TY - JOUR
T1 - Prospective randomized double-blind study of atlas-based organ-at-risk autosegmentation-assisted radiation planning in head and neck cancer
AU - Walker, Gary V.
AU - Awan, Musaddiq
AU - Tao, Randa
AU - Koay, Eugene J.
AU - Boehling, Nicholas S.
AU - Grant, Jonathan D.
AU - Sittig, Dean F.
AU - Gunn, Gary Brandon
AU - Garden, Adam S.
AU - Phan, Jack
AU - Morrison, William H.
AU - Rosenthal, David I.
AU - Mohamed, Abdallah Sherif Radwan
AU - Fuller, Clifton David
N1 - Funding Information:
Dr. Walker is supported by a training fellowship from the Keck Center for Interdisciplinary Bioscience Training of the Gulf Coast Consortia (Grant No. T15 LM007093 ) and from a 2013 Concur Cancer Foundation of the American Society of Clinical Oncology Merit Award. Dr. Fuller received/receives grant/funding support from the SWOG/Hope Foundation Dr. Charles A. Coltman, Jr., Fellowship in Clinical Trials, the National Institutes of Health Clinician Scientist Loan Repayment Program ( L30 CA136381-02 ), Elekta AB (Stockholm, SE), the Center for Radiation Oncology Research at MD Anderson Cancer Center, and the MD Anderson Institutional Research Grant Program.
Funding Information:
In-kind support was provided as pre-release version of Pinnacle3 V9.4 by Koninklijke Philips N.V. (Eindhoven, NL), under a master research agreement (MRA) with the University of Texas MD Anderson Cancer Center.
Publisher Copyright:
© 2014 Elsevier Ireland Ltd. All rights reserved.
PY - 2014/9/1
Y1 - 2014/9/1
N2 - Background and purpose Target volumes and organs-at-risk (OARs) for radiotherapy (RT) planning are manually defined, which is a tedious and inaccurate process. We sought to assess the feasibility, time reduction, and acceptability of an atlas-based autosegmentation (AS) compared to manual segmentation (MS) of OARs. Materials and methods A commercial platform generated 16 OARs. Resident physicians were randomly assigned to modify AS OAR (AS + R) or to draw MS OAR followed by attending physician correction. Dice similarity coefficient (DSC) was used to measure overlap between groups compared with attending approved OARs (DSC = 1 means perfect overlap). 40 cases were segmented. Results Mean ± SD segmentation time in the AS + R group was 19.7 ± 8.0 min, compared to 28.5 ± 8.0 min in the MS cohort, amounting to a 30.9% time reduction (Wilcoxon p < 0.01). For each OAR, AS DSC was statistically different from both AS + R and MS ROIs (all Steel-Dwass p < 0.01) except the spinal cord and the mandible, suggesting oversight of AS/MS processes is required; AS + R and MS DSCs were non-different. AS compared to attending approved OAR DSCs varied considerably, with a chiasm mean ± SD DSC of 0.37 ± 0.32 and brainstem of 0.97 ± 0.03. Conclusions Autosegmentation provides a time savings in head and neck regions of interest generation. However, attending physician approval remains vital.
AB - Background and purpose Target volumes and organs-at-risk (OARs) for radiotherapy (RT) planning are manually defined, which is a tedious and inaccurate process. We sought to assess the feasibility, time reduction, and acceptability of an atlas-based autosegmentation (AS) compared to manual segmentation (MS) of OARs. Materials and methods A commercial platform generated 16 OARs. Resident physicians were randomly assigned to modify AS OAR (AS + R) or to draw MS OAR followed by attending physician correction. Dice similarity coefficient (DSC) was used to measure overlap between groups compared with attending approved OARs (DSC = 1 means perfect overlap). 40 cases were segmented. Results Mean ± SD segmentation time in the AS + R group was 19.7 ± 8.0 min, compared to 28.5 ± 8.0 min in the MS cohort, amounting to a 30.9% time reduction (Wilcoxon p < 0.01). For each OAR, AS DSC was statistically different from both AS + R and MS ROIs (all Steel-Dwass p < 0.01) except the spinal cord and the mandible, suggesting oversight of AS/MS processes is required; AS + R and MS DSCs were non-different. AS compared to attending approved OAR DSCs varied considerably, with a chiasm mean ± SD DSC of 0.37 ± 0.32 and brainstem of 0.97 ± 0.03. Conclusions Autosegmentation provides a time savings in head and neck regions of interest generation. However, attending physician approval remains vital.
KW - Atlas-based autosegmentation
KW - Autocontouring
KW - Automatic segmentation
KW - Head and neck
KW - Normal tissue
KW - Organs-at-risk
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U2 - 10.1016/j.radonc.2014.08.028
DO - 10.1016/j.radonc.2014.08.028
M3 - Article
C2 - 25216572
AN - SCOPUS:84910147436
SN - 0167-8140
VL - 112
SP - 321
EP - 325
JO - Radiotherapy and Oncology
JF - Radiotherapy and Oncology
IS - 3
ER -