2009 Summer project week adaptive radiation planning visualization
Key Investigators
- Des Moines University, Department of Anatomy: Cal Hisley, Ph.D.
- Mercy Des Moines Medical Center, Department of Radiology, William Young, MD
- Mercy Des Moines Medical Center, Department of Radiation Oncology, Richard Deming, MD
- Mercy Des Moines Medical Center, Department of Radiation Oncology, Kenneth Berstein, Ph.D.
Objective
We are applying functional magnetic resonance imaging, including BOLD and DTI to study the feasibility of adaptive radiation therapy treatment planning and longitudinal tracking/visualization. This is our initial effort and we are concentrating on the application of white matter tractography to improved clinical target volume delineation, tumor characterization and theraputic effects tracking.
Approach, Plan
Our approach will be to add DTI pulse sequences to the end of the standard brain MT protocol on our GE HDx 3T magnet and then, along with the routine tissue density mapping performed in RadOnc using CT, perform parallel dosimetry planning procedures - one using just the standard brain MR protocol and one fusing the added white matter tractography FA maps/reconstructions with the MR and CT images. We expect to observe improved delineation of tumor margins, improvements in treatment responses as measured by standard clinical measures and potential prognostic value for patient signs/symptoms course based on the identified white matter tracks involved.<foo>.
Our plan for the project week is to find out what, if any, DICOM-RT import/export functions are available in slicer and design a composite visualization method able to overlay the results from sequential followup scans as a longitudinal tracking tool.
Progress
Scanning is ready to begin and we are ready to begin accumulating cases. We are now working on our SLICER foundation.
References
1. Purdy JA. et. al.; Dose to normal tissue outside the radiation therapy patient's treat volume.; Health Physics 95(5):666-676; 2008. 2. Burnet NG. et. al.; Defining the tumor and target volumes for radiotherapy; Cancer Imaging (2004) 4, 153-161. 3. Jena R. et. al.; Diffusion Tensor Imaging: possible implications for radiotherapy treatment planning of patients with high-grade glioma.; Clinical Oncology (2005 17:581-590. 4. Wei CW. et. al.; Tumor effects on cerebral white matter as characterized by diffusion tensor tractography; Ca. J. Neurological Sciences 2007; 34:62-69. 5. Lu S. et. al.; Diffusion-Tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction to the tumor infiltration index.; Radiology 2004 232:221-228. 6. Goebell E. et. al.; Low-grade and anaplastic gliomas: differences in architecture evaluated with diffusion-tensor MR imaging.; Radiology V239: Number 1 - April 2006, 217-221. 7. Peng H. et. al.; Development of a human brain diffusion tensor template.; Neuroimage 46 (2009) 967-980.
