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. 2020 Dec 11:11:546744.
doi: 10.3389/fneur.2020.546744. eCollection 2020.

LesionQuant for Assessment of MRI in Multiple Sclerosis-A Promising Supplement to the Visual Scan Inspection

Affiliations

LesionQuant for Assessment of MRI in Multiple Sclerosis-A Promising Supplement to the Visual Scan Inspection

Synne Brune et al. Front Neurol. .

Abstract

Background and Goals: Multiple sclerosis (MS) is a central nervous system inflammatory disease where magnetic resonance imaging (MRI) is an important tool for diagnosis and disease monitoring. Quantitative measurements of lesion volume, lesion count, distribution of lesions, and brain atrophy have a potentially significant value for evaluating disease progression. We hypothesize that utilizing software designed for evaluating MRI data in MS will provide more accurate and detailed analyses compared to the visual neuro-radiological evaluation. Methods: A group of 56 MS patients (mean age 35 years, 70% females and 96% relapsing-remitting MS) was examined with brain MRI one and 5 years after diagnosis. The T1 and FLAIR brain MRI sequences for all patients were analyzed using the LesionQuant (LQ) software. These data were compared with data from structured visual evaluations of the MRI scans performed by neuro-radiologists, including assessments of atrophy, and lesion count. The data from LQ were also compared with data from other validated research methods for brain segmentation, including assessments of whole brain volume and lesion volume. Correlations with clinical tests like the timed 25-foot walk test (T25FT) were performed to explore additional value of LQ analyses. Results: Lesion count assessments by LQ and by the neuro-radiologist were significantly correlated one year (cor = 0.92, p = 2.2 × 10-16) and 5 years (cor = 0.84, p = 2.7 × 10-16) after diagnosis. Analyzes of the intra- and interrater variability also correlated significantly (cor = 0.96, p < 0.001, cor = 0.97, p < 0.001). Significant positive correlation was found between lesion volume measured by LQ and by the software Cascade (cor = 0.7, p < 0.001. LQ detected a reduction in whole brain percentile >10 in 10 patients across the time-points, whereas the neuro-radiologist assessment identified six of these. The neuro-radiologist additionally identified five patients with increased atrophy in the follow-up period, all of them displayed decreasing low whole brain percentiles (median 11, range 8-28) in the LQ analysis. Significant positive correlation was identified between lesion volume measured by LQ and test performance on the T25FT both at 1 and 5 years after diagnosis. Conclusion: For the number of MS lesions at both time-points, we demonstrated strong correlations between the assessments done by LQ and the neuro-radiologist. Lesion volume evaluated with LQ correlated with T25FT performance. LQ-analyses classified more patients to have brain atrophy than the visual neuro-radiological evaluation. In conclusion, LQ seems like a promising supplement to the evaluation performed by neuro-radiologists, providing an automated tool for evaluating lesions in MS patients and also detecting early signs of atrophy in both a longitudinal and cross-sectional setting.

Keywords: MRI; automatic lesion detection; brain atrophy; longitudinal lesions; multiple sclerosis.

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Conflict of interest statement

SB has received honoraria for lecturing from Biogen and Novartis. EH has received honoraria for lecturing from Biogen, Merck and Sanofi-Genzyme. PB-H has received advisory board and/or speaker honoraria from Biogen, Novartis, Merck, UCB, and Teva. PS has received honoraria for lecturing and travel support from Merck. HH has received travel support, honoraria for advice or lecturing from Biogen Idec, Sanofi-Genzyme, Merck, Novartis, Roche, and Teva and an unrestricted research grant from Novartis and Biogen. MB has received honoraria for lecturing from Novartis and Biogen Idec, Merck AB, Roche Norge, and Sanofi Genzyme. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
LesionQuant report. Example of a LesionQuant report from one MS subject comparing two MRI scans with a 5-month time interval between the two time-points.
Figure 2
Figure 2
An example of the visual assessment by the neuro-radiologist. In (A) we see an axial T1 MRI at time-point 1, while in (B) we see the MRI at time-point 2, highlighting a circle with an example of a new lesion evolving during the follow-up period. The oval circle is an example of an area showing increased CSF in the sulcus, which was evaluated as representing atrophy between the two time-points.
Figure 3
Figure 3
An overview of the evaluations of change in lesions between the two time-points. The LesionQuant assessments are depicted with a circle, while the neuro-radiological evaluations are depicted using a triangle. Each subject is visualized with both assessments and with a unique color. The green circles show examples of assessments with good agreement between LQ and neuro-radiologist, while the red circles show assessments where the two methods differ a lot in the same patient.

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