Multidetector CT of expected findings and complications after hysterectomy

Diagnostic value of susceptibility-weighted imaging for endometrioma: preliminary results from a retrospective analysis

BACKGROUND

Endometrioma is a common manifestation of endometriosis that can be difficult to diagnose with conventional magnetic resonance imaging (MRI). Susceptibility-weighted imaging (SWI) may be more sensitive than conventional MRI in the detection of chronic, local hemorrhagic disease.

PURPOSE

To investigate whether signal voids in SWI sequences could be used in the preoperative diagnosis of endometrioma.

MATERIAL AND METHODS

This retrospective study included consecutive female patients with clinically suspected endometrioma. All patients underwent pelvic 3-T MRI (T1- and T2-weighted) and SWI within two weeks before laparoscopy. Two experienced radiologists blinded to the histopathologic/clinical diagnoses interpreted the images together, and any disagreements were resolved by consensus.

RESULTS

The final analysis included 73 patients: 46 patients (mean age=37 years; age range=22-68 years) with 85 endometrioma lesions and 27 patients (mean age=34 years; age range=15-68 years) with 34 non-endometrioid cystic lesions (18 hemorrhagic corpus luteal cysts, three simple cysts, three mucinous cystadenomas, two mature teratomas, and one endometrioid cyst with corpus luteum rupture/hemorrhage). The presenting symptoms for patients with endometrioma were chronic pelvic pain (44.6%), dysmenorrhea (31.9%), infertility (12.8%), dyspareunia (6.4%), and menstrual irregularity (4.3%). MRI identified all 119 lesions observed laparoscopically. SWI visualized punctate or curvilinear signal voids along the cyst wall or within the lesion in 67 of 85 endometriomas (78.8%) and only 3 of 31 non-endometrioid cysts (8.8%).

CONCLUSION

The use of SWI to look for signal voids in the cyst wall or within the lesion could facilitate the preoperative diagnosis of endometrioma.

Preoperative Differentiation of Uterine Leiomyomas and Leiomyosarcomas: Current Possibilities and Future Directions

The distinguishing of uterine leiomyosarcomas (ULMS) and uterine leiomyomas (ULM) before the operation and histopathological evaluation of tissue is one of the current challenges for clinicians and researchers. Recently, a few new and innovative methods have been developed. However, researchers are trying to create different scales analyzing available parameters and to combine them with imaging methods with the aim of ULMs and ULM preoperative differentiation ULMs and ULM. Moreover, it has been observed that the technology, meaning machine learning models and artificial intelligence (AI), is entering the world of medicine, including gynecology. Therefore, we can predict the diagnosis not only through symptoms, laboratory tests or imaging methods, but also, we can base it on AI. What is the best option to differentiate ULM and ULMS preoperatively? In our review, we focus on the possible methods to diagnose uterine lesions effectively, including clinical signs and symptoms, laboratory tests, imaging methods, molecular aspects, available scales, and AI. In addition, considering costs and availability, we list the most promising methods to be implemented and investigated on a larger scale.

Vaginal cuff dehiscence: report of two cases

Vaginal cuff dehiscence is a rare but potentially life-threatening post-hysterectomy complication. Here we report two cases of vaginal cuff dehiscence with distinct imaging features and describe the CT findings of vaginal cuff dehiscence. Both patients underwent repair surgery, and the diagnoses were confirmed. Radiologic features of vaginal cuff dehiscence are uncommonly described in the literature. Vaginal cuff mural discontinuity and omental fat tissue or bowel herniation into the vaginal canal are the most common appearances of vaginal cuff dehiscence. Pelvic hematoma, bowel obstruction, and pneumoperitoneum can accompany. These two cases highlight the CT appearances, potential presentations, and management of vaginal cuff dehiscence in the emergency setting.

Elucidating vaginal fistulas on CT and MRI

Vaginal fistulas (VF) represent abnormal communications between the vagina and either the distal portion of the digestive system or the lower urinary tract, but lack an accepted classification and standardised terminology. Regardless of the underlying cause, these uncommon disorders result in profound physical, psychological, sexual and social distress to the patients.Since diagnosis of VF is challenging at gynaecologic examination, ano-proctoscopy and urethro-cystoscopy, imaging is crucial to confirm the fistula, to visualise its site, course and involved organ, and to characterise the underlying disease. The traditional conventional radiographic studies provided limited cross-sectional information and are nowadays largely replaced by CT and MRI studies.Aiming to provide radiologists with an increased familiarity with VF, this pictorial paper summarises their clinical features, pathogenesis and therapeutic approach, and presents the appropriate CT and MRI acquisition and interpretation techniques that vary according to the anatomic site and termination of the fistula. The current role of state-of-the art CT and MRI is presented with examples regarding both entero- (involving the colon, rectum and anus) and urinary (connecting the bladder, distal ureter or urethra) VF. The resulting combined anatomic and functional cross-sectional information is crucial to allow a correct therapeutic choice and surgical planning.

How to differentiate uterine leiomyosarcoma from leiomyoma with imaging

Uterine leiomyomas, the most frequent benign myomatous tumors of the uterus, often cannot be distinguished from malignant uterine leiomyosarcomas using clinical criteria. Furthermore, imaging differentiation between both entities is frequently challenging due to their potential overlapping features. Because a suspected leiomyoma is often managed conservatively or with minimally invasive treatments, the misdiagnosis of leiomyosarcoma for a benign leiomyoma could potentially result in significant treatment delays, therefore increasing morbidity and mortality. In this review, we provide an overview of the differences between leiomyoma and leiomyosarcoma, mainly focusing on imaging characteristics, but also briefly touching upon their demographic, histopathological and clinical differences. The main indications and limitations of available cross-sectional imaging techniques are discussed, including ultrasound, computed tomography, magnetic resonance imaging (MRI) and positron emission tomography/computed tomography. A particular emphasis is placed on the review of specific MRI features that may allow distinction between leiomyomas and leiomyosarcomas according to the most recent evidence in the literature. The potential contribution of texture analysis is also discussed. In order to help guide-imaging diagnosis, we provide an MRI-based diagnostic algorithm which takes into account morphological and functional features, both individually and in combination, in an attempt to optimize radiologic differentiation of leiomyomas from leiomyosarcomas.