Literature DB >> 27986875

Brain MRI atrophy quantification in MS: From methods to clinical application.

Maria A Rocca1, Marco Battaglini1, Ralph H B Benedict1, Nicola De Stefano1, Jeroen J G Geurts1, Roland G Henry1, Mark A Horsfield1, Mark Jenkinson1, Elisabetta Pagani1, Massimo Filippi2.   

Abstract

Patients with the main clinical phenotypes of multiple sclerosis (MS) manifest varying degrees of brain atrophy beyond that of normal aging. Assessment of atrophy helps to distinguish clinically and cognitively deteriorating patients and predicts those who will have a less-favorable clinical outcome over the long term. Atrophy can be measured from brain MRI scans, and many technological improvements have been made over the last few years. Several software tools, with differing requirements on technical ability and levels of operator intervention, are currently available and have already been applied in research or clinical trial settings. Despite this, the measurement of atrophy in routine clinical practice remains an unmet need. After a short summary of the pathologic substrates of brain atrophy in MS, this review attempts to guide the clinician towards a better understanding of the methods currently used for quantifying brain atrophy in this condition. Important physiologic factors that affect brain volume measures are also considered. Finally, the most recent research on brain atrophy in MS is summarized, including whole brain and various compartments thereof (i.e., white matter, gray matter, selected CNS structures). Current methods provide sufficient precision for cohort studies, but are not adequate for confidently assessing changes in individual patients over the scale of months or a few years.
© 2016 American Academy of Neurology.

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Year:  2016        PMID: 27986875      PMCID: PMC5272969          DOI: 10.1212/WNL.0000000000003542

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   9.910


  60 in total

1.  A voxel-based morphometry study of grey matter loss in MS patients with different clinical phenotypes.

Authors:  Antonia Ceccarelli; Maria A Rocca; Elisabetta Pagani; Bruno Colombo; Vittorio Martinelli; Giancarlo Comi; Massimo Filippi
Journal:  Neuroimage       Date:  2008-04-20       Impact factor: 6.556

2.  What drives MRI-measured cortical atrophy in multiple sclerosis?

Authors:  V Popescu; R Klaver; P Voorn; Y Galis-de Graaf; D L Knol; J W R Twisk; A Versteeg; G J Schenk; P Van der Valk; F Barkhof; H E De Vries; H Vrenken; J J G Geurts
Journal:  Mult Scler       Date:  2015-01-12       Impact factor: 6.312

3.  No evidence of disease activity in multiple sclerosis: Implications on cognition and brain atrophy.

Authors:  Alfredo Damasceno; Benito Pereira Damasceno; Fernando Cendes
Journal:  Mult Scler       Date:  2015-10-02       Impact factor: 6.312

4.  Gray matter atrophy in multiple sclerosis: a longitudinal study.

Authors:  Elizabeth Fisher; Jar-Chi Lee; Kunio Nakamura; Richard A Rudick
Journal:  Ann Neurol       Date:  2008-09       Impact factor: 10.422

5.  Prediction of neuropsychological impairment in multiple sclerosis: comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden.

Authors:  Ralph H B Benedict; Bianca Weinstock-Guttman; Inna Fishman; Jitendra Sharma; Christopher W Tjoa; Rohit Bakshi
Journal:  Arch Neurol       Date:  2004-02

6.  Gray and white matter volume changes in early RRMS: a 2-year longitudinal study.

Authors:  M Tiberio; D T Chard; D R Altmann; G Davies; C M Griffin; W Rashid; J Sastre-Garriga; A J Thompson; D H Miller
Journal:  Neurology       Date:  2005-03-22       Impact factor: 9.910

7.  Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis.

Authors:  Nicola De Stefano; Maria Laura Stromillo; Antonio Giorgio; Maria Letizia Bartolozzi; Marco Battaglini; Mariella Baldini; Emilio Portaccio; Maria Pia Amato; Maria Pia Sormani
Journal:  J Neurol Neurosurg Psychiatry       Date:  2015-04-22       Impact factor: 10.154

8.  The longitudinal relation between brain lesion load and atrophy in multiple sclerosis: a 14 year follow up study.

Authors:  D T Chard; P A Brex; O Ciccarelli; C M Griffin; G J M Parker; C Dalton; D R Altmann; A J Thompson; D H Miller
Journal:  J Neurol Neurosurg Psychiatry       Date:  2003-11       Impact factor: 10.154

9.  Accelerated evolution of brain atrophy and "black holes" in MS patients with APOE-epsilon 4.

Authors:  Christian Enzinger; Stefan Ropele; Stephen Smith; Siegrid Strasser-Fuchs; Birgit Poltrum; Helena Schmidt; Paul M Matthews; Franz Fazekas
Journal:  Ann Neurol       Date:  2004-04       Impact factor: 10.422

10.  Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes.

Authors:  Catherine M Dalton; Declan T Chard; Gerard R Davies; Katherine A Miszkiel; Dan R Altmann; Kryshani Fernando; Gordon T Plant; Alan J Thompson; David H Miller
Journal:  Brain       Date:  2004-03-03       Impact factor: 13.501

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  47 in total

1.  MRI quality control for the Italian Neuroimaging Network Initiative: moving towards big data in multiple sclerosis.

Authors:  Loredana Storelli; Maria A Rocca; Patrizia Pantano; Elisabetta Pagani; Nicola De Stefano; Gioacchino Tedeschi; Paola Zaratin; Massimo Filippi
Journal:  J Neurol       Date:  2019-08-17       Impact factor: 4.849

Review 2.  Multiple sclerosis.

Authors:  Massimo Filippi; Amit Bar-Or; Fredrik Piehl; Paolo Preziosa; Alessandra Solari; Sandra Vukusic; Maria A Rocca
Journal:  Nat Rev Dis Primers       Date:  2018-11-08       Impact factor: 52.329

3.  Brain tissue and myelin volumetric analysis in multiple sclerosis at 3T MRI with various in-plane resolutions using synthetic MRI.

Authors:  Laetitia Saccenti; Christina Andica; Akifumi Hagiwara; Kazumasa Yokoyama; Mariko Yoshida Takemura; Shohei Fujita; Tomoko Maekawa; Koji Kamagata; Alice Le Berre; Masaaki Hori; Nobutaka Hattori; Shigeki Aoki
Journal:  Neuroradiology       Date:  2019-06-18       Impact factor: 2.804

Review 4.  The current role of MRI in differentiating multiple sclerosis from its imaging mimics.

Authors:  Ruth Geraldes; Olga Ciccarelli; Frederik Barkhof; Nicola De Stefano; Christian Enzinger; Massimo Filippi; Monika Hofer; Friedemann Paul; Paolo Preziosa; Alex Rovira; Gabriele C DeLuca; Ludwig Kappos; Tarek Yousry; Franz Fazekas; Jette Frederiksen; Claudio Gasperini; Jaume Sastre-Garriga; Nikos Evangelou; Jacqueline Palace
Journal:  Nat Rev Neurol       Date:  2018-03-09       Impact factor: 42.937

5.  The relevance of multiple sclerosis cortical lesions on cortical thinning and their clinical impact as assessed by 7.0-T MRI.

Authors:  Constantina A Treaba; Elena Herranz; Valeria T Barletta; Ambica Mehndiratta; Russell Ouellette; Jacob A Sloane; Eric C Klawiter; Revere P Kinkel; Caterina Mainero
Journal:  J Neurol       Date:  2021-02-01       Impact factor: 4.849

6.  Brain Atrophy Is Associated with Disability Progression in Patients with MS followed in a Clinical Routine.

Authors:  E Ghione; N Bergsland; M G Dwyer; J Hagemeier; D Jakimovski; I Paunkoski; D P Ramasamy; D Silva; E Carl; D Hojnacki; C Kolb; B Weinstock-Guttman; R Zivadinov
Journal:  AJNR Am J Neuroradiol       Date:  2018-11-22       Impact factor: 3.825

7.  The role of cerebellar damage in explaining disability and cognition in multiple sclerosis phenotypes: a multiparametric MRI study.

Authors:  Raffaello Bonacchi; Alessandro Meani; Elisabetta Pagani; Olga Marchesi; Massimo Filippi; Maria A Rocca
Journal:  J Neurol       Date:  2022-03-01       Impact factor: 4.849

8.  'Timed up and go' and brain atrophy: a preliminary MRI study to assess functional mobility performance in multiple sclerosis.

Authors:  Lorena Lorefice; G Coghe; G Fenu; M Porta; G Pilloni; J Frau; F Corona; V Sechi; M A Barracciu; M G Marrosu; M Pau; E Cocco
Journal:  J Neurol       Date:  2017-09-11       Impact factor: 4.849

Review 9.  Cognitive Deficits in Multiple Sclerosis: Recent Advances in Treatment and Neurorehabilitation.

Authors:  Arseny A Sokolov; Petr Grivaz; Riley Bove
Journal:  Curr Treat Options Neurol       Date:  2018-10-22       Impact factor: 3.598

10.  Are multi-contrast magnetic resonance images necessary for segmenting multiple sclerosis brains? A large cohort study based on deep learning.

Authors:  Ponnada A Narayana; Ivan Coronado; Sheeba J Sujit; Xiaojun Sun; Jerry S Wolinsky; Refaat E Gabr
Journal:  Magn Reson Imaging       Date:  2019-10-25       Impact factor: 2.546

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