Cardiovascular Disease, Brain Glucose Metabolism, and Neurocognitive Decline in People With Human Immunodeficiency Virus.

Background: Cardiovascular disease (CVD) and neuroinflammation are thought to exacerbate neurocognitive dysfunction in treated people with human immunodeficiency virus (PWH). Here, we longitudinally measured brain glucose metabolism as a measure of neuronal integrity in treated PWH using [18F]Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in correlation with atherosclerotic cardiovascular disease (ASCVD) scores, cerebrospinal fluid (CSF) neuroinflammatory markers, neurocognitive outcomes, and other clinical and laboratory variables (CLVs). Methods: Well-controlled PWH (n = 36) underwent baseline and follow-up FDG PET/CT obtained 3.5 years apart on average. Longitudinal changes in whole brain and regional relative FDG uptake, brain volumes, CLVs, CSF cytokines, and neuropsychological measures were measured. A variable selection model identified baseline variables related to future brain metabolic changes while multivariable models explored neuropsychological implications of brain metabolism and volumetrics. Results: High ASCVD scores predicted future decreased thalamic uptake (slope = -0.0068, P = .027) and decreasing thalamic uptake correlated with worsening cognition (slope = 15.80, P = .020). Despite longitudinal greater than expected gray matter loss, whole brain FDG uptake did not change over the follow-up period. Most CSF cytokines decreased longitudinally but were not predictive of FDG changes. Conclusions: We found that high ASCVD scores in a group of treated PWH were related to thalamic hypometabolism, which in turn correlated with neurocognitive decline. Our findings support the contribution of CVD to neurocognitive dysfunction. More proactive CVD management may have a role in mitigating progression of cognitive impairment. Lack of change in global brain glucose metabolism despite documented accelerated gray matter volume loss over the same period suggests that FDG PET might underestimate neuronal injury in PWH compared to structural magnetic resonance imaging.

Effect of enzyme substitution therapy on brain magnetic resonance imaging and cognition in adults with phenylketonuria: A case series of three patients.

Phenylketonuria, the most common inherited metabolic disease, results from a deficiency of phenylalanine hydroxylase enzyme activity that causes high blood phenylalanine levels. Most adults do not adhere to the gold standard therapy: lifelong treatment with a low-phenylalanine diet. Elevated and fluctuating phenylalanine levels in untreated adults can cause white matter abnormalities, neurological symptoms, and cognitive dysfunction (executive function). Pegvaliase, a derivative of the phenylalanine ammonia-lyase enzyme, metabolizes phenylalanine to trans-cinnamic acid and ammonia, and is approved by the US Food and Drug Administration and European Medicines Agency for subcutaneous administration in adults with phenylketonuria and blood phenylalanine concentrations > 600 µmol/L. In clinical trials, it reduced blood phenylalanine, even in patients consuming an unrestricted diet. We report longitudinal results on the first three such adults, in whom phenylalanine levels were quantified monthly, starting 1 year before pegvaliase administration and continuing through achievement of a pegvaliase response (defined as six consecutive monthly blood phenylalanine concentrations < 360 µmol/L while consuming an unrestricted diet). Brain magnetic resonance imaging (MRI) and neuropsychological assessments were performed before starting therapy and after response was achieved. Our results show that all three patients had significantly reduced white matter hyperintensities on brain MRI and improved executive function on neuropsychological assessment, especially on the Paced Auditory Serial Addition Test, which is known to be very sensitive to white matter functioning. To the best of our knowledge, this is the first report of concomitant improvements in cognitive performance and white matter damage after a pharmacological intervention to normalize phenylalanine levels in adults with phenylketonuria consuming an unrestricted diet.

Differential correlations of changes in in vivo neuroimaging markers of hippocampal volume and arteriolosclerosis with declining financial and health literacy in old age.

Financial and health literacy is essential for older adults to navigate complex decision processes in late life. However, the neurobiological basis of age-related decline in financial and health literacy is poorly understood. This study aimed to characterize progression of neurodegenerative and vascular conditions over time, and to assess how these changes coincide with declining financial and health literacy in old age. Data came from 319 community-living older adults who were free of dementia at baseline, and underwent annual literacy assessments, as well as biennial 3-Tesla neuroimaging scans. Financial and health literacy was assessed using a battery of 32 items. Two in vivo neuroimaging markers of neurodegenerative and cerebrovascular conditions were used, i.e., hippocampal volume and the ARTS marker of arteriolosclerosis. A multivariate linear mixed effects model estimated the simultaneous changes in financial and health literacy, hippocampal volume, and the ARTS score. Over a mean of 7 years of follow-up, these older adults experienced a significant decline in financial and health literacy, a significant reduction in hippocampal volume, and a significant progression in ARTS score. Individuals with faster hippocampal atrophy had faster decline in literacy. Similarly, those with faster progression in ARTS also had faster decline in literacy. The correlation between the rates of hippocampal atrophy and declining literacy, however, was stronger than the correlation between the progression of ARTS with declining literacy. These findings suggest that neurodegeneration and, to a lesser extent, cerebrovascular conditions are correlated with declining financial and health literacy in old age.

Quantitative reliability assessment of brain MRI volumetric measurements in type II GM1 gangliosidosis patients.

Purpose: GM1-gangliosidosis (GM1) leads to extensive neurodegenerative changes and atrophy that precludes the use of automated MRI segmentation techniques for generating brain volumetrics. We developed a standardized segmentation protocol for brain MRIs of patients with type II GM1 and then assessed the inter- and intra-rater reliability of this methodology. The volumetric data may be used as a biomarker of disease burden and progression, and standardized methodology may support research into the natural history of the disease which is currently lacking in the literature. Approach: Twenty-five brain MRIs were included in this study from 22 type II GM1 patients of which 8 were late-infantile subtype and 14 were juvenile subtype. The following structures were segmented by two rating teams on a slice-by-slice basis: whole brain, ventricles, cerebellum, lentiform nucleus, thalamus, corpus callosum, and caudate nucleus. The inter- and intra-rater reliability of the segmentation method was assessed with an intraclass correlation coefficient as well as Sorensen-Dice and Jaccard coefficients. Results: Based on the Sorensen-Dice and Jaccard coefficients, the inter- and intra-rater reliability of the segmentation method was significantly better for the juvenile patients compared to late-infantile (p < 0.01). In addition, the agreement between the two rater teams and within themselves can be considered good with all p-values < 0.05. Conclusions: The standardized segmentation approach described here has good inter- and intra-rater reliability and may provide greater accuracy and reproducibility for neuromorphological studies in this group of patients and help to further expand our understanding of the natural history of this disease.

Prediction of fetal brain gestational age using multihead attention with Xception.

Accurate gestational age (GA) prediction is crucial for monitoring fetal development and ensuring optimal prenatal care. Traditional methods often face challenges in terms of precision and prediction efficiency. In this context, leveraging modern deep learning (DL) techniques is a promising solution. This paper introduces a novel DL approach for GA prediction using fetal brain images obtained via magnetic resonance imaging (MRI), which combines the strength of the Xception pretrained model with a multihead attention (MHA) mechanism. The proposed model was trained on a diverse dataset comprising 52,900 fetal brain images from 741 patients. The images encompass a GA ranging from 19 to 39 weeks. These pretrained models served as feature extraction components during the training process. The extracted features were subsequently used as the inputs of different configurable MHAs, which produced GA predictions in days. The proposed model achieved promising results with 8 attention heads, 32 dimensionality of the key space and 32 dimensionality of the value space, with an R-squared (R2) value of 96.5 %, a mean absolute error (MAE) of 3.80 days, and a Pearson correlation coefficient (PCC) of 98.50 % for the test set. Additionally, the 5-fold cross-validation results reinforce the model's reliability, with an average R2 of 95.94 %, an MAE of 3.61 days, and a PCC of 98.02 %. The proposed model excels in different anatomical views, notably the axial and sagittal views. A comparative analysis of multiple planes and a single plane highlights the effectiveness of the proposed model against other state-of-the-art (SOTA) models reported in the literature. The proposed model could help clinicians accurately predict GA.

A motion assessment method for reference stack selection in fetal brain MRI reconstruction based on tensor rank approximation.

Slice-to-volume registration and super-resolution reconstruction are commonly used to generate 3D volumes of the fetal brain from 2D stacks of slices acquired in multiple orientations. A critical initial step in this pipeline is to select one stack with the minimum motion among all input stacks as a reference for registration. An accurate and unbiased motion assessment (MA) is thus crucial for successful selection. Here, we presented an MA method that determines the minimum motion stack based on 3D low-rank approximation using CANDECOMP/PARAFAC (CP) decomposition. Compared to the current 2D singular value decomposition (SVD) based method that requires flattening stacks into matrices to obtain ranks, in which the spatial information is lost, the CP-based method can factorize 3D stack into low-rank and sparse components in a computationally efficient manner. The difference between the original stack and its low-rank approximation was proposed as the motion indicator. Experiments on linearly and randomly simulated motion illustrated that CP demonstrated higher sensitivity in detecting small motion with a lower baseline bias, and achieved a higher assessment accuracy of 95.45% in identifying the minimum motion stack, compared to the SVD-based method with 58.18%. CP also showed superior motion assessment capabilities in real-data evaluations. Additionally, combining CP with the existing SRR-SVR pipeline significantly improved 3D volume reconstruction. The results indicated that our proposed CP showed superior performance compared to SVD-based methods with higher sensitivity to motion, assessment accuracy, and lower baseline bias, and can be used as a prior step to improve fetal brain reconstruction.

Central nervous system involvement in Erdheim-Chester disease: a magnetic resonance imaging study.

PURPOSE: To characterize brain MR imaging findings in a cohort of 58 patients with ECD and to evaluate relationship between these findings and the BRAFV600E pathogenic variant. METHODS: ECD patients of any gender and ethnicity, aged 2-80 years, with biopsy-confirmed ECD were eligible to enroll in this study. Two radiologists experienced in evaluating ECD CNS disease activity reviewed MRI studies. Any disagreements were resolved by a third reader. Frequencies of observed lesions were reported. The association between the distribution of CNS lesions and the BRAFV600Epathogenic variant was evaluated using Fisher's exact test and odd ratio. RESULTS: The brain MRI of all 58 patients with ECD revealed some form of CNS lesions, most likely due to ECD. Cortical lesions were noted in 27/58 (46.6 %) patients, cerebellar lesions in 15/58 (25.9 %) patients, brain stem lesions in 17/58 cases (29.3 %), and pituitary lesions in 10/58 (17.2 %) patients. Premature cortical atrophy was observed in 8/58 (13.8 %) patients. BRAFV600E pathogenic variant was significantly associated with cerebellar lesions (p = 0.016) and bilateral brain stem lesions (p = 0.043). A trend toward significance was noted for cerebral atrophy (p = 0.053). CONCLUSION: The study provides valuable insights into the brain MRI findings in ECD and their association with the BRAFV600E pathogenic variant, particularly its association in cases with bilateral lesions. We are expanding our understanding of how ECD affects cerebral structures. Knowledge of MRI CNS lesion patterns and their association with mutations such as the BRAF variant is helpful for both prognosis and clinical management.

Topographical metal burden correlates with brain atrophy and clinical severity in Wilson's disease.

BACKGROUND: Quantitative susceptibility mapping (QSM) is a post-processing technique that creates brain susceptibility maps reflecting metal burden through tissue magnetic susceptibility. We assessed topographic differences in magnetic susceptibility between participants with and without Wilson's disease (WD), correlating these findings with clinical severity, brain volume, and biofluid copper and iron indices. METHODS: A total of 43 patients with WD and 20 unaffected controls, were recruited. QSM images were derived from a 3T MRI scanner. Clinical severity was defined using the minimal Unified Wilson's Disease Rating Scale (M-UWDRS) and Montreal Cognitive Assessment scoring. Differences in magnetic susceptibilities between groups were evaluated using general linear regression models, adjusting for age and sex. Correlations between the susceptibilities and clinical scores were analyzed using Spearman's method. RESULTS: In age- and sex-adjusted analyses, magnetic susceptibility values were increased in WD patients compared with controls, including caudate nucleus, putamen, globus pallidus, and substantia nigra (all p < 0.01). Putaminal susceptibility was greater with an initial neuropsychiatric presentation (n = 25) than with initial hepatic dysfunction (n = 18; p = 0.04). Susceptibility changes correlated negatively with regional brain volume in almost all topographic regions. Serum ferritin, but not serum copper or ceruloplasmin, correlated positively with magnetic susceptibility level in the caudate nucleus (p = 0.04), putamen (p = 0.04) and the hippocampus (p = 0.03). The dominance of magnetic susceptibility in cortical over subcortical regions correlated with M-UWDRS scores (p < 0.01). CONCLUSION: The magnetic susceptibility changes could serve as a surrogate marker for patients with WD.

Discrepancy-based diffusion models for lesion detection in brain MRI.

Diffusion probabilistic models (DPMs) have exhibited significant effectiveness in computer vision tasks, particularly in image generation. However, their notable performance heavily relies on labelled datasets, which limits their application in medical images due to the associated high-cost annotations. Current DPM-related methods for lesion detection in medical imaging, which can be categorized into two distinct approaches, primarily rely on image-level annotations. The first approach, based on anomaly detection, involves learning reference healthy brain representations and identifying anomalies based on the difference in inference results. In contrast, the second approach, resembling a segmentation task, employs only the original brain multi-modalities as prior information for generating pixel-level annotations. In this paper, our proposed model - discrepancy distribution medical diffusion (DDMD) - for lesion detection in brain MRI introduces a novel framework by incorporating distinctive discrepancy features, deviating from the conventional direct reliance on image-level annotations or the original brain modalities. In our method, the inconsistency in image-level annotations is translated into distribution discrepancies among heterogeneous samples while preserving information within homogeneous samples. This property retains pixel-wise uncertainty and facilitates an implicit ensemble of segmentation, ultimately enhancing the overall detection performance. Thorough experiments conducted on the BRATS2020 benchmark dataset containing multimodal MRI scans for brain tumour detection demonstrate the great performance of our approach in comparison to state-of-the-art methods.

Ultrafast Brain MRI at 3 T for MS: Evaluation of a 51-Second Deep Learning-Enhanced T2-EPI-FLAIR Sequence.

In neuroimaging, there is no equivalent alternative to magnetic resonance imaging (MRI). However, image acquisitions are generally time-consuming, which may limit utilization in some cases, e.g., in patients who cannot remain motionless for long or suffer from claustrophobia, or in the event of extensive waiting times. For multiple sclerosis (MS) patients, MRI plays a major role in drug therapy decision-making. The purpose of this study was to evaluate whether an ultrafast, T2-weighted (T2w), deep learning-enhanced (DL), echo-planar-imaging-based (EPI) fluid-attenuated inversion recovery (FLAIR) sequence (FLAIRUF) that has targeted neurological emergencies so far might even be an option to detect MS lesions of the brain compared to conventional FLAIR sequences. Therefore, 17 MS patients were enrolled prospectively in this exploratory study. Standard MRI protocols and ultrafast acquisitions were conducted at 3 tesla (T), including three-dimensional (3D)-FLAIR, turbo/fast spin-echo (TSE)-FLAIR, and FLAIRUF. Inflammatory lesions were grouped by size and location. Lesion conspicuity and image quality were rated on an ordinal five-point Likert scale, and lesion detection rates were calculated. Statistical analyses were performed to compare results. Altogether, 568 different lesions were found. Data indicated no significant differences in lesion detection (sensitivity and positive predictive value [PPV]) between FLAIRUF and axially reconstructed 3D-FLAIR (lesion size ≥3 mm × ≥2 mm) and no differences in sensitivity between FLAIRUF and TSE-FLAIR (lesion size ≥3 mm total). Lesion conspicuity in FLAIRUF was similar in all brain regions except for superior conspicuity in the occipital lobe and inferior conspicuity in the central brain regions. Further findings include location-dependent limitations of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as artifacts such as spatial distortions in FLAIRUF. In conclusion, FLAIRUF could potentially be an expedient alternative to conventional methods for brain imaging in MS patients since the acquisition can be performed in a fraction of time while maintaining good image quality.

Clinical and neuroimaging features in neurological Wilson's disease with claustrum lesions.

According to early research, the incidence of claustrum lesions in patients with neurological Wilson's disease (WD) was inconsistent, ranging from 1.8 to 75% on magnetic resonance imaging (MRI). Our study aims to explore the incidence, clinical presentation features, iconography features, and possible pathological mechanisms in WD patients with claustrum lesions on magnetic resonance imaging (MRI), to characterize the clinical, and brain imaging findings and possible pathological mechanisms in the patients with WD. Retrospective cases meeting the inclusion criteria were studied for analyzing MRI characteristics and associated physicochemical examination data in neurological WD patients with claustrum lesions. 443 (66.3%) with brain MRI abnormalities were screened from 668 WD patients. The three (0.7%) patients with the claustrum lesions characteristics on MRI images were: (a) "bright claustrum" in T2-weighted and FLAIR sequences, (b) bilateral symmetrical, (c) non-isolated lesions, (d) occurred only in severe neurological manifestations. The claustrum lesions are not common in neurological WD and mainly appear in cases with severe neurological symptoms. On MRI, the "bright claustrum" signs may be a radiographic marker of neuroinflammation, the features of the lesions showed bilateral symmetry, and hyperintensity signals on T2-weighted, FLAIR, and DWI.

Primary mitochondrial diseases.

Primary mitochondrial diseases (PMDs) are a heterogeneous group of hereditary disorders characterized by an impairment of the mitochondrial respiratory chain. They are the most common group of genetic metabolic disorders, with a prevalence of 1 in 4,300 people. The presence of leukoencephalopathy is recognized as an important feature in many PMDs and can be a manifestation of mutations in both mitochondrial DNA (classic syndromes such as mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes; myoclonic epilepsy with ragged-red fibers [RRFs]; Leigh syndrome; and Kearns-Sayre syndrome) and nuclear DNA (mutations in maintenance genes such as POLG, MPV17, and TYMP; Leigh syndrome; and mitochondrial aminoacyl-tRNA synthetase disorders). In this chapter, PMDs associated with white matter involvement are outlined, including details of clinical presentations, brain MRI features, and elements of differential diagnoses. The current approach to the diagnosis of PMDs and management strategies are also discussed. A PMD diagnosis in a subject with leukoencephalopathy should be considered in the presence of specific brain MRI features (for example, cyst-like lesions, bilateral basal ganglia lesions, and involvement of both cerebral hemispheres and cerebellum), in addition to a complex neurologic or multisystem disorder. Establishing a genetic diagnosis is crucial to ensure appropriate genetic counseling, multidisciplinary team input, and eligibility for clinical trials.

A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework.

The heterogeneity of psychiatric disorders makes researching disorder-specific neurobiological markers an ill-posed problem. Here, we face the need for disease stratification models by presenting a generalizable multivariate normative modelling framework for characterizing brain morphology, applied to bipolar disorder (BD). We employed deep autoencoders in an anomaly detection framework, combined with a confounder removal step integrating training and external validation. The model was trained with healthy control (HC) data from the human connectome project and applied to multi-site external data of HC and BD individuals. We found that brain deviating scores were greater, more heterogeneous, and with increased extreme values in the BD group, with volumes prominently from the basal ganglia, hippocampus and adjacent regions emerging as significantly deviating. Similarly, individual brain deviating maps based on modified z scores expressed higher abnormalities occurrences, but their overall spatial overlap was lower compared to HCs. Our generalizable framework enabled the identification of subject- and group-level brain normative-deviating patterns, a step forward towards the development of more effective and personalized clinical decision support systems and patient stratification in psychiatry.

Quantitative evaluation of Scout Accelerated Motion Estimation and Reduction (SAMER) MPRAGE for morphometric analysis of brain tissue in patients undergoing evaluation for memory loss.

BACKGROUND: Three-dimensional (3D) T1-weighted MRI sequences such as the magnetization prepared rapid gradient echo (MPRAGE) sequence are important for assessing regional cortical atrophy in the clinical evaluation of dementia but have long acquisition times and are prone to motion artifact. The recently developed Scout Accelerated Motion Estimation and Reduction (SAMER) retrospective motion correction method addresses motion artifact within clinically-acceptable computation times and has been validated through qualitative evaluation in inpatient and emergency settings. METHODS: We evaluated the quantitative accuracy of morphometric analysis of SAMER motion-corrected compared to non-motion-corrected MPRAGE images by estimating cortical volume and thickness across neuroanatomical regions in two subject groups: (1) healthy volunteers and (2) patients undergoing evaluation for dementia. In part (1), we used a set of 108 MPRAGE reconstructed images derived from 12 healthy volunteers to systematically assess the effectiveness of SAMER in correcting varying degrees of motion corruption, ranging from mild to severe. In part (2), 29 patients who were scheduled for brain MRI with memory loss protocol and had motion corruption on their clinical MPRAGE scans were prospectively enrolled. RESULTS: In part (1), SAMER resulted in effective correction of motion-induced cortical volume and thickness reductions. We observed systematic increases in the estimated cortical volume and thickness across all neuroanatomical regions and a relative reduction in percent error values compared to reference standard scans of up to 66 % for the cerebral white matter volume. In part (2), SAMER resulted in statistically significant volume increases across anatomical regions, with the most pronounced increases seen in the parietal and temporal lobes, and general reductions in percent error relative to reference standard clinical scans. CONCLUSION: SAMER improves the accuracy of morphometry through systematic increases and recovery of the estimated cortical volume and cortical thickness following motion correction, which may affect the evaluation of regional cortical atrophy in patients undergoing evaluation for dementia.

Giant cerebral tuberculoma mimicking tumor in a pediatric patient: A case report.

Tuberculosis (TB) is an infection caused by Mycobacterium tuberculosis, an infectious disease endemic in developing countries. Indonesia is ranked second only to India in terms of TB incidence in the world. TB generally manifests in the respiratory system, which can then spread hematogeneously or lymphogeneously to extrapulmonary organs. Intracranial tuberculoma is a rare manifestation of TB when compared to the overall TB presentation. Central nervous system involvement ranges from 2-5% and increases to 15% in cases of AIDS-related TB, with the percentage of tuberculoma findings around 1% in other intracranial TB cases. The most common manifestation is tuberculous meningitis. Central nervous system (CNS) involvement is a severe manifestation of TB, with high mortality and neurological morbidity. In this case report, the author presented a 6-year-old girl with giant cerebral tuberculoma, which, at the time of surgery, resembled a neoplasm with a nonspecific history of TB. MRI can visualize abnormalities with specific characteristics; Clinically and radiologically, CNS TB can mimic other infections or noninfectious conditions such as neoplasms. Therefore, clinicians can take appropriate management actions in order to prevent mortality and disability due to sequelae in CNS TB cases.

Association of polygenic scores for autism with volumetric MRI phenotypes in cerebellum and brainstem in adults.

Previous research on autism spectrum disorders (ASD) have showed important volumetric alterations in the cerebellum and brainstem. Most of these studies are however limited to case-control studies with small clinical samples and including mainly children or adolescents. Herein, we aimed to explore the association between the cumulative genetic load (polygenic risk score, PRS) for ASD and volumetric alterations in the cerebellum and brainstem, as well as global brain tissue volumes of the brain among adults at the population level. We utilized the latest genome-wide association study of ASD by the Psychiatric Genetics Consortium (18,381 cases, 27,969 controls) and constructed the ASD PRS in an independent cohort, the UK Biobank. Regression analyses controlled for multiple comparisons with the false-discovery rate (FDR) at 5% were performed to investigate the association between ASD PRS and forty-four brain magnetic resonance imaging (MRI) phenotypes among ~ 31,000 participants. Primary analyses included sixteen MRI phenotypes: total volumes of the brain, cerebrospinal fluid (CSF), grey matter (GM), white matter (WM), GM of whole cerebellum, brainstem, and ten regions of the cerebellum (I_IV, V, VI, VIIb, VIIIa, VIIIb, IX, X, CrusI and CrusII). Secondary analyses included twenty-eight MRI phenotypes: the sub-regional volumes of cerebellum including the GM of the vermis and both left and right lobules of each cerebellar region. ASD PRS were significantly associated with the volumes of seven brain areas, whereby higher PRS were associated to reduced volumes of the whole brain, WM, brainstem, and cerebellar regions I-IV, IX, and X, and an increased volume of the CSF. Three sub-regional volumes including the left cerebellar lobule I-IV, cerebellar vermes VIIIb, and X were significantly and negatively associated with ASD PRS. The study highlights a substantial connection between susceptibility to ASD, its underlying genetic etiology, and neuroanatomical alterations of the adult brain.

A female adult-onset X-ALD patient with pure cerebellar symptoms:a case report.

X-linked adrenoleukodystrophy (X-ALD) caused by ATP-binding cassette subfamily D member 1 (ABCD1) gene defects is the most common inherited peroxisomal disorder.The female cerebello-brainstem dominant type in which cerebellum and brainstem are mainly involved is very rare. We report a 40-year-old female who was diagnosed as the rare disorder with magnetic resonance imaging (MRI) and genetic analysis mainly. Her initial symptoms were progressive slurred speech and writing disturbance. Her brain MRI showed obvious atrophy of brainstem and cerebellum. She did not have adrenal insufficiency. Genetic analysis showed a heterozygous missense mutation in exon 4 of the coding region of ABCD1 (c.1252C > T, p.Arg418Trp).This is the first report of this particular mutation being associated with the cerebello-brainstem dominant phenotype of X-ALD, as well as the first description of this X-ALD variant in a (heterozygous) female patient.X-ALD should be considered in young and middle-aged patients with slow-progressing ataxia and dysarthria.

Rare Cerebral Location of a Left Lateral Ventricle Solitary Fibrous Tumor (SFT): A Case Report With Literature Review.

Solitary fibrous tumors (SFTs) are rare mesenchymal neoplasms that can occur intraventricularly, presenting diagnostic and management challenges. We describe a case of a 21-year-old male with no significant medical history who presented with intermittent headaches and vomiting, progressing to continuous symptoms. Neurological examination was unremarkable. Brain MRI revealed an isointense lesion in the occipital horn of the left lateral ventricle, diagnosed as an SFT. Surgical excision via a transcortical approach was successful, followed by postoperative radiotherapy. This case highlights the complexities in diagnosing and treating intraventricular SFTs, emphasizing the need for comprehensive evaluation and multimodal management strategies.