Dataset Information

Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method.

ABSTRACT:

Background and purpose

MR imaging is the key examination in the follow-up of patients with MS, by identification of new high-signal T2 brain lesions. However, identifying new lesions when scrolling through 2 follow-up MR images can be difficult and time-consuming. Our aim was to compare an automated coregistration-fusion reading approach with the standard approach by identifying new high-signal T2 brain lesions in patients with multiple sclerosis during follow-up MR imaging.

Materials and methods

This prospective monocenter study included 94 patients (mean age, 38.9 years) treated for MS with dimethyl fumarate from January 2014 to August 2016. One senior neuroradiologist and 1 junior radiologist checked for new high-signal T2 brain lesions, independently analyzing blinded image datasets with automated coregistration-fusion or the standard scroll-through approach with a 3-week delay between the 2 readings. A consensus reading with a second senior neuroradiologist served as a criterion standard for analyses. A Poisson regression and logistic and γ regressions were used to compare the 2 methods. Intra- and interobserver agreement was assessed by the κ coefficient.

Results

There were significantly more new high-signal T2 lesions per patient detected with the coregistration-fusion method (7 versus 4, P < .001). The coregistration-fusion method detected significantly more patients with at least 1 new high-signal T2 lesion (59% versus 46%, P = .02) and was associated with significantly faster overall reading time (86 seconds faster, P < .001) and higher reader confidence (91% versus 40%, P < 1 × 10^-4). Inter- and intraobserver agreement was excellent for counting new high-signal T2 lesions.

Conclusions

Our study showed that an automated coregistration-fusion method was more sensitive for detecting new high-signal T2 lesions in patients with MS and reducing reading time. This method could help to improve follow-up care.

SUBMITTER: Galletto Pregliasco A

PROVIDER: S-EPMC7655423 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Publications

Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method.

Galletto Pregliasco A A Collin A A Guéguen A A Metten M A MA Aboab J J Deschamps R R Gout O O Duron L L Sadik J C JC Savatovsky J J Lecler A A

AJNR. American journal of neuroradiology 20180607 7

<h4>Background and purpose</h4>MR imaging is the key examination in the follow-up of patients with MS, by identification of new high-signal T2 brain lesions. However, identifying new lesions when scrolling through 2 follow-up MR images can be difficult and time-consuming. Our aim was to compare an automated coregistration-fusion reading approach with the standard approach by identifying new high-signal T2 brain lesions in patients with multiple sclerosis during follow-up MR imaging.<h4>Materials ...[more]

PMID: 29880479

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Dataset Information

Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method.

Background and purpose

Materials and methods

Results

Conclusions

Publications

Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method.

Similar Datasets

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