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Author Notes:

Correspondence: xiaofeng.yang@emory.edu


Research Funding:

This research is supported in part by the National Cancer Institute of the National Institutes of Health under Award Number R01CA215718 and Dunwoody Golf Club Prostate Cancer Research Award, a philanthropic award provided by the Winship Cancer Institute of Emory University.


  • Adaptive radiation therapy
  • Cone-beam CT
  • Brain Neoplasms
  • Cone-Beam Computed Tomography
  • Decision Trees
  • Humans
  • Machine Learning
  • Organs at Risk
  • Pelvis
  • Quality Improvement
  • Radiometry
  • Radiosurgery
  • Radiotherapy Dosage
  • Radiotherapy Planning, Computer-Assisted
  • Retrospective Studies

Dosimetric study on learning-based cone-beam CT correction in adaptive radiation therapy

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Journal Title:

Medical Dosimetry


Volume 44, Number 4


, Pages e71-e79

Type of Work:

Article | Post-print: After Peer Review


Introduction: Cone-beam CT (CBCT) image quality is important for its quantitative analysis in adaptive radiation therapy. However, due to severe artifacts, the CBCTs are primarily used for verifying patient setup only so far. We have developed a learning-based image quality improvement method which could provide CBCTs with image quality comparable to planning CTs (pCTs). The accuracy of dose calculations based on these CBCTs is unknown. In this study, we aim to investigate the dosimetric accuracy of our corrected CBCT (CCBCT) in brain stereotactic radiosurgery (SRS) and pelvic radiotherapy. Materials and Methods: We retrospectively investigated a total of 32 treatment plans from 22 patients, each of whom with both original treatment pCTs and CBCTs acquired during treatment setup. The CCBCT and original CBCT (OCBCT) were registered to the pCT for generating CCBCT-based and OCBCT-based treatment plans. The original pCT-based plans served as ground truth. Clinically-relevant dose volume histogram (DVH) metrics were extracted from the ground truth, OCBCT-based and CCBCT-based plans for comparison. Gamma analysis was also performed to compare the absorbed dose distributions between the pCT-based and OCBCT/CCBCT-based plans of each patient. Results: CCBCTs demonstrated better image contrast and more accurate HU ranges when compared side-by-side with OCBCTs. For pelvic radiotherapy plans, the mean dose error in DVH metrics for planning target volume (PTV), bladder and rectum was significantly reduced, from 1% to 0.3%, after CBCT correction. The gamma analysis showed the average pass rate increased from 94.5% before correction to 99.0% after correction. For brain SRS treatment plans, both original and corrected CBCT images were accurate enough for dose calculation, though CCBCT featured higher image quality. Conclusion: CCBCTs can provide a level of dose accuracy comparable to traditional pCTs for brain and prostate radiotherapy planning and the correction method proposed here can be useful in CBCT-guided adaptive radiotherapy.

Copyright information:

© 2019 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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