Literature DB >> 25847605

Quantifying Unnecessary Normal Tissue Complication Risks due to Suboptimal Planning: A Secondary Study of RTOG 0126.

Kevin L Moore1, Rachel Schmidt2, Vitali Moiseenko3, Lindsey A Olsen4, Jun Tan4, Ying Xiao5, James Galvin5, Stephanie Pugh6, Michael J Seider7, Adam P Dicker5, Walter Bosch4, Jeff Michalski4, Sasa Mutic4.   

Abstract

PURPOSE: The purpose of this study was to quantify the frequency and clinical severity of quality deficiencies in intensity modulated radiation therapy (IMRT) planning in the Radiation Therapy Oncology Group 0126 protocol. METHODS AND MATERIALS: A total of 219 IMRT patients from the high-dose arm (79.2 Gy) of RTOG 0126 were analyzed. To quantify plan quality, we used established knowledge-based methods for patient-specific dose-volume histogram (DVH) prediction of organs at risk and a Lyman-Kutcher-Burman (LKB) model for grade ≥2 rectal complications to convert DVHs into normal tissue complication probabilities (NTCPs). The LKB model was validated by fitting dose-response parameters relative to observed toxicities. The 90th percentile (22 of 219) of plans with the lowest excess risk (difference between clinical and model-predicted NTCP) were used to create a model for the presumed best practices in the protocol (pDVH0126,top10%). Applying the resultant model to the entire sample enabled comparisons between DVHs that patients could have received to DVHs they actually received. Excess risk quantified the clinical impact of suboptimal planning. Accuracy of pDVH predictions was validated by replanning 30 of 219 patients (13.7%), including equal numbers of presumed "high-quality," "low-quality," and randomly sampled plans. NTCP-predicted toxicities were compared to adverse events on protocol.
RESULTS: Existing models showed that bladder-sparing variations were less prevalent than rectum quality variations and that increased rectal sparing was not correlated with target metrics (dose received by 98% and 2% of the PTV, respectively). Observed toxicities were consistent with current LKB parameters. Converting DVH and pDVH0126,top10% to rectal NTCPs, we observed 94 of 219 patients (42.9%) with ≥5% excess risk, 20 of 219 patients (9.1%) with ≥10% excess risk, and 2 of 219 patients (0.9%) with ≥15% excess risk. Replanning demonstrated the predicted NTCP reductions while maintaining the volume of the PTV receiving prescription dose. An equivalent sample of high-quality plans showed fewer toxicities than low-quality plans, 6 of 73 versus 10 of 73 respectively, although these differences were not significant (P=.21) due to insufficient statistical power in this retrospective study.
CONCLUSIONS: Plan quality deficiencies in RTOG 0126 exposed patients to substantial excess risk for rectal complications.
Copyright © 2015 Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 25847605      PMCID: PMC4431941          DOI: 10.1016/j.ijrobp.2015.01.046

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  20 in total

Review 1.  Radiation dose-volume effects of the urinary bladder.

Authors:  Akila N Viswanathan; Ellen D Yorke; Lawrence B Marks; Patricia J Eifel; William U Shipley
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-03-01       Impact factor: 7.038

2.  Experience-based quality control of clinical intensity-modulated radiotherapy planning.

Authors:  Kevin L Moore; R Scott Brame; Daniel A Low; Sasa Mutic
Journal:  Int J Radiat Oncol Biol Phys       Date:  2011-01-27       Impact factor: 7.038

3.  Predicting dose-volume histograms for organs-at-risk in IMRT planning.

Authors:  Lindsey M Appenzoller; Jeff M Michalski; Wade L Thorstad; Sasa Mutic; Kevin L Moore
Journal:  Med Phys       Date:  2012-12       Impact factor: 4.071

Review 4.  Radiotherapy protocol deviations and clinical outcomes: a meta-analysis of cooperative group clinical trials.

Authors:  Nitin Ohri; Xinglei Shen; Adam P Dicker; Laura A Doyle; Amy S Harrison; Timothy N Showalter
Journal:  J Natl Cancer Inst       Date:  2013-03-06       Impact factor: 13.506

5.  Variation in external beam treatment plan quality: An inter-institutional study of planners and planning systems.

Authors:  Benjamin E Nelms; Greg Robinson; Jay Markham; Kyle Velasco; Steve Boyd; Sharath Narayan; James Wheeler; Mark L Sobczak
Journal:  Pract Radiat Oncol       Date:  2012-01-10

6.  Do intermediate radiation doses contribute to late rectal toxicity? An analysis of data from radiation therapy oncology group protocol 94-06.

Authors:  Susan L Tucker; Lei Dong; Jeff M Michalski; Walter R Bosch; Kathryn Winter; James D Cox; James A Purdy; Radhe Mohan
Journal:  Int J Radiat Oncol Biol Phys       Date:  2012-02-17       Impact factor: 7.038

7.  Increased organ sparing using shape-based treatment plan optimization for intensity modulated radiation therapy of pancreatic adenocarcinoma.

Authors:  Steven F Petit; Binbin Wu; Michael Kazhdan; André Dekker; Patricio Simari; Rachit Kumar; Russel Taylor; Joseph M Herman; Todd McNutt
Journal:  Radiother Oncol       Date:  2011-06-15       Impact factor: 6.280

Review 8.  What we have learned: the impact of quality from a clinical trials perspective.

Authors:  Thomas J FitzGerald
Journal:  Semin Radiat Oncol       Date:  2012-01       Impact factor: 5.934

Review 9.  Does quality of radiation therapy predict outcomes of multicenter cooperative group trials? A literature review.

Authors:  Alysa Fairchild; William Straube; Fran Laurie; David Followill
Journal:  Int J Radiat Oncol Biol Phys       Date:  2013-05-15       Impact factor: 7.038

10.  Patient geometry-driven information retrieval for IMRT treatment plan quality control.

Authors:  Binbin Wu; Francesco Ricchetti; Giuseppe Sanguineti; Misha Kazhdan; Patricio Simari; Ming Chuang; Russell Taylor; Robert Jacques; Todd McNutt
Journal:  Med Phys       Date:  2009-12       Impact factor: 4.071

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  33 in total

1.  Evaluating inter-campus plan consistency using a knowledge based planning model.

Authors:  Sean L Berry; Rongtao Ma; Amanda Boczkowski; Andrew Jackson; Pengpeng Zhang; Margie Hunt
Journal:  Radiother Oncol       Date:  2016-07-06       Impact factor: 6.280

Review 2.  Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations.

Authors:  Mohammad Hussein; Ben J M Heijmen; Dirk Verellen; Andrew Nisbet
Journal:  Br J Radiol       Date:  2018-09-04       Impact factor: 3.039

3.  An atlas-based method to predict three-dimensional dose distributions for cancer patients who receive radiotherapy.

Authors:  S A Yoganathan; Rui Zhang
Journal:  Phys Med Biol       Date:  2019-04-12       Impact factor: 3.609

4.  Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials.

Authors:  Nan Li; Ruben Carmona; Igor Sirak; Linda Kasaova; David Followill; Jeff Michalski; Walter Bosch; William Straube; Loren K Mell; Kevin L Moore
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-10-13       Impact factor: 7.038

Review 5.  Automated Radiation Treatment Planning for Cervical Cancer.

Authors:  Dong Joo Rhee; Anuja Jhingran; Kelly Kisling; Carlos Cardenas; Hannah Simonds; Laurence Court
Journal:  Semin Radiat Oncol       Date:  2020-10       Impact factor: 5.934

6.  Using deep learning to predict beam-tunable Pareto optimal dose distribution for intensity-modulated radiation therapy.

Authors:  Gyanendra Bohara; Azar Sadeghnejad Barkousaraie; Steve Jiang; Dan Nguyen
Journal:  Med Phys       Date:  2020-08-02       Impact factor: 4.071

7.  Effect of modern, high-quality prostate intensity-modulated radiation therapy on outcome: Evidence from a community radiation oncology program.

Authors:  Johnny Kao; Amanda Zucker; Jonathan Timmins; Shankar Taramangalam; Jeffrey Pettit; Aaron J Woodall; Edward Loizides; Andrew T Wong
Journal:  Mol Clin Oncol       Date:  2017-06-08

8.  Improving Quality and Consistency in NRG Oncology Radiation Therapy Oncology Group 0631 for Spine Radiosurgery via Knowledge-Based Planning.

Authors:  Kelly C Younge; Robin B Marsh; Dawn Owen; Huaizhi Geng; Ying Xiao; Daniel E Spratt; Joseph Foy; Krithika Suresh; Q Jackie Wu; Fang-Fang Yin; Samuel Ryu; Martha M Matuszak
Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-01-04       Impact factor: 7.038

9.  Interobserver variability in radiation therapy plan output: Results of a single-institution study.

Authors:  Sean L Berry; Amanda Boczkowski; Rongtao Ma; James Mechalakos; Margie Hunt
Journal:  Pract Radiat Oncol       Date:  2016-05-08

10.  Validation of in-house knowledge-based planning model for advance-stage lung cancer patients treated using VMAT radiotherapy.

Authors:  Nilesh S Tambe; Isabel M Pires; Craig Moore; Christopher Cawthorne; Andrew W Beavis
Journal:  Br J Radiol       Date:  2020-01-06       Impact factor: 3.039

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