Corpus callosum index correlates with brain volumetry and disability in multiple sclerosis patients

Sugijono, Stefanus E.; Mulyadi, Rahmad; Firdausia, Salsabila; Prihartono, Joedo; Estiasari, Riwanti

doi:10.17712/nsj.2020.3.20190093

Cited by 4 publications

(5 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our reproducibility analysis, we compared the normalized CC area that was obtained from segmentations performed on manually The CC is a promising marker for several neurodegenerative diseases such as Alzheimer's disease, 30 Parkinson's disease, 31 amyotrophic lateral sclerosis, 32 and particularly MS. 33 Its significance in MS is intimately tied to the CC being a large white matter structure in a disease that predominantly affects myelin. Several studies have shown that the extent of damage to the CC significantly correlates to both physical and cognitive disabilities, 7,27,34 and that the CC is a predictor of cognitive disability 8.5 years later. 5 Our observations corroborate this notion, showing significant correlations with both EDSS and SDMT at both baseline and follow-up on average 6-7 years later.…”

Section: Discussionmentioning

confidence: 99%

“…The CC is a promising marker for several neurodegenerative diseases such as Alzheimer's disease, 30 Parkinson's disease, 31 amyotrophic lateral sclerosis, 32 and particularly MS. 33 Its significance in MS is intimately tied to the CC being a large white matter structure in a disease that predominantly affects myelin. Several studies have shown that the extent of damage to the CC significantly correlates to both physical and cognitive disabilities, 7 , 27 , 34 and that the CC is a predictor of cognitive disability 8.5 years later. 5 Our observations corroborate this notion, showing significant correlations with both EDSS and SDMT at both baseline and follow‐up on average 6‐7 years later.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis

Brusini

Plattén

Ouellette

et al. 2022

Journal of Neuroimaging

View full text Add to dashboard Cite

Background and Purpose Corpus callosum (CC) atrophy is predictive of future disability in multiple sclerosis (MS). However, current segmentation methods are either labor‐ or computationally intensive. We therefore developed an automated deep learning‐based CC segmentation tool and hypothesized that its output would correlate with disability. Methods A cohort of 631 MS patients (449 females, baseline age 41 ± 11 years) with both 3‐dimensional T1‐weighted and T2‐weighted fluid‐attenuated inversion recovery (FLAIR) MRI was used for the development. Data from 204 patients were manually segmented to train convolutional neural networks in extracting the midsagittal intracranial and CC areas. Remaining data were used to compare segmentations with FreeSurfer and benchmark the outputs with regard to clinical correlations. A 1.5 and 3 Tesla reproducibility cohort of 9 MS patients evaluated the segmentation robustness. Results The deep learning‐based tool was accurate in selecting the appropriate slice for segmentation (98% accuracy within 3 mm of the manual ground truth) and segmenting the CC (Dice coefficient .88‐.91) and intracranial areas (.97‐.98). The accuracy was lower with higher atrophy. Reproducibility was excellent (intraclass correlation coefficient > .90) for T1‐weighted scans and moderate‐good for FLAIR (.74‐.75). Segmentations were associated with baseline and future (average follow‐up time 6‐7 years) Expanded Disability Status Scale (ρ = –.13 to –.24) and Symbol Digit Modalities Test (r = .18‐.29) scores. Conclusions We present a fully automatic deep learning‐based CC segmentation tool optimized to modern imaging in MS with clinical correlations on par with computationally expensive alternatives.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis

Brusini

Plattén

Ouellette

et al. 2022

Journal of Neuroimaging

View full text Add to dashboard Cite

show abstract

“…All ROIs were visually examined by one rater (EE) for registration errors with respect to the subject's anatomical MR images. Five of 16 PwMS had errors caused by inaccurate registration, reflected as an overestimation of the superior border of the CC body due to drastic differences in CC morphology in MS patients, in whom callosal atrophy is commonly reported 31 . All misaligned ROIs were manually edited to better fit the anatomy (EE).…”

Section: Methodsmentioning

confidence: 99%

“…Five of 16 PwMS had errors caused by inaccurate registration, reflected as an overestimation of the superior border of the CC body due to drastic differences in CC morphology in MS patients, in whom callosal atrophy is commonly reported. 31 All misaligned ROIs were manually edited to better fit the anatomy (EE). Images (T 1 -weighted, FLAIR, MWF, and geomT 2IEW ) from a representative participant are shown in Figure 2.…”

Section: Mwi Acquisition and Postprocessingmentioning

confidence: 99%

Associations between myelin water imaging and measures of fall risk and functional mobility in multiple sclerosis

Edwards

Stanley

Daugherty

et al. 2022

Journal of Neuroimaging

View full text Add to dashboard Cite

Background and Purpose: Myelin water fraction (MWF) deficits as measured by myelin water imaging (MWI) have been related to worse motor function in persons with multiple sclerosis (PwMS). However, it is unknown if measures from MWI metrics in motor areas relate to fall risk measures in PwMS. The objective of this study was to examine the relationship between MWI measures in motor areas to performance on clinical measures of fall risk and disability in PwMS. Methods: Sixteen individuals with relapsing-remitting MS participated (1 male, 15 female; age 47.1 years [12.3]; Expanded Disability Status Scale 4.0 [range 0-6.5]) and completed measures of walking and fall risk (Timed 25 Foot Walk [T25FW] and Timed Up and Go). MWF and the geometric mean of the intra-/extracellular water T 2 (geomT 2IEW ) values reflecting myelin content and contribution of large-diameter axons/density, respectively, were assessed in three motor-related regions. Results:The geomT 2IEW of the corticospinal tract (r = -.599; p = .018) and superior cerebellar peduncles (r = -.613; p = .015) demonstrated significant inverse relationships with T25FW, suggesting that decreased geomT 2IEW was related to slower walking. Though not significant, MWF in the corticospinal tract and superior cerebellar peduncles also demonstrated fair relationships with the T25FW, suggesting that worse performance on the T25FW was associated with lower MWF values.Conclusions: MWI of key motor regions was associated with walking performance in PwMS. Further MWI studies are needed to identify relationships between pathology and clinical function in PwMS to guide targeted rehabilitation therapies aimed at preventing falls.

show abstract

“…It was revealed that this might indicate cortical-spinal atrophy and lesion burden. Correlation has also been shown between the structural measurements of the CC and the volumetric properties of the brain (8,9). It was also determined that CC injury is associated with cognitive impairment in MS patients and may be a clinically significant marker of cognitive impairment (10)(11)(12).…”

Section: Introductionmentioning

confidence: 96%

The Relationship Between Structural Measurements of the Corpus Callosum and Disability in Patients with Multiple Sclerosis

et al. 2022

View full text Add to dashboard Cite

Abstract Purpose: The corpus callosum (CC) is the largest commissural pathway connecting both cerebral cortices. Materials and Methods: Forty MS patients and 40 healthy controls were included in this research, which was planned as a prospective and case-control study. Disability was evaluated with the expanded disability rating scale. The number of attacks, disease duration, and MS disease subtype were determined. CC genu, truncus, splenium, and anterior-posterior diameters were measured in brain magnetic resonance imaging TSE/T1 sagittal sequence, and the corpus callosum index (CCI) was calculated using these measurements. The relationship of all these parameters with each other was examined. Results: There were 40 patients (29 females, 11 males) with a mean age of 36.47±11.14 years in the study. In the CC morphometric measurements of the patients, the genu (mean±SD) was 11.46±1.60, truncus (median, min-max) 5.29 (4.6-6.52), splenium 11.09±1.82, anterior-posterior diameter 65.20 (63.64-67.22) and CCI was determined as 0.43±0.05 millimeters. The anterior-posterior diameter was smaller in MS patients (p=0.022). A negative correlation was determined between CCI and disease duration, the number of attacks, and EDSS scores in MS patients (p

show abstract

Corpus callosum index correlates with brain volumetry and disability in multiple sclerosis patients

Abstract: Objectives:To analyze the correlation between corpus callosum index )CCI(, brain volumetry, and disability in multiple sclerosis )MS( patients. The brain volumetry consists of the corpus callosum, cortical gray matter, subcortical gray matter, and white matter volumes.

Cited by 4 publications

References 34 publications

Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis

Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis

Associations between myelin water imaging and measures of fall risk and functional mobility in multiple sclerosis

The Relationship Between Structural Measurements of the Corpus Callosum and Disability in Patients with Multiple Sclerosis

Contact Info

Product

Resources

About