Abstract
BackgroundMRI assessment in multiple sclerosis (MS) focuses on the presence of typical white matter (WM) lesions. Neurodegeneration characterised by brain atrophy is recognised in the research field as an important prognostic factor. It is not routinely reported clinically, in part due to difficulty in achieving reproducible measurements. Automated MRI quantification of WM lesions and brain volume could provide important clinical monitoring data. In general, lesion quantification relies on both T1 and FLAIR input images, while tissue volumetry relies on T1. However, T1-weighted scans are not routinely included in the clinical MS protocol, limiting the utility of automated quantification. ObjectivesWe address an aspect of this important translational challenge by assessing the performance of FLAIR-only lesion and brain segmentation, against a conventional approach requiring multi-contrast acquisition. We explore whether FLAIR-only grey matter (GM) segmentation yields more variability in performance compared with two-channel segmentation; whether this is related to field strength; and whether the results meet a level of clinical acceptability demonstrated by the ability to reproduce established biological associations. MethodsWe used a multicentre dataset of subjects with a CIS suggestive of MS scanned at 1.5T and 3T in the same week. WM lesions were manually segmented by two raters, ‘manual 1′ guided by consensus reading of CIS-specific lesions and ‘manual 2′ by any WM hyperintensity. An existing brain segmentation method was adapted for FLAIR-only input. Automated segmentation of WM hyperintensity and brain volumes were performed with conventional (T1/T1 + FLAIR) and FLAIR-only methods. ResultsWM lesion volumes were comparable at 1.5T between ‘manual 2′ and FLAIR-only methods and at 3T between ‘manual 2′, T1 + FLAIR and FLAIR-only methods. For cortical GM volume, linear regression measures between conventional and FLAIR-only segmentation were high (1.5T: α = 1.029, R2 = 0.997, standard error (SE) = 0.007; 3T: α = 1.019, R2 = 0.998, SE = 0.006). Age-associated change in cortical GM volume was a significant covariate in both T1 (p = 0.001) and FLAIR-only (p = 0.005) methods, confirming the expected relationship between age and GM volume for FLAIR-only segmentations. ConclusionsFLAIR-only automated segmentation of WM lesions and brain volumes were consistent with results obtained through conventional methods and had the ability to demonstrate biological effects in our study population. Imaging protocol harmonisation and validation with other MS phenotypes could facilitate the integration of automated WM lesion volume and brain atrophy analysis as clinical tools in radiological MS reporting.
Highlights
Magnetic resonance imaging (MRI) assessment is fundamental for diagnosis and monitoring in multiple sclerosis (MS)
We used the dataset described by Hagens et al (2018), which con sists of clinically isolated syndrome (CIS) subjects recruited between July 2013 and September 2015 from six European MS centres in the Magnetic Resonance Imaging in Multiple Sclerosis (MAGNIMS) network
For 1.5T, lesion volumes segmented with manual method 2 were not significantly different to T2-FLAIR-only Bayesian Method of Model Selection (BaMoS) (p = 0.239)
Summary
Magnetic resonance imaging (MRI) assessment is fundamental for diagnosis and monitoring in multiple sclerosis (MS). Once MS has become estab lished, change in lesion load over time and in response to treatment is the focus of radiology reporting Another component of MS pathology – namely neurodegeneration characterised by brain atrophy - has been recognised as an important prognostic factor for disease progression in the research field (Sastre-Garriga et al, 2017). Neurodegeneration characterised by brain atrophy is recognised in the research field as an important prognostic factor It is not routinely reported clinically, in part due to difficulty in achieving reproducible measurements. Conclusions: FLAIR-only automated segmentation of WM lesions and brain volumes were consistent with results obtained through conventional methods and had the ability to demonstrate biological effects in our study
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.