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Generating big-data is becoming imperative with the advent of machine learning. RIN-Neuroimaging Network addresses this need by developing harmonized protocols for multisite studies to identify quantitative MRI (qMRI) biomarkers for neurological diseases. In this context, image quality control (QC) is essential. Here, we present methods and results of how the RIN performs intra- and inter-site reproducibility of geometrical and image contrast parameters, demonstrating the relevance of such QC practice.American College of Radiology (ACR) large and small phantoms were selected. Eighteen sites were equipped with a 3T scanner that differed by vendor, hardware/software versions, and receiver coils. The standard ACR protocol was optimized (in-plane voxel, post-processing filters, receiver bandwidth) and repeated monthly. Uniformity, ghosting, geometric accuracy, ellipse's ratio, slice thickness, and high-contrast detectability tests were performed using an automatic QC script.Measures were mostly within the ACR tolerance ranges for both T1- and T2-weighted acquisitions, for all scanners, regardless of vendor, coil, and signal transmission chain type. All measurements showed good reproducibility over time. Uniformity and slice thickness failed at some sites. Scanners that upgraded the signal transmission chain showed a decrease in geometric distortion along the slice encoding direction. Inter-vendor differences were observed in uniformity and geometric measurements along the slice encoding direction (i.e. ellipse's ratio).Use of the ACR phantoms highlighted issues that triggered interventions to correct performance at some sites and to improve the longitudinal stability of the scanners. This is relevant for establishing precision levels for future multisite studies of qMRI biomarkers.

BACKGROUND: Hemispatial neglect is a complex syndrome associated with a reduced capability to orient attentional resources toward the contralateral side of space, that involves a collection of symptoms [1]. We used three functional magnetic resonance imaging (fMRI) tasks (i.e., visual search, VS; line bisection, LB; extinction, EX), performed by 25 healthy subjects, to investigate the behavioral and neural correlates under these symptoms. MATERIALS AND METHODS: During fMRI, participants were presented with: 1) VS: an array containing 8-12 stimuli such as O-like (target) and Q-like (distractors) shapes projected on both sides; 2) LB: a bisected line covering 18° of visual angle; 3) EX: a black square (target) of 2x2° that equiprobably appeared on either the left, right or both hemifields. Participants pressed one of three response buttons to indicate: left, right and bilateral (i.e., for EX) or central (i.e., for LB). RESULTS: fMRI data showed an increased activation in the right angular gyrus comparing bilateral vs. unilateral stimulus in EX, and a bilateral occipital activation comparing high vs. low load stimulus in VS, highlighting that in both cases subjects make an effort performing the task. These results are confirmed behaviourally, in fact subjects are less accurate when they are presented with bilateral (97,8% vs. 99,5% in unilateral) and high load (88,9% vs. 93,1% low load) stimulus. There are no significant activations regarding LB task. CONCLUSIONS: We found that in healthy conditions the right attentional network is involved in processing simultaneous stimuli and bilateral visual cortex is involved in processing the high load of stimuli. Our findings provide a prior knowledge that can be used to compare with attentional mechanisms in neglect patients performing the same tasks. This will allow us to cluster at least three neglect symptoms, in terms of brain activations raised from compensation mechanisms, due to brain impairments. [This work was funded by a grant from the Italian Ministry of Health (GR-2013-02358098) awarded to B. Spano'].

Background: The importance of predicting disease progression in multiple sclerosis (MS) has increasingly been recognised, hence reliable biomarkers are needed. \ud Objectives: To investigate the prognostic role of cerebrospinal fluid (CSF) Amyloid beta1-42 (A) levels by the determination of a cut-off value to classify patients in slow and fast progressors. To evaluate possible association with white (WM) and grey matter (GM) damage at early disease stages. \ud Methods: Sixty patients were recruited and followed-up for three to five years. Patients underwent clinical assessment, CSF analysis to determine Aβ levels, and brain MRI (at baseline and after 1 year). T1-weighted volumes were calculated. T2-weighted scans were used to quantify WM lesion loads. \ud Results: Lower CSF Aβ levels were observed in patients with a worse follow-up EDSS (r=−0.65, p0.05).\ud Conclusions: Low CSF Aβ levels may represent a predictive biomarker of disease progression in MS.

\ud Background: \ud Amnestic mild cognitive impairment (MCI) is a transitional stage between normal aging and Alzheimer’s disease (AD). However, the clinical conversion from MCI to AD is unpredictable. Hence, identification of non-invasive biomarkers able to detect early changes induced by dementia is a pressing need.\ud \ud Purpose: \ud To explore the added value of histogram analysis applied to measures derived from diffusion tensor imaging (DTI) for detecting brain tissue differences between AD, MCI and healthy subjects (HS).\ud \ud Study type: \ud Retrospective.\ud \ud Population/subjects: \ud Local cohort (57 AD, 28 MCI, 23 HS), Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort (41 AD, 58 MCI, 41 HS).\ud \ud Field Strength: \ud 3T. Dual echo TSE; FLAIR; MDEFT; IR-SPGR; DTI.\ud \ud Assessment: \ud Normal appearing white matter (NAWM) masks were obtained using the T1-weighted volumes for tissue segmentation and T2-weighted images for removal of hyperintensities/lesions. From DTI images, fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AXD) and radial diffusivity (RD) were obtained. NAWM histograms of FA, MD, AXD and RD were derived and characterized estimating: peak height, peak location, mean value (MV), and quartiles (C25, C50, C75), which were compared between groups. Receiver operating characteristic (ROC) and area under ROC curves (AUC) were\ud calculated. To confirm our results, the same analysis was repeated on ADNI dataset.\ud \ud Statistical tests: \ud One-way ANOVA, post-hoc Student’s t-test, multi-class ROC analysis.\ud \ud Results: \ud For the local cohort, C25 of AXD had the maximum capability of group discrimination with AUC of 0.80 for “HS vs patients” comparison and 0.74 for “AD vs others” comparison. For ADNI cohort, MV of AXD revealed the maximum group discrimination capability with AUC of 0.75 for “HS vs patients” comparison and 0.75 for “AD vs others” comparison.\ud \ud Data conclusion: \ud AXD of NAWM might be an early marker of microstructural brain tissue changes occurring during AD course and might be useful for assessing disease progression.