The effect of morphological and microstructural integrity of the corpus callosum on cognition, fatigue and depression in mildly disabled MS patients

Symptom Interconnectivity in Multiple Sclerosis: A Narrative Review of Potential Underlying Biological Disease Processes

Introduction

Fatigue, cognitive impairment, depression, and pain are highly prevalent symptoms in multiple sclerosis (MS). These often co-occur and may be explained by a common etiology. By reviewing existing literature, we aimed to identify potential underlying biological processes implicated in the interconnectivity between these symptoms.

Methods

A literature search was conducted to identify articles reporting research into the biological mechanisms responsible for the manifestation of fatigue, cognitive impairment, depression, and pain in MS. PubMed was used to search for articles published from July 2011 to July 2021. We reviewed and assessed findings from the literature to identify biological processes common to the symptoms of interest.

Results

Of 693 articles identified from the search, 252 were selected following screening of titles and abstracts and assessing reference lists of review articles. Four biological processes linked with two or more of the symptoms of interest were frequently identified from the literature: (1) direct neuroanatomical changes to brain regions linked with symptoms of interest (e.g., thalamic injury associated with cognitive impairment, fatigue, and depression), (2) pro-inflammatory cytokines associated with so-called ‘sickness behavior,’ including manifestation of fatigue, transient cognitive impairment, depression, and pain, (3) dysregulation of monoaminergic pathways leading to depressive symptoms and fatigue, and (4) hyperactivity of the hypothalamic–pituitary-adrenal (HPA) axis as a result of pro-inflammatory cytokines promoting the release of brain noradrenaline, serotonin, and tryptophan, which is associated with symptoms of depression and cognitive impairment.

Conclusion

The co-occurrence of fatigue, cognitive impairment, depression, and pain in MS appears to be associated with a common set of etiological factors, namely neuroanatomical changes, pro-inflammatory cytokines, dysregulation of monoaminergic pathways, and a hyperactive HPA axis. This association of symptoms and biological processes has important implications for disease management strategies and, eventually, could help find a common therapeutic pathway that will impact both inflammation and neuroprotection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-022-00368-2.

Statistical shape analyses of corpus callosum changes at preoperative and postoperative scaphocephaly patients

PURPOSE

Scaphocephaly is the premature closure of the sagittal suture. The treatment strategies mainly focus on correcting the shape of the head, but there are very limited studies examining changes in brain structure. This study aimed to investigate shape differences in the shape of corpus callosum regarding the pre-treatment and post-treatment term at scaphocephaly patients.

METHODS

Cranium shape data were collected from the two-dimensional digital images. The generalized Procrustes analysis was used to obtain mean shapes in the pre- and postoperative phases. The shape deformation of the corpus callosum from the pre- to postoperative phases was evaluated using the thin plate spline method.

RESULTS

There is an enlargement of the splenium part of corpus callosum in the late group. In the early group, corpus callosum genu and body enlargement were observed in the postoperative period compared to the preoperative period, followed by a narrowing of the isthmus region.

CONCLUSION

This study showed structural deformations in the corpus callosum in scaphocephaly patients using head shape with the landmark-based geometric morphometric method by taking into consideration the topographic distribution. An enlargement at the splenium part of corpus callosum exposes after the cranial vault expansion depending on time.

Cortical and white matter lesion topology influences focal corpus callosum atrophy in multiple sclerosis

Background and Purpose

Corpus callosum (CC) atrophy is a strong predictor of multiple sclerosis (MS) disability but the contributing pathological mechanisms remain uncertain. We aimed to apply advanced MRI to explore what drives the often nonuniform callosal atrophy.

Methods

Prospective brain 7 Tesla and 3 Tesla Human Connectom Scanner MRI were performed in 92 MS patients. White matter, leukocortical, and intracortical lesions were manually segmented. FreeSurfer was used to segment the CC and topographically classify lesions per lobe or as deep white matter lesions. Regression models were calculated to predict focal CC atrophy.

Results

The frontal and parietal lobes contained the majority (≥80%) of all lesion classifications in both relapsing‐remitting and secondary progressive MS subtypes. The anterior subsection of the CC had the smallest proportional volume difference between subtypes (11%). Deep, temporal, and occipital white matter lesions, and occipital intracortical lesions were the strongest predictors of middle‐posterior callosal atrophy (adjusted R² = .54‐.39, P < .01).

Conclusions

Both white matter and cortical lesions contribute to regional corpus callosal atrophy. The lobe‐specific lesion topology does not fully explain the inhomogeneous CC atrophy.

Machine learning to investigate superficial white matter integrity in early multiple sclerosis

BACKGROUND AND PURPOSE

This study aims todetermine the sensitivity of superficial white matter (SWM) integrity as a metric to distinguish early multiple sclerosis (MS) patients from healthy controls (HC).

METHODS

Fractional anisotropy and mean diffusivity (MD) values from SWM bundles across the cortex and major deep white matter (DWM) tracts were extracted from 29 early MS patients and 31 age- and sex-matched HC. Thickness of 68 cortical regions and resting-state functional-connectivity (RSFC) among them were calculated. The distribution of structural and functional metrics between groups were compared using Wilcoxon rank-sum test. Utilizing a machine learning method (adaptive boosting), 6 models were built based on: 1-SWM, 2-DWM, 3-SWM and DWM, 4-cortical thickness, or 5-RSFC measures. In model 6, all features from previous models were incorporated. The models were trained with nested 5-folds cross-validation. Area under the receiver operating characteristic curve (AUC_roc ) values were calculated to evaluate classification performance of each model. Permutation tests were used to compare the AUC_roc values.

RESULTS

Patients had higher MD in SWM bundles including insula, inferior frontal, orbitofrontal, superior and medial temporal, and pre- and post-central cortices (p < .05). No group differences were found for any other MRI metric. The model incorporating SWM and DWM features provided the best classification (AUC_roc = 0.75). The SWM model provided higher AUC_roc (0.74), compared to DWM (0.63), cortical thickness (0.67), RSFC (0.63), and all-features (0.68) models (p < .001 for all).

CONCLUSION

Our results reveal a non-random pattern of SWM abnormalities at early stages of MS even before pronounced structural and functional alterations emerge.

Association of brain white matter microstructure with cognitive performance in major depressive disorder and healthy controls: a diffusion-tensor imaging study

Cognitive deficits are central attendant symptoms of major depressive disorder (MDD) with a crucial impact in patients' everyday life. Thus, it is of particular clinical importance to understand their pathophysiology. The aim of this study was to investigate a possible relationship between brain structure and cognitive performance in MDD patients in a well-characterized sample. N = 1007 participants (N_MDD = 482, healthy controls (HC): N_HC = 525) were selected from the FOR2107 cohort for this diffusion-tensor imaging study employing tract-based spatial statistics. We conducted a principal component analysis (PCA) to reduce neuropsychological test results, and to discover underlying factors of cognitive performance in MDD patients. We tested the association between fractional anisotropy (FA) and diagnosis (MDD vs. HC) and cognitive performance factors. The PCA yielded a single general cognitive performance factor that differed significantly between MDD patients and HC (P < 0.001). We found a significant main effect of the general cognitive performance factor in FA (P_tfce-FWE = 0.002) in a large bilateral cluster consisting of widespread frontotemporal-association fibers. In MDD patients this effect was independent of medication intake, the presence of comorbid diagnoses, the number of previous hospitalizations, and depressive symptomatology. This study provides robust evidence that white matter disturbances and cognitive performance seem to be associated. This association was independent of diagnosis, though MDD patients show more pronounced deficits and lower FA values in the global white matter fiber structure. This suggests a more general, rather than the depression-specific neurological basis for cognitive deficits.

Long-term clinical, MRI, and cognitive follow-up in a large cohort of pathologically confirmed, predominantly tumefactive multiple sclerosis

BACKGROUND

Limited studies have described long-term outcomes in pathology confirmed multiple sclerosis (MS).

OBJECTIVES

To describe long-term clinical-radiographic-cognitive outcomes in a prospectively followed cohort of patients with pathologically confirmed CNS demyelinating disease, consistent with MS.

METHODS

Subjects underwent clinical assessment, standardized 3T-MRI brain, and cognitive battery.

RESULTS

Seventy-five patients were included. Biopsied lesion size was ⩾ 2 cm in 62/75. At follow-up, median duration since biopsy was 11 years. Median EDSS was 3 and lesion burden was large (median 10 cm³). At follow-up, 57/75 met MS criteria, 17/75 had clinically isolated syndrome, and 1 radiographic changes only. Disability scores were comparable to a prevalence cohort in Olmsted County (p < 0.001, n = 218). Cognitive outcomes below age-normed standards included psychomotor, attention, working memory, and executive function domains. Total lesion volume and index lesion-related severity correlated with EDSS and cognitive performance. Volumetric cortical/subcortical GM correlated less than lesion metrics to cognitive outcomes.

CONCLUSION

Despite early aggressive course in pathologically confirmed MS, its long-term course was comparable to typical MS in our study. Cognitive impairment in this group seemed to correlate strongest to index lesion severity and total lesion volume. It remains to be established how the aggressive nature of the lesion, biopsy, and treatment affect clinical/cognitive outcomes.

Deep Learning Corpus Callosum Segmentation as a Neurodegenerative Marker in Multiple Sclerosis

BACKGROUND AND PURPOSE

Corpus callosum atrophy is a sensitive biomarker of multiple sclerosis (MS) neurodegeneration but typically requires manual 2D or volumetric 3D-based segmentations. We developed a supervised machine learning algorithm, DeepnCCA, for corpus callosum segmentation and relate callosal morphology to clinical disability using conventional MRI scans collected in clinical routine.

METHODS

In a prospective study of 553 MS patients with 704 acquisitions, 200 unique 2D T₂ -weighted MRI scans were delineated to develop, train, and validate DeepnCCA. Comparative FreeSurfer segmentations were obtained in 504 3D T₁ -weighted scans. Both FreeSurfer and DeepnCCA outputs were correlated with clinical disability. Using principal component analysis of the DeepnCCA output, the morphological changes were explored in relation to clinical disease burden.

RESULTS

DeepnCCA and manual segmentations had high similarity (Dice coefficients 98.1 ± .11%, 89.3 ± .76%, for intracranial and corpus callosum area, respectively through 10-fold cross-validation). DeepnCCA had numerically stronger correlations with cognitive and physical disability as compared to FreeSurfer: Expanded disability status scale (EDSS) ±6 months (r = -.22 P = .002; r = -.17, P = .013), future EDSS (r = -.26, P<.001; r = -.17, P = .012), and future symbol digit modalities test (r = .26, P = .001; r = .24, P = .003). The corpus callosum became thinner with increasing cognitive and physical disability. Increasing physical disability, additionally, significantly correlated with a more angled corpus callosum.

CONCLUSIONS

DeepnCCA (https://github.com/plattenmichael/DeepnCCA/) is an openly available tool that can provide fast and accurate corpus callosum measurements applicable to large MS cohorts, potentially suitable for monitoring disease progression and therapy response.

Brain anatomical correlates of fatigue in multiple sclerosis

Fatigue is one of the most debilitating symptoms in patients with multiple sclerosis (MS). Despite its clinical significance, the aetiology and pathophysiology of MS-related fatigue are not well understood. Current evidence and understanding of the neuroanatomical underpinnings of MS-related fatigue are reviewed in this article. The aims of this paper are to (1) review the findings of previous structural neuroimaging studies on MS-related fatigue and summarize consistent findings regarding brain circuitry associated with fatigue in MS, (2) contextualize these findings with the neurochemistry of the relevant circuits and (3) discuss future perspectives with regard to impact on fatigue management of MS patients and methodological challenges towards improved understanding of fatigue pathogenesis. The detailed understanding of the neuroanatomical underpinnings of fatigue might contribute to the identification of novel treatment targets and factors determining treatment resistance to drugs used in current clinical practice.

The role of functional and structural interhemispheric auditory connectivity for language lateralization - A combined EEG and DTI study

Interhemispheric connectivity between auditory areas is highly relevant for normal auditory perception and alterations are a major factor for the development of auditory verbal hallucinations. Surprisingly, there is no combined EEG-DTI study directly addressing the role of functional and structural connectivity in the same group of subjects. Accordingly, nothing is known about the relationship between functional connectivity such as gamma-band synchrony, structural integrity of the interhemispheric auditory pathways (IAPs) and language lateralization as well as whether the gamma-band synchrony is configured on the backbone of IAPs. By applying multimodal imaging of 64-channel EEG and DTI tractography, we investigated in 27 healthy volunteers the functional gamma-band synchrony between either bilateral primary or secondary auditory cortices from eLORETA source-estimation during dichotic listening, as well as the correspondent IAPs from which fractional anisotropy (FA) values were extracted. Correlation and regression analyses revealed highest values for gamma-band synchrony, followed by FA for secondary auditory cortices, which were both significantly related to a reduced language lateralization. There was no such association between the white-matter microstructure and gamma-band synchrony, suggesting that structural connectivity might also be relevant for other (minor) aspects of information transfer in addition to gamma-band synchrony, which are not detected in the present coupling analyses. The combination of multimodal EEG-DTI imaging provides converging evidence of neural correlates by showing that both stronger pathways and increased gamma-band synchrony within one cohort of subjects are related to a reduced leftward-lateralization for language.

Callosal circularity as an early marker for Alzheimer's disease

Background

Although brain atrophy is considered to be a downstream marker of Alzheimer's disease (AD), subtle changes may allow to identify healthy subjects at risk of developing AD. As the ability to select at-risk persons is considered to be important to assess the efficacy of drugs and as MRI is a widely available imaging technique we have recently developed a reliable segmentation algorithm for the corpus callosum (CC). Callosal atrophy within AD has been hypothesized to reflect both myelin breakdown and Wallerian degeneration.

Methods

We applied our fully automated segmentation and feature extraction algorithm to two datasets: the OASIS database consisting of 316 healthy controls (HC) and 100 patients affected by either mild cognitive impairment (MCI) or Alzheimer's disease dementia (ADD) and a second database that was collected at the Memory Clinic of Hospital Network Antwerp and consists of 181 subjects, including healthy controls, subjects with subjective cognitive decline (SCD), MCI, and ADD. All subjects underwent (among others) neuropsychological testing including the Mini-Mental State Examination (MMSE). The extracted features were the callosal area (CCA), the circularity (CIR), the corpus callosum index (CCI) and the thickness profile.

Results

CIR and CCI differed significantly between most groups. Furthermore, CIR allowed us to discriminate between SCD and HC with an accuracy of 77%. The more detailed callosal thickness profile provided little added value towards the discrimination of the different AD stages. The largest effect of normal ageing on callosal thickness was found in the frontal callosal midbody.

Conclusions

To the best of our knowledge, this is the first study investigating changes in corpus callosum morphometry in normal ageing and AD by exploring both summarizing features (CCA, CIR and CCI) and the complete CC thickness profile in two independent cohorts using a completely automated algorithm. We showed that callosal circularity allows to discriminate between an important subgroup of the early AD spectrum (SCD) and age and sex matched healthy controls.

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Callosal circularity allows to discriminate between subjects with subjective cognitive decline and matched healthy controls

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Callosal circularity is smaller in subjects with AD dementia as compared to matched subjects with mild cognitive impairment

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The callosal thickness profile differs between AD and HC, but not between the different clinical AD stages

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The AD thickness profile strongly correlates with age in HCs

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Callosal circularity correlates with CSF biomarkers (T-tau and P-tau) in MCI.

Corpus callosum atrophy and post-surgical seizures in temporal lobe epilepsy associated with hippocampal sclerosis

OBJECTIVE

Our aim in this retrospective study was to explore whether corpus callosum atrophy could predict the post-surgical seizure control in patients with temporal lobe epilepsy associated with Hippocampal Sclerosis (HS).

METHODS

We used the Corpus Callosum Index (CCI) obtained from best mid-sagittal T2/FLAIR or T1-weighted MRI at two time-points, more than one year apart. CCI has been mainly used in Multiple Sclerosis (MS), but not in epilepsy, so we tested the validity of our results performing a proof of concept cohort, incorporating MS patients with and without epilepsy. Then, we explored this measurement in a well-characterized and long-term cohort of patients with temporal lobe epilepsy associated with HS.

RESULTS

In the proof of concept cohort (MS without epilepsy n:40, and MS with epilepsy, n:15), we found a larger CCI atrophy rate in MS patients with poor epilepsy control vs. MS without epilepsy (p:0.01). Then, in HS patients (n:74), annualized CCI atrophy rate was correlated with the long-term Engel scale (Rho:0.31, p:0.007). In patients with post-surgical seizure recurrence, a larger CCI atrophy rate was found one year before any seizure relapse. Univariate analysis showed an increased risk of seizure recurrence in males, higher pre-surgical seizure frequency, necessity of invasive EEG monitoring, and higher CCI atrophy rate. Two of these variables were independent predictors in the multivariate analysis, male gender (HR:4.87, p:0.002) and CCI atrophy rate (HR:1.21, p:0.001).

CONCLUSION

We demonstrated that atrophy of the corpus callosum, using the CCI, is related with poor seizure control in two different neurological disorders presenting with epilepsy, which might suggest that corpus callosum atrophy obtained in early post-surgical follow-up, could be a biomarker for predicting recurrences and guiding treatment plans.

Reduced GABA levels correlate with cognitive impairment in patients with relapsing-remitting multiple sclerosis

OBJECTIVES

To investigate if brain gamma-aminobutyric acid (GABA) levels in patients with relapsing-remitting multiple sclerosis (RRMS) are abnormal compared with healthy controls, and their relationship to cognitive function in RRMS.

METHODS

Twenty-eight RRMS patients and twenty-six healthy controls underwent magnetic resonance spectroscopy (MRS) at 3-T to detect GABA signals from posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC) and left hippocampus using the 'MEGAPoint Resolved Spectroscopy Sequence' (MEGA-PRESS) technique. All subjects also underwent a cognitive assessment.

RESULTS

In RRMS patients, GABA+ were lower in the PCC (p = 0.036) and left hippocampus (p = 0.039) compared with controls, decreased GABA+ in the PCC and left hippocampus were associated with specific cognitive functions (r = -0.452, p = 0.016 and r = 0.451, p = 0.016 respectively); GABA+ in the mPFC were not significantly decreased or related to any cognitive scores (p > 0.05).

CONCLUSIONS

This study demonstrates that abnormalities of the GABAergic system may be present in the pathogenesis of RRMS and suggests a potential link between regional GABA levels and cognitive impairment in patients with RRMS.

KEY POINTS

• GABA levels may decrease in patients with RRMS. • Lower GABA levels correlated with worse cognitive performance in patients with RRMS. • Dysfunctional GABAergic neurotransmission may have a role in cognitive impairment in RRMS.