Quantifying hypothalamic and pituitary dysfunction in children with brain tumours and congenital diseases: an imaging and neuropeptide study
Year: 2026
Type: dissertation
Study design: Observational Study
Abstract: Background: Hypothalamic dysfunction (HD) is a devastating, poorly characterised and untreatable condition affecting a growing cohort of children with previously life-limiting disorders. The absence of reliable biomarkers and neuroimaging correlates hampers diagnostic precision and personalised treatments. Aim: To prospectively quantify the burden of HD across a diverse paediatric neuroendocrine disease cohort using a multidimensional framework integrating novel clinical scores, advanced neuroimaging, and biomarker analyses. Methods: Sixty-six participants (mean age 12.4 ± 3.1 years; 35 male, 31 female), were followed for 8.2 ± 4.0 years. Assessments comprised: Clinical HD and quality of life (PedsQL) scores; visual, learning, neuro-behavioural phenotypes; High-resolution MRI for quantitative hypothalamo-pituitary volumetry and regional injury scoring (including CISS sequences); novel biomarker profiling. Results: HD affected 77% of congenital and 86% of acquired cohorts, evolving rapidly in tumour cohorts, with tumour regrowth and surgery. PedsQL was markedly reduced – comparable to cerebral palsy - and driven by neuro-behavioural difficulties and neuroendocrine/hypothalamic dysfunction, rather than visual loss. Neuroimaging revealed: i) previously undetectable stalks via CISS, ii) reduced hypothalamic volumes in all ROHHAD(NET) and most SOD cases, iii) associations between biomarkers, neuroimaging, and clinical outcomes towards diagnostic thresholds, v) hypothalamic regional injury patterns: anterior with neuroendocrine, thermoregulatory, visual, and learning phenotypes; tuberal/posterior with thirst, appetite, sleep, and emotional disturbances. Biomarker analyses demonstrated: i) unstimulated copeptin as a general HD marker over and above AVP deficiency; ii) post-surgical AVP and oxytocin deficits; iii) oxytocin deficiency associated with neuro-behavioural phenotypes; iv) POMC/α-MSH and AgRP reflecting disease type and severity of obesity; iv) GLP-1 and BDNF correlating with obesity and neuro-ophthalmic phenotypes. Conclusions: Prospective quantification of HD burden is feasible across aetiologies and provides mechanistic insights and phenotype prediction. Validation in larger cohorts, supported by AI-driven imaging, may enable earlier diagnosis of HD and personalised therapeutic and preventative strategies to improve resulting morbidity and QL.
Author: Cerbone, Manuela
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7221495915