An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset.

It is critical to quantitatively analyse the developing human fetal brain in order to fully understand neurodevelopment in both normal fetuses and those with congenital disorders. To facilitate this analysis, automatic multi-tissue fetal brain segmentation algorithms are needed, which in turn requires open datasets of segmented fetal brains. Here we introduce a publicly available dataset of 50 manually segmented pathological and non-pathological fetal magnetic resonance brain volume reconstructions across a range of gestational ages (20 to 33 weeks) into 7 different tissue categories (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, deep grey matter, brainstem/spinal cord). In addition, we quantitatively evaluate the accuracy of several automatic multi-tissue segmentation algorithms of the developing human fetal brain. Four research groups participated, submitting a total of 10 algorithms, demonstrating the benefits the dataset for the development of automatic algorithms

Treatment of NF1-associated Optic Pathway/Hypothalamic Gliomas in Patients With Diencephalic Syndrome

Diencephalic syndrome is usually associated with tumors in the hypothalamic region, rarely occurring in patients with neurofibromatosis type 1 (NF1)-associated gliomas. We describe the clinical presentation and response to treatment in 3 patients with NF1 presenting with diencephalic syndrome as first symptom of optic pathway/hypothalamic glioma (OPHG). Because of the rarity of this constellation, knowledge about the clinical course and best treatment options for patients with NF1-associated OPHG and diencephalic syndrome is still limited. All 3 patients showed good response to treatment with normalization of body mass index and decrease in tumor volume within 6 months