<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "Quantitative Susceptibility Mapping to Measure the Local Tissue Oxygenation"^^ . "Magnetic resonance imaging (MRI)-based mapping of the tissue oxygenation would be highly beneficial\r\nfor the treatment of patients with brain tumours. Hence, the purpose of this thesis was to incorporate\r\nquantitative susceptibility mapping (QSM) into a reconstruction of the oxygen extraction fraction (OEF),\r\ncerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2). In the first part, a joint QSM\r\nand quantitative blood oxygenation level-dependent (qBOLD) approach from two different MRI sequences,\r\ngradient echo sampling of spin echo (GESSE) and multi-gradient echo (GRE), was compared in seven\r\nhealthy subjects and simulations. GESSE yielded higher parameter accuracy in simulated grey matter\r\nbut produced unphysiological grey–white matter contrast in OEF in vivo. GRE is more efficient and generated\r\nuniform OEF maps in vivo but revealed biases in simulation. In the second part, an artificial\r\nneural network (ANN) was trained for QSM+qBOLD analysis and compared to the initial quasi-Newton (QN)\r\nreconstruction. The ANN allowed a faster and more robust reconstruction of OEF maps with lower intersubject\r\nvariation (OEF_ANN = 43.5 +- 0.8% vs OEF_QN = 43.8 +- 5.2 %). In the third part, machine learning-based\r\nclustering was incorporated into the QN QSM+qBOLD analysis and applied to eight patients with\r\nhigh-grade gliomas. The OEF was significantly lower inside the tumour compared to the contralateral\r\nside 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%\r\nvs OEF_con = 24.8 +- 4.5 %) gliomas. The CBF was significantly higher; yet, only in grade IV gliomas\r\n(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\r\ndifferences. Exploiting the phase and magnitude of the acquired MRI signal and including machine\r\nlearning for reconstruction of the OEF with QSM+qBOLD is promising and might facilitate the implementation\r\nof a robust quantification of the tissue oxygenation in the clinical routine in the future."^^ . "2019" . . . . . . . "Simon Ralph"^^ . "Hubertus"^^ . "Simon Ralph Hubertus"^^ . . . . . . "Quantitative Susceptibility Mapping to Measure the Local Tissue Oxygenation (PDF)"^^ . . . "PhD_Hubertus_2019_Druck.pdf"^^ . . . "Quantitative Susceptibility Mapping to Measure the Local Tissue Oxygenation (Other)"^^ . . . . . . "indexcodes.txt"^^ . . "HTML Summary of #27302 \n\nQuantitative Susceptibility Mapping to Measure the Local Tissue Oxygenation\n\n" . "text/html" . . . "530 Physik"@de . "530 Physics"@en . . . "600 Technik, Medizin, angewandte Wissenschaften"@de . "600 Technology (Applied sciences)"@en . .