Analysis of metabolic abnormalities in high-grade glioma using MRSI and convex NMF.

Da Silva Mendes Pedrosa de Barros, Nuno Miguel; Meier, Raphael; Pletscher, Martin; Stettler, Samuel; Knecht, Urspeter; Reyes, Mauricio; Gralla, Jan; Wiest, Roland; Slotboom, Johannes (2019). Analysis of metabolic abnormalities in high-grade glioma using MRSI and convex NMF. NMR in biomedicine, 32(8), e4109. Wiley Interscience 10.1002/nbm.4109

[img] Text
Barros_et_al-2019-NMR_in_Biomedicine.pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.

Download (2MB) | Request a copy

Clinical use of MRSI is limited by the level of experience required to properly translate MRSI examinations into relevant clinical information. To solve this, several methods have been proposed to automatically recognize a predefined set of reference metabolic patterns. Given the variety of metabolic patterns seen in glioma patients, the decision on the optimal number of patterns that need to be used to describe the data is not trivial. In this paper, we propose a novel framework to (1) separate healthy from abnormal metabolic patterns and (2) retrieve an optimal number of reference patterns describing the most important types of abnormality. Using 41 MRSI examinations (1.5 T, PRESS, T 135 ms) from 22 glioma patients, four different patterns describing different types of abnormality were detected: edema, healthy without Glx, active tumor and necrosis. The identified patterns were then evaluated on 17 MRSI examinations from nine different glioma patients. The results were compared against BraTumIA, an automatic segmentation method trained to identify different tumor compartments on structural MRI data. Finally, the ability to predict future contrast enhancement using the proposed approach was also evaluated.

Item Type:

Journal Article (Original Article)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology

UniBE Contributor:

Da Silva Mendes Pedrosa de Barros, Nuno Miguel; Meier, Raphael; Knecht, Urspeter; Reyes, Mauricio; Gralla, Jan; Wiest, Roland and Slotboom, Johannes

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

0952-3480

Publisher:

Wiley Interscience

Language:

English

Submitter:

Martin Zbinden

Date Deposited:

18 Jul 2019 09:48

Last Modified:

21 Jul 2019 02:40

Publisher DOI:

10.1002/nbm.4109

PubMed ID:

31131943

Uncontrolled Keywords:

MRS and MRSI methods applications cancer head and neck cancer methods and engineering post-acquisition processing spectroscopic imaging visualization methods and engineering

BORIS DOI:

10.7892/boris.131187

URI:

https://boris.unibe.ch/id/eprint/131187

Actions (login required)

Edit item Edit item
Provide Feedback