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Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method.
Galletto Pregliasco, A; Collin, A; Guéguen, A; Metten, M A; Aboab, J; Deschamps, R; Gout, O; Duron, L; Sadik, J C; Savatovsky, J; Lecler, A.
Afiliação
  • Galletto Pregliasco A; From the Departments of Radiology (A.G.P., A.C., L.D., J.C.S., J.S., A.L.).
  • Collin A; From the Departments of Radiology (A.G.P., A.C., L.D., J.C.S., J.S., A.L.).
  • Guéguen A; Neurology (A.G., J.A., R.D., O.G.).
  • Metten MA; Clinical Research Unit (M.A.M.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France.
  • Aboab J; Neurology (A.G., J.A., R.D., O.G.).
  • Deschamps R; Neurology (A.G., J.A., R.D., O.G.).
  • Gout O; Neurology (A.G., J.A., R.D., O.G.).
  • Duron L; From the Departments of Radiology (A.G.P., A.C., L.D., J.C.S., J.S., A.L.).
  • Sadik JC; From the Departments of Radiology (A.G.P., A.C., L.D., J.C.S., J.S., A.L.).
  • Savatovsky J; From the Departments of Radiology (A.G.P., A.C., L.D., J.C.S., J.S., A.L.).
  • Lecler A; From the Departments of Radiology (A.G.P., A.C., L.D., J.C.S., J.S., A.L.) alecler@for.paris.
AJNR Am J Neuroradiol ; 39(7): 1226-1232, 2018 07.
Article em En | MEDLINE | ID: mdl-29880479
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador / Neuroimagem / Esclerose Múltipla Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: AJNR Am J Neuroradiol Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador / Neuroimagem / Esclerose Múltipla Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: AJNR Am J Neuroradiol Ano de publicação: 2018 Tipo de documento: Article