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Utilising pseudo-CT data for dose calculation and plan optimization in adaptive radiotherapy.

Brendan Whelan^1,2,3, Shivani Kumar^4,5, Jason Dowling⁶

¹Liverpool and Macarthur Cancer Therapy Centers and Ingham Institute for Applied Medical Science, Room 302, Medical Foundation Building, 92-94 Parramatta Road, Camperdown, Sydney, NSW, 2050, Australia. brendan.whelan@sydney.edu.au.

Australasian Physical & Engineering Sciences in Medicine

|September 5, 2015

Summary

Using pseudo-computed tomography (pseudo-CT) data for inverse treatment planning in cervix cancer patients results in clinically acceptable dose calculation errors and optimization uncertainty. This approach is feasible for adaptive radiotherapy and MRI-based planning.

Keywords:

Adaptive radiotherapy Electron density Inverse treatment MRI treatment planning Planning

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Area of Science:

Medical Physics
Radiation Oncology
Radiotherapy Planning

Background:

Adaptive radiotherapy and MRI-based planning require accurate electron density data.
Inaccurate electron density data, such as pseudo-CT, can introduce errors in dose calculation and treatment planning.
Quantifying these errors is crucial for clinical implementation.

Purpose of the Study:

To quantify dose calculation error and optimization uncertainty from using pseudo-CT data in inverse treatment planning.
To assess the clinical acceptability of these errors for cervix cancer patients.
To evaluate the feasibility of pseudo-CT for adaptive and MRI-based radiotherapy.

Main Methods:

Generated four pseudo-CT datasets from planning CT data of 10 cervix cancer patients.
Developed inverse-modulated radiotherapy (IMRT) plans on both planning CT and pseudo-CT datasets.
Quantified dose calculation error by comparing dose distributions and optimization uncertainty by re-optimizing plans.
Assessed dose differences using Equivalent Uniform Dose (EUD) for targets and organs at risk.

Main Results:

Absolute mean dose calculation error was 0.2 Gy, within 2% of prescription dose in 98.5% of cases.
Absolute mean optimization error was 0.3 Gy EUD, indicating inverse optimization is impacted.
The additional uncertainty introduced is small compared to existing variations.

Conclusions:

Using pseudo-CT data for inverse treatment planning introduces clinically acceptable dose calculation errors and optimization uncertainty for cervix cancer patients.
Dose calculation and inverse optimization on pseudo-CT are feasible for this patient cohort.
This validates the use of pseudo-CT in adaptive and MRI-based radiotherapy planning.