Prefrontal cortical thickness in motor neuron disease

Active elite rugby participation is associated with altered precentral cortical thickness

There is growing concern that elite rugby participation may negatively influence brain health, but the underlying mechanisms are unclear. Cortical thickness is a widely applied biomarker of grey matter structure, but there is limited research into how it may be altered in active professional rugby players. Cross-sectional MRI data from 44 active elite rugby players, including 21 assessed within 1 week of head injury, and 47 healthy controls were analysed. We investigated how active elite rugby participation with and without sub-acute traumatic brain injury influenced grey matter structure using whole cortex and region of interest cortical thickness analyses. Relationships between cortical thickness and biomarkers of traumatic brain injury, including fractional anisotropy, plasma neurofilament light and glial fibrillary acidic protein, were also examined. In whole-cortex analyses, precentral cortical thickness in the right hemisphere was lower in rugby players compared with controls, which was due to reductions in non-injured players. Post hoc region of interest analyses showed non-injured rugby players had reduced cortical thickness in the inferior precentral sulcal thickness bilaterally (P = 0.005) and the left central sulcus (P = 0.037) relative to controls. In contrast, players in the sub-acute phase of mild traumatic brain injury had higher inferior precentral sulcal cortical thickness in the right hemisphere (P = 0.015). Plasma glial fibrillary acidic protein, a marker of astrocyte activation, was positively associated with right inferior precentral sulcal cortical thickness in injured rugby players (P = 0.0012). Elite rugby participation is associated with localized alterations in cortical thickness, specifically in sulcal motor regions. Sub-acute changes after mild traumatic brain injury are associated with evidence of astrocytic activation. The combination of cortical thickness and glial fibrillary acidic protein may be useful in understanding the pathophysiological relationship between sporting head injury and brain health.

M1/precuneus ratio as a surrogate marker of upper motor neuron sign in ALS

OBJECTIVE

To investigate whether primary motor cortex (M1) volume measured with an automated approach in MRI reflects upper motor neuron dysfunction and whether it can serve as a potential diagnostic and/or disease-tracking biomarker for amyotrophic lateral sclerosis (ALS).

METHODS

In this retrospective study, we enrolled 95 subjects, including 33 possible or laboratory supported probable ALS, 26 probable or definite ALS (Prob/Def), 2 primary lateral sclerosis patients, 8 progressive muscular atrophy patients, 19 normal controls (NC) and 7 ALS patients having a second structural MRI scan. Some subjects also underwent functional MRI. We calculated M1, primary sensory cortex, precuneus volumes, and total gray matter volume (TGMV) with FreeSurfer. The sensorimotor network (SMN) was identified using independent component analysis.

RESULTS

The M1/precuneus ratio showed a significant difference between the NC and Prob/Def groups (p < 0.05). The diagnostic accuracy of the M1/precuneus ratio was moderate for distinguishing Prob/Def from NC (cutoff = 1.00, sensitivity = 0.42, specificity = 0.90). Two of eight cases without upper motor neuron dysfunction could be diagnosed with ALS using M1/precuneus ratio as a surrogate marker. A negative correlation between M1/precuneus ratio and functional activity was found in Brodmann area 6 in the SMN in all subjects. TGMV tended to decrease with disease progression (p = 0.04).

INTERPRETATION

The M1/precuneus volume ratio, associated with the SMN, may have potential as a surrogate biomarker of upper motor neuron dysfunction in ALS. Furthermore, TGMV may serve as an ALS disease-tracking biomarker.

Analysis of brain and spinal MRI measures in a common domain to investigate directional neurodegeneration in motor neuron disease

BACKGROUND

Magnetic resonance imaging (MRI) of the brain and cervical spinal cord is often performed in diagnostic evaluation of suspected motor neuron disease/amyotrophic lateral sclerosis (MND/ALS). Analysis of MRI-derived tissue damage metrics in a common domain facilitates group-level inferences on pathophysiology. This approach was applied to address competing hypotheses of directionality of neurodegeneration, whether anterograde, cranio-caudal dying-forward from precentral gyrus or retrograde, dying-back.

METHODS

In this cross-sectional study, MRI was performed on 75 MND patients and 13 healthy controls. Precentral gyral thickness was estimated from volumetric T1-weighted images using FreeSurfer, corticospinal tract fractional anisotropy (FA) from diffusion tensor imaging using FSL, and cross-sectional cervical cord area between C1-C8 levels using Spinal Cord Toolbox. To analyse these multimodal data within a common domain, individual parameter estimates representing tissue damage at each corticospinal tract level were first converted to z-scores, referenced to healthy control norms. Mixed-effects linear regression models were then fitted to these z-scores, with gradients hypothesised to represent directionality of neurodegeneration.

RESULTS

At group-level, z-scores did not differ significantly between precentral gyral and intracranial corticospinal tract tissue damage estimates (regression coefficient - 0.24, [95% CI - 0.62, 0.14], p = 0.222), but step-changes were evident between intracranial corticospinal tract and C1 (1.14, [95% CI 0.74, 1.53], p < 0.001), and between C5 and C6 cord levels (0.98, [95% CI 0.58, 1.38], p < 0.001).

DISCUSSION

Analysis of brain and cervical spinal MRI data in a common domain enabled investigation of pathophysiological hypotheses in vivo. A cranio-caudal step-change in MND patients was observed, and requires further investigation in larger cohorts.

Sensitivity of brain MRI and neurological examination for detection of upper motor neurone degeneration in amyotrophic lateral sclerosis

OBJECTIVES

To investigate sensitivity of brain MRI and neurological examination for detection of upper motor neuron (UMN) degeneration in patients with amyotrophic lateral sclerosis (ALS).

METHODS

We studied 192 patients with ALS and 314 controls longitudinally. All patients visited our centre twice and underwent full neurological examination and brain MRI. At each visit, we assessed UMN degeneration by measuring motor cortex thickness (CT) and pyramidal tract fibre density (FD) corresponding to five body regions (bulbar region and limbs). For each body region, we measured degree of clinical UMN and lower motor neuron (LMN) symptom burden using a validated scoring system.

RESULTS

We found deterioration over time of CT of motor regions (p≤0.0081) and progression of UMN signs of bulbar region and left arm (p≤0.04). FD was discriminative between controls and patients with moderate/severe UMN signs (all regions, p≤0.034), but did not change longitudinally. Higher clinical UMN burden correlated with reduced CT, but not lower FD, for the bulbar region (p=2.2×10^-10) and legs (p≤0.025). In the arms, we found that severe LMN signs may reduce the detectability of UMN signs (p≤0.043). With MRI, UMN degeneration was detectable before UMN signs became clinically evident (CT: p=1.1×10^-10, FD: p=6.3×10^-4). Motor CT, but not FD, deteriorated more than UMN signs during the study period.

CONCLUSIONS

Motor CT is a more sensitive measure of UMN degeneration than UMN signs. Motor CT and pyramidal tract FD are discriminative between patients and controls. Brain MRI can monitor UMN degeneration before signs become clinically evident. These findings promote MRI as a potential biomarker for UMN progression in clinical trials in ALS.

Genetic basis to structural grey matter associations with chronic pain

Structural neuroimaging studies of individuals with chronic pain conditions have often observed decreased regional grey matter at a phenotypic level. However, it is not known if this association can be attributed to genetic factors. Here we employed a novel integrative data-driven and hypothesis-testing approach to determine whether there is a genetic basis to grey matter morphology differences in chronic pain. Using publicly available genome-wide association study summary statistics for regional chronic pain conditions (n = 196 963) and structural neuroimaging measures (n = 19 629-34 000), we applied bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine the genetic correlations (rG) and genetic causal proportion (GCP) between these complex traits, respectively. Five a priori brain regions (i.e. prefrontal cortex, cingulate cortex, insula, thalamus and superior temporal gyrus) were selected based on systematic reviews of grey matter morphology studies in chronic pain. Across this evidence-based selection of five brain regions, 10 significant negative genetic correlations (out of 369) were found (false discovery rate < 5%), suggesting a shared genetic basis to both reduced regional grey matter morphology and the presence of chronic pain. Specifically, negative genetic correlations were observed between reduced insula grey matter morphology and chronic pain in the abdomen (mean insula cortical thickness), hips (left insula volume) and neck/shoulders (left and right insula volume). Similarly, a shared genetic basis was found for reduced posterior cingulate cortex volume in chronic pain of the hip (left and right posterior cingulate), neck/shoulder (left posterior cingulate) and chronic pain at any site (left posterior cingulate); and for reduced pars triangularis volume in chronic neck/shoulder (left pars triangularis) and widespread pain (right pars triangularis). Across these negative genetic correlations, a significant genetic causal proportion was only found between mean insula thickness and chronic abdominal pain [rG (standard error, SE) = -0.25 (0.08), P = 1.06 × 10-3; GCP (SE) = -0.69 (0.20), P = 4.96 × 10-4]. This finding suggests that the genes underlying reduced cortical thickness of the insula causally contribute to an increased risk of chronic abdominal pain. Altogether, these results provide independent corroborating evidence for observational reports of decreased grey matter of particular brain regions in chronic pain. Further, we show for the first time that this association is mediated (in part) by genetic factors. These novel findings warrant further investigation into the neurogenetic pathways that underlie the development and prolongation of chronic pain conditions.

Feature selection from magnetic resonance imaging data in ALS: a systematic review

Background:

With the advances in neuroimaging in amyotrophic lateral sclerosis (ALS), it has been speculated that multiparametric magnetic resonance imaging (MRI) is capable to contribute to early diagnosis. Machine learning (ML) can be regarded as the missing piece that allows for the useful integration of multiparametric MRI data into a diagnostic classifier. The major challenges in developing ML classifiers for ALS are limited data quantity and a suboptimal sample to feature ratio which can be addressed by sound feature selection.

Methods:

We conducted a systematic review to collect MRI biomarkers that could be used as features by searching the online database PubMed for entries in the recent 4 years that contained cross-sectional neuroimaging data of subjects with ALS and an adequate control group. In addition to the qualitative synthesis, a semi-quantitative analysis was conducted for each MRI modality that indicated which brain regions were most commonly reported.

Results:

Our search resulted in 151 studies with a total of 221 datasets. In summary, our findings highly resembled generally accepted neuropathological patterns of ALS, with degeneration of the motor cortex and the corticospinal tract, but also in frontal, temporal, and subcortical structures, consistent with the neuropathological four-stage model of the propagation of pTDP-43 in ALS.

Conclusions:

These insights are discussed with respect to their potential for MRI feature selection for future ML-based neuroimaging classifiers in ALS. The integration of multiparametric MRI including DTI, volumetric, and texture data using ML may be the best approach to generate a diagnostic neuroimaging tool for ALS.

Longitudinal clinical and neuroanatomical correlates of memory impairment in motor neuron disease

Memory impairment in motor neuron disease (MND) is still an underrecognized feature and has traditionally been attributed to executive dysfunction. Here, we investigate the rate of memory impairment in a longitudinal cohort of MND patients, its relationship to other cognitive functions and the underlying neuroanatomical correlates. 142 patients with MND and 99 healthy controls (HC) underwent comprehensive neuropsychological testing and structural MRI at 3T up to four times over a period of 18 months. Linear-mixed effects models were fitted to identify changes at baseline and over time in episodic memory function (learning, immediate and delayed recall, recognition), composed cognitive scores (memory, verbal fluency, executive function), and memory-related structural brain regions (hippocampus, entorhinal cortex, parahippocampal gyrus). Associations between episodic memory performance and volumetric or cortical thickness changes of these regions were computed using Pearson's r. Learning, immediate and delayed recall, as well as recognition performance were significantly reduced in MND when compared to controls at baseline. Performances in these subtests improved over time although MND showed less improvement than controls. This relationship did not change when only "classical" ALS patients were considered. Patients with MND showed thinning of the right parahippocampal gyrus (PhG) in comparison to controls that was progressing over time. Bilateral hippocampal atrophy was observed in MND patients with memory impairment after splitting the group according to their overall episodic memory performance, with the right hippocampus shrinking over time. In MND patients, the bilateral hippocampal atrophy was associated with impairment in learning, recall, and recognition at baseline. In contrast, left PhG thinning was associated with a poorer learning performance. These results show that episodic memory impairment in MND is a frequent cognitive dysfunction. Since deficits are not clearly declining with disease course, an early involvement of this cognitive domain in the disease seems probable. The memory performance-dependent atrophy of the hippocampus and PhG provide evidence for a widespread involvement of these non-motor cortical areas in disease pathology.

Neuroimaging in primary lateral sclerosis

Increased interest in the underlying pathogenesis of primary lateral sclerosis (PLS) and its relationship to amyotrophic lateral sclerosis (ALS) has corresponded to a growing number of CNS imaging studies, especially in the past decade. Both its rarity and uncertainty of definite diagnosis prior to 4 years from symptom onset have resulted in PLS being less studied than ALS. In this review, we highlight most relevant papers applying magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET) to analyzing CNS changes in PLS, often in relation to ALS. In patients with PLS, mostly brain, but also spinal cord has been evaluated since significant neurodegeneration is essentially restricted to upper motor neuron (UMN) structures and related pathways. Abnormalities of cortex and subcortical white matter tracts have been identified by structural and functional MRI and MRS studies, while metabolic and cell-specific changes in PLS brain have been revealed using various PET radiotracers. Future neuroimaging studies will continue to explore the interface between the PLS-ALS continuum, identify more changes unique to PLS, apply novel MRI and MRS sequences showing greater structural and neurochemical detail, as well as expand the repertoire of PET radiotracers that reveal various cellular pathologies. Neuroimaging has the potential to play an important role in the evaluation of novel therapies for patients with PLS.

Measuring network disruption in neurodegenerative diseases: New approaches using signal analysis

Advanced neuroimaging has increased understanding of the pathogenesis and spread of disease, and offered new therapeutic targets. MRI and positron emission tomography have shown that neurodegenerative diseases including Alzheimer's disease (AD), Lewy body dementia (LBD), Parkinson's disease (PD), frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS) are associated with changes in brain networks. However, the underlying neurophysiological pathways driving pathological processes are poorly defined. The gap between what imaging can discern and underlying pathophysiology can now be addressed by advanced techniques that explore the cortical neural synchronisation, excitability and functional connectivity that underpin cognitive, motor, sensory and other functions. Transcranial magnetic stimulation can show changes in focal excitability in cortical and transcortical motor circuits, while electroencephalography and magnetoencephalography can now record cortical neural synchronisation and connectivity with good temporal and spatial resolution.Here we reflect on the most promising new approaches to measuring network disruption in AD, LBD, PD, FTD, MS, and ALS. We consider the most groundbreaking and clinically promising studies in this field. We outline the limitations of these techniques and how they can be tackled and discuss how these novel approaches can assist in clinical trials by predicting and monitoring progression of neurophysiological changes underpinning clinical symptomatology.

Primary lateral sclerosis: a distinct entity or part of the ALS spectrum?

Primary lateral sclerosis (PLS) has been traditionally viewed as a distinct upper motor neuron condition (UMN) but is increasingly regarded as a sub-phenotype within the amyotrophic lateral sclerosis (ALS) spectrum. Despite established diagnostic criteria, formal diagnosis can be challenging and the protracted diagnostic journey and uncertainty about longer-term prognosis cause considerable distress to patients and caregivers. PLS patients are invariably excluded from ALS clinical trials, while PLS pharmacological trials are lacking. There remains an unmet need for diagnostic biomarkers for upper motor neuron predominant conditions and prognostic indicators regarding prognosis, survival, and risk of conversion to ALS. Validated biomarkers will not only have implications for individualized patient care but also serve as outcome measures in pharmaceutical trials. Given the paucity of post-mortem studies in PLS, novel pathological insights are generally inferred from state-of-the-art imaging studies. Computational neuroimaging has already contributed significantly to the characterization of PLS-associated pathology in vivo and has underscored the role of neuro-inflammation, the presence of extra-motor changes, and confirmed pathological patterns similar to ALS. This systematic review assesses the current state of PLS research across clinical, neuroimaging and neuropathological domains from a combined clinical and academic perspective. We discuss patterns of pathological overlap with other ALS phenotypes, examine if the biological processes of PLS warrant therapeutic strategies distinct from ALS, and evaluate the evidence that classes PLS as a distinct clinico-pathological entity.