Trans-Synaptic Degeneration Following Acute Optic Neuritis in Multiple Sclerosis.

OBJECTIVE: To explore longitudinal changes in brain volumetric measures and retinal layer thicknesses following acute optic neuritis (AON) in people with multiple sclerosis (PwMS), to investigate the process of trans-synaptic degeneration, and determine its clinical relevance. METHODS: PwMS were recruited within 40 days of AON onset (n = 49), and underwent baseline retinal optical coherence tomography and brain magnetic resonance imaging followed by longitudinal tracking for up to 5 years. A comparator cohort of PwMS without a recent episode of AON were similarly tracked (n = 73). Mixed-effects linear regression models were used. RESULTS: Accelerated atrophy of the occipital gray matter (GM), calcarine GM, and thalamus was seen in the AON cohort, as compared with the non-AON cohort (-0.76% vs -0.22% per year [p = 0.01] for occipital GM, -1.83% vs -0.32% per year [p = 0.008] for calcarine GM, -1.17% vs -0.67% per year [p = 0.02] for thalamus), whereas rates of whole-brain, cortical GM, non-occipital cortical GM atrophy, and T2 lesion accumulation did not differ significantly between the cohorts. In the AON cohort, greater AON-induced reduction in ganglion cell+inner plexiform layer thickness over the first year was associated with faster rates of whole-brain (r = 0.32, p = 0.04), white matter (r = 0.32, p = 0.04), and thalamic (r = 0.36, p = 0.02) atrophy over the study period. Significant relationships were identified between faster atrophy of the subcortical GM and thalamus, with worse visual function outcomes after AON. INTERPRETATION: These results provide in-vivo evidence for anterograde trans-synaptic degeneration following AON in PwMS, and suggest that trans-synaptic degeneration may be related to clinically-relevant visual outcomes. ANN NEUROL 2023;93:76-87.

Effect of Direction and Frequency of Skull Motion on Mechanical Vulnerability of the Human Brain.

Strain energy and kinetic energy in the human brain were estimated by magnetic resonance elastography (MRE) during harmonic excitation of the head, and compared to characterize the effect of loading direction and frequency on brain deformation. In brain MRE, shear waves are induced by external vibration of the skull and imaged by a modified MR imaging sequence; the resulting harmonic displacement fields are typically "inverted" to estimate mechanical properties, like stiffness or damping. However, measurements of tissue motion from MRE also illuminate key features of the response of the brain to skull loading. In this study, harmonic excitation was applied in two different directions and at five different frequencies from 20 to 90 Hz. Lateral loading induced primarily left-right head motion and rotation in the axial plane; occipital loading induced anterior-posterior head motion and rotation in the sagittal plane. The ratio of strain energy to kinetic energy (SE/KE) depended strongly on both direction and frequency. The ratio of SE/KE was approximately four times larger for lateral excitation than for occipital excitation and was largest at the lowest excitation frequencies studied. These results are consistent with clinical observations that suggest lateral impacts are more likely to cause injury than occipital or frontal impacts, and also with observations that the brain has low-frequency (∼10 Hz) natural modes of oscillation. The SE/KE ratio from brain MRE is potentially a simple and powerful dimensionless metric of brain vulnerability to deformation and injury.

Deep learning in optical coherence tomography: Where are the gaps?

Optical coherence tomography (OCT) is a non-invasive optical imaging modality, which provides rapid, high-resolution and cross-sectional morphology of macular area and optic nerve head for diagnosis and managing of different eye diseases. However, interpreting OCT images requires experts in both OCT images and eye diseases since many factors such as artefacts and concomitant diseases can affect the accuracy of quantitative measurements made by post-processing algorithms. Currently, there is a growing interest in applying deep learning (DL) methods to analyse OCT images automatically. This review summarises the trends in DL-based OCT image analysis in ophthalmology, discusses the current gaps, and provides potential research directions. DL in OCT analysis shows promising performance in several tasks: (1) layers and features segmentation and quantification; (2) disease classification; (3) disease progression and prognosis; and (4) referral triage level prediction. Different studies and trends in the development of DL-based OCT image analysis are described and the following challenges are identified and described: (1) public OCT data are scarce and scattered; (2) models show performance discrepancies in real-world settings; (3) models lack of transparency; (4) there is a lack of societal acceptance and regulatory standards; and (5) OCT is still not widely available in underprivileged areas. More work is needed to tackle the challenges and gaps, before DL is further applied in OCT image analysis for clinical use.

Optic Neuritis-Independent Retinal Atrophy in Neuromyelitis Optica Spectrum Disorder.

BACKGROUND: A limited number of studies have investigated the presence of ongoing disease activity independent of clinical relapses in neuromyelitis optica spectrum disorder (NMOSD), and data are conflicting. The objective of our study was to examine whether patients with aquaporin-4 (AQP4)-IgG seropositive NMOSD exhibit progressive retinal neuroaxonal loss, independently of optic neuritis (ON) attacks. METHODS: In this single-center, longitudinal study, 32 AQP4-IgG+ NMOSD patients and 48 healthy controls (HC) were followed with serial spectral-domain optical coherence tomography and visual acuity (VA) assessments. NMOSD patients with ON less than 6 months before baseline were excluded, whereas data from patients with ON during follow-up were censored at the last visit before ON. VA worsening was defined as a decrease in monocular letter acuity ≥5 letters for high-contrast VA and ≥7 letters for low-contrast VA. Analyses were performed with mixed-effects linear regression models adjusted for age, sex, and race. RESULTS: The median follow-up duration was 4.2 years (interquartile range: 1.8-7.5). Relative to HC, NMOSD eyes had faster peripapillary retinal nerve fiber layer (pRNFL) (ß = -0.25 µm/year faster, 95% confidence interval [CI]: -0.45 to -0.05, P = 0.014) and GCIPL thinning (ß = -0.09 µm/year faster, 95% CI: -0.17 to 0, P = 0.05). This difference seemed to be driven by faster pRNFL and GCIPL thinning in NMOSD eyes without a history of ON compared with HC (GCIPL: ß = -0.15 µm/year faster; P = 0.005; pRNFL: ß = -0.43 µm/year faster, P < 0.001), whereas rates of pRNFL (ß: -0.07 µm/year, P = 0.53) and GCIPL (ß = -0.01 µm/year, P = 0.90) thinning did not differ between NMOSD-ON and HC eyes. Nine NMOSD eyes had VA worsening during follow-up. CONCLUSIONS: In this longitudinal study, we observed progressive pRNFL and GCIPL atrophy in AQP4-IgG+ NMOSD eyes unaffected by ON. These results support that subclinical involvement of the anterior visual pathway may occur in AQP4-IgG+ NMOSD.

Unsupervised MR harmonization by learning disentangled representations using information bottleneck theory.

In magnetic resonance (MR) imaging, a lack of standardization in acquisition often causes pulse sequence-based contrast variations in MR images from site to site, which impedes consistent measurements in automatic analyses. In this paper, we propose an unsupervised MR image harmonization approach, CALAMITI (Contrast Anatomy Learning and Analysis for MR Intensity Translation and Integration), which aims to alleviate contrast variations in multi-site MR imaging. Designed using information bottleneck theory, CALAMITI learns a globally disentangled latent space containing both anatomical and contrast information, which permits harmonization. In contrast to supervised harmonization methods, our approach does not need a sample population to be imaged across sites. Unlike traditional unsupervised harmonization approaches which often suffer from geometry shifts, CALAMITI better preserves anatomy by design. The proposed method is also able to adapt to a new testing site with a straightforward fine-tuning process. Experiments on MR images acquired from ten sites show that CALAMITI achieves superior performance compared with other harmonization approaches.

Prospective motion detection and re-acquisition in diffusion MRI using a phase image-based method-Application to brain and tongue imaging.

PURPOSE: To develop an image-based motion-robust diffusion MRI (dMRI) acquisition framework that is able to minimize motion artifacts caused by rigid and nonrigid motion, applicable to both brain and tongue dMRI. METHODS: We developed a novel prospective motion-correction technique in dMRI using a phase image-based real-time motion-detection method (PITA-MDD) with re-acquisition of motion-corrupted images. The prospective PITA-MDD acquisition technique was tested in the brains and tongues of volunteers. The subjects were instructed to move their heads or swallow, to induce motion. Motion-detection efficacy was validated against visual inspection as the gold standard. The effect of the PITA-MDD technique on diffusion-parameter estimates was evaluated by comparing reconstructed fiber tracts using tractography with and without re-acquisition. RESULTS: The prospective PITA-MDD technique was able to effectively and accurately detect motion-corrupted data as compared with visual inspection. Tractography results demonstrated that PITA-MDD motion detection followed by re-acquisition helps in recovering lost and misshaped fiber tracts in the brain and tongue that would otherwise be corrupted by motion and yield erroneous estimates of the diffusion tensor. CONCLUSION: A prospective PITA-MDD technique was developed for dMRI acquisition, providing improved dMRI image quality and motion-robust diffusion estimation of the brain and tongue.

Progressive Multiple Sclerosis Is Associated with Faster and Specific Retinal Layer Atrophy.

OBJECTIVE: Therapeutic development in progressive multiple sclerosis (PMS) has been hampered by a lack of reliable biomarkers to monitor neurodegeneration. Optical coherence tomography (OCT)-derived retinal measures have been proposed as promising biomarkers to fulfill this role. However, it is unclear whether retinal atrophy persists in PMS, exceeds normal aging, or can be distinguished from relapsing-remitting multiple sclerosis (RRMS). METHODS: 178 RRMS, 186 PMS, and 66 control participants were followed with serial OCT for a median follow-up of 3.7 years. RESULTS: The estimated proportion of peripapillary retinal nerve fiber layer (pRNFL) and macular ganglion cell + inner plexiform layer (GCIPL) thinning in multiple sclerosis (MS) attributable to normal aging increased from 42.7% and 16.7% respectively at age 25 years, to 83.7% and 81.1% at age 65 years. However, independent of age, PMS was associated with faster pRNFL (-0.34 ± 0.09%/yr, p < 0.001) and GCIPL (-0.27 ± 0.07%/yr, p < 0.001) thinning, as compared to RRMS. In both MS and controls, higher baseline age was associated with faster inner nuclear layer (INL) and outer nuclear layer (ONL) thinning. INL and ONL thinning were independently faster in PMS, as compared to controls (INL:-0.09 ± 0.04%/yr, p = 0.03; ONL:-0.12 ± 0.06%/yr, p = 0.04), and RRMS (INL:-0.10 ± 0.04%/yr, p = 0.01; ONL:-0.13 ± 0.05%/yr, p = 0.01), whereas they were similar in RRMS and controls. Unlike RRMS, disease-modifying therapies (DMTs) did not impact rates of retinal layer atrophy in PMS. INTERPRETATION: PMS is associated with faster retinal atrophy independent of age. INL and ONL measures may be novel biomarkers of neurodegeneration in PMS that appear to be unaffected by conventional DMTs. The effects of aging on rates of retinal layer atrophy should be considered in clinical trials incorporating OCT outcomes. ANN NEUROL 2020;87:885-896.

Serum ceramide levels are altered in multiple sclerosis.

BACKGROUND: Sphingolipids are myelin components and inflammatory signaling intermediates. Sphingolipid metabolism may be altered in people with multiple sclerosis (PwMS), but existing studies are limited by small sample sizes. OBJECTIVES: To compare the levels of serum ceramides between PwMS and healthy controls (HCs) and to determine whether ceramide levels correlate with disability status, as well as optical coherence tomography (OCT)-derived rates of retinal layer atrophy. METHODS: We performed targeted lipidomics analyses for 45 ceramides in PwMS (n = 251) and HCs (n = 68). For a subset of PwMS, baseline and 5-year Expanded Disability Status Scale (EDSS) assessments (n = 185), or baseline and serial spectral-domain OCT (n = 180) were assessed. RESULTS: Several ceramides, including hexosylceramides, lactosylceramides, and dihydroceramides, were altered in PwMS compared with HCs. Higher levels of Cer16:0 were associated with higher odds of EDSS worsening at 5 years in univariable (odds ratio (OR) = 3.84, 95% confidence interval (CI) = 1.41-10.43) and multivariable analyses accounting for age, sex, and race (OR = 2.97, 95% CI = 1.03-8.59). Each 1 ng/mL higher concentration of Hex-Cer22:0 and DH-HexCer22:0 was associated with accelerated rates (µm/year) of ganglion cell + inner plexiform layer (-0.138 ± 0.053, p = 0.01; -0.158 ± 0.053, p = 0.003, respectively) and peripapillary retinal nerve fiber layer thinning (-0.305 ± 0.107, p = 0.004; -0.358 ± 0.106, p = 0.001, respectively). CONCLUSION: Ceramide levels are altered in PwMS and may be associated with retinal neurodegeneration and physical disability.

Evidence of subclinical quantitative retinal layer abnormalities in AQP4-IgG seropositive NMOSD.

BACKGROUND: Prior studies have suggested that subclinical retinal abnormalities may be present in aquaporin-4 immunoglobulin G (AQP4-IgG) seropositive neuromyelitis optica spectrum disorder (NMOSD), in the absence of a clinical history of optic neuritis (ON). OBJECTIVE: Our aim was to compare retinal layer thicknesses at the fovea and surrounding macula between AQP4-IgG+ NMOSD eyes without a history of ON (AQP4-nonON) and healthy controls (HC). METHODS: In this single-center cross-sectional study, 83 AQP4-nonON and 154 HC eyes were studied with spectral-domain optical coherence tomography (OCT). RESULTS: Total foveal thickness did not differ between AQP4-nonON and HC eyes. AQP4-nonON eyes exhibited lower outer nuclear layer (ONL) and inner photoreceptor segment (IS) thickness at the fovea (ONL: -4.01 ± 2.03 µm, p = 0.049; IS: -0.32 ± 0.14 µm, p = 0.029) and surrounding macula (ONL: -1.98 ± 0.95 µm, p = 0.037; IS: -0.16 ± 0.07 µm, p = 0.023), compared to HC. Macular retinal nerve fiber layer (RNFL: -1.34 ± 0.51 µm, p = 0.009) and ganglion cell + inner plexiform layer (GCIPL: -2.44 ± 0.93 µm, p = 0.009) thicknesses were also lower in AQP4-nonON compared to HC eyes. Results were similar in sensitivity analyses restricted to AQP4-IgG+ patients who had never experienced ON in either eye. CONCLUSIONS: AQP4-nonON eyes exhibit evidence of subclinical retinal ganglion cell neuronal and axonal loss, as well as structural evidence of photoreceptor layer involvement. These findings support that subclinical anterior visual pathway involvement may occur in AQP4-IgG+ NMOSD.

A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises.

Since its renaissance, deep learning has been widely used in various medical imaging tasks and has achieved remarkable success in many medical imaging applications, thereby propelling us into the so-called artificial intelligence (AI) era. It is known that the success of AI is mostly attributed to the availability of big data with annotations for a single task and the advances in high performance computing. However, medical imaging presents unique challenges that confront deep learning approaches. In this survey paper, we first present traits of medical imaging, highlight both clinical needs and technical challenges in medical imaging, and describe how emerging trends in deep learning are addressing these issues. We cover the topics of network architecture, sparse and noisy labels, federating learning, interpretability, uncertainty quantification, etc. Then, we present several case studies that are commonly found in clinical practice, including digital pathology and chest, brain, cardiovascular, and abdominal imaging. Rather than presenting an exhaustive literature survey, we instead describe some prominent research highlights related to these case study applications. We conclude with a discussion and presentation of promising future directions.

Early Stage Longitudinal Subcortical Volumetric Changes following Mild Traumatic Brain Injury.

Objective: To investigate early brain volumetric changes from acute to 6 months following mild traumatic brain injury (mTBI) in deep gray matter regions and their association with patient 6-month outcome.Methods: Fifty-six patients with mTBI underwent MRI and behavioral evaluation at acute (<10 days) and approximately 1 and 6 months post injury. Regional volume changes were investigated in key gray matter regions: thalamus, hippocampus, putamen, caudate, pallidum, and amygdala, and compared with volumes from 34 healthy control subjects. In patients with mTBI, we further assessed associations between longitudinal regional volume changes with patient outcome measures at 6 months including post-concussive symptoms, cognitive performance, and overall satisfaction with life.Results: Reduction in thalamic and hippocampal volumes was observed at 1 month among patients with mTBI. Such volume reduction persisted in the thalamus until 6 months. Changes in thalamic volumes also correlated with multiple symptom and functional outcome measures in patients at 6 months.Conclusion: Our results indicate that the thalamus may be differentially affected among patients with mTBI, resulting in both structural and functional deficits with subsequent post-concussive sequelae and may serve as a biomarker for the assessment of efficacy of novel therapeutic interventions.

Automatic cerebellum anatomical parcellation using U-Net with locally constrained optimization.

The cerebellum plays a central role in sensory input, voluntary motor action, and many neuropsychological functions and is involved in many brain diseases and neurological disorders. Cerebellar parcellation from magnetic resonance images provides a way to study regional cerebellar atrophy and also provides an anatomical map for functional imaging. In a recent comparison, a multi-atlas approach proved to be superior to other parcellation methods including some based on convolutional neural networks (CNNs) which have a considerable speed advantage. In this work, we developed an alternative CNN design for cerebellar parcellation, yielding a method that achieves the leading performance to date. The proposed method was evaluated on multiple data sets to show its broad applicability, and a Singularity container has been made publicly available.

Longitudinal analysis of regional cerebellum volumes during normal aging.

Some cross-sectional studies suggest reduced cerebellar volumes with aging, but there have been few longitudinal studies of age changes in cerebellar subregions in cognitively healthy older adults. In this work, 2,023 magnetic resonance (MR) images of 822 cognitively normal participants from the Baltimore Longitudinal Study of Aging (BLSA) were analyzed. Participants ranged in age from 50 to 95 years (mean 70.7 years) at the baseline assessment. Follow-up intervals were 1-9 years (mean 3.7 years) for participants with two or more visits. We used a recently developed cerebellum parcellation algorithm based on convolutional neural networks to divide the cerebellum into 28 subregions. Linear mixed effects models were applied to the volume of each cerebellar subregion to investigate cross-sectional and longitudinal age effects, as well as effects of sex and their interactions, after adjusting for intracranial volume. Our findings suggest spatially varying atrophy patterns across the cerebellum with respect to age and sex both cross-sectionally and longitudinally.

Association of body mass index with longitudinal rates of retinal atrophy in multiple sclerosis.

BACKGROUND: Studies evaluating associations between body mass index (BMI) and optical coherence tomography (OCT) measures in multiple sclerosis (MS) are lacking. OBJECTIVE: To assess whether elevated BMI is associated with accelerated retinal atrophy. METHODS: In this observational study, 513 MS patients were followed with serial spectral-domain OCT for a median of 4.4 years. Participants were categorized as normal weight (BMI: 18.5-24.9 kg/m2), overweight (BMI: 25-29.9 kg/m2), and obese (BMI: ⩾30 kg/m2). Participants with diabetes mellitus or uncontrolled hypertension and eyes with optic neuritis (ON) ⩽6 months prior to baseline OCT or during follow-up were excluded. Statistical analyses were performed with mixed-effects linear regression. RESULTS: Obese patients (n = 146) exhibited accelerated rates of ganglion cell + inner plexiform layer (GCIPL) atrophy relative to normal weight patients (n = 214; -0.57%/year (95% confidence interval (CI): -0.65% to -0.48%) versus -0.42%/year (95% CI: -0.49% to -0.35%); p = 0.012). GCIPL atrophy rate did not differ between overweight (n = 153) and normal weight patients (-0.47%/year vs -0.42%/year; p = 0.41). Each 1 kg/m2 higher BMI was associated with accelerated GCIPL (-0.011%/year; 95% CI: -0.019% to -0.004%; p = 0.003) atrophy. Multivariable analyses accounting for age, sex, race, MS subtype, and ON history did not alter the above findings. CONCLUSIONS: Elevated BMI, in the absence of overt metabolic comorbidities, may be associated with accelerated GCIPL atrophy. Obesity, a modifiable risk factor, may be associated with accelerated neurodegeneration in MS.

Aquaporin-4 IgG seropositivity is associated with worse visual outcomes after optic neuritis than MOG-IgG seropositivity and multiple sclerosis, independent of macular ganglion cell layer thinning.

BACKGROUND: Comparative studies of characteristics of optic neuritis (ON) associated with myelin oligodendrocyte glycoprotein-IgG (MOG-ON) and aquaporin-4-IgG (AQP4-ON) seropositivity are limited. OBJECTIVE: To compare visual and optical coherence tomography (OCT) measures following AQP4-ON, MOG-ON, and multiple sclerosis associated ON (MS-ON). METHODS: In this cross-sectional study, 48 AQP4-ON, 16 MOG-ON, 40 MS-ON, and 31 healthy control participants underwent monocular letter-acuity assessment and spectral-domain OCT. Eyes with a history of ON >3 months prior to evaluation were analyzed. RESULTS: AQP4-ON eyes exhibited worse high-contrast letter acuity (HCLA) compared to MOG-ON (-22.3 ± 3.9 letters; p < 0.001) and MS-ON eyes (-21.7 ± 4.0 letters; p < 0.001). Macular ganglion cell + inner plexiform layer (GCIPL) thickness was lower, as compared to MS-ON, in AQP4-ON (-9.1 ± 2.0 µm; p < 0.001) and MOG-ON (-7.6 ± 2.2 µm; p = 0.001) eyes. Lower GCIPL thickness was associated with worse HCLA in AQP4-ON (-16.5 ± 1.5 letters per 10 µm decrease; p < 0.001) and MS-ON eyes (-8.5 ± 2.3 letters per 10 µm decrease; p < 0.001), but not in MOG-ON eyes (-5.2 ± 3.8 letters per 10 µm decrease; p = 0.17), and these relationships differed between the AQP4-ON and other ON groups (p < 0.01 for interaction). CONCLUSION: AQP4-IgG seropositivity is associated with worse visual outcomes after ON compared with MOG-ON and MS-ON, even with similar severity of macular GCIPL thinning.

Effect of disease-modifying therapies on subcortical gray matter atrophy in multiple sclerosis.

BACKGROUND: The effects of disease-modifying therapies (DMTs) on region-specific brain atrophy in multiple sclerosis (MS) are unclear. OBJECTIVE: To determine the effects of higher versus lower efficacy DMTs on rates of brain substructure atrophy in MS. METHODS: A non-randomized, observational cohort of people with MS followed with annual brain magnetic resonance imaging (MRI) was evaluated retrospectively. Whole brain, subcortical gray matter (GM), cortical GM, and cerebral white matter (WM) volume fractions were obtained. DMTs were categorized as higher (DMT-H: natalizumab and rituximab) or lower (DMT-L: interferon-beta and glatiramer acetate) efficacy. Follow-up epochs were analyzed if participants had been on a DMT for ⩾6 months prior to baseline and had at least one follow-up MRI while on DMTs in the same category. RESULTS: A total of 86 DMT epochs (DMT-H: n = 32; DMT-L: n = 54) from 78 participants fulfilled the study inclusion criteria. Mean follow-up was 2.4 years. Annualized rates of thalamic (-0.15% vs -0.81%; p = 0.001) and putaminal (-0.27% vs -0.73%; p = 0.001) atrophy were slower during DMT-H compared to DMT-L epochs. These results remained significant in multivariate analyses including demographics, clinical characteristics, and T2 lesion volume. CONCLUSION: DMT-H treatment may be associated with slower rates of subcortical GM atrophy, especially of the thalamus and putamen. Thalamic and putaminal volumes are promising imaging biomarkers in MS.

Alterations in the retinal vasculature occur in multiple sclerosis and exhibit novel correlations with disability and visual function measures.

BACKGROUND: The retinal vasculature may be altered in multiple sclerosis (MS), potentially acting as a biomarker of disease processes. OBJECTIVE: To compare retinal vascular plexus densities in people with MS (PwMS) and healthy controls (HCs), and examine correlations with visual function and global disability. METHODS: In this cross-sectional study, 111 PwMS (201 eyes) and 50 HCs (97 eyes) underwent optical coherence tomography angiography (OCTA). Macular superficial vascular plexus (SVP) and deep vascular plexus (DVP) densities were quantified, and poor quality images were excluded according to an artifact-rating protocol. RESULTS: Mean SVP density was 24.1% (SD = 5.5) in MS eyes (26.0% (SD = 4.7) in non-optic neuritis (ON) eyes vs. 21.7% (SD = 5.5) in ON eyes, p < 0.001), as compared to 29.2% (SD = 3.3) in HC eyes (p < 0.001 for all MS eyes and multiple sclerosis optic neuritis (MSON) eyes vs. HC eyes, p = 0.03 for MS non-ON eyes vs. HC eyes). DVP density did not differ between groups. In PwMS, lower SVP density was associated with higher levels of disability (expanded disability status scale (EDSS): R2 = 0.26, p = 0.004; multiple sclerosis functional composite (MSFC): R2 = 0.27, p = 0.03) and lower letter acuity scores (100% contrast: R2 = 0.29; 2.5% contrast: R2 = 0.40; 1.25% contrast: R2 = 0.31; p < 0.001 for all). CONCLUSIONS: Retinal SVP density measured by OCTA is reduced across MS eyes, and correlates with visual function, EDSS, and MSFC scores.

Spinal cord and infratentorial lesions in radiologically isolated syndrome are associated with decreased retinal ganglion cell/inner plexiform layer thickness.

BACKGROUND: The role of retinal imaging with optical coherence tomography (OCT) in assessing individuals with radiologically isolated syndrome (RIS) remains largely unexplored. OBJECTIVE: To assess retinal layer thicknesses in RIS and examine their associations with clinical features suggestive of increased risk for conversion to multiple sclerosis (MS). METHODS: A total of 30 RIS subjects and 60 age- and sex-matched healthy controls (HC) underwent retinal imaging with spectral-domain OCT, followed by automated segmentation of retinal layers. RESULTS: Overall, retinal layer thicknesses did not differ between RIS and HC. However, RIS subjects with spinal cord (SC) lesions had lower ganglion cell + inner plexiform layer (GCIP) thickness compared to HC (-4.41 µm; p = 0.007) and RIS without SC lesions (-3.53 µm; p = 0.041). Similarly, RIS subjects with infratentorial (IT) brain lesions had lower GCIP thickness compared to HC (-4.07 µm; p < 0.001) and RIS without IT lesions (-3.49 µm; p = 0.029). Multivariate analyses revealed that the presence of SC or IT lesions were independently associated with lower GCIP thickness in RIS (p = 0.04 and p = 0.03, respectively). Other patient characteristics, including sex, abnormal cerebrospinal fluid, and presence of gadolinium-enhancing or juxtacortical lesions, were not associated with retinal layer thicknesses. CONCLUSION: The presence of SC or IT lesions in RIS may be associated with retinal neuro-axonal loss, supporting the presence of more disseminated disease.

Differentiating post-cancer from healthy tongue muscle coordination patterns during speech using deep learning.

The ability to differentiate post-cancer from healthy tongue muscle coordination patterns is necessary for the advancement of speech motor control theories and for the development of therapeutic and rehabilitative strategies. A deep learning approach is presented to classify two groups using muscle coordination patterns from magnetic resonance imaging (MRI). The proposed method uses tagged-MRI to track the tongue's internal tissue points and atlas-driven non-negative matrix factorization to reduce the dimensionality of the deformation fields. A convolutional neural network is applied to the classification task yielding an accuracy of 96.90%, offering the potential to the development of therapeutic or rehabilitative strategies in speech-related disorders.

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.

The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is important in the study of several neurological diseases including cerebellar ataxia, autism, and schizophrenia. Different structural subdivisions of the cerebellum have been shown to correlate with differing pathologies. To further understand these pathologies, it is helpful to automatically parcellate the cerebellum at the highest fidelity possible. In this paper, we coordinated with colleagues around the world to evaluate automated cerebellum parcellation algorithms on two clinical cohorts showing that the cerebellum can be parcellated to a high accuracy by newer methods. We characterize these various methods at four hierarchical levels: coarse (i.e., whole cerebellum and gross structures), lobe, subdivisions of the vermis, and the lobules. Due to the number of labels, the hierarchy of labels, the number of algorithms, and the two cohorts, we have restricted our analyses to the Dice measure of overlap. Under these conditions, machine learning based methods provide a collection of strategies that are efficient and deliver parcellations of a high standard across both cohorts, surpassing previous work in the area. In conjunction with the rank-sum computation, we identified an overall winning method.