# Optimization and Evaluation of Anatomical Models of Liver Radiation Response

> **NIH NIH R01** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2020 · $362,432

## Abstract

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,...

## Key facts

- **NIH application ID:** 9956594
- **Project number:** 5R01CA221971-03
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** Kristy Brock
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $362,432
- **Award type:** 5
- **Project period:** 2018-07-03 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9956594

## Citation

> US National Institutes of Health, RePORTER application 9956594, Optimization and Evaluation of Anatomical Models of Liver Radiation Response (5R01CA221971-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9956594. Licensed CC0.

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