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Background Hemorrhage is the most devastating complication of brain arteriovenous malformations (bAVMs), and to date, there is still concern about the needing for treatment in case of unruptured and asymptomatic bAVM. In fact, the morbidity and mortality of treatments may exceed that of the AVM’s natural history. None of the classifications and scores for bAVM allows to predict the risk of bleeding. In this study, we aimed to identify the angio-architectural characteristics of brain AVMs associated with bleeding. Methods We retrospectively evaluated all consecutive patients diagnosed with cerebral AVMs, between January 2010 and December 2019 from our prospective bAVM database. Univariate and multivariate logistic regression analysis were used to evaluate relationships between angio-architectural features of ruptured and unruptured bAVMs. Results Of the 143 retrieved bAVMs, 65 were unruptured and 78 were ruptured. The univariate logistic regression analysis demonstrated statistically significant differences into angio-architectural features of unruptured and ruptured bAVMs. The multivariate logistic regression analysis fitted well ( p =.113) with a good discrimination capacity (ROC = 0.83) of three independent angio-architectural features mainly related to bleeding in bAVMs: a smaller diameter of the nidus ( p < .001), the absence of venous drainage alterations ( p = .047), of the presence of prenidal aneurysms ( p = .005). Conclusions In our study, several features resulted related to an increased probability of rupture for bAVMs, among which the more relevant were a small diameter of the nidus, the absence of venous drainage alterations, and the presence of prenidal aneurysms.

We present the neuroimaging findings of three cases of non-ketotic hyperglycaemia (NKH) associated with focal seizures and a review of the previous cases and series reported in literature. NKH is a cause of seizures in both long-standing and newly diagnosed diabetic patients. They are usually focal motor seizures, rarely with a secondary generalisation. This condition does not fully respond to anticonvulsant therapy if glycaemic levels are not normalised. Of interest, magnetic resonance imaging (MRI) of NKH could be different from those observed during other kinds of seizures. Indeed, seizure-related MRI abnormalities mainly involve the cortical grey matter, while NKH-related seizures usually appear as reversible subcortical T2/fluid attenuation inversion recovery (FLAIR) hypointensity. This latter abnormality shows a good spatial correlation with the area of the ictal focus on electroencephalogram and could be associated with other more common post-ictal MRI changes (cortical grey matter T2/FLAIR hyperintensity, cortical or leptomeningeal enhancement). Although these abnormalities tend to be transient, a focal volume loss or gliosis can result on follow-up imaging. Our cases confirm T2/FLAIR subcortical hypointensity as a main neuroradiological hallmark of NKH-induced seizures.

Spinal dural arteriovenous fistulae (SDAVF) are the most common vascular malformations of the spine. Although digital subtraction angiography (DSA) remains the standard of reference to diagnose and classify vascular spinal lesions, we investigated the clinical value of contrast-enhanced MR angiography (CE-MRA), equipped with TRICKS sequences, in localizing SDAVF before selective catheter angiography and possible subsequent treatment. We studied 16 consecutive patients suspected of harbouring vascular spinal cord malformations and we tried to determine the level and the side of the arterial feeder to the arteriovenous abnormality. In 12 cases the results were compared with DSA and/or possible post-operative findings. In nine cases CE-MRA correctly depicted the origin of the fistula: in particular one patient was treated surgically only on the basis of MRA results. Thanks to its elevated spatial and temporal resolution, spinal contrast-enhanced MRA using TRICKS sequences proved reliable in detecting and localizing the SDAVF arterial feeders and can be used as a guide to subsequent selective DSA examination.

We describe a rare case of giant intracranial chordoma, emphasizing the patient's long survival and his excellent response to radiotherapy that led to a progressive regression of neurological symptomatology up to disappearance, in the absence of cerebral white matter damages.

We describe a patient with right temporal lobe epilepsy with MR findings of an ischaemic thalamic lesion extending to the mammillothalamic tract and absent visualization of the mammillary body without signal changes in the hippocampus.

Hippocampal abnormalities correlated with mesial temporal sclerosis (MTS) are well documented. MTS may be associated with extrahippocampal anomalies involving limbic structures along a known neuroanatomic pathway (Papez circuit). We report a patient with MTS and thalamic changes. Seizure-related thalamic damage could have been caused by abnormal electric discharges from the mamillary body to the anterior thalamus through the mamillothalamic tract. This suggests that MTS is not limited to the temporal lobe but could represent a limbic system pathology.

Independent component analysis (ICA) is a powerful technique for the multivariate, non-inferential, data-driven analysis of functional magnetic resonance imaging (fMRI) data-sets. The non-inferential nature of ICA makes this a suitable technique for the study of complex mental states whose temporal evolution would be difficult to describe analytically in terms of classical statistical regressors. Taking advantage of this feature, ICA can extract a number of functional connectivity patterns regardless of the task executed by the subject. The technique is so powerful that functional connectivity patterns can be derived even when the subject is just resting in the scanner, opening the opportunity for functional investigation of the human mind at its basal “default” state, which has been proposed to be altered in several brain disorders. However, one major drawback of ICA consists in the difficulty of managing its results, which are not represented by a single functional image as in inferential studies. This produces the need for a classification of ICA results and exacerbates the difficulty of obtaining group “averaged” functional connectivity patterns, while preserving the interpretation of individual differences. Addressing the subject-level variability in the very same framework of “grouping” appears to be a favourable approach towards the clinical evaluation and application of ICA-based methodologies. Here we present a novel strategy for group-level ICA analyses, namely the self-organizing group-level ICA (sog-ICA), which is used on visual activation fMRI data from a block-design experiment repeated on six subjects. We propose the sog-ICA as a multi-subject analysis tool for grouping ICA data while assessing the similarity and variability of the fMRI results of individual subject decompositions.