Immunophenotype of uterine tumor resembling ovarian sex cord tumor (UTROSCT): Case series and meta-analysis of the literature.

Objectives: This study aimed to define the frequency of positivity of several immunohistochemical markers in uterine tumor resembling ovarian sex cord tumor (UTROSCT).

Methods: All consecutive UTROSCT cases were retrieved from consultation files of one of the authors. Histological and immunohistochemical slides were reviewed.

Risk of Stroke or Heart Attack in Mild Cognitive Impairment and Subjective Cognitive Impairment.

Background: The study aimed to identify Mild Cognitive Impairment (MCI) as an alert clinical manifestation of increased probability of major acute vascular events (MVEs), such as Ischemic Stroke and heart attack.

Methods: In a longitudinal study, 181 (M = 81, F = 100; mean age of 75.8 ± 8.

Micropapillary pattern in serous borderline ovarian tumor and the risk of extraovarian localization of low-grade serous carcinoma ('invasive implants'): A systematic review and meta-analysis.

In serous borderline ovarian tumor (SBOT), a micropapillary (MP) pattern has been considered analogous to intraepithelial low-grade serous carcinoma (LGSC). On this account, it is reasonable to hypothesize that MP-SBOT is more likely to be associated with extraovarian LGSC localizations (also referred to as 'invasive implants') compared to conventional SBOT. The aim of this study was to investigate the potential association between a MP pattern and invasive implants in SBOT.

Assessing the impact of deep-learning assistance on the histopathological diagnosis of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes.

In recent years, it has become clear that artificial intelligence (AI) models can achieve high accuracy in specific pathology-related tasks. An example is our deep-learning model, designed to automatically detect serous tubal intraepithelial carcinoma (STIC), the precursor lesion to high-grade serous ovarian carcinoma, found in the fallopian tube. However, the standalone performance of a model is insufficient to determine its value in the diagnostic setting.

Beyond the WHO 2020 Classification of Female Genital Tumors: Types of Endometrial Cancer: A Pathological and Molecular Focus on Challenging Rare Variants.

Endometrial carcinoma is a heterogeneous group of malignancies characterized by distinct histopathological features and genetic underpinnings. The 2020 WHO classification has provided a comprehensive framework for the categorization of endometrial carcinoma. However, it has not fully addressed the spectrum of uncommon entities that are currently not recognized by the 2020 WHO and have only been described in the form of small case series and case reports.