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Background The purpose of this study was to analyse less known clinical scenarios associated with idiopathic intracranial hypertension. Methods The study involved analysis of magnetic resonance imaging signs of idiopathic intracranial hypertension in patients with spontaneous rhinoliquorrhoea ( n = 7), in patients with temporal lobe epilepsy and surgically treated antero-inferior temporal lobe meningo-encephaloceles (n = 15), and in patients who developed clinical signs of idiopathic intracranial hypertension following the treatment of spontaneous intracranial hypotension ( n = 7). Results Three of six patients with spontaneous rhinoliquorrhoea and six of 15 operated patients with temporal lobe epilepsy due to temporal lobe meningo-encephaloceles showed magnetic resonance imaging signs of idiopathic intracranial hypertension and had a body mass index >30 kg/m2. Rebound high pressure headaches and sings of idiopathic intracranial hypertension occurred in seven of 44 surgically treated spontaneous intracranial hypotension patients. Conclusions Magnetic resonance imaging findings should guide the clinician to consider (idiopathic) intracranial hypertension when patients develop spontaneous rhinoliquorrhoea, temporal lobe epilepsy secondary to temporal lobe meningoencephaloceles or high pressure headaches in spontaneous intracranial hypotension. Whether idiopathic intracranial hypertension must be regarded as a differential diagnosis or as a cause, or whether there are common pathophysiological pathways that lead to signs of idiopathic intracranial hypertension in this wider spectrum of disease is the focus of further study.

The aim of this study was to evaluate whether ganglioglioma (GGL), dysembryoplastic neuroepithelial tumour (DNET) and FCD (focal cortical dysplasia) are distinguishable through diffusion tensor imaging. Additionally, it was investigated whether the diffusion measures differed in the perilesional (pNAWM) and in the contralateral normal appearing white matter (cNAWM). Six GGLs, eight DNETs and seven FCDs were included in this study. Quantitative diffusion measures, that is, axial, radial and mean diffusivity and fractional anisotropy, were determined in the lesion identified on isotropic T2 or FLAIR-weighted images and in pNAWM and cNAWM, respectively. DNET differed from FCD in mean diffusivity, and GGL from FCD in radial diffusivity. Both types of glioneuronal tumours were different from pNAWM in fractional anisotropy and radial diffusivity. For identifying the tumour edges, threshold values for tumour-free tissue were investigated with receiver operating characteristic analyses: tumour could be separated from pNAWM at a threshold ≤ 0.32 (fractional anisotropy) or ≥ 0.56 (radial diffusivity) *10–3 mm2/s (area under the curve 0.995 and 0.990 respectively). While diffusion parameters of FCDs differed from cNAWM (radial diffusivity (*10–3 mm/s2): 0.74 ± 0.19 vs. 0.43 ± 0.05; corrected p-value