Sellar Tumors

Analysis of Diffusion-Weighted and T2-Weighted Imaging in the Prediction of Distinct Granulation Patterns of Somatotroph Adenomas

OBJECTIVE

The heterogeneity of the somatotroph adenomas, especially for sparsely granulated (SG) and densely granulated (DG) subtypes, has attracted great attention in identifying their imaging biomarker. The purpose of the current study was to compare the diagnostic performance of diffusion-weighted and T2-weighted magnetic resonance imaging (MRI) sequences for preoperatively distinguishing the granulation patterns of somatotroph adenomas.

METHODS

Thirty-two patients with a clinical diagnosis of somatotroph adenomas from October 2018 to March 2023 were included in this study. Coronal diffusion-weighted imaging (DWI) and T2-weighted MRI sequence data were collected from 3.0T MRI and compared between SG and DG groups. The immunohistochemistry was used to confirm the electron microscopy pathologic subtypes and Ki67 expression levels of somatotroph adenomas postoperatively.

RESULTS

Patients in the SG group had significantly higher signal intensity (SI) ratio of DWI (rDWI) (P < 0.001), lower SI ratio of apparent diffusion coefficient (rADC) (P < 0.001), and higher SI ratio of T2-weighted imaging (P = 0.011). The combined diagnosis index of rDWI and rADC had the highest diagnostic efficiency in predicting SG adenomas (sensitivity, 93.3%; specificity, 88.2%; P < 0.001). The rDWI and rADC values had positive and negative correlations with the Ki67 index and tumor maximum diameter, respectively. Lower rADC×103 was an independent predictor for SG adenomas.

CONCLUSIONS

Our results indicated that compared with previously used T2-weighted imaging, the DWI sequence, especially the combined diagnosis index of rDWI and rADC, could more efficiently distinguish the granulation patterns of somatotroph adenomas preoperatively.

Applications and Integration of Radiomics for Skull Base Oncology

Radiomics, a quantitative approach to extracting features from medical images, represents a new frontier in skull base oncology. Novel image analysis approaches have enabled us to capture patterns from images imperceptible by the human eye. This rich source of data can be combined with a range of clinical features, holding the potential to be a noninvasive source of biomarkers. Applications of radiomics in skull base pathologies have centered around three common tumor classes: meningioma, sellar/parasellar tumors, and vestibular schwannomas. Radiomic investigations can be categorized into five domains: tumor detection/segmentation, classification between tumor types, tumor grading, detection of tumor features, and prognostication. Various computational architectures have been employed across these domains, with deep-learning methods becoming more common versus machine learning. Across radiomic applications, contrast-enhanced T1-weighted MRI images remain the most utilized sequence for model development. Efforts to standardize and connect radiomic features to tumor biology have facilitated more clinically applicable radiomic models. Despite the advancement in model performance, several challenges continue to hinder translatability, including small sample sizes and model training on homogenous single institution data. To recognize the potential of radiomics for skull base oncology, prospective, multi-institutional collaboration will be the cornerstone for a validated radiomic technology.

Sellar Mass in 2 Patients With Acute-Onset Headache and Visual Symptoms: Not Your Usual Pituitary Adenoma

Background/Objective

Clinical diagnosis of rare aggressive sellar malignancies requires a high index of suspicion. The objective was to report 2 patients with primary sellar atypical teratoid (AT)/rhabdoid tumor (RT) who presented with acute-onset headache and visual symptoms.

Case Report

Patient 1 was a 45-year-old woman who presented with 3 weeks of headache and 1 week of eye pain and diplopia. Magnetic resonance imaging (MRI) identified a 2.2-cm sellar mass. Pituitary hormone testing showed elevated prolactin and suppressed luteinizing hormone, follicle-stimulating hormone, and estradiol levels. Patient 2 was a 32-year-old woman who presented with 1 month of headache and 1 week of diplopia. MRI showed a 2.1-cm sellar mass. Hormonal test results were reportedly unremarkable. Both patients did not have a significant medical history. They each underwent transsphenoidal resection. Surgical histology and molecular studies were consistent with primary sellar AT/RT. After surgery, patient 1 developed bilateral blindness and was lost to follow-up. Patient 2 developed hypopituitarism; her visual symptoms improved temporarily but recurred 2 weeks later. Pituitary MRI showed sellar recurrence. She underwent further debulking, but the tumor recurred promptly again. Despite radiation therapy, she died 4 months after the original presentation.

Discussion

AT/RT appears to be the most aggressive sellar malignancy.

Conclusion

Based on the 2 cases presented and the literature, I conclude that rapidly progressive headache with subsequent visual impairment in women with large sellar masses is almost pathognomonic of sellar AT/RT.

Growth hormone after CNS tumor diagnosis: the fundamentals, fears, facts, and future directions

Growth hormone deficiency (GHD) may occur in pediatric patients with central nervous system (CNS) tumors at initial tumor presentation or later as treatment-related sequelae. While it is well recognized that growth hormone (GH) has beneficial effects on growth and endocrinopathies, there's often hesitancy by clinicians to initiate GH therapy for GHD after CNS tumor diagnosis due to the perceived increased risk of tumor recurrence. The available data is described here and based on this review, there is no evidence of increased risk of tumor recurrence or secondary malignancy in patients treated with GH after CNS tumor diagnosis. Further understanding of tumor biology and presence of downstream GH targets including insulin-like growth factor-1 (IGF-1) and insulin receptor activity is still needed.

Application of dural suturing in the endoscopic endonasal approach to the sellar region

Objectives

The endoscopic endonasal approach (EEA) is widely used in the treatment of cranial base tumors. Skull base reconstruction is a crucial part of EEA, which has a great impact on patients’ prognosis. In this study, we report our experience with sellar dural suturing in cranial base reconstruction and retrospectively analyze its effect.

Methods

The clinical data of 134 patients who suffered intraoperative CSF leakage and underwent EEA surgery in the Department of Neurosurgery of the First Affiliated Hospital of Nanjing Medical University from October 2018 to November 2020 were retrospectively collected and analyzed. According to whether sellar dural suturing was performed during the operation, they were divided into a suture group (55 cases) and a control group (79 cases).

Results

The results showed that dural suturing of the sellar floor effectively reduced the postoperative hospitalization duration (p = 0.026) and the use rates of lumbar drainage (p = 0.047), autologous fat transplantation (p = 0.038), and pedicled nasoseptal flaps (p = 0.026).

Conclusion

Sellar dural suturing under endoscopy is a promising and effective method for cranial base reconstruction in EEA surgery and is worthy of clinical application.

Sellar Glomus Tumor Misdiagnosed as Pituitary Adenoma: A Case Report and Review of the Literature

Glomus tumor is a rare mesenchymal tumor with an organ-like structure. Sellar glomus tumors are extremely rare with only six reported cases in the literature. Because of the lack of special clinical manifestations and imaging features, the disorder may be easily misdiagnosed as other sellar tumors, especially pituitary adenomas. Here, the present study showed a case of a 69-year-old male with hypopituitarism who was preliminarily misdiagnosed as non-functional pituitary adenoma.

Pituitary Metastasis From Urothelial Carcinoma: A Case Report and Review of the Diagnosis and Treatment of Pituitary Metastases

The sellar and parasellar regions are a rare site of brain metastasis, most commonly from breast and lung cancer. Pituitary metastasis (PM) often presents as the first sign of metastatic disease but may herald early disseminated cancer. The diagnosis of PM requires differentiation from a benign pituitary adenoma. Although this may be proven definitively via surgical biopsy, a constellation of clinical findings including oculomotor palsy, visual disturbances, retroorbital pain, and diabetes insipidus is more suggestive of PM. Imaging is neither sensitive nor specific for differentiation but may inform the broader clinical picture. Due to its rarity, treatment guidelines for PM lack consensus, often including a mixture of radiation and surgery. Gross resection is challenging because of the vascular, invasive nature of these lesions. Stereotactic radiosurgery may be used to good effect either alone or in addition to resection. Even with treatment, the prognosis is poor. In this article, we present the third reported case of urothelial carcinoma metastasis to the pituitary. In addition, we review the clinical presentation, diagnosis, and treatment options including surgical resection and radiosurgery.

A Nomogram for Preoperatively Predicting the Ki-67 Index of a Pituitary Tumor: A Retrospective Cohort Study

Background

The Ki-67 index is an indicator of proliferation and aggressive behavior in pituitary adenomas (PAs). This study aims to develop and validate a predictive nomogram for forecasting Ki-67 index levels preoperatively in PAs.

Methods

A total of 439 patients with PAs underwent PA resection at the Department of Neurosurgery in Jinling Hospital between January 2018 and October 2020; they were enrolled in this retrospective study and were classified randomly into a training cohort (n = 300) and a validation cohort (n = 139). A range of clinical, radiological, and laboratory characteristics were collected. The Ki-67 index was classified into the low Ki-67 index (<3%) and the high Ki-67 index (≥3%). Least absolute shrinkage and selection operator algorithm and uni- and multivariate logistic regression analyses were applied to identify independent risk factors associated with Ki-67. A nomogram was constructed to visualize these risk factors. The receiver operation characteristic curve and calibration curve were computed to evaluate the predictive performance of the nomogram model.

Results

Age, primary-recurrence subtype, maximum dimension, and prolactin were included in the nomogram model. The areas under the curve (AUCs) of the nomogram model were 0.694 in the training cohort and 0.658 in the validation cohort. A well-fitted calibration curve was also generated for the nomogram model. A subgroup analysis revealed stable predictive performance for the nomogram model. A correlation analysis revealed that age (R = −0.23; p < 0.01), maximum dimension (R = 0.17; p < 0.01), and prolactin (R = 0.16; p < 0.01) were all significantly correlated with the Ki-67 index level.

Conclusions

Age, primary-recurrence subtype, maximum dimension, and prolactin are independent predictors for the Ki-67 index level. The current study provides a novel and feasible nomogram, which can further assist neurosurgeons to develop better, more individualized treatment strategies for patients with PAs by predicting the Ki-67 index level preoperatively.