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SPectroscOpic prediction of bRain Tumours (SPORT): study protocol of a prospective imaging trial.
Franco, Pamela; Würtemberger, Urs; Dacca, Karam; Hübschle, Irene; Beck, Jürgen; Schnell, Oliver; Mader, Irina; Binder, Harald; Urbach, Horst; Heiland, Dieter Henrik.
Affiliation
  • Franco P; Department of Neurosurgery, Medical Centre, University of Freiburg, Breisacher Str. 64, 79106, Freiburg im Breisgau, Germany. pamela.franco@uniklinik-freiburg.de.
  • Würtemberger U; Faculty of Medicine, University of Freiburg, Breisacher Str. 153, 79110, Freiburg im Breisgau, Germany. pamela.franco@uniklinik-freiburg.de.
  • Dacca K; Department of Neuroradiology, Medical Centre, University of Freiburg, Breisacher Str. 64, 79106, Freiburg im Breisgau, Germany.
  • Hübschle I; Faculty of Medicine, University of Freiburg, Breisacher Str. 153, 79110, Freiburg im Breisgau, Germany.
  • Beck J; Faculty of Medicine, University of Freiburg, Breisacher Str. 153, 79110, Freiburg im Breisgau, Germany.
  • Schnell O; Faculty of Medicine, University of Freiburg, Breisacher Str. 153, 79110, Freiburg im Breisgau, Germany.
  • Mader I; Department of Neurosurgery, Medical Centre, University of Freiburg, Breisacher Str. 64, 79106, Freiburg im Breisgau, Germany.
  • Binder H; Faculty of Medicine, University of Freiburg, Breisacher Str. 153, 79110, Freiburg im Breisgau, Germany.
  • Urbach H; Department of Neurosurgery, Medical Centre, University of Freiburg, Breisacher Str. 64, 79106, Freiburg im Breisgau, Germany.
  • Heiland DH; Faculty of Medicine, University of Freiburg, Breisacher Str. 153, 79110, Freiburg im Breisgau, Germany.
BMC Med Imaging ; 20(1): 123, 2020 11 23.
Article in En | MEDLINE | ID: mdl-33228567
BACKGROUND: The revised 2016 WHO-Classification of CNS-tumours now integrates molecular information of glial brain tumours for accurate diagnosis as well as for the development of targeted therapies. In this prospective study, our aim is to investigate the predictive value of MR-spectroscopy in order to establish a solid preoperative molecular stratification algorithm of these tumours. We will process a 1H MR-spectroscopy sequence within a radiomics analytics pipeline. METHODS: Patients treated at our institution with WHO-Grade II, III and IV gliomas will receive preoperative anatomical (T2- and T1-weighted imaging with and without contrast enhancement) and proton MR spectroscopy (MRS) by using chemical shift imaging (MRS) (5 × 5 × 15 mm3 voxel size). Tumour regions will be segmented and co-registered to corresponding spectroscopic voxels. Raw signals will be processed by a deep-learning approach for identifying patterns in metabolic data that provides information with respect to the histological diagnosis as well patient characteristics obtained and genomic data such as target sequencing and transcriptional data. DISCUSSION: By imaging the metabolic profile of a glioma using a customized chemical shift 1H MR spectroscopy sequence and by processing the metabolic profiles with a machine learning tool we intend to non-invasively uncover the genetic signature of gliomas. This work-up will support surgical and oncological decisions to improve personalized tumour treatment. TRIAL REGISTRATION: This study was initially registered under another name and was later retrospectively registered under the current name at the German Clinical Trials Register (DRKS) under DRKS00019855.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain Neoplasms / Magnetic Resonance Spectroscopy / Glioma Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: BMC Med Imaging Journal subject: DIAGNOSTICO POR IMAGEM Year: 2020 Document type: Article Affiliation country: Germany Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain Neoplasms / Magnetic Resonance Spectroscopy / Glioma Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: BMC Med Imaging Journal subject: DIAGNOSTICO POR IMAGEM Year: 2020 Document type: Article Affiliation country: Germany Country of publication: United kingdom