Evaluating patients for infertility is common in the primary care setting and can involve multiple differentials and treatment options. This case report describes a 34-year-old woman whose infertility evaluation led to the diagnosis of a pituitary adenoma.
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Background: Acromegaly, although rare, is associated with multiple manifestations and complications; its high morbidity and mortality makes it a challenge. Treatment involves surgery and pharmacological therapies, focusing on biochemical normalization. This study analyzes the biochemical control in Colombian patients with acromegaly, seeking to improve the understanding of the effects of treatments in the management of the disease.
View Article and Find Full Text PDFA hybrid explainable model based on advanced machine learning and deep learning models for classifying brain tumors using MRI images.
Sci Rep
January 2025
Institute of Optoelectronics, Military University of Technology, Gen. S. Kaliskiego 2, Warsaw, 00-908, Poland.
Brain tumors present a significant global health challenge, and their early detection and accurate classification are crucial for effective treatment strategies. This study presents a novel approach combining a lightweight parallel depthwise separable convolutional neural network (PDSCNN) and a hybrid ridge regression extreme learning machine (RRELM) for accurately classifying four types of brain tumors (glioma, meningioma, no tumor, and pituitary) based on MRI images. The proposed approach enhances the visibility and clarity of tumor features in MRI images by employing contrast-limited adaptive histogram equalization (CLAHE).
View Article and Find Full Text PDFPredictive Modeling of Non-functioning Giant Pituitary Neuroendocrine Tumor Resection: A Multi-Planar Perspective.
World Neurosurg
January 2025
Department of Neurosurgery, Emory University, Atlanta, Georgia, USA; Department of Otolaryngology, Emory University, Atlanta, Georgia, USA. Electronic address:
Background: Giant pituitary neuroendocrine tumor (GPitNET) are challenging tumors with low rates of gross total resection (GTR) and high morbidity. Previously reported machine-learning (ML) models for prediction of pituitary neuroendocrine tumor extent of resection (EOR) using preoperative imaging included a heterogenous dataset of functional and non-functional pituitary neuroendocrine tumors of various sizes leading to variability in results.
Objective: The aim of this pilot study is to construct a ML model based on the multi-dimensional geometry of tumor to accurately predict the EOR of non-functioning GPitNET.
Progress in investigating pituitary stalk lesions: A review.
Medicine (Baltimore)
January 2025
Department of Endocrinology and Metabolism, Affiliated Hospital of Jining Medical University, Jining, Shandong, P.R. China.
Pituitary stalk lesions are uncommon and are typically identified through pituitary magnetic resonance imaging and screening for causes of diabetes insipidus. Recent literature indicates that pituitary stalk lesions primarily manifest as pituitary stalk interruption syndrome and thickening of the pituitary stalk. The etiology of these lesions is complex and can be divided into major categories: congenital disorders, inflammatory or infectious diseases, and tumors.
View Article and Find Full Text PDFHyperprolactinemia complicated with peliosis hepatis: One case report and review of literature.
Medicine (Baltimore)
January 2025
Department of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Rationale: Peliosis hepatis (PH) is a rare disease with few clinical reports and complex etiology. However, there have been no reports of hyperprolactinemia (HPRL) leading to PH at present. This paper, through case reports, expands the understanding of the etiology of PH and the pathological damage effect of prolactin (PRL).
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