Literature DB >> 29714673

Measurement of Whole-Brain and Gray Matter Atrophy in Multiple Sclerosis: Assessment with MR Imaging.

Loredana Storelli1, Maria A Rocca1, Elisabetta Pagani1, Wim Van Hecke1, Mark A Horsfield1, Nicola De Stefano1, Alex Rovira1, Jaume Sastre-Garriga1, Jacqueline Palace1, Diana Sima1, Dirk Smeets1, Massimo Filippi1.   

Abstract

Purpose To compare available methods for whole-brain and gray matter (GM) atrophy estimation in multiple sclerosis (MS) in terms of repeatability (same magnetic resonance [MR] imaging unit) and reproducibility (different system/field strength) for their potential clinical applications. Materials and Methods The softwares ANTs-v1.9, CIVET-v2.1, FSL-SIENAX/SIENA-5.0.1, Icometrix-MSmetrix-1.7, and SPM-v12 were compared. This retrospective study, performed between March 2015 and March 2017, collected data from (a) eight simulated MR images and longitudinal data (2 weeks) from 10 healthy control subjects to assess the cross-sectional and longitudinal accuracy of atrophy measures, (b) test-retest MR images in 29 patients with MS acquired within the same day at different imaging unit field strengths/manufacturers to evaluate precision, and (c) longitudinal data (1 year) in 24 patients with MS for the agreement between methods. Tissue segmentation, image registration, and white matter (WM) lesion filling were also evaluated. Multiple paired t tests were used for comparisons. Results High values of accuracy (0.87-0.97) for whole-brain and GM volumes were found, with the lowest values for MSmetrix. ANTs showed the lowest mean error (0.02%) for whole-brain atrophy in healthy control subjects, with a coefficient of variation of 0.5%. SPM showed the smallest mean error (0.07%) and coefficient of variation (0.08%) for GM atrophy. Globally, good repeatability (P > .05) but poor reproducibility (P < .05) were found for all methods. WM lesion filling technique mainly affected ANTs, MSmetrix, and SPM results (P < .05). Conclusion From this comparison, it would be possible to select a software for atrophy measurement, depending on the requirements of the application (research center, clinical trial) and its goal (accuracy and repeatability or reproducibility). An improved reproducibility is required for clinical application. © RSNA, 2018 Online supplemental material is available for this article.

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Year:  2018        PMID: 29714673     DOI: 10.1148/radiol.2018172468

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  17 in total

1.  Morphometric evaluation of traumatic axonal injury and the correlation with post-traumatic cerebral atrophy and functional outcome.

Authors:  Cedric Bohyn; Thijs Vande Vyvere; Frederik De Keyzer; Diana M Sima; Philippe Demaerel
Journal:  Neuroradiol J       Date:  2021-10-13

2.  Advanced diffusion-weighted imaging models better characterize white matter neurodegeneration and clinical outcomes in multiple sclerosis.

Authors:  Loredana Storelli; Elisabetta Pagani; Alessandro Meani; Paolo Preziosa; Massimo Filippi; Maria A Rocca
Journal:  J Neurol       Date:  2022-04-10       Impact factor: 6.682

3.  Comparing longitudinal brain atrophy measurement techniques in a real-world multiple sclerosis clinical practice cohort: towards clinical integration?

Authors:  H N Beadnall; C Wang; W Van Hecke; A Ribbens; T Billiet; M H Barnett
Journal:  Ther Adv Neurol Disord       Date:  2019-01-25       Impact factor: 6.570

4.  Supervised Domain Adaptation for Automatic Sub-cortical Brain Structure Segmentation with Minimal User Interaction.

Authors:  Kaisar Kushibar; Sergi Valverde; Sandra González-Villà; Jose Bernal; Mariano Cabezas; Arnau Oliver; Xavier Lladó
Journal:  Sci Rep       Date:  2019-05-01       Impact factor: 4.379

Review 5.  Advances in brain imaging in multiple sclerosis.

Authors:  Rosa Cortese; Sara Collorone; Olga Ciccarelli; Ahmed T Toosy
Journal:  Ther Adv Neurol Disord       Date:  2019-06-27       Impact factor: 6.570

6.  Gray matter network reorganization in multiple sclerosis from 7-Tesla and 3-Tesla MRI data.

Authors:  Gabriel Gonzalez-Escamilla; Dumitru Ciolac; Silvia De Santis; Angela Radetz; Vinzenz Fleischer; Amgad Droby; Alard Roebroeck; Sven G Meuth; Muthuraman Muthuraman; Sergiu Groppa
Journal:  Ann Clin Transl Neurol       Date:  2020-04-07       Impact factor: 4.511

7.  Age-dependent cut-offs for pathological deep gray matter and thalamic volume loss using Jacobian integration.

Authors:  Roland Opfer; Julia Krüger; Lothar Spies; Marco Hamann; Carla A Wicki; Hagen H Kitzler; Carola Gocke; Diego Silva; Sven Schippling
Journal:  Neuroimage Clin       Date:  2020-10-27       Impact factor: 4.881

8.  Generating Longitudinal Atrophy Evaluation Datasets on Brain Magnetic Resonance Images Using Convolutional Neural Networks and Segmentation Priors.

Authors:  Jose Bernal; Sergi Valverde; Kaisar Kushibar; Mariano Cabezas; Arnau Oliver; Xavier Lladó
Journal:  Neuroinformatics       Date:  2021-01-02

Review 9.  MAGNIMS consensus recommendations on the use of brain and spinal cord atrophy measures in clinical practice.

Authors:  Jaume Sastre-Garriga; Deborah Pareto; Marco Battaglini; Maria A Rocca; Olga Ciccarelli; Christian Enzinger; Jens Wuerfel; Maria P Sormani; Frederik Barkhof; Tarek A Yousry; Nicola De Stefano; Mar Tintoré; Massimo Filippi; Claudio Gasperini; Ludwig Kappos; Jordi Río; Jette Frederiksen; Jackie Palace; Hugo Vrenken; Xavier Montalban; Àlex Rovira
Journal:  Nat Rev Neurol       Date:  2020-02-24       Impact factor: 42.937

10.  Alterations of peripheral nerve excitability in an experimental autoimmune encephalomyelitis mouse model for multiple sclerosis.

Authors:  Nathalia Bernardes Teixeira; Gisele Picolo; Aline Carolina Giardini; Fawzi Boumezbeur; Géraldine Pottier; Bertrand Kuhnast; Denis Servent; Evelyne Benoit
Journal:  J Neuroinflammation       Date:  2020-09-07       Impact factor: 8.322

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