Brain volumes quantification from MRI in healthy controls: Assessing correlation, agreement and robustness of a convolutional neural network-based software against FreeSurfer, CAT12 and FSL

Association Between White Matter Hyperintensity and Cognitive Impairment in Cerebral Small Vessel Disease: The Frequency-dependent Role of Brain Functional Activity

BACKGROUND

Cognitive dysfunction in cerebral small vessel disease (CSVD) patients is associated with white matter hyperintensity (WMH), which demonstrates frequency-dependent correlations with brain functional activities. However, the neural mechanisms underlying the relationship between these structural and functional abnormalities and cognitive impairment remain unclear.

METHODS

We recruited 34 CSVD patients (mean age 63.74 ± 4.85 years, 19 males) and 45 age-matched healthy controls (mean age 63.69 ± 6.15 years, 15 males). All participants underwent magnetic resonance imaging (MRI) scanning and comprehensive cognitive assessments, including three behavioral tasks and a cognitive questionnaire battery. Regional brain activity and network topological properties were separately compared between the two groups for each of the three frequency bands (slow-4, slow-5, and typical band) using two-sample t-tests. Simple and multiple mediation analyses were performed to examine the relationships among WMH, functional brain measures, and global cognition.

RESULTS

CSVD patients exhibited frequency-specific alterations in regional activity and reduced global functional organization in the slow-4 band. Frequency-dependent functional measures in the slow-4 band significantly mediated the relationship between deep WMH and cognitive performance.

CONCLUSION

Our findings demonstrate the frequency-specific mediating role of abnormal brain functions in the pathophysiological pathway linking WMHs to cognitive impairment. This study provides new insight into the pathological mechanisms underlying WMH-related cognitive dysfunction.

CLINICAL TRIAL REGISTRATION

ChiCTR2100043346, 02 November 2021, https://www.chictr.org.cn/showproj.html?proj=52285.

Impact of oral Cladribine on paramagnetic rim lesions of Multiple Sclerosis patients

BACKGROUND

Paramagnetic rim lesions (PRLs), marked by chronic inflammation and iron-loaded microglia, are linked to severe disease progression in multiple sclerosis (MS). The impact of cladribine, an immune reconstitution therapy, on PRLs remains underexplored.

OBJECTIVE

To evaluate the effect of cladribine tablets on PRLs in relapsing-remitting MS (RRMS) patients and explore the association between PRLs dynamics and brain atrophy.

METHODS

We conducted a retrospective analysis of 52 RRMS patients treated with cladribine in Buenos Aires between 2018 and 2021. Brain MRIs were analyzed at baseline, 12, and 24 months post-treatment, focusing on PRLs count and brain volume measurements. Statistical analyses included Wilcoxon tests, Poisson mixed models, and linear mixed models.

RESULTS

The cohort included 52 patients (32 women) with a median age of 36 years (range 21-66 years). PRLs were present in 61.5% of patients at baseline. Cladribine treatment significantly reduced PRLs count (IRR=0.68, 95% CI [0.49, 0.95], p=0.02), independent of prior treatment or disease activity. While no significant relationship was found between PRLs changes and overall brain atrophy, a significant interaction between PRLs dynamics and atrophy in the right thalamus was observed (p<0.05).

CONCLUSION

Cladribine tablets are associated with a reduction in PRLs in RRMS patients, potentially influencing regional brain atrophy over time.

Towards contrast-agnostic soft segmentation of the spinal cord

Spinal cord segmentation is clinically relevant and is notably used to compute spinal cord cross-sectional area (CSA) for the diagnosis and monitoring of cord compression or neurodegenerative diseases such as multiple sclerosis. While several semi and automatic methods exist, one key limitation remains: the segmentation depends on the MRI contrast, resulting in different CSA across contrasts. This is partly due to the varying appearance of the boundary between the spinal cord and the cerebrospinal fluid that depends on the sequence and acquisition parameters. This contrast-sensitive CSA adds variability in multi-center studies where protocols can vary, reducing the sensitivity to detect subtle atrophies. Moreover, existing methods enhance the CSA variability by training one model per contrast, while also producing binary masks that do not account for partial volume effects. In this work, we present a deep learning-based method that produces soft segmentations of the spinal cord that are stable across MRI contrasts. Using the Spine Generic Public Database of healthy participants (n=267; contrasts=6), we first generated participant-wise soft ground truth (GT) by averaging the binary segmentations across all 6 contrasts. These soft GT, along with aggressive data augmentation and a regression-based loss function, were then used to train a U-Net model for spinal cord segmentation. We evaluated our model against state-of-the-art methods and performed ablation studies involving different GT mask types, loss functions, contrast-specific models and domain generalization methods. Our results show that using the soft average segmentations along with a regression loss function reduces CSA variability (p<0.05, Wilcoxon signed-rank test). The proposed spinal cord segmentation model generalizes better than the state-of-the-art contrast-specific methods amongst unseen datasets, vendors, contrasts, and pathologies (compression, lesions), while accounting for partial volume effects. Our model is integrated into the Spinal Cord Toolbox (v6.2 and higher).

Dysregulation of the molecular clock by blood-borne factors in Alzheimer's disease patients

BACKGROUND

Circadian disruptions are increasingly recognized in Alzheimer's disease (AD) patients and may influence disease onset and progression. This study examines how AD pathology affects blood-borne factors that regulate circadian rhythms.

METHODS

Eighty-five participants from the Sino Longitudinal Study on Cognitive Decline were enrolled: 35 amyloid-beta negative normal controls (Aβ- NCs), 23 amyloid-beta positive normal controls (Aβ+ NCs), 15 patients with amnestic mild cognitive impairment (aMCI), and 12 with Alzheimer's disease dementia (ADD). Patients with aMCI and ADD were grouped as cognitively impaired (CI). Cellular circadian period length was assessed using a serum-based assay. Expression levels of clock genes in serum-treated cells and in leukocytes of participants were measured via real-time PCR. Plasma biomarkers were quantified using a single-molecule array immunoassay. Pineal parenchymal and hippocampal volumes were determined by magnetic resonance imaging.

RESULTS

The cellular circadian period length was significantly extended by serum from CI patients than by that from Aβ- NCs (p < 0.01). Treatment of cells with serum from the CI patients resulted in suppressed expression of the clock genes Bmal1 and Nr1d1. Strong relationships between the expression levels of clock genes observed in leukocytes of the Aβ- NC group did not appear in those of the Aβ+ NC or CI groups. The significant correlation of cellular circadian period length and the pineal volume was only observed in the Aβ- NC group, but not in the Aβ+ NC or CI groups.

CONCLUSIONS

This study indicates the presence of significant changes in blood-borne factors that could affect the circadian rhythms in AD, starting even at preclinical stages. These alterations could precede cognitive decline and contribute to AD pathogenesis.

TRIAL REGISTRATION

The cohort is registered at ClinicalTrials.gov (SILCODE: NCT03370744; Registered on Mar 15th, 2017).

The utility of customised tissue probability maps and templates for patients with idiopathic normal pressure hydrocephalus: a computational anatomy toolbox (CAT12) study

BACKGROUND

Disproportionately enlarged subarachnoid space hydrocephalus (DESH) is one of the neuroradiological characteristics of idiopathic normal pressure hydrocephalus (iNPH), which makes statistical analyses of brain images difficult. This study aimed to develop and validate methods of accurate brain segmentation and spatial normalisation in patients with DESH by using the Computational Anatomy Toolbox (CAT12).

METHODS

Two hundred ninety-eight iNPH patients with DESH and 25 healthy controls (HCs) who underwent cranial MRI were enrolled in this study. We selected the structural images of 169 patients to create customised tissue probability maps and diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) templates for patients with DESH (DESH-TPM and DESH-Template). The structural images of 38 other patients were used to evaluate the validity of the DESH-TPM and DESH-Template. DESH-TPM and DESH-Template were created using the 114 well-segmented images after the segmentation processing of CAT12. In the validation study, we compared the accuracy of brain segmentation and spatial normalisation among three conditions: customised condition, applying DESH-TPM and DESH-Template to CAT12 and patient images; standard condition, applying the default setting of CAT12 to patient images; and reference condition, applying the default setting of CAT12 to HC images.

RESULTS

In the validation study, we identified three error types during segmentation. (1) The proportions of misidentifying the dura and/or extradural structures as brain structures in the customised, standard, and reference conditions were 10.5%, 44.7%, and 13.6%, respectively; (2) the failure rates of white matter hypointensity (WMH) cancellation in the customised, standard, and reference conditions were 18.4%, 44.7%, and 0%, respectively; and (3) the proportions of cerebrospinal fluid (CSF)-image deficits in the customised, standard, and reference conditions were 97.4%, 84.2%, and 28%, respectively. The spatial normalisation accuracy of grey and white matter images in the customised condition was the highest among the three conditions, especially in terms of superior convexity.

CONCLUSIONS

Applying the combination of the DESH-TPM and DESH-Template to CAT12 could improve the accuracy of grey and white matter segmentation and spatial normalisation in patients with DESH. However, this combination could not improve the CSF segmentation accuracy. Another approach is needed to overcome this challenge.

Serum neurofilament light chain predicts spinal cord atrophy in neuromyelitis optica spectrum disorder

Levels of serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein (sGFAP) are useful biomarkers of disease activity and disability in neuromyelitis optica spectrum disorder (NMOSD). Here we investigated the association of sNfL and sGFAP levels with brain and spinal cord volumes in patients with NMOSD. Fifteen patients with NMOSD were enrolled in this prospective study. The median baseline level of sNfL was 42.2 (IQR, 16.1-72.6) pg/mL and decreased to 8.5 (IQR, 7.4-16.6) pg/mL at the end of the study. The reduction in sNfL was associated with a 7.5% loss of cervical spinal cord volume (CSCV) (p = 0.001). The levels of sGFAP reduced from 239.2 (IQR, 139.0-3393.3) pg/mL at baseline to 108.5 (IQR, 74.2-154.6) pg/mL. However, there was no strong correlation between sGFAP levels and CSCV changes during the follow-up period. Our data suggested that sNfL level is a useful biomarker for predicting spinal cord atrophy in patients with NMOSD.

Emerging Applications of Radiomics in Neurological Disorders: A Review

Radiomics has achieved significant momentum in radiology research and can reveal image information invisible to radiologists' eyes. Radiomics first evolved for oncologic imaging. Oncologic applications (histopathology, tumor grading, gene mutation analysis, patient survival, and treatment response prediction) of radiomics are widespread. However, it is not limited to oncologic analysis, and any digital medical images can benefit from radiomics analysis. This article reviews the current literature on radiomics in non-oncologic, neurological disorders including ischemic strokes, hemorrhagic stroke, cerebral aneurysms, and demyelinating disorders.