Literature DB >> 22658513

Toward fully automated multicriterial plan generation: a prospective clinical study.

Peter W J Voet1, Maarten L P Dirkx, Sebastiaan Breedveld, Dennie Fransen, Peter C Levendag, Ben J M Heijmen.   

Abstract

PURPOSE: To prospectively compare plans generated with iCycle, an in-house-developed algorithm for fully automated multicriterial intensity modulated radiation therapy (IMRT) beam profile and beam orientation optimization, with plans manually generated by dosimetrists using the clinical treatment planning system. METHODS AND MATERIALS: For 20 randomly selected head-and-neck cancer patients with various tumor locations (of whom 13 received sequential boost treatments), we offered the treating physician the choice between an automatically generated iCycle plan and a manually optimized plan using standard clinical procedures. Although iCycle used a fixed "wish list" with hard constraints and prioritized objectives, the dosimetrists manually selected the beam configuration and fine tuned the constraints and objectives for each IMRT plan. Dosimetrists were not informed in advance whether a competing iCycle plan was made. The 2 plans were simultaneously presented to the physician, who then selected the plan to be used for treatment. For the patient group, differences in planning target volume coverage and sparing of critical tissues were quantified.
RESULTS: In 32 of 33 plan comparisons, the physician selected the iCycle plan for treatment. This highly consistent preference for the automatically generated plans was mainly caused by the improved sparing for the large majority of critical structures. With iCycle, the normal tissue complication probabilities for the parotid and submandibular glands were reduced by 2.4% ± 4.9% (maximum, 18.5%, P=.001) and 6.5% ± 8.3% (maximum, 27%, P=.005), respectively. The reduction in the mean oral cavity dose was 2.8 ± 2.8 Gy (maximum, 8.1 Gy, P=.005). For the swallowing muscles, the esophagus and larynx, the mean dose reduction was 3.3 ± 1.1 Gy (maximum, 9.2 Gy, P<.001). For 15 of the 20 patients, target coverage was also improved.
CONCLUSIONS: In 97% of cases, automatically generated plans were selected for treatment because of the superior quality. Apart from the improved plan quality, automatic plan generation is economically attractive because of the reduced workload.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22658513     DOI: 10.1016/j.ijrobp.2012.04.015

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


  33 in total

Review 1.  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

2.  Automatic configuration of the reference point method for fully automated multi-objective treatment planning applied to oropharyngeal cancer.

Authors:  Rens van Haveren; Ben J M Heijmen; Sebastiaan Breedveld
Journal:  Med Phys       Date:  2020-03-05       Impact factor: 4.071

Review 3.  Artificial intelligence in radiation oncology.

Authors:  Elizabeth Huynh; Ahmed Hosny; Christian Guthier; Danielle S Bitterman; Steven F Petit; Daphne A Haas-Kogan; Benjamin Kann; Hugo J W L Aerts; Raymond H Mak
Journal:  Nat Rev Clin Oncol       Date:  2020-08-25       Impact factor: 66.675

4.  Automated intensity modulated treatment planning: The expedited constrained hierarchical optimization (ECHO) system.

Authors:  Masoud Zarepisheh; Linda Hong; Ying Zhou; Jung Hun Oh; James G Mechalakos; Margie A Hunt; Gig S Mageras; Joseph O Deasy
Journal:  Med Phys       Date:  2019-05-29       Impact factor: 4.071

5.  Assessment of a model based optimization engine for volumetric modulated arc therapy for patients with advanced hepatocellular cancer.

Authors:  Antonella Fogliata; Po-Ming Wang; Francesca Belosi; Alessandro Clivio; Giorgia Nicolini; Eugenio Vanetti; Luca Cozzi
Journal:  Radiat Oncol       Date:  2014-10-28       Impact factor: 3.481

6.  Multicriteria optimization enables less experienced planners to efficiently produce high quality treatment plans in head and neck cancer radiotherapy.

Authors:  Roel G J Kierkels; Ruurd Visser; Hendrik P Bijl; Johannes A Langendijk; Aart A van 't Veld; Roel J H M Steenbakkers; Erik W Korevaar
Journal:  Radiat Oncol       Date:  2015-04-12       Impact factor: 3.481

7.  Automatic interactive optimization for volumetric modulated arc therapy planning.

Authors:  Jim P Tol; Max Dahele; Jarkko Peltola; Janne Nord; Ben J Slotman; Wilko F A R Verbakel
Journal:  Radiat Oncol       Date:  2015-04-01       Impact factor: 3.481

8.  Validation of Fully Automated VMAT Plan Generation for Library-Based Plan-of-the-Day Cervical Cancer Radiotherapy.

Authors:  Abdul Wahab M Sharfo; Sebastiaan Breedveld; Peter W J Voet; Sabrina T Heijkoop; Jan-Willem M Mens; Mischa S Hoogeman; Ben J M Heijmen
Journal:  PLoS One       Date:  2016-12-29       Impact factor: 3.240

9.  A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers.

Authors:  Antonella Fogliata; Giorgia Nicolini; Alessandro Clivio; Eugenio Vanetti; Sarbani Laksar; Angelo Tozzi; Marta Scorsetti; Luca Cozzi
Journal:  Radiat Oncol       Date:  2015-10-31       Impact factor: 3.481

10.  Can knowledge-based DVH predictions be used for automated, individualized quality assurance of radiotherapy treatment plans?

Authors:  Jim P Tol; Max Dahele; Alexander R Delaney; Ben J Slotman; Wilko F A R Verbakel
Journal:  Radiat Oncol       Date:  2015-11-19       Impact factor: 3.481

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