DATABASES REVIEWED: Science Direct, Pubmed, Embase via Ovid databases, and Cochrane library.
METHODS: This review following the guidelines of PRISMA, systematically and independently examined papers published up to March 2021 which fulfilled the predetermined criteria. PROSPERO Registration (CRD42020222334).
RESULTS: A total of 15 studies were included (MRI = 4, SPECT = 1, resting state fMRI = 4, task-based fMRI = 5, task-based fMRI + MRI = 1). Significant changes in the gray matter volume, cortical folding, blood flow, and connectivity were seen at different brain regions involved in vestibular, visual, emotion, and motor processing.
CONCLUSION: There is a multisensory dimension to the impairment resulting in chronic compensatory changes in PPPD that is evident by the significant alterations in multiple networks involved in maintaining balance. These changes observed offer some explanation for the symptoms that a PPPD patient may experience.Systematic Review Registration: This study is registered with PROSPERO (CRD42020222334).
METHODS: The study prospectively enrolled 62 patients with IIC on EEG. The diagnosis of nonconvulsive status epilepticus was attempted with Salzburg criteria as well as clinical and neuroimaging data. IICs were dichotomized into patients with nonconvulsive status epilepticus and coma-IIC. The 2HELPS2B score was evaluated as the original proposal. The suppression ratio was analyzed with Persyst software.
RESULTS: Forty-seven cases (75.8%) were nonconvulsive status epilepticus-IIC and 15 cases (24.2%) were coma-IIC. Multivariate analysis revealed that the 2HELPS2B score was the only significant variable dichotomizing the spectrum of IIC (odds ratio, 3.0; 95% confidence interval, 1.06-8.6; P = 0.03 for nonconvulsive status epilepticus-IIC). In addition, the suppression ratio was significantly negatively correlated with 2HELPS2B scores (Spearman coefficient = -0.37, P = 0.004 for left hemisphere and Spearman coefficient = -0.3, P = 0.02 for right hemisphere). Furthermore, patients with higher 2HELPS2B score (74% [14/19] in ≥2 points vs. 44% [14/32] in <2 points, P = 0.03 by χ 2 test) and lower suppression ratio (62% [23/37] in ≤2.18 vs. 35% [6/17] in >2.18, P = 0.06 by χ 2 test) seemed to be more responsive to subsequent anti-seizure drug.
CONCLUSIONS: The 2HELPS2B score and background suppression can be used to distinguish the spectrum of IIC and thereby predict the response to subsequent anti-seizure drug.
OBJECTIVE: Our study aimed to examine and contrast the clinical and radiological characteristics of TDL, high-grade gliomas (HGG) and primary CNS lymphoma (CNSL).
METHOD: This was a retrospective review of 66 patients (23 TDL, 31 HGG and 12 CNSL). Clinical and laboratory data were obtained. MRI brain at presentation were analyzed by two independent, blinded neuroradiologists.
RESULTS: Patients with TDLs were younger and predominantly female. Sensorimotor deficits and ataxia were more common amongst TDL whereas headaches and altered mental status were associated with HGG and CNSL. Compared to HGG and CNSL, MRI characteristics supporting TDL included relatively smaller size, lack of or mild mass effect, incomplete peripheral rim enhancement, absence of central enhancement or restricted diffusion, lack of cortical involvement, and presence of remote white matter lesions on the index scan. Paradoxically, some TDLs may present atypically or radiologically mimic CNS lymphomas.
CONCLUSION: Careful evaluation of clinical and radiological features helps in differentiating TDLs at first presentation from CNS neoplasms.
METHODS: In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes.
RESULTS: Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature.
CONCLUSIONS: The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.
PATIENT CONCERNS: A 37-year-old construction worker was brought in by his wife and coworker due to a sudden loss of consciousness while resting after completing his work.
DIAGNOSES: Due to challenges faced during the coronavirus disease 2019 pandemic, as well as language barriers, a detailed history from the coworker who witnessed the patient's altered sensorium was not available. He was initially suspected of having encephalitis and brainstem stroke. However, subsequent investigations revealed multiorgan dysfunction with a normal brain computed tomography and cerebral computed tomography angiogram. In view of the multiple risk factors for heat stroke, pupillary constriction, and urine color suggestive of rhabdomyolysis, a diagnosis of heat stroke was made.
INTERVENTIONS: Despite delayed diagnosis, the patient's multiorgan dysfunction recovered within days with basic supportive care.
OUTCOMES: There were no noticeable complications on follow-up 14 months later.
LESSONS: Heat stroke can be easily confused with other neurological pathologies, particularly if no history can be obtained from the patient or informant. When approaching a comatose patient, we propose that serum creatinine kinase should be considered as an initial biochemical screening test.