OBJECTIVE: To compare long-term oncologic outcomes in patients with clinically uterine-confined endometrioid endometrial cancer who underwent surgical staging with robot-assisted (RA) versus conventional laparoscopy.
The potential benefits and limitations of benign hysterectomy surgical approaches are still debated. We aimed at evaluating any differences with a systematic review and meta-analysis. PubMed, MEDLINE, and EMBASE databases were last searched on 6/2/20...
OBJECTIVE: To describe a novel high-precision technique for robotic excision of uterine isthmocele, employing a carbon dioxide laser fiber, under hysteroscopic guidance, and near-infrared guidance.
We compared the effectiveness of conventional total laparoscopic hysterectomy (TLH) against robot-assisted total hysterectomy (RAH) in patients with a large uterus. According to the subtype of minimally invasive hysterectomy performed for benign indi...
OBJECTIVE: Uterine smooth muscle hyperplasia causes a tumor called a uterine fibroid. With an incidence of up to 30%, it is one of the most prevalent tumors in women and has the third highest prevalence of all gynecological illnesses. Although uterin...
Cancer is characterized by abnormal cell growth and proliferation, which are both diagnostic indicators of the disease. When cancerous cells enter one organ, there is a risk that they may spread to adjacent tissues and eventually to other organs. Can...
International journal of environmental research and public health
Jan 18, 2023
BACKGROUND: This study aims to evaluate the diagnostic performance of Deep Learning (DL) machine for the detection of adenomyosis on uterine ultrasonographic images and compare it to intermediate ultrasound skilled trainees.
INTRODUCTION AND HYPOTHESIS: Our study was aimed at comparing the outcomes of laparoscopic and robot-assisted laparoscopic suture-based hysteropexy (SutureH) versus sacral hysteropexy using mesh (MeshH) for bothersome uterine prolapse. Our hypothesis...
OBJECTIVE: This study aimed to evaluate the effects of deep learning (DL) reconstruction and a postprocessing sharpening filter on the image quality of single-shot fast spin-echo (SSFSE) T2-weighted imaging (T2WI) of the uterus.
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