Riemannian Geometry of Functional Connectivity Matrices for Multi-Site Attention-Deficit/Hyperactivity Disorder Data Harmonization

Riemannian geometry; Attention-deficit/hyperactivity disorder; Functional connectivityGeometria riemanniana; Trastorn per dèficit d'atenció/hiperactivitat; Connectivitat funcionalGeometría riemanniana; Trastorno por déficit de atención/hiperactividad; Conectividad funcionalThe use of multi-site datasets in neuroimaging provides neuroscientists with more statistical power to perform their analyses. However, it has been shown that the imaging-site introduces variability in the data that cannot be attributed to biological sources. In this work, we show that functional connectivity matrices derived from resting-state multi-site data contain a significant imaging-site bias. To this aim, we exploited the fact that functional connectivity matrices belong to the manifold of symmetric positive-definite (SPD) matrices, making it possible to operate on them with Riemannian geometry. We hereby propose a geometry-aware harmonization approach, Rigid Log-Euclidean Translation, that accounts for this site bias. Moreover, we adapted other Riemannian-geometric methods designed for other domain adaptation tasks and compared them to our proposal. Based on our results, Rigid Log-Euclidean Translation of multi-site functional connectivity matrices seems to be among the studied methods the most suitable in a clinical setting. This represents an advance with respect to previous functional connectivity data harmonization approaches, which do not respect the geometric constraints imposed by the underlying structure of the manifold. In particular, when applying our proposed method to data from the ADHD-200 dataset, a multi-site dataset built for the study of attention-deficit/hyperactivity disorder, we obtained results that display a remarkable correlation with established pathophysiological findings and, therefore, represent a substantial improvement when compared to the non-harmonization analysis. Thus, we present evidence supporting that harmonization should be extended to other functional neuroimaging datasets and provide a simple geometric method to address it

T1w/FLAIR ratio standardization as a myelin marker in MS patients

Image calibration; Integrity; Multiple sclerosisCalibración de imagen; Integridad; Esclerosis múltipleCalibració d'imatge; Integritat; Esclerosi múltipleIntroduction Calculation of a T1w/T2w ratio was introduced as a proxy for myelin integrity in the brain of multiple sclerosis (MS) patients. Since nowadays 3D FLAIR is commonly used for lesion detection instead of T2w images, we introduce a T1w/FLAIR ratio as an alternative for the T1w/T2w ratio. Objectives Bias and intensity variation are widely present between different scanners, between subjects and within subjects over time in T1w, T2w and FLAIR images. We present a standardized method for calculating a histogram calibrated T1w/FLAIR ratio to reduce bias and intensity variation in MR sequences from different scanners and at different time-points. Material and methods 207 Relapsing Remitting MS patients were scanned on 4 different 3 T scanners with a protocol including 3D T1w, 2D T2w and 3D FLAIR images. After bias correction, T1w/FLAIR ratio maps and T1w/T2w ratio maps were calculated in 4 different ways: without calibration, with linear histogram calibration as described by Ganzetti et al. (2014), and by using 2 methods of non-linear histogram calibration. The first nonlinear calibration uses a template of extra-cerebral tissue and cerebrospinal fluid (CSF) brought from Montreal Neurological Institute (MNI) space to subject space; for the second nonlinear method we used an extra-cerebral tissue and CSF template of our own subjects. Additionally, we segmented several brain structures such as Normal Appearing White Matter (NAWM), Normal Appearing Grey Matter (NAGM), corpus callosum, thalami and MS lesions using Freesurfer and Samseg. Results The coefficient of variation of T1w/FLAIR ratio in NAWM for the no calibrated, linear, and 2 nonlinear calibration methods were respectively 24, 19.1, 9.5, 13.8. The nonlinear methods of calibration showed the best results for calculating the T1w/FLAIR ratio with a smaller dispersion of the data and a smaller overlap of T1w/FLAIR ratio in the different segmented brain structures. T1w/T2w and T1w/FLAIR ratios showed a wider range of values compared to MTR values. Conclusions Calibration of T1w/T2w and T1w/FLAIR ratio maps is imperative to account for the sources of variation described above. The nonlinear calibration methods showed the best reduction of between-subject and within-subject variability. The T1w/T2w and T1w/FLAIR ratio seem to be more sensitive to smaller changes in tissue integrity than MTR. Future work is needed to determine the exact substrate of T1w/FLAIR ratio and to obtain correlations with clinical outcome

MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies

Harmonization; MRI; Multiple sclerosisHarmonització; Ressonància magnètica; Esclerosi múltipleArmonización; Resonancia magnética; Esclerosis múltipleThere is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources

Comparison between gadolinium-enhanced 2D T1-weighted gradient-echo and spin-echo sequences in the detection of active multiple sclerosis lesions on 3.0T MRI

Objectives To compare the sensitivity of enhancing multiple sclerosis (MS) lesions in gadolinium-enhanced 2D T1-weighted gradient-echo (GRE) and spin-echo (SE) sequences, and to assess the influence of visual conspicuity and laterality on detection of these lesions. Methods One hundred MS patients underwent 3.0T brain MRI including gadolinium-enhanced 2D T1-weighted GRE and SE sequences. The two sets of contrast-enhanced scans were evaluated in random fashion by three experienced readers. Lesion conspicuity was assessed by the image contrast ratio (CR) and contrast-to-noise ratio (CNR). The intracranial region was divided into four quadrants and the impact of lesion location on detection was assessed in each slice. Results Six hundred and seven gadolinium-enhancing MS lesions were identified. GRE images were more sensitive for lesion detection (0.828) than SE images (0.767). Lesions showed a higher CR in SE than in GRE images, whereas the CNR was higher in GRE than SE. Most misclassifications occurred in the right posterior quadrant. Conclusions The gadolinium-enhanced 2D T1-weighted GRE sequence at 3.0T MRI enables detection of enhancing MS lesions with higher sensitivity and better lesion conspicuity than 2D T1-weighted SE. Hence, we propose the use of gadolinium-enhanced GRE sequences rather than SE sequences for routine scanning of MS patients at 3.0T. Key Points • 2D SE and GRE sequences are useful for detecting active MS lesions. • Which of these sequences is more sensitive at high field remains uncertain. • GRE sequence showed better sensitivity for detecting active MS lesions than SE. • We propose GRE sequence for detecting active MS lesions at 3.0T.Postprint (author's final draft

Neuroimaging analyses from a randomized, controlled study to evaluate plasma exchange with albumin replacement in mild-to-moderate Alzheimer’s disease: additional results from the AMBAR study

Albumin; Intravenous immunoglobulin; PlasmapheresisAlbúmina; Inmunoglobulina intravenosa; PlasmaféresisAlbúmina; Immunoglobulina intravenosa; PlasmafèresiPurpose This study was designed to detect structural and functional brain changes in Alzheimer’s disease (AD) patients treated with therapeutic plasma exchange (PE) with albumin replacement, as part of the recent AMBAR phase 2b/3 clinical trial. Methods Mild-to-moderate AD patients were randomized into four arms: three arms receiving PE with albumin (one with low-dose albumin, and two with low/high doses of albumin alternated with IVIG), and a placebo (sham PE) arm. All arms underwent 6 weeks of weekly conventional PE followed by 12 months of monthly low-volume PE. Magnetic resonance imaging (MRI) volumetric analyses and regional and statistical parametric mapping (SPM) analysis on 18F-fluorodeoxyglucose positron emission tomography (18FDG-PET) were performed. Results MRI analyses (n = 198 patients) of selected subcortical structures showed fewer volume changes from baseline to final visit in the high albumin + IVIG treatment group (p < 0.05 in 3 structures vs. 4 to 9 in other groups). The high albumin + IVIG group showed no statistically significant reduction of right hippocampus. SPM 18FDG-PET analyses (n = 213 patients) showed a worsening of metabolic activity in the specific areas affected in AD (posterior cingulate, precuneus, and parieto-temporal regions). The high-albumin + IVIG treatment group showed the greatest metabolic stability over the course of the study, i.e., the smallest percent decline in metabolism (MaskAD), and least progression of defect compared to placebo. Conclusions PE with albumin replacement was associated with fewer deleterious changes in subcortical structures and less metabolic decline compared to the typical of the progression of AD. This effect was more marked in the group treated with high albumin + IVIG.The AMBAR study is sponsored by Grifols, a manufacturer of therapeutic human serum albumin and intravenous immune globulin. GC-B, IR, JC-C, DP, MBo, and OLL received direct or indirect funding from Grifols to carry out the study and the preparation of the manuscript

One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks

Automatic lesion segmentation; Convolutional neural networks; Multiple sclerosisSegmentació automàtica de les lesions ; Xarxes neuronals convolucionals; Esclerosi múltipleSegmentación automática de las lesiones ; Redes neuronales convolucionales; Esclerosis múltipleIn recent years, several convolutional neural network (CNN) methods have been proposed for the automated white matter lesion segmentation of multiple sclerosis (MS) patient images, due to their superior performance compared with those of other state-of-the-art methods. However, the accuracies of CNN methods tend to decrease significantly when evaluated on different image domains compared with those used for training, which demonstrates the lack of adaptability of CNNs to unseen imaging data. In this study, we analyzed the effect of intensity domain adaptation on our recently proposed CNN-based MS lesion segmentation method. Given a source model trained on two public MS datasets, we investigated the transferability of the CNN model when applied to other MRI scanners and protocols, evaluating the minimum number of annotated images needed from the new domain and the minimum number of layers needed to re-train to obtain comparable accuracy. Our analysis comprised MS patient data from both a clinical center and the public ISBI2015 challenge database, which permitted us to compare the domain adaptation capability of our model to that of other state-of-the-art methods. In both datasets, our results showed the effectiveness of the proposed model in adapting previously acquired knowledge to new image domains, even when a reduced number of training samples was available in the target dataset. For the ISBI2015 challenge, our one-shot domain adaptation model trained using only a single case showed a performance similar to that of other CNN methods that were fully trained using the entire available training set, yielding a comparable human expert rater performance. We believe that our experiments will encourage the MS community to incorporate its use in different clinical settings with reduced amounts of annotated data. This approach could be meaningful not only in terms of the accuracy in delineating MS lesions but also in the related reductions in time and economic costs derived from manual lesion labeling

Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study

Atrofia; IRM; Esclerosis múltipleAtròfia; IRM; Esclerosi múltipleAtrophy; MRI; Multiple SclerosisBackground and rationale Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Methods Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. Results In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. Conclusion Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings.The study was funded by the Nauta fonds through a travel grant. The MS Center Amsteram is supported by the Dutch MS Research Foundation through a program grant (current grant 18-358f). D.B. is supported by project PI18/00823 from the “Fondo de Investigación Sanitaria Carlos III”. F.B. and O.C. are supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The acquisition of data in London was funded by supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. A sincere thank you to Tom Verhoeven for his editing of the figures

Quantification of Cervical Cord Cross-Sectional Area: Which Acquisition, Vertebra Level, and Analysis Software? A Multicenter Repeatability Study on a Traveling Healthy Volunteer

Atrofia; Área transversal; Médula espinalAtròfia; Àrea transversal; Medul·la espinalAtrophy; Cross-sectional area; Spinal cordBackground: Considerable spinal cord (SC) atrophy occurs in multiple sclerosis (MS). While MRI-based techniques for SC cross-sectional area (CSA) quantification have improved over time, there is no common agreement on whether to measure at single vertebral levels or across larger regions and whether upper SC CSA can be reliably measured from brain images. Aim: To compare in a multicenter setting three CSA measurement methods in terms of repeatability at different anatomical levels. To analyze the agreement between measurements performed on the cervical cord and on brain MRI. Method: One healthy volunteer was scanned three times on the same day in six sites (three scanner vendors) using a 3T MRI protocol including sagittal 3D T1-weighted imaging of the brain (covering the upper cervical cord) and of the SC. Images were analyzed using two semiautomated methods [NeuroQLab (NQL) and the Active Surface Model (ASM)] and the fully automated Spinal Cord Toolbox (SCT) on different vertebral levels (C1–C2; C2/3) on SC and brain images and the entire cervical cord (C1–C7) on SC images only. Results: CSA estimates were significantly smaller using SCT compared to NQL and ASM (p < 0.001), regardless of the cord level. Inter-scanner repeatability was best in C1–C7: coefficients of variation for NQL, ASM, and SCT: 0.4, 0.6, and 1.0%, respectively. CSAs estimated in brain MRI were slightly lower than in SC MRI (all p ≤ 0.006 at the C1–C2 level). Despite protocol harmonization between the centers with regard to image resolution and use of high-contrast 3D T1-weighted sequences, the variability of CSA was partly scanner dependent probably due to differences in scanner geometry, coil design, and details of the MRI parameter settings. Conclusion: For CSA quantification, dedicated isotropic SC MRI should be acquired, which yielded best repeatability in the entire cervical cord. In the upper part of the cervical cord, use of brain MRI scans entailed only a minor loss of CSA repeatability compared to SC MRI. Due to systematic differences between scanners and the CSA quantification software, both should be kept constant within a study. The MRI dataset of this study is available publicly to test new analysis approaches.Parts of this work were funded by the German Federal Ministry for Education and Research, BMBF, German Competence Network Multiple Sclerosis KKNMS (Grant Nos. 01GI1601I and 01GI0914) and by grants from the UK MS Society. FP, CG, and MY were supported by the National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Center. The funding institutions did not interfere with the study design, the collection, analysis and interpretation of data, the writing of the report, or the decision to submit the article for publication

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

Databases; Imaging techniques; Spinal cord diseasesBases de datos; Tècnicas de imagen; Enfermedades de la médula espinalBases de dades; Tècniques d'imatge; Malalties de la medul·la espinalIn 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

Serum neurofilament light chain levels predict long-term disability progression in patients with progressive multiple sclerosis

© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.Objective : There is a lack of sensitive and specific biomarkers for use in progressive multiple sclerosis (MS). The study aimed to assess the potential of serum neurofilament light chain (sNfL) levels as biomarker of disability progression in patients with progressive MS. Methods: We performed a prospective observational cohort study in 51 patients with progressive MS who participated in a 2-year phase II single-centre, randomised, double-blind, placebo-controlled trial of interferon-beta. Mean (SD) follow-up duration was 13.9 (6.2) years. Levels of sNfL were measured using a single molecule array immunoassay at baseline, 1, 2 and 6 years. Univariable and multivariable analyses were carried out to evaluate associations between sNfL levels and disability progression at short term (2 years), medium term (6 years) and long term (at the time of the last follow-up). Results: A sNfL cut-off value of 10.2¿pg/mL at baseline discriminated between long-term progressors and non-progressors with a 75% sensitivity and 67% specificity (adjusted OR 7.8; 95%¿CI 1.8 to 46.4; p=0.01). Similar performance to discriminate between long-term progressors and non-progressors was observed using age/body mass index-adjusted sNfL Z-scores derived from a normative database of healthy controls. A cut-off increase of 5.1¿pg/mL in sNfL levels between baseline and 6 years also discriminated between long-term progressors and non-progressors with a 71% sensitivity and 86% specificity (adjusted OR 49.4; 95%¿CI 4.4 to 2×103; p=0.008). Conclusions: sNfL can be considered a prognostic biomarker of future long-term disability progression in patients with progressive MS. These data expand the little knowledge existing on the role of sNfL as long-term prognostic biomarker in patients with progressive MS.Postprint (author's final draft