Automated planning of breast radiotherapy using cone beam CT imaging

Authors

  • Amit Guy,

    1. Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G2M9, Canada
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  • Purdie Thomas G.

    1. Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G2M9, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5S 3E2, Canada; and Techna Institute, University Health Network, University of Toronto, Toronto, Ontario M5G 1P5, Canada
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Abstract

Purpose:

Develop and clinically validate a methodology for using cone beam computed tomography (CBCT) imaging in an automated treatment planning framework for breast IMRT.

Methods:

A technique for intensity correction of CBCT images was developed and evaluated. The technique is based on histogram matching of CBCT image sets, using information from “similar” planning CT image sets from a database of paired CBCT and CT image sets (n = 38). Automated treatment plans were generated for a testing subset (n = 15) on the planning CT and the corrected CBCT. The plans generated on the corrected CBCT were compared to the CT-based plans in terms of beam parameters, dosimetric indices, and dose distributions.

Results:

The corrected CBCT images showed considerable similarity to their corresponding planning CTs (average mutual information 1.0±0.1, average sum of absolute differences 185 ± 38). The automated CBCT-based plans were clinically acceptable, as well as equivalent to the CT-based plans with average gantry angle difference of 0.99°±1.1°, target volume overlap index (Dice) of 0.89±0.04 although with slightly higher maximum target doses (4482±90 vs 4560±84, P < 0.05). Gamma index analysis (3%, 3 mm) showed that the CBCT-based plans had the same dose distribution as plans calculated with the same beams on the registered planning CTs (average gamma index 0.12±0.04, gamma <1 in 99.4%±0.3%).

Conclusions:

The proposed method demonstrates the potential for a clinically feasible and efficient online adaptive breast IMRT planning method based on CBCT imaging, integrating automation.

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