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Objective To find and validate the optimal combination of criteria that define interictal epileptiform EEG discharges (IEDs). Our target was a specificity over 95%, to avoid over-reading in clinical EEG. Methods We constructed 63 combinations of the six criteria from the operational definition of IEDs, recently issued in the EEG-glossary of the International Federation of Clinical Neurophysiology (IFCN). The diagnostic gold standard was derived from video-EEG recordings. In a testing EEG dataset from 100 patients, we selected the best performing combinations of criteria and then we validated them in an independent dataset from 70 patients. We compared their performance with subjective, expert-scorings and we determined inter-rater agreement (IRA). Results Without using criteria, the specificity of expert-scorings was lower than the pre-defined threshold (86%). The best performing combination of criteria was the following: waves with spiky morphology, followed by a slow-afterwave and voltage map suggesting a source in the brain. In the validation dataset this achieved a specificity of 97% and a sensitivity of 89%. IRA was substantial. Conclusions The optimized set of criteria for defining IEDs has high accuracy and IRA. Significance Using these criteria will contribute to decreasing over-reading of EEG and avoid misdiagnosis of epilepsy.

Objective: To evaluate the diagnostic performance of artificial intelligence (AI)–based algorithms for identifying the presence of interictal epileptiform discharges (IEDs) in routine (20-min) electroencephalography (EEG) recordings. Methods: We evaluated two approaches: a fully automated one and a hybrid approach, where three human raters applied an operational IED definition to assess the automated detections grouped into clusters by the algorithms. We used three previously developed AI algorithms: Encevis, SpikeNet, and Persyst. The diagnostic gold standard (epilepsy or not) was derived from video-EEG recordings of patients' habitual clinical episodes. We compared the algorithms with the gold standard at the recording level (epileptic or not). The independent validation data set (not used for training) consisted of 20-min EEG recordings containing sharp transients (epileptiform or not) from 60 patients: 30 with epilepsy (with a total of 340 IEDs) and 30 with nonepileptic paroxysmal events. We compared sensitivity, specificity, overall accuracy, and the review time-burden of the fully automated and hybrid approaches, with the conventional visual assessment of the whole recordings, based solely on unrestricted expert opinion. Results: For all three AI algorithms, the specificity of the fully automated approach was too low for clinical implementation (16.67%; 63.33%; 3.33%), despite the high sensitivity (96.67%; 66.67%; 100.00%). Using the hybrid approach significantly increased the specificity (93.33%; 96.67%; 96.67%) with good sensitivity (93.33%; 56.67%; 76.67%). The overall accuracy of the hybrid methods (93.33%; 76.67%; 86.67%) was similar to the conventional visual assessment of the whole recordings (83.33%; 95% confidence interval [CI]: 71.48–91.70%; p >.5), yet the time-burden of review was significantly lower (p

ObjectiveTo validate relative source power (RSP) imaging of extratemporal interictal epileptiform discharges (IEDs).MethodsThe accuracy of RSP was validated in a cohort of patients with extratemporal focal epilepsy and a confined epileptogenic lesion (ResultsThirty-three of 41 consecutive patients (80%) had IED averages suitable for analysis. While the peak negativity in voltage maps localized above the epileptogenic lesion only in 18 cases, RSP-maps matched in 29 cases (88%, p < 0.0026). Source localization showed a median distance of 9.8 mm from the lesion. Source-regions with 20 mm radius included 98% of all source-to-lesion distances. In the 21 surgical cases, outcome showed a sensitivity of 82.35% and specificity of 50% without significant differences between the three source imaging methods.ConclusionsRSP-maps provide a rapid, intuitive and more accurate source estimation than voltage maps. At sublobar level, RSP localizes with an accuracy similar to conventional methods and results of previous studies.SignificanceThe definition of a source region with 20 mm radius helps in guiding further exploration in extratemporal focal epilepsy. Objective: To validate relative source power (RSP) imaging of extratemporal interictal epileptiform discharges (IEDs). Methods: The accuracy of RSP was validated in a cohort of patients with extratemporal focal epilepsy and a confined epileptogenic lesion (3) using distance to the lesion, concordance with resected area and postoperative outcome. Performance was compared with three conventional methods: voltage maps, equivalent current dipole and a distributed source model. Results: Thirty-three of 41 consecutive patients (80%) had IED averages suitable for analysis. While the peak negativity in voltage maps localized above the epileptogenic lesion only in 18 cases, RSP-maps matched in 29 cases (88%, p < 0.0026). Source localization showed a median distance of 9.8 mm from the lesion. Source-regions with 20 mm radius included 98% of all source-to-lesion distances. In the 21 surgical cases, outcome showed a sensitivity of 82.35% and specificity of 50% without significant differences between the three source imaging methods. Conclusions: RSP-maps provide a rapid, intuitive and more accurate source estimation than voltage maps. At sublobar level, RSP localizes with an accuracy similar to conventional methods and results of previous studies. Significance: The definition of a source region with 20 mm radius helps in guiding further exploration in extratemporal focal epilepsy.

OBJECTIVE: To characterize in detail the electroclinical features of typical absence seizures and elucidate whether EEG or semiology features, alone or in combination, can predict long-term therapeutic outcome. METHODS: We analysed video-EEG recordings from 213 typical absence seizures from 61 patients with idiopathic generalized epilepsy. We extracted semiological features, in addition to hallmark manifestations (motor/behavioural arrest, non-responsiveness), their location, timing and frequency. We evaluated the duration and frequency of generalized spike-wave discharges and the presence of polyspikes. We used a supervised machine-learning approach (random forest) to search for classifier features for long-term therapeutic outcome (>one year). RESULTS: Besides the hallmark manifestations, additional semiological features were identified in 87% of patients (75% of seizures). The most common additional semiological features were automatisms and eye blinking (observed in 45% and 41.5% of seizures, respectively). Automatisms were associated with longer seizure duration, and oral automatisms occurred earlier compared to limb automatisms (4.03 vs. 6.19 seconds; p=0.005). The mean duration of the ictal spike-wave discharges was nine seconds, and the median frequency was 3 Hz. Polyspikes occurred in 46 seizures (21.6%), in 19 patients (31%). Median follow-up was five years, and 73% of the patients were seizure-free at the end of the follow-up. None of the semiological features, alone or in combination, were predictors of therapeutic outcome. The only significant classifier was the presence of polyspikes, predicting a non-seizure-free outcome with an accuracy of 73% (95% CI: 70-77%), positive predictive value of 92% (95% CI: 84-98%) and negative predictive value of 60% (95% CI: 39-81%). SIGNIFICANCE: Semiological features, in addition to behavioural arrest and non-responsiveness, are common in typical absence seizures, but they do not predict long-term therapeutic outcome. The presence of polyspikes has a high positive predictive value for unfavourable therapeutic outcome, and their presence should therefore be included when reporting EEGs in patients with typical absence seizures.

ObjectiveTo define and validate criteria for accurate identification of EEG interictal epileptiform discharges (IEDs) using (1) the 6 sensor space criteria proposed by the International Federation of Clinical Neurophysiology (IFCN) and (2) a novel source space method. Criteria yielding high specificity are needed because EEG over-reading is a common cause of epilepsy misdiagnosis.MethodsSeven raters reviewed EEG sharp transients from 100 patients with and without epilepsy (diagnosed definitively by video-EEG recording of habitual events). Raters reviewed the transients, randomized, and classified them as epileptiform or nonepileptiform in 3 separate rounds: in 2, EEG was reviewed in sensor space (scoring the presence/absence of each IFCN criterion for each transient or classifying unrestricted by criteria [expert scoring]); in the other, review and classification were performed in source space.ResultsCutoff values of 4 and 5 criteria in sensor space and analysis in source space provided high accuracy (91%, 88%, and 90%, respectively), similar to expert scoring (92%). Two methods had specificity exceeding the desired threshold of 95%: using 5 IFCN criteria as cutoff and analysis in source space (both 95.65%); the sensitivity of these methods was 81.48% and 85.19%, respectively.ConclusionsThe presence of 5 IFCN criteria in sensor space and analysis in source space are optimal for clinical implementation. By extracting these objective features, diagnostic accuracy similar to expert scorings is achieved.Classification of evidenceThis study provides Class III evidence that IFCN criteria in sensor space and analysis in source space have high specificity (>95%) and sensitivity (81%–85%) for identification of IEDs.

Objective The operational definition of interictal epileptiform discharges (IEDs) of the International Federation of Clinical Neurophysiology (IFCN) described six morphological criteria. Our objective was to assess the impact of pattern-repetition in the EEG-recording, on the diagnostic accuracy of using the IFCN criteria. For clinical implementation, specificity over 95% was set as target. Methods Interictal EEG-recordings of 20-minutes, containing sharp-transients, from 60 patients (30 with epilepsy and 30 with non-epileptic paroxysmal events) were evaluated by three experts, who first marked IEDs solely based on expert opinion, and then, independently from the first session evaluated the presence of the IFCN criteria for each sharp-transient. The gold standard was derived from long-term video-EEG recordings of the patientś habitual paroxysmal episodes. Results Presence of at least one discharge fulfilling five criteria provided a specificity of 100% (sensitivity: 70%). For discharges fulfilling fewer criteria, a higher number of discharges was needed to keep the specificity over 95% (5 discharges, when only 3 criteria were fulfilled). A sequential combination of these sets of criteria and thresholds provided a specificity of 97% and sensitivity of 80%. Conclusions Pattern-repetition and IED morphology influence diagnostic accuracy. Significance Systematic application of these criteria will improve quality of clinical EEG interpretation.

Background/aim The aim of this study was to assess the nutritional status and risk factors for malnutrition in Behcet’s disease (BD) and neuro-Behcet’s disease (NBD) patients. Materials and methods Medical recordings of 74 patients with BD without neurological involvement (BDWoNI), 72 patients with NBD, and 50 patients with other diseases (carpal tunnel syndrome or lumbar discopathy) were analyzed retrospectively. The serum analyses were performed in the inactive period of disease. Chronic malnutrition was defined as low levels of serum albumin (

PURPOSE: Triphasic waves (TWs) have been observed in the EEG recorded in patients with various types of encephalopathy, yet their genesis and significance is still debated. The aim of this study was to elucidate the localization of the cortical generators of TWs using EEG source imaging.METHODS: In 20 consecutive patients who had encephalopathy with TWs, EEG source imaging of the first negative and the positive phases of the TW was performed. Three different approaches were used: equivalent current dipoles, a distributed source model, and a recently described spatial filtration method for visualizing EEG in source space.RESULTS: Equivalent current dipole models failed to provide valid solutions. The distributed source model and the spatial filtration method suggested that TWs were generated by large, bilateral cortical networks, invariably involving the anterior frontal and the temporo-polar areas.CONCLUSIONS: Source imaging localized TWs to anterior frontal and temporo-frontal structures. Involvement of these regions is consistent with the typical pathophysiological changes of altered consciousness and cognitive changes observed in patients with TW encephalopathy.

Introduction Rapid and accessible methods for diagnosing diabetic polyneuropathy (DPN) have been developed, but not validated, in large cohorts of people with diabetes. Methods The performance of a point-of-care device (POCD) was studied in 168 patients with type 2 diabetes, estimating the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) compared with conventional sural nerve conduction studies (NCS). Results A POCD amplitude limit of 6 µV increased the sensitivity (96%) and NPV (98%), but decreased the specificity (71%) and PPV (54%) compared with the 4-µV limit, which had values of 78%, 92%, 89%, and 71%, respectively. POCD on both legs showed better performance than on 1 leg. POCD amplitudes and conduction velocities correlated significantly with conventional sural NCS, but POCD values were underestimated compared with NCS. Discussion The POCD may be used as a suitable screening tool for detection of DPN. Patients with abnormal and borderline results should undergo conventional NCS. Muscle Nerve 59:187-193, 2019.

Objective Neuro-Behcet's disease (NBD) is a rare manifestation of Behcet's disease (BD) and may cause severe disability. The aim of this study was to evaluate the treatment response in patients with NBD and to investigate the parameters that may influence the prognosis of the disease in patients with severe to mild-moderate disability. Methods The files of 60 patients admitted to our outpatient clinic for NBD between January 2007 and June 2014 were retrospectively reviewed. We compared the BD duration, time to NBD, NBD type and course, clinical findings of BD, functional neurological system involvement, localization of lesions on brain MRI, and all the medications between the severe and mild-moderate disability groups. Results The mean time to the onset of NBD was significantly longer (17.8±4.6 years) and the mean age was significantly higher (50.25±9.1 years) in patients with severe disability than in those with mild-moderate disability (7.5±8.0 years and 37.5±10.9 years; p=0.01 and p=0.03, respectively). Moreover, hemispheric involvement was significantly associated with severe disability (p=0.006). No difference was found with regard toother investigated parameters between the groups. Conclusion We believe that severe neurological disability may be associated with older age at the onset of NBD or longer time to NBD and hemispheric lesions on brain MRI. However, our results should be cautiously evaluated with further research.

Objective To validate an artificial intelligence-based computer algorithm for detection of epileptiform EEG discharges (EDs) and subsequent identification of patients with epilepsy. Methods We developed an algorithm for automatic detection of EDs, based on a novel deep learning method that requires a low amount of labeled EEG data for training. Detected EDs are automatically grouped into clusters, consisting of the same type of EDs, for rapid visual inspection. We validated the algorithm on an independent dataset of 100 patients with sharp transients in their EEG recordings (54 with epilepsy and 46 with non-epileptic paroxysmal events). The diagnostic gold standard was derived from the video-EEG recordings of the patients’ habitual events. Results The algorithm had a sensitivity of 89% for identifying EEGs with EDs recorded from patients with epilepsy, a specificity of 70%, and an overall accuracy of 80%. Conclusions Automated detection of EDs using an artificial intelligence-based computer algorithm had a high sensitivity. Human (expert) supervision is still necessary for confirming the clusters of detected EDs and for describing clinical correlations. Further studies on different patient populations will be needed to confirm our results. Significance The automated algorithm we describe here is a useful tool, assisting neurophysiologist in rapid assessment of EEG recordings.

Objectives: This study aims to report the outcomes of patients with Behcet’s disease (BD) with cerebral venous thrombosis (CVT) due to BD compared to patients with CVT due to other causes and to discuss the treatment options. Patients and methods: Files of 47 patients admitted to our outpatient clinic for CVT between January 2007 and November 2014 were retrospectively reviewed. Patients were divided into two groups; group 1 included 21 CVT patients with BD (9 males, 12 females; mean age 47±12 years; range 27 to 69 years) and group 2 included 26 CVT patients without BD (11 males, 15 females; mean age 45±16 years; range 25 to 79 years). We collected data for diagnosis for BD and CVT, duration of all medications, functional system involvement, baseline Expanded Disability Status Scale scores, modified Rankin Scale scores at follow-up, and localizations of lesions in brain magnetic resonance imaging and magnetic resonance venography. Results: Mean follow-up duration was four years in group 1 and two years in group 2. There was no significant difference between the groups regarding age, sex, neurological symptoms/findings and baseline Expanded Disability Status Scale scores. Localizations of occluded sinus in group 1 and group 2 were similar. For acute CVT, patients were treated with intravenous high dose prednisolone in group 1 and with anticoagulant in group 2. Follow-up modified Rankin Scale score was 0 in both groups. Conclusion: Our study revealed similar clinical and radiological findings in CVT patients with or without BD. Although medications used for treatment were different between the groups, treatment responses were good in both groups. Treatment with prednisolone may be sufficient and anticoagulation therapy may not be necessary for acute CVT attacks in BD.

PURPOSE The sural nerve can be examined by either surface electrode recording or near-nerve technique (NNT) for electrodiagnosis of polyneuropathy. This study compared the sensitivity of these two methods and correlated nerve conduction studies to "The Utah Early Neuropathy Scale" (UENS) and HbA1c levels. METHODS In 29 diabetic patients, 55 sural nerves were examined with both antidromic surface recording and orthodromic NNT. The sensitivities were compared with chi-square statistics. Nerve conduction study parameters were correlated with UENS and HbA1c levels using regression analysis. RESULTS More often absent responses were seen with surface electrodes than NNT (15 vs. 0) (P < 0.001). A higher number of normal nerves were found with surface recording (27) than with NNT (15) (P < 0.001). The decrease in sensory nerve action potential amplitude correlated significantly to total UENS scores and UENS subscores for both surface recordings and NNT. However, decrease in conduction velocity and sensory nerve action potential duration correlated to UENS scores and subscores more often for NNT than for surface recording. Similarly, there was significant correlation between HbA1c levels and sensory nerve action potential amplitude and duration for NNT, but not for surface electrode recordings. CONCLUSIONS Near-nerve technique is recommended for better and more sensitive electrodiagnosis of polyneuropathy, and clinical scoring with UENS is of importance for diabetic neuropathy diagnosis.

Objective The electrodiagnosis of polyneuropathy (PNP) may benefit from examination using near-nerve needle technique (NNT) and from inclusion of distal nerves. This study compared the diagnostic utility of distal nerve conduction studies (NCS) and NNT recording. Methods Bilateral NNT and surface recording of the sural nerve and surface recording of the dorsal sural and medial plantar nerves were prospectively done in 91 patients with clinically suspected PNP. Distal NCS were additionally done in 37 healthy controls. Diagnostic reference standard was the final clinical diagnosis retrieved from the patients medical records after 1–4 years. Results The clinical follow-up diagnosis confirmed PNP in 68 patients. Equally high sensitivities of the dorsal sural (72%), medial plantar (75%), and sural nerve with NNT recording (77%) were seen, while the sensitivity of conventional surface recording of the sural nerve was lower (60%). Sural NCS with both NNT and surface recording and dorsal sural NCS showed high specificities (85–95%) and positive predictive values (94–98%), while a lower specificity was seen for the medial plantar nerve (68%). Conclusion NCS of distal nerves, especially the dorsal sural nerve, have high diagnostic power equalling sural NNT recording. Significance The electrodiagnostic evaluation of patients with suspected PNP benefits from NCS of distal nerves.

Background Presence of Epileptiform Discharges (ED) in EEG recordings are highly associated with an epilepsy diagnosis. The International Federation of Clinical Neurophysiology (IFCN) suggested 6 criteria in EEG sensor-space, so that presence of at least 4 of them defines a waveform as ED. The aim of our study to assess inter-rater agreement (IRA) and accuracy of identifying spikes in sensor space (using the IFCN criteria at different thresholds) and in source space. Methods EEG samples from 100 consecutive patients with epilepsy and non-epileptic paroxysmal events were reviewed separately in sensor-space and source-space, in different, randomized order, by 7 raters, who scored the presence/absence of each IFCN-criterion in sensor-space, and presence/absence of EDs in source-space. EDs were defined in sensor-space using different thresholds (2–6 criteria) and without counting criteria. Accuracy was determined for each rater and for the majority decisions for each sample. Material and results IRA was moderate both in sensor space and in source space (k: 0.49–0.60). In sensor-space, the highest accuracy (91%) and sensitivity (96%) was achieved using a threshold of 4 criteria. However, this gave a specificity that was lower than acceptable for EEG (85%). Using a threshold of 5 criteria in sensor-space specificity of 96% was achieved, at a sensitivity of 83% and accuracy of 89%. Results in source-space were identical to using the threshold of 5 criteria in sensor-space. Conclusions Using a threshold of 5 IFCN-criteria in sensor-space, and using source-space yields a high specificity and acceptable sensitivity for identifying EDs.

Objectives To compare the diagnostic utilities of distal surface electrode recording of dorsal sural and medial plantar nerves and near-nerve technique (NNT) and conventional surface recording of sural nerve. Methods Ninety-one patients referred for electrodiagnostic examination of polyneuropathy (PNP) were included. Bilateral nerve conduction studies (NCS) of the sural nerve with NNT and surface recording, and of the distal nerves with surface recording were done in all patients. Results were compared to 37 age-matched healthy subjects. The final clinical diagnosis retrieved from the patients’ medical records as diagnostic reference standard showed PNP in 68 patients (PNP+) and 20 patients did not have PNP (PNP−). Results The sensitivities of the dorsal sural (68%) and medial plantar (70%) nerves were similar to that of NNT recording of the sural nerve (74%), while the sensitivity of surface recording of the sural nerve was lower (55%). High specificities (93–98%) were seen for sural NCS with both NNT and surface recording and for the dorsal sural nerve, while the specificity for medial plantar nerve was low (76%). Discussion In concert with previous reports, distal nerves have higher sensitivity than conventional sural nerve. Additionally, the sensitivity of distal nerves was found to be similar to examination of sural nerve with NNT. Conclusion NCS of the distal nerves, especially the dorsal sural nerve, have a high diagnostic power at an identical level of that of needle recording of the sural nerve. Significance Examination of distal nerves.should be included into routine electrodiagnostic evaluation of patients with suspected PNP.

Objective To determine the diagnostic value of quantitative motor unit potential (MUP) analysis and peak-ratio analysis of the turns amplitude analysis (Fuglsang-Frederiksen et al., 1992) in electrophysiological diagnosis of myopathy. Methods Electromyography (EMG) data of 163 patients consecutively referred for myopathy and in whom both MUP and peak-ratio analysis were done in biceps brachii (BB) muscle were analysed retrospectively. MUP and peak ratio analysis data from BB muscle were compared. Results Of 163 patients, the overall clinical and electrophysiological diagnosis estimated using the whole electrophysiological examination was myopathy in 97 patients, normal in 45 and other disorders in 21. In 97 myopathy patients, both MUP and peak-ratio analysis were myopathic in 33 BB muscles (34%), whereas 20 muscles (21%) showed normal peak-ratio but myopathic MUP and 26 muscles (27%) showed myopathic peak-ratio but normal MUP analysis. Overall, myopathic changes were seen in 79 muscles (82%). In 39 of 45 subjects without abnormality (87%) and in 18 of 21 subjects (86%) with other disorders, both MUP and peak-ratio analysis were normal without myopathic changes. Conclusion MUP and peak-ratio analysis supplement each other in electrophysiological diagnosis of myopathy.

Objective To compare the sensitivity of sensory nerve conduction studies recorded with near-nerve technique (NNT) and surface electrodes in polyneuropathy. Methods A total of 566 sural nerves in 287 consecutive patients aged 18–91 years referred with the suspicion of polyneuropathy were studied prospectively. All nerves were examined with orthodromic NNT from lateral malleolus to sura and with antidromic surface recording from sura to lateral malleolus. The sensitivities were compared with chi-square statistics. Results The overall conclusion of NCSs was polyneuropathy in 157 and no signs of polyneuropathy were found in 130 patients. In patients with no polyneuropathy, sural nerve was normal both with surface electrodes and NNT in 254 (98%) of 258 sural nerves without any significant difference. In patients with polyneuropathy, surface recordings and NNT showed significant difference in 308 sural nerves examined ( p Conclusion Near-nerve recordings of the sural nerve are more sensitive than surface recordings in the diagnosis of polyneuropathy. Key message Near-nerve technique may be recommended in electrodiagnosis of polyneuropathy.