Spinal cord reserve in multiple sclerosis

Disability Moderates Dual Task Walking Performance and Neural Efficiency in Older Adults With Multiple Sclerosis

BACKGROUND

Mobility and cognitive impairment are prevalent and co-occurring in older adults with multiple sclerosis (OAMS), yet there is limited research concerning the role of disability status in the cognitive control of gait among OAMS.

OBJECTIVE

We investigated the levels of prefrontal cortex (PFC) activation, using oxygenated hemoglobin (HbO2), during cognitively-demanding tasks in OAMS with lower and higher disability using functional near-infrared spectroscopy (fNIRS) to: (1) identify PFC activation differences in single task walk and cognitively-demanding tasks in OAMS with different levels of disability; and (2) evaluate if disability may moderate practice-related changes in neural efficiency in OAMS.

METHODS

We gathered data from OAMS with lower (n = 51, age = 65 ± 4 years) or higher disability (n = 48, age = 65 ± 5 years), using a cutoff of 3 or more, in the Patient Determined Disease Steps, for higher disability, under 3 different conditions (single-task walk, Single-Task-Alpha, and Dual-Task-Walk [DTW]) administered over 3 counterbalanced, repeated trials.

RESULTS

OAMS who had a lower disability level exhibited decreased PFC activation levels during Single-Task-Walk (STW) and larger increases in PFC activation levels, when going from STW to a cognitively-demanding task, such as a DTW, than those with higher disability. OAMS with a lower disability level exhibited greater declines in PFC activation levels with additional within session practice than those with a higher disability level.

CONCLUSIONS

These findings suggest that disability moderates brain adaptability to cognitively-demanding tasks and demonstrate the potential for fNIRS-derived outcome measures to complement neurorehabilitation outcomes.

Understanding multiple sclerosis as a disease spectrum: above and below the clinical threshold

PURPOSE OF REVIEW

Research in multiple sclerosis (MS) has long been predicated on clinical groupings that do not reflect the underlying biologic heterogeneity apparent within patient populations. This review explicates the various levels of explanation through which the spectrum of disease is described and investigated both above and below the clinical threshold of detection, as framed by the topographical model of MS, to help advance a cogent mechanistic framework.

RECENT FINDINGS

Contemporary evidence has amended the view of MS as consisting of sequential disease phases in favor of a spectrum of disease with an admixture of interdependent and dynamic pathobiological axes driving tissue injury and progression. Recent studies have shown the presence of acute and compartmentalized inflammation and mechanisms of neurodegeneration beginning early and evolving throughout the disease continuum. Still, the gap between the understanding of immunopathologic processes in MS and the tools used to measure relevant molecular, laboratory, radiologic, and clinical metrics needs attention to enable better prognostication of disease and monitoring for changes along specific pathologic axes and variable treatment outcomes.

SUMMARY

Aligning on a consistently-applied mechanistic framework at distinct levels of explanation will enable greater precision across bench and clinical research, and inform discourse on drivers of disability progression and delivery of care for individuals with MS.

Defining the concept of reserve in the motor domain: a systematic review

A reserve in the motor domain may underlie the capacity exhibited by some patients to maintain motor functionality in the face of a certain level of disease. This form of "motor reserve" (MR) could include cortical, cerebellar, and muscular processes. However, a systematic definition has not been provided yet. Clarifying this concept in healthy individuals and patients would be crucial for implementing prevention strategies and rehabilitation protocols. Due to its wide application in the assessment of motor system functioning, non-invasive brain stimulation (NIBS) may support such definition. Here, studies focusing on reserve in the motor domain and studies using NIBS were revised. Current literature highlights the ability of the motor system to create a reserve and a possible role for NIBS. MR could include several mechanisms occurring in the brain, cerebellum, and muscles, and NIBS may support the understanding of such mechanisms.

Association of Mean Upper Cervical Spinal Cord Cross-Sectional Area With Cerebral Small Vessel Disease: A Community-Based Cohort Study

BACKGROUND

The purpose of this study was to investigate the association between the mean upper cervical spinal cord cross-sectional area (MUCCA) and the risk and severity of cerebral small vessel disease (CSVD).

METHODS

Community-dwelling residents in Lishui City, China, from the cross-sectional survey in the PRECISE cohort study (Polyvascular Evaluation for Cognitive Impairment and Vascular Events) conducted from 2017 to 2019. We included 1644 of 3067 community-dwelling adults in the PRECISE study after excluding those with incorrect, incomplete, insufficient, or missing clinical or imaging data. Total and modified total CSVD scores, as well as magnetic resonance imaging features, including white matter hyperintensity, lacunes, cerebral microbleeds, enlarged perivascular spaces, and brain atrophy, were assessed at the baseline. The Spinal Cord Toolbox was used to measure the upper cervical spinal cord cross-sectional area of the C1 to C3 segments of the spinal cord and its average value was taken as MUCCA. Participants were divided into 4 groups according to quartiles of MUCCA. Associations were analyzed using linear regression models adjusted for age, sex, current smoking and drinking, medical history, intracranial volume, and total cortical volume.

RESULTS

The means±SD age of the participants was 61.4±6.5 years, and 635 of 1644 participants (38.6%) were men. The MUCCA was smaller in patients with CSVD than those without CSVD. Using the total CSVD score as a criterion, the MUCCA was 61.78±6.12 cm2 in 504 of 1644 participants with CSVD and 62.74±5.94 cm2 in 1140 of 1644 participants without CSVD. Using the modified total CSVD score, the MUCCA was 61.81±6.04 cm2 in 699 of 1644 participants with CSVD and 62.91±5.94 cm2 in 945 of 1644 without CSVD. There were statistical differences between the 2 groups after adjusting for covariates in 3 models. The MUCCA was negatively associated with the total and modified total CSVD scores (adjusted β value, -0.009 [95% CI, -0.01 to -0.003] and -0.007 [95% CI, -0.01 to -0.0006]) after adjustment for covariates. Furthermore, the MUCCA was negatively associated with the white matter hyperintensity burden (adjusted β value, -0.01 [95% CI, -0.02 to -0.003]), enlarged perivascular spaces in the basal ganglia (adjusted β value, -0.005 [95% CI, -0.009 to -0.001]), lacunes (adjusted β value, -0.004 [95% CI, -0.007 to -0.0007]), and brain atrophy (adjusted β value, -0.009 [95% CI, -0.01 to -0.004]).

CONCLUSIONS

The MUCCA and CSVD were correlated. Spinal cord atrophy may serve as an imaging marker for CSVD; thus, small vessel disease may involve the spinal cord in addition to being intracranial.

Differentiating multiple sclerosis from non-specific white matter changes using a convolutional neural network image classification model

BACKGROUND

The diagnosis of multiple sclerosis (MS) relies heavily on neuroimaging with magnetic resonance imaging (MRI) and exclusion of mimics. This can be a challenging task due to radiological overlap in several disorders and may require ancillary testing or longitudinal follow up. One of the most common radiological MS mimickers is non-specific white matter disease (NSWMD). We aimed to develop and evaluate models leveraging machine learning algorithms to help distinguish MS and NSWMD.

METHODS

All adult patients who underwent MRI brain using a demyelinating protocol with available electronic medical records between 2015 and 2019 at Cleveland Clinic affiliated facilities were included. Diagnosis of MS and NSWMD were assessed from clinical documentation. Those with a diagnosis of MS and NSWMD were matched using total T2 lesion volume (T2LV) and used to train models with logistic regression and convolutional neural networks (CNN). Performance metrices were reported for each model.

RESULTS

A total of 250 NSWMD MRI scans were identified, and 250 unique MS MRI scans were matched on T2LV. Cross validated logistic regression model was able to use 20 variables (including spinal cord area, regional volumes, and fractions) to predict MS compared to NSWMD with 68.0% accuracy while the CNN model was able to classify MS compared to NSWMD in two independent validation and testing cohorts with 77% and 78% accuracy on average.

CONCLUSION

Automated methods can be used to differentiate MS compared to NSWMD. These methods can be used to supplement currently available diagnostic tools for patients being evaluated for MS.

Brain and cognitive reserve mitigate balance dysfunction in multiple sclerosis

BACKGROUND

Approximately two-thirds of patients with multiple sclerosis (MS) complain different degrees of balance dysfunction, but some of them are able to withstand considerable disease burden without an overt balance impairment. Here, we tested the hypothesis that brain and cognitive reserve lessen the effect of MS-related tissue damage on balance control.

METHODS

We measured the postural sway of 148 patients and 74 sex- and age-matched healthy controls by force platform under different conditions reflecting diverse neuro-pathological substrates of balance dysfunction: eyes opened (EO), eyes closed (EC), and while performing the Stroop test, i.e., dual-task (DT). Lesion volumes on T2-hyperintense and T1-hypointense sequences, and normalized brain volume provided estimations of MS-related tissue damage in patients with MS. Hierarchical linear regressions explored the protective effect against the MS-related tissue damage of intracranial volume and educational attainment (proxies for brain and cognitive reserve, respectively) on balance.

RESULTS

Larger intracranial volume and high educational attainment mitigated the detrimental effect of MS-related tissue damage on postural sway under EO (adjusted-R2=0.20 and 0.27, respectively, p<0.01) and DT (adjusted-R2=0.22 and 0.30, respectively, p<0.06) conditions. Neither educational level nor brain size was associated with postural sway under EC condition.

CONCLUSION

Our findings suggest a protective role of brain and cognitive reserve even on balance, an outcome that relies on both motor control and higher order processing resources. The lack of a protective effect on postural sway under EC condition confirms that this latter outcome is closer associated with spinal cord rather than brain damage.

Validation of a New Semiautomated Segmentation Pipeline Based on the Spinal Cord Toolbox DeepSeg Algorithm to Estimate the Cervical Canal Area

BACKGROUND AND PURPOSE

As in the brain reserve concept, a larger cervical canal area may also protect against disability. In this context, a semiautomated pipeline has been developed to obtain quantitative estimations of the cervical canal area. The aim of the study was to validate the pipeline, to evaluate the consistency of the cervical canal area measurements during a 1-year period, and to compare cervical canal area estimations obtained from brain and cervical MRI acquisitions.

MATERIALS AND METHODS

Eight healthy controls and 18 patients with MS underwent baseline and follow-up 3T brain and cervical spine sagittal 3D MPRAGE. The cervical canal area was measured in all acquisitions, and estimations obtained with the proposed pipeline were compared with manual segmentations performed by 1 evaluator using the Dice similarity coefficient. The cervical canal area estimations obtained on baseline and follow-up T1WI were compared; brain and cervical cord acquisitions were also compared using the individual and average intraclass correlation coefficients.

RESULTS

The agreement between the manual cervical canal area masks and the masks provided by the proposed pipeline was excellent, with a mean Dice similarity coefficient mean of 0.90 (range, 0.73-0.97). The cervical canal area estimations obtained from baseline and follow-up scans showed a good level of concordance (intraclass correlation coefficient = 0.76; 95% CI, 0.44-0.88); estimations obtained from brain and cervical MRIs also had good agreement (intraclass correlation coefficient = 0.77; 95% CI, 0.45-0.90).

CONCLUSIONS

The proposed pipeline is a reliable tool to estimate the cervical canal area. The cervical canal area is a stable measure across time; moreover, when cervical sequences are not available, the cervical canal area could be estimated using brain T1WI.