Reliability of measuring regional callosal atrophy in neurodegenerative diseases

Microstructural Changes in the Corpus Callosum in Neurodegenerative Diseases

The corpus callosum, the largest white matter structure in the brain, plays a crucial role in interhemispheric communication and cognitive function. This review examines the microstructural changes observed in the corpus callosum across various neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis (ALS). New neuroimaging studies, mainly those that use diffusion tensor imaging (DTI) and advanced tractography methods, were put together to show how changes have happened in the organization of white matter and the connections between them. Some of the most common ways the corpus callosum breaks down are discussed, including less fractional anisotropy, higher mean diffusivity, and atrophy in certain regions. The relationship between these microstructural changes and cognitive decline, motor dysfunction, and disease progression is explored. Additionally, we consider the potential of corpus callosum imaging as a biomarker for early disease detection and monitoring. Studies show that people with these disorders have lower fractional anisotropy and higher mean diffusivity in the corpus callosum, often in ways that are specific to the disease. These changes often happen before gray matter atrophy and are linked to symptoms, which suggests that the corpus callosum could be used as an early sign of neurodegeneration. The review also highlights the implications of these findings for understanding disease mechanisms and developing therapeutic strategies. Future directions, including the application of advanced imaging techniques and longitudinal studies, are discussed to elucidate the role of corpus callosum degeneration in neurodegenerative processes. This review underscores the importance of the corpus callosum in understanding the pathophysiology of neurodegenerative diseases and its potential as a target for therapeutic interventions.

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.

A biocompatible and injectable hydrogel to boost the efficacy of stem cells in neurodegenerative diseases treatment

AIMS

Stem cell therapies emerged as treatment modalities with potential to cure neurodegenerative diseases (NDs). However, despite high expectations, their clinical use is still limited. Critical issues in treatment outcomes may be related to stem cells formulation and administration route. We develop a hydrogel as a cell carrier, consisting of compounds (phospholipids and hyaluronic acid-HA) naturally present in the central nervous system (CNS). The HA-based hydrogel physically crosslinked with liposomes is designed for direct injection into the CNS to significantly increase the bone marrow mesenchymal stem cells (BMSCs) bioavailability.

MATERIALS AND METHODS

Hydrogel compatibility is confirmed in vitro with BMSCs and in vivo through its intracerebroventricular injection in rats. To assess its efficacy, the main cause of chronic neurologic disability in young adults is selected, namely multiple sclerosis (MS). The efficacy of the developed formulation containing a lower number of cells than previously reported is demonstrated using an experimental autoimmune encephalomyelitis (EAE) rat model.

KEY FINDINGS

The distribution of the engineered hydrogel into corpus callosum can be ideal for NDs treatment, since damage of this white matter structure is responsible for important neuronal deficits. Moreover, the BMSCs-laden hydrogel significantly decreases disease severity and maximum clinical score and eliminated the relapse.

SIGNIFICANCE

The engineering of advanced therapies using this natural carrier can result in efficacious treatments for MS and related debilitating conditions.

Corpus Callosum Integrity Relates to Improvement of Upper-Extremity Function Following Intensive Rehabilitation in Children With Unilateral Spastic Cerebral Palsy

BACKGROUND

The corpus callosum (CC) plays an important role in upper extremity (UE) function. The impact on UE function in children with unilateral spastic cerebral palsy (USCP) and improvements following intensive interventions remain unknown.

OBJECTIVES

To examine the (1) relationship between UE function and CC integrity and (2) relationship between CC integrity and changes in UE function following intensive interventions.

METHODS

We retrospectively analyzed clinical and neuroimaging data from a sample of convenience of 44 participants (age 9.40 ± 3.10 years) from 2 larger trials. Participants received 90 hours of Hand-Arm Bimanual Intensive Therapy (HABIT) or Constraint-Induced Movement Therapy (CIMT). Unimanual dexterity (Jebsen-Taylor Test of Hand Function [JTTHF]) and bimanual performance (Assisting Hand Assessment [AHA]) were assessed preintervention and postintervention. CC tractography was reconstructed with diffusion tensor imaging (DTI) and segmented into 3 regions (genu, midbody, splenium). Pearson correlations and regression were used to assess the relationship between outcomes and DTI parameters (ie, fractional anisotropy [FA], number of streamlines, and mean, radial, and axial diffusivity).

RESULTS

Both groups improved in bimanual performance (P < .01). The CIMT group improved in unimanual dexterity (P < .01). Baseline unimanual dexterity and bimanual performance correlated with FA and number of streamlines for most CC regions (P < .05). Following CIMT, pre-post changes in JTTHF were negatively correlated with axial and radial diffusivity of the CC, and AHA with splenium and number of streamlines for the CC, midbody, and splenium (all P < .05). Following HABIT, midbody FA was positively correlated with pre-post AHA changes (r = 0.417; P = .042).

CONCLUSIONS

CC integrity is important for UE function in children with USCP.

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.

MRI-Based Manual versus Automated Corpus Callosum Volumetric Measurements in Multiple Sclerosis

BACKGROUND AND PURPOSE

Corpus callosum atrophy is a neurodegenerative biomarker in multiple sclerosis (MS). Manual delineations are gold standard but subjective and labor intensive. Novel automated methods are promising but require validation. We aimed to compare the robustness of manual versus automatic corpus callosum segmentations based on FreeSurfer.

METHODS

Nine MS patients (6 females, age 38 ± 13 years, disease duration 7.3 ± 5.2 years) were scanned twice with repositioning using 3-dimensional T₁ -weighted magnetic resonance imaging on three scanners (two 1.5 T and one 3.0 T), that is, six scans/patient, on the same day. Normalized corpus callosum areas were measured independently by a junior doctor and neuroradiologist. The cross-sectional and longitudinal streams of FreeSurfer were used to segment the corpus callosum volume.

RESULTS

Manual measurements had high intrarater (junior doctor .96 and neuroradiologist .96) and interrater agreement (.94), by intraclass correlation coefficient (P < .001). The coefficient of variation was lowest for longitudinal FreeSurfer (.96% within scanners; 2.0% between scanners) compared to cross-sectional FreeSurfer (3.7%, P = .001; 3.8%, P = .058) and the neuroradiologist (2.3%, P = .005; 2.4%, P = .33). Longitudinal FreeSurfer was also more accurate than cross-sectional (Dice scores 83.9 ± 7.5% vs. 78.9 ± 8.4%, P < .01 relative to manual segmentations). The corpus callosum measures correlated with physical disability (longitudinal FreeSurfer r = -.36, P < .01; neuroradiologist r = -.32, P < .01) and cognitive disability (longitudinal FreeSurfer r = .68, P < .001; neuroradiologist r = .64, P < .001).

CONCLUSIONS

FreeSurfer's longitudinal stream provides corpus callosum measures with better repeatability than current manual methods and with similar clinical correlations. However, due to some limitations in accuracy, caution is warranted when using FreeSurfer with clinical data.

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.

Translocator Protein-18 kDa (TSPO) Positron Emission Tomography (PET) Imaging and Its Clinical Impact in Neurodegenerative Diseases

In vivo exploration of activated microglia in neurodegenerative diseases is achievable by Positron Emission Tomography (PET) imaging, using dedicated radiopharmaceuticals targeting the translocator protein-18 kDa (TSPO). In this review, we emphasized the major advances made over the last 20 years, thanks to TSPO PET imaging, to define the pathophysiological implication of microglia activation and neuroinflammation in neurodegenerative diseases, including Parkinson’s disease, Huntington’s disease, dementia, amyotrophic lateral sclerosis, multiple sclerosis, and also in psychiatric disorders. The extent and upregulation of TSPO as a molecular biomarker of activated microglia in the human brain is now widely documented in these pathologies, but its significance, and especially its protective or deleterious action regarding the disease’s stage, remains under debate. Thus, we exposed new and plausible suggestions to enhance the contribution of TSPO PET imaging for biomedical research by exploring microglia’s role and interactions with other cells in brain parenchyma. Multiplex approaches, associating TSPO PET radiopharmaceuticals with other biomarkers (PET imaging of cellular metabolism, neurotransmission or abnormal protein aggregates, but also other imaging modalities, and peripheral cytokine levels measurement and/or metabolomics analysis) was considered. Finally, the actual clinical impact of TSPO PET imaging as a routine biomarker of neuroinflammation was put into perspective regarding the current development of diagnostic and therapeutic strategies for neurodegenerative diseases.