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An Imaging-Informed Model for Convection Enhanced Radio-Liposome Delivery

R Woodall1*, D Hormuth1 , X Feng1 , W Phillips2 , A Bao3 , A Brenner2 , T Yankeelov1 , (1) The University of Texas at Austin, Austin, TX, (2) The University Of Texas San Antonio, San Antonio, Texas, (3) University Hospitals Cleveland Medical Center, Cleveland, OH

Presentations

(Sunday, 7/29/2018) 2:05 PM - 3:00 PM

Room: Karl Dean Ballroom B1

Purpose: To develop, calibrate, and validate a spatiotemporal model of convection enhanced rhenium-186 (¹��Re) liposome delivery for pre-surgical estimation of dosimetry in treatment of recurrent glioblastoma multiforme (GBM).

Methods: SPECT (137 keV) and x-ray CT imaging are performed on patients receiving 186Re-liposome treatment at time points during and immediately following infusion, as well as 24, 48, 120, and 196 hours post-infusion. Contrast-enhanced Tâ‚?-weighted MRI, and diffusion weighted MRI are performed prior to the procedure. CT images are used to develop a finite element model domain of the brain and catheter. Diffusion MRI data informs liposome diffusivity and permeability, while the post-contrast T1 data informs perfusion. An advection diffusion model of post-delivery liposome transport is developed, using the above domain and boundary conditions determined by the prescribed infusion rate. The model is calibrated to match SPECT images through 120 hours, and predicts the distribution of liposomes at 196 hours. Model error is assessed as the mean-squared error (MSE) between decay-corrected SPECT images and model output. The performance of a simplified model based on a small molecule agent, and constant material properties from literature, is used as a reference for model comparison.

Results: Qualitatively, the reference model overestimates the delivery volume of liposomes to the target region. Utilizing a diffusion imaging-informed diffusivity model calibrated to patient data, error was reduced by 14%. Further addition of a Tâ‚?-informed clearance term to the diffusion-informed model reduced error by 26%.

Conclusion: Models of convection enhanced liposome deliver, which assume a small molecular agent, are less accurate at predicting liposome distribution than patient-calibrated models making no assumptions of liposome size. The addition of imaging data further increased the accuracy of the model. These preliminary results indicate the potential of a patient-specific modeling tool for pre-surgical dosimetry, similar to those used for planning external beam therapy.

Funding Support, Disclosures, and Conflict of Interest: National Cancer Institutes, National Institutes of Health, Livestrong Foundation, Cancer Prevention Institute of Texas

Keywords

Brachytherapy, MRI, Optimization

Taxonomy

IM/TH- MRI in Radiation Therapy: MRI for treatment planning

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