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.
Acute patella dislocations account for approximately 2%–3% of knee injuries and are therefore a relatively common presentation in the accident and emergency department. The majority of patella dislocations can be reduced with simple manoeuvres or even spontaneously and can be managed conservatively by bracing and rehabilitation. The aim of this study is to identify and review the main causes of the unique and unexpected event of irreducible patella dislocation and their characteristic presentations. Irreducible patella dislocations can happen but are very rare. Currently, a limited number of case reports are available, prompting for a need for research on this topic. This case study can shed light on the possible pathogenesis and pathognomonic features of irreducible patella dislocations and provide insight on the available therapeutic approaches.
Purpose: Computer-assisted tissue image analysis (CATIA) enables an optical biopsy of human tissue during minimally invasive surgery and endoscopy. Thus far, it has been implemented in gastrointestinal, endometrial, and dermatologic examinations that use computational analysis and image texture feature systems. We review and evaluate the impact of in vivo optical biopsies performed by tissue image analysis on the surgeon’s diagnostic ability and sampling precision and investigate how operation complications could be minimized. Methods: We performed a literature search in PubMed, IEEE, Xplore, Elsevier, and Google Scholar, which yielded 28 relevant articles. Our literature review summarizes the available data on CATIA of human tissues and explores the possibilities of computer-assisted early disease diagnoses, including cancer. Results: Hysteroscopic image texture analysis of the endometrium successfully distinguished benign from malignant conditions up to 91% of the time. In dermatologic studies, the accuracy of distinguishing nevi melanoma from benign disease fluctuated from 73% to 81%. Skin biopsies of basal cell carcinoma and melanoma exhibited an accuracy of 92.4%, sensitivity of 99.1%, and specificity of 93.3% and distinguished nonmelanoma and normal lesions from benign precancerous lesions with 91.9% and 82.8% accuracy, respectively. Gastrointestinal and endometrial examinations are still at the experimental phase. Conclusions: CATIA is a promising application for distinguishing normal from abnormal tissues during endoscopic procedures and minimally invasive surgeries. However, the efficacy of computer-assisted diagnostics in distinguishing benign from malignant states is still not well documented. Prospective and randomized studies are needed before CATIA is implemented in clinical practice.
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