Literature DB >> 28083844

Attention and processing speed performance in multiple sclerosis is mostly related to thalamic volume.

Alvino Bisecco1,2, Svetlana Stamenova1,3, Giuseppina Caiazzo2, Alessandro d'Ambrosio1, Rosaria Sacco1,2, Renato Docimo1, Sabrina Esposito1, Mario Cirillo2,4, Fabrizio Esposito2,5, Simona Bonavita1,2, Gioacchino Tedeschi1,2, Antonio Gallo6,7.   

Abstract

Cognitive impairment (CI), mainly involving attention and processing speed (A-PS), is a common and disabling symptom in multiple sclerosis (MS). Symbol Digit Modalities Test (SDMT) is one of the more sensitive and reliable tests to assess A-PS deficits in MS. Structural MRI correlates of A-PS in MS still need to be clarified. This study aimed to investigate, in a large group of MS patients, the relationship between regional gray matter (GM) atrophy and SDMT performance. 125 relapsing remitting MS patients and 52 healthy controls (HC) underwent a 3 T-MRI protocol including high-resolution 3D-T1 imaging. All subjects underwent a neurological evaluation and SDMT. A Voxel Based Morphometry analysis was performed to assess: 1) correlations between regional GM volume and SDMT performance in MS patients; 2) regional differences in GM volume between MS patients and HC. Thalamic, putamen and cerebellar volumes were also calculated using FIRST tool from the FMRIB Software Library. A linear regression analysis was performed to assess the contribution of each one of these structures to A-PS performance. A significant negative correlation was found between regional GM volume and SDMT score at the level of the thalamus, cerebellum, putamen, and occipital cortex in MS patients. Thalamus, cerebellum and putamen also showed significant GM atrophy in MS patients compared to HC. Thalamic atrophy is also an independent and additional contributor to A-PS deficits in MS patients. These findings support the role of thalamus as the most relevant GM structure subtending A-PS performance in MS, as measured by SDMT.

Entities:  

Keywords:  Attention; Gray matter; Magnetic resonance imaging; Multiple sclerosis; Processing speed; Thalamus

Mesh:

Year:  2018        PMID: 28083844     DOI: 10.1007/s11682-016-9667-6

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  10 in total

1.  Mapping of thalamic magnetic susceptibility in multiple sclerosis indicates decreasing iron with disease duration: A proposed mechanistic relationship between inflammation and oligodendrocyte vitality.

Authors:  Ferdinand Schweser; Ana Luiza Raffaini Duarte Martins; Jesper Hagemeier; Fuchun Lin; Jannis Hanspach; Bianca Weinstock-Guttman; Simon Hametner; Niels Bergsland; Michael G Dwyer; Robert Zivadinov
Journal:  Neuroimage       Date:  2017-10-31       Impact factor: 6.556

2.  Thalamic atrophy moderates associations among aerobic fitness, cognitive processing speed, and walking endurance in persons with multiple sclerosis.

Authors:  Brian M Sandroff; Robert W Motl; Cristina A F Román; Glenn R Wylie; John DeLuca; Gary R Cutter; Ralph H B Benedict; Michael G Dwyer; Robert Zivadinov
Journal:  J Neurol       Date:  2022-06-19       Impact factor: 6.682

Review 3.  Gray Matter Atrophy in the Cortico-Striatal-Thalamic Network and Sensorimotor Network in Relapsing-Remitting and Primary Progressive Multiple Sclerosis.

Authors:  Yuan Cao; Wei Diao; Fangfang Tian; Feifei Zhang; Laichang He; Xipeng Long; Fuqinq Zhou; Zhiyun Jia
Journal:  Neuropsychol Rev       Date:  2021-02-13       Impact factor: 7.444

4.  A network-based cognitive training induces cognitive improvements and neuroplastic changes in patients with relapsing-remitting multiple sclerosis: an exploratory case-control study.

Authors:  Riccardo Manca; Micaela Mitolo; Iain D Wilkinson; David Paling; Basil Sharrack; Annalena Venneri
Journal:  Neural Regen Res       Date:  2021-06       Impact factor: 5.135

5.  Identification of Cortical and Subcortical Correlates of Cognitive Performance in Multiple Sclerosis Using Voxel-Based Morphometry.

Authors:  Jordi A Matías-Guiu; Ana Cortés-Martínez; Paloma Montero; Vanesa Pytel; Teresa Moreno-Ramos; Manuela Jorquera; Miguel Yus; Juan Arrazola; Jorge Matías-Guiu
Journal:  Front Neurol       Date:  2018-10-29       Impact factor: 4.003

6.  MRI Markers and Functional Performance in Patients With CIS and MS: A Cross-Sectional Study.

Authors:  Ludwig Rasche; Michael Scheel; Karen Otte; Patrik Althoff; Annemieke B van Vuuren; Rene M Gieß; Joseph Kuchling; Judith Bellmann-Strobl; Klemens Ruprecht; Friedemann Paul; Alexander U Brandt; Tanja Schmitz-Hübsch
Journal:  Front Neurol       Date:  2018-08-29       Impact factor: 4.003

7.  Gray Matter Morphometry Correlates with Attentional Efficiency in Young-Adult Multiple Sclerosis.

Authors:  Sindhuja T Govindarajan; Ruiqi Pan; Lauren Krupp; Leigh Charvet; Tim Q Duong
Journal:  Brain Sci       Date:  2021-01-09

8.  Disrupted functional and structural connectivity within default mode network contribute to WMH-related cognitive impairment.

Authors:  Xin Chen; Lili Huang; Qing Ye; Dan Yang; Ruomeng Qin; Caimei Luo; Mengchun Li; Bing Zhang; Yun Xu
Journal:  Neuroimage Clin       Date:  2019-11-12       Impact factor: 4.881

9.  Voxel-based analysis of gray matter relaxation rates shows different correlation patterns for cognitive impairment and physical disability in relapsing-remitting multiple sclerosis.

Authors:  Maria Teresa Cassiano; Roberta Lanzillo; Bruno Alfano; Teresa Costabile; Marco Comerci; Anna Prinster; Marcello Moccia; Rosario Megna; Vincenzo Brescia Morra; Mario Quarantelli; Arturo Brunetti
Journal:  Neuroimage Clin       Date:  2020-01-30       Impact factor: 4.881

10.  Impact of aerobic exercise on clinical and magnetic resonance imaging biomarkers in persons with multiple sclerosis: An exploratory randomized controlled trial.

Authors:  Lina Savšek; Tamara Stergar; Vojko Strojnik; Alojz Ihan; Aleš Koren; Žiga Špiclin; Saša Šega Jazbec
Journal:  J Rehabil Med       Date:  2021-04-01       Impact factor: 2.912

  10 in total

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