Atle Bjørnerud^{1,2}, Magne Mørk Kleppestø^{1}, Tracy T Batchelor^{3,4}, Patrick Y Wen^{5}, Gregory Sorensen^{6}, and Kyrre Eeg Emblem^{1,7}

^{1}The Intervention Centre, Oslo University Hospital, Oslo, Norway, ^{2}Dept. of Physics, University of Oslo, Oslo, Norway, ^{3}Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States, ^{4}Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States, ^{5}Center for Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, United States, ^{6}Siemens Healthcare Health Services, Malvern, MA, United States, ^{7}MGH-HST A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States

### Synopsis

**Contrast agent extravasation is
known to be a serious confounder in
estimations of cerebral blood volume (CBV) analysis of primary brain tumors
using DSC-MRI. We here propose a modified MTT-insensitive method for correction
of contrast agent extravasation based on parametric analysis of the tissue impulse
response function from a two-compartment kinetic model combined with automated global
arterial input function (AIF) approximation. Using DSC-MRI data from 28
patients with recurrent glioblastoma which were scanned twice prior to
treatment initiation, we show that the proposed method yields test-retest
stability similar to the current reference method, but with the added advantage
of reduced MTT sensitivity. **### Purpose

To test the utility
of a modified method for correction of contrast agent extravasation in DSC-MRI
which is independent of tumor mean transit time (MTT) based on parametric
analysis of the tissue impulse response function combined with automated global
arterial input function (AIF) approximation.

### Background

Contrast agent
extravasation is known to be a
serious confounder in estimations of cerebral blood volume (CBV) analysis of
primary brain tumors using DSC-MRI (1). It has been recently shown that leakage
correction based on analysis of the tumor impulse response function (IRF) is
less sensitive to mean transit time (MTT) -induced error compared to an
established method as originally proposed by Weisskoff et al. (2). The
usefulness of the MTT-insensitive approach reported in (3) is however limited
by the need to determine the AIF in
order to obtain the IRF and further by the empirical determination of the
leakage-dependent portion of the IRF. Here, we propose a modified method whereby
the AIF is estimated directly from the mean brain tissue response and the
contrast agent leakage is derived from a full parametric curve fit of the IRF using
the two-compartment uptake model.

### Theory

Kinetic model: The two-compartment
uptake model (4) incorporates the effect of finite MTT and extravasation but
assumes absence of significant contrast agent reflux (K^{trans}/ *v*_{e}
≈ 0). The IRF is then given by:

$$I(t)=exp(-t/T_{p}) + E\cdot(1-exp(-t/T_{p}))$$ (Eq.1)

where E
is the extraction fraction = K^{trans}/(*F*+K^{trans}), F is tissue flow and MTT= T_{p}/(1-E). Leakage corrected CBV is then given by :

$$CBV_{corr}= F\cdot T_{p}/(1-E) $$ (Eq.2)

AIF estimation: An
idealized AIF was estimated from the measured global tissue response (excluding
tumor tissue) by assuming an exponential IRF in (non-leaky) brain tissue so that: $$\overline{C_{t}(t)}=C_{a}(t)\otimes \overline{F} \cdot exp(-t/\overline{MTT})$$ (Eq. 3)

where $$$\otimes$$$ is the convolution operator, $$$\overline{C_{t}(t)}$$$ is global tissue response, $$$ \overline{F}$$$ is global mean perfusion, $$$\overline{MTT}$$$ is the global mean transit time and C_{a}(t) is the estimated AIF. C_{a}(t) can then be determined by SVD deconvolution by assuming fixed values for $$$ \overline{F}$$$ and $$$\overline{MTT}$$$.

### Method

^{}Twenty eight
patients with recurrent glioblastomas enrolled in a phase II clinical trial of the
VEGFR inhibitor cediranib (clinicaltrials.gov, NTC00305656) were imaged twice
on separate days prior to cediranib administration. Imaging was performed at 3
T (Magnetom Trio, Siemens Medical) and the protocol included DSC-MRI, pre-and
post T1- weighted
spin-echo images used for expert definition of tumor regions-of-interest (5). The DSC examination was preceded by a DCE-MRI, thereby minimizing T1-leakage effects. From the DSC data, global tissue response, excluding tumor was determined as
previously described (6) and AIF was derived from Eq. 3 using $$$ \overline{F}$$$= 50 mL/100g/min and $$$\overline{MTT}$$$ = 4 sec.
Using this AIF, pixel-wise estimates of

*F*,
MTT, E and K

^{trans} were obtained by first estimating the IRF from SVD deconvolution with Tikhonov
regularization (6) and then obtaining the model parameters from non-linear
least squares fit of the resulting IRF to Eq. 1. The results for the proposed method (

**Model 1)** were compared to the apparent
leakage rate (K

_{a}) and leakage corrected normalized CBV (nCBV

_{corr})
estimated from the reference model of
Weisskoff et al. (

**Model 2**), implemented as in (3). Correlation between the estimates of K

^{trans}/ K

_{a}
and nCBV

_{corr} for the two models were compared using Spearman
correlation coefficient (ρ) from the mean tumor values obtained from the two
separate scanning sessions. Image
analysis was performed using nordicICE (NordicNeuroLab, Bergen, Norway).

### Results

Figure 1 shows sample cases of the generated maps using Model 1. Figure 2 shows the
test-retest correlation of leakage estimated from the two models. There was no
significant difference in the Spearman correlation coefficient for Model 1
versus Model 2 (McNemars test). Figure 2A shows the correlation between
corrected nCBV values obtained with Model 1 versus Model 2. Although the
overall correlation is high, a significant MTT-dependent difference in the nCBV
ratio between the two correction methods is observed (Figure 2B), in line with
the previously observed MTT-dependence of Model 2 (3).

### Discussion

We propose a modified CBV leakage correction method for DSC-MRI applying
the two-compartment uptake model and without the need for explicit AIF
determination. The proposed method yields test-retest stability similar to the
reference method, but with the added advantage of reduced MTT sensitivity and estimation of extraction fraction, E.
The model makes global assumptions about tissue perfusion and MTT in order to
construct an idealized AIF. Although average perfusion is likely to vary
between individuals and as a result of pathology, the method proved to have a high test-retest stability of leakage estimations
in glioblastoma patients.

### Acknowledgements

No acknowledgement found.### References

1. Boxerman J et
al. *AJNR* 2006 (27) 2. Weisskoff RM et al. *Proc SMR* San Francisco
(1994) 3. Bjornerud A et al. *J Cereb Blood Flow Metab* 2011 (31) 4. Sourbron S et al. *Magn Reson Med* 2009 (62) 5.
Sorensen AG et al. *Cancer
Res* 2012 (72). 6.
Bjornerud A et al. *J Cereb Blood Flow Metab* 2010 30(5).