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Imaging Markers of Isocitrate Dehydrogenase-1 Mutations in Gliomas.
Glioblastomas (GBM) are the commonest and most aggressive primary tumour of the brain. They are associated with an appalling prognosis with only survivals of a matter of weeks in untreated patients, improving to 14 - 16 months with radiotherapy with concomitant and adjuvant chemotherapy. In this era of molecular biology diagnosis still relies on the WHO Classification system that only requires a tumour to have features of an astrocytic tumour with either necrosis or microvascular proliferation on light microscopy. Yet it is clear that GBMs form a very heterogenous group of tumours. Although there are recognized histological variants (e.g. giant cell GBM, GBM with oligodendroglial differentiation) it is doubtful how useful these are for predicting outcome. It is clear we need to be able to better subtype GBMs to consider individualizing treatment.
We have known for some time that glioblastomas can arise from two pathways – either as a primary ‘de novo’ GBM or a ‘secondary’ GBM from a pre-existing low grade glioma. These two subtypes have different mutations and activate different pathways within the cells. The discovery of mutations of the isocitrate dehydrogenase (IDH) gene, an early marker of astrocytic tumor development, has lead to the realization that some GBMs have this mutation. This cohort of patients have a far better prognosis with a median survival of 31 months compared to the 15 months in IDH-wild type.Stephen Price is supported with a Clinician Scientist Fellowship from the National Institute of Health Research.This is the final version of the article. It first appeared from Lippincott, Williams & Wilkins via http://dx.doi.org/10.1227/NEU.000000000000081
The Kozai-Lidov Mechanism in Hydrodynamical Disks
We use three dimensional hydrodynamical simulations to show that a highly
misaligned accretion disk around one component of a binary system can exhibit
global Kozai-Lidov cycles, where the inclination and eccentricity of the disk
are interchanged periodically. This has important implications for accreting
systems on all scales, for example, the formation of planets and satellites in
circumstellar and circumplanetary disks, outbursts in X-ray binary systems and
accretion on to supermassive black holes.Comment: Accepted for publication in ApJ Letter
Connectome analysis for pre-operative brain mapping in neurosurgery.
OBJECT: Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains 'wiring diagram'. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations. METHODS: Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal-parietal-occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series. RESULTS: Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location. CONCLUSIONS: Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits.S. J. P. received funding for this study through a National Institute for Health Research (NIHR) (UK) – Clinician Scientist Award (Ref: NIHR/CS/009/011). M. G. H. is funded by the Wellcome Trust Neuroscience in Psychiatry Network with additional support from the National Institute for Health Research Cambridge Biomedical Research Centre. This paper presents independent research funded by the NIHR.This is the final version of the article. It first appeared from Taylor & Francis via http://dx.doi.org/10.1080/02688697.2016.120880
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