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Purpose: The present consensus statement was developed by the GINECOR working group on behalf of the Spanish Society of Radiation Oncology (SEOR). This document addresses sexual health management in patients with gynaecological cancer after pelvic radiotherapy., Methods: A modified two-round online Delphi study was conducted, where GINECOR members were surveyed on the diagnosis, treatment, and follow-up of sexual health problems. An expert panel of radiation oncologists, nurses and a gynaecologist participated in the Delphi study to reach a consensus, applying GRADE criteria to establish the level of agreement., Results: The consensus recommendations cover both diagnosis and treatment, with an emphasis on patient-reported outcome measures (PROMs). They highlight recommendations such as the systematic assessment of genitourinary, gastrointestinal, and sexual symptoms, and the use of several treatments after radiotherapy. Recommendations include pharmacological options like vaginal lubricants and hormone therapy, and mechanical interventions such as vaginal dilators and vibrators. These suggestions stem from both scientific evidence and clinical expertise., Conclusion: This consensus statement describes a comprehensive, multidisciplinary approach developed to address the sexual needs and enhance the quality of life of patients with gynaecological tumours after pelvic radiotherapy. It offers specific recommendations for managing sexual issues, emphasizing the importance of specialized care and regular assessment. The document underscores the significance of proactive, patient-centered sexual health management in gynaecological cancer patients., (© 2024. The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO).)

Purpose: The present consensus statement was developed by the GINECOR working group on behalf of the Spanish Society of Radiation Oncology (SEOR). This document provides an up-to-date review of the technical aspects in radiation treatment of vulvar cancer., Methods: A two-round modified Delphi study was conducted to reach consensus on the appropriateness of technical aspects of external beam radiotherapy and brachytherapy. Three clinical scenarios were proposed: adjuvant treatment of vulvar cancer, radiation treatment of locally advanced vulvar carcinoma and locoregional recurrences. After the first round, an extensive analysis of current medical literature from peer-reviewed journal was performed to define evidence-based treatment options. In the second round, participants were asked to indicate their level of agreement with the preliminary recommendations according to the GRADE (Grade of Recommendation, Assessment, Development, and Evaluation) criteria, as follows: strongly agree; agree; neither agree nor disagree; disagree and strongly disagree., Results: The main recommendations on external beam radiotherapy and brachytherapy, both in adjuvant setting and local advanced disease are summarized. Recommendations include treatment technique, treatment volume, and doses in target and organs at-risk. Taking into consideration the different clinical scenarios of recurrent disease, the radiation treatment should be individualized., Conclusions: In the absence of robust clinical data, these recommendations may help to select the optimal radiotherapy approach for this relatively rare cancer., (© 2023. The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO).)

Purpose: The present consensus statement was developed by the GINECOR working group on behalf of the Spanish Society of Radiation Oncology (SEOR). Given the lack of prospective data on the management of vulvar carcinoma, this document provides an up-to-date review of radiotherapy treatment in vulvar cancer and a series of consensus-based recommendations from a group of experts., Methods: A two-round, online modified Delphi study was conducted to reach consensus treatment recommendations in three clinical settings: 1) adjuvant treatment, 2) locally-advanced vulvar cancer (LAVC), and 3) recurrent disease. After the first round, we comprehensively reviewed the available medical literature from peer-reviewed journals to assess and define the evidence-based treatment options. In the second round, participants were asked to indicate their level of agreement with the preliminary recommendations according to the GRADE (Grade of Recommendation, Assessment, Development, and Evaluation) criteria, as follows: strongly agree; agree; neither agree nor disagree; disagree; strongly disagree., Results: The main recommendations were as follows: 1) following surgical resection, adjuvant radiotherapy is recommended with the presence of adverse risk factors (primarily positive margins and lymph node involvement); 2) radiotherapy (with or without chemotherapy) should be considered in LAVC; and 3) in recurrent disease, radiotherapy should be individualised on a case-by-case basis. A high level of agreement over 80% was reached., Conclusions: In the absence of robust clinical data, these final recommendations may help to select the optimal radiotherapy approach for this relatively rare cancer., (© 2023. The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO).)

Action recognition in robotics is a research field that has gained momentum in recent years. In this work, a video activity recognition method is presented, which has the ultimate goal of endowing a robot with action recognition capabilities for a more natural social interaction. The application of Common Spatial Patterns (CSP), a signal processing approach widely used in electroencephalography (EEG), is presented in a novel manner to be used in activity recognition in videos taken by a humanoid robot. A sequence of skeleton data is considered as a multidimensional signal and filtered according to the CSP algorithm. Then, characteristics extracted from these filtered data are used as features for a classifier. A database with 46 individuals performing six different actions has been created to test the proposed method. The CSP-based method along with a Linear Discriminant Analysis (LDA) classifier has been compared to a Long Short-Term Memory (LSTM) neural network, showing that the former obtains similar or better results than the latter, while being simpler.