Adaptive modification of treatment planning to minimize the deleterious effects of treatment setup errors
| Autor: | Cheng Pan, Alvaro Martinez, John Wong, Eric M. Horwitz, Di Yan, Jeff M. Michalski, Frank A. Vicini, Arthur Frazier |
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| Rok vydání: | 1997 |
| Předmět: |
Male
Cancer Research medicine.medical_specialty Lung Neoplasms medicine.medical_treatment Portal imaging Treatment plan Margin (machine learning) medicine Humans Radiology Nuclear Medicine and imaging Radiation treatment planning Pelvic Neoplasms Retrospective Studies Radiation business.industry Radiotherapy Planning Computer-Assisted Treatment process Prostatic Neoplasms Confidence interval Surgery Multileaf collimator Radiation therapy Oncology Head and Neck Neoplasms Nuclear medicine business Algorithms |
| Zdroj: | International Journal of Radiation Oncology*Biology*Physics. 38:197-206 |
| ISSN: | 0360-3016 |
| Popis: | PURPOSE: Using daily setup variation measured from an electronic portal imaging device (EPID), radiation treatment of the individual patient can be adaptively reoptimized during the course of therapy. In this study, daily portal images were retrospectively examined to: (a) determine the number of initial days of portal imaging required to give adequate prediction of the systematic and random setup errors; and (b) explore the potential of using the prediction as feedback to reoptimize the individual treatment part-way through the treatment course. METHODS AND MATERIALS: Daily portal images of 64 cancer patients, whose treatment position was not adjusted during the course of treatment, were obtained from two independent clinics with similar setup procedures. Systematic and random setup errors for each patient were predicted using different numbers of initial portal measurements. The statistical confidence of the predictions was tested to determine the number of daily portal measurements needed to give reasonable predictions. Two treatment processes were simulated to examine the potential opportunity for setup margin reduction and dose escalation. The first process mimicked a conventional treatment. A constant margin was assigned to each treatment field to compensate for the average setup error of the patient population. A treatment dose was then prescribed with reference to a fixed normal tissue tolerance, and then fixed in the entire course of treatment. In the second process, the same treatment fields and prescribed dose were used only for the initial plan and treatment. After several initial days of treatments, the treatment field shape and position were assumed to be adaptively modified using a computer-controlled multileaf collimator (MLC) in light of the predicted systematic and random setup errors. The prescribed dose was then escalated until the same normal tissue tolerance, as determined in the first treatment process, was reached. RESULTS: The systematic setup error and the random setup error were predicted to be within +/-1 mm for the former and +/-0.5 mm for the latter at a > or = 95% confidence level using < or = 9 initial daily portal measurements. In the study, a large number of patients could be treated using a smaller field margin if the adaptive modification process were used. Simulation of the adaptive modification process for prostate treatment demonstrates that additional treatment dose could be safely applied to 64% of patients. CONCLUSION: The adaptive modification process represents a different approach for use of on-line portal images. The portal imaging information from the initial treatments is used as feedback for reoptimization of the treatment plan, rather than adjustment of the treatment setup. Results from the retrospective study show that the treatment of individual patient can be improved with the adaptive modification process. |
| Databáze: | OpenAIRE |
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