Machine Log Files Research Articles

RapidArc patient specific mechanical delivery accuracy under extreme mechanical limits using linac log files

To assess the accuracy of RapidArc (RA) delivery for treatment machine operation near allowable mechanical limits in dynamic multileaf collimator (DMLC) leaf velocities, gantry speeds, and dose rates. Thirty RA patient plans were created for treatment of lung, gastrointestinal, and head and neck cancers on a Trilogy unit. For each patient, three RA plans were generated; one with medium MLC velocities, highest gantry speeds, and dose rates (case A); one with maximal allowable MLC leaf velocities (case B); and one with lowest gantry speeds (case C). Combinations of dose rates (140-600 MU/min), gantry speeds (2-5.4°/s), and DMLC leaf velocities (1.3-2.4 cm/s) were utilized to test the RapidArc delivery accuracy. Linac delivery log files were acquired after delivery of each plan. In-house developed software was used to read in the original RapidArc DICOM plan and update the plan to reflect the delivered plan by using the leaf position (L), gantry position (G), and MU dose values (D) extracted from the linac log files. This modified DICOM RT plan was imported back to ECLIPSE and the delivered 3D dose map recomputed. Finally, the planned and delivered 3D isodose maps were compared under three criteria to evaluate the dosimetric differences: maximum percentage dose difference, 3D gamma analysis criteria for 3%/3mm DTA, number of dose voxels having a dose difference that is greater than 1%, 2%, or 3% of the maximum dose, and their respective percentages. For the three cases indicated above, MLC leaf position discrepancies between planned and delivered values are 0.8 ± 0.2, 1.2 ± 0.2, and 0.8 ± 0.2 mm; the maximum gantry position discrepancies are 0.9° ± 0.2°, 0.9° ± 0.2°, and 0.6° ± 0.1°, and the maximum differences in delivered MU per control point are 0.2 ± 0.1, 0.2 ± 0.1, and 0.04 ± 0.01, respectively. Maximum percentage dose difference observed is 6.7%, for a case where 1 cm MLC leaves were used with high MLC leaf velocity. Maximum number (percentage) of dose voxels having a dose difference that is greater than 1%, 2%, and 3% of the maximum dose were 4761 (0.35%), 897 (0.07%), and 188 (0.01%). This also corresponds to the plan utilizing the most number of 1 cm MLC leaves. The 3D Gamma factor acceptance rates are better than 99%. This work shows that the accuracy of RapidArc delivery holds across the full range of gantry speeds, leaf velocities, and dose rates with small dosimetric uncertainties for 0.5 cm MLC leaves. However, caution should be exercised when using large MLC leaves in RapidArc. A novel technique to obtain the delivered 3D dose distributions using machine log files is also presented.

Optimizing the accuracy of a helical diode array dosimeter: A comprehensive calibration methodology coupled with a novel virtual inclinometer

The goal of any dosimeter is to be as accurate as possible when measuring absolute dose to compare with calculated dose. This limits the uncertainties associated with the dosimeter itself and allows the task of dose QA to focus on detecting errors in the treatment planning (TPS) and/or delivery systems. This work introduces enhancements to the measurement accuracy of a 3D dosimeter comprised of a helical plane of diodes in a volumetric phantom. We describe the methods and derivations of new corrections that account for repetition rate dependence, intrinsic relative sensitivity per diode, field size dependence based on the dynamic field size determination, and positional correction. Required and described is an accurate "virtual inclinometer" algorithm. The system allows for calibrating the array directly against an ion chamber signal collected with high angular resolution. These enhancements are quantitatively validated using several strategies including ion chamber measurements taken using a "blank" plastic shell mimicking the actual phantom, and comparison to high resolution dose calculations for a variety of fields: static, simple arcs, and VMAT. A number of sophisticated treatment planning algorithms were benchmarked against ion chamber measurements for their ability to handle a large air cavity in the phantom. Each calibration correction is quantified and presented vs its independent variable(s). The virtual inclinometer is validated by direct comparison to the gantry angle vs time data from machine log files. The effects of the calibration are quantified and improvements are seen in the dose agreement with the ion chamber reference measurements and with the TPS calculations. These improved agreements are a result of removing prior limitations and assumptions in the calibration methodology. Average gamma analysis passing rates for VMAT plans based on the AAPM TG-119 report are 98.4 and 93.3% for the 3%/3 mm and 2%/2 mm dose-error/distance to agreement threshold criteria, respectively, with the global dose-error normalization. With the local dose-error normalization, the average passing rates are reduced to 94.6 and 85.7% for the 3%/3 mm and 2%/2 mm criteria, respectively. Some algorithms in the convolution/superposition family are not sufficiently accurate in predicting the exit dose in the presence of a 15 cm diameter air cavity. Introduction of the improved calibration methodology, enabled by a robust virtual inclinometer algorithm, improves the accuracy of the dosimeter's absolute dose measurements. With our treatment planning and delivery chain, gamma analysis passing rates for the VMAT plans based on the AAPM TG-119 report are expected to be above 91% and average at about 95% level for γ(3%/3 mm) with the local dose-error normalization. This stringent comparison methodology is more indicative of the true VMAT system commissioning accuracy compared to the often quoted dose-error normalization to a single high value.

MO-B-224-01: Clinical Implementation and Application of Monte Carlo Methods in Photon and Electron Dose Calculation - New Issues to Consider in Clinical Practice

Current advances in image guided radiation therapy have enabled very accurate delivery of radiation for the treatment of cancer. It then becomes more important that the radiationdose is calculated with utmost accuracy in patient geometry. For past two decades Monte Carlo(MC) methods have been known to be the most accurate methods available for dose calculation. However, it has been only recently that MC based commercial treatment planning systems are becoming available for routine use in the clinic. Even now radiation therapy community is struggling in adopting MCtreatment planning systems (TPS) as the only TPS in the clinic. This is either because of additional computational burden associated with the MCdose calculation or due to the lack of information available on clinical benchmarked data where the effect of MC is most significant. Although use of parallel processing and more recently GPU implementation of MC algorithms have overcome computational burden, the need for clinical use and significance of MC methods are still topics of debate. The main goal of this educational session is to familiarize clinical medical physicists with the application and implementation of Monte Carlo in routine radiotherapytreatment planning with the emphasis on the clinical significance. The continuing education session will be divided into two sections in order to specifically address implementation issues related to Monte Carlo‐based photon and electron treatment planning techniques. The following broad general topics will be addressed: 1. Introduction to Monte Carlo Methods: with its application to radiation treatment planning and commercial availability of MC based TPS 2. Commissioning and clinical implementation of MC based systems‐Beam data required for source modeling and commissioning of a MC based TPS. Use of MC in IMRT optimization and VMAT for photontreatment planning 3. Implementation, operational and physics related issues: Issues related to beam modeling, inherent statistical uncertainty in MCdose calculations, importance of CT‐to‐material conversion and dose reporting in terms of dose‐to‐medium versus dose‐to‐water. 4. Clinical significance of MC based treatment plans:Dosimetric differences of MCdose calculations compared to kernel based methods for treatment sites such as head and neck, spine, breast, lung etc and how it affects our current clinical practice in terms of new prescription and dose escalation. 5. MC as a QA tool? Use of MC method as an independent and additional QA tool. Effect of QA by calculating dose in actual patient geometry rather than water phantom. Accounting for machine delivery uncertainty by reconstructing doses from machine log files etc Learning Objectives: 1. A review of MC methods with its application to radiation treatment planning for photon and electron beams 2. To understand the clinical implementation and commissioning of MC based TPS and issues related to its routine clinical operation 3. To understand the clinical significance of MC methods for different treatment sites and how it change our current clinical practice 4. To understand the use of MC TPS as an additional and independent QA tool in routine clinical practice.

TU‐E‐BRB‐08: Rapid Arc Patient Specific Dose Delivery Accuracy under Extreme Mechanical Limits Using Linac Log Files

Purpose: To assess the accuracy of RapidArc (RA) delivery for treatment machine operation near allowable mechanical limits in DMLC leaf velocities, gantry speeds, and dose rates. Method and Materials: Thirty RA patient plans were created for treatment of gastrointestinal and head and neck cancers on a Trilogy unit. Three RA plans per patient were generated; one with medium MLC velocities, highest gantry speeds and dose rates (case 1); one with maximal allowable MLC leaf velocities (case 2); and one with lowest gantry speeds (case 3). Combinations of dose rates (140 – 600 Mu /min), gantry speeds (2 – 5.4 deg/s), and DMLC leaf velocities (1.3 – 2.4 cm/s) were utilized to test the RapidArc delivery accuracy. Linac delivery log files were acquired after delivery of each plan. In‐house software was used to read in the original RapidArc DICOM plan and update the plan to reflect the delivered plan taking into account the MLC leaf positions, gantry positions and MU. This DICOM RT plan was imported back to Eclipse and the delivered 3D dose map recomputed. Finally the planned and delivered 3D isodose maps were imported into a 3D gamma analysis algorithm to evaluate the dosimetric differences. Results: For the three cases indicated above MLC leaf position discrepancies are: 0.8 ±0.2, 1.2 ± 0.2, 0.8 ± 0.2 mm; maximum gantry position discrepancies are: 0.9 ±0.2, 0.9 ±0.2, 0.6 ±0.1 deg, and maximum differences in delivered MU per control point are: 0.2±0.1, 0.2 ±0.1, and 0.04±0.01 respectively. The 3D Gamma factor acceptance rates are better than 97%. Conclusion: This work shows that the accuracy of RapidArc delivery holds across the full space of gantry speeds, leaf velocities, and dose rates with small dosimetric uncertainties. A novel technique to obtain the delivered 3D dose distributions using machine log files is also presented.

RapidArc Radiation Therapy: First Year Experience at the University of Alabama at Birmingham

To evaluate treatment planning and delivery for patients treated during our initial year of experience with RapidArc radiation therapy. RapidArc was used to treat 52 patients at The University of Alabama at Birmingham between May 2008 and April 2009. A single ionization chamber phantom with film and a two-dimensional ionization chamber array were used for quality assurance measurements. Of the 52 patients, 44 had a static gantry dynamic multileaf collimated (SG-DMLC) IMRT treatment plan, seven of which had quality assurance (QA) measurements. The mean difference between ionization chamber measurement and calculation was 1.2% +/- 0.9% (1 standard deviation). For film, the mean fraction of pixels with gamma > 1 (3%/3 mm criterion) was 4.6% and for the two-dimensional chamber array was 1.4%. For the seven corresponding SG-DMLC plans, the results were similar. Differences in important dosimetric indicators were typically within 1% relative to SG-DMLC. The volume of nontarget tissue that received >20 Gy was less for RapidArc compared with SG-DMLC, whereas the volume that received more than 10 Gy was larger. The mean difference between the measured and planned leaf positions and the monitor units obtained from machine log files was 0.0 +/- 0.5 mm and 0.4 +/- 0.3 MU, respectively. Mean delivery times were 1.5 +/- 0.2 and 3.3 +/- 0.4 min for one- and two-arc plans, respectively. On average, SG-DMLC delivery took 4.4 min longer. RapidArc plans have quality comparable to our standard SG-DMLC IMRT technique, and are delivered with similar accuracy in shorter time.

SU‐FF‐T‐445: Use of the Monte Carlo Method as a Comprehensive Tool for SMLC and DMLC‐Based IMRT Delivery and Quality Assurance (QA)

Purpose: To report on use of a thoroughly benchmarked MC dose calculation algorithm as an accurate tool for IMRT delivery and QA, in patient‐like media, where direct measurements for routine QA are impractical. Methods and material: We have developed a source model to investigate dosimetric effects related to MLC based delivery techniques such as step‐and‐shoot and sliding window using the DPM MC code. The model incorporates details of the Varian, 120‐leaf MLC and has been comprehensively verified against measurements in homogeneous and heterogeneous phantoms. As part of this development, we have investigated an efficient algorithm, using adaptive kernel density estimation for sampling phase space files. Using this accurate source model, we have studied beams that were sequenced with 1% and 10% fluence intervals for prostate, brain, head and neck and breast IMRT beams. Dose differences between SMLC and DMLC delivery types were evaluated in homogeneous and heterogeneous media (bone, lung and low‐density slabs) using DPM. We have also investigated dosimetric differences between optimized planned leaf sequences and actual delivered sequences, using machine log (Dynalog) files, which capture the physical leaf positions during delivery. Results: Benchmarking of the source model showed average agreement with measurements within 1%/2 mm. For a given fluence interval, calculated dose differences between SMLC and DMLC delivery techniques are different in homogeneous and heterogeneous media. Dose differences of up to 10% were found between plans developed with 1% and 10% fluence intervals for either SMLC or DMLC delivered sequences. Calculated dose differences of up to ±3cGy were observed between planned and delivered sequences (computed using the Dynalog files) for a prostate beam; these differences were in good agreement with film measurements. Conclusions: A well commissioned MC‐based dose algorithm provides a useful tool to study dosimetric issues related to fluence modulation and static versus dynamic delivery in IMRT.