Label-fusion-segmentation and deformation-based shape analysis of deep gray matter in multiple sclerosis: the impact of thalamic subnuclei on disability

Quantitative susceptibility mapping based basal ganglia segmentation via AGSeg: leveraging active gradient guiding mechanism in deep learning

Background

With better visual contrast and the ability for magnetic susceptibility quantification analysis, quantitative susceptibility mapping (QSM) has emerged as an important magnetic resonance imaging (MRI) method for basal ganglia studies. Precise segmentation of basal ganglia is a prerequisite for quantification analysis of tissue magnetic susceptibility, which is crucial for subsequent disease diagnosis and surgical planning. The conventional method of localizing and segmenting basal ganglia heavily relies on layer-by-layer manual annotation by experts, resulting in a tedious amount of workload. Although several morphology registration and deep learning based methods have been developed to automate segmentation, the voxels around the nuclei boundary remain a challenge to distinguish due to insufficient tissue contrast. This paper proposes AGSeg, an active gradient guidance-based susceptibility and magnitude information complete (MIC) network for real-time and accurate basal ganglia segmentation.

Methods

Various datasets, including clinical scans and data from healthy volunteers, were collected across multiple centers with different magnetic field strengths (3T/5T/7T), with a total of 210 three-dimensional (3D) susceptibility measurements. Manual segmentations following fixed rules for anatomical borders annotated by experts were used as ground truth labels. The proposed network took QSM maps and Magnitude images as two individual inputs, of which the features are selectively enhanced in the proposed magnitude information complete (MIC) module. AGSeg utilized a dual-branch architecture, with Seg-branch aiming to generate a proper segmentation map and Grad-branch to reconstruct the gradient map of regions of interest (ROIs). With the support of the newly designed active gradient module (AGM) and gradient guiding module (GGM), the Grad-branch provided attention guidance for the Seg-branch, facilitating it to focus on the boundary of target nuclei.

Results

Ablation studies were conducted to assess the functionality of the proposed modules. Significant performance decrement was observed after ablating relative modules. AGSeg was evaluated against several existing methods on both healthy and clinical data, achieving an average Dice similarity coefficient (DSC) =0.874 and average 95% Hausdorff distance (HD95) =2.009. Comparison experiments indicated that our model had superior performance on basal ganglia segmentation and better generalization ability over existing methods. The AGSeg outperformed all implemented comparison deep learning algorithms with average DSC enhancement ranging from 0.036 to 0.074.

Conclusions

The current work integrates a deep learning-based method into automated basal ganglia segmentation. The high processing speed and segmentation robustness of AGSeg contribute to the feasibility of future surgery planning and intraoperative navigation. Experiments show that leveraging active gradient guidance mechanisms and magnitude information completion can facilitate the segmentation process. Moreover, this approach also offers a portable solution for other multi-modality medical image segmentation tasks.

Hippocampal subfields and thalamic nuclei associations with clinical outcomes in multiple sclerosis: An ultrahigh field MRI study

BACKGROUND

Previous studies have shown that thalamic and hippocampal neurodegeneration is associated with clinical decline in Multiple Sclerosis (MS). However, contributions of the specific thalamic nuclei and hippocampal subfields require further examination.

OBJECTIVE

Using 7 Tesla (7T) magnetic resonance imaging (MRI), we investigated the cross-sectional associations between functionally grouped thalamic nuclei and hippocampal subfields volumes and T1 relaxation times (T1-RT) and subsequent clinical outcomes in MS.

METHODS

High-resolution T1-weighted and T2-weighted images were acquired at 7T (n=31), preprocessed, and segmented using the Thalamus Optimized Multi Atlas Segmentation (THOMAS, for thalamic nuclei) and the Automatic Segmentation of Hippocampal Subfields (ASHS, for hippocampal subfields) packages. We calculated Pearson correlations between hippocampal subfields and thalamic nuclei volumes and T1-RT and subsequent multi-modal rater-determined and patient-reported clinical outcomes (∼2.5 years after imaging acquisition), correcting for confounders and multiple tests.

RESULTS

Smaller volume bilaterally in the anterior thalamus region correlated with worse performance in gait function, as measured by the Patient Determined Disease Steps (PDDS). Additionally, larger volume in most functional groups of thalamic nuclei correlated with better visual information processing and cognitive function, as measured by the Symbol Digit Modalities Test (SDMT). In bilateral medial and left posterior thalamic regions, there was an inverse association between volumes and T1-RT, potentially indicating higher tissue degeneration in these regions. We also observed marginal associations between the right hippocampal subfields (both volumes and T1-RT) and subsequent clinical outcomes, though they did not survive correction for multiple testing.

CONCLUSION

Ultrahigh field MRI identified markers of structural damage in the thalamic nuclei associated with subsequently worse clinical outcomes in individuals with MS. Longitudinal studies will enable better understanding of the role of microstructural integrity in these brain regions in influencing MS outcomes.

Ocrelizumab reduces thalamic volume loss in patients with RMS and PPMS

Background:

In multiple sclerosis (MS), thalamic integrity is affected directly by demyelination and neuronal loss, and indirectly by gray/white matter lesions outside the thalamus, altering thalamic neuronal projections.

Objective:

To assess the efficacy of ocrelizumab compared with interferon beta-1a (IFNβ1a)/placebo on thalamic volume loss and the effect of switching to ocrelizumab on volume change in the Phase III trials in relapsing MS (RMS, OPERA I/II; NCT01247324/NCT01412333) and in primary progressive MS (PPMS, ORATORIO; NCT01194570).

Methods:

Thalamic volume change was computed using paired Jacobian integration and analyzed using an adjusted mixed-effects repeated measurement model.

Results:

Over the double-blind period, ocrelizumab treatment significantly reduced thalamic volume loss with the largest effect size (Cohen’s d: RMS: 0.561 at week 96; PPMS: 0.427 at week 120) compared with whole brain, cortical gray matter, and white matter volume loss. At the end of up to 7 years of follow-up, patients initially randomized to ocrelizumab still showed less thalamic volume loss than those switching from IFNβ1a ( p < 0.001) or placebo ( p < 0.001).

Conclusion:

Ocrelizumab effectively reduced thalamic volume loss compared with IFNβ1a/placebo. Early treatment effects on thalamic tissue preservation persisted over time. Thalamic volume loss could be a potential sensitive marker of persisting tissue damage.

Longitudinal changes of deep gray matter shape in multiple sclerosis

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Specific shape changes over time occur at the bilateral ventrolateral pallidal and the left posterolateral striatal surface in relapse-onset multiple sclerosis.

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These shape changes over time were not associated with disease progression.

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The average shape of deep gray matter structures was associated with the patients’ average disease severity as well as white matter lesion-load.

Objective

This study aimed to investigate longitudinal deep gray matter (DGM) shape changes and their relationship with measures of clinical disability and white matter lesion-load in a large multiple sclerosis (MS) cohort.

Materials and Methods

A total of 230 MS patients (179 relapsing-remitting, 51 secondary progressive; baseline age 44.5 ± 11.3 years; baseline disease duration 12.99 ± 9.18) underwent annual clinical and MRI examinations over a maximum of 6 years (mean 4.32 ± 2.07 years). The DGM structures were segmented on the T1-weighted images using the “Multiple Automatically Generated Templates” brain algorithm. White matter lesion-load was measured on T2-weighted MRI. Clinical examination included the expanded disability status scale, 9-hole peg test, timed 25-foot walk test, symbol digit modalities test and paced auditory serial addition test. Vertex‐wise longitudinal analysis of DGM shapes was performed using linear mixed effect models and evaluated the association between average/temporal changes of DGM shapes with average/temporal changes of clinical measurements, respectively.

Results

A significant shrinkage over time of the bilateral ventrolateral pallidal and the left posterolateral striatal surface was observed, whereas no significant shape changes over time were observed at the bilateral thalamic and right striatal surfaces. Higher average lesion-load was associated with an average inwards displacement of the global thalamic surface with relative sparing on the posterior side (slight left-side predominance), the antero-dorso-lateral striatal surfaces bilaterally (symmetric on both sides) and the antero-lateral pallidal surface (left-side predominance). There was also an association between shrinkage of large lateral DGM surfaces with higher clinical motor and cognitive disease severity. However, there was no correlation between any DGM shape changes over time and measurements of clinical progression or lesion-load changes over time.

Conclusions

This study showed specific shape change of DGM structures occurring over time in relapse-onset MS. Although these shape changes over time were not associated with disease progression, we demonstrated a link between DGM shape and the patients’ average disease severity as well as white matter lesion-load.

Statistical shape analysis of putamen in early-onset Parkinson's disease

OBJECTIVE

To investigate the shape differences in the putamen of early-onset Parkinson's patients compared with healthy controls and to assess and to assess sub-regional brain abnormalities.

METHODS

This study was conducted using the 3-T MRI scans of 23 early-onset Parkinson's patients and age and gender matched control subjects. Landmark coordinate data obtained and Procrustes analysis was used to compare mean shapes. The relationships between the centroid sizes of the left and right putamen, and the durations of disease examined using growth curve models.

RESULTS

While there was a significant difference between the right putamen shape of control and patient groups, there was not found a significant difference in terms of left putamen. Sub-regional analyses showed that for the right putamen, the most prominent deformations were localized in the middle-posterior putamen and minimal deformations were seen in the anterior putamen.

CONCLUSION

Although they were not as pronounced as those in the right putamen, the deformations in the left putamen mimic the deformations in the right putamen which are found mainly in the middle-posterior putamen and at a lesser extend in the anterior putamen.

Central nervous system atrophy predicts future dynamics of disability progression in a real-world multiple sclerosis cohort

Background and purpose

In an era of individualized multiple sclerosis (MS) patient management, biomarkers for accurate prediction of future clinical outcomes are needed. We aimed to evaluate the potential of short‐term magnetic resonance imaging (MRI) atrophy measures and serum neurofilament light chain (sNfL) as predictors of the dynamics of disability accumulation in relapse‐onset MS.

Methods

Brain gray and white matter, thalamic, striatal, pallidal and cervical spinal cord volumes, and lesion load were measured over three available time points (mean time span 2.24 ± 0.70 years) for 183 patients (140 relapsing‐remitting [RRMS] and 43 secondary‐progressive MS (SPMS); 123 female, age 46.4 ± 11.0 years; disease duration 15.7 ± 9.3 years), and their respective annual changes were calculated. Baseline sNfL was also measured at the third available time point for each patient. Subsequently, patients underwent annual clinical examinations over 5.4 ± 3.7 years including Expanded Disability Status Scale (EDSS) scoring, the nine‐hole peg test and the timed 25‐foot walk test.

Results

Higher annual spinal cord atrophy rates and lesion load increase predicted higher future EDSS score worsening over time in SPMS. Lower baseline thalamic volumes predicted higher walking speed worsening over time in RRMS. Lower baseline gray matter, as well as higher white matter and spinal cord atrophy rates, lesion load increase, baseline striatal volumes and baseline sNfL, predicted higher future hand dexterity worsening over time. All models showed reasonable to high prediction accuracy.

Conclusion

This study demonstrates the capability of short‐term MRI metrics to accurately predict future dynamics of disability progression in a real‐world relapse‐onset MS cohort. The present study represents a step towards the utilization of structural MRI measurements in patient care.

Regional Cerebellar Volume Loss Predicts Future Disability in Multiple Sclerosis Patients

Cerebellar symptoms in multiple sclerosis (MS) are well described; however, the exact contribution of cerebellar damage to MS disability has not been fully explored. Longer-term observational periods are necessary to better understand the dynamics of pathological changes within the cerebellum and their clinical consequences. Cerebellar lobe and single lobule volumes were automatically segmented on 664 3D-T1-weighted MPRAGE scans (acquired at a single 1.5 T scanner) of 163 MS patients (111 women; mean age: 47.1 years; 125 relapsing–remitting (RR) and 38 secondary progressive (SP) MS, median EDSS: 3.0) imaged annually over 4 years. Clinical scores (EDSS, 9HPT, 25FWT, PASAT, SDMT) were determined per patient per year with a maximum clinical follow-up of 11 years. Linear mixed-effect models were applied to assess the association between cerebellar volumes and clinical scores and whether cerebellar atrophy measures may predict future disability progression. SPMS patients exhibited faster posterior superior lobe volume loss over time compared to RRMS, which was related to increase of EDSS over time. In RRMS, cerebellar volumes were significant predictors of motor scores (e.g. average EDSS, T25FWT and 9HPT) and SDMT. Atrophy of motor-associated lobules (IV-VI + VIII) was a significant predictor of future deterioration of the 9HPT of the non-dominant hand. In SPMS, the atrophy rate of the posterior superior lobe (VI + Crus I) was a significant predictor of future PASAT performance deterioration. Regional cerebellar volume reduction is associated with motor and cognitive disability in MS and may serve as a predictor for future disease progression, especially of dexterity and impaired processing speed.

Lateral geniculate nucleus volume changes after optic neuritis in neuromyelitis optica: A longitudinal study

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LGN correlates with structural markers of the anterior and posterior visual pathway.

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LGN volume may reduce after an episode of ON, shown in four patients.

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LGN volume does not change over time in the absence of ON episodes.

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Our findings argue against occult neurodegeneration in the visual pathway in NMO.

Objectives

Lateral geniculate nucleus (LGN) volume is reduced after optic neuritis (ON) in neuromyelitis optica spectrum disorders (NMOSD). We aimed at a longitudinal assessment of LGN volume in NMOSD.

Methods

Twenty-nine patients with aquaporin 4-IgG seropositive NMOSD (age: 47.8 ± 14.6 years (y), female: n = 27, history of ON (NMO-ON): n = 17, median time since ON: 3[1.2–12.1]y) and 18 healthy controls (HC; age: 39.3 ± 15.8y; female: n = 13) were included. Median follow-up was 4.1[1.1–4.7]y for patients and 1.7[0.9–3.2]y for HC. LGN volume was measured using a multi-atlas-based approach of automated segmentation on 3 Tesla magnetic resonance images. Retinal optical coherence tomography and probabilistic tractography of the optic radiations (OR) were also performed.

Results

At baseline, NMO-ON patients had lower LGN volumes (395.4 ± 48.9 mm³) than patients without ON (NMO-NON: 450.7 ± 55.6 mm³; p = 0.049) and HC (444.5 ± 61.5 mm³, p = 0.025). LGN volume was associated with retinal neuroaxonal loss and microstructural OR damage. Longitudinally, there was no change in LGN volumes in the absence of ON, neither in all patients (B = −0.6, SE = 1.4, p = 0.670), nor in NMO-ON (B = −0.8, SE = 1.6, p = 0.617) and NMO-NON (B = 1.7, SE = 3.5, p = 0.650). However, in four patients with new ON during follow-up, LGN volume was reduced at last visit (median time since ON: 2.6 [1.8–3.9] y) compared to the measurement before ON (352 ± 52.7 vs. 371.1 ± 55.9 mm³; t = −3.6, p = 0.036).

Conclusion

Although LGN volume is reduced after ON in NMOSD, this volume loss is not progressive over longer follow-up or independent of ON. Thus, our findings -at least in this relatively small cohort- do not support occult neurodegeneration of the afferent visual pathway in NMOSD.

Classification of multiple sclerosis based on patterns of CNS regional atrophy covariance

There is evidence that multiple sclerosis (MS) pathology leads to distinct patterns of volume loss over time (VLOT) in different central nervous system (CNS) structures. We aimed to use such patterns to identify patient subgroups. MS patients of all classical disease phenotypes underwent annual clinical, blood, and MRI examinations over 6 years. Spinal, striatal, pallidal, thalamic, cortical, white matter, and T2‐weighted lesion volumes as well as serum neurofilament light chain (sNfL) were quantified. CNS VLOT patterns were identified using principal component analysis and patients were classified using hierarchical cluster analysis. 225 MS patients were classified into four distinct Groups A, B, C, and D including 14, 59, 141, and 11 patients, respectively). These groups did not differ in baseline demographics, disease duration, disease phenotype distribution, and lesion‐load expansion. Interestingly, Group A showed pronounced spinothalamic VLOT, Group B marked pallidal VLOT, Group C small between‐structure VLOT differences, and Group D myelocortical volume increase and pronounced white matter VLOT. Neurologic deficits were more severe and progressed faster in Group A that also had higher mean sNfL levels than all other groups. Group B experienced more frequent relapses than Group C. In conclusion, there are distinct patterns of VLOT across the CNS in MS patients, which do not overlap with clinical MS subtypes and are independent of disease duration and lesion‐load but are partially associated to sNfL levels, relapse rates, and clinical worsening. Our findings support the need for a more biologic classification of MS subtypes including volumetric and body‐fluid markers.

Levels of brain-derived neurotrophic factor in patients with multiple sclerosis

Objective

To determine the levels of brain‐derived neurotrophic factor (BDNF) in the serum of patients suffering from multiple sclerosis (MS) to evaluate the potential of serum BDNF as a biomarker for MS.

Methods

Using a recently validated enzyme‐linked immunoassay (ELISA) we measured BDNF in patients with MS (pwMS), diagnosed according to the 2001 McDonald criteria and aged between 18 and 70 years, participating in a long‐term cohort study with annual clinical visits, including blood sampling, neuropsychological testing, and brain magnetic resonance imaging (MRI). The results were compared with an age‐ and sex‐matched cohort of healthy controls (HC). Correlations between BDNF levels and a range of clinical and magnetic resonance imaging variables were assessed using an adjusted linear model.

Results

In total, 259 pwMS and 259 HC were included, with a mean age of 44.42 ± 11.06 and 44.31 ± 11.26 years respectively. Eleven had a clinically isolated syndrome (CIS), 178 relapsing remitting MS (RRMS), 56 secondary progressive MS (SPMS), and 14 primary progressive MS (PPMS). Compared with controls, mean BDNF levels were lower by 8 % (p˂0.001) in pwMS. The level of BDNF in patients with SPMS was lower than in RRMS (p = 0.004).

Interpretation

We conclude that while the use of comparatively large cohorts enables the detection of a significant difference in BDNF levels between pwMS and HC, the difference is small and unlikely to usefully inform decision‐making processes at an individual patient level.

A multi-contrast MRI approach to thalamus segmentation

Thalamic alterations occur in many neurological disorders including Alzheimer's disease, Parkinson's disease and multiple sclerosis. Routine interventions to improve symptom severity in movement disorders, for example, often consist of surgery or deep brain stimulation to diencephalic nuclei. Therefore, accurate delineation of grey matter thalamic subregions is of the upmost clinical importance. MRI is highly appropriate for structural segmentation as it provides different views of the anatomy from a single scanning session. Though with several contrasts potentially available, it is also of increasing importance to develop new image segmentation techniques that can operate multi-spectrally. We hereby propose a new segmentation method for use with multi-modality data, which we evaluated for automated segmentation of major thalamic subnuclear groups using T1 -weighted, T 2 * -weighted and quantitative susceptibility mapping (QSM) information. The proposed method consists of four steps: Highly iterative image co-registration, manual segmentation on the average training-data template, supervised learning for pattern recognition, and a final convex optimisation step imposing further spatial constraints to refine the solution. This led to solutions in greater agreement with manual segmentation than the standard Morel atlas based approach. Furthermore, we show that the multi-contrast approach boosts segmentation performances. We then investigated whether prior knowledge using the training-template contours could further improve convex segmentation accuracy and robustness, which led to highly precise multi-contrast segmentations in single subjects. This approach can be extended to most 3D imaging data types and any region of interest discernible in single scans or multi-subject templates.

Longitudinal patterns of cortical thinning in multiple sclerosis

In multiple sclerosis (MS), cortical atrophy is correlated with clinical and neuropsychological measures. We aimed to examine the differences in the temporospatial evolution of cortical thickness (CTh) between MS‐subtypes and to study the association of CTh with T2‐weighted white matter lesions (T2LV) and clinical progression. Two hundred and forty‐three MS patients (180 relapsing–remitting [RRMS], 51 secondary‐progressive [SPMS], and 12 primary‐progressive [PPMS]) underwent annual clinical (incl. expanded disability status scale [EDSS]) and MRI‐examinations over 6 years. T2LV and CTh were measured. CTh did not differ between MS‐subgroups. Higher total T2LV was associated with extended bilateral CTh‐reduction on average, but did not correlate with CTh‐changes over time. In RRMS, CTh‐ and EDSS‐changes over time were negatively correlated in large bilateral prefrontal, frontal, parietal, temporal, and occipital areas. In SPMS, CTh was not associated with the EDSS. In PPMS, CTh‐ and EDSS‐changes over time were correlated in small clusters predominantly in left parietal areas. Increase of brain lesion load does not lead to an immediate CTh‐reduction. Although CTh did not differ between MS‐subtypes, a dissociation in the correlation between CTh‐ and EDSS‐changes over time between RRMS and progressive‐MS was shown, possibly underlining the contribution of subcortical pathology to clinical progression in progressive‐MS.

Volume loss in the deep gray matter and thalamic subnuclei: a longitudinal study on disability progression in multiple sclerosis

BACKGROUND

Volume loss in the deep gray matter (DGM) has been reported in patients with multiple sclerosis (MS) already at early stages of the disease and is thought to progress throughout the disease course.

OBJECTIVE

To investigate the impact and predictive value of volume loss in DGM and thalamic subnuclei on disability worsening in patients MS over a 6-year follow-up period.

METHODS

Hundred and seventy-nine patients with RRMS (132 women; median Expanded Disability Status Scale, EDSS: 2.5) and 50 with SPMS (27 women; median EDSS: 4.5) were included in the study. Patients underwent annual EDSS assessments and annual MRI at 1.5 T. DGM/thalamic subnuclei volumes were identified on high-resolution T1-weighted. A hierarchical linear mixed model for each anatomical DGM area and each thalamic subnucleus was performed to investigate the associations with disability scores. Cox regression was used to estimate the predictive properties of volume loss in DGM and thalamic subnuclei on disease worsening.

RESULTS

In the whole sample and in RRMS, volumes of the thalamus and the striatum were associated with the EDSS; however, only thalamic volume loss was associated with EDSS change at follow-up. Regarding thalamic subnuclei, volume loss in the anterior nucleus, the pulvinar and the ventral anterior nucleus was associated with EDSS change in the whole cohort. A trend was observed for the ventral lateral nucleus. Volume loss in the anterior and ventral anterior nuclei was associated with EDSS change over time in patients with RRMS. Moreover, MS phenotype and annual rates of volume loss in the thalamus and ventral lateral nucleus were predictive of disability worsening.

CONCLUSION

These results highlight the relevance of volume loss in the thalamus as a key metric for predicting disability worsening as assessed by EDSS (in RRMS). Moreover, the volume loss in specific nuclei such as the ventral lateral nucleus seems to play a role in disability worsening.

Attack-related damage of thalamic nuclei in neuromyelitis optica spectrum disorders

OBJECTIVES

In neuromyelitis optica spectrum disorders (NMOSD) thalamic damage is controversial, but thalamic nuclei were never studied separately. We aimed at assessing volume loss of thalamic nuclei in NMOSD. We hypothesised that only specific nuclei are damaged, by attacks affecting structures from which they receive afferences: the lateral geniculate nucleus (LGN), due to optic neuritis (ON) and the ventral posterior nucleus (VPN), due to myelitis.

METHODS

Thirty-nine patients with aquaporin 4-IgG seropositive NMOSD (age: 50.1±14.1 years, 36 women, 25 with prior ON, 36 with prior myelitis) and 37 healthy controls (age: 47.8 ± 12.5 years, 32 women) were included in this cross-sectional study. Thalamic nuclei were assessed in magnetic resonance images, using a multi-atlas-based approach of automated segmentation. Retinal optical coherence tomography was also performed.

RESULTS

Patients with ON showed smaller LGN volumes (181.6±44.2 mm³) compared with controls (198.3±49.4 mm³; B=-16.97, p=0.004) and to patients without ON (206.1±50 mm³ ; B=-23.74, p=0.001). LGN volume was associated with number of ON episodes (Rho=-0.536, p<0.001), peripapillary retinal nerve fibre layer thickness (B=0.70, p<0.001) and visual function (B=-0.01, p=0.002). Although VPN was not smaller in patients with myelitis (674.3±67.5 mm³) than controls (679.7±68.33; B=-7.36, p=0.594), we found reduced volumes in five patients with combined myelitis and brainstem attacks (B=-76.18, p=0.017). Volumes of entire thalamus and other nuclei were not smaller in patients than controls.

CONCLUSION

These findings suggest attack-related anterograde degeneration rather than diffuse thalamic damage in NMOSD. They also support a potential role of LGN volume as an imaging marker of structural brain damage in these patients.

Stereological Investigation of Regional Brain Volumes after Acute and Chronic Cuprizone-Induced Demyelination

Brain volume measurement is one of the most frequently used biomarkers to establish neuroprotective effects during pre-clinical multiple sclerosis (MS) studies. Furthermore, whole-brain atrophy estimates in MS correlate more robustly with clinical disability than traditional, lesion-based metrics. However, the underlying mechanisms leading to brain atrophy are poorly understood, partly due to the lack of appropriate animal models to study this aspect of the disease. The purpose of this study was to assess brain volumes and neuro-axonal degeneration after acute and chronic cuprizone-induced demyelination. C57BL/6 male mice were intoxicated with cuprizone for up to 12 weeks. Brain volume, as well as total numbers and densities of neurons, were determined using design-based stereology. After five weeks of cuprizone intoxication, despite severe demyelination, brain volumes were not altered at this time point. After 12 weeks of cuprizone intoxication, a significant volume reduction was found in the corpus callosum and diverse subcortical areas, particularly the internal capsule and the thalamus. Thalamic volume loss was accompanied by glucose hypermetabolism, analyzed by [¹⁸F]-fluoro-2-deoxy-d-glucose (18F-FDG) positron-emission tomography. This study demonstrates region-specific brain atrophy of different subcortical brain regions after chronic cuprizone-induced demyelination. The chronic cuprizone demyelination model in male mice is, thus, a useful tool to study the underlying mechanisms of subcortical brain atrophy and to investigate the effectiveness of therapeutic interventions.

Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies

The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.

Damage of the lateral geniculate nucleus in MS: Assessing the missing node of the visual pathway

OBJECTIVE

To study if the thalamic lateral geniculate nucleus (LGN) is affected in multiple sclerosis (MS) due to anterograde degeneration from optic neuritis (ON) or retrograde degeneration from optic radiation (OR) pathology, and if this is relevant for visual function.

METHODS

In this cross-sectional study, LGN volume of 34 patients with relapsing-remitting MS and 33 matched healthy controls (HC) was assessed on MRI using atlas-based automated segmentation (MAGeT). ON history, thickness of the ganglion cell-inner plexiform layer (GC-IPL), OR lesion volume, and fractional anisotropy (FA) of normal-appearing OR (NAOR-FA) were assessed as measures of afferent visual pathway damage. Visual function was tested, including low-contrast letter acuity (LCLA) and Hardy-Rand-Rittler (HRR) plates for color vision.

RESULTS

LGN volume was reduced in patients vs HC (165.5 ± 45.5 vs 191.4 ± 47.7 mm³, B = -25.89, SE = 5.83, p < 0.001). It was associated with GC-IPL thickness (B = 0.95, SE = 0.33, p = 0.006) and correlated with OR lesion volume (Spearman ρ = -0.53, p = 0.001), and these relationships remained after adjustment for normalized brain volume. There was no association between NAOR-FA and LGN volume (B = -133.28, SE = 88.47, p = 0.137). LGN volume was not associated with LCLA (B = 5.5 × 10^-5, SE = 0.03, p = 0.998), but it correlated with HRR color vision (ρ = 0.39, p = 0.032).

CONCLUSIONS

LGN volume loss in MS indicates structural damage with potential functional relevance. Our results suggest both anterograde degeneration from the retina and retrograde degeneration from the OR lesions as underlying causes. LGN volume is a promising marker reflecting damage of the visual pathway in MS, with the advantage of individual measurement per patient on conventional MRI.

Spinal cord volume loss: A marker of disease progression in multiple sclerosis

OBJECTIVE

Cross-sectional studies have shown that spinal cord volume (SCV) loss is related to disease severity in multiple sclerosis (MS). However, long-term data are lacking. Our aim was to evaluate SCV loss as a biomarker of disease progression in comparison to other MRI measurements in a large cohort of patients with relapse-onset MS with 6-year follow-up.

METHODS

The upper cervical SCV, the total brain volume, and the brain T2 lesion volume were measured annually in 231 patients with MS (180 relapsing-remitting [RRMS] and 51 secondary progressive [SPMS]) over 6 years on 3-dimensional, T1-weighted, magnetization-prepared rapid-acquisition gradient echo images. Expanded Disability Status Scale (EDSS) score and relapses were recorded at every follow-up.

RESULTS

Patients with SPMS had lower baseline SCV (p < 0.01) but no accelerated SCV loss compared to those with RRMS. Clinical relapses were found to predict SCV loss over time (p < 0.05) in RRMS. Furthermore, SCV loss, but not total brain volume and T2 lesion volume, was a strong predictor of EDSS score worsening over time (p < 0.05). The mean annual rate of SCV loss was the strongest MRI predictor for the mean annual EDSS score change of both RRMS and SPMS separately, while correlating stronger in SPMS. Every 1% increase of the annual SCV loss rate was associated with an extra 28% risk increase of disease progression in the following year in both groups.

CONCLUSION

SCV loss over time relates to the number of clinical relapses in RRMS, but overall does not differ between RRMS and SPMS. SCV proved to be a strong predictor of physical disability and disease progression, indicating that SCV may be a suitable marker for monitoring disease activity and severity.

Preferential spinal cord volume loss in primary progressive multiple sclerosis

BACKGROUND

Little is known on longer term changes of spinal cord volume (SCV) in primary progressive multiple sclerosis (PPMS).

OBJECTIVE

Longitudinal evaluation of SCV loss in PPMS and its correlation to clinical outcomes, compared to relapse-onset multiple sclerosis (MS) subtypes.

METHODS

A total of 60 MS age-, sex- and disease duration-matched patients (12 PPMS, each 24 relapsing-remitting (RRMS) and secondary progressive MS (SPMS)) were analysed annually over 6 years of follow-up. The upper cervical SCV was measured on 3D T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images using a semi-automatic software (CORDIAL), along with the total brain volume (TBV), brain T2 lesion volume (T2LV) and Expanded Disability Status Scale (EDSS).

RESULTS

PPMS showed faster SCV loss over time than RRMS ( p < 0.01) and by trend ( p = 0.066) compared with SPMS. In contrast to relapse-onset MS, in PPMS SCV loss progressed independent of TBV and T2LV changes. Moreover, in PPMS, SCV was the only magnetic resonance imaging (MRI) measurement associated with EDSS increase over time ( p < 0.01), as opposed to RRMS and SPMS.

CONCLUSION

SCV loss is a strong predictor of clinical outcomes in PPMS and has shown to be faster and independent of brain MRI metrics compared to relapse-onset MS.

Subcortical Shape Changes, Hippocampal Atrophy and Cortical Thinning in Future Alzheimer's Disease Patients

Efficacy of future treatments depends on biomarkers identifying patients with mild cognitive impairment at highest risk for transitioning to Alzheimer's disease. Here, we applied recently developed analysis techniques to investigate cross-sectional differences in subcortical shape and volume alterations in patients with stable mild cognitive impairment (MCI) (n = 23, age range 59–82, 47.8% female), future converters at baseline (n = 10, age range 66–84, 90% female) and at time of conversion (age range 68–87) compared to group-wise age and gender matched healthy control subjects (n = 23, age range 61–81, 47.8% female; n = 10, age range 66–82, 80% female; n = 10, age range 68–82, 70% female). Additionally, we studied cortical thinning and global and local measures of hippocampal atrophy as known key imaging markers for Alzheimer's disease. Apart from bilateral striatal volume reductions, no morphometric alterations were found in cognitively stable patients. In contrast, we identified shape alterations in striatal and thalamic regions in future converters at baseline and at time of conversion. These shape alterations were paralleled by Alzheimer's disease like patterns of left hemispheric morphometric changes (cortical thinning in medial temporal regions, hippocampal total and subfield atrophy) in future converters at baseline with progression to similar right hemispheric alterations at time of conversion. Additionally, receiver operating characteristic curve analysis indicated that subcortical shape alterations may outperform hippocampal volume in identifying future converters at baseline. These results further confirm the key role of early cortical thinning and hippocampal atrophy in the early detection of Alzheimer's disease. But first and foremost, and by distinguishing future converters but not patients with stable cognitive abilities from cognitively normal subjects, our results support the value of early subcortical shape alterations and reduced hippocampal subfield volumes as potential markers for the early detection of Alzheimer's disease.

Volumetric and shape analysis of the thalamus and striatum in amnestic mild cognitive impairment

Alterations in brain structures, including progressive neurodegeneration, are a hallmark in patients with Alzheimer's disease (AD). However, pathological mechanisms, such as the accumulation of amyloid and the proliferation of tau, are thought to begin years, even decades, before the initial clinical manifestations of AD. In this study, we compare the brain anatomy of amnestic mild cognitive impairment patients (aMCI, n = 16) to healthy subjects (CS, n = 22) using cortical thickness, subcortical volume, and shape analysis, which we believe to be complimentary to volumetric measures. We were able to replicate "classical" cortical thickness alterations in aMCI in the hippocampus, amygdala, putamen, insula, and inferior temporal regions. Additionally, aMCI showed significant thalamic and striatal shape differences. We observed higher global amyloid deposition in aMCI, a significant correlation between striatal displacement and global amyloid, and an inverse correlation between executive function and right-hemispheric thalamic displacement. In contrast, no volumetric differences were detected in thalamic, striatal, and hippocampal regions. Our results provide new evidence for early subcortical neuroanatomical changes in patients with aMCI, which are linked to cognitive abilities and amyloid deposition. Hence, shape analysis may aid in the identification of structural biomarkers for identifying individuals at highest risk of conversion to AD.

Thalamus Degeneration and Inflammation in Two Distinct Multiple Sclerosis Animal Models

There is a broad consensus that multiple sclerosis (MS) represents more than an inflammatory disease: it harbors several characteristic aspects of a classical neurodegenerative disorder, i.e., damage to axons, synapses, and nerve cell bodies. While several accepted paraclinical methods exist to monitor the inflammatory-driven aspects of the disease, techniques to monitor progression of early and late neurodegeneration are still in their infancy and have not been convincingly validated. It was speculated that the thalamus with its multiple reciprocal connections is sensitive to inflammatory processes occurring in different brain regions, thus acting as a "barometer" for diffuse brain parenchymal damage in MS. To what extent the thalamus is affected in commonly applied MS animal models is, however, not known. In this article we describe direct and indirect damage to the thalamus in two distinct MS animal models. In the cuprizone model, we observed primary oligodendrocyte stress which is followed by demyelination, microglia/astrocyte activation, and acute axonal damage. These degenerative cuprizone-induced lesions were found to be more severe in the lateral compared to the medial part of the thalamus. In MOG35-55-induced EAE, in contrast, most parts of the forebrain, including the thalamus were not directly involved in the autoimmune attack. However, important thalamic afferent fiber tracts, such as the spinothalamic tract were inflamed and demyelinated on the spinal cord level. Quantitative immunohistochemistry revealed that this spinal cord inflammatory-demyelination is associated with neuronal loss within the target region of the spinothalamic tract, namely the sensory ventral posterolateral nucleus of the thalamus. This study highlights the possibility of trans-neuronal degeneration as one mechanism of secondary neuronal damage in MS. Further studies are now warranted to investigate involved cell types and cellular mechanisms.

Morphological Abnormalities of Thalamic Subnuclei in Migraine: A Multicenter MRI Study at 3 Tesla

The thalamus contains third-order relay neurons of the trigeminal system, and animal models as well as preliminary imaging studies in small cohorts of migraine patients have suggested a role of the thalamus in headache pathophysiology. However, larger studies using advanced imaging techniques in substantial patient populations are lacking. In the present study, we investigated changes of thalamic volume and shape in a large multicenter cohort of patients with migraine. High-resolution T1-weighted MRI data acquired at 3 tesla in 131 patients with migraine (38 with aura; 30.8 ± 9 years old; 109 women; monthly attack frequency: 3.2 ± 2.5; disease duration: 14 ± 8.4 years) and 115 matched healthy subjects (29 ± 7 years old; 81 women) from four international tertiary headache centers were analyzed. The thalamus and thalamic subnuclei, striatum, and globus pallidus were segmented using a fully automated multiatlas approach. Deformation-based shape analysis was performed to localize surface abnormalities. Differences between patients with migraine and healthy subjects were assessed using an ANCOVA model. After correction for multiple comparisons, performed using the false discovery rate approach (p < 0.05 corrected), significant volume reductions of the following thalamic nuclei were observed in migraineurs: central nuclear complex (F(1,233) = 6.79), anterior nucleus (F(1,237) = 7.38), and lateral dorsal nucleus (F(1,238) = 6.79). Moreover, reduced striatal volume (F(1,238) = 6.9) was observed in patients. This large-scale study indicates structural thalamic abnormalities in patients with migraine. The thalamic nuclei with abnormal volumes are densely connected to the limbic system. The data hence lend support to the view that higher-order integration systems are altered in migraine.

SIGNIFICANCE STATEMENT

This multicenter imaging study shows morphological thalamic abnormalities in a large cohort of patients with episodic migraine compared with healthy subjects using state-of-the-art MRI and advanced, fully automated multiatlas segmentation techniques. The results stress that migraine is a disorder of the CNS in which not only is brain function abnormal, but also brain structure is undergoing significant remodeling.

Hippocampal (subfield) volume and shape in relation to cognitive performance across the adult lifespan

Newer approaches to characterizing hippocampal morphology can provide novel insights regarding cognitive function across the lifespan. We comprehensively assessed the relationships among age, hippocampal morphology, and hippocampal-dependent cognitive function in 137 healthy individuals across the adult lifespan (18-86 years of age). They underwent MRI, cognitive assessments and genotyping for Apolipoprotein E status. We measured hippocampal subfield volumes using a new multiatlas segmentation tool (MAGeT-Brain) and assessed vertex-wise (inward and outward displacements) and global surface-based descriptions of hippocampus morphology. We examined the effects of age on hippocampal morphology, as well as the relationship among age, hippocampal morphology, and episodic and working memory performance. Age and volume were modestly correlated across hippocampal subfields. Significant patterns of inward and outward displacement in hippocampal head and tail were associated with age. The first principal shape component of the left hippocampus, characterized by a lengthening of the antero-posterior axis was prominently associated with working memory performance across the adult lifespan. In contrast, no significant relationships were found among subfield volumes and cognitive performance. Our findings demonstrate that hippocampal shape plays a unique and important role in hippocampal-dependent cognitive aging across the adult lifespan, meriting consideration as a biomarker in strategies targeting the delay of cognitive aging.

Brain MRI lesions and atrophy are associated with employment status in patients with multiple sclerosis

Multiple sclerosis (MS) commonly affects occupational function. We investigated the link between brain MRI and employment status. Patients with MS (n = 100) completed a Work Productivity and Activity Impairment (WPAI) (general health version) survey measuring employment status, absenteeism, presenteeism, and overall work and daily activity impairment. Patients “working for pay” were considered employed; “temporarily not working but looking for work,” “not working or looking for work due to age,” and “not working or looking for work due to disability” were considered not employed. Brain MRI T1 hypointense (T1LV) and T2 hyperintense (T2LV) lesion volumes were quantified. To assess lesional destructive capability, we calculated each subject’s ratio of T1LV to T2LV (T1/T2). Normalized brain parenchymal volume (BPV) assessed brain atrophy. The mean (SD) age was 45.5 (9.7) years; disease duration was 12.1 (8.1) years; 75 % were women, 76 % were relapsing-remitting, and 76 % were employed. T1LV, T1/T2, Expanded Disability Status Scale (EDSS) scores, and activity impairment were lower and BPV was higher in the employed vs. not employed group (Wilcoxon tests, p < 0.05). Age, disease duration, MS clinical subtype, and T2LV did not differ between groups (p > 0.05). In multivariable logistic regression modeling, adjusting for age, sex, and disease duration, higher T1LV predicted a lower chance of employment (p < 0.05). Pearson correlations showed that EDSS was associated with activity impairment (p < 0.05). Disease duration, age, and MRI measures were not correlated with activity impairment or other WPAI outcomes (p > 0.05). We report a link between brain atrophy and lesions, particularly lesions with destructive potential, to MS employment status.

Connectivity-based parcellation of the thalamus in multiple sclerosis and its implications for cognitive impairment: A multicenter study

In this multicenter study, we performed a tractography-based parcellation of the thalamus and its white matter connections to investigate the relationship between thalamic connectivity abnormalities and cognitive impairment in multiple sclerosis (MS). Dual-echo, morphological and diffusion tensor (DT) magnetic resonance imaging (MRI) scans were collected from 52 relapsing-remitting MS patients and 57 healthy controls from six European centers. Patients underwent an extensive neuropsychological assessment. Thalamic connectivity defined regions (CDRs) were segmented based on their cortical connectivity using diffusion tractography-based parcellation. Between-group differences of CDRs and cortico-thalamic tracts DT MRI indices were assessed. A vertex analysis of thalamic shape was also performed. A random forest analysis was run to identify the best imaging predictor of global cognitive impairment and deficits of specific cognitive domains. Twenty-two (43%) MS patients were cognitively impaired (CI). Compared to cognitively preserved, CI MS patients had increased fractional anisotropy of frontal, motor, postcentral and occipital connected CDRs (0.002<P<0.02). They also experienced more pronounced atrophy in anterior thalamic regions and abnormal DT MRI indices of all cortico-thalamic tracts. Damage of specific cortico-thalamic tracts explained global cognitive dysfunction and impairment of selected cognitive domains better than all other MRI variables. Thalamic CDR DT MRI abnormalities were correlated with abnormalities of the corresponding cortico-thalamic tracts. Cortico-thalamic disconnection is, at various levels, implicated in cognitive dysfunction in MS. Thalamic involvement in CI MS patients is likely related to gray matter rather than white matter damage of thalamic subregions.

Striatal morphology is associated with tobacco cigarette craving

The striatum has a clear role in addictive disorders and is involved in drug-related craving. Recently, enhanced striatal volume was associated with greater lifetime nicotine exposure, suggesting a bridge between striatal function and structural phenotypes. To assess this link between striatal structure and function, we evaluated the relationship between striatal morphology and this brain region's well-established role in craving. In tobacco smokers, we assessed striatal volume, surface area, and shape using a new segmentation methodology coupled with local shape indices. Striatal morphology was then related with two measures of craving: state-based craving, assessed by the brief questionnaire of smoking urges (QSU), and craving induced by smoking-related images. A positive association was found between left striatal volume and surface area with both measures of craving. A more specific relationship was found between both craving measures and the dorsal, but not in ventral striatum. Evaluating dorsal striatal subregions showed a single relationship between the caudate and QSU. Although cue-induced craving and the QSU were both associated with enlarged striatal volume and surface area, these measures were differentially associated with global or more local striatal volumes. We also report a connection between greater right striatal shape deformations and cue-induced craving. Shape deformations associated with cue-induced craving were specific to striatal subregions involved in habitual responding to rewarding stimuli, which is relevant given the habitual nature of cue-induced craving. The current findings confirm a relationship between striatal function and morphology and suggest that variation in striatal morphology may be a biomarker for craving severity.