Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma cases.

Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we investigated whether deep neural network (DNN) models can improve the accuracy of preoperative MRI-based diagnosis in patients with uterine sarcomas. Fifteen sequences of MRI for patients (uterine sarcoma group: n = 63; uterine leiomyoma: n = 200) were used to train the models.

A Case of Nonpuerperal Uterine Inversion Caused by Cervical Cancer.

Uterine inversion is a rare puerperal event in the third stage of labor. Nonpuerperal uterine inversion is even rarer and is mainly caused by uterine fibroids, uterine sarcoma, or endometrial cancer. This is the first report of uterine inversion caused by cervical cancer.

Retreatment with nedaplatin in patients with recurrent gynecological cancer after the development of hypersensitivity reaction to carboplatin.

Aim: Platinum is a milestone drug against gynecologic malignancies. The purpose of this retrospective study was to investigate the feasibility of replacing carboplatin with nedaplatin in patients who had developed a hypersensitivity reaction to carboplatin.

Material And Methods: Fifteen patients with recurrent gynecologic cancer (12 ovarian, 1 fallopian tube, 1 endometrial and 1 cervical cancer) who had experienced a hypersensitivity reaction to carboplatin and a possible clinical indication for continuing treatment with platinum were treated with nedaplatin (80 mg/m(2) )-containing regimen.