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Advanced MR Techniques in Detection of Tumor Infiltration and Grading in Gliomas

NCT01225003 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 30

Last updated 2011-09-29

No results posted yet for this study

Summary

In this study, we evaluate the role of diffusion kurtosis imaging (DKI) and MR spectroscopy (MRS), two advanced imaging techniques in magnetic resonance (MR) in grading and detection of microscopic infiltrating tumour in gliomas. These parameters are of utmost importance in optimal choice and planning of treatment.

Patients treated with gliomatous brain tumours are included voluntarily. They undergo one imaging session on a 3T MR scanner prior to treatment.

DKI data are quantitively analyzed in order to estimate specific parameters in normal appearing white matter, grey matter, tumor and peritumoral edema. MRS data are analyzed quantitatively and qualitatively with peak integration, ratio calculation and classification algorithms. Histological confirmation is obtained at subsequent surgery.

Information from this study can be of significant importance in avoiding brain biopsies. Furthermore, information on microscopic tumour spread can be used during neurosurgery or in radiotherapy planning. An important advantage of these advanced MR techniques is the non-invasivity and the lack of ionizing radiation, two important issues in this relatively young patient population.

Conditions

Sponsors & Collaborators

  • Universitaire Ziekenhuizen KU Leuven

    lead OTHER

Principal Investigators

  • Stefan Sunaert, MD, PhD · Universitaire Ziekenhuizen KU Leuven

  • Uwe Himmelreich, PhD · Catholic University Leuven

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2010-07-31

Countries

  • Belgium

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT01225003 on ClinicalTrials.gov