Automated quantification of deep grey matter structures and white matter lesions using magnetic resonance imaging in relapsing remission multiple sclerosis

Abstract Background Brain volume loss (BVL) is widespread in MS and occurs throughout the disease course at a rate considerably greater than in the general population. In MS, brain volume correlates with and predicts future disability, making BVL a relevant measure of diffuse CNS damage leading to clinical disease progression, as well as serving as a useful outcome in evaluating MS therapies. The aim of our study was to evaluate the role of automated segmentation and quantification of deep grey matter structures and white matter lesions in Relapsing Remitting Multiple Sclerosis patients using MR images and to correlate the volumetric results with different degrees of disability based on expanded disability status scale (EDSS) scores. Results All the patients in our study showed relative atrophy of the thalamus and the putamen bilaterally when compared with the normal control group. Statistical analysis was significant for the thalamus and the putamen atrophy (P value < 0.05). On the other hand, statistical analysis was not significant for the caudate and the hippocampus (P value > 0.05); there was a significant positive correlation between the white matter lesions volume and EDSS scores (correlation coefficient of 0.7505). On the other hand, there was a significant negative correlation between the thalamus and putamen volumes, and EDSS scores (correlation coefficients < − 0.9), while the volumes of the caudate and the hippocampus had a very weak and non-significant correlation with the EDSS scores (correlation coefficients > − 0.35). Conclusions The automated segmentation and quantification tools have a great role in the assessment of brain structural changes in RRMS patients, and that it became essential to integrate these tools in the daily medical practice for the great value they add to the current evaluation measures.

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Multi-parametric structural magnetic resonance imaging in relation to cognitive dysfunction in long-standing multiple sclerosis

Multiple Sclerosis Journal ◽

10.1177/1352458515596598 ◽

2015 ◽

Vol 22 (5) ◽

pp. 608-619 ◽

Cited By ~ 23

Author(s):

Marita Daams ◽

Martijn D Steenwijk ◽

Menno M Schoonheim ◽

Mike P Wattjes ◽

Lisanne J Balk ◽

...

Keyword(s):

Multiple Sclerosis ◽

White Matter ◽

Cognitive Dysfunction ◽

Cognitive Deficits ◽

Grey Matter ◽

White Matter Damage ◽

Diffuse White Matter ◽

Brain White Matter ◽

Deep Grey Matter ◽

Imaging Markers

Background: Cognitive deficits are common in multiple sclerosis. Most previous studies investigating the imaging substrate of cognitive deficits in multiple sclerosis included patients with relatively short disease durations and were limited to one modality/brain region. Objective: To identify the strongest neuroimaging predictors for cognitive dysfunction in a large cohort of patients with long-standing multiple sclerosis. Methods: Extensive neuropsychological testing and multimodal 3.0T MRI was performed in 202 patients with multiple sclerosis and 52 controls. Cognitive scores were compared between groups using Z-scores. Whole-brain, white matter, grey matter, deep grey matter and lesion volumes; cortical thickness, (juxta)cortical and cerebellar lesions; and extent and severity of diffuse white matter damage were measured. Stepwise linear regression was used to identify the strongest predictors for cognitive dysfunction. Results: All cognitive domains were affected in patients. Patients showed extensive atrophy, focal pathology and damage in up to 75% of the investigated white matter. Associations between imaging markers and average cognition were two times stronger in cognitively impaired patients than in cognitively preserved patients. The final model for average cognition consisted of deep grey matter DGMV volume and fractional anisotropy severity (adjusted R²=0.490; p<0.001). Conclusion: From all imaging markers, deep grey matter atrophy and diffuse white matter damage emerged as the strongest predictors for cognitive dysfunction in long-standing multiple sclerosis.

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Automated segmentation of changes in FLAIR-hyperintense white matter lesions in multiple sclerosis on serial magnetic resonance imaging

NeuroImage Clinical ◽

10.1016/j.nicl.2019.101849 ◽

2019 ◽

Vol 23 ◽

pp. 101849 ◽

Cited By ~ 11

Author(s):

Paul Schmidt ◽

Viola Pongratz ◽

Pascal Küster ◽

Dominik Meier ◽

Jens Wuerfel ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Multiple Sclerosis ◽

White Matter ◽

Magnetic Resonance ◽

White Matter Lesions ◽

Automated Segmentation ◽

Resonance Imaging ◽

Serial Magnetic Resonance Imaging ◽

Hyperintense White Matter

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Cardiovascular risk and white matter lesions after endocrine control of Cushing's syndrome

Acta Endocrinologica ◽

10.1530/eje-15-0600 ◽

2015 ◽

Vol 173 (6) ◽

pp. 765-775 ◽

Cited By ~ 22

Author(s):

Alicia Santos ◽

Eugenia Resmini ◽

Beatriz Gómez-Ansón ◽

Iris Crespo ◽

Esther Granell ◽

...

Keyword(s):

Cardiovascular Risk ◽

White Matter ◽

Cushing’S Syndrome ◽

Grey Matter ◽

Brain Volume ◽

White Matter Lesions ◽

Cushing's Syndrome ◽

Vascular Age ◽

Patient Groups ◽

Active Patients

ObjectiveCushing's syndrome (CS) is associated with high cardiovascular risk. White matter lesions (WML) are common on brain magnetic resonance imaging (MRI) in patients with increased cardiovascular risk.AimTo investigate the relationship between cardiovascular risk, WML, neuropsychological performance and brain volume in CS.Design/methodsThirty-eight patients with CS (23 in remission, 15 active) and 38 controls sex-, age- and education-level matched underwent a neuropsychological and clinical evaluation, blood and urine tests and 3Tesla brain MRI. WML were analysed with the Scheltens scale. Ten-year cardiovascular risk (10CVR) and vascular age (VA) were calculated according to an algorithm based on the Framingham heart study.ResultsPatients in remission had a higher degree of WML than controls and active patients (P<0.001 andP=0.008 respectively), which did not correlate with cognitive performance in any group. WML severity positively correlated with diastolic blood pressure (r=0.659,P=0.001) and duration of hypertension (r=0.478,P=0.021) in patients in remission. Both patient groups (active and in remission) had higher 10CVR (P=0.030,P=0.041) and VA than controls (P=0.013,P=0.039). Neither the 10CVR nor the VA correlated with WML, although both negatively correlated with cognitive function and brain volume in patients in remission (P<0.05). Total brain volume and grey matter volume in both CS patient groups were reduced compared to controls (total volume: activeP=0.006, in remissionP=0.012; grey matter: activeP=0.001, in remissionP=0.003), with no differences in white matter volume between groups.ConclusionsPatients in remission of Cushing's syndrome (but not active patients) have more severe white matter lesions than controls, positively correlated with diastolic pressure and duration of hypertension. Ten-year cardiovascular risk and vascular age appear to be negatively correlated with the cognitive function and brain volume in patients in remission of Cushing's syndrome.

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Contrasting the brain imaging features of MOG-antibody disease, with AQP4-antibody NMOSD and multiple sclerosis

Multiple Sclerosis Journal ◽

10.1177/13524585211018987 ◽

2021 ◽

pp. 135245852110189

Author(s):

Silvia Messina ◽

Romina Mariano ◽

Adriana Roca-Fernandez ◽

Ana Cavey ◽

Maciej Jurynczyk ◽

...

Keyword(s):

Multiple Sclerosis ◽

Grey Matter ◽

Diffusion Imaging ◽

White Matter Lesions ◽

Lesion Volume ◽

Imaging Features ◽

Strongly Correlated ◽

Deep Grey Matter ◽

Magnetic Resonance Imaging Mri ◽

Aqp4 Antibody

Background: Identifying magnetic resonance imaging (MRI) markers in myelin-oligodendrocytes-glycoprotein antibody-associated disease (MOGAD), neuromyelitis optica spectrum disorder-aquaporin-4 positive (NMOSD-AQP4) and multiple sclerosis (MS) is essential for establishing objective outcome measures. Objectives: To quantify imaging patterns of central nervous system (CNS) damage in MOGAD during the remission stage, and to compare it with NMOSD-AQP4 and MS. Methods: 20 MOGAD, 19 NMOSD-AQP4, 18 MS in remission with brain or spinal cord involvement and 18 healthy controls (HC) were recruited. Volumetrics, lesions and cortical lesions, diffusion-imaging measures, were analysed. Results: Deep grey matter volumes were lower in MOGAD ( p = 0.02) and MS ( p = 0.0001), compared to HC and were strongly correlated with current lesion volume (MOGAD R = −0.93, p < 0.001, MS R = −0.65, p = 0.0034). Cortical/juxtacortical lesions were seen in a minority of MOGAD, in a majority of MS and in none of NMOSD-AQP4. Non-lesional tissue fractional anisotropy (FA) was only reduced in MS ( p = 0.01), although focal reductions were noted in NMOSD-AQP4, reflecting mainly optic nerve and corticospinal tract pathways. Conclusion: MOGAD patients are left with grey matter damage, and this may be related to persistent white matter lesions. NMOSD-AQP4 patients showed a relative sparing of deep grey matter volumes, but reduced non-lesional tissue FA. Observations from our study can be used to identify new markers of damage for future multicentre studies.

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Neuroinflammation and its relationship to changes in brain volume and white matter lesions in multiple sclerosis

Brain ◽

10.1093/brain/awx228 ◽

2017 ◽

Vol 140 (11) ◽

pp. 2927-2938 ◽

Cited By ~ 28

Author(s):

Gourab Datta ◽

Alessandro Colasanti ◽

Eugenii A Rabiner ◽

Roger N Gunn ◽

Omar Malik ◽

...

Keyword(s):

Multiple Sclerosis ◽

White Matter ◽

Brain Volume ◽

White Matter Lesions

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Cognitive impairment in early MS: contribution of white matter lesions, deep grey matter atrophy, and cortical atrophy

Journal of Neurology ◽

10.1007/s00415-020-09841-0 ◽

2020 ◽

Vol 267 (8) ◽

pp. 2307-2318 ◽

Cited By ~ 1

Author(s):

Christina Engl ◽

Laura Tiemann ◽

Sophia Grahl ◽

Matthias Bussas ◽

Paul Schmidt ◽

...

Keyword(s):

Cognitive Impairment ◽

White Matter ◽

Grey Matter ◽

White Matter Lesions ◽

Cortical Atrophy ◽

Deep Grey Matter ◽

Grey Matter Atrophy

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Cerebrospinal fluid neurofilament light levels mark grey matter volume in clinically isolated syndrome suggestive of multiple sclerosis

Multiple Sclerosis Journal ◽

10.1177/1352458517711774 ◽

2017 ◽

Vol 24 (8) ◽

pp. 1039-1045 ◽

Cited By ~ 7

Author(s):

Carla Tortorella ◽

Vita Direnzo ◽

Maddalena Ruggieri ◽

Stefano Zoccolella ◽

Mariangela Mastrapasqua ◽

...

Keyword(s):

Multiple Sclerosis ◽

Cerebrospinal Fluid ◽

White Matter ◽

Grey Matter ◽

Brain Volume ◽

Clinically Isolated Syndrome ◽

Grey Matter Volume ◽

Neurofilament Light ◽

Brain Volumes ◽

Matter Volume

Background: Brain atrophy is a known marker of irreversible tissue damage in multiple sclerosis (MS). Cerebrospinal fluid (CSF) osteopontin (OPN) and neurofilament light chain (NF-L) have been proposed as candidate surrogate markers of inflammatory and neurodegenerative processes in MS. Objective: To evaluate the relationship between CSF NF-L and OPN levels and brain grey and white matter volumes in patients with clinically isolated syndrome (CIS) suggestive of MS. Methods: A total of 41 CIS patients and 30 neurological controls (NCs) were included. CSF NF-L and OPN were measured by commercial ELISA. Measures of brain volume (normalized brain volume (NBV), normalized grey matter volume (NGV), peripheral grey matter volume (PGV), normalized white matter volume (WMV), and ventricular volume) were obtained by SIENAX. Corpus callosum index (CCI) was calculated. Brain volumes were categorized into ‘high’ and ‘low’ according to the median value. Results: CSF NF-L and OPN levels were higher in CIS patients in comparison with NCs. CIS patients with ‘low’ TGV, PGV, and TBV showed higher CSF NF-L levels than CIS patients with ‘high’ brain volumes. TGV and PGV correlated inversely with NF-L levels, whereas CCI was inversely related to OPN levels. CSF NF-L was the only independent predictor of TGV and PGV. Conclusion: CSF NF-L tracks mainly grey matter damage in patients with CIS suggestive of MS.

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Simultaneous lesion and brain segmentation in multiple sclerosis using deep neural networks

Scientific Reports ◽

10.1038/s41598-020-79925-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Richard McKinley ◽

Rik Wepfer ◽

Fabian Aschwanden ◽

Lorenz Grunder ◽

Raphaela Muri ◽

...

Keyword(s):

Multiple Sclerosis ◽

Neural Networks ◽

Grey Matter ◽

White Matter Lesions ◽

Brain Structures ◽

Training Dataset ◽

Single Centre ◽

Deep Grey Matter ◽

Reference Implementation ◽

Dataset Shift

AbstractSegmentation of white matter lesions and deep grey matter structures is an important task in the quantification of magnetic resonance imaging in multiple sclerosis. In this paper we explore segmentation solutions based on convolutional neural networks (CNNs) for providing fast, reliable segmentations of lesions and grey-matter structures in multi-modal MR imaging, and the performance of these methods when applied to out-of-centre data. We trained two state-of-the-art fully convolutional CNN architectures on the 2016 MSSEG training dataset, which was annotated by seven independent human raters: a reference implementation of a 3D Unet, and a more recently proposed 3D-to-2D architecture (DeepSCAN). We then retrained those methods on a larger dataset from a single centre, with and without labels for other brain structures. We quantified changes in performance owing to dataset shift, and changes in performance by adding the additional brain-structure labels. We also compared performance with freely available reference methods. Both fully-convolutional CNN methods substantially outperform other approaches in the literature when trained and evaluated in cross-validation on the MSSEG dataset, showing agreement with human raters in the range of human inter-rater variability. Both architectures showed drops in performance when trained on single-centre data and tested on the MSSEG dataset. When trained with the addition of weak anatomical labels derived from Freesurfer, the performance of the 3D Unet degraded, while the performance of the DeepSCAN net improved. Overall, the DeepSCAN network predicting both lesion and anatomical labels was the best-performing network examined.

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Contrasting the brain imaging features of MOG-Antibody disease, with AQP4-Antibody NMOSD and Multiple Sclerosis

10.1101/2020.09.22.20198978 ◽

2020 ◽

Author(s):

Silvia Messina ◽

Romina Mariano ◽

Adriana Roca-Fernandez ◽

Ana Cavey ◽

Maciej Jurynczyk ◽

...

Keyword(s):

Multiple Sclerosis ◽

Visual Acuity ◽

White Matter ◽

Grey Matter ◽

Optic Chiasm ◽

Lesion Volume ◽

Imaging Features ◽

Conventional Imaging ◽

Cortical Lesions ◽

Deep Grey Matter

Neuromyelitis optica associated with aquaporin-4-antibodies (NMOSD-AQP4) and myelin oligodentrocyte-glycoprotein antibody-associated disorder (MOGAD) have been recently recognised as different from multiple sclerosis. Although conventional MRI may help distinguish multiple sclerosis from antibody-mediated diseases, the use of quantitative and non-conventional imaging may give more pathological information and explain the clinical differences. We compared, using non-conventional imaging, brain MRI findings in 75 subjects in remission with NMOSD-AQP4, MOGAD, multiple sclerosis or healthy controls (HC). Volumetrics, white matter and cortical lesions, and tissue integrity measures using diffusion imaging, were analysed in the four groups along with their association with disability (expanded disability status scale [EDSS] and visual acuity). The volumetric analysis showed that, deep grey matter volumes were significantly lower in multiple sclerosis (p=0.0001) and MOGAD (p=0.02), compared to HC. Relapsing MOGAD had lower white matter, pallidus and hippocampus volumes than in monophasic (p<0.05). Optic chiasm volume was reduced only in NMOSD-AQP4 who had at least one episode of optic neuritis (ON) (NMOSD-AQP4-ON vs NMOSD-AQP4 p<0.001, HC p<0.001, MOGAD-ON p=0.04, multiple sclerosis-ON p=0.02) likely reflecting the recognised posterior location of NMOSD-AQP4-ON and its severity. Lesion volume was greatest in multiple sclerosis followed by MOGAD and in these two diseases, the lesion volume correlated with disease duration (multiple sclerosis R=0.46, p=0.05, MOGAD R=0.81, p<0.001), cortical thickness (multiple sclerosis R=-0.64, p=0.0042, MOGAD=-0.71, p=0.005) and deep grey matter volumes (multiple sclerosis R=-0.65, p=0.0034, MOGAD R=-0.93, p<0.001). Lesional-fractional anisotropy (FA) was reduced and mean diffusivity increased in all patients, but overall, FA was only reduced in the non-lesional tissue in multiple sclerosis (p=0.01), although focal reductions were noted in NMOSD-AQP4, reflecting mainly optic nerve and corticospinal tract pathways. Cortical/juxtacortical lesions were seen in a minority of MOGAD, while cortical/juxtacortical and purely cortical lesions were identified in the majority of multiple sclerosis and in none of the NMOSD-AQP4. Non-lesional FA in NMOSD-AQP4, lower white-matter volume and female sex in multiple sclerosis, and lower brainstem volume in MOGAD were the best predictors of EDSS disability (accounting for 46%, 49% and 19% respectively). Worse visual acuity associated with lower optic chiasm volume in NMOSD-AQP4 and lower thalamus volume in MOGAD (accounting for 58% and 35% respectively). Although MOGAD patients had good outcomes, deep grey matter atrophy was present. In contrast, NMOSD-AQP4 patients showed a relative sparing of deep grey matter volumes, despite greater residual disability as compared with MOGAD patients. NMOSD-AQP4 but not MOGAD patients showed reduced FA in non-lesional tissue.

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