Monitoring and modeling cancer cell
migration in the rat brain
Investigators: W. O'Dell, Anitha Krishnan, Divya Raman, Sharmistha Chaudhuri, Scott Kennedy, John Olschowka, Bruce Fenton, Sammy N'dive.

Aims
While patient data provides valuable observations of cancer recurrence patterns (see our patient MR-DTI/MRS page for further details), to advance our scientific understanding of the effects of tissue architecture on cell migratory behavior and thereby improve the accuracy of our model, more quantitative and direct measures of cell spread in animal models are needed. For an animal model of high-grade human glioma, we are using a unique, genetically-enhanced infiltrating native rat brain cancer cell line (HEBAB/brevican CNS-1 Rat Glioma cells) prepared by our colleagues Drs. Hong Zhang and Russell Matthews.

Figure 1 [A] In vivo and [C] ex vivo> T2-weighted MR images of the same rat brain at comparable resolution.	[B] Tractography was performed on the ex vivo MR-DTI data to demonstrate major fiber bundles passing through the corpus callosum.	[C] The computational migration model was run starting at the location indicated by the arrow. Most simulated cells stayed on or near the major fiber bundle with many moving out of plane (not seen here).

Methods
In vivo anatomical (T2-weighted) MR images in a rat brain were acquired at 3T with 0.27x0.27x1.0 mm resolution and the same brain was then extracted, fixed and scanned ex vivo with a DTI sequence on the 9.4T system with a resolution of 117x163x117 um. Representative images are shown in Figure 1A&C. The MR-DTI from the above ex vivo study was processed to generate 3D fiber maps of the major fiber bundles of the rat (Figure 1B). The computational model was then run on this data set, as demonstrated in Figure 1C, starting from a point adjacent to a major fiber bundle.

A second rat brain was MR-DTI imaged ex vivo as above and histologically sectioned. A representative set of six sequential histological sections, without staining, were photographed, each slice 40?m thick and separated by 920?m. The approximate MR section was selected by inspection for comparison (Figure 2). A close match is observed before application of any high level registration.

Figure 2. Representative ex vivo MRI [A] and histological [B] sections in the same rat brain showing high fidelity results and good spatial correspondence. These results give credence that with appropriate deformable registration the MR and histological results can be aligned adequately for the purposes of this study.

Future Work
In vivo MR-DTI at 3T will be performed as demonstrated by us in Figure 1A prior to the engraftment of approximately 100,000 cells. The brains will be carefully harvested and imaged ex vivo at 9.4T to aid in registration, followed by histological analysis of sectioned brain slices (as in Figure 1B but with 40?m thick slices imaged every ~120?m throughout the hemi-brain of interest) to identify the spread of GFP-labeled cells. Custom image processing software for automatic detection and statistical assessment of labeled cells will be created. Registration of the histological sections with the ex vivo MR image (as in Figure 2A) will be performed using a b-spline grid-based deformable registration method developed previously by the PI and colleagues.

Related Presentions

1. Krishnan AP, Davis DD, Okunieff P, O'Dell WG
   Random walk model for predicting patterns of microscopic glioma spread using DTI: A prospective study
   17th ISMRM Scientific Meeting and Exhibition (#142 - Talk), Honolulu, Hawaii, April 2009
2. Krishnan AP, Davis DD, Okunieff P, O'Dell WG
   Random walk models based on DTI for determining the microscopic spread of gliomas
   5th IEEE International Symposium on Biomedical Imaging, Paris FR, June 2008
3. Krishnan AP, Davis DD, Okunieff P, O'Dell WG
   Preliminary results of the effects of higher order reconstruction on Diffusion MRI data on our predictive model for tumor recurrence
   16th Annual ISMRM Scientific Meeting (#5545 -Eposter), Toronto CA, May 2008
4. Krishnan AP, Asher MI, Fuller D, Davis DD, Okunieff P, O’Dell WG
   Evidence That Diffusion Tensor Imaging Predicts the Natural History of Regional Recurrence in Patients Irradiated Conformally for Primary Brain Tumors
   15th Annual ISMRM Scientific Meeting (#345 - Talk), Berlin GER, June 2007
5. Krishnan AP, Asher MI, Fuller D, Davis DD, Okunieff P, O’Dell WG
   Patterns of Brain Tumor Recurrence Predicted From DTI Tractography
   48th Annual AAPM Meeting (TU-C-330A-2), Orlando FL, July 2006