Abstract

Abstract The optimal neurosurgical strategy for pediatric craniopharyngiomas is on debate with shifts from gross total resection to limited resections in combination with local radiotherapy. The most relevant question underlying this ongoing discussion is how to prevent additional surgical morbidity to the hypothalamus. Limited neurosurgical resection in combination with local radiotherapy has been proved a safe alternative to gross total resection concerning tumor control. Pre-operative anatomical grading of hypothalamic involvement has been proposed by Puget et al using MRI discriminating between no hypothalamic involvement (grade 0), hypothalamic displacement (grade 1), and hypothalamic disruption (grade 2). Subsequently, post-operative hypothalamic damage can also be assessed on post-op MRI by the grading of the Vile et al in no discernable damage (grade 0), abnormality of floor of third ventricle (grade 1), or damaged or deficient floor of third ventricle (grade 2). Three questions remain to be settled: 1. How to define pre-operatively the extent of resection 2. How to realize per-operatively the intended limited resection, and three. How to determine post-operatively the (additional) surgical damage to the hypothalamus. We retrospectively evaluated a series of 25 children with craniopharyngioma being resected in our center from June 2018 until January 2022, with pre- and post-operative grading of hypothalamic involvement. In total 11 patients were downgraded on the post-operative compared to the pre-operative scale; either by 1 grade (n=6) or by 2 grades (n=5). These findings illustrate that the preoperative grading score does not always represent the actual hypothalamic involvement. This complicates the definition of limited surgery pre-operatively and illustrates the importance of both how to integrate per-operative findings in the realization of the intended limited resection and how to evaluate hypothalamic damage caused by tumor growth versus neurosurgical intervention. A more detailed treatment algorithm will be discussed.

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