Published May 2019
| Version v1
Journal article
Modelling MR and clinical features in grade II/III astrocytomas to predict IDH mutation status
Creators
- 1. Imaging Department, UCLH NHS Trust, London (United Kingdom)
- 2. Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London (United Kingdom)
- 3. National Hospital for Neurology and Neurosurgery, Queen Square, London (United Kingdom)
- 4. Department of Neurodegenerative Diseases, UCL Institute of Neurology, London (United Kingdom)
- 5. Division of Neuropathology, National Hospital for Neurology and Neurosurgery, Queen Square, London (United Kingdom)
Description
Background and Purpose: There is increasing evidence that many IDH wildtype (IDHwt) astrocytomas have a poor prognosis and although MR features have been identified, there remains diagnostic uncertainty in the clinic. We have therefore conducted a comprehensive analysis of conventional MR features of IDHwt astrocytomas and performed a Bayesian logistic regression model to identify critical radiological and basic clinical features that can predict IDH mutation status.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.ejrad.2019.03.003Additional details
Identifiers
- DOI
- 10.1016/j.ejrad.2019.03.003;
- PII
- S0720048X19300956;
Publishing Information
- Journal Title
- European Journal of Radiology
- Journal Volume
- 114
- Journal Page Range
- p. 120-127
- ISSN
- 0720-048X
- CODEN
- EJRADR
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 51013745
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- ASTROCYTOMAS; MUTATIONS; NMR IMAGING; SIMULATION
- Descriptors DEC
- DIAGNOSTIC TECHNIQUES; DISEASES; GLIOMAS; NEOPLASMS; NERVOUS SYSTEM DISEASES
Optional Information
- Notes
- © 2019 Elsevier B.V. All rights reserved.