BackgroundTo evaluate the feasibility and clinical outcomes of vaginoplasties using a neovaginal polylactic acid prosthesis made with 3-dimensional (3D) printing technology as an intraneovaginal mould.MethodsThis was an interventionist, prospective, and multicentre clinical pilot investigation of a sanitary product (PACIENA prosthesis®) aiming to recruit and operate on 8 patients over 6 months with a follow-up period of 6 months. Only six patients with Rokitansky syndrome and one patient with Morris syndrome (7 patients in total) were operated on in two university hospitals: “La Fe”, Valencia (H1) and “Arrixaca”, Murcia (H2). Interventions: Extensive surgical dissection of a defined space between the urethra and bladder in the front and of the rectum in the back as well as insertion of the PACIENA prosthesis® covered with Interceed® were performed. After 12 days, the prosthesis was changed to the silicone-covered version for daily application.ResultsIn the 6 patients with Rokitansky syndrome (86%), the primary endpoint (satisfactory vaginal outcome in terms of appearance, function, and sensation without relevant additional morbidity) was achieved, although only 2 patients (28%) were sexually active at the end of 6 months of follow-up. The patient with Morris syndrome withdrew from the study after 1 month. Patients without bacterial colonization showed positive Schiller tests at 1 month, and subsequent biopsies showed adequate keratinization and epidermization. Epithelization and iodopositivity were delayed in the patients who developed inflammatory granulomas.ConclusionsGood anatomical and functional results can be achieved with the PACIENA prosthesis® for vaginoplasties without skin grafts. However, adequate patient selection and education, good surgical techniques and haemostasis, postoperative support, and prevention of bacterial colonization are important.Trial registrationThis clinical study was approved by the Ethical Clinical Investigation Committee of San Juan University Hospital on September 27, 2016, to be conducted in the participating centres; it was authorized by the Spanish Agency of Medicines and Health Products (AEMPS) on April 24, 2017 (exp. no. 585/16/EC), to be carried out in that hospitals.
Expanding the performance and autonomous-decision capability of driver-assistance systems is critical in today’s automotive engineering industry to help drivers and reduce accident incidence. It is essential to provide vehicles with the necessary perception systems, but without creating a prohibitively expensive product. In this area, the continuous and precise estimation of a road surface on which a vehicle moves is vital for many systems. This paper proposes a low-cost approach to solve this issue. The developed algorithm resorts to analysis of vibrations generated by the tyre-rolling movement to classify road surfaces, which allows for optimizing vehicular-safety-system performance. The signal is analyzed by means of machine-learning techniques, and the classification and estimation of the surface are carried out with the use of a self-organizing-map (SOM) algorithm. Real recordings of the vibration produced by tyre rolling on six different types of surface were used to generate the model. The efficiency of the proposed model (88.54%) and its speed of execution were compared with those of other classifiers in order to evaluate its performance.
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