Exploiting tumor shrinkage through temporal optimization of radiotherapy.

Area of Science:

• Radiation Oncology
• Mathematical Modeling
• Tumor Biology

Background:

• Multi-stage radiotherapy offers potential normal tissue sparing by exploiting tumor shrinkage.
• Clinical management of large liver tumors is limited by normal tissue dose constraints.
• Single-stage treatments may not achieve ablative doses due to these constraints.

Purpose of the Study:

• To optimize the design of multi-stage radiotherapy treatments.
• To minimize total normal tissue dose while ensuring prescribed tumor dose delivery.
• To investigate optimal radiation timing and dose fractionation for liver tumors.

Main Methods:

• Introduction of a dynamic tumor model incorporating cell kill, shrinkage, and repopulation.
• Formulation of multi-stage radiotherapy design as a mathematical optimization problem.
• Detailed analysis of two-stage treatment scenarios.

Main Results:

• Optimal timing for the second stage is just before tumor repopulation negates shrinkage benefits.
• Approximately one-third of the total dose is recommended for the first stage.
• Model predicts potential normal tissue dose reductions exceeding a factor of 2.

Conclusions:

• Optimal design of multi-stage radiotherapy can substantially reduce normal tissue dose.
• Exploiting tumor shrinkage through dynamic treatment planning is key.
• This approach warrants consideration for sites with significant tumor regression.