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Title: Automated planning of breast radiotherapy using cone beam CT imaging

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 themore » 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.« less

Authors:
 [1];  [1];  [2];  [2]
  1. Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G2M9 (Canada)
  2. (Canada)
Publication Date:
OSTI Identifier:
22413443
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 42; Journal Issue: 2; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; 60 APPLIED LIFE SCIENCES; AUTOMATION; CAT SCANNING; MAMMARY GLANDS; PLANNING; RADIATION DOSE DISTRIBUTIONS; RADIOTHERAPY

Citation Formats

Amit, Guy, Purdie, Thomas G., E-mail: tom.purdie@rmp.uhn.ca, Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5S 3E2, and Techna Institute, University Health Network, University of Toronto, Toronto, Ontario M5G 1P5. Automated planning of breast radiotherapy using cone beam CT imaging. United States: N. p., 2015. Web. doi:10.1118/1.4905111.
Amit, Guy, Purdie, Thomas G., E-mail: tom.purdie@rmp.uhn.ca, Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5S 3E2, & Techna Institute, University Health Network, University of Toronto, Toronto, Ontario M5G 1P5. Automated planning of breast radiotherapy using cone beam CT imaging. United States. doi:10.1118/1.4905111.
Amit, Guy, Purdie, Thomas G., E-mail: tom.purdie@rmp.uhn.ca, Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5S 3E2, and Techna Institute, University Health Network, University of Toronto, Toronto, Ontario M5G 1P5. Sun . "Automated planning of breast radiotherapy using cone beam CT imaging". United States. doi:10.1118/1.4905111.
@article{osti_22413443,
title = {Automated planning of breast radiotherapy using cone beam CT imaging},
author = {Amit, Guy and Purdie, Thomas G., E-mail: tom.purdie@rmp.uhn.ca and Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5S 3E2 and Techna Institute, University Health Network, University of Toronto, Toronto, Ontario M5G 1P5},
abstractNote = {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.},
doi = {10.1118/1.4905111},
journal = {Medical Physics},
number = 2,
volume = 42,
place = {United States},
year = {Sun Feb 15 00:00:00 EST 2015},
month = {Sun Feb 15 00:00:00 EST 2015}
}