scholarly journals Viability of Preictal High-Frequency Oscillation Rates as a Biomarker for Seizure Prediction

2021 ◽  
Vol 14 ◽  
Author(s):  
Jared M. Scott ◽  
Stephen V. Gliske ◽  
Levin Kuhlmann ◽  
William C. Stacey
Keyword(s):  
High Frequency ◽  
Statistical Tests ◽  
Temporal Trends ◽  
Area Under The Curve ◽  
Receiver Operating Curve ◽  
High Frequency Oscillation ◽  
Seizure Prediction ◽  
Potential Biomarker ◽  
Preictal State ◽  
Better Than

Motivation: There is an ongoing search for definitive and reliable biomarkers to forecast or predict imminent seizure onset, but to date most research has been limited to EEG with sampling rates <1,000 Hz. High-frequency oscillations (HFOs) have gained acceptance as an indicator of epileptic tissue, but few have investigated the temporal properties of HFOs or their potential role as a predictor in seizure prediction. Here we evaluate time-varying trends in preictal HFO rates as a potential biomarker of seizure prediction.Methods: HFOs were identified for all interictal and preictal periods with a validated automated detector in 27 patients who underwent intracranial EEG monitoring. We used LASSO logistic regression with several features of the HFO rate to distinguish preictal from interictal periods in each individual. We then tested these models with held-out data and evaluated their performance with the area-under-the-curve (AUC) of their receiver-operating curve (ROC). Finally, we assessed the significance of these results using non-parametric statistical tests.Results: There was variability in the ability of HFOs to discern preictal from interictal states across our cohort. We identified a subset of 10 patients in whom the presence of the preictal state could be successfully predicted better than chance. For some of these individuals, average AUC in the held-out data reached higher than 0.80, which suggests that HFO rates can significantly differentiate preictal and interictal periods for certain patients.Significance: These findings show that temporal trends in HFO rate can predict the preictal state better than random chance in some individuals. Such promising results indicate that future prediction efforts would benefit from the inclusion of high-frequency information in their predictive models and technological architecture.

scholarly journals A potential biomarker for treatment stratification in psychosis: evaluation of an [18F] FDOPA PET imaging approach

2020 ◽  
Author(s):  
Mattia Veronese ◽  
Barbara Santangelo ◽  
Sameer Jauhar ◽  
Enrico D’Ambrosio ◽  
Arsime Demjaha ◽  
...  
Keyword(s):  
Pet Imaging ◽  
Area Under The Curve ◽  
Total Sample ◽  
Receiver Operating Curve ◽  
Support Vector ◽  
Antipsychotic Treatment ◽  
Good Test ◽  
Simplified Approach ◽  
Potential Biomarker ◽  
Non Linear

Abstract [18F]FDOPA PET imaging has shown dopaminergic function indexed as Kicer differs between antipsychotic treatment responders and non-responders. However, the theragnostic potential of this biomarker to identify non-responders has yet to be evaluated. In view of this, we aimed to evaluate this as a theragnostic test using linear and non-linear machine-learning (i.e., Bernoulli, support vector, random forest and Gaussian processes) analyses and to develop and evaluate a simplified approach, standardised uptake value ratio (SUVRc). Both [18F]FDOPA PET approaches had good test-rest reproducibility across striatal regions (Kicer ICC: 0.68–0.94, SUVRc ICC: 0.76–0.91). Both our linear and non-linear classification models showed good predictive power to distinguish responders from non-responders (receiver operating curve area under the curve for region-of-interest approach: Kicer = 0.80, SUVRc = 0.79; for voxel-wise approach using a linear support vector machine: 0.88) and similar sensitivity for identifying treatment non-responders with 100% specificity (Kicer: ~50%, SUVRc: 40–60%). Although the findings were replicated in two independent datasets, given the total sample size (n = 84) and single setting, they warrant testing in other samples and settings. Preliminary economic analysis of [18F]FDOPA PET to fast-track treatment-resistant patients with schizophrenia to clozapine indicated a potential healthcare cost saving of ~£3400 (equivalent to $4232 USD) per patient. These findings indicate [18F]FDOPA PET dopamine imaging has potential as biomarker to guide treatment choice.

scholarly journals Identifying and measuring the severity of somatic symptom disorder using the Self-reported Somatic Symptom Scale-China (SSS-CN): a research protocol for a diagnostic study

BMJ Open ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. e024290
Author(s):  
Meng Jiang ◽  
Weituo Zhang ◽  
Xuan Su ◽  
Chuang Gao ◽  
Bingxu Chen ◽  
...  
Keyword(s):  
Somatic Symptom ◽  
Statistical Tests ◽  
Area Under The Curve ◽  
The Self ◽  
Self Report ◽  
Receiver Operating Curve ◽  
Diagnostic Study ◽  
Severity Assessment ◽  
Somatic Symptom Disorder ◽  
Symptom Scale

IntroductionThe detection rate of somatic symptom disorder (SSD) in general hospitals is unsatisfactory. Self-report questionnaires that assess both somatic symptoms and psychological characteristics will improve the process of screening for SSD. The Somatic Symptom Scale-China (SSS-CN) questionnaire has been developed to meet this urgent clinical demand. The aim of this research is to validate the self-reported SSS-CN as a timely and practical instrument that can be used to identify SSD and to assess the severity of this disorder.Methods and analysisAt least 852 patients without organic disease but presenting physical discomfort will be recruited at a general hospital. Each patient will undergo aDiagnostic and Statistical Manual of Mental Disorders, 5th Edition(DSM-5)-guided physician diagnosis, including disease identification and severity assessment, as the reference standard. This research will compare the diagnostic performance of the SSS-CN for SSD, the Patient Health Questionnaire-15 (PHQ-15) and other SSD-related questionnaires. Statistical tests to measure the area under the curve (AUC) and volume under the surface of the receiver operating curve will be used to assess the accuracy of the SSD identification and the severity assessment, respectively. In addition to this standard diagnostic study, we will conduct follow-up investigations to explore the effectiveness of the SSS-CN in monitoring treatment effects.Ethics and disseminationEthical approval was obtained from the Renji Hospital Human Research Ethics Committee, approval number 2 015 016. The findings of this study will be disseminated via peer-reviewed journals and presented at international conferences.Trial registration numberNCT03513185.

scholarly journals Scoring of Growth of Unruptured Intracranial Aneurysms

2020 ◽  
Vol 9 (10) ◽  
pp. 3339
Author(s):  
Seppo Juvela
Keyword(s):  
Intracranial Aneurysms ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Receiver Operating Curve ◽  
Female Sex ◽  
Unruptured Intracranial Aneurysms ◽  
Long Term Follow Up ◽  
Better Than

The purpose was to obtain a reliable scoring for growth of unruptured intracranial aneurysms (UIAs) in a long-term follow-up study from variables known at baseline and to compare it with the ELAPSS (Earlier subarachnoid hemorrhage, Location of the aneurysm, Age > 60 years, Population, Size of the aneurysm, and Shape of the aneurysm) score obtained from an individual-based meta-analysis. The series consists of 87 patients with 111 UIAs and 1669 person-years of follow-up between aneurysm size measurements (median follow-up time per patient 21.7, range 1.2 to 51.0 years). These were initially diagnosed between 1956 and 1978, when UIAs were not treated in our country. ELAPSS scores at baseline did not differ between those with and those without aneurysm growth. The area under the curve (AUC) for the receiver operating curve (ROC) of the ELAPSS score for predicting long-term growth was fail (0.474, 95% CI 0.345–0.603), and the optimal cut-off point was obtained at ≥7 vs. <7 points for sensitivity (0.829) and specificity (0.217). In the present series UIA growth was best predicted by female sex (4 points), smoking at baseline (3 points), and age <40 years (2 points). The AUC for the ROC of the new scoring was fair (0.662, 95% CI 0.546–0.779), which was significantly better than that of ELAPSS score (p < 0.05). The optimal cut-off point was obtained at ≥4 vs. <4 points for sensitivity (0.971) and specificity (0.304). A new simple scoring consisting of only female sex, cigarette smoking and age <40 years predicted growth of an intracranial aneurysm in long-term follow-up, significantly better than the ELAPSS score.

scholarly journals Temporal changes of neocortical high-frequency oscillations in epilepsy

2013 ◽  
Vol 110 (5) ◽  
pp. 1167-1179 ◽  
Author(s):  
Allison Pearce ◽  
Drausin Wulsin ◽  
Justin A. Blanco ◽  
Abba Krieger ◽  
Brian Litt ◽  
...  
Keyword(s):  
High Frequency ◽  
Statistical Tests ◽  
Relative Rate ◽  
Temporal Analysis ◽  
Temporal Changes ◽  
Patient Specific ◽  
Mixed Frequency ◽  
Potential Biomarker ◽  
Before And After ◽  
Intracranial Electrodes

High-frequency (100–500 Hz) oscillations (HFOs) recorded from intracranial electrodes are a potential biomarker for epileptogenic brain. HFOs are commonly categorized as ripples (100–250 Hz) or fast ripples (250–500 Hz), and a third class of mixed frequency events has also been identified. We hypothesize that temporal changes in HFOs may identify periods of increased the likelihood of seizure onset. HFOs (86,151) from five patients with neocortical epilepsy implanted with hybrid (micro + macro) intracranial electrodes were detected using a previously validated automated algorithm run over all channels of each patient's entire recording. HFOs were characterized by extracting quantitative morphologic features and divided into four time epochs (interictal, preictal, ictal, and postictal) and three HFO clusters (ripples, fast ripples, and mixed events). We used supervised classification and nonparametric statistical tests to explore quantitative changes in HFO features before, during, and after seizures. We also analyzed temporal changes in the rates and proportions of events from each HFO cluster during these periods. We observed patient-specific changes in HFO morphology linked to fluctuation in the relative rates of ripples, fast ripples, and mixed frequency events. These changes in relative rate occurred in pre- and postictal periods up to thirty min before and after seizures. We also found evidence that the distribution of HFOs during these different time periods varied greatly between individual patients. These results suggest that temporal analysis of HFO features has potential for designing custom seizure prediction algorithms and for exploring the relationship between HFOs and seizure generation.

scholarly journals Phase-amplitude coupling between infraslow and high-frequency activities well discriminates between the preictal and interictal states

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroaki Hashimoto ◽  
Hui Ming Khoo ◽  
Takufumi Yanagisawa ◽  
Naoki Tani ◽  
Satoru Oshino ◽  
...  
Keyword(s):  
High Frequency ◽  
Focal Epilepsy ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Discrimination Performance ◽  
Epileptic Seizures ◽  
Electrode Placement ◽  
Seizure Onset ◽  
Phase Amplitude ◽  
Preictal State

AbstractInfraslow activity (ISA) and high-frequency activity (HFA) are key biomarkers for studying epileptic seizures. We aimed to elucidate the relationship between ISA and HFA around seizure onset. We enrolled seven patients with drug-resistant focal epilepsy who underwent intracranial electrode placement. We comparatively analyzed the ISA, HFA, and ISA-HFA phase-amplitude coupling (PAC) in the seizure onset zone (SOZ) or non-SOZ (nSOZ) in the interictal, preictal, and ictal states. We recorded 15 seizures. HFA and ISA were larger in the ictal states than in the interictal or preictal state. During seizures, the HFA and ISA of the SOZ were larger and occurred earlier than those of nSOZ. In the preictal state, the ISA-HFA PAC of the SOZ was larger than that of the interictal state, and it began increasing at approximately 87 s before the seizure onset. The receiver-operating characteristic curve revealed that the ISA-HFA PAC of the SOZ showed the highest discrimination performance in the preictal and interictal states, with an area under the curve of 0.926. This study demonstrated the novel insight that ISA-HFA PAC increases before the onset of seizures. Our findings indicate that ISA-HFA PAC could be a useful biomarker for discriminating between the preictal and interictal states.

scholarly journals Phase-Amplitude Coupling between Infraslow and High-Frequency Activities is a Potential Biomarker for Seizure Prediction

2020 ◽  
Author(s):  
Hiroaki Hashimoto ◽  
Hui Ming Khoo ◽  
Takufumi Yanagisawa ◽  
Naoki Tani ◽  
Satoru Oshino ◽  
...  
Keyword(s):  
High Frequency ◽  
Characteristic Curve ◽  
Case Series ◽  
Discrimination Performance ◽  
Electrode Placement ◽  
Seizure Prediction ◽  
Seizure Onset ◽  
Seizure Onset Zone ◽  
Potential Biomarker ◽  
Phase Amplitude

IMPORTANCEThis research describes a method to accurately predict the onset of epileptic seizures; this will help treat patients timely, prevent future seizures, and improve outcomes.OBJECTIVEWe aimed to assess whether the phase-amplitude coupling (PAC) between infraslow activities (ISA) and high-frequency activities (HFA) increases before seizure onset.DESIGN AND SETTINGThis retrospective, single-center case series included patients admitted to the neurosurgery department at Osaka University Hospital in Suita, Osaka, from July 2018 to July 2019.PARTICIPANTSWe enrolled seven patients with drug-resistant focal epilepsy who underwent intracranial electrode placement as part of a presurgical invasive electroencephalography study.MAIN OUTCOMES AND MEASURESWe comparatively analyzed the ISA, HFA, and ISA-HFA PAC in the seizure onset zone (SOZ) or non-SOZ (nSOZ) in the interictal, preictal, and ictal states.RESULTSWe recorded 15 seizures in seven patients [1 female (14%); mean (SD) age = 26 (12) years; age range, 15-47 years]. HFA and ISA were larger in the ictal states than in the interictal and preictal states. During seizures, the HFA and ISA of the SOZ were larger and earlier than those of nSOZ. In the preictal states, the ISA-HFA PAC was larger than that of the interictal states, and it began increasing at 93 seconds before the seizure onset (95% confidence interval: −116 – −71 s). There were no differences in the values and time of ISA-HFA PAC between both zones. Our phase-based analysis revealed differences between the SOZ- and nSOZ-PAC. In SOZ, the HFA amplitudes were tuned at the trough of the ISA oscillations, and in nSOZ, the HFA amplitudes were tuned at the peak of these oscillations. The receiver-operating characteristic curve showed that the ISA-HFA PAC of the SOZ showed the highest discrimination performance in the preictal and interictal states, with an area under the curve (AUC) of 0.926. However, ISA-HFA PAC was not suitable to differentiate between SOZ and nSOZ (interictal AUC = 0.555, preictal AUC = 0.691, and ictal AUC = 0.646).CONCLUSION AND RELEVANCEThis study demonstrated the novel insight that ISA-HFA PAC increases before the onset of seizures, regardless of the seizure onset zone. Our findings indicate that ISA-HFA PAC is a potential biomarker for predicting the onset of seizures and may be valuable to physicians who routinely treat epileptic patients.Key PointsQuestionIs phase-amplitude coupling (PAC) between infraslow activities (ISA) and high-frequency activities (HFA) a useful biomarker for seizure prediction?FindingsIn this case series study on 15 focal-onset seizures in seven epileptic patients who underwent intracranial electrode placement, we found that a PAC of the ISA phase and HFA amplitude achieved significantly higher values in preictal states than in the interictal states, and ISA-HFA PAC of the seizure onset zone (SOZ) began increasing at 93 seconds before seizure onset (SO), while both HFA and ISA increased after SO. The receiver-operating characteristic curve showed that the ISA-HFA PAC of the SOZ showed the highest discrimination performance in the preictal and interictal states, with an area under the curve of 0.926.MeaningThis study demonstrates that ISA-HFA PAC can differentiate between the preictal and interictal states of a seizure, indicating that it is a potential marker for seizure prediction.

High-Frequency Oscillation and Chronic Lung Disease in Very Low Birth Weight Infants

PEDIATRICS ◽  
2001 ◽  
Vol 108 (1) ◽  
pp. 212-214
Author(s):  
J. P. Shenai; ◽  
P. Rimensberger; ◽  
U. Thome ◽  
F. Pohlandt; ◽  
P. Rimensberger
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Lung Disease ◽  
Chronic Lung Disease ◽  
High Frequency ◽  
Very Low Birth Weight ◽  
High Frequency Oscillation ◽  
Frequency Oscillation ◽  
Low Birth Weight Infants

scholarly journals Sphingolipid Analysis Indicate Lactosylceramide as a Potential Biomarker of Inflammatory Bowel Disease in Children

Biomolecules ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1083
Author(s):  
Aleksandra Filimoniuk ◽  
Agnieszka Blachnio-Zabielska ◽  
Monika Imierska ◽  
Dariusz Marek Lebensztejn ◽  
Urszula Daniluk
Keyword(s):  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
High Performance ◽  
Area Under The Curve ◽  
Study Groups ◽  
Diagnostic Value ◽  
Serum Samples ◽  
Specificity And Sensitivity ◽  
Potential Biomarker ◽  
Inflammatory Bowel

An altered ceramide composition in patients with inflammatory bowel disease (IBD) has been reported recently. The aim of this study was to evaluate the concentrations of sphingolipids in the serum of treatment-naive children with newly diagnosed IBD and to determine the diagnostic value of the tested lipids in pediatric IBD. The concentrations of sphingolipids in serum samples were evaluated using a quantitative method, an ultra-high-performance liquid chromatography-tandem mass spectrometry in children with Crohn’s disease (CD) (n=34), ulcerative colitis (UC) (n = 39), and controls (Ctr) (n = 24). Among the study groups, the most significant differences in concentrations were noted for C16:0-LacCer, especially in children with CD compared to Ctr or even to UC. Additionally, the relevant increase in C20:0-Cer and C18:1-Cer concentrations were detected in both IBD groups compared to Ctr. The enhanced C24:0-Cer level was observed only in UC, while C18:0-Cer only in the CD group. The highest area under the curve (AUC), specificity, and sensitivity were determined for C16:0-LacCer in CD diagnosis. Our results suggest that the serum LacC16-Cer may be a potential biomarker that distinguishes children with IBD from healthy controls and differentiates IBD subtypes. In addition, C20:0-Cer and C18:0-Cer levels also seem to be closely connected with IBD.

scholarly journals Modeling and Optimization of Microwave-Based Bio-Jet Fuel from Coconut Oil: Investigation of Response Surface Methodology (RSM) and Artificial Neural Network Methodology (ANN)

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 295
Author(s):  
Mei Yin Ong ◽  
Saifuddin Nomanbhay ◽  
Fitranto Kusumo ◽  
Raja Mohamad Hafriz Raja Shahruzzaman ◽  
Abd Halim Shamsuddin
Keyword(s):  
Statistical Tests ◽  
Coconut Oil ◽  
Jet Fuel ◽  
Molar Ratio ◽  
Ann Model ◽  
Fuel Production ◽  
Turbine Engine ◽  
Renewable Fuel ◽  
American Society ◽  
Better Than

In this study, coconut oils have been transesterified with ethanol using microwave technology. The product obtained (biodiesel and FAEE) was then fractional distillated under vacuum to collect bio-kerosene or bio-jet fuel, which is a renewable fuel to operate a gas turbine engine. This process was modeled using RSM and ANN for optimization purposes. The developed models were proved to be reliable and accurate through different statistical tests and the results showed that ANN modeling was better than RSM. Based on the study, the optimum bio-jet fuel production yield of 74.45 wt% could be achieved with an ethanol–oil molar ratio of 9.25:1 under microwave irradiation with a power of 163.69 W for 12.66 min. This predicted value was obtained from the ANN model that has been optimized with ACO. Besides that, the sensitivity analysis indicated that microwave power offers a dominant impact on the results, followed by the reaction time and lastly ethanol–oil molar ratio. The properties of the bio-jet fuel obtained in this work was also measured and compared with American Society for Testing and Materials (ASTM) D1655 standard.

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