Author name cluster

Albert Saiz

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

5 papers

1 author row

YNICL Journal 2021 Journal Article

Cortical fractal dimension predicts disability worsening in Multiple Sclerosis patients

Eloy Roura
Grégory Maclair
Magí Andorrà
Ferran Juanals
Irene Pulido-Valdeolivas
Albert Saiz
Yolanda Blanco
Maria Sepulveda

BACKGROUND: Fractal geometry measures the morphology of the brain and detects CNS damage. We aimed to assess the longitudinal changes on brain's fractal geometry and its predictive value for disease worsening in patients with Multiple Sclerosis (MS). METHODS: We prospectively analyzed 146 consecutive patients with relapsing-remitting MS with up to 5 years of clinical and brain MRI (3 T) assessments. The fractal dimension and lacunarity were calculated for brain regions using box-counting methods. Longitudinal changes were analyzed in mixed-effect models and the risk of disability accumulation were assessed using Cox Proportional Hazard regression analysis. RESULTS: There was a significant decrease in the fractal dimension and increases of lacunarity in different brain regions over the 5-year follow-up. Lower cortical fractal dimension increased the risk of disability accumulation for the Expanded Disability Status Scale [HR 0.9734, CI 0.8420-0.9125; Harrell C 0.59; Wald p 0.038], 9-hole peg test [HR 0.9734, CI 0.8420-0.9125; Harrell C 0.59; Wald p 0.0083], 2.5% low contrast vision [HR 0.4311, CI 0.2035-0.9133; Harrell C 0.58; Wald p 0.0403], symbol digit modality test [HR 2.215, CI 1.043-4.705; Harrell C 0.65; Wald p 0.0384] and MS Functional Composite-4 [HR 0.55, CI 0.317-0.955; Harrell C 0.59; Wald p 0.0029]. CONCLUSIONS: Fractal geometry analysis of brain MRI identified patients at risk of increasing their disability in the next five years.

Details DOI

YNICL Journal 2020 Journal Article

Characterization of multiple sclerosis lesions with distinct clinical correlates through quantitative diffusion MRI

Eloy Martínez-Heras
Elisabeth Solana
Ferran Prados
Magí Andorrà
Aleix Solanes
Elisabet López-Soley
Carmen Montejo
Irene Pulido-Valdeolivas

Diffusion magnetic resonance imaging can reveal quantitative information about the tissue changes in multiple sclerosis. The recently developed multi-compartment spherical mean technique can map different microscopic properties based only on local diffusion signals, and it may provide specific information on the underlying microstructural modifications that arise in multiple sclerosis. Given that the lesions in multiple sclerosis may reflect different degrees of damage, we hypothesized that quantitative diffusion maps may help characterize the severity of lesions “in vivo” and correlate these to an individual’s clinical profile. We evaluated this in a cohort of 59 multiple sclerosis patients (62% female, mean age 44. 7 years), for whom demographic and disease information was obtained, and who underwent a comprehensive physical and cognitive evaluation. The magnetic resonance imaging protocol included conventional sequences to define focal lesions, and multi-shell diffusion imaging was used with b-values of 1000, 2000 and 3000 s/mm2 in 180 encoding directions. Quantitative diffusion properties on a macro- and micro-scale were used to discriminate distinct types of lesions through a k-means clustering algorithm, and the number and volume of those lesion types were correlated with parameters of the disease. The combination of diffusion tensor imaging metrics (fractional anisotropy and radial diffusivity) and multi-compartment spherical mean technique values (microscopic fractional anisotropy and intra-neurite volume fraction) differentiated two type of lesions, with a prediction strength of 0. 931. The B-type lesions had larger diffusion changes compared to the A-type lesions, irrespective of their location (P < 0. 001). The number of A and B type lesions was similar, although in juxtacortical areas B-type lesions predominated (60%, P < 0. 001). Also, the percentage of B-type lesion volume was higher (64%, P < 0. 001), indicating that these lesions were larger. The number and volume of B-type lesions was related to the severity of disease evolution, clinical disability and cognitive decline (P = 0. 004, Bonferroni correction). Specifically, more and larger B-type lesions were correlated with a worse Multiple Sclerosis Severity Score, cerebellar function and cognitive performance. Thus, by combining several microscopic and macroscopic diffusion properties, the severity of damage within focal lesions can be characterized, further contributing to our understanding of the mechanisms that drive disease evolution. Accordingly, the classification of lesion types has the potential to permit more specific and better-targeted treatment of patients with multiple sclerosis.

Details DOI

YNICL Journal 2018 Journal Article

Magnetic resonance markers of tissue damage related to connectivity disruption in multiple sclerosis

Elisabeth Solana
Eloy Martinez-Heras
Elena H. Martinez-Lapiscina
Maria Sepulveda
Nuria Sola-Valls
Nuria Bargalló
Joan Berenguer
Yolanda Blanco

Patients with multiple sclerosis (MS) display reduced structural connectivity among brain regions, but the pathogenic mechanisms underlying network disruption are still unknown. We aimed to investigate the association between the loss of diffusion-based structural connectivity, measured with graph theory metrics, and magnetic resonance (MR) markers of microstructural damage. Moreover, we evaluated the cognitive consequences of connectivity changes. We analysed the frontoparietal network in 102 MS participants and 25 healthy volunteers (HV). MR measures included radial diffusivity (RD), as marker of demyelination, and ratios of myo-inositol, N-acetylaspartate and glutamate+glutamine with creatine in white (WM) and grey matter as markers of astrogliosis, neuroaxonal integrity and glutamatergic neurotoxicity. Patients showed decreased global and local efficiency, and increased assortativity (p < 0. 01) of the network, as well as increased RD and myo-inositol, and decreased N-acetylaspartate in WM compared with HV (p < 0. 05). In patients, the age-adjusted OR of presenting abnormal global and local efficiency was increased for each increment of 0. 01 points in RD and myo-inositol, while it was decreased for each increment of 0. 01 points in N-acetylaspartate (the increase of N-acetylaspartate reduced the risk of having abnormal connectivity), all in WM. In a multiple logistic regression analysis, the OR of presenting abnormal global efficiency was 0. 95 (95% confidence interval, CI: 0. 91–0. 99, p = 0. 011) for each 0. 01 increase in N-acetylaspartate, and the OR of presenting abnormal local efficiency was 1. 39 (95% CI: 1. 14–1. 71, p = 0. 001) for each 0. 01 increase in RD. Patients with abnormal efficiency had worse performance in attention, working memory and processing speed (p < 0. 05). In conclusion, patients with MS exhibit decreased structural network efficiency driven by diffuse microstructural impairment of the WM, probably related to demyelination, astroglial and neuroaxonal damage. The accumulation of neuroaxonal pathological burden seems to magnify the risk of global network collapse, while demyelination may contribute to the regional disorganization. These network modifications have negative consequences on cognition.

Details DOI

YNICL Journal 2017 Journal Article

Structural networks involved in attention and executive functions in multiple sclerosis

Sara Llufriu
Eloy Martinez-Heras
Elisabeth Solana
Nuria Sola-Valls
Maria Sepulveda
Yolanda Blanco
Elena H. Martinez-Lapiscina
Magi Andorra

Attention and executive deficits are disabling symptoms in multiple sclerosis (MS) that have been related to disconnection mechanisms. We aimed to investigate changes in structural connectivity in MS and their association with attention and executive performance applying an improved framework that combines high order probabilistic tractography and anatomical exclusion criteria postprocessing. We compared graph theory metrics of structural networks and fractional anisotropy (FA) of white matter (WM) connections or edges between 72 MS subjects and 38 healthy volunteers (HV) and assessed their correlation with cognition. Patients displayed decreased network transitivity, global efficiency and increased path length compared with HV (p <0. 05, corrected). Also, nodal strength was decreased in 26 of 84 gray matter regions. The distribution of nodes with stronger connections or hubs of the network was similar among groups except for the right pallidum and left insula, which became hubs in patients. MS subjects presented reduced edge FA widespread in the network, while FA was increased in 24 connections (p <0. 05, corrected). Decreased integrity of frontoparietal networks, deep gray nuclei and insula correlated with worse attention and executive performance (r between 0. 38 and 0. 55, p <0. 05, corrected). Contrarily, higher strength in the right transverse temporal cortex and increased FA of several connections (mainly from cingulate, frontal and occipital cortices) were associated with worse functioning (r between −0. 40 and −0. 47, p <0. 05 corrected). In conclusion, structural brain connectivity is disturbed in MS due to widespread impairment of WM connections and gray matter structures. The increased edge connectivity suggests the presence of reorganization mechanisms at the structural level. Importantly, attention and executive performance relates to frontoparietal networks, deep gray nuclei and insula. These results support the relevance of network integrity to maintain optimal cognitive skills.

Details DOI

YNIMG Journal 2016 Journal Article

Power estimation for non-standardized multisite studies

Anisha Keshavan
Friedemann Paul
Mona K. Beyer
Alyssa H. Zhu
Nico Papinutto
Russell T. Shinohara
William Stern
Michael Amann

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions.

Details DOI