Deep Gray Matter Research Articles

PLA2G6-associated neurodegeneration in four different populations-case series and literature review

BackgroundPLA2G6-Associated Neurodegeneration, PLAN, is subdivided into: Infantile neuroaxonal dystrophy, atypical neuroaxonal dystrophy, and adult-onset dystonia parkinsonism [1]. It is elicited by a biallelic pathogenic variant in phospholipase A2 group VI (PLA2G6) gene. In this study we describe new cases and provide a comprehensive review of previously published cases. MethodsEleven patients, from four different institutions and four different countries. All underwent a comprehensive chart review. ResultsAges at onset ranged from 1 to 36 years, with a median of 16 and a mean of 16.18 ± 11.91 years. Phenotypic characteristics were heterogenous and resembled that of patients with infantile neuroaxonal dystrophy (n = 2), atypical neuroaxonal dystrophy (n = 1), adult-onset dystonia parkinsonism (n = 1), complex hereditary spastic paraparesis (n = 3), and early onset Parkinson's disease (n = 2). Parental genetic studies were performed for all patients and confirmed with sanger sequencing in five. Visual evoked potential illustrated optic atrophy in P4. Mineralization was evident in brain magnetic resonance imaging of P1, P2, P4, P5, P7, and P11. Single photon emission computed tomography was conducted for three patients, revealed decreased perfusion in the occipital lobes for P10. DaTscan was performed for P11 and showed decreased uptake in the deep gray matter, bilateral caudate nuclei, and bilateral putamen. Positive response to Apomorphine was noted for P10 and to Baclofen in P2, and P3. ConclusionsPLAN encompasses a wide clinical spectrum. Age and symptom at onset are crucial when classifying patients. Reporting new variants is critical to draw more attention to this condition and identify biomarkers to arrive at potential therapeutics.

Associations of Macronutrient Intake Determined by Point-of-Care Human Milk Analysis with Brain Development among very Preterm Infants.

Point-of-care human milk analysis is now feasible in the neonatal intensive care unit (NICU) and allows accurate measurement of macronutrient delivery. Higher macronutrient intakes over this period may promote brain growth and development. In a prospective, observational study of 55 infants born at <32 weeks’ gestation, we used a mid-infrared spectroscopy-based human milk analyzer to measure the macronutrient content in repeated samples of human milk over the NICU hospitalization. We calculated daily nutrient intakes from unfortified milk and assigned infants to quintiles based on median intakes over the hospitalization. Infants underwent brain magnetic resonance imaging at term equivalent age to quantify total and regional brain volumes and fractional anisotropy of white matter tracts. Infants in the highest quintile of energy intake from milk, as compared with the lower four quintiles, had larger total brain volume (31 cc, 95% confidence interval [CI]: 5, 56), cortical gray matter (15 cc, 95%CI: 1, 30), and white matter volume (23 cc, 95%CI: 12, 33). Higher protein intake was associated with larger total brain (36 cc, 95%CI: 7, 65), cortical gray matter (22 cc, 95%CI: 6, 38) and deep gray matter (1 cc, 95%CI: 0.1, 3) volumes. These findings suggest innovative strategies to close nutrient delivery gaps in the NICU may promote brain growth for preterm infants.

Multi-echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla.

PurposeTo compare different multi‐echo combination methods for MRI QSM. Given the current lack of consensus, we aimed to elucidate how to optimally combine multi‐echo gradient‐recalled echo signal phase information, either before or after applying Laplacian‐base methods (LBMs) for phase unwrapping or background field removal.MethodsMulti‐echo gradient‐recalled echo data were simulated in a numerical head phantom, and multi‐echo gradient‐recalled echo images were acquired at 3 Tesla in 10 healthy volunteers. To enable image‐based estimation of gradient‐recalled echo signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: 1 applied nonlinear phase fitting over TEs before LBMs; 2 applied LBMs to the TE‐dependent phase and then combined multiple TEs via either TE‐weighted or SNR‐weighted averaging; and 2 calculated TE‐dependent susceptibility maps via either multi‐step or single‐step QSM and then combined multiple TEs via magnitude‐weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland–Altman) and regional differences between the means (nonparametric tests).ResultsNonlinearly fitting the multi‐echo phase over TEs before applying LBMs provided the highest regional accuracy of χ and the lowest phase noise propagation compared to averaging the LBM‐processed TE‐dependent phase. This result was especially pertinent in high‐susceptibility venous regions.ConclusionFor multi‐echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs.

Post mortem evaluation of brain edema using quantitative MRI

The post mortem assessment of brain edema is routinely performed during autopsy by forensic pathologists who evaluate the macroscopically visible signs. In this study, the suitability of magnetic resonance imaging (MRI) for a differentiation between edematous and nonedematous brains was examined as an objective, noninvasive and quantitative rating method. In this study, 22 deceased underwent post mortem in situ MRI prior to regular autopsy. Acquired MRI sequences allowed the computation of the quantitative MRI parameters T1, T2, T2*, fractional anisotropy (FA) and mean diffusivity for the cortex, white matter and deep gray matter separately. Beside the autopsy results, which represent the gold standard for rating brain edema, also the normalized cerebral weight (NCW) was determined by dividing the brain weight by the intracranial volume as developed by Bauer et al. [10]. For further examination of the relation of MRI parameters with the NCW, linear regression models were calculated. The results revealed highly significant correlations of the MRI parameters T2 and FA with the NCW in the cortex. These combinations additionally showed the best fitting results of the linear regression models. In conclusion, quantitative MRI is suitable for differentiating edematous from nonedematous brains by calculating T2 and FA in the cortex. A post mortem in situ MRI scan of the brain can, besides delivering morphological information, add relevant and objective information on the edema status of the brain prior to autopsy or when no autopsy is ordered.

Brain structural and functional connectivity alterations are associated with fatigue in neuromyelitis optica spectrum disorder

BackgroundMany patients with neurological disorders experience chronic fatigue, but the neural mechanisms involved are unclear.ObjectiveHere we investigated whether the brain structural and functional connectivity alterations were involved in fatigue related to neuromyelitis optica spectrum disorder (NMOSD).MethodsThis prospective pilot study used structural and resting-state functional brain magnetic resonance imaging to compare total cortical thickness, cortical surface area, deep gray matter volume and functional connectivity (FC) between 33 patients with NMOSD and 20 healthy controls (HCs). Patients were subgrouped as low fatigue (LF) and high fatigue (HF).ResultsHF patients scored higher on the Hamilton Anxiety Rating Scale and Hamilton Rating Scale for Depression than LF patients and HCs. The two patient subgroups and HC group did not differ significantly in cortical thickness, cortical surface area and volumes of the bilateral caudate nucleus, bilateral putamen, bilateral amygdala, bilateral hippocampus, bilateral thalamus proper or right nucleus accumbens (p > 0.05). However, after correcting for age, sex, years of education, anxiety and depression, HF patients showed larger left pallidum than HCs (0.1573 ± 0.0214 vs 0.1372 ± 0.0145, p = 0.009). Meanwhile, both LF patients (0.0377 ± 0.0052 vs 0.0417 ± 0.0052, p = 0.009) and HF patients (0.0361 ± 0.0071 vs 0.0417 ± 0.0052, p = 0.013) showed smaller left nucleus accumbens than HCs.. Compared with LF patients, HF patients showed significantly decreased FC between the left pallidum and bilateral cerebellar posterior lobes.ConclusionsThis was the first evidence linking structural and functional alterations in the brain to fatigue in NMOSD, and in the future, long term follow-up was necessary.

White Matter Tract Injury by MRI in CADASIL Patients is Associated With Iron Accumulation.

Widespread white matter (WM) injury is a hallmark feature of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). However, controversies about the mechanism of WM tract injury exist persistently. Excessive iron accumulation, frequently reported in CADASIL patients, might cause WM tract injury. To test the association between iron accumulation and WM tract injury in CADASIL patients. Retrospective. A total of 35 CADASIL patients (age = 50.4 ± 6.4, 62.9% female) and 48 healthy controls (age = 55.7 ± 8.0, 68.8% female). Diffusion-weighted spin-echo echo-planar sequence; enhanced susceptibility-weighted angiography (ESWAN) gradient echo sequence on a 3T scanner. The phase images acquired by ESWAN were used to calculate quantitative susceptibility mapping (QSM). Iron accumulation was evaluated in deep gray matters using QSM. WM tract injury was quantified by diffusion metrics based on WM major tracts skeleton. We compared iron deposition between groups and analyzed the correlation between WM tract injury and iron deposition in regions showing significant differences from healthy controls. Exploratory analysis was carried out to investigate whether WM tract injury mediated the relationship between iron deposition and cognitive impairment evaluated by Mini-Mental State Examination (MMSE). General linear model (GLM), partial correlation, stepwise linear regression and mediation analysis were used. The threshold of statistical significance was set as p < 0.05. Compared with healthy controls, CADASIL patients had significantly increased iron deposition in the caudate and putamen. Aberrant iron deposition in these two regions was significantly associated with decreased WM fractional anisotropy (FA) (caudate, r = -0.373； putamen, r = - 0.421), and increased radial diffusivity (RD) (caudate, r = 0.372; putamen, r = 0.386). Furthermore, WM tract injury mediated the relationship between iron deposition and cognitive impairment. Patients with CADASIL show increased iron deposition in the caudate and putamen that is correlated to WM tract injury, which may in turn mediate the association with cognitive impairment. 2 TECHNICAL EFFICACY: Stage 2.

The Effect of Smoking on Long-term Gray Matter Atrophy and Clinical Disability in Patients with Relapsing-Remitting Multiple Sclerosis.

Background and ObjectivesThe relationship between smoking, long-term brain atrophy, and clinical disability in patients with multiple sclerosis (MS) is unclear. Here, we assessed long-term effects of smoking by evaluating MRI and clinical outcome measures after 10 years in smoking and nonsmoking patients with relapsing-remitting MS (RRMS).MethodsWe included 85 treatment-naive patients with RRMS with recent inflammatory disease activity who participated in a 10-year follow-up visit after a multicenter clinical trial of 24 months. Smoking status was decided for each patient by 2 separate definitions: by serum cotinine levels measured regularly for the first 2 years of the follow-up (during the clinical trial) and by retrospective patient self-reporting. At the 10-year follow-up visit, clinical tests were repeated, and brain atrophy measures were obtained from MRI using FreeSurfer. Differences in clinical and MRI measurements at the 10-year follow-up between smokers and nonsmokers were investigated by 2-sample t tests or Mann-Whitney tests and linear mixed-effect regression models. All analyses were conducted separately for each definition of smoking status.ResultsAfter 10 years, smoking (defined by serum cotinine levels) was associated with lower total white matter volume (β = −21.74, p = 0.039) and higher logT2 lesion volume (β = 0.22, p = 0.011). When defining smoking status by patient self-reporting, the repeated analyses found an additional association with lower deep gray matter volume (β = −2.35, p = 0.049), and smoking was also associated with a higher score (higher walking impairment) on the log timed 25-foot walk test (β = 0.050, p = 0.039) after 10 years and a larger decrease in paced auditory serial addition test (attention) scores (β = −3.58, p = 0.029).DiscussionSmoking was associated with brain atrophy and disability progression 10 years later in patients with RRMS. The findings imply that patients should be advised and offered aid in smoking cessation shortly after diagnosis, to prevent long-term disability progression.

Magnetic Resonance Imaging Evaluation of Perivascular Space Abnormalities in Neuromyelitis Optica

ObjectiveAstrocytes outline the perivascular space (PVS) and regulate fluid exchange through the aquaporin‐4 water channel. As neuromyelitis optica is an autoimmune astrocytopathy targeting aquaporin‐4, we hypothesized that it could be associatied with PVS abnormalities.MethodsA total of 34 patients, and 46 age‐ and sex‐matched healthy controls from two independent cohorts (exploratory and validation dataset) underwent a standardized 3.0‐T magnetic resonance imaging protocol including conventional and diffusion tensor imaging. Susceptibility‐weighted imaging was also acquired in the exploratory dataset. We evaluated macroscopic and microstructural abnormalities of PVS in terms of enlargement and water diffusivity (DTI‐ALPS index). In the exploration dataset, a susceptibility‐weighted sequence was used to draw the regions of interest for the DTI‐ALPS index calculation in areas having veins perpendicular to lateral ventricles. Between‐group comparisons, correlations, and regression models were run to assess associations between PVS abnormalities, and clinical and magnetic resonance imaging variables.ResultsPatients had a higher frequency of severe PVS enlargement in the centrum semiovale (29.4% vs 8.7%), which correlated with brain atrophy, deep grey matter atrophy, and poorer cognitive performance (r‐values range: −0.44, −0.36; p values: 0.01–0.046).In both datasets, patients had reduced DTI‐ALPS index compared with controls (p values 0.004–0.038). Lower DTI‐ALPS index, deep gray matter volume, and cortical volume could discriminate between patients and controls (R 2 = 0.62), whereas lower DTI‐ALPS index, higher number of myelitis, and higher T2‐lesion volume were associated with worse disability (R 2 = 0.55).InterpretationPatients with neuromyelitis optica spectrum disorder are characterized by abnormal enlargement and impaired water diffusion along the PVS, whose clinical implications suggest a direct correlation with disease pathogenesis and severity. ANN NEUROL 2022;92:173–183

Postnatal serum IGF-1 levels associate with brain volumes at term in extremely preterm infants

BackgroundGrowth factors important for normal brain development are low in preterm infants. This study investigated the link between growth factors and preterm brain volumes at term.Material/methodsInfants born <28 weeks gestational age (GA) were included. Endogenous levels of insulin-like growth factor (IGF)−1, brain-derived growth factor, vascular endothelial growth factor, and platelet-derived growth factor (expressed as area under the curve [AUC] for serum samples from postnatal days 1, 7, 14, and 28) were utilized in a multivariable linear regression model. Brain volumes were determined by magnetic resonance imaging (MRI) at term equivalent age.ResultsIn total, 49 infants (median [range] GA 25.4 [22.9–27.9] weeks) were included following MRI segmentation quality assessment and AUC calculation. IGF-1 levels were independently positively associated with the total brain (p < 0.001, β = 0.90), white matter (p = 0.007, β = 0.33), cortical gray matter (p = 0.002, β = 0.43), deep gray matter (p = 0.008, β = 0.05), and cerebellar (p = 0.006, β = 0.08) volume adjusted for GA at birth and postmenstrual age at MRI. No associations were seen for other growth factors.ConclusionsEndogenous exposure to IGF-1 during the first 4 weeks of life was associated with total and regional brain volumes at term. Optimizing levels of IGF-1 might improve brain growth in extremely preterm infants.ImpactHigh serum levels of insulin-like growth factor (IGF)-1 during the first month of life were independently associated with increased total brain volume, white matter, gray matter, and cerebellar volume at term equivalent age in extremely preterm infants.IGF-1 is a critical regulator of neurodevelopment and postnatal levels are low in preterm infants. The effects of IGF-1 levels on brain development in extremely preterm infants are not fully understood.Optimizing levels of IGF-1 may benefit early brain growth in extremely preterm infants. The effects of systemically administered IGF-1/IGFBP3 in extremely preterm infants are now being investigated in a randomized controlled trial (Clinicaltrials.gov: NCT03253263).

Post-acute blood biomarkers and disease progression in traumatic brain injury.

There is substantial interest in the potential for traumatic brain injury to result in progressive neurological deterioration. While blood biomarkers such as glial fibrillary acid protein (GFAP) and neurofilament light have been widely explored in characterizing acute traumatic brain injury (TBI), their use in the chronic phase is limited. Given increasing evidence that these proteins may be markers of ongoing neurodegeneration in a range of diseases, we examined their relationship to imaging changes and functional outcome in the months to years following TBI.Two-hundred and three patients were recruited in two separate cohorts; 6 months post-injury (n = 165); and >5 years post-injury (n = 38; 12 of whom also provided data ∼8 months post-TBI). Subjects underwent blood biomarker sampling (n = 199) and MRI (n = 172; including diffusion tensor imaging). Data from patient cohorts were compared to 59 healthy volunteers and 21 non-brain injury trauma controls. Mean diffusivity and fractional anisotropy were calculated in cortical grey matter, deep grey matter and whole brain white matter. Accelerated brain ageing was calculated at a whole brain level as the predicted age difference defined using T1-weighted images, and at a voxel-based level as the annualized Jacobian determinants in white matter and grey matter, referenced to a population of 652 healthy control subjects.Serum neurofilament light concentrations were elevated in the early chronic phase. While GFAP values were within the normal range at ∼8 months, many patients showed a secondary and temporally distinct elevations up to >5 years after injury. Biomarker elevation at 6 months was significantly related to metrics of microstructural injury on diffusion tensor imaging. Biomarker levels at ∼8 months predicted white matter volume loss at >5 years, and annualized brain volume loss between ∼8 months and 5 years. Patients who worsened functionally between ∼8 months and >5 years showed higher than predicted brain age and elevated neurofilament light levels.GFAP and neurofilament light levels can remain elevated months to years after TBI, and show distinct temporal profiles. These elevations correlate closely with microstructural injury in both grey and white matter on contemporaneous quantitative diffusion tensor imaging. Neurofilament light elevations at ∼8 months may predict ongoing white matter and brain volume loss over >5 years of follow-up. If confirmed, these findings suggest that blood biomarker levels at late time points could be used to identify TBI survivors who are at high risk of progressive neurological damage.

CAU-Net: A Deep Learning Method for Deep Gray Matter Nuclei Segmentation

The abnormal iron deposition of the deep gray matter nuclei is related to many neurological diseases. With the quantitative susceptibility mapping (QSM) technique, it is possible to quantitatively measure the brain iron content in vivo. To assess the magnetic susceptibility of the deep gray matter nuclei in the QSM, it is mandatory to segment the nuclei of interest first, and many automatic methods have been proposed in the literature. This study proposed a contrast attention U-Net for nuclei segmentation and evaluated its performance on two datasets acquired using different sequences with different parameters from different MRI devices. Experimental results revealed that our proposed method was superior on both datasets over other commonly adopted network structures. The impacts of training and inference strategies were also discussed, which showed that adopting test time augmentation during the inference stage can impose an obvious improvement. At the training stage, our results indicated that sufficient data augmentation, deep supervision, and nonuniform patch sampling contributed significantly to improving the segmentation accuracy, which indicated that appropriate choices of training and inference strategies were at least as important as designing more advanced network structures.

Oxidative Stress Markers in Cerebrospinal Fluid of Newly Diagnosed Multiple Sclerosis Patients and Their Link to Iron Deposition and Atrophy.

Oxidative stress has been implied in cellular injury even in the early phases of multiple sclerosis (MS). In this study, we quantified levels of biomarkers of oxidative stress and antioxidant capacity in cerebrospinal fluid (CSF) in newly diagnosed MS patients and their associations with brain atrophy and iron deposits in the brain tissue. Consecutive treatment-naive adult MS patients (n = 103) underwent brain MRI and CSF sampling. Healthy controls (HC, n = 99) had brain MRI. CSF controls (n = 45) consisted of patients with non-neuroinflammatory conditions. 3T MR included isotropic T1 weighted (MPRAGE) and gradient echo (GRE) images that were processed to quantitative susceptibility maps. The volume and magnetic susceptibility of deep gray matter (DGM) structures were calculated. The levels of 8-hydroxy-2′-deoxyguanosine (8-OHdG), 8-iso prostaglandin F2α (8-isoPG), neutrophil gelatinase-associated lipocalin (NGAL), peroxiredoxin-2 (PRDX2), and malondialdehyde and hydroxyalkenals (MDA + HAE) were measured in CSF. Compared to controls, MS patients had lower volumes of thalamus, pulvinar, and putamen, higher susceptibility in caudate nucleus and globus pallidus, and higher levels of 8-OHdG, PRDX2, and MDA + HAE. In MS patients, the level of NGAL correlated negatively with volume and susceptibility in the dentate nucleus. The level of 8-OHdG correlated negatively with susceptibility in the caudate, putamen, and the red nucleus. The level of PRDX2 correlated negatively with the volume of the thalamus and both with volume and susceptibility of the dentate nucleus. From MRI parameters with significant differences between MS and HC groups, only caudate susceptibility and thalamic volume were significantly associated with CSF parameters. Our study shows that increased oxidative stress in CSF detected in newly diagnosed MS patients suggests its role in the pathogenesis of MS.

Serum neurofilament as a predictor of 10-year grey matter atrophy and clinical disability in multiple sclerosis: a longitudinal study

BackgroundThe predictive value of serum neurofilament light chain (sNfL) on long-term prognosis in multiple sclerosis (MS) is still unclear.ObjectiveInvestigate the relation between sNfL levels over a 2-year period in patients...

White Matter, Behavioral Neurology, and the Influence of Corticocentrism.

White matter in the human brain occupies roughly the same volume as gray matter but has received far less attention in behavioral neurology and related disciplines. In particular, the cerebral cortex has long dominated thinking about the organization of brain-behavior relationships. As a result, subcortical structures, including deep gray matter and, most notably, white matter, have been accorded relatively little neuroscientific study compared with the extensive work devoted to the cerebral cortex. The influence of corticocentrism can be explained by several factors, including historical precedent in neurology strongly emphasizing the importance of the cortex, a preponderance of investigative methods that selectively target this structure, and a misinterpretation of comparative neuroanatomic data gathered from normal brains. This paper will describe the background of the corticocentric bias and emphasize that white matter merits its own place within the study of the higher functions. Although corticocentrism continues to exert a powerful impact on behavioral neurology, considerable progress is being made in the study of white matter-a development that promises to expand our knowledge of the normal brain and lead to an improved understanding of how it mediates behavior. In turn, a range of vexing neurologic and psychiatric disorders may become better illuminated by considering pathology within, or dysfunction of, white matter tracts. A complete appreciation of brain-behavior relationships requires an understanding not only of the outermost layer of the cerebral hemispheres, but also of white matter connectivity that links gray matter regions into distributed neural networks that subserve cognition and emotion.

P.089 Characteristics of children with cerebral palsy secondary to intrapartum asphyxia in the post-therapeutic hypothermia era

Background: We explored the profile of children with cerebral palsy (CP) secondary to intrapartum asphyxia (IAP), who were treated with therapeutic hypothermia (TH). We compared neonatal characteristics between children treated with TH with a mild vs severe CP. Methods: We collected perinatal and outcome measures of children treated with TH for IAP. We searched the literature for characteristics of children prior to TH to compare to our cohort. We subdivided our cohort into mild vs. severe CP and compared neonatal characteristics to identify predictors of severe phenotype. Results: We found more children with severe (19/30) compared to mild CP (11/30). Post-TH era children leaned towards a more severe phenotype compared to prior to TH. Children with severe CP had significantly higher mean birth weight, lower 5- and 10-minute Apgars, and more often white matter with associated deep gray matter injury or near-total injury pattern on MRI compared to the mild phenotype group (all p&lt;0.05). Conclusions: Our data leaned to a more severe CP in cooled children compared to pre-TH. Birthweight, 5- and 10-minute Apgars and MRI findings were significantly different between our mild vs severe group. Our findings can guide clinicians how to better weigh these factors when counseling parents in the neonatal period.

P.080 Outcomes in Influenza and RANBP2 mutation associated Acute Necrotizing Encephalopathy of Childhood

Background: Acute Necrotizing Encephalopathy (ANEC) is a rare neuroinflammatory disorder involving the deep grey matter following viral infection and has been associated with the RANBP2 gene. We aimed to evaluate clinical and imaging features in ANEC patients. Methods: This retrospective chart review of ANEC patients (2012-2020) seen at a tertiary pediatric center included analysis of outcomes including ANE-Severity Score, Expanded Disability Status Scale (EDSS) and the modified Rankin Scale (mRS), semi-quantitative imaging scores (degree of swelling or hemorrhage rated 0 (none)-5 (severe/massive)), and dichotomous outcomes including RANBP2 gene status, influenza status. Results: 20 patients were included (Avg. age at presentation 3.5 yrs IQR=3.56., F:M 2.33:1). 3/20 experienced recurrences. All patients with recurrences were positive for RANBP2 mutations. 10/20 patients were influenza positive. 7/20 were RANBP2 mutation positive. We observed higher likelihood of hemorrhage in influenza-positive compared to negative patients (W=78, p=0.048). Kaplan-Meier survival curve analysis revealed that patients without brainstem lesions were more likely to reach minimal/no disability (EDSS&lt;=2) than patients with brainstem lesions (p=0.035). Conclusions: Hemorrhage is more likely to be seen in children with ANEC who are positive for influenza. RANBP2 status was predictive of relapse but not predictive of overall outcome.

Logistic Regression-Based Model Is More Efficient Than U-Net Model for Reliable Whole Brain Magnetic Resonance Imaging Segmentation.

Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remarkable potential in this area, they may perform poorly in nonoptimal conditions, such as limited training data availability. Manual whole brain segmentation is an incredibly tedious process, so minimizing the data set size required for training segmentation algorithms may be of wide interest. The purpose of this study was to compare the performance of the prototypical deep learning segmentation architecture (U-Net) with a previously published atlas-free traditional machine learning method, Classification using Derivative-based Features (C-DEF) for whole brain segmentation, in the setting of limited training data. C-DEF and U-Net models were evaluated after training on manually curated data from 5, 10, and 15 participants in 2 research cohorts: (1) people living with clinically diagnosed HIV infection and (2) relapsing-remitting multiple sclerosis, each acquired at separate institutions, and between 5 and 295 participants' data using a large, publicly available, and annotated data set of glioblastoma and lower grade glioma (brain tumor segmentation). Statistics was performed on the Dice similarity coefficient using repeated-measures analysis of variance and Dunnett-Hsu pairwise comparison. C-DEF produced better segmentation than U-Net in lesion (29.2%-38.9%) and cerebrospinal fluid (5.3%-11.9%) classes when trained with data from 15 or fewer participants. Unlike C-DEF, U-Net showed significant improvement when increasing the size of the training data (24%-30% higher than baseline). In the brain tumor segmentation data set, C-DEF produced equivalent or better segmentations than U-Net for enhancing tumor and peritumoral edema regions across all training data sizes explored. However, U-Net was more effective than C-DEF for segmentation of necrotic/non-enhancing tumor when trained on 10 or more participants, probably because of the inconsistent signal intensity of the tissue class. These results demonstrate that classical machine learning methods can produce more accurate brain segmentation than the far more complex deep learning methods when only small or moderate amounts of training data are available (n ≤ 15). The magnitude of this advantage varies by tissue and cohort, while U-Net may be preferable for deep gray matter and necrotic/non-enhancing tumor segmentation, particularly with larger training data sets (n ≥ 20). Given that segmentation models often need to be retrained for application to novel imaging protocols or pathology, the bottleneck associated with large-scale manual annotation could be avoided with classical machine learning algorithms, such as C-DEF.

Increased Magnetic Susceptibility in the Deep Gray Matter Nuclei of Wilson's Disease: Have We Been Ignoring Atrophy?

BackgroundHistopathological studies in Wilson's disease (WD) have revealed increased copper and iron concentrations in the deep gray matter nuclei. However, the commonly used mean bulk susceptibility only reflects the regional metal concentration rather than the total metal content, and regional atrophy may affect the assessment of mean bulk susceptibility. Our study aimed to quantitatively assess the changes of metal concentration and total metal content in deep gray matter nuclei by quantitative susceptibility mapping to distinguish patients with neurological and hepatic WD from healthy controls.MethodsQuantitative susceptibility maps were obtained from 20 patients with neurological WD, 10 patients with hepatic WD, and 25 healthy controls on a 3T magnetic resonance imaging system. Mean bulk susceptibility, volumes, and total susceptibility of deep gray matter nuclei in different groups were compared using a linear regression model. The area under the curve (AUC) was calculated by receiver characteristic curve to analyze the diagnostic capability of mean bulk susceptibility and total susceptibility.ResultsMean bulk susceptibility and total susceptibility of multiple deep gray matter nuclei in patients with WD were higher than those in healthy controls. Compared with patients with hepatic WD, patients with neurological WD had higher mean bulk susceptibility but similar total susceptibility in the head of the caudate nuclei, globus pallidus, and putamen. Mean bulk susceptibility of putamen demonstrated the best diagnostic capability for patients with neurological WD, the AUC was 1, and the sensitivity and specificity were all equal to 1. Total susceptibility of pontine tegmentum was most significant for the diagnosis of patients with hepatic WD, the AUC was 0.848, and the sensitivity and specificity were 0.7 and 0.96, respectively.ConclusionBrain atrophy may affect the assessment of mean bulk susceptibility in the deep gray matter nuclei of patients with WD, and total susceptibility should be an additional metric for total metal content assessment. Mean bulk susceptibility and total susceptibility of deep gray matter nuclei may be helpful for the early diagnosis of WD.

Microinfarcts in the Deep Gray Matter on 7T MRI: Risk Factors, MRI Correlates, and Relation to Cognitive Functioning-The SMART-MR Study.

The clinical relevance of cortical microinfarcts has recently been established; however, studies on microinfarcts in the deep gray matter are lacking. We examined the risk factors and MR imaging correlates of microinfarcts in the deep gray matter on 7T MR imaging and their relation to cognitive functioning. Within the Second Manifestations of ARTerial disease-Magnetic Resonance (SMART-MR) study, 213 patients (mean age, 68 [SD, 8] years) had a risk-factor assessment, 7T and 1.5T brain MR imaging, and a cognitive examination. Microinfarcts on 7T MR imaging were defined as lesions of <5 mm. Regression models were used to examine the age-adjusted associations among risk factors, MR imaging markers, and microinfarcts. Cognitive function was summarized as composite and domain-specific z scores. A total of 47 microinfarcts were found in 28 patients (13%), most commonly in the thalamus. Older age, history of stroke, hypertension, and intima-media thickness were associated with microinfarcts. On 1.5T MR imaging, cerebellar infarcts (relative risk = 2.75; 95% CI, 1.4-5.33) and lacunes in the white (relative risk = 3.28; 95% CI, 3.28-6.04) and deep gray matter (relative risk = 3.06; 95% CI, 1.75-5.35) were associated with microinfarcts, and on 7T MR imaging cortical microinfarcts (relative risk = 2.33; 95% CI, 1.32-4.13). Microinfarcts were also associated with poorer global cognitive functioning (mean difference in the global z score between patients with multiple microinfarcts versus none = -0.97; 95% CI, -1.66 to -0.28, P = .006) and across all cognitive domains. Microinfarcts in the deep gray matter on 7T MR imaging were associated with worse cognitive functioning and risk factors and MR imaging markers of small-vessel and large-vessel disease. Our findings suggest that microinfarcts in the deep gray matter may represent a novel imaging marker of vascular brain injury.

Brain atrophy pattern in de novo Parkinson’s disease with probable RBD associated with cognitive impairment

Rapid eye movement sleep behavior disorder (RBD) is associated with high likelihood of prodromal Parkinson’s disease (PD) and is common in de novo PD. It is associated with greater cognitive impairment and brain atrophy. However, the relation between structural brain characteristics and cognition remains poorly understood. We aimed to investigate subcortical and cortical atrophy in de novo PD with probable RBD (PD-pRBD) and to relate it with cognitive impairment. We analyzed volumetry, cortical thickness, and cognitive measures from 79 PD-pRBD patients, 126 PD without probable RBD patients (PD-non pRBD), and 69 controls from the Parkinson’s Progression Markers Initiative (PPMI). Regression models of cognition were tested using magnetic resonance imaging measures as predictors. We found lower left thalamus volume in PD-pRBD compared with PD-non pRBD. Compared with controls, PD-pRBD group showed atrophy in the bilateral putamen, left hippocampus, left amygdala, and thinning in the right superior temporal gyrus. Specific deep gray matter nuclei volumes were associated with impairment in global cognition, phonemic fluency, processing speed, and visuospatial function in PD-pRBD. In conclusion, cognitive impairment and gray matter atrophy are already present in de novo PD-pRBD. Thalamus, hippocampus, and putamen volumes were mainly associated with these cognitive deficits.