eprintid: 27302
rev_number: 15
eprint_status: archive
userid: 4727
dir: disk0/00/02/73/02
datestamp: 2019-10-28 08:59:09
lastmod: 2019-11-14 11:53:53
status_changed: 2019-10-28 08:59:09
type: doctoralThesis
metadata_visibility: show
creators_name: Hubertus, Simon Ralph
title: Quantitative Susceptibility Mapping to Measure the Local Tissue Oxygenation
subjects: ddc-530
subjects: ddc-600
divisions: i-130001
adv_faculty: af-13
abstract: Magnetic resonance imaging (MRI)-based mapping of the tissue oxygenation would be highly beneficial
for the treatment of patients with brain tumours. Hence, the purpose of this thesis was to incorporate
quantitative susceptibility mapping (QSM) into a reconstruction of the oxygen extraction fraction (OEF),
cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2). In the first part, a joint QSM
and quantitative blood oxygenation level-dependent (qBOLD) approach from two different MRI sequences,
gradient echo sampling of spin echo (GESSE) and multi-gradient echo (GRE), was compared in seven
healthy subjects and simulations. GESSE yielded higher parameter accuracy in simulated grey matter
but produced unphysiological grey–white matter contrast in OEF in vivo. GRE is more efficient and generated
uniform OEF maps in vivo but revealed biases in simulation. In the second part, an artificial
neural network (ANN) was trained for QSM+qBOLD analysis and compared to the initial quasi-Newton (QN)
reconstruction. The ANN allowed a faster and more robust reconstruction of OEF maps with lower intersubject
variation (OEF_ANN = 43.5 +- 0.8% vs OEF_QN = 43.8 +- 5.2 %). In the third part, machine learning-based
clustering was incorporated into the QN QSM+qBOLD analysis and applied to eight patients with
high-grade gliomas. The OEF was significantly lower inside the tumour compared to the contralateral
side in grade III (OEF_tum = 12.5 +- 0.5% vs OEF_con = 24.5 +- 2.3 %) and grade IV (OEF_tum = 17.2 +- 6.1%
vs OEF_con = 24.8 +- 4.5 %) gliomas. The CBF was significantly higher; yet, only in grade IV gliomas
(CBF_tum = 108.1 +- 83.3 ml/100 g/min vs CBF_con = 29.1 +- 21.0 ml/100 g/min). The CMRO2 revealed no significant
differences. Exploiting the phase and magnitude of the acquired MRI signal and including machine
learning for reconstruction of the OEF with QSM+qBOLD is promising and might facilitate the implementation
of a robust quantification of the tissue oxygenation in the clinical routine in the future.
date: 2019
id_scheme: DOI
id_number: 10.11588/heidok.00027302
ppn_swb: 1681356538
own_urn: urn:nbn:de:bsz:16-heidok-273029
date_accepted: 2019-10-16
advisor: HASH(0x55fc36c77fd8)
language: eng
bibsort: HUBERTUSSIQUANTITATI2019
full_text_status: public
place_of_pub: Heidelberg
citation:   Hubertus, Simon Ralph  (2019) Quantitative Susceptibility Mapping to Measure the Local Tissue Oxygenation.  [Dissertation]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/27302/1/PhD_Hubertus_2019_Druck.pdf