Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer

2018 ◽  
pp. 41-66
Author(s):  
Emma Stubington ◽  
Matthias Ehrgott ◽  
Glyn Shentall ◽  
Omid Nohadani
Keyword(s):  
Prostate Cancer ◽  
Treatment Plans ◽  
Radiotherapy Treatment

scholarly journals Outcomes of Peer Review for Radiotherapy Treatment Plans With Palliative Intent

2018 ◽  
Vol 14 (12) ◽  
pp. e794-e800
Author(s):  
Dina Thompson ◽  
Kimberly Cox ◽  
James Loudon ◽  
Ivan Yeung ◽  
Woodrow Wells
Keyword(s):  
Peer Review ◽  
Treatment Plan ◽  
Palliative Radiotherapy ◽  
Cancer Center ◽  
Palliative Intent ◽  
Treatment Plans ◽  
Important Quality ◽  
Radiation Medicine ◽  
Radiotherapy Treatment

Purpose: Peer review of a proposed treatment plan is increasingly recognized as an important quality activity in radiation medicine. Although peer review has been emphasized in the curative setting, applying peer review for treatment plans that have palliative intent is receiving increased attention. This study reports peer review outcomes for a regional cancer center that applied routine interprofessional peer review as a standard practice for palliative radiotherapy. Methods and Materials: Peer review outcomes for palliative radiotherapy plans were recorded prospectively for patients who began radiotherapy between October 1, 2015, and September 30, 2017. Recommended and implemented changes were recorded. The content of detailed discussions was recorded to gain insight into the complexities of palliative treatment plans considered during peer review. Results: Peer review outcomes were reviewed for 1,413 treatment plans with palliative intent. The proportions of detailed discussions and changes recommended were found to be 139 (9.8%) and 29 (2.1%), respectively. The content of detailed discussions and changes recommended was categorized. Major changes represented 75.9% of recommended changes, of which 84.2% were implemented clinically. Conclusion: Many complexities exist that are specific to palliative radiotherapy. Interprofessional peer review provides a forum for these complexities to be openly discussed and is an important activity to optimize the quality of care for patients with treatment plans that have palliative intent.

Social support and quality of life of prostate cancer patients after radiotherapy treatment

2010 ◽  
Vol 19 (2) ◽  
pp. 251-259 ◽  
Author(s):  
J.A. QUEENAN ◽  
D. FELDMAN-STEWART ◽  
M. BRUNDAGE ◽  
P.A. GROOME
Keyword(s):  
Quality Of Life ◽  
Prostate Cancer ◽  
Social Support ◽  
Cancer Patients ◽  
Radiotherapy Treatment

SU-FF-T-574: Radiotherapy Treatment Plans with RapidArc for Prostate Cancer Involving Seminal Vesicles

2009 ◽  
Vol 36 (6Part18) ◽  
pp. 2656-2656
Author(s):  
S Yoo ◽  
Q Wu ◽  
W Lee ◽  
F Yin
Keyword(s):  
Prostate Cancer ◽  
Seminal Vesicles ◽  
Treatment Plans ◽  
Radiotherapy Treatment

PO-1798: Quality of radiotherapy treatment plans for locally advanced sinonasal tumors in a phase II trial

2020 ◽  
Vol 152 ◽  
pp. S1003-S1004
Author(s):  
B. Vischioni ◽  
A. Mirandola ◽  
M. Bonora ◽  
S. Ronchi ◽  
E. Mastella ◽  
...  
Keyword(s):  
Phase Ii ◽  
Phase Ii Trial ◽  
Locally Advanced ◽  
Treatment Plans ◽  
Radiotherapy Treatment

TBS-BAO: fully automated beam angle optimization for IMRT guided by a total-beam-space reference plan

2022 ◽  
Author(s):  
Bastiaan Wilhelmus Klaas Schipaanboord ◽  
Ben J M Heijmen ◽  
Sebastiaan Breedveld
Keyword(s):  
Dose Distribution ◽  
A Priori ◽  
Beam Angle ◽  
Delivery Times ◽  
Beam Angle Optimization ◽  
Novel Approach ◽  
Treatment Plans ◽  
Discrete Nature ◽  
Radiotherapy Treatment

Abstract Properly selected beam angles contribute to the quality of radiotherapy treatment plans. However, the Beam Angle Optimization (BAO) problem is difficult to solve to optimality due to its non-convex discrete nature with many local minima. In this study, we propose TBS-BAO, a novel approach for solving the BAO problem, and test it for non-coplanar robotic CyberKnife radiotherapy for prostate cancer. First, an ideal Pareto-optimal reference dose distribution is automatically generated using a priori multi-criterial fluence map optimization (FMO) to generate a plan that includes all candidate beams (total-beam-space, TBS). Then, this ideal dose distribution is reproduced as closely as possible in a subsequent segmentation/beam angle optimization step (SEG/BAO), while limiting the number of allowed beams to a user-selectable preset value. SEG/BAO aims at a close reproduction of the ideal dose distribution. For each of 33 prostate SBRT patients, 18 treatment plans with different pre-set numbers of allowed beams were automatically generated with the proposed TBS-BAO. For each patient, the TBS-BAO plans were then compared to a plan that was automatically generated with an alternative BAO method (Erasmus-iCycle) and to a high-quality manually generated plan. TBS-BAO was able to automatically generate plans with clinically feasible numbers of beams (∽25), with a quality highly similar to corresponding 91-beam ideal reference plans. Compared to the alternative Erasmus-iCycle BAO approach, similar plan quality was obtained for 25-beam segmented plans, while computation times were reduced from 10.7 hours to 4.8/1.5 hours, depending on the applied pencil-beam resolution in TBS-BAO. 25-beam TBS-BAO plans had similar quality as manually generated plans with on average 48 beams, while delivery times reduced from 22.3 to 18.4/18.1 min. TBS reference plans could effectively steer the discrete non-convex BAO.

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