Objectives: Genital automatisms (GAs) are uncommon clinical phenomena of focal seizures. They are defined as repeated fondling, grabbing, or scratching of the genitals. The aim of this study was to determine the lateralizing and localizing value and associated clinical characteristics of GAs.
Methods: Three hundred thirteen consecutive patients with drug-resistant seizures who were referred to our tertiary center for presurgical evaluation between 2009 and 2016 were investigated. The incidence of specific kinds of behavior, clinical semiology, associated symptoms/signs with corresponding ictal electroencephalography (EEG) findings, and their potential role in seizure localization and lateralization were evaluated.
Results: Fifteen (4.8%) of 313 patients had GAs. Genital automatisms were identified in 19 (16.4%) of a total 116 seizures. Genital automatisms were observed to occur more often in men than in women (M/F: 10/5). Nine of fifteen patients (60%) had temporal lobe epilepsy (right/left: 4/5) and three (20%) had frontal lobe epilepsy (right/left: 1/2), whereas the remaining two patients could not be classified. One patient was diagnosed as having Rasmussen encephalitis. Genital automatisms were ipsilateral to epileptic focus in 12 patients and contralateral in only one patient according to ictal-interictal EEG and neuroimaging findings. Epileptic focus could not be lateralized in the last 2 patients. Genital automatisms were associated with unilateral hand automatisms such as postictal nose wiping or manual automatisms in 13 (86.7%) of 15 and contralateral dystonia was seen in 6 patients. All patients had amnesia of the performance of GAs.
Conclusion: Genital automatisms are more frequent in seizures originating from the temporal lobe, and they can also be seen in frontal lobe seizures. Genital automatisms seem to have a high lateralizing value to the ipsilateral hemisphere and are mostly concordant with other unilateral hand automatisms. Men exhibit GAs more often than women.
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http://dx.doi.org/10.1016/j.yebeh.2017.12.023 | 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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