Pelvic nerve endometriosis: MRI features and key findings for surgical decision.

Endometriosis is a prevalent gynecological disorder in women of reproductive age. It is the leading cause of chronic pelvic pain. While the mechanisms underlying this pain remain elusive, rare cases of pelvic nerve involvement can result in severe, debilitating symptoms, adding complexity to the clinical landscape.

Endometriosis MR mimickers: T2-hypointense lesions.

Endometriosis is a common crippling disease in women of reproductive age. Magnetic resonance imaging (MRI) is considered the cornerstone radiological technique for both the diagnosis and management of endometriosis. While its sensitivity, especially in deep infiltrating endometriosis, is superior to that of ultrasonography, many sources of false-positive results exist, leading to a lack of specificity.

Breast nodule classification with two-dimensional ultrasound using Mask-RCNN ensemble aggregation.

Purpose: The purpose of this study was to create a deep learning algorithm to infer the benign or malignant nature of breast nodules using two-dimensional B-mode ultrasound data initially marked as BI-RADS 3 and 4.

Materials And Methods: An ensemble of mask region-based convolutional neural networks (Mask-RCNN) combining nodule segmentation and classification were trained to explicitly localize the nodule and generate a probability of the nodule to be malignant on two-dimensional B-mode ultrasound. These probabilities were aggregated at test time to produce final results.

Three artificial intelligence data challenges based on CT and ultrasound.

Purpose: The 2020 edition of these Data Challenges was organized by the French Society of Radiology (SFR), from September 28 to September 30, 2020. The goals were to propose innovative artificial intelligence solutions for the current relevant problems in radiology and to build a large database of multimodal medical images of ultrasound and computed tomography (CT) on these subjects from several French radiology centers.

Materials And Methods: This year the attempt was to create data challenge objectives in line with the clinical routine of radiologists, with less preprocessing of data and annotation, leaving a large part of the preprocessing task to the participating teams.

Rectal endometriosis: predictive MRI signs for segmental bowel resection.

Objective: To retrospectively determine the accuracy of MRI rectal and pararectal signs in predicting the necessity for segmental resection in the case of lesions located in the rectum.

Methods: MR images of consecutive patients treated for rectal endometriosis over a 5-year period were reviewed in consensus by two blinded readers. A systematic analysis of 7 rectal (lesion length, transverse axis, thickness and circumference, and presence of a convex base, submucosal oedema and hyperintense cystic areas) and 4 pararectal (posterior vaginal fornix, parametrial, ureteral and sacro-recto-genital septum involvements) signs was performed for each lesion.

Breast abscesses in lactating women: evidences for ultrasound-guided percutaneous drainage to avoid surgery.

Background: Surgical incision with drainage remains the first-line therapy recommendation for breast abscesses greater than 5 cm.

Purpose: To determine recovery with ultrasound guided (US-guided) procedures for treatment of lactational breast abscesses without surgical incision for drainage.

Material And Methods: Institutional review board approval and written informed patient consent were obtained for this retrospective study.

Bowel endometriosis: preoperative diagnostic accuracy of 3.0-T MR enterography--initial results.

Purpose: To prospectively determine the accuracy of 3.0-T magnetic resonance (MR) enterography in the preoperative assessment of deep infiltrating endometriosis (DIE) lesions located in the bowel above the rectosigmoid junction.

Materials And Methods: Institutional review board approval for this study was obtained, and each patient gave written informed consent.