Background: Gigantism is rare with the majority of cases caused by a growth hormone (GH)-secreting pituitary adenoma. Treatment options for GH-secreting pituitary adenomas have been widened with the availability of long-acting dopamine agonists, depot preparations of somatostatin analogues, and recently the GH receptor antagonist pegvisomant.
Case Report: A 23-year-old male patient presented with continuous increase in height during the past 6 years due to a GH-secreting giant pituitary adenoma. Because of major intracranial extension and failure of octreotide treatment to shrink the tumour, the tumour was partially resected by a trans-frontal surgical approach. At immunohistochemistry, the tumour showed a marked expression of GH and a sparsely focal expression of prolactin. Somatostatin receptors (sst) 1-5 were not detected. Tumour tissue weakly expressed dopamine receptor type 2. The Gs alpha subunit was intact. Conversion from somatostatin analogue to pegvisomant normalized insulin-like-growth-factor-I (IGF-I) levels and markedly improved glucose tolerance.
Conclusion: Pegvisomant is a potent treatment option in patients with pituitary gigantism. In patients who do not respond to somatostatin analogues, knowledge of the SST receptor status may shorten the time to initiation of pegvisomant treatment.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1055/s-2007-956172 | DOI Listing |
Medicine (Baltimore)
November 2024
The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
The etiological basis of pituitary neuroendocrine tumors is uncertain. We used Mendelian randomization technique to investigate the potential influence of several risk factors on the likelihood of developing pituitary neuroendocrine tumors. We admitted 8 risk factors, divided into 3 lifestyle factors and 5 chronic diseases as exposure factors.
View Article and Find Full Text PDFCancer Metab
January 2025
Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China.
Invasiveness of pituitary adenoma is the main cause of its poor prognosis, mechanism of which remains largely unknown. In this study, the differential proteins between invasive and non-invasive pituitary tumors (IPA and NIPA) were identified by TMT labeled quantitative proteomics. The differential metabolites in venous bloods from patients with IPA and NIPA were analyzed by untargeted metabolomics.
View Article and Find Full Text PDFBackground: 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 PDFSci 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 PDFWorld 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.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!