Optimization and Evaluation of Anatomical Models of Liver Radiation Response

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The full utilization of radiation for liver cancer is limited by uncertainty in the radiation toxicity risk for patients with underlying liver disease and the inability to compute aggregate dose in the re-treatment setting due to large anatomical changes in responses to therapy. The NCI hepatocellular cancer working group has stated that the use of radiation to downstage prior to liver transplant should be a clinical research priority. In this setting, it is essential to induce complete ablation of the macroscopic disease, which has been shown to correlate with increased disease free survival, while maintaining a low toxicity profile. Functional imaging is beginning to play a role in understanding the impact of radiation on liver function, however the translation of image-based assessments have been hampered by the inability to accurately link the serially acquired images indicating response over time with an accurate assessment of the therapy that was delivered. Early experience with dynamic multi-organ anatomical models demonstrated that deformation technologies can improve treatment design, delivery, and evaluation of the accumulated dose in both the tumor and normal tissues. However, it was noted in these investigations that currently available anatomical models were not sufficient to describe complex deformation due the therapeutic response, notably in the liver where hypertrophy is observed in areas receiving minimal dose and fibrosis/necrosis/atrophy occurs in higher dose regions. Currently, there is not a clear understanding of determinants of hypertrophy/atrophy and methods to optimize this effect. We hypothesize that the differential anatomical changes in otherwise normal liver in response to radiation therapy of liver tumors can be described via dose-driven expansions/contractions in biomechanical models. Our preliminary data shows that these initial models can predict, a priori, the induced hypertrophy and fibrosis/necrosis/atrophy rates to within a 95% confidence interval in 80% of the cases. The sensitivity of the models to the optimization parameters indicate that additional refinement of the models can further improve this accuracy. The combination of this dose-driven expansion/contraction component of the model with the overall biomechanics describing stiffness and deformation, can facilitate safe dose-escalation to the tumor either in the definitive setting or as a bridge to transplant, enable quantitative assessment of therapy response during therapy and throughout follow up via deformable dose summation of the treatment received, and allow accurate correlation between longitudinal imaging of functional response and the delivered radiation therapy dose. IMPACT: The successful completion of this work will develop metrics to aid in the safe utilization of radiotherapy for the liver, improve correlation of functional imaging with delivered therapy, and, where necessary, enable the safe treatment of subsequent tumors in the liver, should they arise.