Neuro research presentation sessions at ECR 2020
- PDF / 171,611 Bytes
- 3 Pages / 595.276 x 790.866 pts Page_size
- 10 Downloads / 189 Views
EDITORIAL
Neuro research presentation sessions at ECR 2020 Philippe Demaerel 1 Received: 28 January 2020 / Revised: 7 February 2020 / Accepted: 12 February 2020 # European Society of Radiology 2020
Neuroradiology research presented at ECR 2020: main findings, novelties, and remaining questions The greatest novelties in the research presentation sessions (RPS) on neuroimaging at the European Congress of Radiology (ECR) 2020 are related to progress in advanced magnetic resonance imaging (MRI) techniques and artificial intelligence (AI). But, as is the case every year at ECR, advances in the fields of stroke, brain tumours, neurodegenerative disease, and multiple sclerosis (MS) are included in the programme too. All abstracts are published in the ECR 2020 Book of Abstracts [1], with session and presentation numbers mentioned in brackets. In brain tumour imaging, the recently revised WHO classification has resulted in an increasing use of deep learning in the study of new biomarkers. The central focus is the methods in isocitrate dehydrogenase (IDH) genotype prediction and the presence or absence of O6-methylguanine-methyltransferase (MGMT) in glioblastoma. In a preliminary study of 25 patients, classifiers provided natural boundaries for efficient discrimination of IDH-wild type and IDH-mutation (RPS 1011a4). The usefulness of rCBV measurements to differentiate the IDH genotype is also reported (RPS 1011a-7). The proteomic footprint of IDH-mutation is the presence of 2-hydroxy-glutarate (2HG). The authors studied 39 patients and found 80% sensitivity and 75% specificity of single voxel MR spectroscopy in the detection of 2HG (RPS 1011a-5). The study of the topographical distribution of MGMT promoter methylation in 436 IDH-wild type glioblastoma revealed no statistically significant differences between methylated and unmethylated status (RPS 1011a-6).
* Philippe Demaerel [email protected] 1
Department of Radiology, University Hospital KU Leuven, Herestraat 49, 3000 Leuven, Belgium
There is an increasing use of radiomics for volumetry and for assessing response to treatment in brain tumour imaging. In a series of 124 patients, it was shown that it was possible to predict patient survival by analysing radiomics features quantifying tumour intensity and heterogeneity (RPS 1011b-3). In stroke imaging, several abstracts focus on improvement in stroke patient selection for thrombolysis. One study reports that the mothership and drip-and-ship strategies do not differ significantly in impact on outcome, provided that ‘bridging’ intravenous thrombolysis is given to the acute stroke patient in the drip-and-ship strategy (RPS 1411b-1). Automated attenuation measurements on CT angiography source images present excellent performance in detecting ischaemia in acute stroke patients and bear the potential to reduce the use of CT perfusion (RPS 1411b-7). AI can provide an e-CT angiography collateral score for patients eligible for thrombectomy (RPS 1411b-8). Automated assessment of regional hypoattenuations was able to
Data Loading...
