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

Measuring iron deposits within focal lesions in patients presenting clinically isolated syndrome

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Measuring cervical cord atrophy in multiple sclerosis patients. A longitudinal MRI study

Postprint (author's final draft

Correlation between brain volume change and T2 relaxation time in patients with clinically isolated syndrome

Postprint (published version

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

In 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. For the ISBI2015 challenge, our one-shot domain adaptation model trained using only a single image 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

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

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

Correlación entre cambios de volumen cerebral y el tiempo de relajación T2 en pacientes con síndrome clínicamente aislado

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