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Title: Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans

Abstract

Purpose: Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided guidance on the achievable sparing to organs-at-risk (OARs). However, in certain sites, such as head-and-neck, the clinical plans may not be sufficiently optimized because of anatomical complexity and clinical time constraints. This could lead to automated plans that suboptimally exploit OAR sparing. This work investigates a novel dose warping and scaling scheme that attempts to reduce effects of suboptimal sparing in clinical database plans, thus improving the quality of semiautomated head-and-neck cancer (HNC) plans. Methods: Knowledge-based radiotherapy (KBRT) plans for each of ten “query” patients were semiautomatically generated by identifying the most similar “match” patient in a database of 103 clinical manually created patient plans. The match patient’s plans were adapted to the query case by: (1) deforming the match beam fluences to suit the query target volume and (2) warping the match primary/boost dose distribution to suit the query geometry and using the warped distribution to generate query primary/boost optimization dose-volume constraints. Item (2) included a distance scaling factor to improvemore » query OAR dose sparing with respect to the possibly suboptimal clinical match plan. To further compensate for a component plan of the match case (primary/boost) not optimally sparing OARs, the query dose volume constraints were reduced using a dose scaling factor to be the minimum from either (a) the warped component plan (primary or boost) dose distribution or (b) the warped total plan dose distribution (primary + boost) scaled in proportion to the ratio of component prescription dose to total prescription dose. The dose-volume constraints were used to plan the query case with no human intervention to adjust constraints during plan optimization. Results: KBRT and original clinical plans were dosimetrically equivalent for parotid glands (mean/median doses), spinal cord, and brainstem (maximum doses). KBRT plans significantly reduced larynx median doses (21.5 ± 6.6 Gy to 17.9 ± 3.9 Gy), and oral cavity mean (32.3 ± 6.2 Gy to 28.9 ± 5.4 Gy) and median (28.7 ± 5.7 Gy to 23.2 ± 5.3 Gy) doses. Doses to ipsilateral parotid gland, larynx, oral cavity, and brainstem were lower or equivalent in the KBRT plans for the majority of cases. By contrast, KBRT plans generated without the dose warping and dose scaling steps were not significantly different from the clinical plans. Conclusions: Fast, semiautomatically generated HNC IMRT plans adapted from existing plans in a clinical database can be of equivalent or better quality than manually created plans. The reductions in OAR doses in the semiautomated plans, compared to the clinical plans, indicate that the proposed dose warping and scaling method shows promise in mitigating the impact of suboptimal clinical plans.« less

Authors:
;  [1];  [1];  [2];  [3];  [4]
  1. Medical Physics Graduate Program, Duke University, Durham, North Carolina 27708 (United States)
  2. Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708 (United States)
  3. Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27708 (United States)
  4. Medical Physics Graduate Program, Duke University, Durham, North Carolina 27708 and Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27708 (United States)
Publication Date:
OSTI Identifier:
22581391
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 42; Journal Issue: 8; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; GLANDS; HEAD; LARYNX; LIMITING VALUES; NECK; NEOPLASMS; OPTIMIZATION; ORAL CAVITY; PATIENTS; PLANNING; RADIATION DOSE DISTRIBUTIONS; RADIATION DOSES; RADIOTHERAPY; SCALING; SPINAL CORD

Citation Formats

Schmidt, Matthew, Grzetic, Shelby, Lo, Joseph Y., Department of Radiology, Duke University Medical Center, Durham, North Carolina 27708, Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, Lutzky, Carly, Brizel, David M., and Das, Shiva K. Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans. United States: N. p., 2015. Web. doi:10.1118/1.4923174.
Schmidt, Matthew, Grzetic, Shelby, Lo, Joseph Y., Department of Radiology, Duke University Medical Center, Durham, North Carolina 27708, Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, Lutzky, Carly, Brizel, David M., & Das, Shiva K. Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans. United States. https://doi.org/10.1118/1.4923174
Schmidt, Matthew, Grzetic, Shelby, Lo, Joseph Y., Department of Radiology, Duke University Medical Center, Durham, North Carolina 27708, Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, Lutzky, Carly, Brizel, David M., and Das, Shiva K. 2015. "Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans". United States. https://doi.org/10.1118/1.4923174.
@article{osti_22581391,
title = {Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans},
author = {Schmidt, Matthew and Grzetic, Shelby and Lo, Joseph Y. and Department of Radiology, Duke University Medical Center, Durham, North Carolina 27708 and Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708 and Lutzky, Carly and Brizel, David M. and Das, Shiva K.},
abstractNote = {Purpose: Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided guidance on the achievable sparing to organs-at-risk (OARs). However, in certain sites, such as head-and-neck, the clinical plans may not be sufficiently optimized because of anatomical complexity and clinical time constraints. This could lead to automated plans that suboptimally exploit OAR sparing. This work investigates a novel dose warping and scaling scheme that attempts to reduce effects of suboptimal sparing in clinical database plans, thus improving the quality of semiautomated head-and-neck cancer (HNC) plans. Methods: Knowledge-based radiotherapy (KBRT) plans for each of ten “query” patients were semiautomatically generated by identifying the most similar “match” patient in a database of 103 clinical manually created patient plans. The match patient’s plans were adapted to the query case by: (1) deforming the match beam fluences to suit the query target volume and (2) warping the match primary/boost dose distribution to suit the query geometry and using the warped distribution to generate query primary/boost optimization dose-volume constraints. Item (2) included a distance scaling factor to improve query OAR dose sparing with respect to the possibly suboptimal clinical match plan. To further compensate for a component plan of the match case (primary/boost) not optimally sparing OARs, the query dose volume constraints were reduced using a dose scaling factor to be the minimum from either (a) the warped component plan (primary or boost) dose distribution or (b) the warped total plan dose distribution (primary + boost) scaled in proportion to the ratio of component prescription dose to total prescription dose. The dose-volume constraints were used to plan the query case with no human intervention to adjust constraints during plan optimization. Results: KBRT and original clinical plans were dosimetrically equivalent for parotid glands (mean/median doses), spinal cord, and brainstem (maximum doses). KBRT plans significantly reduced larynx median doses (21.5 ± 6.6 Gy to 17.9 ± 3.9 Gy), and oral cavity mean (32.3 ± 6.2 Gy to 28.9 ± 5.4 Gy) and median (28.7 ± 5.7 Gy to 23.2 ± 5.3 Gy) doses. Doses to ipsilateral parotid gland, larynx, oral cavity, and brainstem were lower or equivalent in the KBRT plans for the majority of cases. By contrast, KBRT plans generated without the dose warping and dose scaling steps were not significantly different from the clinical plans. Conclusions: Fast, semiautomatically generated HNC IMRT plans adapted from existing plans in a clinical database can be of equivalent or better quality than manually created plans. The reductions in OAR doses in the semiautomated plans, compared to the clinical plans, indicate that the proposed dose warping and scaling method shows promise in mitigating the impact of suboptimal clinical plans.},
doi = {10.1118/1.4923174},
url = {https://www.osti.gov/biblio/22581391}, journal = {Medical Physics},
issn = {0094-2405},
number = 8,
volume = 42,
place = {United States},
year = {Sat Aug 15 00:00:00 EDT 2015},
month = {Sat Aug 15 00:00:00 EDT 2015}
}