Aim: Pituitary adenomas do not have a single factor of aggressive behavior or recurrence. The objective of this study was to determine factors influencing the prognosis in pituitary adenomas.
Material And Methods: 243 patients who were operated between January 2000 and June 2012 were included in this retrospective study. Demographic data, age at diagnosis, date of diagnosis, date of operation, type of operation, post-operative medications, pre- and postoperative hormone levels, and MRI findings were evaluated in each patient.
Results: The rate of total resection of sellar tumors was less than 50% in our patient population. The prognosis was better in cases with total resection. Tumor size was a poor prognostic factor in sellar tumors. Female sex was a poor prognostic factor in acromegaly and male sex in prolactinoma. The prognosis was worse in patients with cavernous sinus invasion. In acromegaly, pre-operative level of 850 ng/ml for IGF-1 was noted as a possible prognostic cut-off value.
Conclusion: Long-term follow-up results of our study suggest that factors common to all sellar tumors including tumor type, tumor size, total resection, and cavernous sinus invasion and tumor type-specific factors including sex and hormone levels play important roles in the prognosis.
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http://dx.doi.org/10.5137/1019-5149.JTN.9140-13.1 | DOI Listing |
Cureus
December 2024
Department of Pathology, Section of Oncopathology and Morphological Pathology, Faculty of Medicine, University of Miyazaki, Miyazaki, JPN.
Immature pituitary-specific transcription factor 1 (PIT1)-lineage pituitary neuroendocrine tumors are composed of PIT1-lineage cells with cytological atypia and limited differentiation. These tumors are rare and no cytological features of this neoplasm have been reported. This study is the first to report the cytological features of an immature PIT1-lineage tumor.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Pediatrics and Pediatric Hematology/Oncology, University Children's Hospital, Carl Von Ossietzky Universität, Klinikum Oldenburg AöR, Rahel-Straus-Straße 10, 26133, Oldenburg, Germany.
Survivors of sellar/suprasellar tumors involving hypothalamic structures face a risk of impaired quality of life, including tumor- and/or treatment-related hypothalamic obesity (TTR-HO) defined as abnormal weight gain resulting in severe persistent obesity due to physical, tumor- and/or treatment related damage of the hypothalamus. We analyze German claims data to better understand treatment pathways for patients living TTR-HO during the two years following the index surgical treatment. A database algorithm identified patients with TTR-HO in a representative German payer claims database between 2010 and 2021 (n = 5.
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.
Cureus
December 2024
Department of Technology and Clinical Trials, Advanced Research, Deerfield Beach, USA.
This paper investigates the potential of artificial intelligence (AI) and machine learning (ML) to enhance the differentiation of cystic lesions in the sellar region, such as pituitary adenomas, Rathke cleft cysts (RCCs) and craniopharyngiomas (CP), through the use of advanced neuroimaging techniques, particularly magnetic resonance imaging (MRI). The goal is to explore how AI-driven models, including convolutional neural networks (CNNs), deep learning, and ensemble methods, can overcome the limitations of traditional diagnostic approaches, providing more accurate and early differentiation of these lesions. The review incorporates findings from critical studies, such as using the Open Access Series of Imaging Studies (OASIS) dataset (Kaggle, San Francisco, USA) for MRI-based brain research, highlighting the significance of statistical rigor and automated segmentation in developing reliable AI models.
View Article and Find Full Text PDFCureus
December 2024
Department of Neurosurgery, NMC Royal Hospital, Abu Dhabi, ARE.
Patients presenting with acute onset of headache and ophthalmoplegia are clinically diagnosed as having a pituitary adenoma with apoplexy. Rarely, other diseases can mimic this condition clinically and radiologically, requiring a high index of suspicion to reach the correct diagnosis. We present a case of a 37-year-old male of Indian origin, who had intra- and supra-sellar tuberculosis (TB), presenting with classical clinical features of pituitary apoplexy and constitutional symptoms.
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