Lesions sub-diagnostic of endometrioid intra-epithelial neoplasia/atypical hyperplasia: value of morphology and immunohistochemistry in predicting neoplastic outcome.

Aims: Areas of gland crowding that do not fulfil diagnostic criteria of endometrioid intra-epithelial neoplasia (EIN) are often encountered in endometrial biopsies. In this study, we document the prevalence of neoplastic outcome in patients with these subdiagnostic lesions (SL) and assess the utility of morphological features and a three-marker immunohistochemistry panel (PAX2, PTEN, beta-catenin) to predict outcome.

Methods And Results: Of 430 women with SL on endometrial sampling at Brigham and Women's Hospital between 2001 and 2021 with available follow-up biopsy, 72 (17%) had a neoplastic outcome (EIN or endometrioid carcinoma).

Hypertension and Risk of Endometrial Cancer: A Pooled Analysis in the Epidemiology of Endometrial Cancer Consortium (E2C2).

Background: The incidence rates of endometrial cancer are increasing, which may partly be explained by the rising prevalence of obesity, an established risk factor for endometrial cancer. Hypertension, another component of metabolic syndrome, is also increasing in prevalence, and emerging evidence suggests that it may be associated with the development of certain cancers. The role of hypertension independent of other components of metabolic syndrome in the etiology of endometrial cancer remains unclear.

Measuring Digital Pathology Throughput and Tissue Dropouts.

Background: Digital pathology operations that precede viewing by a pathologist have a substantial impact on costs and fidelity of the digital image. Scan time and file size determine throughput and storage costs, whereas tissue omission during digital capture ("dropouts") compromises downstream interpretation. We compared how these variables differ across scanners.

Endometrial Tumor Classification by Histomorphology and Biomarkers in the Nurses' Health Study.

Objective: Endometrial cancers have historically been classified by histomorphologic appearance, which is subject to interobserver disagreement. As molecular and biomarker testing has become increasingly available, the prognostic significance and accuracy of histomorphologic diagnoses have been questioned. To address these issues for a large, prospective cohort study, we provide the results of a centralized pathology review and biomarker analysis of all incidental endometrial carcinomas occurring between 1976 and 2012 in the Nurses' Health Study.

Machine Learning Photovoltaic String Analyzer.

Photovoltaic (PV) system energy production is non-linear because it is influenced by the random nature of weather conditions. The use of machine learning techniques to model the PV system energy production is recommended since there is no known way to deal well with non-linear data. In order to detect PV system faults, the machine learning models should provide accurate outputs.

Computational augmentation of neoplastic endometrial glands in digital pathology displays.

The pathologic diagnosis of neoplasia requires localization and classification of lesional tissue, a process that depends on the recognition of an abnormal spatial distribution of neoplastic elements relative to admixed normal background tissue. In endometrial intraepithelial neoplasia (EIN), a pre-cancer usually managed by hysterectomy, a clonally mutated proliferation of cytologically altered glands ('neoplastic-EIN') aggregates in clusters that also contain background non-neoplastic glands ('background-NL'). Here, we used image analysis to classify individual glands within endometrial tissue fragments as neoplastic-EIN or background-NL, and we used the distribution of predictions to localize foci diagnostic of EIN.

Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks.

Background: Ovarian cancer causes 151,900 deaths per year worldwide. Treatment and prognosis are primarily determined by the histopathologic interpretation in combination with molecular diagnosis. However, the relationship between histopathology patterns and molecular alterations is not fully understood, and it is difficult to predict patients' chemotherapy response using the known clinical and histological variables.

A New Classification of Benign, Premalignant, and Malignant Endometrial Tissues Using Machine Learning Applied to 1413 Candidate Variables.

Benign normal (NL), premalignant (endometrial intraepithelial neoplasia, EIN) and malignant (cancer, EMCA) endometria must be precisely distinguished for optimal management. EIN was objectively defined previously as a regression model incorporating manually traced histologic variables to predict clonal growth and cancer outcomes. Results from this early computational study were used to revise subjective endometrial precancer diagnostic criteria currently in use.

Issues in the Differential Diagnosis of Uterine Low-grade Endometrioid Carcinoma, Including Mixed Endometrial Carcinomas: Recommendations from the International Society of Gynecological Pathologists.

This article provides practical recommendations developed from the International Society of Gynecological Pathologists Endometrial Carcinoma Project to address 4 issues that may arise in the diagnosis of uterine corpus low-grade endometrioid carcinoma: (1) The distinction between atypical hyperplasia and low-grade endometrioid carcinoma. (2) The distinction between low-grade endometrioid carcinoma and serous carcinoma. (3) The distinction between corded and hyalinized or spindle cell variants of low-grade endometrioid carcinoma and carcinosarcoma.

Implementing the DICOM Standard for Digital Pathology.

Background: Digital Imaging and Communications in Medicine (DICOM) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network.

A general framework dedicated to computational morphogenesis Part I - Constitutive equations.

In order to understand living organisms, considerable experimental efforts and resources have been devoted to correlate genes and their expressions with cell, tissue, organ and whole organisms' phenotypes. This data driven approach to knowledge discovery has led to many breakthrough in our understanding of healthy and diseased states, and is paving the way to improve the diagnosis and treatment of diseases. Complementary to this data-driven approach, computational models of biological systems based on first principles have been developed in order to deepen our understanding of the multi-scale dynamics that drives normal and pathological biological functions.

Computational morphogenesis - Embryogenesis, cancer research and digital pathology.

Overall survival benefits of cancer therapies have, in general, fallen short of what was expected from them. By examining the many parallels that exist between embryogenesis and carcinogenesis, we discuss how clinical and fundamental cancer research can benefit from computational morphogenesis (CM) insofar as carcinogenesis is causally related to altered mechanisms underlying embryogenesis and post-embryonic tissue homeostasis. We also discuss about the critical role played by digital pathology (DP) since it constitutes the main source of data for the model-fitting and validation of CM-generated virtual tissues.

Assessment of a Chemotherapy Response Score (CRS) System for Tubo-Ovarian High-Grade Serous Carcinoma (HGSC).

A chemotherapy response score (CRS) system was recently described to assess the histopathologic response and prognosis of patients with tubo-ovarian high-grade serous carcinoma (HGSC) receiving neoadjuvant chemotherapy. The current study was performed as an independent assessment of this CRS system. We retrospectively identified advanced stage HGSC patients who received neoadjuvant chemotherapy and underwent interval debulking.

Adiponectin, Leptin, and Insulin-Pathway Receptors as Endometrial Cancer Subtyping Markers.

Developing a system of molecular subtyping for endometrial tumors might improve insight into disease etiology and clinical prediction of patient outcomes. High body mass index (BMI) has been implicated in development of endometrial cancer through hormonal pathways and might influence tumor expression of biomarkers involved in BMI-sensitive pathways. We evaluated whether endometrial tumor expression of 7 markers from BMI-sensitive pathways of insulin resistance could effectively characterize molecular subtypes: adiponectin receptor 1, adiponectin receptor 2, leptin receptor, insulin receptor (beta subunit), insulin receptor substrate 1, insulin-like growth factor 1 receptor, and insulin-like growth factor 2 receptor.

Diagnostic and Treatment Reproducibility of Cervical Intraepithelial Neoplasia / Squamous Intraepithelial Lesion and Factors Affecting the Diagnosis.

Objective: Inter-observer differences in the diagnosis of HPV related cervical lesions are problematic and response of gynecologists to these diagnostic entities is non-standardized. This study evaluated the diagnostic reproducibility of "cervical intraepithelial neoplasia" (CIN) and "squamous intraepithelial lesion" (SIL) diagnoses.

Material And Method: 19 pathologists evaluated 66 cases once using H&E slides and once with immunohistochemical studies (p16, Ki-67 and Pro-ExC).

Endometrial Cancer Risk Factors, Hormone Receptors, and Mortality Prediction.

Endometrial tumors arise from a hormonally responsive tissue. Defining subtypes by hormone receptor expression might better inform etiology and prediction of patient outcomes. We evaluated the potential role of tumor estrogen receptor (ER) and progesterone receptor (PR) expression to define endometrial cancer subtypes.

Toxicology Study of Single-walled Carbon Nanotubes and Reduced Graphene Oxide in Human Sperm.

Carbon-based nanomaterials such as single-walled carbon nanotubes and reduced graphene oxide are currently being evaluated for biomedical applications including in vivo drug delivery and tumor imaging. Several reports have studied the toxicity of carbon nanomaterials, but their effects on human male reproduction have not been fully examined. Additionally, it is not clear whether the nanomaterial exposure has any effect on sperm sorting procedures used in clinical settings.

Sperm processing for advanced reproductive technologies: Where are we today?

Assisted reproductive technologies (ARTs) utilize sperm sorting methods to select viable sperm from the semen samples. Conventional sperm sorting techniques in current use are density gradient centrifugation, direct swim-up, and conventional swim-up. These methods use multiple centrifugation steps, which have been shown to generate reactive oxygen species (ROS) that decrease DNA integrity and damage sperm.

Dyssynchronous secretory endometrial glands often show sporadically acquired progesterone nonresponsiveness.

Primary sporadic gene-inactivating events within the progesterone response cascade might explain the presence of individual dyssynchronous (outlier) glands commonly observed in a secretory background. We queried morphologically dyssynchronous glands in mid-secretory endometrium with a series of markers normally downregulated by progesterone. Seventy-nine mid-secretory endometrial biopsies were stained with hematoxylin and eosin, MIB-1, PAX2, estrogen and progesterone receptors, and PTEN.

Biomarker resolution of uterine smooth muscle tumor necrosis as benign vs malignant.

Uterine leiomyosarcomas are rare malignant tumors with a poor prognosis while leiomyomas are common benign tumors unrelated to their malignant counterparts. Diagnostic features commonly present in leiomyosarcoma include cytologic atypia, high mitotic index, and a sarcoma-specific geographic cell death designated 'tumor cell necrosis (TCN)'. TCN has a sharp viable-nonviable boundary lacking inflammation, fibrosis or granulation tissue seen in nonspecific infarction.

ARID1A is a useful marker of malignancy in peritoneal washings for endometrial carcinoma.

Background: ARID1A (AT-rich interactive domain 1A gene) has recently been identified as a novel tumor suppressor gene and one of the driver genes in endometrial carcinogenesis. Approximately 30% to 40% of endometrial carcinomas harbor mutations in the ARID1A gene, which results in complete loss of ARID1A protein expression. Although ARID1A aberrations are not restricted to endometrial cancer, the authors hypothesized that it might be a useful marker of malignancy in peritoneal washings for patients with endometrial cancer.