Literature DB >> 10639661

Visual analysis of serial T2-weighted MRI in multiple sclerosis: intra- and interobserver reproducibility.

P D Molyneux1, D H Miller, M Filippi, T A Yousry, E W Radü, H J Adèr, F Barkhof.   

Abstract

We evaluated the effect of consensus formation and training on the agreement between observers in scoring the number of new and enlarging multiple sclerosis (MS) lesions on serial T2-weighted MRI studies. The baseline and month 9 MRI studies of 16 patients with a range of MRI activity were used (dual-echo conventional spin-echo sequence, TR 2000, TE 34 and 90 ms, 5 mm contiguous slices, inplane resolution 1 mm). First, the serial studies were visually analysed for the presence of new and enlarging lesions, on two occasions, by five experienced observers, without adopting any consensus strategy and in isolation. Next, the observers met to identify the common sources of inconsistencies in reporting between observers and formulate consensus rules. Finally, a further independent reading session was performed on the same MRI dataset, this time applying the consensus rules. Agreement between observers was assessed using kappa scores. Without the consensus rules, interobserver kappa scores for the first and second reading sessions for new lesions were only 0.51 and 0.39 respectively; agreement for enlarging lesions was even worse. The mean intraobserver kappa score for new lesions was higher at 0.72, reflecting the fact that the observers were consistently applying their individual assessment strategies. Application of the consensus rules did not lead to a significant improvement in inter observer kappas; the kappa scores adopting the guidelines were 0.46 and 0.21 for new and enlarging lesions respectively. Consensus guidelines thus did not improve the reproducibility of visual analysis of serial T2-weighted MRI, and the level of agreement between observers remained only moderate. Suboptimal repositioning is likely to be a major source of residual variability and this suggests a future role for image registration strategies; until then, a single observer, or pair of observers working in consensus, should be used in MS studies.

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Year:  1999        PMID: 10639661     DOI: 10.1007/s002340050860

Source DB:  PubMed          Journal:  Neuroradiology        ISSN: 0028-3940            Impact factor:   2.804


  13 in total

Review 1.  MRI monitoring of immunomodulation in relapse-onset multiple sclerosis trials.

Authors:  Frederik Barkhof; Jack H Simon; Franz Fazekas; Marco Rovaris; Ludwig Kappos; Nicola de Stefano; Chris H Polman; John Petkau; Ernst W Radue; Maria P Sormani; David K Li; Paul O'Connor; Xavier Montalban; David H Miller; Massimo Filippi
Journal:  Nat Rev Neurol       Date:  2011-12-06       Impact factor: 42.937

2.  Interobserver agreement on the radiological criteria of the International Panel on the diagnosis of multiple sclerosis.

Authors:  Tijmen Korteweg; Bernard M J Uitdehaag; Dirk L Knol; Robin H M Smithuis; Paul R Algra; Cees de Vries; Peter A Poppe; Jan-Hein T M van Waesberghe; Elisabeth Bergers; Geert J Lycklama à Nijeholt; Chris H Polman; Frederik Barkhof
Journal:  Eur Radiol       Date:  2006-05-18       Impact factor: 5.315

Review 3.  Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis-clinical implementation in the diagnostic process.

Authors:  Àlex Rovira; Mike P Wattjes; Mar Tintoré; Carmen Tur; Tarek A Yousry; Maria P Sormani; Nicola De Stefano; Massimo Filippi; Cristina Auger; Maria A Rocca; Frederik Barkhof; Franz Fazekas; Ludwig Kappos; Chris Polman; David Miller; Xavier Montalban
Journal:  Nat Rev Neurol       Date:  2015-07-07       Impact factor: 42.937

4.  Clinical and imaging correlates of the multiple sclerosis impact scale in secondary progressive multiple sclerosis.

Authors:  T Hayton; J Furby; K J Smith; D R Altmann; R Brenner; J Chataway; K Hunter; D J Tozer; D H Miller; R Kapoor
Journal:  J Neurol       Date:  2011-08-24       Impact factor: 4.849

5.  Multiple sclerosis: identification of temporal changes in brain lesions with computer-assisted detection software.

Authors:  M Bilello; M Arkuszewski; P Nucifora; I Nasrallah; E R Melhem; L Cirillo; J Krejza
Journal:  Neuroradiol J       Date:  2013-05-10

6.  Trimmed-likelihood estimation for focal lesions and tissue segmentation in multisequence MRI for multiple sclerosis.

Authors:  Daniel García-Lorenzo; Sylvain Prima; Douglas L Arnold; D Louis Collins; Christian Barillot
Journal:  IEEE Trans Med Imaging       Date:  2011-02-14       Impact factor: 10.048

7.  Reliability of classifying multiple sclerosis disease activity using magnetic resonance imaging in a multiple sclerosis clinic.

Authors:  Edru Erbayat Altay; Elizabeth Fisher; Stephen E Jones; Claire Hara-Cleaver; Jar-Chi Lee; Richard A Rudick
Journal:  JAMA Neurol       Date:  2013-03-01       Impact factor: 18.302

8.  Induction of serum soluble tumor necrosis factor receptor II (sTNF-RII) and interleukin-1 receptor antagonist (IL-1ra) by interferon beta-1b in patients with progressive multiple sclerosis.

Authors:  Manuel Comabella; E Julià; M Tintoré; L Brieva; N Téllez; J Río; C López; A Rovira; X Montalban
Journal:  J Neurol       Date:  2008-05-20       Impact factor: 4.849

9.  Subtraction MR images in a multiple sclerosis multicenter clinical trial setting.

Authors:  Bastiaan Moraal; Dominik S Meier; Peter A Poppe; Jeroen J G Geurts; Hugo Vrenken; William M A Jonker; Dirk L Knol; Ronald A van Schijndel; Petra J W Pouwels; Christoph Pohl; Lars Bauer; Rupert Sandbrink; Charles R G Guttmann; Frederik Barkhof
Journal:  Radiology       Date:  2008-11-26       Impact factor: 11.105

Review 10.  Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML).

Authors:  Rima Hajjo; Dima A Sabbah; Sanaa K Bardaweel; Alexander Tropsha
Journal:  Diagnostics (Basel)       Date:  2021-04-21
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