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. 2009 Jul-Aug;8(4):187-98.

Coregistration of ultrasonography and magnetic resonance imaging with a preliminary investigation of the spatial colocalization of vascular endothelial growth factor receptor 2 expression and tumor perfusion in a murine tumor model

Mary E Loveless  1 , Jennifer G Whisenant, Kevin Wilson, Andrej Lyshchik, Tuhin K Sinha, John C Gore, Thomas E Yankeelov
Affiliations

Coregistration of ultrasonography and magnetic resonance imaging with a preliminary investigation of the spatial colocalization of vascular endothelial growth factor receptor 2 expression and tumor perfusion in a murine tumor model

Mary E Loveless et al. Mol Imaging. 2009 Jul-Aug.

Abstract

We present an ultrasonography (US)-magnetic resonance imaging (MRI) coregistration technique and examine its application in a preliminary multimodal, multiparametric study in a preclinical model of breast cancer. Nine mice were injected with 67NR breast cancer cells and imaged 6 and 9 days later with 4.7 T MRI and high-frequency US. Tumor volumes from each data set were segmented independently by two investigators and coregistered using an iterative closest point algorithm. In addition to anatomic images, vascular endothelial growth factor receptor 2 (VEGFR2) distribution images from the central tumor slice using VEGFR2-targeted ultrasound contrast agent (UCA) and measurements of perfusion and extravascular-extracellular volume fraction using dynamic contrast-enhanced MRI were acquired from five mice for multiparametric coregistration. Parametric maps from each modality were coregistered and examined for spatial correlation. Average registration root mean square (RMS) error was 0.36 +/- 0.11 mm, less than approximately two voxels. Segmented volumes were compared between investigators to minimize interobserver variability; the average RMS error was 0.23 +/- 0.09 mm. In the preliminary study, VEGFR2-targeted UCA data did not demonstrate direct spatial correlation with magnetic resonance measures of vascular properties. In summary, a method for accurately coregistering small animal US and MRI has been presented that allows for comparison of quantitative metrics provided by the two modalities.

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Figures

Figure 1
Figure 1
Time line of the imaging protocols used in this study. A minimum of ~1.5 hours are required for high resolution anatomical and DCE-MRI data acquisition. The VEGFR2-targeted UCA requires four minutes, per manufacturer's guidelines, to bind in vivo. A destruction pulse is administered, destroying all UCA so that the unbound contrast agent that flow into the region (Reference frames) can be subtract from the frames containing both
Figure 2
Figure 2
US and MRI coregistration steps. Tumor margins were manually segmented from MRI and US images (A,D); contour lines (blue and green) and cross hairs (yellow) were drawn to demonstrate registration results (B,E); for clarity, segmented tumor volume from US (“jet” color scheme) was overlaid on MRI (C,F). Note the difference in FOV listed at the bottom of panels a and d.
Figure 3
Figure 3
Registration results for mouse 4 and 7 at time points 1 (A,B; E,F) and 2 (C,D; G,H). Contour lines and cross hairs are drawn, as in Figure 2, to demonstrate registration results. In each of these panels, the arrow and the letters T and M represent the skin layer, center of the tumor, and surrounding muscle, respectively.
Figure 4
Figure 4
Results from US-MRI Registration. Panel A: In order to reduce inter-observer variation, boundaries were assessed and volumes for each image set for each modality. The `·' shows the average volume calculated from both investigators and both modalities while the dashed lines (horizontal is MRI and vertical is US) show the error associated with the volume for the respective modality. The data points fit the line of unity with an r = 0.9997 (y = 0.9808x + 1.8441). Panel B: Average registration RMS error (·) and the associated standard deviations (dashed lines) are plotted versus average volume. The linear fit (solid line) shows an upward trend with increasing volume (y = 0.0007x + 0.2546, r = 0.657).
Figure 5
Figure 5
Results from US-MRI Segmentation. Panel A: Average segmentation RMS error (·) and the associated standard deviations (dashed lines) are plotted versus average volume. The linear fit (solid line) shows a similar increasing trend with increasing volume (y = 0.0005x + 0.1499, r = 0.680). Panel B: RMS segmentation error is plotted for each modality, depicting a larger variability with segmentation in US than MRI.
Figure 6
Figure 6
Step by step demonstration of the registration between parametric maps produced by MRI and US. Panels a and d illustrate the segmentation of the tumor from both MRI (A) and US (D). Once the image sets have been registered (panels B and E), transformations are applied to the maps of Ktrans and VEGFR2 from the respective modalities. The maps can then be compared on a voxel by voxel basis (panels C and F).
Figure 7
Figure 7
Parametric maps of VEGFR2 distribution, Ktrans, and ve for two mice at two time points. Panels A and D and panels G and J show the VEGFR2 distributions for mouse 1 and mouse 4, respectively at both time point while B, E, H, K demonstrate the Ktrans maps. ve maps are presented in panels C, F, I, and L. While a spatial correlation between VEGFR2 and ve maps was not expected, correlation between VEGFR2 and Ktrans was anticipated; however, both visual and quantitative analysis show that there does not appear to be any significant correlation between these two metrics.
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