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Title: SU-F-J-148: A Collapsed Cone Algorithm Can Be Used for Quality Assurance for Monaco Treatment Plans for the MR-Linac

Abstract

Purpose: Treatment plans for the MR-linac, calculated in Monaco v5.19, include direct simulation of the effects of the 1.5T B{sub 0}-field. We tested the feasibility of using a collapsed-cone (CC) algorithm in Oncentra, which does not account for effects of the B{sub 0}-field, as a fast online, independent 3D check of dose calculations. Methods: Treatment plans for six patients were generated in Monaco with a 6 MV FFF beam and the B{sub 0}-field. All plans were recalculated with a CC model of the same beam. Plans for the same patients were also generated in Monaco without the B{sub 0}-field. The mean dose (Dmean) and doses to 10% (D10%) and 90% (D90%) of the volume were determined, as percentages of the prescribed dose, for target volumes and OARs in each calculated dose distribution. Student’s t-tests between paired parameters from Monaco plans and corresponding CC calculations were performed. Results: Figure 1 shows an example of the difference between dose distributions calculated in Monaco, with the B{sub 0}-field, and the CC algorithm. Figure 2 shows distributions of (absolute) difference between parameters for Monaco plans, with the B{sub 0}-field, and CC calculations. The Dmean and D90% values for the CTVs and PTVs were significantlymore » different, but differences in dose distributions arose predominantly at the edges of the target volumes. Inclusion of the B{sub 0}-field had little effect on agreement of the Dmean values, as illustrated by Figure 3, nor on agreement of the D10% and D90% values. Conclusion: Dose distributions recalculated with a CC algorithm show good agreement with those calculated with Monaco, for plans both with and without the B{sub 0}-field, indicating that the CC algorithm could be used to check online treatment planning for the MRlinac. Agreement for a wider range of treatment sites, and the feasibility of using the γ-test as a simple pass/fail criterion, will be investigated.« less

Authors:
; ; ; ; ; ;  [1];  [2];  [3];  [4]
  1. University Medical Center, Utrecht (Netherlands)
  2. Elekta Instrument AB, Stockholm (Sweden)
  3. Elekta Inc., Atlanta, GA (United States)
  4. Elekta BV, Best (Netherlands)
Publication Date:
OSTI Identifier:
22634751
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ALGORITHMS; BEAMS; CALCULATION METHODS; LINEAR ACCELERATORS; PATIENTS; PLANNING; QUALITY ASSURANCE; RADIATION DOSE DISTRIBUTIONS; RADIATION DOSES; RADIOTHERAPY; SIMULATION

Citation Formats

Hackett, S, Asselen, B van, Wolthaus, J, Kotte, A, Bol, G, Lagendijk, J, Raaymakers, B, Feist, G, Pencea, S, and Akhiat, H. SU-F-J-148: A Collapsed Cone Algorithm Can Be Used for Quality Assurance for Monaco Treatment Plans for the MR-Linac. United States: N. p., 2016. Web. doi:10.1118/1.4956056.
Hackett, S, Asselen, B van, Wolthaus, J, Kotte, A, Bol, G, Lagendijk, J, Raaymakers, B, Feist, G, Pencea, S, & Akhiat, H. SU-F-J-148: A Collapsed Cone Algorithm Can Be Used for Quality Assurance for Monaco Treatment Plans for the MR-Linac. United States. doi:10.1118/1.4956056.
Hackett, S, Asselen, B van, Wolthaus, J, Kotte, A, Bol, G, Lagendijk, J, Raaymakers, B, Feist, G, Pencea, S, and Akhiat, H. 2016. "SU-F-J-148: A Collapsed Cone Algorithm Can Be Used for Quality Assurance for Monaco Treatment Plans for the MR-Linac". United States. doi:10.1118/1.4956056.
@article{osti_22634751,
title = {SU-F-J-148: A Collapsed Cone Algorithm Can Be Used for Quality Assurance for Monaco Treatment Plans for the MR-Linac},
author = {Hackett, S and Asselen, B van and Wolthaus, J and Kotte, A and Bol, G and Lagendijk, J and Raaymakers, B and Feist, G and Pencea, S and Akhiat, H},
abstractNote = {Purpose: Treatment plans for the MR-linac, calculated in Monaco v5.19, include direct simulation of the effects of the 1.5T B{sub 0}-field. We tested the feasibility of using a collapsed-cone (CC) algorithm in Oncentra, which does not account for effects of the B{sub 0}-field, as a fast online, independent 3D check of dose calculations. Methods: Treatment plans for six patients were generated in Monaco with a 6 MV FFF beam and the B{sub 0}-field. All plans were recalculated with a CC model of the same beam. Plans for the same patients were also generated in Monaco without the B{sub 0}-field. The mean dose (Dmean) and doses to 10% (D10%) and 90% (D90%) of the volume were determined, as percentages of the prescribed dose, for target volumes and OARs in each calculated dose distribution. Student’s t-tests between paired parameters from Monaco plans and corresponding CC calculations were performed. Results: Figure 1 shows an example of the difference between dose distributions calculated in Monaco, with the B{sub 0}-field, and the CC algorithm. Figure 2 shows distributions of (absolute) difference between parameters for Monaco plans, with the B{sub 0}-field, and CC calculations. The Dmean and D90% values for the CTVs and PTVs were significantly different, but differences in dose distributions arose predominantly at the edges of the target volumes. Inclusion of the B{sub 0}-field had little effect on agreement of the Dmean values, as illustrated by Figure 3, nor on agreement of the D10% and D90% values. Conclusion: Dose distributions recalculated with a CC algorithm show good agreement with those calculated with Monaco, for plans both with and without the B{sub 0}-field, indicating that the CC algorithm could be used to check online treatment planning for the MRlinac. Agreement for a wider range of treatment sites, and the feasibility of using the γ-test as a simple pass/fail criterion, will be investigated.},
doi = {10.1118/1.4956056},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To present the dose per pulse dependence of various QA devices under Flattening Filter Free (FFF) conditions. Methods: Air and liquid filled ion chamber arrays, diode arrays, radiochromic film and optically stimulated luminescence detectors were investigated. All detectors were irradiated under similar conditions of varying dose per pulse on a TrueBeam linac. Dose per pulse was controlled by varying SSD from 70 to 160 cm providing a range from ~0.5 to ~3 mGy per pulse. MU rates of up to 2400 MU/min for 10X FFF and 1400 MU/min for the 6X FFF beam were used. Beam pulses were countedmore » using the Profiler™ diode array and pulse timing was confirmed by examining linac node files. Delivered doses were calculated with the Eclipse™ treatment planning system. Results: The detectors show a range of behaviors depending on the detector type, as expected. Diode arrays show up to 4% change in sensitivity (sensitivity increases with increasing dose per pulse) over the range tested. Air and liquid ion chambers arrays show a change in sensitivity of up to 3% (air) and 6% (liquid) (sensitivity decreases with increasing dose per pulse) while film and OSLD do not demonstrate a dependence on dose per pulse. Conclusion: Dependence of detector response on dose per pulse varies considerably depending on detector design. Interplay between dose per pulse and MU rate also exists for some detectors. Due diligence is required to characterize detector response prior to implementation of a QA protocol for FFF treatment delivery. During VMAT delivery, the MU rate may also vary dramatically within a treatment fraction. We intend to further investigate the implications of this for VMAT FFF patient specific quality assurance. T Karan and F Viel have received partial funding through the Varian Research program.« less
  • Purpose: To analyze the application of volume implant (V100) data as a method for a global check of low dose rate (LDR) brachytherapy plans. Methods: Treatment plans for 335 consecutive patients undergoing permanent seed implants for prostate cancer and for 113 patients treated with plaque therapy for ocular melanoma were analyzed. Plaques used were 54 COMS (10 to 20 mm, notched and regular) and 59 Eye Physics EP917s with variable loading. Plots of treatment time x implanted activity per unit dose versus v100 ^.667 were made. V100 values were obtained using dose volume histograms calculated by the treatment planning systemsmore » (Variseed 8.02 and Plaque Simulator 5.4). Four different physicists were involved in planning the prostate seed cases; two physicists for the eye plaques. Results: Since the time and dose for the prostate cases did not vary, a plot of implanted activity vs V100 ^.667 was made. A linear fit with no intercept had an r{sup 2} = 0.978; more than 94% of the actual activities fell within 5% of the activities calculated from the linear fit. The greatest deviations were in cases where the implant volumes were large (> 100 cc). Both COMS and EP917 plaque linear fits were good (r{sup 2} = .967 and .957); the largest deviations were seen for large volumes. Conclusions: The method outlined here is effective for checking planning consistency and quality assurance of two types of LDR brachytherapy treatment plans (temporary and permanent). A spreadsheet for the calculations enables a quick check of the plan in situations were time is short (e.g. OR-based prostate planning)« less
  • Purpose: To report on the patient-specific quality assurance (PSQA) results for 295 spot-scanning proton therapy treatment plans from the MD Anderson PTC-Houston. We show how the results differed by treatment site and how they were affected by the treatment plan optimization method and by a range shifter in the treatment field. We also discuss some causes of PSQA problems. Methods: The PSQA procedure, which is designed to verify both the accuracy of the treatment planning system's (Eclipse™ v8.9) dose calculations and the dose delivery of the Hitachi PROBEAT synchrotron, consists of (1) an end-to-end test in which the beam ismore » delivered and measured at the prescribed gantry angle, and (2) additional dose plane measurements made from gantry angle 270°. HPlusQA™ software automatically performs the gamma analysis with criteria 3% (dose tolerance), 3 mm (distance-to-agreement, DTA) and 2%, 2 mm. Passing is defined as at least 90% of the pixels having a gamma score less than 1. Results: The PSQA gamma passing rate was 96.2% for 3%, 3 mm, and 85.3% for 2%, 2 mm. The rate depended on the treatment site. For example, the 3%, 3 mm passing rate was 95% for head and neck plans, vs 100% for prostate plans. The passing rates of multi- vs. single-field optimization plans did not significantly differ. However, the rate for fields with range shifters was 94.8±0.6%, vs 99.0±0.6% for those without (p = 0.002). Longitudinal dose gradients caused most of the low scores. Overestimation of the calculated dose proximal to the spread-out Bragg peak (SOBP) caused many of the others. Conclusion: The planned and delivered doses consistently agreed within tolerance levels. Minor dose modeling deficiencies remain proximal to the SOBP. The 3% dose tolerance, 3 mm DTA, with 90% pixel passing rate is a reasonable action level for 2D gamma comparisons.« less
  • Purpose: An important challenge facing online adaptive radiation therapy is the development of feasible and efficient quality assurance (QA). This project aimed to validate the deliverability of online adapted plans and develop a proof-of-concept online delivery monitoring system for online adaptive radiation therapy QA. Methods: The first part of this project benchmarked automatically online adapted prostate treatment plans using traditional portal dosimetry IMRT QA. The portal dosimetry QA results of online adapted plans were compared to original (unadapted) plans as well as randomly selected prostate IMRT plans from our clinic. In the second part, an online delivery monitoring system wasmore » designed and validated via a simulated treatment with intentional multileaf collimator (MLC) errors. This system was based on inputs from the dynamic machine information (DMI), which continuously reports actual MLC positions and machine monitor units (MUs) at intervals of 50 ms or less during delivery. Based on the DMI, the system performed two levels of monitoring/verification during the delivery: (1) dynamic monitoring of cumulative fluence errors resulting from leaf position deviations and visualization using fluence error maps (FEMs); and (2) verification of MLC positions against the treatment plan for potential errors in MLC motion and data transfer at each control point. Validation of the online delivery monitoring system was performed by introducing intentional systematic MLC errors (ranging from 0.5 to 2 mm) to the DMI files for both leaf banks. These DMI files were analyzed by the proposed system to evaluate the system’s performance in quantifying errors and revealing the source of errors, as well as to understand patterns in the FEMs. In addition, FEMs from 210 actual prostate IMRT beams were analyzed using the proposed system to further validate its ability to catch and identify errors, as well as establish error magnitude baselines for prostate IMRT delivery. Results: Online adapted plans were found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system’s ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. Conclusions: The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy.« less
  • Purpose: Dosimetry using film, CR, electronic portal imaging, or other 2D detectors requires calibration of the raw image data to obtain dose. Typically, a series of known doses are given to the detector, the raw signal for each dose is obtained, and a calibration curve is created. This calibration curve is then applied to the measured raw signals to convert them to dose. With the advent of IMRT, film dosimetry for quality assurance has become a routine and labor intensive part of the physicist's day. The process of calibrating the film or other 2D detector takes time and additional filmmore » or images for performing the calibration, and comes with its own source of errors. This article studies a new methodology for the relative dose calibration of 2D imaging detectors especially useful for IMRT QA, which relies on the treatment plan dose image to provide the dose information which is paired with the raw QA image data after registration of the two images (plan-based calibration). Methods: Validation of the accuracy and robustness of the method is performed on ten IMRT cases performed using EDR2 film with conventional and plan-based calibration. Also, for each of the ten cases, a 5 mm registration error was introduced and the Gamma analysis was reevaluated. In addition, synthetic image tests were performed to test the limits of the method. The Gamma analysis is used as a measure of dosimetric agreement between plan and film for the clinical cases and a dose difference metric for the synthetic cases. Results: The QA image calibrated by the plan-based method was found to more accurately match the treatment plan doses than the conventionally calibrated films and also to reveal dose errors more effectively when a registration error was introduced. When synthetic acquired images were systematically studied, localized and randomly placed dose errors were correctly identified without excessive falsely passing or falsely failing pixels, unless the errors were concentrated in a majority of pixels in a contiguous narrow dose band. Irregularities seen in the calibration curve expose these errors. Conclusions: The plan-based calibration method was found to be an accurate, efficient procedure, capable of detecting IMRT QA relative dosimetry errors as well as, or better than conventional calibration methods.« less