Universität zu Köln

Zopfs, David ORCID: 0000-0001-9978-7453, Laukamp, Kai R., Paquet, Stefanie, Lennartz, Simon, dos Santos, Daniel Pinto, Kabbasch, Christoph, Bunck, Alexander, Schlamann, Marc and Borggrefe, Jan ORCID: 0000-0003-2908-7560 (2019). Follow-up MRI in multiple sclerosis patients: automated co-registration and lesion color-coding improves diagnostic accuracy and reduces reading time. Eur. Radiol., 29 (12). S. 7047 - 7055. NEW YORK: SPRINGER. ISSN 1432-1084

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Abstract

Objectives In multiple sclerosis (MS), the heterogeneous and numerous appearances of lesions may impair diagnostic accuracy. This study investigates if a combined automated co-registration and lesion color-coding method (AC) improves assessment of MS follow-up MRI compared with conventional reading (CR). Methods We retrospectively assessed 70 follow-up MRI of 53 patients. Heterogeneous datasets of diverse scanners and institutions were used. Two readers determined presence of (a) progression, (b) regression, (c) mixed change, or (d) stable disease between the two examinations using corresponding FLAIR sequences in CR and AC-assisted reading. Consensus reference reading was provided by two blinded radiologists. Kappa statistics tested interrater agreement, McNemar's test dichotomous variables, and Wilcoxon's test continuous variables (statistical significance p <= 0.05). Results The cohort comprised 41 female and 12 male patients with a mean age of 40 (14) years. Average rating time was reduced from 78 (36) to 44 (22) s with the AC approach (p<0.001). The time needed to start and match datasets with AC was 14 (1) s. Compared with CR, AC improved interrater agreement, both between raters (0.52 vs. 0.67) and between raters and consensus reference reading (0.47/0.5 vs. 0.83/0.78). Compared with CR, the diagnostic accuracy increased from 67 to 90% (reader 1, p<0.01) and from 70 to 87% (reader 2, p<0.05) in the AC-assisted reading. Conclusions Compared with CR, automated co-registration and lesion color-coding of MS-associated FLAIR-lesions in follow-up MRI increased diagnostic accuracy and reduced the time required for follow-up evaluation significantly. The AC algorithm therefore appears to be helpful to improve MS follow-up assessments in clinical routine.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Zopfs, David UNSPECIFIED orcid.org/0000-0001-9978-7453 UNSPECIFIED Laukamp, Kai R. UNSPECIFIED UNSPECIFIED UNSPECIFIED Paquet, Stefanie UNSPECIFIED UNSPECIFIED UNSPECIFIED Lennartz, Simon UNSPECIFIED UNSPECIFIED UNSPECIFIED dos Santos, Daniel Pinto UNSPECIFIED UNSPECIFIED UNSPECIFIED Kabbasch, Christoph UNSPECIFIED UNSPECIFIED UNSPECIFIED Bunck, Alexander UNSPECIFIED UNSPECIFIED UNSPECIFIED Schlamann, Marc UNSPECIFIED UNSPECIFIED UNSPECIFIED Borggrefe, Jan UNSPECIFIED orcid.org/0000-0003-2908-7560 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-125950
DOI:	10.1007/s00330-019-06273-x
Journal or Publication Title:	Eur. Radiol.
Volume:	29
Number:	12
Page Range:	S. 7047 - 7055
Date:	2019
Publisher:	SPRINGER
Place of Publication:	NEW YORK
ISSN:	1432-1084
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language SUBTRACTION; BRAIN; SEGMENTATION; IDENTIFICATION; PREVALENCE; MS Multiple languages Radiology, Nuclear Medicine & Medical Imaging Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/12595