Literature DB >> 35600511

Predictive value of number and volume of demyelinating plaques in treatment response in patients with multiple sclerosis treated with INF-B.

Maryam Azizian1, Nadia Ghasemi Darestani2, Athena Aliabadi3, Mahdieh Afzali4, Nooshin Tavoosi5, Mahnaz Fosouli6, Jalil Khataei6, Halimeh Aali7, Sayed Mohammad Amin Nourian8.   

Abstract

BACKGROUND: Multiple Sclerosis (MS) is an autoimmune, inflammatory disease of the central nervous system. Magnetic resonance imaging (MRI) findings are associated with disease clinical activity and response to treatment. This study aimed to evaluate the future value of plaque number and volume in MRI as radiological criteria in determining the treatment response to INF-B in patients with MS.
METHODS: This is a cross-sectional study performed in 2016-2021 in Iran on patients with the newly diagnosed (less than one year) relapsing-remitting MS. Brain MRI was taken for all patients. The number and volumes of the MS plaques were evaluated from FLAIR images by the two radiologists. Patients were treated with INF-B1a with a dosage of 12 million units equal to 44 micrograms subcutaneously, three times per week. Patients were visited monthly by neurologists to examine their clinical status. After one year, the brain MRI was conducted with the similar characteristics to the beginning of the study, and the number and volume of MS plaques were measured again.
RESULTS: The study population consisted of 33 males and 90 females with a mean age of 28.37 ± 6.29 years. The mean Expanded Disability Status Scale (EDSS) of the patients was 3.16 ± 0.23 at the beginning of the study. The specificity for a 50% reduction in the number and volume of plaques as two separate criteria was the same and equal to 100%. The sensitivity of the number and volume of plaques were 65.5% and 90.6%, respectively. In addition, considering 10% as the cut-off point of the number of plaques, the sensitivity of the number of plaques as a criterion was equal to the sensitivity of the plaque volume.
CONCLUSION: The results of this study showed that imaging criteria provide a more objective tool for evaluating the effectiveness of treatment. These findings indicate that the number and volume of plaques could be two reliable MRI imaging criteria for assessing therapy response. The number of plaques was less accurate than the volume of plaques. AJND
Copyright © 2022.

Entities:  

Keywords:  Multiple sclerosis; accuracy; interferon β; magnetic resonance imaging; relapsing-remitting

Year:  2022        PMID: 35600511      PMCID: PMC9123433     

Source DB:  PubMed          Journal:  Am J Neurodegener Dis        ISSN: 2165-591X


  10 in total

Review 1.  Experimental Autoimmune Encephalomyelitis (EAE) as Animal Models of Multiple Sclerosis (MS).

Authors:  Simon Glatigny; Estelle Bettelli
Journal:  Cold Spring Harb Perspect Med       Date:  2018-11-01       Impact factor: 6.915

Review 2.  Unraveling treatment response in multiple sclerosis: A clinical and MRI challenge.

Authors:  Claudio Gasperini; Luca Prosperini; Mar Tintoré; Maria Pia Sormani; Massimo Filippi; Jordi Rio; Jacqueline Palace; Maria A Rocca; Olga Ciccarelli; Frederik Barkhof; Jaume Sastre-Garriga; Hugo Vrenken; Jette L Frederiksen; Tarek A Yousry; Christian Enzinger; Alex Rovira; Ludwig Kappos; Carlo Pozzilli; Xavier Montalban; Nicola De Stefano
Journal:  Neurology       Date:  2018-12-26       Impact factor: 9.910

3.  Automated Detection and Segmentation of Multiple Sclerosis Lesions Using Ultra-High-Field MP2RAGE.

Authors:  Mário João Fartaria; Pascal Sati; Alexandra Todea; Ernst-Wilhelm Radue; Reza Rahmanzadeh; Kieran OʼBrien; Daniel S Reich; Meritxell Bach Cuadra; Tobias Kober; Cristina Granziera
Journal:  Invest Radiol       Date:  2019-06       Impact factor: 6.016

4.  Accuracy of Unenhanced MRI in the Detection of New Brain Lesions in Multiple Sclerosis.

Authors:  Paul Eichinger; Simon Schön; Viola Pongratz; Hanni Wiestler; Haike Zhang; Matthias Bussas; Muna-Miriam Hoshi; Jan Kirschke; Achim Berthele; Claus Zimmer; Bernhard Hemmer; Mark Mühlau; Benedikt Wiestler
Journal:  Radiology       Date:  2019-03-12       Impact factor: 11.105

Review 5.  Multiple sclerosis: clinical aspects.

Authors:  Jiwon Oh; Angela Vidal-Jordana; Xavier Montalban
Journal:  Curr Opin Neurol       Date:  2018-12       Impact factor: 5.710

Review 6.  Mechanism and adverse effects of multiple sclerosis drugs: a review article. Part 1.

Authors:  Aryan Rafiee Zadeh; Mozhde Askari; Niloufar Nasr Azadani; Akram Ataei; Keyvan Ghadimi; Nooshin Tavoosi; Masih Falahatian
Journal:  Int J Physiol Pathophysiol Pharmacol       Date:  2019-08-15

7.  Trial of Fingolimod versus Interferon Beta-1a in Pediatric Multiple Sclerosis.

Authors:  Tanuja Chitnis; Douglas L Arnold; Brenda Banwell; Wolfgang Brück; Angelo Ghezzi; Gavin Giovannoni; Benjamin Greenberg; Lauren Krupp; Kevin Rostásy; Marc Tardieu; Emmanuelle Waubant; Jerry S Wolinsky; Amit Bar-Or; Tracy Stites; Yu Chen; Norman Putzki; Martin Merschhemke; Jutta Gärtner
Journal:  N Engl J Med       Date:  2018-09-13       Impact factor: 91.245

8.  Onset of secondary progressive multiple sclerosis is not influenced by current relapsing multiple sclerosis therapies.

Authors:  Francisco Coret; Francisco C Pérez-Miralles; Francisco Gascón; Carmen Alcalá; Arantxa Navarré; Ana Bernad; Isabel Boscá; Matilde Escutia; Sara Gil-Perotin; Bonaventura Casanova
Journal:  Mult Scler J Exp Transl Clin       Date:  2018-06-26

9.  Predicting conversion from clinically isolated syndrome to multiple sclerosis-An imaging-based machine learning approach.

Authors:  Haike Zhang; Esther Alberts; Viola Pongratz; Mark Mühlau; Claus Zimmer; Benedikt Wiestler; Paul Eichinger
Journal:  Neuroimage Clin       Date:  2018-11-05       Impact factor: 4.881

10.  The Effect of Levothyroxine on Serum Levels of Interleukin 10 and Interferon-gamma in Rat Model of Multiple Sclerosis.

Authors:  Cobra Payghani; Fatemeh Khani; Aryan Rafiee Zadeh; Parham Reisi; Hojjatallah Alaei; Bahman Rashidi
Journal:  Adv Biomed Res       Date:  2017-09-21
  10 in total

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