Rathke's cleft cyst classification and outcomes after endoscopic endonasal approach

Background: Rathke's cleft cyst is rare, with variable characteristics and no unified categorization system. This study aimed to evaluate long-term outcomes, based on different categorizations, of symptomatic Rathke's cleft cysts treated with endoscopic endonasal approach. Methods: This retrospective study of 38 patients with symptomatic Rathke's cleft cyst treated with endoscopic endonasal approach from 2006/06–2021/08 recorded pre- and post-operative clinical presentation, endocrine and visual tests, radiological findings, and resection status. Rathke's cleft cysts were categorized by both cyst consistency and radiological features and clinical characteristics were analyzed. Results: The most common pre-operative symptoms were visual field deficit (65.8%) and hypopituitarism (39.5 %). Visual field deficit improved in 84% of affected patients, and hyperprolactinemia improved in 80% of affected patients. Pre-operative hypothyroidism and hypogonadism were associated with radiological type 3 cysts, while headache was more common in type B and C. Type 3 cysts were also associated post-operative hypogonadism and hypothyroidism. Permanent Diabetes insipidus was found in 3 patients (7.9%). Cyst height was a significant factor related to pre-operative visual field deficit and post-operative Diabetes insipidus. Residual cysts were found in 11 cases (30.6%) and 9 patients experienced regrowth/recurrence. Residual cysts were a significant factor in regrowth/recurrence. Recurrence rate and post-operative complications were not correlated with different subtypes. Conclusions: Endoscopic endonasal approach for removal of Rathke's cleft cyst is a safe and effective intervention. It leads to significant improvement in visual field deficit and recovery of hyperprolactinemia. Although the incidence of post-operative Diabetes insipidus is high, it is usually temporary. Although different categorizations are not correlated to recurrence rate, they could help predict the status of hormone deficit.