We report the case of a 29-yr-old woman who first presented an aseptic meningitis at the beginning of a pregnancy. She was admitted one month later with headaches and vomiting. Panhypopituitarism with diabetes insipidus was diagnosed. Magnetic resonance imaging (MRI) data suggested the existence of lymphocytic infundibulohypophysitis, with inflammation of the suprasellar area. No new symptoms were noticed until 6 months later when this patient pointed out troubles of the visual field, due to a compression of the optic chiasma. Three boluses of 1 g methylprednisolone were prescribed, with no effects. After delivery, the defects of the visual field increased. A neurosurgical intervention was decided. Diagnosis of Rathke's cleft cyst (RCC) was made. We concluded that this patient presented a rupture of a RCC, which occurred at the beginning of pregnancy, associated later with panhypopituitarism with diabetes insipidus, due to a probable hypophysitis. The end of the pregnancy was marked by consequences of an increased volume of the RCC. To our knowledge, this case is the first described during pregnancy.
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http://dx.doi.org/10.1007/BF03344108 | DOI Listing |
World Neurosurg
January 2025
Department of Neurosurgery, The Ohio State University and Wexner Medical Centre, Columbus, Ohio, USA. Electronic address:
Background: Epidermoid cyst (EC) located completely within the pituitary infundibulum is a rare entity with only seven reported cases. In this study, we have described our experience with resection of intra-infundibular epidermoid cysts (IECs) and reviewed the existing literature highlighting its distinguishing features and operative nuances.
Methods: Three consecutive cases of IEC operated at our institute was retrospectively studied.
J Neurosurg Case Lessons
January 2025
Department of Neurosurgery, Stanford University School of Medicine, Stanford, California.
Background: The co-occurrence of Rathke cleft cysts (RCCs) and meningiomas in the sellar and parasellar regions represents an exceedingly rare clinical entity. Achieving maximal resection through a single operative approach while minimizing adverse events is challenging, often necessitating multiple surgical approaches, as suggested by previous reports.
Observations: The authors report the case of a 49-year-old female with a history of kidney transplant who presented with headaches and was diagnosed with coexisting RCC and meningioma in the sellar and planum sphenoidale regions, respectively.
J Neurosurg Case Lessons
January 2025
Department of Neurological Surgery, University of California, San Diego, La Jolla, California.
Background: Rathke cleft cysts (RCCs) are benign sellar/suprasellar lesions that result from mucin-secreting vestigial remnants within the pars intermedia of the pituitary gland. When symptomatic, they can present with retro-orbital headaches, visual field defects, and/or pituitary dysfunction.
Observations: A 35-year-old female presented with subacute retro-orbital headache, right ptosis, and blurred vision.
BMJ Case Rep
January 2025
Radiology, The Aga Khan University, Karachi, Sindh, Pakistan
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.
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