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AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Research ArticleAdult Brain

PACS Integration of Semiautomated Imaging Software Improves Day-to-Day MS Disease Activity Detection

A. Dahan, R. Pereira, C.B. Malpas, T. Kalincik and F. Gaillard
American Journal of Neuroradiology October 2019, 40 (10) 1624-1629; DOI: https://doi.org/10.3174/ajnr.A6195
A. Dahan
aFrom the Department of Radiology (A.D.), Austin Hospital, Heidelberg, Australia
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R. Pereira
bDepartments of Radiology (R.P., F.G.)
dDepartment of Radiology (R.P.), University of Queensland, Brisbane, Queensland, Australia
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C.B. Malpas
cNeurology (T.K., C.M.), Royal Melbourne Hospital, Parkville, Victoria, Australia
eClinical Outcomes Research Unit (CORe) (C.M., T.K.)
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T. Kalincik
cNeurology (T.K., C.M.), Royal Melbourne Hospital, Parkville, Victoria, Australia
eClinical Outcomes Research Unit (CORe) (C.M., T.K.)
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F. Gaillard
bDepartments of Radiology (R.P., F.G.)
fDepartments of Medicine and Radiology (F.G.), University of Melbourne, Melbourne, Australia.
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Abstract

BACKGROUND AND PURPOSE: The standard for evaluating interval radiologic activity in MS, side-by-side MR imaging comparison, is restricted by its time-consuming nature and limited sensitivity. VisTarsier, a semiautomated software for comparing volumetric FLAIR sequences, has shown better disease-activity detection than conventional comparison in retrospective studies. Our objective was to determine whether implementing this software in day-to-day practice would show similar efficacy.

MATERIALS AND METHODS: VisTarsier created an additional coregistered image series for reporting a color-coded disease-activity change map for every new MS MR imaging brain study that contained volumetric FLAIR sequences. All other MS studies, including those generated during software-maintenance periods, were interpreted with side-by-side comparison only. The number of new lesions reported with software assistance was compared with those observed with traditional assessment in a generalized linear mixed model. Questionnaires were sent to participating radiologists to evaluate the perceived day-to-day impact of the software.

RESULTS: Nine hundred six study pairs from 538 patients during 2 years were included. The semiautomated software was used in 841 study pairs, while the remaining 65 used conventional comparison only. Twenty percent of software-aided studies reported having new lesions versus 9% with standard comparison only. The use of this software was associated with an odds ratio of 4.15 for detection of new or enlarging lesions (P = .040), and 86.9% of respondents from the survey found that the software saved at least 2–5 minutes per scan report.

CONCLUSIONS: VisTarsier can be implemented in real-world clinical settings with good acceptance and preservation of accuracy demonstrated in a retrospective environment.

ABBREVIATIONS:

AIC
akaike information criterion
CSSC
conventional side-by-side comparison
EDSS
Expanded Disability Status Scale
VT
VisTarsier
  • © 2019 by American Journal of Neuroradiology
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American Journal of Neuroradiology: 40 (10)
American Journal of Neuroradiology
Vol. 40, Issue 10
1 Oct 2019
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Cite this article
A. Dahan, R. Pereira, C.B. Malpas, T. Kalincik, F. Gaillard
PACS Integration of Semiautomated Imaging Software Improves Day-to-Day MS Disease Activity Detection
American Journal of Neuroradiology Oct 2019, 40 (10) 1624-1629; DOI: 10.3174/ajnr.A6195

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PACS Integration of Semiautomated Imaging Software Improves Day-to-Day MS Disease Activity Detection
A. Dahan, R. Pereira, C.B. Malpas, T. Kalincik, F. Gaillard
American Journal of Neuroradiology Oct 2019, 40 (10) 1624-1629; DOI: 10.3174/ajnr.A6195
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