Purpose: To describe frequency and electroclinical characteristics as well as localizing and lateralizing value of childhood periictal genital automatisms (GAs).
Methods: Five-hundred-forty-one videotaped seizures of 109 consecutive patients <12 years with refractory partial epilepsy and postoperatively seizure-free outcome were analyzed. Genital automatisms (scratching, fondling or grabbing of the genitals) were monitored by two independent investigators.
Results: Eight (four temporal, four extratemporal) patients (7%) showed GA at least once during 20 (3.7%) seizures. Age of patients with GA was between 4.5 and 11.9 (mean 9.5+/-2.4) years and was significantly higher than the age of children without GA (p=0.006). Boys showed GAs more frequently than girls (p=0.026). Genital automatisms appeared both ictally and postictally with a mean duration of 51s. They were unilateral (completed by one hand) in 18/20 seizures and were done by the hand ipsilateral to the seizure onset zone in 16/18 cases (p=0.001). Although consciousness was preserved during GA in 3/8 patients, neither periictal urinary urge nor penile erection was associated with it.
Conclusions: Periictal GAs appear in school-age patients with a similar frequency to that in adults but almost lack in preschool children. Although the presence of childhood GA has neither localizing nor lateralizing value per se, the hand used for GA is more frequently ipsilateral to the seizure onset zone. The mechanisms for childhood GAs are not clear but probably different from those of adults.
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http://dx.doi.org/10.1016/j.eplepsyres.2005.06.003 | DOI Listing |
Sci Rep
January 2025
Department of Biomedical Engineering, School of Life Science and Technology, Changchun University of Science and Technology, Changchun, 130022, China.
The cervical cell classification technique can determine the degree of cellular abnormality and pathological condition, which can help doctors to detect the risk of cervical cancer at an early stage and improve the cure and survival rates of cervical cancer patients. Addressing the issue of low accuracy in cervical cell classification, a deep convolutional neural network A2SDNet121 is proposed. A2SDNet121 takes DenseNet121 as the backbone network.
View Article and Find Full Text PDFRadiol Imaging Cancer
January 2025
From the Department of Radiology (A.C., A.N.Y., R.E., C.H., G.L., M.M., E.B.J., A.L.C., B.G., G.S.K., A.O.), Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy (A.C., A.N.Y., M.M., A.L.C., B.G.), Department of Surgery, Section of Urology (G.G., L.F.R., P.K.M., S.E.), Department of Pathology (T.A.), and Department of Public Health Sciences (M.G.), University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.
Purpose To evaluate the use of an automated hybrid multidimensional MRI (HM-MRI)-based tool to prospectively identify prostate cancer targets before MRI/US fusion biopsy in comparison with Prostate Imaging and Reporting Data System (PI-RADS)-based multiparametric MRI (mpMRI) evaluation by expert radiologists. Materials and Methods In this prospective clinical trial (ClinicalTrials.gov registration no.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325035, China.
Cervical cancer is one of the deadliest cancers that pose a significant threat to women's health. Early detection and treatment are commonly used methods to prevent cervical cancer. The use of pathological image analysis techniques for the automatic interpretation of cervical cells in pathological slides is a prominent area of research in the field of digital medicine.
View Article and Find Full Text PDFSci Rep
December 2024
INRAE, CNRS, Université de Tours, PRC, Nouzilly, 37380, France.
Ovaries are of paramount importance in reproduction as they produce female gametes through a complex developmental process known as folliculogenesis. In the prospect of better understanding the mechanisms of folliculogenesis and of developing novel pharmacological approaches to control it, it is important to accurately and quantitatively assess the later stages of ovarian folliculogenesis (i.e.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
School of Automation, Central South University, Changsha, China.
Background: Private-part skin diseases (PPSDs) can cause a patient's stigma, which may hinder the early diagnosis of these diseases. Artificial intelligence (AI) is an effective tool to improve the early diagnosis of PPSDs, especially in preventing the deterioration of skin tumors in private parts such as Paget disease. However, to our knowledge, there is currently no research on using AI to identify PPSDs due to the complex backgrounds of the lesion areas and the challenges in data collection.
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