Sebastian C. Niesporek1, Armin M. Nagel1,2, Reiner Umathum1, Nicolas G.R. Behl1, Mark E. Ladd1, Heinz-Peter Schlemmer3, and Daniel Paech3
1Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Institute of Radiology, University Hospital Erlangen, Erlangen, Germany, 3Division of Radiology, German Cancer Research Center (DKFZ), Heidelverg, Germany
Synopsis
The
cerebral metabolic rate of oxygen (CMRO2) is an interesting biomarker and can
be used as a diagnostic parameter in various neurodegenerative diseases or
tumors. A dynamic 17O MRI inhalation method was optimized for application in a clinical
setting and employed in two patient examinations to investigate CMRO2 in human
brain tumors as part of an ongoing pilot study. In tumor tissue, a decrease in oxygen
consumption was detected, which is in consistent with the Warburg effect. To
our knowledge, the presented work includes the first patient study with dynamic
17O MRI.
PURPOSE
In the energy metabolism of most organisms molecular oxygen (O2) plays a
vital role. In various diseases such as cancer (‘Warburg effect’) [1], Parkinson’s [2], or Alzheimer’s disease [3]
the functional parameter of cerebral metabolic rate of oxygen consumption (CMRO2)
contains information about tissue viability. The CMRO2 parameter can
be measured via dynamic 17O MRI of the stable oxygen isotope 17O employing an
inhalation procedure where enriched 17O2 gas is administered during continuous
imaging [4]. Recently, the
reproducibility and reliability of CMRO2 determination via 17O MRI with
additional partial volume (PV) correction was demonstrated in a small volunteer
cohort [5]. The presence of strong
PV effects in 17O-MRI is caused by low spatial resolution and rapid transverse
relaxation (T2~5ms), requiring an efficient correction procedure to
separate signal contribution from different compartments. In the presented work
the verified method from [5] was utilized in a clinical setting to measure two tumor patients and quantifying
CMRO2 values in various regions in healthy tissue and tumor regions.
METHODS
A three-phase
inhalation experiment [4] (t1 baseline-phase; t2 17O-inhalation-phase; t3 decay-phase)
was performed with a MR‑compatible breathing system in which a 17O2-bolus is
administered in a closed circuit. In this ongoing IRB approved study one
untreated glioma-patient (male, 26y.-o. astrocytoma WHO grade II) and one
untreated glioblastoma-patient (male, 34y.-o., WHO grade IV) were included.
17O MRI was conducted at a 7 Tesla whole-body scanner (Siemens
Healthineers, Erlangen, Germany) with a nominal spatial resolution of (7.5mm)3
employing a density-adapted radial sequence [6] with Golden Angle acquisition scheme [7] (TR/TE=20/0.56ms, total
acquisition time 30:00min). Data were reconstructed with a temporal resolution of Δt=1:00min. Per experiment 3.8±0.1L of 70%-enriched 17O2 gas (NUKEM Isotopes Imaging GmbH, Alzenau, Germany) were administered.
High-resolution T1 MPRAGE (0.6mm)3 and T2 TSE (0.4x0.4x0.5mm)3
sequences were additionally acquired and used for tumor and normal brain
segmentation for the employed PV correction algorithm [8,9]. Prior to patient measurements the imaging protocol was optimized
utilizing dynamic numerical signal simulation of the human brain: the impact of
shortening of the baseline- and decay-phases on the accuracy of quantification was
investigated and the final patient protocol was adjusted accordingly.RESULTS
The available fit information in
individual breathing phases (t1, t3) was systematically reduced in two
considered compartments (gray matter (GM), white matter (WM)). The deviation from the simulation ground truth is shown in
Fig.1. Only a minor dependence is seen for variation of t1 and a deviation >5% for t3<15min. With this information the patient inhalation protocol
was set to: t1=5:00min, t2≤10:00min (variable until 17O2 is exhausted) , t3≤15:00min. Results of the glioma WHO II -patient
revealed significantly decreased CMRO2 in tumor tissue (0.59–0.66±0.16μmol/g/min)
compared to contralateral normal appearing brain tissue (1.10–1.22±0.08 μmol/g/min, control compartment, Tab.1).
Quantitative data are shown in Fig.2
and a map of relative 17O signal increase visualizes the decrease of oxygen metabolization in the tumor region (Fig.3). Further, CMRO2 was
significantly increased in gray matter (2.34–2.58±0.20μmol/g/min) compared to white matter tissue (0.56–0.62±0.06μmol/g/min) after application of PVC. CMRO2 determination in the glioblastoma
patient, revealed an even more pronounced metabolization drop in the tumor tissue, with lowest
values in the necrotic (NE) as well as contrast enhancing (CE) tumor region (Tab.1).DISCUSSION
Application
of a simulation tool allowed protocol optimization and estimation of expected
fitting errors due to information reduction in individual breathing phases. The
protocol and utilized inhalation setup allowed measurements in two patients and
show the feasibility of transferring the suggested method to a clinical
environment. The drop in quantified functional parameters in the malignant
tissue (CE, NE, PE) corresponds to the Warburg effect, which describes decreased CMRO2 in
tumors due to the shift in glucose metabolism from oxidative phosphorylation to
lactate production for energy generation as reported for 17O MRI
data for the first time by Hofmann et al. [10]. Overall functional
parameters are in good agreement with previous reports (Tab.1) [10,
11]. Due to large voxel volumes and rapid transverse relaxation, the quantified
H217O concentrations might be underestimated despite the
application of a dedicated PVC algorithm. Uncertainties in the prior 17O
enrichment factor as well as limitations of the PVC as discussed in [5] are
the main sources of error in the suggested method. However, CMRO2 values
of healthy tissue (GM, WM) and cerebrospinal fluid (CSF) are in correspondence with
previous work [4,5].CONCLUSION
This work presents
the first results of an ongoing study investigating brain tumor metabolism in
glioma-patients with the help of dynamic 17O MRI. Further application may
provide new insights into tumor pathophysiology through the visualization
of the cerebral metabolic rate of oxygen consumption.Acknowledgements
The authors want to
thank NUKEM Isotopes Imaging GmbH for their generous supply of 17O2-gas and support of this project.References
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