Displaying publications 1 - 20 of 66 in total

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  1. Wahab S, Md Rani SA, Sharis Othman S
    Asia Pac Psychiatry, 2013 Apr;5 Suppl 1:90-4.
    PMID: 23857843 DOI: 10.1111/appy.12050
    Neurosyphilis may presents with a range of psychiatric symptoms. This report illustrates a case of neurosyphilis in a man who presented with psychosis and cognitive dysfunction. Clinical findings and investigations done in the present case showed positive results for syphilis. Reduction of symptoms was noted after treatment with antibiotic. This case further highlights the importance of having high index of suspicion for neurosyphilis in patients presenting with psychiatric symptoms.
    Matched MeSH terms: Neuroimaging
  2. Idris Z, Kandasamy R, Reza F, Abdullah JM
    Asian J Neurosurg, 2014 Jul-Sep;9(3):144-52.
    PMID: 25685205 DOI: 10.4103/1793-5482.142734
    BACKGROUND: Magnetoencephalography (MEG) is a method of functional neuroimaging. The concomitant use of MEG and electrocorticography has been found to be useful in elucidating neural oscillation and network, and to localize epileptogenic zone and functional cortex. We describe our early experience using MEG in neurosurgical patients, emphasizing on its impact on patient management as well as the enrichment of our knowledge in neurosciences.
    MATERIALS AND METHODS: A total of 10 subjects were included; five patients had intraaxial tumors, one with an extraaxial tumor and brain compression, two with arteriovenous malformations, one with cerebral peduncle hemorrhage and one with sensorimotor cortical dysplasia. All patients underwent evoked and spontaneous MEG recordings. MEG data was processed at band-pass filtering frequency of between 0.1 and 300 Hz with a sampling rate of 1 kHz. MEG source localization was performed using either overdetermined equivalent current dipoles or underdetermined inversed solution. Neuromag collection of events software was used to study brain network and epileptogenic zone. The studied data were analyzed for neural oscillation in three patients; brain network and clinical manifestation in five patients; and for the location of epileptogenic zone and eloquent cortex in two patients.
    RESULTS: We elucidated neural oscillation in three patients. One demonstrated oscillatory phenomenon on stimulation of the motor-cortex during awake surgery, and two had improvement in neural oscillatory parameters after surgery. Brain networks corresponding to clinico-anatomical relationships were depicted in five patients, and two networks were illustrated here. Finally, we demonstrated epilepsy cases in which MEG data was found to be useful in localizing the epileptogenic zones and functional cortices.
    CONCLUSION: The application of MEG while enhancing our knowledge in neurosciences also has a useful role in epilepsy and awake surgery.
    KEYWORDS: Awake craniotomy; brain network; epilepsy; magnetoencephalography; neural oscillation
    Matched MeSH terms: Functional Neuroimaging
  3. Kartikasalwah A, Lh N
    Biomed Imaging Interv J, 2010 Jan-Mar;6(1):e6.
    PMID: 21611066 MyJurnal DOI: 10.2349/biij.6.1.e6
    Leigh syndrome is a progressive neurodegenerative disorder of childhood. The symmetrical necrotic lesions in the basal ganglia and/or brainstem which appear as hyperintense lesions on T2-weighted MRI is characteristic and one of the essential diagnostic criteria. Recognising this MR imaging pattern in a child with neurological problems should prompt the clinician to investigate for Leigh syndrome. We present here two cases of Leigh syndrome due to different biochemical/genetic defects, and discuss the subtle differences in their MR neuroimaging features.
    Matched MeSH terms: Neuroimaging
  4. Schnakers C, Hirsch M, Noé E, Llorens R, Lejeune N, Veeramuthu V, et al.
    Brain Sci, 2020 Dec 02;10(12).
    PMID: 33276451 DOI: 10.3390/brainsci10120930
    Covert cognition in patients with disorders of consciousness represents a real diagnostic conundrum for clinicians. In this meta-analysis, our main objective was to identify clinical and demographic variables that are more likely to be associated with responding to an active paradigm. Among 2018 citations found on PubMed, 60 observational studies were found relevant. Based on the QUADAS-2, 49 studies were considered. Data from 25 publications were extracted and included in the meta-analysis. Most of these studies used electrophysiology as well as counting tasks or mental imagery. According to our statistical analysis, patients clinically diagnosed as being in a vegetative state and in a minimally conscious state minus (MCS-) show similar likelihood in responding to active paradigm and responders are most likely suffering from a traumatic brain injury. In the future, multi-centric studies should be performed in order to increase sample size, with similar methodologies and include structural and functional neuroimaging in order to identify cerebral markers related to such a challenging diagnosis.
    Matched MeSH terms: Functional Neuroimaging
  5. Verma RK, Pandey M, Chawla P, Choudhury H, Mayuren J, Bhattamisra SK, et al.
    PMID: 33982657 DOI: 10.2174/1871527320666210512014505
    BACKGROUND: The complication of Alzheimer's disease (AD) has made the development of its therapeutic a challenging task. Even after decades of research, we have achieved no more than a few years of symptomatic relief. The inability to diagnose the disease early is the foremost hurdle behind its treatment. Several studies have aimed to identify potential biomarkers that can be detected in body fluids (CSF, blood, urine, etc) or assessed by neuroimaging (i.e., PET and MRI). However, the clinical implementation of these biomarkers is incomplete as they cannot be validated.

    METHOD: To overcome the limitation, the use of artificial intelligence along with technical tools has been extensively investigated for AD diagnosis. For developing a promising artificial intelligence strategy that can diagnose AD early, it is critical to supervise neuropsychological outcomes and imaging-based readouts with a proper clinical review.

    CONCLUSION: Profound knowledge, a large data pool, and detailed investigations are required for the successful implementation of this tool. This review will enlighten various aspects of early diagnosis of AD using artificial intelligence.

    Matched MeSH terms: Neuroimaging
  6. Eshkoor SA, Hamid TA, Mun CY, Ng CK
    Clin Interv Aging, 2015;10:687-93.
    PMID: 25914527 DOI: 10.2147/CIA.S73922
    Mild cognitive impairment (MCI) is a common condition in the elderly. It is characterized by deterioration of memory, attention, and cognitive function that is beyond what is expected based on age and educational level. MCI does not interfere significantly with individuals' daily activities. It can act as a transitional level of evolving dementia with a range of conversion of 10%-15% per year. Thus, it is crucial to protect older people against MCI and developing dementia. The preventive interventions and appropriate treatments should improve cognitive performance, and retard or prevent progressive deficits. The avoidance of toxins, reduction of stress, prevention of somatic diseases, implementation of mental and physical exercises, as well as the use of dietary compounds like antioxidants and supplements can be protective against MCI. The modification of risk factors such as stopping smoking, as well as the treatment of deficiency in vitamins and hormones by correcting behaviors and lifestyle, can prevent cognitive decline in the elderly. The progressive increase in the growth rate of the elderly population can enhance the rate of MCI all over the world. There is no exact cure for MCI and dementia; therefore, further studies are needed in the future to determine causes of MCI and risk factors of progression from MCI to dementia. This will help to find better ways for prevention and treatment of cognitive impairment worldwide.
    Matched MeSH terms: Neuroimaging
  7. Law ZK, Appleton JP, Bath PM, Sprigg N
    Clin Med (Lond), 2017 Apr;17(2):166-172.
    PMID: 28365631 DOI: 10.7861/clinmedicine.17-2-166
    Managing acute intracerebral haemorrhage is a challenging task for physicians. Evidence shows that outcome can be improved with admission to an acute stroke unit and active care, including urgent reversal of anticoagulant effects and, potentially, intensive blood pressure reduction. Nevertheless, many management issues remain controversial, including the use of haemostatic therapy, selection of patients for neurosurgery and neurocritical care, the extent of investigations for underlying causes and the benefit versus risk of restarting antithrombotic therapy after an episode of intracerebral haemorrhage.
    Matched MeSH terms: Neuroimaging
  8. Mumtaz W, Vuong PL, Malik AS, Rashid RBA
    Cogn Neurodyn, 2018 Apr;12(2):141-156.
    PMID: 29564024 DOI: 10.1007/s11571-017-9465-x
    The screening test for alcohol use disorder (AUD) patients has been of subjective nature and could be misleading in particular cases such as a misreporting the actual quantity of alcohol intake. Although the neuroimaging modality such as electroencephalography (EEG) has shown promising research results in achieving objectivity during the screening and diagnosis of AUD patients. However, the translation of these findings for clinical applications has been largely understudied and hence less clear. This study advocates the use of EEG as a diagnostic and screening tool for AUD patients that may help the clinicians during clinical decision making. In this context, a comprehensive review on EEG-based methods is provided including related electrophysiological techniques reported in the literature. More specifically, the EEG abnormalities associated with the conditions of AUD patients are summarized. The aim is to explore the potentials of objective techniques involving quantities/features derived from resting EEG, event-related potentials or event-related oscillations data.
    Matched MeSH terms: Neuroimaging
  9. Bhat S, Acharya UR, Hagiwara Y, Dadmehr N, Adeli H
    Comput Biol Med, 2018 11 01;102:234-241.
    PMID: 30253869 DOI: 10.1016/j.compbiomed.2018.09.008
    Parkinson's disease (PD) is a neurodegenerative disease of the central nervous system caused due to the loss of dopaminergic neurons. It is classified under movement disorder as patients with PD present with tremor, rigidity, postural changes, and a decrease in spontaneous movements. Comorbidities including anxiety, depression, fatigue, and sleep disorders are observed prior to the diagnosis of PD. Gene mutations, exposure to toxic substances, and aging are considered as the causative factors of PD even though its genesis is unknown. This paper reviews PD etiologies, progression, and in particular measurable indicators of PD such as neuroimaging and electrophysiology modalities. In addition to gene therapy, neuroprotective, pharmacological, and neural transplantation treatments, researchers are actively aiming at identifying biological markers of PD with the goal of early diagnosis. Neuroimaging modalities used together with advanced machine learning techniques offer a promising path for the early detection and intervention in PD patients.
    Matched MeSH terms: Neuroimaging
  10. Cheng J, Wang H, Wei S, Mei J, Liu F, Zhang G
    Comput Biol Med, 2024 Mar;170:108000.
    PMID: 38232453 DOI: 10.1016/j.compbiomed.2024.108000
    Alzheimer's disease (AD) is a neurodegenerative disease characterized by various pathological changes. Utilizing multimodal data from Fluorodeoxyglucose positron emission tomography(FDG-PET) and Magnetic Resonance Imaging(MRI) of the brain can offer comprehensive information about the lesions from different perspectives and improve the accuracy of prediction. However, there are significant differences in the feature space of multimodal data. Commonly, the simple concatenation of multimodal features can cause the model to struggle in distinguishing and utilizing the complementary information between different modalities, thus affecting the accuracy of predictions. Therefore, we propose an AD prediction model based on de-correlation constraint and multi-modal feature interaction. This model consists of the following three parts: (1) The feature extractor employs residual connections and attention mechanisms to capture distinctive lesion features from FDG-PET and MRI data within their respective modalities. (2) The de-correlation constraint function enhances the model's capacity to extract complementary information from different modalities by reducing the feature similarity between them. (3) The mutual attention feature fusion module interacts with the features within and between modalities to enhance the modal-specific features and adaptively adjust the weights of these features based on information from other modalities. The experimental results on ADNI database demonstrate that the proposed model achieves a prediction accuracy of 86.79% for AD, MCI and NC, which is higher than the existing multi-modal AD prediction models.
    Matched MeSH terms: Neuroimaging/methods
  11. Kamaluddin NA, Tai E, Wan Hitam WH, Ibrahim M, Samsudin AHZ
    Cureus, 2019 Jun 05;11(6):e4834.
    PMID: 31404358 DOI: 10.7759/cureus.4834
    Optic perineuritis (OPN) involvement in demyelinating disease is rarely encountered. To our knowledge, this is the first reported case of bilateral OPN associated with neuromyelitis optica spectrum disorder (NMOSD). We present a case of a healthy young gentleman who presented with OPN, initially presumed to have a young stroke but later diagnosed to be NMOSD. Early neuroimaging is essential to help distinguish optic neuritis (ON), and prolonged treatment of systemic immunosuppression is the mainstay of treatment.
    Matched MeSH terms: Neuroimaging
  12. Chew C, Wan Hitam WH, Ahmad Tajudin LS
    Cureus, 2021 Mar 31;13(3):e14200.
    PMID: 33936906 DOI: 10.7759/cureus.14200
    Leptomeningeal carcinomatosis (LC) and optic nerve metastasis are uncommon occurrences in breast cancer. We report a rare case of LC with optic nerve infiltration secondary to breast cancer. A 45-year-old lady who was a known case of treated right breast carcinoma six years ago presented with a blurring of vision in both eyes, floaters, and diplopia for one month. She also had recurrent attacks of seizure-like episodes, headache, and vomiting. Examination revealed high blood pressure with tachycardia. Her right eye visual acuity was counting fingers at two feet and 6/36 in the left eye. She had right abducens nerve palsy. Fundoscopy showed bilateral optic disc swelling with pre-retinal, flame-shaped haemorrhages and macular oedema. CT scan of brain and orbit was normal. She was admitted for further investigations. While in the ward, her vision deteriorated further. Her visual acuity in both eyes was at the level of no perception to light. She also developed bilateral abducens nerve palsy and right facial nerve palsy. Subsequently, she started having bilateral hearing loss. There were few episodes of fluctuations in conscious awareness. MRI brain showed mild hydrocephalus. Both optic nerves were thickened and enhanced on T1-weighted and post-gadolinium. Lumbar puncture was performed. There was high opening pressure. Cerebrospinal fluid cytology showed the presence of malignant cells. Family members opted for palliative care in view of poor prognosis. Unfortunately, she succumbed after a month's stay in hospital. Diagnosis of LC and optic nerve infiltration presents a formidable challenge to clinicians especially in the early stages where neuroimaging appears normal and lumbar puncture has high false negatives. Multiple high-volume taps are advised if clinical suspicion of LC is high.
    Matched MeSH terms: Neuroimaging
  13. Zhang L, Hussain Z, Ren Z
    Curr Drug Targets, 2019 Feb 14.
    PMID: 30767742 DOI: 10.2174/1389450120666190214141626
    BACKGROUND: Normal pressure hydrocephalus (NPH) is a critical brain disorder in which excess cerebrospinal fluid (CSF) is accumulated in the brain's ventricles causing damage or disruption of the brain tissues. Amongst various signs and symptoms, difficulty in walking, blurred speech, impaired decision making and critical thinking, and loss of bladder and bowl control are considered the hallmark features of NPH.

    OBJECTIVE: The current review was aimed to present a comprehensive overview and critical appraisal of majorly employed neuroimaging techniques for rational diagnosis and effective monitoring of effectiveness of employed therapeutic intervention for NPH. Moreover, a critical overview of recent developments and utilization of pharmacological agents for treatment of hydrocephalus has also been appraised.

    RESULTS: Considering the complications associated with the shunt-based surgical operations, consistent monitoring of shunting via neuroimaging techniques hold greater clinical significance. Despite having extensive applicability of MRI and CT scan, these conventional neuroimaging techniques are associated with misdiagnosis or several health risks to patients. Recent advances in MRI (i.e., Sagittal-MRI, coronal-MRI, Time-SLIP (time-spatial-labeling-inversion-pulse), PC-MRI and diffusion-tensor-imaging (DTI)) have shown promising applicability in diagnosis of NPH. Having associated with several adverse effects with surgical interventions, non-invasive approaches (pharmacological agents) have earned greater interest of scientists, medical professional, and healthcare providers. Amongst pharmacological agents, diuretics, isosorbide, osmotic agents, carbonic anhydrase inhibitors, glucocorticoids, NSAIDs, digoxin, and gold-198 have been employed for management of NPH and prevention of secondary sensory/intellectual complications.

    CONCLUSION: Employment of rational diagnostic tool and therapeutic modalities avoids misleading diagnosis and sophisticated management of hydrocephalus by efficient reduction of cerebrospinal fluid (CSF) production, reduction of fibrotic and inflammatory cascades secondary to meningitis and hemorrhage, and protection of brain from further deterioration.

    Matched MeSH terms: Neuroimaging
  14. Zhang L, Hussain Z, Ren Z
    Curr Drug Targets, 2019;20(10):1041-1057.
    PMID: 30767741 DOI: 10.2174/1389450120666190214121342
    BACKGROUND: Normal pressure hydrocephalus (NPH) is a critical brain disorder in which excess Cerebrospinal Fluid (CSF) is accumulated in the brain's ventricles causing damage or disruption of the brain tissues. Amongst various signs and symptoms, difficulty in walking, slurred speech, impaired decision making and critical thinking, and loss of bladder and bowl control are considered the hallmark features of NPH.

    OBJECTIVE: The current review was aimed to present a comprehensive overview and critical appraisal of majorly employed neuroimaging techniques for rational diagnosis and effective monitoring of the effectiveness of the employed therapeutic intervention for NPH. Moreover, a critical overview of recent developments and utilization of pharmacological agents for the treatment of hydrocephalus has also been appraised.

    RESULTS: Considering the complications associated with the shunt-based surgical operations, consistent monitoring of shunting via neuroimaging techniques hold greater clinical significance. Despite having extensive applicability of MRI and CT scan, these conventional neuroimaging techniques are associated with misdiagnosis or several health risks to patients. Recent advances in MRI (i.e., Sagittal-MRI, coronal-MRI, Time-SLIP (time-spatial-labeling-inversion-pulse), PC-MRI and diffusion-tensor-imaging (DTI)) have shown promising applicability in the diagnosis of NPH. Having associated with several adverse effects with surgical interventions, non-invasive approaches (pharmacological agents) have earned greater interest of scientists, medical professional, and healthcare providers. Amongst pharmacological agents, diuretics, isosorbide, osmotic agents, carbonic anhydrase inhibitors, glucocorticoids, NSAIDs, digoxin, and gold-198 have been employed for the management of NPH and prevention of secondary sensory/intellectual complications.

    CONCLUSION: Employment of rational diagnostic tool and therapeutic modalities avoids misleading diagnosis and sophisticated management of hydrocephalus by efficient reduction of Cerebrospinal Fluid (CSF) production, reduction of fibrotic and inflammatory cascades secondary to meningitis and hemorrhage, and protection of brain from further deterioration.

    Matched MeSH terms: Neuroimaging
  15. Blair GW, Appleton JP, Flaherty K, Doubal F, Sprigg N, Dooley R, et al.
    EClinicalMedicine, 2019 04 24;11:34-43.
    PMID: 31317131 DOI: 10.1016/j.eclinm.2019.04.001
    Background: Lacunar stroke, a frequent clinical manifestation of small vessel disease (SVD), differs pathologically from other ischaemic stroke subtypes and has no specific long-term secondary prevention. Licenced drugs, isosorbide mononitrate (ISMN) and cilostazol, have relevant actions to prevent SVD progression.

    Methods: We recruited independent patients with clinically confirmed lacunar ischaemic stroke without cognitive impairment to a prospective randomised clinical trial, LACunar Intervention-1 (LACI-1). We randomised patients using a central web-based system, 1:1:1:1 with minimisation, to masked ISMN 25 mg bd, cilostazol 100 mg bd, both ISMN and cilostazol started immediately, or both with start delayed. We escalated doses to target over two weeks, sustained for eight weeks. Primary outcome was the proportion achieving target dose. Secondary outcomes included symptoms, safety (haemorrhage, recurrent vascular events), cognition, haematology, vascular function, and neuroimaging. LACI-1 was powered (80%, alpha 0.05) to detect 35% (90% versus 55%) difference between the proportion reaching target dose on one versus both drugs at 55 patients. Registration ISRCTN12580546.

    Findings: LACI-1 enrolled 57 participants between March 2016 and August 2017: 18 (32%) females, mean age 66 (SD 11, range 40-85) years, onset-randomisation 203 (range 6-920) days. Most achieved full (64%) or over half (87%) dose, with no difference between cilostazol vs ISMN, single vs dual drugs. Headache and palpitations increased initially then declined similarly with dual versus single drugs. There was no between-group difference in BP, pulse-wave velocity, haemoglobin or platelet function, but pulse rate was higher (mean difference, MD, 6.4, 95%CI 1.2-11.7, p = 0.02), platelet count higher (MD 35.7, 95%CI 2.8, 68.7, p = 0.03) and white matter hyperintensities reduced more (Chi-square p = 0.007) with cilostazol versus no cilostazol.

    Interpretation: Cilostazol and ISMN are well tolerated when the dose is escalated, without safety concerns, in patients with lacunar stroke. Larger trials with longer term follow-up are justified.

    Funding: Alzheimer's Society (AS-PG-14-033).

    Matched MeSH terms: Neuroimaging
  16. Khoo CS, Kim SE, Lee BI, Shin KJ, Ha SY, Park J, et al.
    Eur Neurol, 2020;83(1):56-64.
    PMID: 32320976 DOI: 10.1159/000506591
    INTRODUCTION: Seizures as acute stroke mimics are a diagnostic challenge.

    OBJECTIVE: The aim of the study was to characterize the perfusion patterns on perfusion computed tomography (PCT) in patients with seizures masquerading as acute stroke.

    METHODS: We conducted a study on patients with acute seizures as stroke mimics. The inclusion criteria for this study were patients (1) initially presenting with stroke-like symptoms but finally diagnosed to have seizures and (2) with PCT performed within 72 h of seizures. The PCT of seizure patients (n = 27) was compared with that of revascularized stroke patients (n = 20) as the control group.

    RESULTS: Among the 27 patients with seizures as stroke mimics, 70.4% (n = 19) showed characteristic PCT findings compared with the revascularized stroke patients, which were as follows: (1) multi-territorial cortical hyperperfusion {(73.7% [14/19] vs. 0% [0/20], p = 0.002), sensitivity of 73.7%, negative predictive value (NPV) of 80%}, (2) involvement of the ipsilateral thalamus {(57.9% [11/19] vs. 0% [0/20], p = 0.007), sensitivity of 57.9%, NPV of 71.4%}, and (3) reduced perfusion time {(84.2% [16/19] vs. 0% [0/20], p = 0.001), sensitivity of 84.2%, NPV of 87%}. These 3 findings had 100% specificity and positive predictive value in predicting patients with acute seizures in comparison with reperfused stroke patients. Older age was strongly associated with abnormal perfusion changes (p = 0.038), with a mean age of 66.8 ± 14.5 years versus 49.2 ± 27.4 years (in seizure patients with normal perfusion scan).

    CONCLUSIONS: PCT is a reliable tool to differentiate acute seizures from acute stroke in the emergency setting.

    Matched MeSH terms: Neuroimaging/methods*
  17. Sobri M., Mezlina W.Z., Subramaniam, J.H.
    MyJurnal
    Dural arteriovenous malformation (DAVM) is relatively rare and defined as abnormal connections or shunts between the arterial and the venous side of vascular tree located within the dura mater. Spontaneous closures of DAVM are rare and have been scarcely reported. This case report will describe the neuroimaging findings and classification of DAVM. A 50 year old lady presented with headache. Neuroimaging showed prominent serpinginous flow-void structures, cerebral angiogram confirmed the presence of DAVM at the occipital region. She had defaulted treatment and follow-up for 3 years. On second admission, she had a cerebral angiogram which showed normal findings with no evidence of fistulas or malformation. She was discharged well. Causes of spontaneous closure of DAVM are discussed.
    Matched MeSH terms: Neuroimaging
  18. Lee DA, Park KM, Kim HC, Khoo CS, Lee BI, Kim SE
    J Clin Neurophysiol, 2023 May 01;40(4):364-370.
    PMID: 34510091 DOI: 10.1097/WNP.0000000000000894
    PURPOSE: The aims of this study were to identify (1) the spectrum of ictal-interictal continuum (IIC) using the two dimensions of 2HELPS2B score and background suppression and (2) the response to subsequent anti-seizure drugs depends on the spectrum of IIC.

    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.

    Matched MeSH terms: Neuroimaging
  19. Kaplan E, Chan WY, Altinsoy HB, Baygin M, Barua PD, Chakraborty S, et al.
    J Digit Imaging, 2023 Dec;36(6):2441-2460.
    PMID: 37537514 DOI: 10.1007/s10278-023-00889-8
    Detecting neurological abnormalities such as brain tumors and Alzheimer's disease (AD) using magnetic resonance imaging (MRI) images is an important research topic in the literature. Numerous machine learning models have been used to detect brain abnormalities accurately. This study addresses the problem of detecting neurological abnormalities in MRI. The motivation behind this problem lies in the need for accurate and efficient methods to assist neurologists in the diagnosis of these disorders. In addition, many deep learning techniques have been applied to MRI to develop accurate brain abnormality detection models, but these networks have high time complexity. Hence, a novel hand-modeled feature-based learning network is presented to reduce the time complexity and obtain high classification performance. The model proposed in this work uses a new feature generation architecture named pyramid and fixed-size patch (PFP). The main aim of the proposed PFP structure is to attain high classification performance using essential feature extractors with both multilevel and local features. Furthermore, the PFP feature extractor generates low- and high-level features using a handcrafted extractor. To obtain the high discriminative feature extraction ability of the PFP, we have used histogram-oriented gradients (HOG); hence, it is named PFP-HOG. Furthermore, the iterative Chi2 (IChi2) is utilized to choose the clinically significant features. Finally, the k-nearest neighbors (kNN) with tenfold cross-validation is used for automated classification. Four MRI neurological databases (AD dataset, brain tumor dataset 1, brain tumor dataset 2, and merged dataset) have been utilized to develop our model. PFP-HOG and IChi2-based models attained 100%, 94.98%, 98.19%, and 97.80% using the AD dataset, brain tumor dataset1, brain tumor dataset 2, and merged brain MRI dataset, respectively. These findings not only provide an accurate and robust classification of various neurological disorders using MRI but also hold the potential to assist neurologists in validating manual MRI brain abnormality screening.
    Matched MeSH terms: Neuroimaging
  20. Sweeti, Joshi D, Panigrahi BK, Anand S, Santhosh J
    J Healthc Eng, 2018;2018:9213707.
    PMID: 29808111 DOI: 10.1155/2018/9213707
    This paper presents a classification system to classify the cognitive load corresponding to targets and distractors present in opposite visual hemifields. The approach includes the study of EEG (electroencephalogram) signal features acquired in a spatial attention task. The process comprises of EEG feature selection based on the feature distribution, followed by the stepwise discriminant analysis- (SDA-) based channel selection. Repeated measure analysis of variance (rANOVA) is applied to test the statistical significance of the selected features. Classifiers are developed and compared using the selected features to classify the target and distractor present in visual hemifields. The results provide a maximum classification accuracy of 87.2% and 86.1% and an average classification accuracy of 76.5 ± 4% and 76.2 ± 5.3% over the thirteen subjects corresponding to the two task conditions. These correlates present a step towards building a feature-based neurofeedback system for visual attention.
    Matched MeSH terms: Neuroimaging
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