Subependymomas of the fourth ventricle: To operate or not to operate?

BACKGROUND: There is a paucity of literature regarding the clinical characteristics and management of subependymomas of the fourth ventricle due to their rarity. Here, we describe the operative and non-operative management and outcomes of patients with such tumors. METHODS: This retrospective single-institution case series was gathered after Institutional Review Board (IRB) approval. Patients diagnosed with a subependymoma of the fourth ventricle between 1993 and 2021 were identified. Clinical, radiology and pathology reports along with magnetic resonance imaging (MRI) images were reviewed. RESULTS: Patients identified (n = 20), showed a male predominance (n = 14). They underwent surgery (n = 9) with resection and histopathological confirmation of subependymoma or were followed with imaging surveillance (n = 11). The median age at diagnosis was 51.5 years. Median tumor volume for the operative cohort was 8.64 cm3 and median length of follow-up was 65.8 months. Median tumor volume for the non-operative cohort was 0.96 cm3 and median length of follow-up was 78 months. No tumor recurrence post-resection was noted in the operative group, and no tumor growth from baseline was noted in the non-operative group. Most patients (89 %) in the operative group had symptoms at diagnosis, all of which improved post-resection. No patients were symptomatic in the non-operative group. CONCLUSIONS: Surgical resection is safe and is associated with alleviation of presenting symptoms in patients with large tumors. Observation and routine surveillance are warranted for smaller, asymptomatic tumors.

The T2-FLAIR mismatch sign in oncologic neuroradiology: History, current use, emerging data, and future directions.

The T2-Fluid-Attenuated Inversion Recovery (T2-FLAIR) mismatch sign is a radiogenomic marker that is easily discernible on preoperative conventional MR imaging. Application of strict criteria (adult population, cerebral hemisphere location, and classic imaging morphology) permits the noninvasive preoperative diagnosis of isocitrate dehydrogenase (IDH)-mutant 1p/19q-non-codeleted diffuse astrocytoma with near-perfect specificity, albeit with variably low sensitivity. This leads to improved preoperative planning and patient counseling. More recent research has shown that the application of less strict criteria compromises the near-perfect specificity of the sign but remains adequate for ruling out IDH-wildtype (glioblastoma) phenotype, which bears a far grimmer prognosis compared to IDH-mutant diffuse astrocytic disease. In this review, we elaborate on the various definitions of the T2-FLAIR mismatch sign present in the literature, illustrate these with images obtained at a comprehensive cancer center, discuss the potential of the mismatch sign for application to certain pediatric-type brain tumors, namely dysembryoplastic neuroepithelial tumor and diffuse midline glioma, and elaborate upon the clinical, histologic, and molecular associations of the T2-FLAIR mismatch sign as recognized to date. Finally, the sign's correlates in diffusion- and perfusion-weighted imaging are presented, and opportunities to further maximize the diagnostic and prognostic applications of the sign in the context of the 2021 revision of the WHO Classification of Central Nervous System Tumors are discussed.

Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence.

Importance: Electroencephalograms (EEGs) are a fundamental evaluation in neurology but require special expertise unavailable in many regions of the world. Artificial intelligence (AI) has a potential for addressing these unmet needs. Previous AI models address only limited aspects of EEG interpretation such as distinguishing abnormal from normal or identifying epileptiform activity. A comprehensive, fully automated interpretation of routine EEG based on AI suitable for clinical practice is needed. Objective: To develop and validate an AI model (Standardized Computer-based Organized Reporting of EEG-Artificial Intelligence [SCORE-AI]) with the ability to distinguish abnormal from normal EEG recordings and to classify abnormal EEG recordings into categories relevant for clinical decision-making: epileptiform-focal, epileptiform-generalized, nonepileptiform-focal, and nonepileptiform-diffuse. Design, Setting, and Participants: In this multicenter diagnostic accuracy study, a convolutional neural network model, SCORE-AI, was developed and validated using EEGs recorded between 2014 and 2020. Data were analyzed from January 17, 2022, until November 14, 2022. A total of 30 493 recordings of patients referred for EEG were included into the development data set annotated by 17 experts. Patients aged more than 3 months and not critically ill were eligible. The SCORE-AI was validated using 3 independent test data sets: a multicenter data set of 100 representative EEGs evaluated by 11 experts, a single-center data set of 9785 EEGs evaluated by 14 experts, and for benchmarking with previously published AI models, a data set of 60 EEGs with external reference standard. No patients who met eligibility criteria were excluded. Main Outcomes and Measures: Diagnostic accuracy, sensitivity, and specificity compared with the experts and the external reference standard of patients' habitual clinical episodes obtained during video-EEG recording. Results: The characteristics of the EEG data sets include development data set (N = 30 493; 14 980 men; median age, 25.3 years [95% CI, 1.3-76.2 years]), multicenter test data set (N = 100; 61 men, median age, 25.8 years [95% CI, 4.1-85.5 years]), single-center test data set (N = 9785; 5168 men; median age, 35.4 years [95% CI, 0.6-87.4 years]), and test data set with external reference standard (N = 60; 27 men; median age, 36 years [95% CI, 3-75 years]). The SCORE-AI achieved high accuracy, with an area under the receiver operating characteristic curve between 0.89 and 0.96 for the different categories of EEG abnormalities, and performance similar to human experts. Benchmarking against 3 previously published AI models was limited to comparing detection of epileptiform abnormalities. The accuracy of SCORE-AI (88.3%; 95% CI, 79.2%-94.9%) was significantly higher than the 3 previously published models (P < .001) and similar to human experts. Conclusions and Relevance: In this study, SCORE-AI achieved human expert level performance in fully automated interpretation of routine EEGs. Application of SCORE-AI may improve diagnosis and patient care in underserved areas and improve efficiency and consistency in specialized epilepsy centers.

Normal variants and artifacts: Importance in EEG interpretation.

Overinterpretation of EEG is an important contributor to the misdiagnosis of epilepsy. For the EEG to have a high diagnostic value and high specificity, it is critical to recognize waveforms that can be mistaken for abnormal patterns. This article describes artifacts, normal rhythms, and normal patterns that are prone to being misinterpreted as abnormal. Artifacts are potentials generated outside the brain. They are divided into physiologic and extraphysiologic. Physiologic artifacts arise from the body and include EMG, eyes, various movements, EKG, pulse, and sweat. Some physiologic artifacts can be useful for interpretation such as EMG and eye movements. Extraphysiologic artifacts arise from outside the body, and in turn can be divided into the environments (electrodes, equipment, and cellphones) and devices within the body (pacemakers and neurostimulators). Normal rhythms can be divided into awake patterns (alpha rhythm and its variants, mu rhythm, lambda waves, posterior slow waves of youth, HV-induced slowing, photic driving, and photomyogenic response) and sleep patterns (POSTS, vertex waves, spindles, K complexes, sleep-related hypersynchrony, and frontal arousal rhythm). Breach can affect both awake and sleep rhythms. Normal variants or variants of uncertain clinical significance include variants that may have been considered abnormal in the early days of EEG but are now considered normal. These include wicket spikes and wicket rhythms (the most common normal pattern overread as epileptiform), small sharp spikes (aka benign epileptiform transients of sleep), rhythmic midtemporal theta of drowsiness (aka psychomotor variant), Cigánek rhythm (aka midline theta), 6 Hz phantom spike-wave, 14 and 6 Hz positive spikes, subclinical rhythmic epileptiform discharges of adults (SREDA), slow-fused transients, occipital spikes of blindness, and temporal slowing of the elderly. Correctly identifying artifacts and normal patterns can help avoid overinterpretation and misdiagnosis. This is an educational review paper addressing a learning objective of the International League Against Epilepsy (ILAE) curriculum.

Imaging characteristics of 4th ventricle subependymoma.

PURPOSE: Subependymomas located within the 4th ventricle are rare, and the literature describing imaging characteristics is sparse. Here, we describe the clinical and radiological characteristics of 29 patients with 4th ventricle subependymoma. METHODS: This is a retrospective multi-center study performed after Institutional Review Board (IRB) approval. Patients diagnosed with suspected 4th ventricle subependymoma were identified. A review of clinical, radiology, and pathology reports along with magnetic resonance imaging (MRI) images was performed. RESULTS: Twenty-nine patients, including 6 females, were identified. Eighteen patients underwent surgery with histopathological confirmation of subependymoma. The median age at diagnosis was 52 years. Median tumor volume for the operative cohort was 9.87 cm3, while for the non-operative cohort, it was 0.96 cm3. Thirteen patients in the operative group exhibited symptoms at diagnosis. For the total cohort, the majority of subependymomas (n = 22) were isointense on T1, hyperintense (n = 22) on T2, and enhanced (n = 24). All tumors were located just below the body of the 4th ventricle, terminating near the level of the obex. Fourteen cases demonstrated extension of tumor into foramen of Magendie or Luschka. CONCLUSION: To the best of our knowledge, this is the largest collection of 4th ventricular subependymomas with imaging findings reported to date. All patients in this cohort had tumors originating between the bottom of the body of the 4th ventricle and the obex. This uniform and specific site of origin aids with imaging diagnosis and may infer possible theories of origin.

Cerebrovascular Reactivity Mapping Using Resting-State Functional MRI in Patients With Gliomas.

BACKGROUND: Recently, a data-driven regression analysis method was developed to utilize the resting-state (rs) blood oxygenation level-dependent signal for cerebrovascular reactivity (CVR) mapping (rs-CVR), which was previously optimized by comparing with the CO2 inhalation-based method in health subjects and patients with neurovascular diseases. PURPOSE: To investigate the agreement of rs-CVR and the CVR mapping with breath-hold MRI (bh-CVR) in patients with gliomas. STUDY TYPE: Retrospective. POPULATION: Twenty-five patients (12 males, 13 females; mean age ± SD, 48 ± 13 years) with gliomas. FIELD STRENGTH/SEQUENCE: Dynamic T2*-weighted gradient-echo echo-planar imaging during a breath-hold paradigm and during the rs on a 3-T scanner. ASSESSMENT: rs-CVR with various frequency ranges and resting-state fluctuation amplitude (RSFA) were assessed. The agreement between each rs-based CVR measurement and bh-CVR was determined by voxel-wise correlation and Dice coefficient in the whole brain, gray matter, and the lesion region of interest (ROI). STATISTICAL TESTS: Voxel-wise Pearson correlation, Dice coefficient, Fisher Z-transformation, repeated-measure analysis of variance and post hoc test with Bonferroni correction, and nonparametric repeated-measure Friedman test and post hoc test with Bonferroni correction were used. Significance was set at P < 0.05. RESULTS: Compared with bh-CVR, the highest correlations were found at the frequency bands of 0.04-0.08 Hz and 0.02-0.04 Hz for rs-CVR in both whole brain and the lesion ROI. RSFA had significantly lower correlations than did rs-CVR of 0.02-0.04 Hz and a wider frequency range (0-0.1164 Hz). Significantly higher correlations and Dice coefficient were found in normal tissues than in the lesion ROI for all three methods. DATA CONCLUSION: The optimal frequency ranges for rs-CVR are determined by comparing with bh-CVR in patients with gliomas. The rs-CVR method outperformed the RSFA. Significantly higher correlation and Dice coefficient between rs- and bh-CVR were found in normal tissue than in the lesion. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Neuropsychological effects in children exposed to anticonvulsant monotherapy during gestation: Phenobarbital, carbamazepine, and phenytoin.

OBJECTIVE: Usage during pregnancy of the antiseizure medication (ASM), phenobarbital (PB), carbamazepine (CBZ), and phenytoin (PHT), has been associated with adverse pregnancy outcomes. While morphological effects on offspring are well-documented, inconsistent findings have been reported on neuropsychological development, possibly due to differences in attention to maternal demographics, and other design characteristics. Herein, we report the results of a carefully designed protocol used to examine the effects of gestational monotherapy with PB, CBZ, or PHT upon children's general mental abilities, when compared to age- and gender- matched children born to unexposed women of similar age, education, and socioeconomic status. METHODS: For each ASM, we selected qualifying cases from children born to PB, CBZ, or PHT monotherapy-exposed and unexposed women. Following the application of inclusion, exclusion, and matching criteria, our sample included 34 PB-exposed, 40 PHT-exposed, and 41 CBZ-exposed children along with matched unexposed children for each drug group. Criteria were applied through examination of maternal medical and educational histories, parental socioeconomic characteristics, and child's age and gender. Each child's physical and neuropsychological characteristics were examined, using standardized protocols. We report on the cognitive performance of the children as assessed by the Wechsler Intelligence Scale for Children - III (WISC-III), the leading measure of mental ability in the U.S. RESULTS: An overall mixed model ANOVA of the adjusted performance of the children across all groups controlling for maternal IQ revealed significant effects on verbal IQ, but not full-scale IQ or performance IQ. In the individual drug and unexposed group comparisons, only reduced verbal and full-scale IQ scores in PB-exposed versus matched unexposed children were found. Comparisons between drug groups revealed a significant reduction in verbal IQ and full-scale IQ in PB-exposed versus PHT-exposed children, but not in other drug-drug comparisons. SIGNIFICANCE: These results demonstrate effects on children's mental ability due to prenatal PB exposure, such that analyses adjusted for maternal IQ scores, revealed reduced verbal mental abilities and reduced full-scale IQ scores when scores in exposed children were compared to scores from children of the same age and sex born to demographically similar, healthy unexposed women. When comparisons were made between drug groups, children exposed prenatally to PB performed significantly worse than prenatally PHT-exposed children, but CBZ-exposed children's scores were not significantly different from those of PB or PHT-exposed groups. In light of shared effects on structural teratogenicity, these findings suggest that use of PB monotherapy for the management of seizures during pregnancy may be associated with increased risk in comparison to PHT when neurobehavioral functioning is considered, and that only PB-exposed children have reduced performance compared to matched controls. Attention to these effects is critical in the developing world where use of these older medications remains predominant, and prudent choices can be made to reduce impact on cognitive development.

Microscale Physiological Events on the Human Cortical Surface.

Despite ongoing advances in our understanding of local single-cellular and network-level activity of neuronal populations in the human brain, extraordinarily little is known about their "intermediate" microscale local circuit dynamics. Here, we utilized ultra-high-density microelectrode arrays and a rare opportunity to perform intracranial recordings across multiple cortical areas in human participants to discover three distinct classes of cortical activity that are not locked to ongoing natural brain rhythmic activity. The first included fast waveforms similar to extracellular single-unit activity. The other two types were discrete events with slower waveform dynamics and were found preferentially in upper cortical layers. These second and third types were also observed in rodents, nonhuman primates, and semi-chronic recordings from humans via laminar and Utah array microelectrodes. The rates of all three events were selectively modulated by auditory and electrical stimuli, pharmacological manipulation, and cold saline application and had small causal co-occurrences. These results suggest that the proper combination of high-resolution microelectrodes and analytic techniques can capture neuronal dynamics that lay between somatic action potentials and aggregate population activity. Understanding intermediate microscale dynamics in relation to single-cell and network dynamics may reveal important details about activity in the full cortical circuit.

Ambulatory EEG Monitoring, Reviewing, and Interpreting.

SUMMARY: This section of this volume of the Journal of Neurophysiology's review of ambulatory EEG (aEEG) is an overview of the uses of the technique, the clinicians who most often use it, and why they use it. It looks at the use of aEEG from the perspectives of the "generalist" and the "specialist" and discusses where they have similar interests and where their interest may diverge. It compares the use of aEEG to the more classic inpatient-based epilepsy monitoring unit service and compares the advantages and disadvantages of the two approaches (aEEG vs. epilepsy monitoring unit). This section then reviews how aEEGs are clinically interpreted based on a best practices approach and how aEEGs can be modified to address recording problems that, until recently, have been approached only in an epilepsy monitoring unit environment. Finally, this section addresses the qualifications necessary for the proper interpretation and reporting of aEEG studies. At the end of this section, there are five case examples using aEEG techniques that demonstrate various aspects covered in this section. These case reports demonstrate not only the utility of aEEG but also show how aEEG recordings can be integrated into the care of complex clinical situations that are frequently encountered not only by the practicing generalists but also by epilepsy specialists who practices out of a comprehensive epilepsy program.

Effect of brain normalization methods on the construction of functional connectomes from resting-state functional MRI in patients with gliomas.

PURPOSE: Spatial normalization is an essential step in resting-state functional MRI connectomic analysis with atlas-based parcellation, but brain lesions can confound it. Cost-function masking (CFM) is a popular compensation approach, but may not benefit modern normalization methods. This study compared three normalization methods with and without CFM and determined their impact on connectomic measures in patients with glioma. METHODS: Fifty patients with glioma were included. T1 -weighted images were normalized using three different methods in SPM12, with and without CFM, which were then overlaid on the ICBM152 template and scored by two neuroradiologists. The Dice coefficient of gray-matter correspondence was also calculated. Normalized resting-state functional MRI data were parcellated using the AAL90 atlas to construct an individual connectivity matrix and calculate connectomic measures. The R2 among the different normalization methods was calculated for the connectivity matrices and connectomic measures. RESULTS: The older method (Original) performed significantly worse than the modern methods (Default and DARTEL; P < .005 in observer ranking). The use of CFM did not significantly improve the normalization results. The Original method had lower correlation with the Default and DARTEL methods (R2 = 0.71-0.74) than Default with DARTEL (R2 = 0.96) in the connectivity matrix. The clustering coefficient appears to be the most, and modularity the least, sensitive connectomic measures to normalization performance. CONCLUSION: The spatial normalization method can have an impact on resting-state functional MRI connectome and connectomic measures derived using atlas-based brain parcellation. In patients with glioma, this study demonstrated that Default and DARTEL performed better than the Original method, and that CFM made no significant difference.

The Calcium Versus Hemorrhage Trial: Developing Diagnostic Criteria for Chronic Intracranial Susceptibility Lesions Using Single-Energy Computed Tomography, Dual-Energy Computed Tomography, and Quantitative Susceptibility Mapping.

PURPOSE: Chronic susceptibility lesions in the brain can be either hemorrhagic (potentially dangerous) or calcific (usually not dangerous) but are difficult to discriminate on routine imaging. We proposed to develop quantitative diagnostic criteria for single-energy computed tomography (SECT), dual-energy computed tomography (DECT), and quantitative susceptibility mapping (QSM) to distinguish hemorrhage from calcium. MATERIALS AND METHODS: Patients with positive susceptibility lesions on routine T2*-weighted magnetic resonance of the brain were recruited into this prospective imaging clinical trial, under institutional review board approval and with informed consent. The SECT, DECT, and QSM images were obtained, the lesions were identified, and the regions of interest were defined, with the mean values recorded. Criteria for quantitative interpretation were developed on the first 50 patients, and then applied to the next 45 patients. Contingency tables, scatter plots, and McNemar test were applied to compare classifiers. RESULTS: There were 95 evaluable patients, divided into a training set of 50 patients (328 lesions) and a validation set of 45 patients (281 lesions). We found the following classifiers to best differentiate hemorrhagic from calcific lesions: less than 68 Hounsfield units for SECT, calcium level of less than 15 mg/mL (material decomposition value) for DECT, and greater than 38 ppb for QSM. There was general mutual agreement among the proposed criteria. The proposed criteria outperformed the current published criteria. CONCLUSIONS: We provide the updated criteria for the classification of chronic positive susceptibility brain lesions as hemorrhagic versus calcific for each major clinically available imaging modality. These proposed criteria have greater internal consistency than the current criteria and should likely replace it as gold standard.

Synthetic generation of DSC-MRI-derived relative CBV maps from DCE MRI of brain tumors.

PURPOSE: Perfusion MRI with gadolinium-based contrast agents is useful for diagnosis and treatment response evaluation of brain tumors. Dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI are two gadolinium-based contrast agent perfusion imaging techniques that provide complementary information about the tumor vasculature. However, each requires a separate administration of a gadolinium-based contrast agent. The purpose of this retrospective study was to determine the feasibility of synthesizing relative cerebral blood volume (rCBV) maps, as computed from DSC MRI, from DCE MRI of brain tumors. METHODS: One hundred nine brain-tumor patients underwent both DCE and DSC MRI. Relative CBV maps were computed from the DSC MRI, and blood plasma volume fraction maps were computed from the DCE MRIs. Conditional generative adversarial networks were developed to synthesize rCBV maps from the DCE MRIs. Tumor-to-white matter ratios were calculated from real rCBV, synthetic rCBV, and plasma volume fraction maps and compared using correlation analysis. Real and synthetic rCBV in white and gray matter regions were also compared. RESULTS: Pearson correlation analysis showed that both the tumor rCBV and tumor-to-white matter ratios in the synthetic and real rCBV maps were strongly correlated (ρ = 0.87, P < .05 and ρ = 0.86, P < .05, respectively). Tumor plasma volume fraction and real rCBV were not strongly correlated (ρ = 0.47). Bland-Altman analysis showed a mean difference between the synthetic and real rCBV tumor-to-white matter ratios of 0.20 with a 95% confidence interval of ±0.47. CONCLUSION: Realistic rCBV maps can be synthesized from DCE MRI and contain quantitative information, enabling robust brain-tumor perfusion imaging of DSC and DCE parameters with a single gadolinium-based contrast agent administration.

Alterations in Functional Connectomics Associated With Neurocognitive Changes Following Glioma Resection.

BACKGROUND: Decline in neurocognitive functioning (NCF) often occurs following brain tumor resection. Functional connectomics have shown how neurologic insults disrupt cerebral networks underlying NCF, though studies involving patients with brain tumors are lacking. OBJECTIVE: To investigate the impact of brain tumor resection upon the connectome and relationships with NCF outcome in the early postoperative period. METHODS: A total of 15 right-handed adults with left perisylvian glioma underwent resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological assessment before and after awake tumor resection. Graph theoretical analysis was applied to rs-fMRI connectivity matrices to calculate network properties. Network properties and NCF measures were compared across the pre- to postoperative periods with matched pairs Wilcoxon signed-rank tests. Associations between pre- to postoperative change in network and NCF measures were determined with Spearman rank-order correlations (ρ). RESULTS: A majority of the sample showed postoperative decline on 1 or more NCF measures. Significant postoperative NCF decline was found across measures of verbal memory, processing speed, executive functioning, receptive language, and a composite index. Regarding connectomic properties, betweenness centrality and assortativity were significantly smaller postoperatively, and reductions in these measures were associated with better NCF outcomes. Significant inverse associations (ρ = -.51 to -.78, all P < .05) were observed between change in language, executive functioning, and learning and memory, and alterations in segregation, centrality, and resilience network properties. CONCLUSION: Decline in NCF was common shortly following resection of glioma involving eloquent brain regions, most frequently in verbal learning/memory and executive functioning. Better postoperative outcomes accompanied reductions in centrality and resilience connectomic measures.

Electroencephalography: basic biophysical and technological aspects important for clinical applications.

Electroencephalography (EEG) is the most commonly used functional investigative method in epilepsy. The goal of this educational review paper is to summarize the most important aspects related to the biophysical phenomena of EEG signal generation and the technical features that a clinician needs to understand in order to read and interpret EEGs. We explain the EEG electrodes and recording arrays, amplifiers, filters, analogue-to-digital conversion and signal display. We describe the advantages and disadvantages of the different montages and the indications for the various types of EEG recordings and provocative maneuvers. We explain how to use topographic maps to estimate the source of the cortical generator.

(TS)2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients.

Glioblastoma (GBM) brain tumor is the most aggressive white matter (WM) invasive cerebral primary neoplasm. Due to its inherently heterogeneous appearance and shape, previous studies pursued either the segmentation precision of the tumors or qualitative analysis of the impact of brain tumors on WM integrity with manual delineation of tumors. This paper aims to develop a comprehensive analytical pipeline, called (TS)2WM, to integrate both the superior performance of brain tumor segmentation and the impact of GBM tumors on the WM integrity via tumor segmentation and tract statistics using the diffusion tensor imaging (DTI) technique. The (TS)2WM consists of three components: (i) A dilated densely connected convolutional network (D2C2N) for automatically segment GBM tumors. (ii) A modified structural connectome processing pipeline to characterize the connectivity pattern of WM bundles. (iii) A multivariate analysis to delineate the local and global associations between different DTI-related measurements and clinical variables on both brain tumors and language-related regions of interest. Among those, the proposed D2C2N model achieves competitive tumor segmentation accuracy compared with many state-of-the-art tumor segmentation methods. Significant differences in various DTI-related measurements at the streamline, weighted network, and binary network levels (e.g., diffusion properties along major fiber bundles) were found in tumor-related, language-related, and hand motor-related brain regions in 62 GBM patients as compared to healthy subjects from the Human Connectome Project.

Central nervous system miliary metastasis in breast cancer: a case series analysis and proposed identification criteria of a rare metastasis subtype.

BACKGROUND: CNS miliary metastasis (MiM) is poorly recognised in breast and other malignancies. Given its rarity, little epidemiologic, radiographic and clinical data are known. Although usually identified on neuroimaging, criteria for radiographic diagnosis do not exist. In this analysis, we establish its presence in breast cancer and identify factors contributing to outcome. METHODS: We identified 546 female patients with brain metastasis from breast cancer between 2000 and 2015. Radiographic criteria were established through review of neuroimages by a senior Neuroradiologist, and defined as: (1) ≥20 lesions per image on ≥2 non-contiguous MRI images or ≥10 lesions per image on ≥2 non-contiguous CT images, and (2) bilateral lesions located in both the supratentorial and infratentorial compartments. RESULTS: Twenty-one MiM cases were identified (3.8%). Number and anatomical distribution of metastases best identified MiM, while lesion size did not. Ten patients were diagnosed with MiM as initial CNS metastasis; 11 developed MiM following known CNS metastasis. Breast cancer subtype did not influence MiM development before or after other CNS metastasis. CONCLUSIONS: This is the first study to propose radiographic criteria for MiM diagnosis. Additional analysis is needed to verify data, but our results may enable a standardised approach for future MiM research.

The role of resting-state functional MRI for clinical preoperative language mapping.

BACKGROUND: Task-based functional MRI (tb-fMRI) is a well-established technique used to identify eloquent cortex, but has limitations, particularly in cognitively impaired patients who cannot perform language paradigms. Resting-state functional MRI (rs-fMRI) is a potential alternative modality for presurgical mapping of language networks that does not require task performance. The purpose of our study is to determine the utility of rs-fMRI for clinical preoperative language mapping when tb-fMRI is limited. METHODS: We retrospectively reviewed 134 brain tumor patients who underwent preoperative fMRI language mapping. rs-fMRI was post-processed with seed-based correlation (SBC) analysis, when language tb-fMRI was limited. Two neuroradiologists reviewed both the tb-fMRI and rs-fMRI results. Six neurosurgeons retrospectively rated the usefulness of rs-fMRI for language mapping in their patients. RESULTS: Of the 134 patients, 49 cases had limited tb-fMRI and rs-fMRI was post-processed. Two neuroradiologists found rs-fMRI beneficial for functional language mapping in 41(84%) and 43 (88%) cases respectively; Cohen's kappa is 0.83, with a 95% confidence interval (0.61, 1.00). The neurosurgeons found rs-fMRI "definitely" useful in 26 cases (60%) and "somewhat" useful in 13 cases (30%) in locating potential eloquent language centers of clinical interest. Six unsuccessful rs-fMRI cases were due to: head motion (2 cases), nonspecific functionality connectivity outside the posterior language network (1 case), and an unknown system instability (3 cases). CONCLUSIONS: This study is a proof of concept that shows SBC rs-fMRI may be a viable alternative for clinical language mapping when tb-fMRI is limited.

Identification of neuronal structures and pathways corresponding to clinical functioning in galactosemia.

Classic galactosemia (OMIM# 230400) is an autosomal recessive disorder due to galactose-1-phosphate uridyltransferase deficiency. Newborn screening and prompt treatment with a galactose-free diet prevent the severe consequences of galactosemia, but clinical outcomes remain suboptimal. Five men and five women with classic galactosemia (mean age = 27.2 ± 5.47 years) received comprehensive neurological and neuropsychological evaluations, electroencephalogram (EEG) and magnetic resonance imaging (MRI). MRI data from nine healthy controls (mean age = 30.22 ± 3.52 years) were used for comparison measures. Galactosemia subjects experienced impaired memory, language processing, visual-motor skills, and increased anxiety. Neurological examinations revealed tremor and dysarthria in six subjects. In addition, there was ataxia in three subjects and six subjects had abnormal gait. Mean full scale IQ was 80.4 ± 17.3. EEG evaluations revealed right-sided abnormalities in five subjects and bilateral abnormalities in one subject. Compared to age- and gender-matched controls, subjects with galactosemia had reduced volume in left cerebellum white matter, bilateral putamen, and left superior temporal sulcus. Galactosemia patients also had lower fractional anisotropy and higher radial diffusivity values in the dorsal and ventral language networks compared to the controls. Furthermore, there were significant correlations between neuropsychological test results and the T1 volume and diffusivity scalars. Our findings help to identify anatomic correlates to motor control, learning and memory, and language in subjects with galactosemia. The results from this preliminary assessment may provide insights into the pathophysiology of this inborn error of metabolism.