Reliability of DCE pharmacokinetic parameter values for quantitative longitudinal assessment of brain tumors
Moran Artzi1, Gilad Liberman2,3, Deborah Blumenthal4, Orna Aizenstein1, and Dafna Ben Bashat1,5

1Functional Brain Center, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel, 2Functional Brain Centerasky Medical Cente, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel, 3Department of Chemical Physics, Weizmann Institute, Rehovot, Israel, 4Neuro-Oncology Service, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel, 5Sackler Faculty of Medicine and Sagol School of Neuroscience, Tel Aviv University, Tel-Aviv, Israel

Synopsis

DCE-MRI parameters have been shown to be useful for therapy response assessment in patient with glioblastoma, yet the estimated parameters may show high variation in their values. This study investigated the reliability of DCE parameters for quantitative longitudinal assessment of brain tumors. 14% standard-deviation in the WM and 12% in the GM, were detected for vp in healthy subjects(n=27). Results from six patients showed mean differences of 3.2%/9.7% in vp for WM/GM in the hemisphere contralateral to the lesion, comparing two longitudinal scans. Parametric-response-maps calculated within lesion areas based on the threshold values from the healthy controls supported radiological assessment.

PURPOSE

Quantitative measurement of brain tumors using dynamic-contrast-enhancement (DCE-MRI) has been shown to be useful for assessment of therapy response in patients with high grade tumors [1, 2]. However the estimated parameters may show high variation in their values due to biological differences, protocol parameters and analysis procedure. The aim of this study was to investigate the reliability of DCE pharmacokinetic (PK) values for quantitative longitudinal assessment of brain tumors.

METHODS

Subjects and MRI Protocol: 27 healthy controls (age 38±13 y) and six patients with biopsy-proven glioblastoma (GB) (age 49±19 y) were included in this study. Scans were performed on a 3.0T GE system and included T1 weighted imaging (T1WI) performed before and after contrast agent (Gd), FLAIR images and DCE acquired using multi-phase 3D SPGR with the variable flip angle method used for T1 maps calculation. Each patient was scanned twice.

Preprocessing: included skull stripping, inhomogeneity correction, T1 mapping, motion correction and coregistration to DCE space. Plasma volume(vp) and the volume transfer constant (ktrans) parameters were calculated from the DCE data using DUSTER (DCE-Up-Sampled-TEmporal Resolution), an in-house tool for DCE analysis, based on the Extended-Tofts-Model [3] with T1 maps calculated with correction of inaccuracy in the flip angles and accounting for differences in the bolus arrival time [4, 5]. The gray matter (GM) and white matter (WM) volumes of interest (VOIs) were extracted for each subject from pre-contrast T1WI; for the right and the left hemisphere for the healthy controls; and for the contra-lesional hemisphere only, for patients with GB. In patients, the lesion area was extracted at each time point from the T1WI+Gd images using threshold-based segmentation [6]. Lesion VOI was defined as the overlap lesion area between the two time points. Mean and standard deviation (SD) values and histograms of vp and ktrans in each VOI, were calculated.

Parametric response maps: were calculated separately for the vp and ktrans parameters. The SD values obtained in the control group from the WM area were used as threshold values for determining voxel-by-voxel differences between scans in patients, where Δ<-2SD=reduction; -2SD<Δ<+2SD=no change; Δ>+2SD=increase.

RESULTS & DISCUSSION

Healthy controls: Mean and SD values, of vp and ktrans in the WM and GM of healthy subjects (n=27), are shown in Table 1. Figure 1 shows the mean histograms of (a) vp and (b) ktrans obtained for the WM (red) and GM (blue) of healthy controls. vp and ktrans values were significantly (p<0.05) higher in the GM compared with the WM. No age, gender or hemispherical differences were detected for either parameter. The SD values of this group showed the reliability of the values of DCE parameters in the healthy population, and were set as threshold values for patients' assessment.

Patients: The mean values in the contra-lesional hemisphere were similar between the two time points in each patient, with mean differences of vp: GM=10%, WM=6%; ktrans: GM= 17%, WM=17% across time. Histograms of ktrans and vp in the WM (red), GM (blues) and lesion (black) areas at time point 1 (solid line) and time point 2 (dashed line), of three patients, are shown in Figure 2, demonstrating the high reproducibility of those parameters between the two time points. Parametric response maps within lesion area obtained for each patient (Fig.1; insets b-c). Patients #1 and #2 (two upper rows) were scanned before and two weeks following bevacizumab therapy, and revealed a substantial reduction in their mean values of: 30% and 81% for the vp and ktrans, respectively. The radiological assessment of these patients indicated improvement according to RANO criteria. Patient #3 was treated with VBL and bevacizumab therapies and was scanned at two month intervals. This patient demonstrated substantial increase of 52% and 128% for the vp and ktrans values, supporting the diagnosis of progression.

CONCLUSION

The means and SD values obtained from healthy subjects enable definition of threshold values for reliable quantitative assessment of changes of DCE PK parameters across longitudinal scans. Parametric response maps, based on these values, are suggested to be used for longitudinal assessment of patients with brain tumors, in order to improve patients' diagnosis and therapy response assessment.

Acknowledgements

To Faina Vitinshtein and Tuvia Genot for assistance in patient recruitment and MRI scans

References

[1] Hoff, B.A., et al., DCE and DW-MRI monitoring of vascular disruption following VEGF-Trap treatment of a rat glioma model. NMR Biomed, 2012. 25(7): p. 935-42; [2] O'Connor, J.P., et al., DCE-MRI biomarkers in the clinical evaluation of antiangiogenic and vascular disrupting agents. Br J Cancer, 2007. 96(2): p. 189-95; [3] Tofts, P.S. and A.G. Kermode, Measurement of the blood-brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts. MRM, 1991. 17(2): p. 357-67; [4] Liberman, G., Y. Louzoun, and D. Ben Bashat, T1 Mapping Using Variable Flip Angle SPGR Data With Flip Angle Correction. Journal of MRI, 2013; [5] Liberman, G., et al., Bolus Arrival Time extraction using Super Temporal Resolution Analysis of DCE, in The ISMRM 2014: Milan, Italy; [6] Artzi, M., et al., FLAIR lesion segmentation: application in patients with brain tumors and acute ischemic stroke. Eur J Radiol, 2013. 82(9): p. 1512-8.

Figures

Table 1: vp and ktrans values in the normal brain

Figure1: Histograms of the vp (a) and ktrans (b) values, obtained from right and the left hemisphere of all healthy controls (n=27); white matter (red), gray matter (blue).

Figure2: T1WI+Gd anatomical images (a); ktrans (b), and vp (c) histograms of the normal appearing white matter (red), gray matter (blue) and lesion area (black) obtained from longitudinal scans of 3 patients; Parametric response maps for ktrans and vp parameters are given as insets in b-c, light-blue=reduction; green=no change; orange=increase values.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
2776