Faculty Bibliography

PURPOSE/OBJECTIVE:Hypophysitis can clinically and radiologically mimic other nonfunctioning masses of the sella turcica, complicating preoperative diagnosis. While sellar masses may be treated surgically, hypophysitis is often treated medically, so differentiating between them facilitates optimal management. The objective of our study was to develop a scoring system for the preoperative diagnosis of hypophysitis. METHODS:A thorough literature review identified published hypophysitis cases, which were compared to a retrospective group of non-functioning pituitary adenomas (NFA) from our institution. A preoperative hypophysitis scoring system was developed and internally validated. RESULTS:Fifty-six pathologically confirmed hypophysitis cases were identified in the literature. After excluding individual cases with missing values, 18 hypophysitis cases were compared to an age- and sex-matched control group of 56 NFAs. Diabetes insipidus (DI) (p < 0.001), infundibular thickening (p < 0.001), absence of cavernous sinus invasion (CSI) (p < 0.001), relation to pregnancy (p = 0.002), and absence of visual symptoms (p = 0.007) were significantly associated with hypophysitis. Stepwise logistic regression identified DI and infundibular thickening as positive predictors of hypophysitis. CSI and visual symptoms were negative predictors. A 6-point hypophysitis-risk scoring system was derived: + 2 for DI, + 2 for absence of CSI, + 1 for infundibular thickening, + 1 for absence of visual symptoms. Scores ≥ 3 supported a diagnosis of hypophysitis (AUC 0.96, sensitivity 100%, specificity 75%). The scoring system identified 100% of hypophysitis cases at our institution with an estimated 24.7% false-positive rate. CONCLUSIONS:The proposed scoring system may aid preoperative diagnosis of hypophysitis, preventing unnecessary surgery in these patients.

OBJECTIVE:Silent corticotroph adenomas (SCAs) behave more aggressively than other non-functioning adenomas (NFAs). This study aims to expand the body of knowledge of the behavior of SCAs. METHODS:Retrospective analysis of 196 non-corticotroph NFAs and 20 SCAs from 2012-2017 was completed. Demographics, clinical presentation, imaging and biochemical data were gathered. The primary endpoint was to identify features of SCAs vs. other NFAs that suggest aggressive disease, including pre-surgical comorbidities, postoperative complications, extent of tumor and recurrence. GRASP MRI images were obtained from a subset of SCAs and NFAs. Permeability data was obtained to compare signal-to-time curve variation between the two groups. RESULTS:With multivariate regression analysis, SCAs showed higher rates of hemorrhage on preoperative imaging than NFAs (p=0.017). SCAs presented more frequently with headache, vision changes and fatigue (p=0.012, p=0.041, p=0.028). SCAs exhibited greater extent of tumor burden with increased occurrence of stalk deviation, suprasellar invasion, optic chiasm compression and cavernous sinus invasion (p=0.008, p=0.021, p=0.022, p=0.015). On GRASP imaging, SCAs had significantly lower permeability of contrast than NFAs (p=0.001). 30% of SCAs were noted to recur with a 14% recurrence rate in other NFAs, though this difference was not of statistical significance (p=0.220). CONCLUSIONS:SCAs exhibit features of more aggressive disease. Interestingly, a significant increase in recurrence was not seen despite these features. The results of this study support the growing body of evidence that SCAs behave more aggressively than other NFPAs and was able to provide some insight into factors that may contribute to recurrence.

Prolactin is a polypeptide hormone that is well known for its role in reproductive physiology. Recent studies highlight its role in neurohormonal appetite regulation and metabolism. Elevated prolactin levels are widely associated with worsening metabolic disease, but it appears that low prolactin levels could also be metabolically unfavorable. This review discusses the pathophysiology of prolactin related metabolic changes, and the less commonly recognized effects of prolactin on adipose tissue, pancreas, liver, and small bowel. Furthermore, the effect of dopamine agonists on the metabolic profiles of patients with hyperprolactinemia are discussed as well.

OBJECTIVE:Prolactin secreting tumors respond well to medical management with a small fraction of patients requiring surgery. We conducted a systematic review and meta-analysis to study the determinants of surgical remission in these tumors. METHODS:We searched PubMed to identify eligible studies reporting postoperative remission in patients treated with transsphenoidal surgery for prolactinoma. Primary outcomes included postoperative remission, follow-up remission, and recurrence. Postoperative and follow-up remission were defined as normoprolactinemia at less than and greater than one-year post-operation respectively. Recurrence was defined as hyperprolactinemia after initial normalization of prolactin levels. Odds ratios (OR) were calculated, stratified by radiological size, tumor extension, and tumor invasion, and analyzed using a random-effects model meta-analysis. RESULTS:Thirty-five studies were included. Macroadenomas were associated with lower rates of postoperative remission OR 0.20, 95% confidence interval [CI] 0.16-0.24) and lower rates of remission at follow-up (OR 0.11, 95% CI 0.053-0.22). Postoperative remission was less likely in tumors with extra- or suprasellar extension (OR 0.16, 95% CI 0.06-0.43) and tumors with cavernous sinus invasion (OR 0.03, 95% CI 0.01-0.13). Female gender and absence of preoperative dopamine agonist (DA) treatment were also associated with higher remission rates. Across the included studies, there was considerable heterogeneity in each primary outcome (postoperative remission I2=94%, follow-up remission I2=86%, recurrence I2=68%). CONCLUSIONS:Transsphenoidal surgery for prolactinomas may be particularly effective in small, non-invasive, treatment naive tumors and may provide a viable first-line alternative to dopamine agonist therapy in such patients.

OBJECTIVE:Pituitary carcinoma is a rare tumor, defined as a tumor of adenohypophyseal cells with systemic or craniospinal metastasis. We present a case of a growth hormone (GH)-secreting pituitary carcinoma with a review of literature to better characterize this disease. DESIGN:Case report and literature review of 25 cases of GH-secreting pituitary carcinomas RESULTS: The age of diagnosis of GH-secreting carcinomas ranged 24-69 years old with a mean age of 44.4 with 52% of cases present in females. Mean latency period between diagnosis of acromegaly and transition to pituitary carcinoma was 11.4 years with mean survival being 3.4 years. CONCLUSION:Growth hormone (GH)-secreting pituitary carcinomas are rare and hard to distinguish from aggressive pituitary adenomas. From review of literature, treatment options include debulking surgery, radiotherapy, or chemotherapy with dismal outcomes. There are no diagnostic markers or features which can predict metastatic progression of these tumors. Future studies with genomic landscapes and relevant tumor markers are needed to identify pituitary tumors most likely to metastasize.

PURPOSE/OBJECTIVE:Both prolactinomas and nonfunctioning adenomas (NFAs) can present with hyperprolactinemia. Distinguishing them is critical because prolactinomas are effectively managed with dopamine agonists, whereas compressive NFAs are treated surgically. Current guidelines rely only on serum prolactin (PRL) levels, which are neither sensitive nor specific enough. Recent studies suggest that accounting for tumor volume may improve diagnosis. The objective of this study is to investigate the diagnostic utility of PRL, tumor volume, and imaging features in differentiating prolactinoma and NFA. METHODS:Adult patients with pathologically confirmed prolactinoma (n = 21) or NFA with hyperprolactinemia (n = 58) between 2013 and 2020 were retrospectively identified. Diagnostic performance of clinical and imaging variables was analyzed using receiver-operating characteristic curves to calculate area under the curve (AUC). RESULTS:with sensitivity of 100% and specificity of 82.76%. Binary logistic regression found that PRL was a significant positive predictor of prolactinoma diagnosis, whereas tumor volume, presence of CSI not previously defined, and T2 hyperintensity were significant negative predictors. The regression model had an AUC of 0.9915 (p < 0.0001). CONCLUSIONS:Consideration of tumor volume improves differentiation between prolactinomas and NFAs, which in turn leads to effective management.