SIGNAL REGULARITY-BASED AUTOMATED SEIZURE DETECTION SYSTEM FOR SCALP EEG MONITORING.

The purpose of the present study was to build a clinically useful automated seizure detection system for scalp EEG recordings. To achieve this, a computer algorithm was designed to translate complex multichannel scalp EEG signals into several dynamical descriptors, followed by the investigations of their spatiotemporal properties that relate to the ictal (seizure) EEG patterns as well as to normal physiologic and artifact signals. This paper describes in detail this novel seizure detection algorithm and reports its performance in a large clinical dataset.

Assessment of a scalp EEG-based automated seizure detection system.

OBJECTIVE: The purpose of this study was to evaluate and validate an offline, automated scalp EEG-based seizure detection system and to compare its performance to commercially available seizure detection software. METHODS: The test seizure detection system, IdentEvent™, was developed to enhance the efficiency of post-hoc long-term EEG review in epilepsy monitoring units. It translates multi-channel scalp EEG signals into multiple EEG descriptors and recognizes ictal EEG patterns. Detection criteria and thresholds were optimized in 47 long-term scalp EEG recordings selected for training (47 subjects, ∼3653h with 141 seizures). The detection performance of IdentEvent was evaluated using a separate test dataset consisting of 436 EEG segments obtained from 55 subjects (∼1200h with 146 seizures). Each of the test EEG segments was reviewed by three independent epileptologists and the presence or absence of seizures in each epoch was determined by majority rule. Seizure detection sensitivity and false detection rate were calculated for IdentEvent as well as for the comparable detection software (Persyst's Reveal®, version 2008.03.13, with three parameter settings). Bootstrap re-sampling was applied to establish the 95% confidence intervals of the estimates and for the performance comparison between two detection algorithms. RESULTS: The overall detection sensitivity of IdentEvent was 79.5% with a false detection rate (FDR) of 2 per 24h, whereas the comparison system had 80.8%, 76%, and 74% sensitivity using its three detection thresholds (perception score) with FDRs of 13, 8, and 6 per 24h, respectively. Bootstrap 95% confidence intervals of the performance difference revealed that the two detection systems had comparable detection sensitivity, but IdentEvent generated a significantly (p<0.05) smaller FDR. CONCLUSIONS: The study validates the performance of the IdentEvent™ seizure detection system. SIGNIFICANCE: With comparable detection sensitivity, an improved false detection rate makes the automated seizure detection software more useful in clinical practice.

Invasive differences among Porphyromonas gingivalis strains from healthy and diseased periodontal sites.

BACKGROUND AND OBJECTIVE: The purpose of this study was to determine any difference between Porphyromonas gingivalis isolates from periodontally healthy sites as compared to those from diseased sites with respect to the ability to invade host cells. MATERIAL AND METHODS: Subgingival plaque samples were obtained from periodontally healthy and diseased sites using paper points. P. gingivalis colonies were isolated and tested, using an antibiotic protection assay, for their ability to invade KB cells. P. gingivalis 381 and Escherichia coli MC1061 were used as controls. RESULTS: Mean values of 16.79 +/- 0.86 x 10(3) colony-forming units/mL and 26.14 +/- 2.11 x 10(3) colony-forming units/mL were observed in invasion assays for isolates from periodontally healthy and diseased sites, respectively. P. gingivalis present in diseased sites had significantly greater invasive abilities than strains isolated from healthy sites. No statistical difference was noted between male or female subjects concerning the degree of invasion; isolates from diseased sites from both genders had significantly greater invasion abilities than those from healthy sites. A significant correlation was found between the increased invasive capabilities of P. gingivalis isolates vs. an increased probing depth. CONCLUSION: The increased invasion noted with P. gingivalis isolates from diseased sites vs. healthy sites, and the increased invasive capabilities with increasing probing depth, indicate that P. gingivalis isolates have a varying ability to invade host cells in the periodontal pocket.

Accuracy of probing attachment levels using a CEJ probe versus traditional probes.

BACKGROUND: Current interest in the assessment of probing attachment level measurements has been stimulated by recent introduction of novel periodontal probes as well as by the reclassification of periodontal diseases. Clinical attachment level (CAL) is currently the "gold standard" for diagnosing and monitoring periodontal diseases. AIM: To evaluate the performance of the newly introduced cementoenamel junction (CEJ) Probe in detecting CAL using the CEJ as a fixed reference point, and to compare the CEJ Probe with the Florida Disk Probe and a standard Manual Probe (North Carolina Probe). MATERIALS AND METHODS: Three examiners probed 12 periodontal patients to determine intra- and inter-consistency of both the probes and the examiners, over a 4-week time interval. Subjects ranged in age from 22 to 74 years. The experimental design was structured to balance the intra- and inter-examiner consistency at the same site during the two visits. RESULTS: Using the PROC MIXED of SAS, a strong interaction (p<0.001) between the examiner and probes was found. The consistency of probing (repeatability of measurements) depended upon the type of periodontal probe used as well as the skill (experience) of the examiner. Overall, the CEJ Probe displayed a more consistent performance. The CEJ Probe demonstrated greater intra-examiner consistency than the Disk Probe for two examiners (p<0.01). The CEJ Probe also showed increased inter-examiner consistency (p<0.01). CONCLUSIONS: The CEJ Probe has the potential to offer the dental team an efficient, accurate mechanism to chart and monitor attachment level measurements over time. Additional studies, using large numbers of examiners, are needed to assess more clearly the performance of each individual probe.

Microarray experimental design: power and sample size considerations.

Gene expression analysis using high-throughput microarray technology has become a powerful approach to study systems biology. The exponential growth in microarray experiments has spawned a number of investigations into the reliability and reproducibility of this type of data. However, the sample size requirements necessary to obtain statistically significant results has not had as much attention. We report here statistical methods for the determination of the sufficient number of subjects necessary to minimize the false discovery rate while maintaining high power to detect differentially expressed genes. Two experimental designs were considered: 1) a comparison between two groups at a single time point, and 2) a comparison of two experimental groups with sequential time points. Computer programs are available for the methods discussed in this paper and are adaptable to more complicated situations.