TITLE:
Magnetic Resonance Perfusion in Brain Tumors: Comparison of Different Evaluation Approaches in Dual-Echo and Multi-Echo Techniques
AUTHORS:
Volker Hietschold, Andrij Abramyuk, Tareq Juratli, Kerim Hakan Sitoci-Ficici, Michael Laniado, Jennifer Linn
KEYWORDS:
MRI, Brain Tumors, Perfusion
JOURNAL NAME:
International Journal of Medical Physics, Clinical Engineering and Radiation Oncology,
Vol.6 No.2,
May
23,
2017
ABSTRACT: Dynamic measurements of
T1 shortening (dynamic contrast
enhanced—DCE) as well as of T2* shortening
(dynamic susceptibility contrast—DSC) as two separate measurement strategies
are widely used to quantitatively describe tumor perfusion and vascularity.
Dual-echo approaches allow for the simultaneous assessment of both effects. The
extension to multi-echo sequences should inhere the advantage of improved
signal-to-noise ratios and more precise sampling of the
T2* decay. The aim of
our study is to investigate, if an extension of the dual-echo approach to the
multi-echo approach allows for more stable quantitative determination of pharmacokinetic
parameters in brain tumors. This study applies a multi-echo approach to obtain
different estimations of a vascular input function and analyzes various
combinations of vascular input functions and pharmacokinetic models. Perfusion
measurements were performed with 52 consecutive patients with different brain
tumors using a 10-echo gradient echo sequence. Our findings show that the
extension to multi-echo sequences leads to an 11%-improvement of the
Contrast-to-Noise ratio. Compared to other combinations, an application of
Extended Tofts model using the
T2*-related venous
output function or an output function estimated in the tumor tissue enables the
most reliable determination of perfusion parameters, reducing the
reproducibility range by a factor of 1.2 to 10 for
Ktrans and of 1.2 to 5.5 in the case of rBV calculation.
Determination of Ktrans within repeated measurements
within about 3 days results as most stable, if AIF from tumor pixels is used as
vascular input function, meaning that the scatter is reduced by a factor of 1.2
compared to the next best VIF and by a factor of 10 compared to the worst of
the tested approaches. In addition, this study shows that signal decomposition
into two components with different Larmor frequencies might provide additional
information concerning tissue composition of brain tumors.