Endometrial cancer occurs in up to 29% of women before 40 years of age. Seventy percent of these patients are nulliparous at the time. Decision making regarding fertility preservation in early stage endometrial cancer (ES-EC) is, therefore, a big challenge since the decision between the risk of cancer progression and a chance to parenthood needs to be made. Sixty-two percent of women with complete remission of ES-EC after fertility-sparing treatment (FST) report to have a pregnancy wish which, if not for FST, they would not be able to fulfil. The aim of this review was to identify and summarise the currently established biomolecular and genetic prognostic factors that can facilitate decision making for FST in ES-EC. A comprehensive search strategy was carried out across four databases; Cochrane, Embase, MEDLINE, and PubMed; they were searched between March 1946 and 22nd December 2022. Thirty-four studies were included in this study which was conducted in line with the PRISMA criteria checklist. The final 34 articles encompassed 9165 patients. The studies were assessed using the Critical Appraisal Skills Program (CASP). PTEN and POLE alterations we found to be good prognostic factors of ES-EC, favouring FST. MSI, CTNNB1, and K-RAS alterations were found to be fair prognostic factors of ES-EC, favouring FST but carrying a risk of recurrence. PIK3CA, HER2, ARID1A, P53, L1CAM, and FGFR2 were found to be poor prognostic factors of ES-EC and therefore do not favour FST. Clinical trials with bigger cohorts are needed to further validate the fair genetic prognostic factors. Using the aforementioned good and poor genetic prognostic factors, we can make more confident decisions on FST in ES-EC.

Background: Malignant-associated abdominal wall endometriosis (AWE) is a rare pathology, likely to occur in 1% of scar endometriosis. The objectives of this study were to update the evidence on tumor degeneration arising from AWE to notify about the clinical characteristics, the different treatments offered to patients and their outcomes. Methods: A comprehensive systematic review of the literature was conducted. PubMed, Embase and Cochrane Library databases were used. Prospero (ID number: CRD42024505274). Results: Out of the 152 studies identified, 63 were included, which involved 73 patients. The main signs and symptoms were a palpable abdominal mass (85.2%) and cyclic pelvic pain (60.6%). The size of the mass varied between 3 and 25 cm. Mean time interval from the first operation to onset of malignant transformation was 20 years. Most common cancerous histological types were clear cell and endometrioid subtypes. Most widely accepted treatment is the surgical resection of local lesions with wide margins combined with adjuvant chemotherapy. The prognosis for endometriosis-associated malignancy in abdominal wall scars is poor, with a five-year survival rate of around 40%. High rates of relapse have been reported. Conclusions: Endometrial implants in the abdominal wall should be considered as preventable complications of gynecological surgeries. Special attention should be paid to women with a history of cesarean section or uterine surgery.

This review of our experience in computer-assisted tissue image analysis (CATIA) research shows that significant information can be extracted and used to diagnose and distinguish normal from abnormal endometrium. CATIA enabled the evaluation and differentiation between the benign and malignant endometrium during diagnostic hysteroscopy. The efficacy of texture analysis in the endometrium image during hysteroscopy was examined in 40 women, where 209 normal and 209 abnormal regions of interest (ROIs) were extracted. There was a significant difference between normal and abnormal endometrium for the statistical features (SF) features mean, variance, median, energy and entropy; for the spatial grey-level difference matrix (SGLDM) features contrast, correlation, variance, homogeneity and entropy; and for the gray-level difference statistics (GLDS) features homogeneity, contrast, energy, entropy and mean. We further evaluated 52 hysteroscopic images of 258 normal and 258 abnormal endometrium ROIs, and tissue diagnosis was verified by histopathology after biopsy. The YCrCb color system with SF, SGLDM and GLDS color texture features based on support vector machine (SVM) modeling correctly classified 81% of the cases with a sensitivity and a specificity of 78% and 81%, respectively, for normal and hyperplastic endometrium. New technical and computational advances may improve optical biopsy accuracy and assist in the precision of lesion excision during hysteroscopy. The exchange of knowledge, collaboration, identification of tasks and CATIA method selection strategy will further improve computer-aided diagnosis implementation in the daily practice of hysteroscopy.

Background: Human-centric artificial intelligence (HCAI) aims to provide support systems that can act as peer companions to an expert in a specific domain, by simulating their way of thinking and decision-making in solving real-life problems. The gynaecological artificial intelligence diagnostics (GAID) assistant is such a system. Based on artificial intelligence (AI) argumentation technology, it was developed to incorporate, as much as possible, a complete representation of the medical knowledge in gynaecology and to become a real-life tool that will practically enhance the quality of healthcare services and reduce stress for the clinician. Our study aimed to evaluate GAIDS’ efficacy and accuracy in assisting the working expert gynaecologist during day-to-day clinical practice. Methods: Knowledge-based systems utilize a knowledge base (theory) which holds evidence-based rules (“IF-THEN” statements) that are used to prove whether a conclusion (such as a disease, medication or treatment) is possible or not, given a set of input data. This approach uses argumentation frameworks, where rules act as claims that support a specific decision (arguments) and argue for its dominance over others. The result is a set of admissible arguments which support the final decision and explain its cause. Results: Based on seven different subcategories of gynaecological presentations—bleeding, endocrinology, cancer, pelvic pain, urogynaecology, sexually transmitted infections and vulva pathology in fifty patients—GAID demonstrates an average overall closeness accuracy of zero point eighty-seven. Since the system provides explanations for supporting a diagnosis against other possible diseases, this evaluation process further allowed for a learning process of modular improvement in the system of the diagnostic discrepancies between the system and the specialist. Conclusions: GAID successfully demonstrates an average accuracy of zero point eighty-seven when measuring the closeness of the system’s diagnosis to that of the senior consultant. The system further provides meaningful and helpful explanations for its diagnoses that can help clinicians to develop an increasing level of trust towards the system. It also provides a practical database, which can be used as a structured history-taking assistant and a friendly, patient record-keeper, while improving precision by providing a full list of differential diagnoses. Importantly, the design and implementation of the system facilitates its continuous development with a set methodology that allows minimal revision of the system in the face of new information. Further large-scale studies are required to evaluate GAID more thoroughly and to identify its limiting boundaries.

(1) Background: Acute patella dislocation (APD) is a prevalent knee injury, with rates between 5.8–77.8 per 100,000. APD often results in repeat lateral patella dislocations due to the instability of the medial patellofemoral ligament (MPFL). Non-operative treatments have a 50% recurrence rate. While autologous grafting for MPFL has been favored, surgeons are now exploring synthetic grafts. We aimed to assess the effectiveness of synthetic grafts in MPFL reconstruction surgeries for repeated patellar dislocations; (2) Methods: Our research was based on a thorough search from the National Institute of Health and Clinical Excellence Healthcare Databases, using the Modified Coleman Methodology Score for quality assessment; (3) Results: Six studies met the inclusion criteria. A total of 284 patients and 230 knees were included. Seventy-five percent of patients were graded to have excellent-good clinical outcomes using the Crosby and Insall Grading System. International Knee Documentation Committee score and Knee injury and Osteoarthritis Outcome Score scores showed 59% and 60% post-operative improvement, respectively; (4) Conclusions: All studies showed improvement in post-operative functional outcomes and report no serious adverse events. The 6 mm, LARS (Orthomedic Ltd., Dollard-des-Ormeaux, QC, Canada) proved to have the most improvement in post-operative outcomes when used as a double bundle graft.