Combined robotic surgery for concomitant treatment of endometrial cancer and obesity.

Background: Endometrial Cancer (EC) is strongly linked to obesity. Bariatric surgery is recognized as a long-term solution for weight loss in severely obese patients. This pilot study investigates the feasibility, intraoperative and 30-day morbidity outcomes of integrating gynecological surgical staging and bariatric robotic surgery in class II and III obese patients affected by early EC or Endometrial Intraepithelial Neoplasia (EIN).

Machine Learning Applied to Pre-Operative Computed-Tomography-Based Radiomic Features Can Accurately Differentiate Uterine Leiomyoma from Leiomyosarcoma: A Pilot Study.

Background: The accurate discrimination of uterine leiomyosarcomas and leiomyomas in a pre-operative setting remains a current challenge. To date, the diagnosis is made by a pathologist on the excised tumor. The aim of this study was to develop a machine learning algorithm using radiomic data extracted from contrast-enhanced computed tomography (CECT) images that could accurately distinguish leiomyosarcomas from leiomyomas.