Akila N Viswanathan1, Beth Erickson2, David K Gaffney3, Sushil Beriwal4, Sudershan K Bhatia5, Omer Lee Burnett6, David P D'Souza7, Nikhilesh Patil7, Michael G Haddock8, Anuja Jhingran9, Ellen L Jones10, Charles A Kunos11, Larissa J Lee12, Lilie L Lin13, Nina A Mayr14, Ivy Petersen8, Primoz Petric15, Lorraine Portelance16, William Small17, Jonathan B Strauss18, Kanokpis Townamchai12, Aaron H Wolfson16, Catheryn M Yashar19, Walter Bosch20. 1. Brigham & Women's Hospital/Dana-Farber Cancer Institute, Boston, Massachusetts. Electronic address: aviswanathan@lroc.harvard.edu. 2. Medical College of Wisconsin, Milwaukee, Wisconsin. 3. University of Utah Huntsman Cancer Hospital, Salt Lake City, Utah. 4. University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania. 5. University of Iowa, Iowa City, Iowa. 6. University of Alabama, Birmingham, Alabama. 7. London Health Sciences Centre and Western University, London, Ontario, Canada. 8. Mayo Medical Center, Rochester, Minnesota. 9. University of Texas MD Anderson Cancer Center, Houston, Texas. 10. University of North Carolina, Chapel Hill, North Carolina. 11. Case Western Reserve University, Cleveland, Ohio. 12. Brigham & Women's Hospital/Dana-Farber Cancer Institute, Boston, Massachusetts. 13. University of Pennsylvania, Philadelphia, Pennsylvania. 14. University of Washington, Seattle, Washington. 15. Division of Radiotherapy, Institute of Oncology Ljubljana, Ljubljana, Slovenia; Department of Radiation Oncology, National Center for Cancer Care and Research, Doha, Qatar. 16. University of Miami Miller School of Medicine, Miami, Florida. 17. Loyola University Strich School of Medicine, Chicago, Illinois. 18. The Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, Illinois. 19. University of California, San Diego, California, Washington University, St. Louis, Missouri. 20. Washington University, St. Louis, Missouri.
Abstract
OBJECTIVE: To create and compare consensus clinical target volume (CTV) contours for computed tomography (CT) and 3-Tesla (3-T) magnetic resonance (MR) image-based cervical-cancer brachytherapy. METHODS AND MATERIALS: Twenty-three experts in gynecologic radiation oncology contoured the same 3 cervical cancer brachytherapy cases: 1 stage IIB near-complete response (CR) case with a tandem and ovoid, 1 stage IIB partial response (PR) case with tandem and ovoid with needles, and 1 stage IB2 CR case with a tandem and ring applicator. The CT contours were completed before the MRI contours. These were analyzed for consistency and clarity of target delineation using an expectation maximization algorithm for simultaneous truth and performance level estimation (STAPLE), with κ statistics as a measure of agreement between participants. The conformity index was calculated for each of the 6 data sets. Dice coefficients were generated to compare the CT and MR contours of the same case. RESULTS: For all 3 cases, the mean tumor volume was smaller on MR than on CT (P<.001). The κ and conformity index estimates were slightly higher for CT, indicating a higher level of agreement on CT. The Dice coefficients were 89% for the stage IB2 case with a CR, 74% for the stage IIB case with a PR, and 57% for the stage IIB case with a CR. CONCLUSION: In a comparison of MR-contoured with CT-contoured CTV volumes, the higher level of agreement on CT may be due to the more distinct contrast medium visible on the images at the time of brachytherapy. MR at the time of brachytherapy may be of greatest benefit in patients with large tumors with parametrial extension that have a partial or complete response to external beam. On the basis of these results, a 95% consensus volume was generated for CT and for MR. Online contouring atlases are available for instruction at http://www.nrgoncology.org/Resources/ContouringAtlases/GYNCervicalBrachytherapy.aspx.
OBJECTIVE: To create and compare consensus clinical target volume (CTV) contours for computed tomography (CT) and 3-Tesla (3-T) magnetic resonance (MR) image-based cervical-cancer brachytherapy. METHODS AND MATERIALS: Twenty-three experts in gynecologic radiation oncology contoured the same 3 cervical cancer brachytherapy cases: 1 stage IIB near-complete response (CR) case with a tandem and ovoid, 1 stage IIB partial response (PR) case with tandem and ovoid with needles, and 1 stage IB2 CR case with a tandem and ring applicator. The CT contours were completed before the MRI contours. These were analyzed for consistency and clarity of target delineation using an expectation maximization algorithm for simultaneous truth and performance level estimation (STAPLE), with κ statistics as a measure of agreement between participants. The conformity index was calculated for each of the 6 data sets. Dice coefficients were generated to compare the CT and MR contours of the same case. RESULTS: For all 3 cases, the mean tumor volume was smaller on MR than on CT (P<.001). The κ and conformity index estimates were slightly higher for CT, indicating a higher level of agreement on CT. The Dice coefficients were 89% for the stage IB2 case with a CR, 74% for the stage IIB case with a PR, and 57% for the stage IIB case with a CR. CONCLUSION: In a comparison of MR-contoured with CT-contoured CTV volumes, the higher level of agreement on CT may be due to the more distinct contrast medium visible on the images at the time of brachytherapy. MR at the time of brachytherapy may be of greatest benefit in patients with large tumors with parametrial extension that have a partial or complete response to external beam. On the basis of these results, a 95% consensus volume was generated for CT and for MR. Online contouring atlases are available for instruction at http://www.nrgoncology.org/Resources/ContouringAtlases/GYNCervicalBrachytherapy.aspx.
Authors: Akila N Viswanathan; Carien L Creutzberg; Peter Craighead; Mary McCormack; Takafumi Toita; Kailash Narayan; Nicholas Reed; Harry Long; Hak-Jae Kim; Christian Marth; Jacob C Lindegaard; Annmarie Cerrotta; William Small; Edward Trimble Journal: Int J Radiat Oncol Biol Phys Date: 2010-12-22 Impact factor: 7.038
Authors: Ina M Jürgenliemk-Schulz; Robbert J H A Tersteeg; Judith M Roesink; Stefan Bijmolt; Christel N Nomden; Marinus A Moerland; Astrid A C de Leeuw Journal: Radiother Oncol Date: 2009-09-11 Impact factor: 6.280
Authors: Rawan Allozi; X Allen Li; Julia White; Aditya Apte; An Tai; Jeff M Michalski; Walter R Bosch; Issam El Naqa Journal: Radiother Oncol Date: 2010-08-11 Impact factor: 6.280
Authors: Hiram A Gay; H Joseph Barthold; Elizabeth O'Meara; Walter R Bosch; Issam El Naqa; Rawan Al-Lozi; Seth A Rosenthal; Colleen Lawton; W Robert Lee; Howard Sandler; Anthony Zietman; Robert Myerson; Laura A Dawson; Christopher Willett; Lisa A Kachnic; Anuja Jhingran; Lorraine Portelance; Janice Ryu; William Small; David Gaffney; Akila N Viswanathan; Jeff M Michalski Journal: Int J Radiat Oncol Biol Phys Date: 2012-04-06 Impact factor: 7.038
Authors: Richard Pötter; Petra Georg; Johannes C A Dimopoulos; Magdalena Grimm; Daniel Berger; Nicole Nesvacil; Dietmar Georg; Maximilian P Schmid; Alexander Reinthaller; Alina Sturdza; Christian Kirisits Journal: Radiother Oncol Date: 2011-08-05 Impact factor: 6.280
Authors: Sophia C Kamran; Matthias M Manuel; Linda P Cho; Antonio L Damato; Ehud J Schmidt; Clare Tempany; Robert A Cormack; Akila N Viswanathan Journal: Gynecol Oncol Date: 2017-03-18 Impact factor: 5.482
Authors: Sophia C Kamran; Matthias M Manuel; Paul Catalano; Linda Cho; Antonio L Damato; Larissa J Lee; Ehud J Schmidt; Akila N Viswanathan Journal: Brachytherapy Date: 2017-08-17 Impact factor: 2.362
Authors: Cameron W Swanick; Katherine O Castle; Sastry Vedam; Mark F Munsell; Lehendrick M Turner; Gaiane M Rauch; Anuja Jhingran; Patricia J Eifel; Ann H Klopp Journal: Int J Radiat Oncol Biol Phys Date: 2016-07-30 Impact factor: 7.038
Authors: Hayeon Kim; Yongsook C Lee; Stanley H Benedict; Brandon Dyer; Michael Price; Yi Rong; Ananth Ravi; Eric Leung; Sushil Beriwal; Mark E Bernard; Jyoti Mayadev; Jessica R L Leif; Ying Xiao Journal: Int J Radiat Oncol Biol Phys Date: 2021-06-17 Impact factor: 7.038