction. Corresponding to clinically relevant NASCET strata, results were grouped into severity ranges: normal, 1-49%, 50-69%, and 70-99%, and occlusion. Results: We included 647 ICA pairs from 330 patients (median age of 74 [66-80, IQR]; 38-92 years; 58% men; median NIHSS 4 [1-9, IQR]). MPR diameter and semiautomated caliber measurements resulted in stenosis grades of 0-49% in 143 vs. 93, 50-69% in 29 vs. 27, 70-99% in 6 vs. 14, and occlusion in 34 vs. 34 ICAs (p = 0.003), respectively. We found excellent reliability between repeated manual CTA assessments of one expert reader (ICC = 0.997; 95% CI, 0.993-0.999) and assessments of two expert readers (ICC = 0.972; 95% CI, 0.936-0.988). For the semiautomated vessel analysis software, both intrarater reliability and interrater reliability were similarly strong (ICC = 0.981; 95% CI, 0.952-0.992 and ICC = 0.745; 95% CI, 0.486-0.883, respectively). However, Bland-Altman analysis revealed a mean difference of 1.6% between the methods within disease range with wide 95% limits of agreement (-16.7-19.8%). This interval even increased with exclusively considered vessel pairs of stenosis ≥1% (mean 5.3%; -24.1-34.7%) or symptomatic stenosis ≥50% (mean 0.1%; -25.7-26.0%). Conclusion: Our findings suggest that MPR-based diameter measurement and the semiautomated perpendicular area minimal caliber computation methods cannot be used interchangeably for the quantification of ICA steno-occlusive disease.

Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers.

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/ . The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.

Clinical field-strength MRI of amyloid plaques induced by low-level cholesterol feeding in rabbits.

Two significant barriers have limited the development of effective treatment of Alzheimer's disease. First, for many cases the aetiology is unknown and likely multi-factorial. Among these factors, hypercholesterolemia is a known risk predictor and has been linked to the formation of beta-amyloid plaques, a pathological hallmark this disease. Second, standardized diagnostic tools are unable to definitively diagnose this disease prior to death; hence new diagnostic tools are urgently needed. Magnetic resonance imaging (MRI) using high field-strength scanners has shown promise for direct visualization of beta-amyloid plaques, allowing in vivo longitudinal tracking of disease progression in mouse models. Here, we present a new rabbit model for studying the relationship between cholesterol and Alzheimer's disease development and new tools for direct visualization of beta-amyloid plaques using clinical field-strength MRI. New Zealand white rabbits were fed either a low-level (0.125-0.25% w/w) cholesterol diet (n = 5) or normal chow (n = 4) for 27 months. High-resolution (66 x 66 x 100 microm(3); scan time = 96 min) ex vivo MRI of brains was performed using a 3-Tesla (T) MR scanner interfaced with customized gradient and radiofrequency coils. Beta-amyloid-42 immunostaining and Prussian blue iron staining were performed on brain sections and MR and histological images were manually registered. MRI revealed distinct signal voids throughout the brains of cholesterol-fed rabbits, whereas minimal voids were seen in control rabbit brains. These voids corresponded directly to small clusters of extracellular beta-amyloid-positive plaques, which were consistently identified as iron-loaded (the presumed source of MR contrast). Plaques were typically located in the hippocampus, parahippocampal gyrus, striatum, hypothalamus and thalamus. Quantitative analysis of the number of histologically positive beta-amyloid plaques (P < 0.0001) and MR-positive signal voids (P < 0.05) found in cholesterol-fed and control rabbit brains corroborated our qualitative observations. In conclusion, long-term, low-level cholesterol feeding was sufficient to promote the formation of extracellular beta-amyloid plaque formation in rabbits, supporting the integral role of cholesterol in the aetiology of Alzheimer's disease. We also present the first evidence that MRI is capable of detecting iron-associated beta-amyloid plaques in a rabbit model of Alzheimer's disease and have advanced the sensitivity of MRI for plaque detection to a new level, allowing clinical field-strength scanners to be employed. We believe extension of these technologies to an in vivo setting in rabbits is feasible and that our results support future work exploring the role of MRI as a leading imaging tool for this debilitating and life-threatening disease.

Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNs.

Multiple sclerosis is an inflammatory autoimmune demyelinating disease that is characterized by lesions in the central nervous system. Typically, magnetic resonance imaging (MRI) is used for tracking disease progression. Automatic image processing methods can be used to segment lesions and derive quantitative lesion parameters. So far, methods have focused on lesion segmentation for individual MRI scans. However, for monitoring disease progression, lesion activity in terms of new and enlarging lesions between two time points is a crucial biomarker. For this problem, several classic methods have been proposed, e.g., using difference volumes. Despite their success for single-volume lesion segmentation, deep learning approaches are still rare for lesion activity segmentation. In this work, convolutional neural networks (CNNs) are studied for lesion activity segmentation from two time points. For this task, CNNs are designed and evaluated that combine the information from two points in different ways. In particular, two-path architectures with attention-guided interactions are proposed that enable effective information exchange between the two time point's processing paths. It is demonstrated that deep learning-based methods outperform classic approaches and it is shown that attention-guided interactions significantly improve performance. Furthermore, the attention modules produce plausible attention maps that have a masking effect that suppresses old, irrelevant lesions. A lesion-wise false positive rate of 26.4% is achieved at a true positive rate of 74.2%, which is not significantly different from the interrater performance.