杉本 恵子

PURPOSE: Shear wave velocity (Vs) measurements can be unstable in individuals with obesity or with a skin-capsule distance (SCD) of ≥ 20 mm. However, instability of Vs has also been observed in cases where SCD is not markedly increased; therefore, the present study aimed to investigate the factors contributing to reduced VsN (net amount of effective shear wave velocity), an index that reflects the reliability of individual Vs measurements. METHODS: In total, 317 individuals who underwent community-based health screening were included in this study. We investigated the relationship between VsN and physical findings, laboratory data, SCD, and structure of the SCD (single vs. multilayered) to identify factors associated with decreased VsN. RESULTS: Multiple regression analysis revealed that body fat percentage (β = - 0.135, p = 0.011), SCD (β = - 0.347, p < 0.0001), and the structure of the SC region (β = - 0.295, p < 0.0001) were independently associated with decreased VsN. In cases where the SCD exceeded 20 mm, the VsN within the SCD was significantly lower in the multilayer structural type [52 (28-75)] than in the single-layer structural type [95 (77-99)] (p = 0.004). Furthermore, even when the SCD was 20 mm or less, the VsN within the SCD was significantly lower in the multilayer structure type [80 (68-89)] than in the single-layer structure type [99 (92-100)] (p < 0.0001). CONCLUSION: The results show that, in addition to SCD thickness, its internal structure reduces the VsN and contributes to Vs measurement instability.

PURPOSE: Carotid plaque is a major risk factor for cerebral infarction. Ultrasonography (US) is extensively used for screening carotid plaque, but US images contain more noise than those of computed tomography and magnetic resonance imaging, and the edges of the plaque regions are unclear. In addition, B-mode echogenicity evaluation, which is important for plaque risk assessment, has challenges involving the subjectivity of the evaluator. Although previous studies on carotid plaque assessment have included plaque segmentation, most studies involved manual operations. In this study, we propose an automated scheme of plaque classification based on segmentation in carotid US images using the transformer approach, to resolve the issues of previous studies and to perform plaque echogenicity classification. METHODS: The B-mode video captured in the long-axis cross-section was converted to still images, and region extraction and echogenicity classification were performed using TransUNet. The results of the TransUNet output and US images were fed into the Vision Transformer (ViT) for classification into hypoechoic or isoechoic-hyperechoic plaques. RESULTS: The Dice index, which indicates the accuracy of plaque region extraction, was 0.592. The Dice indices by echogenicity were 0.200, 0.493, and 0.542 for the hypoechoic, isoechoic, and hyperechoic regions, respectively. The balanced accuracy, which indicates the classification accuracy, was 79.6%. The correct classification rate for high-risk hypoechoic plaques was 95.2%. CONCLUSION: These results suggest that the proposed method is useful for evaluating the echogenicity classification of carotid artery plaques.

OBJECTIVE: The accuracy of self-reported seizure-freedom duration are essentially limited. Scalp high-frequency oscillations (HFOs) are more tightly linked to seizures than spikes alone and are a promising new biomarker. The purpose of this study is to determine the relationship between scalp HFO and time since the last reported seizure. METHODS: The study population consisted of 169 pediatric epilepsy patients (91 males; age range, 0-20 years). A holdout method was used to develop and validate a predictive model (multivariate HFO model) to estimate the time since the last reported seizure. RESULTS: The multivariate HFO model was created with four variables: scalp HFO detection rate, developmental delay, epilepsy duration, and the use of antiepileptic drugs. The area under the curve (AUC) of the multivariate HFO model was higher than that for the HFO and spike models in all four discriminations for time since the last reported seizure (≥ 2 years: AUC = 0.95, ≥ 1 year: 0.91, ≥ 2 months: 0.82, and ≥ 2 weeks: 0.76). CONCLUSIONS: The multivariate HFO model showed higher performance in patients with a longer time since the last reported seizure (≥ 1 year). SIGNIFICANCE: This model may help establish a new measure of epilepsy remission.

PURPOSE: High-frequency oscillation (HFO) in scalp electroencephalography is a promising new noninvasive prognostic epilepsy biomarker, but further data are needed to ascertain the utility of this parameter. The present work investigated the association between epileptic activity and scalp HFO in pediatric patients with various types of epilepsy, using multivariable regression models to correct for possible confounding factors. METHODS: The authors analyzed 97 subjects who were divided into groups with active epilepsy (within 1 year of seizure), seizure-free epilepsy (>1 year without seizure), and nonepilepsy. Regarding the frequency of seizure occurrence as an indicator of epileptic activity, we categorized subjects into four groups (Daily/Weekly, Monthly, Yearly, and Rarely). RESULTS: Multiple linear regression analysis showed that the scalp HFO detection rate was significantly higher in patients with active epilepsy than in those with nonepilepsy (β [95% confidence interval] = 2.77 [1.79-4.29]; P < 0.001). The association between scalp HFO detection rate and frequency of seizure occurrence was highest in the Daily/Weekly group (β [95% confidence interval] = 3.38 [1.57-7.27]; P = 0.002), followed by Monthly and Yearly groups (β [95% confidence interval] = 2.42 [1.02-5.73]; P = 0.046 and 0.36 [0.16-0.83]; P = 0.017). In addition, HFO duration, number of peaks, and number of channels detected were significantly higher in patients with active epilepsy. CONCLUSIONS: Pediatric patients with active epilepsy and high frequency of seizure occurrence exhibited a higher scalp HFO detection rate. These results may help to establish HFO detectable by noninvasive scalp electroencephalography as a biomarker of active epilepsy in pediatric patients.

OBJECTIVE: Epilepsy treatment with anti-seizure medications (ASMs) is based on careful assessment of the balance between the likelihood of further seizures and the risk of side effects of treatment. However, there is currently no established biomarker to ascertain seizure control status with ASMs. High-frequency oscillations (HFOs), transient bursts of EEG activity with frequencies beyond 80 Hz, are a new and promising noninvasive epilepsy biomarker. We compared the risk of scalp HFO appearance between pediatric patients with good and poor seizure control by treatment with ASMs. METHODS: A total of 72 epilepsy patients (aged 0-18 years, 39 males) with good and poor seizure control with ASMs participated in this study. We applied a validated automated detector to determine HFO and spike. We calculated the odds ratios (ORs) for scalp HFO and spike appearance according to seizure control status by multiple logistic regression analysis. RESULTS: Scalp HFO was seen more commonly and with a significantly higher detection rate in patients with poor seizure control as compared with patients with good seizure control for both ripple and fast ripple. These significant associations were found for both focal and generalized epilepsy. The ORs for scalp HFO appearance adjusted for confounding factors were significantly higher in patients with poor seizure control compared to those with good seizure control (ripple: OR [95% CI] = 11.91 [2.21-64.30], p = 0.004; fast ripple: 4.98 [1.03-24.09], p = 0.046). There were no significant associations between spike appearance and seizure control status. SIGNIFICANCE: We found an increased risk of scalp HFO appearance in patients with poor seizure control. The results of this study support that scalp HFO is associated with patients having frequent seizures after treatment in both ripple and fast ripple. PLAIN LANGUAGE SUMMARY: This study analyzed scalp high-frequency oscillations and spikes in pediatric patients with various types of epilepsy who were being treated using ASMs. The results showed that an increased risk of scalp HFO appearance was observed in patients with poor seizure control compared to those with good seizure control. These findings were observed in both the ripple (80-250 Hz) and fast ripple (250-500 Hz) bands. The scalp HFO is associated with patients having frequent seizures after treatment in both ripple and fast ripple.