Periventricular White Matter Changes Research Articles

A predictive model in patients with chronic hydrocephalus following aneurysmal subarachnoid hemorrhage: a retrospective cohort study.

Our aim was to develop a nomogram that integrates clinical and radiological data obtained from computed tomography (CT) scans, enabling the prediction of chronic hydrocephalus in patients with aneurysmal subarachnoid hemorrhage (aSAH). A total of 318 patients diagnosed with subarachnoid hemorrhage (SAH) and admitted to the Department of Neurosurgery at the Affiliated People's Hospital of Jiangsu University between January 2020 and December 2022 were enrolled in our study. We collected clinical characteristics from the hospital's medical record system. To identify risk factors associated with chronic hydrocephalus, we conducted both univariate and LASSO regression models on these clinical characteristics and radiological features, accompanied with penalty parameter adjustments conducted through tenfold cross-validation. All features were then incorporated into multivariate logistic regression analyses. Based on these findings, we developed a clinical-radiological nomogram. To evaluate its discrimination performance, we conducted Receiver Operating Characteristic (ROC) curve analysis and calculated the Area Under the Curve (AUC). Additionally, we employed calibration curves, and utilized Brier scores as an indicator of concordance. Additionally, Decision Curve Analysis (DCA) was performed to determine the clinical utility of our models by estimating net benefits at various threshold probabilities for both training and testing groups. The study included 181 patients, with a determined chronic hydrocephalus prevalence of 17.7%. Univariate logistic regression analysis identified 11 potential risk factors, while LASSO regression identified 7 significant risk factors associated with chronic hydrocephalus. Multivariate logistic regression analysis revealed three independent predictors for chronic hydrocephalus following aSAH: Periventricular white matter changes, External lumbar drainage, and Modified Fisher Grade. A nomogram incorporating these factors accurately predicted the risk of chronic hydrocephalus in both the training and testing cohorts. The AUC values were calculated as 0.810 and 0.811 for each cohort respectively, indicating good discriminative ability of the nomogram model. Calibration curves along with Hosmer-Lemeshow tests demonstrated excellent agreement between predicted probabilities and observed outcomes in both cohorts. Furthermore, Brier scores (0.127 for the training and 0.09 for testing groups) further validated the predictive performance of our nomogram model. The DCA confirmed that this nomogram provides superior net benefit across various risk thresholds when predicting chronic hydrocephalus. The decision curve demonstrated that when an individual's threshold probability ranged from 5 to 62%, this model is more effective in predicting the occurrence of chronic hydrocephalus after aSAH. A clinical-radiological nomogram was developed to combine clinical characteristics and radiological features from CT scans, aiming to enhance the accuracy of predicting chronic hydrocephalus in patients with aSAH. This innovative nomogram shows promising potential in assisting clinicians to create personalized and optimal treatment plans by providing precise predictions of chronic hydrocephalus among aSAH patients.

PMPCA-Related Encephalopathy: Novel Variants, Phenotype Extension, and Mitochondrial Morphology.

The PMPCA gene encodes the α-subunit of mitochondrial processing peptidase (α-MPP), an enzyme responsible for cleavage of nuclear-encoded mitochondrial precursor proteins after their import into mitochondria. Mutations in this gene have been described in patients with nonprogressive or slow progressive cerebellar ataxia, with variable age at onset and severity. Cerebellar atrophy and striatum changes were found in severe cases. The patient was diagnosed using whole exome sequencing. Skin fibroblasts were used for confirmation of α-MPP levels using western blot and mitochondrial morphology assessment of immunofluorescent confocal microscopy images. Two novel compound heterozygous variants in the PMPCA gene (p.Tyr241Ser and p.Met251Val) were identified in an 8-year-old proband with progressive spastic quadriparesis, delayed psychomotor development, and intellectual disability, with onset at 13 months. The brain imaging showed cortical and cerebellar atrophy, reduced volume of basal ganglia with striatum hyperintensity, and periventricular white matter changes. The patient's fibroblasts showed a decreased α-MPP level and reduced and fragmented mitochondria. The described case contributes to the number of patients with progressive PMPCA-related disease with a severe intermediate phenotype. Moreover, we extend the phenotype to Leigh-like white matter changes that have not been described in previously reported cases.

282 Radiological Features Predicting Shunt Response in Normal Pressure Hydrocephalus, a Systematic Review and Meta-Analysis

Abstract Aim To produce a systematic review and meta-analysis to identify radiological features that predict shunt response in normal pressure hydrocephalus (NPH), evaluate their effectiveness and therefore recommend the most predictive feature. Method The authors searched MEDLINE, Embase, Scopus, PubMed, Google scholar and JSTOR databases for all original studies investigating NPH radiological features that predict shunt response. Selected studies were assessed with ROBINS-1 tool and included studies were evaluated by a univariate meta-analysis. Results 301 full text papers were selected from screening, 28 studies were included, and 26 features were identified, of these 5 were selected for the meta-analysis based off the inclusion criteria: disproportionately enlarged subarachnoid space (DESH), callosal angle, periventricular white matter changes, cerebral blood flow (CBF), and computerized tomography cisternography. The diagnostic odds ratios of colossal angle (1.88) and periventricular white matter changes (1.01) showed they were significant differentiators between shunt responders from non-responders. None of the other features could differentiate between the two. Conclusions Colossal angle and periventricular white matter changes are the only statistically effective features which can identify shunt responders. Their role, however, may be overstated as their DORs approximate 1, therefore it is advised they be used in combination with other diagnostic predictors, such as clinical tests, of shunt responders. More research is required to evaluate the combined use of multiple radiological features together.

Leukoencephalopathy with vanishing white matter disease: a case report study.

The authors report two cases of VWM disease. In the first case, an 8-month-old female child, brought to the pediatric clinic with seizure and loss of consciousness. The second case was a 24-month-old girl, presented with weakness, a disability to walk and swallow, and poor feeding. Her brain MRI demonstrated cystic changes (white matter rarefaction) in supratentorial peri-ventricular white matter and genetic testing result showed an EIF2B3 gene mutation. Leukoencephalopathy with VWM, also known as Cree encephalopathy is caused by mutations in the EIF2B gene. The disease is inherited in an autosomal recessive fashion. There are various agents leading to symptoms and signs of VWM disease. Physical stress like head trauma even in a mild degree, infections, and febrile diseases can be mentioned as causes of VWM. The eIF2B complex, plays a role as an important factor in the regulation of protein synthesis in cells under different conditions. As a conclusion, genetic counseling could be recommended to all individuals with VWM disease and their family members for next pregnancies and possible precautions for consanguineous marriages.

Research on clinical and molecular genetics of hereditary spastic paraplegia 11 patients in China.

The hereditary spastic paraplegia (HSP) is a rare hereditary disease in nervous system due to the damage of corticospinal tract. HSP has various inheritance modes, including autosomal dominant inheritance, autosomal recessive inheritance, X-linked inheritance, and mitochondrial inheritance in some cases. At present, there are at least 80 subtypes of HSP. Hereditary spastic paraplegia type 11 (SPG11) is the most common subtype in autosomal recessive inheritance, and its pathogenic factor is KIAA1840 gene, which encodes spatacsin protein. A total of 52 SPG11 patients aged from 4-24 years old have been reported. Their initial symptoms were gait disturbance and/or mental retardation. As the disease develops, they may present with mental retardation, sphincter disturbance, decreased vision, ataxia, amyotrophy, pes arcuatus, ophthalmoplegia, peripheral neuropathy, and others. Except agenesis of the corpus callosum and periventricular white matter changes, patients might show cortical atrophy, ventricular dilation, and cerebellar atrophy, and so on. Chinese SPG11 patients manifested significant clinical and genetical heterogeneity and no obvious gender difference. Of them, 37 pathogenic mutations of KIAA1840 gene were detected, which all introduced truncated mutation of spatacsin protein. KIAA1840 gene frameshift mutation is the most common type of mutation.

Radiological predictors of shunt response in the diagnosis and treatment of idiopathic normal pressure hydrocephalus: a systematic review and meta-analysis

BackgroundPatients with the dementia subtype idiopathic normal pressure hydrocephalus (iNPH) may improve clinically following cerebrospinal fluid (CSF) diversion (shunt) surgery, though the predictors of shunt response remain debated. Currently, radiological features play an important role in the diagnosis of iNPH, but it is not well established which radiological markers most precisely predict shunt responsive iNPH.ObjectiveTo conduct a systematic review and meta-analysis to identify radiological predictors of shunt responsiveness, evaluate their diagnostic effectiveness, and recommend the most predictive radiological features.MethodsEmbase, MEDLINE, Scopus, PubMed, Google Scholar, and JSTOR were searched for original studies investigating radiological predictors of shunt response in iNPH patients. Included studies were assessed using the ROBINS-1 tool, and eligible studies were evaluated using a univariate meta-analysis.ResultsOverall, 301 full-text papers were screened, of which 28 studies were included, and 26 different radiological features were identified, 5 of these met the inclusion criteria for the meta-analysis: disproportionately enlarged subarachnoid space (DESH), callosal angle, periventricular white matter changes, cerebral blood flow (CBF), and computerized tomography cisternography. The meta-analysis showed that only callosal angle and periventricular white matter changes significantly differentiated iNPH shunt responders from non-responders, though both markers had a low diagnostic odds ratio (DOR) of 1.88 and 1.01 respectively. None of the other radiological markers differentiated shunt responsive from shunt non-responsive iNPH.ConclusionCallosal angle and periventricular changes are the only diagnostically effective radiological predictors of shunt responsive iNPH patients. However, due to the DORs approximating 1, they are insufficient as sole predictors and are advised to be used only in combination with other diagnostic tests of shunt response. Future research must evaluate the combined use of multiple radiological predictors, as it may yield beneficial additive effects that may allow for more robust radiological shunt response prediction.

Automatic CT Angiography Lesion Segmentation Compared to CT Perfusion in Ischemic Stroke Detection: a Feasibility Study

In stroke imaging, CT angiography (CTA) is used for detecting arterial occlusions. These images could also provide information on the extent of ischemia. The study aim was to develop and evaluate a convolutional neural network (CNN)–based algorithm for detecting and segmenting acute ischemic lesions from CTA images of patients with suspected middle cerebral artery stroke. These results were compared to volumes reported by widely used CT perfusion–based RAPID software (IschemaView). A 42-layer-deep CNN was trained on 50 CTA volumes with manually delineated targets. The lower bound for predicted lesion size to reliably discern stroke from false positives was estimated. The severity of false positives and false negatives was reviewed visually to assess the clinical applicability and to further guide the method development. The CNN model corresponded to the manual segmentations with voxel-wise sensitivity 0.54 (95% confidence interval: 0.44–0.63), precision 0.69 (0.60–0.76), and Sørensen–Dice coefficient 0.61 (0.52–0.67). Stroke/nonstroke differentiation accuracy 0.88 (0.81–0.94) was achieved when only considering the predicted lesion size (i.e., regardless of location). By visual estimation, 46% of cases showed some false findings, such as CNN highlighting chronic periventricular white matter changes or beam hardening artifacts, but only in 9% the errors were severe, translating to 0.91 accuracy. The CNN model had a moderately strong correlation to RAPID-reported Tmax > 10 s volumes (Pearson’s r = 0.76 (0.58–0.86)). The results suggest that detecting anterior circulation ischemic strokes from CTA using a CNN-based algorithm can be feasible when accompanied with physiological knowledge to rule out false positives.

Increased interstitial fluid in periventricular and deep white matter hyperintensities in patients with suspected idiopathic normal pressure hydrocephalus

Periventricular white matter changes are common in patients with idiopathic normal pressure hydrocephalus (iNPH) and considered to represent focally elevated interstitial fluid. We compared diffusion measures in periventricular hyperintensities in patients with imaging features of iNPH to patients without. The hypothesis is that periventricular hyperintensities in patients with presumed iNPH show higher water content than in patients without imaging features of iNPH. 21 patients with iNPH Radscale 7–12 (“high probability of iNPH”) and 10 patients with iNPH Radscale 2–4 (“low probability of iNPH”) were examined with a neurodegeneration imaging protocol including a diffusion microstructure imaging sequence. Periventricular hyperintensities and deep white matter hyperintensities were segmented and diffusion measures were compared. In patients with imaging features of iNPH, the free water content in periventricular hyperintensities was significantly higher compared to the control group (p = 0.005). This effect was also detectable in deep white matter hyperintensities (p = 0.024). Total brain volumes and total gray or white matter volumes did not differ between the groups. Periventricular cap free water fraction was highly discriminative regarding patients with presumed iNPH and controls with an ROC AUC of 0.933. Quantitative diffusion microstructure imaging shows elevated water content in periventricular hyperintensities in patients with imaging features of iNPH, which could be the imaging correlate for pathologic fluid accumulation and may be used as an imaging biomarker in the future.

A Rare Case of Hereditary Spastic Paraplegia: Case Report and Literature Review

Hereditary spastic paraplegia (HSP) is a rare neurodegenerative disorder presenting as lower limb spasticity having two clinical types and various modes of inheritance. A young male patient presented with bilateral lower limb weakness of one-year duration showing both sensory and motor abnormalities on examination. MRI of brain and spine done as part of workup revealed marked atrophy of anterior corpus callosum with abnormal signal intensity at tips of frontal horns of ventricles mimicking the appearance of the ear of a Eurasian lynx. No other abnormality was encountered in the brain or spinal cord in our case. Other imaging abnormalities which can be encountered in such a case include periventricular and central white matter changes as well as spinal cord atrophy. Pathologically this condition is recognised by degeneration of lateral and posterior columns of the spinal cord. The differential diagnosis includes structural, metabolic, neurodegenerative, motor and nutritional deficiency disorders.

TREM2 variants as a possible cause of frontotemporal dementia with distinct neuroimaging features.

Nasu-Hakola disease (NHD) is a rare, autosomal recessive disorder characterized by skeletal and neurological symptoms. Behavioral symptoms with cognitive impairment may mimic the behavioral variant of frontotemporal dementia (bvFTD) and other early-onset dementias. Our patients were analyzed and the literature was reviewed to delineate neurological and neuroimaging findings suggestive of NHD. Fourteen patients carrying a pathogenic mutation in the TREM2 gene were found in our database. Demographic, clinical, laboratory and radiological data were retrieved and analyzed. The presenting clinical picture was behavioral changes with cognitive decline resembling bvFTD in all patients. The mean age was 37.1±4.97years and the mean duration of the disease was 8.9±3.51years. Only two patients had typical bone cysts. Seven patients had bilateral calcification of the basal ganglia in computed tomography of the brain. Magnetic resonance imaging of the brain revealed severe atrophy of the corpus callosum, enlargement of the ventricles, atrophy of the caudate nuclei and periventricular white matter changes in all patients. Symmetrical global atrophy of the brain mainly affecting frontoparietal and lateral temporal regions were observed in all cases, and 13 patients had atrophy of the hippocampus. Cerebrospinal fluid examination of 10 patients showed elevated protein levels in six and the presence of oligoclonal bands in four patients. A combination of white matter changes, enlarged ventricles, atrophy of the caudate nuclei and thinning of the corpus callosum in magnetic resonance imaging strongly suggests NHD in patients with FTD syndrome. Molecular genetic analysis should be performed in suspected cases, and families should receive genetic counseling.

Manifestation of cognitive impairments after a prior coronavirus infection COVID-19 in a patient with ApoE ε4 genotype

Nowadays, the novel coronavirus infection (COVID-19) pandemic is one of the most important global health problems. There is increasing evidence that COVID-19 affects central and peripheral nervous system as well. The paper presents a clinical case of a 47 old patient with the ApoE ε4 haplotype and family history of Alzheimer’s disease who developed cognitive impairment after acute COVID-19. Before the infection the patient has no cognitive complaints and preserved everyday activity. After novel coronavirus infection, which was observed in mild form, the patient had started to complain on constant excessive forgetfulness. Neuropsychological assessment confirmed the presence of pre-mild cognitive impairment of predominantly single domain amnestic type. However, brain MRI showed only subtle periventricular white matter changes usually attributed to small vessel disease. Memory complaints were observed for 3 months of follow up despite intensive cognitive training, optimization of lifestyle and therapy with choline alphoscerate. Probable links between coronavirus infectious and cognitive impairment manifestation are discussed. There is data that ApoE ε4 haplotype is associated with increase of microglia mediated neuro-inflammation and it can be significant for accelerating of progression of neurodegenerative diseases after COVID-19. Further follow up of the patient is necessary for determination of nosological diagnosis explaining manifested predominantly amnestic type pre-mild cognitive impairment.

The association between white matter changes and development of malignant middle cerebral artery infarction: A case-control study.

Disrupted blood–brain barrier (BBB) in patients with ischemic stroke plays a critical role in malignant middle cerebral artery infarction (MMI) development.Cerebral white matter changes (WMC), particularly in the deep subcortical area or in severe one, may be also underlain by disrupted BBB. It is unclear whether the presence of WMC with potential premorbid disruption of BBB makes patients susceptible to MMI. Therefore, this study aimed to clarify any putative relationship between the MMI and WMC in terms of their severity and locations.In this case–control study, patients with infarction in the middle cerebral artery territory were retrospectively reviewed. Brain magnetic resonance images were analyzed according to Fazekas scale, and identified WMC were divided into periventricular WMC (PV-WMC) and deep subcortical WMC (deep-WMC). Patients were scored as having WMC, PV-WMC, deep-WMC, severe PV-WMC, and severe deep-WMC according to the severity and locations. Patients were defined as having MMI if either a progressive conscious disturbance or signs of uncal herniation was recorded in combination with a midline shift >5 mm identified on the follow-up computed tomography.Among 297 patients admitted between July 2009 and February 2015, 92 patients were eligible for final analysis. Compared to patients without MMI, patients with MMI had a higher score of National Institutes of Health Stroke Scale, a larger infarct volume, and an increasingly greater proportion of severe PV-WMC, deep-WMC, and severe deep-WMC, respectively. After adjustment for sex, age, infarct volume, and history of hypertension, severe deep-WMC (odds ratio [OR] = 6.362, 95% confidence interval [CI] = 1.444–28.023, P = .0144) and severe PV-WMC (odds ratio = 5.608, 95% confidence interval = 1.107–28.399, P = .0372) were significantly associated with MMI development.MMI and WMC are significantly associated such that MMI development is more likely when PV-WMC or deep-WMC is more severe. We hypothesize that Fazekas scale-defined severe deep-WMC and PV-WMC may be considered as clinically approachable predictors of MMI development. These findings support that the WMC with potential premorbid disrupted BBB may make patients susceptible to MMI, and further prospective study should be conducted to clarify this hypothesis.

Magnetic resonance white matter changes in patients with obstructive sleep apnoea. The subset of the PURE-MIND (Prospective Urban and Rural Epidemiological) cohort study

IntroductionChanges typical for cerebral small vessel disease (i.a. white matter hyperintensities – WMHs) are often found accidentally in neuroimaging studies. Although asymptomatic, this condition increases the risk of future ischaemic incidents and neurodegenerative disorders. Sleep apnoea is a recognised risk factor for vascular diseases. The aim of our study was to assess the prevalence of, and association between, obstructive sleep apnea (OSA) and cerebral small vessel disease in the studied population.Material and methodsTwo hundred and seven patients (participants of Prospective Urban Rural Epidemiology Study) took part in our study. The study group consisted of 31 patients with OSA (11 women and 20 men). Nine of them were diagnosed with mild OSA, nine with moderate OSA, and 13 with severe OSA. The control group consisted of 176 patients (133 women and 43 men) who scored 0–2 points in the STOP-BANG questionnaire. All patients underwent brain magnetic resonance imaging. We evaluated the occurrence and severity of WMHs.ResultsSignificantly higher incidence of WMHs was found in the study group compared to controls. In univariate analyses, age was a significant predictor of periventricular white matter changes. For subcortical area, age and waist-to-hip ratio were significant predictors.ConclusionsSignificantly higher incidence of WMHs in the studied group suggests that patients with OSA may have a higher risk of neurodegeneration.

Abstract P329: White Matter Score Does Not Predict Post-tPA Hemorrhage in Elderly Patients Evaluated Acutely via Telestroke

Background: While tPA may be safe in the elderly, increasing age appears to augment risk of post-tPA symptomatic intracranial hemorrhage (sICH). Age-related white matter changes (ARWMC) are associated with increased sICH. Patients evaluated for acute ischemic stroke (AIS) via telestroke (TS) may not have access to MRI to allow incorporation of microbleeds in tPA decisions. We assessed if increased CT-based ARWMC was associated with increased sICH in elderly patients. Methods: Patients 80 years and older who received tPA for AIS at spoke hospitals were selected from our TS network registry from 9/2015 to 12/2018. TS spoke CT scans from patient presentation were reviewed by three of the authors for periventricular white matter (PWMC) and deep white matter (DWMC) changes. Total ARWMC score, based on the Fazekas score, was collected. Total ARWMC score was either mild (0-2), moderate (3-4), or severe (5-6). PWMC and DWMC were either mild (0-1) or moderate-severe (2-3). Logistic regression adjusted for age, sex, race, ethnicity, NIHSS and premorbid mRS was used to analyze relationship of ARWMC scores with sICH and patient-outcomes. Results: Of 241 patients, median age overall was 86 years (IQR 83-90), and 66% were female. The overall median ARWMC score was 3 (IQR 2-5). Regression analysis showed that more severe ARWMC scores did not lead to higher frequency of post-tPA ICH (moderate OR 0.57, CI 0.19-1.71; severe OR 1.32, CI 0.48-3.65) including sICH (moderate OR 0.78, CI 0.21-2.94; severe OR 2.09, CI 0.62-7.02). Similarly, severe PWMC and DWMC were not associated with increased risk of post-tPA ICH (PWMC OR 1.31, CI 0.51-3.38; DWMC OR 1.25, CI 0.52-3.01), including sICH (PWMC OR 1.61, CI 0.51-5.08; DWMC OR 1.81, CI 0.65-5.01). In our cohort, older patients had no difference in hemorrhage (ICH OR 0.93 CI 0.85-1.00: sICH OR 0.95 CI 0.86-1.04), and patients with less severe stroke were more likely to have hemorrhage (ICH OR 1.06 CI 1.02-1.10; sICH OR 1.08 CI 1.03-1.13). IRR among the CT scan readers was moderate (k=0.504). Conclusions: ARWMC scores were not associated with post-tPA ICH in the elderly. Our analysis lends support for the use of tPA despite severity of white matter disease. ARWMC should not be used to assist in tPA decision-making in elderly patients via telestroke.

Abstract P390: Prediction Enhancement of the Post-Stroke Delirium by Adding of the Brain Lesional Characteristics to the Clinical Features in Acute Ischemic Stroke Patients

Background: We evaluated whether the brain regional features could enhance the prediction of the occurrence of the post-stroke delirium along with consideration of clinical features in acute ischemic stroke patients. Method: We analyzed magnetic resonance imaging and clinical datasets prospectively collected from 1,024 acute ischemic stroke patients (620 men; mean age±SD, 70.2±11.8 years), who were admitted in stroke unit. Delirium occurrence in the patients was initially screened with Confusion Assessment Method and finally diagnosed using the criteria of the Diagnostic and Statistical Manual of Mental Disorders (fifth edition). The prediction performance of the clinical features was evaluated using the logistic regression analysis, and then, compared with the performance obtained after adding of the brain lesional features. Results: Post-stroke delirium occurred in 100 (9.8%) of the total patients. Independent features of the clinical features were old age (odds ratio [OR] for the delirium prediction: 1.07, 95% confidence interval [CI] 1.038-1.103), preexisting dementia (OR 0.423, CI 0.209-0.853) and atrial fibrillation OR 1.599, CI 0.938-2.726), neglect (OR 2.395, CI 1.152-4.976), visual defect (OR 2.209, CI 0.994-4.907), diplopia (OR 2.42, CI 1.021-5.738), dysuria (OR 2.404, 95% CI 1.155-5.000), Foley catheter insertion (OR 0.46, CI 0.24-0.881) and pneumonia (OR 1.954, CI 1.004-3.803). Right-sided hemispheric and mixed acute lesions (p=0.003), lesion locations in occipital lobe (OR 1.814, CI 0.923-3.564), cerebellum (OR 2.875, CI 1.32-6.258) and brainstem (OR 4.057, CI 1.714-9.601), and the presence of the periventricular white matter change (OR 1.321, CI 0.964-1.811) increased the risk for delirium. Sensitivity to predict the delirium of the regression model was enhanced from 10% obtained with the clinical features to 18% by adding the brain lesional features. Area under the curve of the receiver operating characteristics analysis was also enhanced from 0.827 with the clinical features to 0.847 after adding the brain lesions to the clinical features. Conclusion: The present study shows brain lesional characteristics that could enhance the prediction of the post-stroke delirium in acute ischemic stroke patients.

Hereditary spastic paraplegia type 11: Clinicogenetic lessons from 339 patients

Hereditary spastic paraplegia type 11 (SPG11) is the most common subtype of autosomal recessive hereditary spastic paraplegia (HSP), to date, there are more than 181 different KIAA1840 gene mutations detected, and yet the genetic landscape of SPG11 is far from complete. To find the clinical and genetic characteristics of SPG11, we performed a reanalysis of the clinical features and genotype-phenotype correlations in all reported studies exhibiting SPG11 mutations. A total of 339 patients were collected, their mean age at onset was 13.10 ± 3.65 years, with initial symptoms like gait disturbance (107/195, 54.87%) and mental retardation (47/195, 24.10%). Cognitive decline (228/270, 84.44%) was the most common complex manifestation stepped by dysarthria (134/195, 68.72%), neuropathy (112/177, 63.28%), amyatrophy, sphincter disturbance (60/130, 46.15%) and ataxia (90/194, 46.39%). The most common brain MRI abnormality is thinning of the corpus callosum (TCC) (173/190, 91.05%), followed by periventricular white matter changes (130/158, 82.28%), cerebral or cerebellar cortical atrophy (55/107, 51.40%). The mutational spectrum associated with KIAA1840 gene is wide, and frameshift mutations are the most common type followed by nonsense mutations. Our reanalysis demonstrated that SPG11 exhibited significant clinical and genetic heterogeneity, and no clear genotype-phenotype correlation was observed. There is no mutational hot spot in the KIAA1840 gene, which emphasizes the need to analyse the whole gene in clinical practice. In addition to conventional genetic testing methods, further mRNA analysis should be conducted on some cases to yield a definitive diagnosis.

CD8 encephalitis with CSF EBV viraemia and HIV drug resistance, a case series

IntroductionCD8 encephalitis is a relatively recently described condition in the setting of HIV infection. It is becoming increasingly recognised in recent years though is still likely underdiagnosed. MethodsWe present three cases of encephalitis in HIV-positive black African females initially presenting with neurological pathology. Two cases concern recent presentations of patients attending HIV services at a large tertiary referral hospital and the third case involves a retrospective analysis of an archived case. Results and discussionMRI brain demonstrated periventricular white matter changes in 2 cases and a cerebellar lesion in the third case. CSF examination revealed lymphocytosis and elevated protein levels. CSF HIV viral load analysis showed viral escape along with new antiretroviral drug resistance mutations. CSF flow cytometry studies demonstrated a reversed CD4:CD8 ratio with a high CD8+ cells percentage. All patients had EBV DNA detected in their CSF. Brain biopsy in two patients confirmed CD8 encephalitis and also revealed isolated cells demonstrating EBV positivity by in-situ hybridization using EBER (Epstein–Barr virus-encoded small RNAs). Treatment with steroids and ART optimisation led to significant clinical and radiological improvements in all cases. DiscussionCD8 encephalitis should be considered as a cause of neurological symptoms and confusion in the HIV-positive patient, particularly if poor ART adherence or viral resistance are suspected. Brain biopsy should be considered in HIV-positive patients with encephalopathy of uncertain cause. Early treatment with high-dose corticosteroids when suspecting this diagnosis is essential for a favourable outcome. The prognosis is variable but can be favourable even following severe encephalopathy. The presence of new INSTI mutations in the CSF but absent peripherally in two INSTI-era patients is a novel finding for this case series in the context of CD8 encephalitis. The role played by EBV in this disease remains unclear and warrants further investigation.

Brain MRI features of methylmalonic acidemia in children: the relationship between neuropsychological scores and MRI findings

Methylmalonic acidemia (MMA) is a severe, heterogeneous disorder of methylmalonate and cobalamin (cbl; vitamin B12) metabolism with a poor prognosis that can cause brain damage. Identifying the magnetic resonance imaging (MRI) findings of MMA might help to make accurate diagnoses earlier in the disease course and exploring the relationship between neuropsychological scores and MRI findings, when therapy is more effective and to improve therapeutic efficacy. Cerebral MRI studies from 37 children with MMA were evaluated by a neuroradiologist. Clinical and imaging data were collected from each patient. All tests were performed during routine investigations and in accordance with the ethical principles of the Declaration of Helsinki. Informed consent was obtained from the guardians of all patients for inclusion in the study. The most common and significant findings were periventricular white matter changes (78.4%), ventricular dilation (29.7%) and cerebral atrophy (40.5%). According to the developmental quotient, the 37 patients were divided into the normal intelligence subgroup (NI, developmental quotient ≥ 85) and the low intelligence subgroup (LI, developmental quotient < 85). The incidence of corpus callosal thinning, cortical atrophy, subcortical white matter changes, and ventricular dilation (grades 0–3) was significantly higher in the LI subgroup than in the NI subgroup (P < 0.05). The incidence of no-mild and moderate-severe ventricular dilation was significantly higher in the LI subgroup than in the NI subgroup (P < 0.05). Ventricular dilatation, cerebral atrophy, white matter changes, and corpus callosal thinning are the main MRI abnormalities in MMA patients, and these manifestations are significantly correlated with delayed development in children.

Cerebrovascular pathology and misdiagnosis of multiple system atrophy: An autopsy study

BackgroundMultiple system atrophy (MSA) is a progressive neurodegenerative disease characterized by a combination of dysautonomia, parkinsonism, and cerebellar ataxia. Other disorders can mimic MSA, but it is unknown whether cerebrovascular pathology, so-called “vascular parkinsonism,” can mimic MSA. This study aimed to determine the clinicopathological features and red flags for vascular parkinsonism masquerading as MSA. MethodsUsing a brain bank database, we screened 270 patients with an antemortem diagnosis of MSA, who did not have pathologic evidence of MSA, but rather cerebrovascular pathology, including leukoencephalopathy, lacunar infarcts, and microinfarcts. Histologic sections from the neocortex, basal ganglia, thalamus, brainstem, and cerebellum were reviewed. Medical records were reviewed to characterize the clinical features. The probability of a clinical diagnosis of MSA was assigned retrospectively, guided by current consensus criteria. ResultsFour patients had cerebrovascular pathology without neurodegenerative processes. Chronic ischemic changes in periventricular white matter, subcortical leukoencephalopathy, lacunar infarcts, or microinfarcts were detected in basal ganglia of all patients. Cerebrovascular pathology that might contribute to autonomic failure was not identified. Clinically, two patients were diagnosed with possible MSA-parkinsonism, one with probable MSA-parkinsonism, and one with possible MSA-cerebellar type; however, they also had one or more non-supporting features of MSA (e.g., onset >75-years of age, dementia), vascular risk factors, and other etiologies (e.g., autonomic neuropathy) that could cause autonomic failure. ConclusionsWhen combined with cerebrovascular risk factors and comorbidities, cerebrovascular pathology may masquerade as MSA. The important lesson from this study is that the diagnosis of MSA requires exclusion of other causes, including cerebrovascular disease.

Abstract WP368: Evaluation of Brain Regional Characteristics Related With Post-Stroke Delirium Using Machine Learning and Statistical Analysis

Background: The present study was performed to evaluate the brain regional characteristics related with development of post-stroke delirium using the machine learning and statistical analysis. Method: We used clinical and radiological data prospectively collected from 675 acute ischemic stroke patients, who were admitted in stroke unit from August 2017 to July 2018. Delirium occurrence in the patients was screened with Confusion Assessment Method and finally diagnosed using the criteria of the Diagnostic and Statistical Manual of Mental Disorders (fifth edition). Three machine learning models, Support Vector Machine (SVM), Random Forest (RF) and Tree-based Gradient Boosting (XGBoost), were applied for the prediction of post-stroke delirium with the clinical and radiologic data. And logistic regression analysis was performed to evaluate the significance of the brain regional parameters included in the importance features which were obtained from the XGBoost result. Results: Post-stroke delirium occurred in 66 (9.8%) of the total patients. On the comparison of the test accuracy to predict delirium occurrence, RF (94%), XGBoost test (93%), and SVM (89%) showed similar prediction rates. Of the brain regional parameters included in the top 30 feature importance, right side cerebral hemisphere, non-lacunar infarction, severity of periventricular white matter changes, acute temporal lobe lesion, cerebellum, brain stem, and previous lesions developed on right side cerebral hemisphere, and in temporal or frontal lobe. Conclusion: The present study shows that the brain regional characteristics related with the post-stroke delirium are shown to be significant when controlling the other features using statistical analysis with machine learning. Even though we need more studies to validate the relationships between post-stroke delirium and brain regional characteristics, the present brain regional characteristics could provide significant evidences to predict post-stroke delirium for the acute ischemic stroke patients.