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The 2022 Delphi revision of the MUSA (Morphological Uterus Sonographic Assessment) criteria for the ultrasound diagnosis of adenomyosis divides the ultrasound signs for diagnosis into direct and indirect ones, considering the presence of at least one direct sign as a mandatory criterion. This study aimed to reclassify the patients referred to the Pelvic Pain specialist outpatient clinic of the Gynecological Clinic of Udine according to the new criteria, evaluating the number of overdiagnoses and the possible correlation between the direct and indirect signs and the patients' symptoms. 62 patients affected by adenomyosis were retrospectively recruited. The patients were then re-evaluated by ultrasound and clinically. At least one direct sign of adenomyosis was found in 52 patients, while 16% of the population examined did not present any. There was no statistically significant difference between patients presenting direct signs and those presenting none for the symptoms considered. According to the new criteria, 16% of the patients examined were not affected by adenomyosis; applying the new consensus to symptomatic patients could increase false negatives. In a population of symptomatic patients, the diagnosis of adenomyosis is still highly probable even without direct ultrasound signs, given the clinical symptoms and having ruled out other causes of such symptoms. [ABSTRACT FROM AUTHOR]

Simple Summary: In patients with locally advanced cervical cancer, the availability of imaging techniques for accurately defining the residual tumor would be clinically relevant for selecting patients who could be offered a more tailored surgery. The novelty of this prospective study is the development of multiparametric predictive models of histopathological response using a unique data set with three imaging modalities (transvaginal ultrasound, magnetic resonance (MRI) and 18F-FDG-PET/CT) evaluated at three time points ("baseline", two ("early") and five ("final") weeks after treatment). In a cohort of 88 patients, the predictive models retrieved integrating morphometric, vascular, perfusion and metabolic parameters, demonstrated that two imaging approaches (MRI and PET/CT at "final" evaluation or PET/CT at "baseline" and "final" evaluation) are sufficient to identify possible residual disease after chemotherapy. These findings could be useful in selecting patients with residual disease, helping clinicians to tailor the radicality of the surgical approach. Purpose: This study aimed to develop predictive models for pathological residual disease after neoadjuvant chemoradiation (CRT) in locally advanced cervical cancer (LACC) by integrating parameters derived from transvaginal ultrasound, MRI and PET/CT imaging at different time points and time intervals. Methods: Patients with histologically proven LACC, stage IB2–IVA, were prospectively enrolled. For each patient, the three examinations were performed before, 2 and 5 weeks after treatment ("baseline", "early" and "final", respectively). Multivariable logistic regression models to predict complete vs. partial pathological response (pR) were developed and a cost analysis was performed. Results: Between October 2010 and June 2014, 88 patients were included. Complete or partial pR was found in 45.5% and 54.5% of patients, respectively. The two most clinically useful models in pR prediction were (1) using percentage variation of SUVmax retrieved at PET/CT "baseline" and "final" examination, and (2) including high DWI signal intensity (SI) plus, ADC, and SUVmax collected at "final" evaluation (area under the curve (95% Confidence Interval): 0.80 (0.71–0.90) and 0.81 (0.72–0.90), respectively). Conclusion: The percentage variation in SUVmax in the time interval before and after completing neoadjuvant CRT, as well as DWI SI plus ADC and SUVmax obtained after completing neoadjuvant CRT, could be used to predict residual cervical cancer in LACC patients. From a cost point of view, the use of MRI and PET/CT is preferable. [ABSTRACT FROM AUTHOR]

Background: complete uterine septum, double cervix and vaginal septum is a rare complex Müllerian anomaly affecting patients' quality of life in terms of fertility and pelvic pain. The aim of our review is to gather the studies concerning the diagnosis and treatment this complex malformation and to describe the related fertility outcomes. Methods: this study was conducted in 2022, according to the criteria of Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and the protocol was submitted to the International Prospective Register for Systematic Reviews (PROSPERO). PubMed, Scopus and Web of Science electronic databases were searched to find eligible articles. In total, 538 articles were identified through literature research. A total of ten articles satisfied the eligibility criteria and were included in the systematic review. Results: 86 affected women were evaluated, and 71 of them were treated. Almost all patients included in our research presented with primary infertility or with a history of recurrent miscarriages; half of all patients also reported dyspareunia. After surgical treatment, 47 pregnancies were achieved: 41 live birth and ongoing pregnancies and six spontaneous miscarriages occurred; a significantly lower miscarriage rate was reported after surgical treatment. Conclusion: hysteroscopic treatment of U2b C2 V1 anomaly can be safely performed, leading to favorable fertility outcomes, measured as the achievement of pregnancy and a reduction in miscarriage rate. [ABSTRACT FROM AUTHOR]

Statistical Analysis Population Analysis We discerned the following population analysis: (1) all patients recruited in all centers will constitute the full-analysis (FA) group; (2) all patients recruited at centers that test everyone (with PCR) for COVID-19 will constitute the testing-all group; and (3) all patients who were symptomatic (but not yet confirmed COVID-19 positive) will be considered symptomatic patients. Inclusion criteria are pregnant patients admitted during the COVID-19 pandemic: (1) patients with confirmed COVID-19 infection (see below); (2) symptomatic patients with suspicion of COVID-19 infection (swab taken on admission); and (3) patients asymptomatic for COVID-19 with other fetal-maternal diseases or who come for delivery or cesarean delivery. I To the Editor i : During the coronavirus disease 2019 (COVID-19) outbreak, all patient categories have been affected, including one of the most fragile groups: pregnant women. In pregnant patients, lung ultrasound (LUS) could be a valid alternative imaging tool instead of thoracic CT to guarantee appropriate care for these patients. [Extracted from the article]

Gynecological cancers require complex intervention since patients have specific needs to be addressed. Centralization to high-volume centers improves the oncological outcomes of patients with gynecological cancers. Research in gynecological oncology is increasing thanks to modern technologies, from the comprehensive molecular characterization of tumors and individual pathophenotypes. Ongoing studies are focusing on personalizing therapies by integrating information across genomics, proteomics, and metabolomics with the genetic makeup and immune system of the patient. Hence, several challenges must be faced to provide holistic benefit to the patient. Personalized approaches should also recognize the unmet needs of each patient to successfully deliver the promise of personalized care, in a multidisciplinary effort. This may provide the greatest opportunity to improve patients' outcomes. Starting from a narrative review on gynecological oncology patients' needs, this article focuses on the experience of building a research and care infrastructure for personalized patient management. [ABSTRACT FROM AUTHOR]

The aim of this paper was to explore the role of artificial intelligence (AI) applied to ultrasound imaging in gynecology oncology. Web of Science, PubMed, and Scopus databases were searched. All studies were imported to RAYYAN QCRI software. The overall quality of the included studies was assessed using QUADAS-AI tool. Fifty studies were included, of these 37/50 (74.0%) on ovarian masses or ovarian cancer, 5/50 (10.0%) on endometrial cancer, 5/50 (10.0%) on cervical cancer, and 3/50 (6.0%) on other malignancies. Most studies were at high risk of bias for subject selection (i.e., sample size, source, or scanner model were not specified; data were not derived from open-source datasets; imaging preprocessing was not performed) and index test (AI models was not externally validated) and at low risk of bias for reference standard (i.e., the reference standard correctly classified the target condition) and workflow (i.e., the time between index test and reference standard was reasonable). Most studies presented machine learning models (33/50, 66.0%) for the diagnosis and histopathological correlation of ovarian masses, while others focused on automatic segmentation, reproducibility of radiomics features, improvement of image quality, prediction of therapy resistance, progression-free survival, and genetic mutation. The current evidence supports the role of AI as a complementary clinical and research tool in diagnosis, patient stratification, and prediction of histopathological correlation in gynecological malignancies. For example, the high performance of AI models to discriminate between benign and malignant ovarian masses or to predict their specific histology can improve the diagnostic accuracy of imaging methods., (© 2024 The Author(s). International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Background: A laparoscopy-based scoring system was developed by Fagotti et al (Fagotti or Predictive Index Value (PIV)score) based on the intraoperative presence or absence of carcinomatosis on predefined sites. Later, the authors updated the PIV score calculated only in the absence of one or both absolute criteria of non-resectability (mesenteric retraction and miliary carcinomatosis of the small bowel) (updated PIV model)., Objective: The aim was to demonstrate the non-inferiority of ultrasound to other imaging methods (contrast enhanced computed tomography (CT) and whole-body diffusion-weighted (WB DWI)/MRI) in predicting non-resectable tumor (defined as residual disease>1 cm) using the updated PIV model in patients with tubo-ovarian cancer. The agreement between imaging and intraoperative findings as a reference was also calculated., Study Design: This was a European prospective multicenter observational study. We included patients with suspected tubo-ovarian carcinoma who underwent preoperative staging and prediction of non-resectability at ultrasound, CT, WB-DWI/MRI and surgical exploration. The predictors of non-resectability were suspicious mesenteric retraction and/or miliary carcinomatosis of the small bowel or if absent, a PIV>8 (updated PIV model). The PIV score ranges from 0 to 12 according to the presence of disease in six predefined intra-abdominal sites (great omentum, liver surface, lesser omentum/stomach/spleen, parietal peritoneum, diaphragms, bowel serosa/mesentery). The reference standard was surgical outcome, in terms of residual disease>1 cm, assessed by laparoscopy and/or laparotomy. The area under the receiver operating characteristic curve (AUC) to assess the performance of the methods in predicting non-resectability was reported. Concordance between index tests at detection of disease at six predefined sites and intraoperative exploration as reference standard was also calculated using Cohen's kappa., Results: The study was between 2018 and 2022 in five European gynecological oncology centers. Data from 242 patients having both mandatory index tests (ultrasound and CT) were analyzed. 145/242 (59.9%) patients had no macroscopic residual tumor after surgery (R0) (5/145 laparoscopy and 140/145 laparotomy) and 17/242 (7.0%) had residual tumor ≤1cm (R1) (laparotomy). In 80/242 patients (33.1%), the residual tumor was >1 cm (R2), 30 of them underwent laparotomy and maximum surgery was carried out and 50/80 underwent laparoscopy and cytoreduction was not feasible in all of them. After excluding 18/242 (7.4%) patients operated on but not eligible for extensive surgery, the predictive performance of three imaging methods was analyzed in 167 women. The AUCs of all methods in discriminating between resectable and non-resectable tumor was 0.80 for ultrasound, 0.76 for CT, 0.71 for WB-DWI/MRI and 0.90 for surgical exploration. Ultrasound had the highest agreement (Cohen's kappa ranging from 0.59 to 0.79) compared to CT and WB-DWI/MRI to assess all parameters included in the updated PIV model., Conclusions: Ultrasound showed non-inferiority to CT and to WB-DWI/MRI in discriminating between resectable and non-resectable tumor using the updated PIV model. Ultrasound had the best agreement between imaging and intraoperative findings in the assessment of parameters included in the updated PIV model. Ultrasound is an acceptable method to assess abdominal disease and predict non-resectability in patients with tubo-ovarian cancer in the hands of specially trained ultrasound examiners., (Copyright © 2024. Published by Elsevier Inc.)

Objective: To assess the accuracy of pathological diagnosis by transvaginal ultrasound-guided biopsy versus surgery in patients with suspicious primary advanced tubo-ovarian carcinoma. The Feasibility, adequacy, and safety of the procedure were also evaluated., Methods: Consecutive women with pre-operative suspicious primary advanced tubo-ovarian carcinoma presenting between July 2019 and September 2021 were enrolled. Accuracy was calculated including only cases who underwent surgery. Feasibility was defined as the number of cases in which ultrasound-guided biopsy was possible according to tumor characteristics (morphology and site). Adequacy was defined as the number of conclusive diagnoses out of the samples collected. Safety was defined by the number of major complications which were defined as hospitalization, surgery, and/or blood transfusion., Results: A total of 278 patients were eligible for the study; 158 were enrolled, while 120 were excluded for logistic reasons or patient refusal. Ultrasound-guided biopsy was not feasible in 30 (19%) patients. The samples obtained in the remaining 128 patients were all adequate (100%), and no major complications were noted. A total of 26 (20%) patients started neoadjuvant chemotherapy on the basis of the diagnosis obtained by ultrasound, whereas 102 (80%) patients underwent surgery. Accuracy of ultrasound-guided biopsy versus surgery was 94% (96/102), with six false negative cases at ultrasound (6%). Site (prevesical peritoneum) and size (<8 mm) of the nodules resulted as major predictive factors for ultrasound-guided biopsy failure (false negative). Ultrasound-guided biopsy correctly identified 86 primary invasive tubo-ovarian carcinomas and 10 metastatic tumors., Conclusion: Ultrasound-guided biopsy is a feasible, safe, and accurate method to provide histological diagnosis in suspicious advanced tubo-ovarian cancer patients., Competing Interests: Competing interests: None declared., (© IGCS and ESGO 2023. No commercial re-use. See rights and permissions. Published by BMJ.)