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Using detector arrays to improve the efficiency of linear accelerator quality assurance and radiation data collection

Dissertation
Author: Thomas Allan Simon
Abstract:
The complexity of radiation therapy is continually increasing as new treatment modalities are implemented in the clinic. While these advances often benefit tumor dose localization, they also increase pressure on departmental resources as the new modality is adopted. This driving force comes at a time of increased pressure to perform quality assurance (QA) of the entire treatment process. The effect is a work force with too many measurements to do and not enough time in which to do them. The purpose of this work is to establish the use of detector arrays to improve the automation and efficiency of linear accelerator (LINAC) quality assurance and radiation data collection. Two traditionally time consuming measurement processes were evaluated for the potential for increased efficiency and automation: multi-leaf collimator (MLC) calibration and scanning water tank measurements. Using traditional measurement techniques, MLC calibration can take hours to accomplish with mixed results or require a significant investment of time to write in-house software. We developed a quantitative and efficient (less than 30 minutes for both leaf banks) MLC calibration method that we termed the radiation defined reference line (RDRL) method. The method uses a detector array [PROFILER 2(TM); Sun Nuclear Corporation (SNC), Melbourne, FL USA] to measure the penumbral position of each leaf relative to a known reference point (or line). Profile measurements are typically obtained with a scanning water tank. While time tested, the system requires above average skill and time to properly setup and acquire data. We extensively characterized and assessed the potential of a multi-axis ionization chamber array (IC PROFILER(TM); SNC) to measure water tank equivalent profiles. The IC PROFILER(TM) had an error spread of approximately (±) 0.75% relative to a water scan, with the potential of a positive offset in that error. During the characterization, the array calibration method was found to be susceptible to the LINACs symmetry stability. Symmetry variations of (±) 0.1% can cause calibration errors of (±) 2%. The cause was investigated and corrective measures were developed. Finally, a time efficient QA program was developed to determine the operation of the detector arrays.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS..................................................................................................4 LIST OF TABLES............................................................................................................8 LIST OF FIGURES..........................................................................................................9 LIST OF ABBREVIATIONS...........................................................................................11 ABSTRACT...................................................................................................................13 CHAPTER 1 INTRODUCTION....................................................................................................15 General Introduction...............................................................................................15 New Treatment Modalities Increase a Facility’s Resource Requirements........16 How Do We Solve this Problem?.....................................................................17 Streamlining Data Collection............................................................................19 Study Aims..............................................................................................................20 2 MLC CALIBRATION USING A DETECTOR ARRAY..............................................23 Introduction.............................................................................................................23 Materials and Methods............................................................................................24 Materials...........................................................................................................24 Linear accelerator and MLC.......................................................................24 Detector arrays..........................................................................................25 Methods............................................................................................................26 Measuring minor leaf offsets......................................................................27 Measuring major leaf offsets......................................................................33 MLC calibration..........................................................................................36 Other MLC types........................................................................................37 Results....................................................................................................................37 Detector Offsets...............................................................................................37 MLC Measurement Comparison and Reproducibility.......................................38 MLC Service Issues.........................................................................................39 Discussion..............................................................................................................39 MLC Calibration Stability and QA.....................................................................39 Device Comparisons........................................................................................40 Conclusion..............................................................................................................42 3 CHARACTERIZATION OF A MULTI-AXIS IONIZATION CHAMBER ARRAY.......47 Introduction.............................................................................................................47 5

Materials and Methods............................................................................................48 Materials...........................................................................................................48 Methods............................................................................................................49 Reproducibility...........................................................................................50 Dose and instantaneous dose rate dependence........................................50 PRF dependence.......................................................................................52 Energy dependence...................................................................................53 Response to power being applied to the electronics..................................54 Calibration constancy.................................................................................55 Backscatter dependence...........................................................................56 Beam profile measurements and output factors.........................................57 Results and Discussion...........................................................................................58 Reproducibility..................................................................................................58 Dose and Instantaneous Dose Rate Dependence...........................................58 PRF Dependence.............................................................................................61 Energy Dependence.........................................................................................63 Response to Power Applied to the Electronics.................................................64 Calibration Constancy......................................................................................64 Backscatter Dependence.................................................................................65 Beam Profile Measurements and Output Factors.............................................66 Conclusion..............................................................................................................67 4 WIDE FIELD ARRAY CALIBRATION DEPENDENCE ON THE STABILITY OF MEASURED DOSE DISTRIBUTIONS....................................................................78 Introduction.............................................................................................................78 Materials and Methods............................................................................................79 Materials...........................................................................................................79 Methods............................................................................................................80 Wide field calibration theory.......................................................................80 Limiting calibration error.............................................................................83 Effects of postulate failure..........................................................................83 Limiting violations of the first postulate......................................................84 Limiting violations of the second postulate.................................................85 Limiting violations of the third postulate.....................................................86 Evaluating calibration factors.....................................................................87 Results and Discussion...........................................................................................90 Effects of Postulate Failure...............................................................................90 Limiting Violations of the First Calibration Postulate.........................................91 Limiting Violations of the Third Calibration Postulate.......................................92 Evaluating Calibration Factors..........................................................................93 Other Factors Affecting the WF Calibration......................................................94 Other Arrays and IMRT....................................................................................95 Conclusion..............................................................................................................95 5 A QUALITY ASSURANCE PROGRAM FOR A DETECTOR ARRAY...................102 6

Introduction...........................................................................................................102 Materials and Methods..........................................................................................103 Materials.........................................................................................................103 Methods..........................................................................................................104 Physical...................................................................................................104 Firmware and software............................................................................105 Electronics...............................................................................................108 Array calibration.......................................................................................111 Results and Discussion.........................................................................................114 Physical..........................................................................................................114 Firmware and Software..................................................................................115 Electronics......................................................................................................115 Array Calibration.............................................................................................119 Conclusion............................................................................................................120 6 SUMMARY AND FUTURE WORK.......................................................................126 LIST OF REFERENCES.............................................................................................130 BIOGRAPHICAL SKETCH..........................................................................................135

7

LIST OF TABLES Table page

2-1 List of collimator settings for PROFILER 2™......................................................43 2-2 List of additional collimator settings for PROFILER 2™ measurements of the major leaf offsets................................................................................................43 3-1 List of subscripts, variables, and equations........................................................69 3-2 The panel’s short and long-term reproducibility were evaluated on a 60 Co teletherapy unit...................................................................................................70 3-3 The short and long term reproducibility of the relative detector calibration factors.................................................................................................................70 4-1 The short term reproducibility of WF calibrations performed on the Elekta........97 5-1 Quality assurance program for the IC PROFILER™........................................122 5-2 Percent of detectors rejecting H 0 ......................................................................122

8

LIST OF FIGURES Figure page

2-1 Minor leaf offsets are defined as the spatial offset of each leaf in a leaf.............44 2-2 (A) The radiation defined reference line (RDRL) method requires......................44 2-3 The measurements required to radiographically align the array.........................45 2-4 (A) Detector offsets relative to a reference detector...........................................45 2-5 MLC leaf offsets relative to leaf number 20, the reference leaf..........................46 2-6 Change in relative MLC offsets after replacement of the primary.......................46 2-7 Calibration of the X1 MLC leaf bank...................................................................46 3-1 Overlay of the IC PROFILER™ (panel) showing the multiple detector...............71 3-2 The panel’s dose response relative to the Farmer-type chamber’s dose...........71 3-3 The panel’s instantaneous dose rate response relative to the Farmer-..............72 3-4 The panel’s PRF response relative to the Farmer-type chamber’s PRF.............72 3-5 The off-axis PRF response for the x-axis detectors relative to the center..........73 3-6 The difference between the 180° and 0° OA_Response(PRF) values for..........73 3-7 The energy response of the panel’s center detector presented as a ratio..........73 3-8 The accuracy of the calibration factors...............................................................74 3-9 The energy response of the calibration factors...................................................74 3-10 The buildup response of the calibration factors for 6 and 18 MV........................74 3-11 Off axis backscatter response of the x-axis detectors for (A) a 6 MV.................75 3-12 Normalized cross-plane measurements with a CC13™ and the panel...............75 3-13 Profile agreement (over 80% of the field width) between the panel and.............76 3-14 FDDs for a 6 MV 10 x 10 cm 2 field.....................................................................76 3-15 Output factors measured with the panel’s center chamber and three.................77 4-1 Wide field (WF) calibration reproducibility on LINACs with beam.......................98 9

4-2 Oblique view of the panel’s arrays and electronics. The panel’s y-axis is..........98 4-3 (A) The perturbation that was applied to the hypothetical calibration.................99 4-4 The percentage error between ten consecutive measurements and their..........99 4-5 Calibration reproducibility using a continuous beam during..............................100 4-6 The effect of additional side-scatter on (A) beam measurements and (B)........100 4-7 The agreement between calibration factors obtained with side-scatter............100 4-8 The calibration accuracy was evaluated for four measurement........................101 4-9 The calibration accuracy expressed as the ratio between water tank...............101 5-1 Cable damage as a result of (A) disconnecting the cable by pulling the...........123 5-2 The measurement reproducibility for the panel on the Elekta Synergy®..........123 5-3 (A) An example of two background measurements that were separated.........124 5-4 The PDF of UC for the (-) 12.5 cm x-axis detector (X8)....................................124 5-5 The accuracy of the panel’s calibration factors were determined using............125 5-6 (A) Profile measurements with the panel and a scanning water tank...............125

10

LIST OF ABBREVIATIONS AAPM American Association of Physicists in Medicine CAX Central axis of the LINAC coordinate system CCD Charge coupled device camera used in the control of the MLC EPID Electronic portal imaging device EDW Enhanced dynamic wedge FDD Fractional depth dose FMEA Failure mode and effects analysis IBA Ion Beam Applications (equipment manufacturer) IMRT Intensity modulated radiation therapy LINAC Linear accelerator LSI Local standard instrument MALO Major leaf offset MILO Minor leaf offset MLC Multi-leaf collimator NIST Nation Institute of Standards and Technology panel IC PROFILER™ PTW Physikalisch-Technische Werkstätten (equipment manufacturer) QA Quality assurance RDRL Radiation defined reference line method SA1 Specific aim 1 SA2 Specific aim 2 SA3 Specific aim 3 SA4 Specific aim 4 SNC Sun Nuclear Corporation (equipment manufacturer) 11

SDD Source to detector distance SSD Source to surface distance TG Task group TPS Treatment planning system

12

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

USING DETECTOR ARRAYS TO IMPROVE THE EFFICIENCY OF LINEAR ACCELERATOR QUALITY ASSURANCE AND RADIATION DATA COLLECTION By Thomas Allan Simon

August 2010

Chair: Chihray Liu Major: Nuclear Engineering Sciences

The complexity of radiation therapy is continually increasing as new treatment modalities are implemented in the clinic. While these advances often benefit tumor dose localization, they also increase pressure on departmental resources as the new modality is adopted. This driving force comes at a time of increased pressure to perform quality assurance (QA) of the entire treatment process. The effect is a work force with too many measurements to do and not enough time in which to do them. The purpose of this work is to establish the use of detector arrays to improve the automation and efficiency of linear accelerator (LINAC) quality assurance and radiation data collection. Two traditionally time consuming measurement processes were evaluated for the potential for increased efficiency and automation: multi-leaf collimator (MLC) calibration and scanning water tank measurements. Using traditional measurement techniques, MLC calibration can take hours to accomplish with mixed results or require a significant investment of time to write in-house software. We developed a quantitative and efficient (less than 30 minutes for both leaf banks) MLC calibration method that we termed the radiation defined reference line (RDRL) method. The method uses a detector array 13

14 [PROFILER 2™; Sun Nuclear Corporation (SNC), Melbourne, FL USA] to measure the penumbral position of each leaf relative to a known reference point (or line). Profile measurements are typically obtained with a scanning water tank. While time tested, the system requires above average skill and time to properly setup and acquire data. We extensively characterized and assessed the potential of a multi-axis ionization chamber array (IC PROFILER™; SNC) to measure water tank equivalent profiles. The IC PROFILER™ had an error spread of approximately (±) 0.75% relative to a water scan, with the potential of a positive offset in that error. During the characterization, the array calibration method was found to be susceptible to the LINACs symmetry stability. Symmetry variations of (±) 0.1% can cause calibration errors of (±) 2%. The cause was investigated and corrective measures were developed. Finally, a time efficient QA program was developed to determine the operation of the detector arrays.

CHAPTER 1 INTRODUCTION General Introduction The complexity of radiation therapy is continually increasing as new treatment modalities are implemented in the clinic. While these advances often benefit tumor dose localization, they also increase pressure on departmental resources as the new modality is adopted. 1 An example of this cause and effect is the use of dynamic wedges over the more traditional physical wedge. The enhanced dynamic wedge (EDW) increased the efficiency of radiation treatment by eliminating the need to enter the treatment vault to install a wedge. Instead of a physical beam attenuator, the wedge intensity pattern is created by dynamically sweeping the collimator across the field while delivering radiation. The EDW increased treatment efficiency; but it also complicated the radiation data collection process. Measuring an EDW with a scanning water tank requires each profile point to be integrated through an entire delivery. Measuring a range of field sizes, depths, and energies could extend to several days. To cope with the increased measurement requirements, the clinical physicist relied on a new measurement technology – detector arrays. The use of detector arrays greatly increased the efficiency of EDW measurements due to their simultaneous measurement of multiple points. What previously took scanning water tanks several days to measure was reduced to a few hours with detector arrays. Just as dynamic wedges increased the complexity of radiation therapy, an abundance of new treatment modalities are poised to do the same. 2-4 This comes at a time when the demands on the physics department are already high. 5, 6 To adapt and 15

evolve with the shifting clinical environment, we need to reevaluate how quality assurance (QA) and radiation data collection is performed. The purpose of this work is to establish the use of detector arrays to improve the automation and efficiency of LINAC QA and radiation data collection. New Treatment Modalities Increase a Facility’s Resource Requirements New treatment modalities in radiation therapy are becoming increasingly complex through the incorporation of various imaging, treatment planning system (TPS), patient localization, and delivery options. 2-4 While the level of patient care is improved, the overall complexity and verification requirements for those treatments increase as well. This cause and effect is usually accompanied with a corresponding lag in the evolution of QA technology. 1 An example lies in the introduction of intensity modulated radiation therapy (IMRT). The radiation therapy process tree grew in complexity with the adoption of IMRT. It affected all aspects of the clinic, but it greatly increased the time demand on physicists in the form of treatment verification. 7 During its initial introduction, the primary method for verifying two dimensional dose distributions was film dosimetry. 7, 8 While this verification process provided high-spatial-density-dosimetric-information, it was inefficient considering the multi-field, multi-film nature of IMRT QA. A simple seven field prostate plan could take up to two hours to verify. An emerging modality that threatens to further increase complexity is single arc IMRT. This combines the principles of dynamic IMRT with the added complexity of continuously moving gantry components and a varying dose rate. 9 Just as film was initially used to verify IMRT plans, the tools and methods that were developed for IMRT are now being used to verify arc therapies. 10-12 While these technologies may prove to 16

be just as arduous as film dosimetry was to IMRT, new dosimetry systems are already emerging that promise to efficiently handle the QA requirements of single arc IMRT. 13, 14

How Do We Solve this Problem? With each new treatment modality, new verification requirements are added to the existing regime. So many tests already exist that it would be nearly impossible to do them all. 15 This begs the question “is all of this QA needed?” For example, if a physicist performs annual QA that takes 10 hours and no problems were discovered, then were those 10 hours wasted? Could they have been spent on an item that is more likely to fail? Does this mean we should not perform annual QA? No; it means we need to approach certain aspects of QA and data collection differently. Looking at QA in a different light is already being addressed. The American Association of Physicists in Medicine (AAPM) is taking two separate approaches, led by Task Groups (TGs) 100 and 142. 16, 17 The approach of TG-100 is to apply Failure Mode and Effects Analysis (FMEA) to the radiation therapy process. This process is a powerful tool that aids in the allocation of resources to a system in an effort to detect modes of failure before they occur. The goal of TG-100 is for each radiation oncology clinic to compose a personalized FMEA analysis for each treatment process tree in its clinic. While a completed FMEA analysis would help to focus departmental resources, the creation of the FMEA analysis will greatly increase the time requirements on the clinic and its physicists. The approach of TG-142 is somewhat different. Similar to TG-40, it provides updated machine item tolerances. Unlike TG-40, it recommends different tolerances for different modalities. While addressing that conventional radiotherapy LINACs do not need the same mechanical tolerances that stereotactic-radio-surgery LINACs do, TG- 17

142 fails to address the associated time load that already exists. As new modalities are introduced, the time load will only increase. Both TG-100 and 142 provide useful QA recommendations and insights. However, the overall result is likely to be an increase in time and measurement requirements. We feel that measurement automation and increased efficiency is the key to aid the clinical physicist. Again, dosimetric verification of IMRT illustrates an example. A typical seven field prostate plan requires nearly 2 hours for verification using film. There is also a high potential for error in the film dosimetry process that can be a source of inconsistency throughout the community. 18-21 The introduction of two dimensional detector arrays streamlined the IMRT QA process. The effect was a reduction in the time requirements from nearly two hours to 45 minutes for a typical seven field prostate exam. The acquisition of the results was also standardized to a certain extent with the 2D arrays. 22

This provided the community with a much more consistent reporting of results and also an increase in care. A second example exists with the measurement of EDWs. Initially, scanning water tanks were used to measure EDWs with a series of point measurements. 23 Each measurement point represented the duration of an EDW delivery. This was a time intensive undertaking even without factoring in the time of tank setup and break-down. The whole process could easily take several days to complete. The introduction of detector arrays that are mounted in a scanning water tank decreased the time requirements by providing multiple integration points per measurement. 23, 24 However, 18

the process still required a scanning water tank. The introduction of a detector array that lay on the treatment reduced the required time to minutes. 25

Streamlining Data Collection Automating and streamlining the QA and data collection regimen is a daunting task due to the variety of measurements and delivery systems. It is nearly impossible for one agency or group to solve all of these problems. However, a published group of tests that the agencies could recommend would help to solve this problem. This would allow for a much faster response time as QA and data collection demands shifted. As an example, two methods that have traditionally been resource intensive were investigated for the possibility of streamlining. They are the calibration of MLCs and scanning water tank measurements. The current methods for calibrating MLCs include the use of graph paper, film, electronic portal imaging devices (EPIDs), and scanning water tanks. Each of these measurement methods has certain advantages and disadvantages. Graph paper and film are both time tested and intuitive. However, they are resource intensive and may only provide qualitative results. Water tanks are well understood with highly accurate and repeatable mechanics, but require a large amount of resources and suffer from detector volume averaging unless a pinpoint (diamond, 26 diode detector, 27 etc.) detector is used. The calibration of MLCs with any of these methods takes many hours to complete. A dosimeter that is more efficient is the EPID. Unfortunately, they require user written code due to a relative lack of commercial software. Detector arrays have the potential to reduce that time requirement from hours to minutes. Scanning water tanks are the gold standard of radiation therapy measurements. They are time tested, precise, and reproducible. They do however require large 19

amounts of time for setup and data collection. 28 They also require a higher degree of skill to accurately use. 28 The clinical physicist therefore rarely uses the scanning water tank. Most are only used during the LINAC beam commissioning and annual QA. Advances in computer technology have improved their efficiency. However, they still require large amounts of preparation time (~ 1 ½ hours to setup and break down) and actual scanning time [several days to measure linear accelerator (LINAC) beam commissioning data]. 28 Infrequent use by the clinical physicist adds to these inefficiencies and decreases the likelihood of obtaining quality data. The skill required to obtain quality beam profile measurements with a detector array is less. This is due to physicists being more familiar with detector panels and also due to their lack of mechanical parts and liquid water. Study Aims For this dissertation, two time consuming measurement processes were chosen as a showcase for the potential of detector arrays to increase measurement automation and efficiency. The first specific aim covers the calibration of multi-leaf-collimators (MLC). The remaining specific aims deal with using the IC PROFILER™ as a water tank alternative. Specific Aim 1 (SA1) – MLC calibration with detector arrays: Each leaf end creates a penumbral position that corresponds to its actual position. An array that uses a detector with minimal volume averaging can accurately measure these leaf positions for QA or calibration purposes. The purpose of this aim is to create an efficient and quantitative MLC calibration method that uses a commercially available detector array (e.g. the PROFILER 2™ or an EPID). 20

Specific Aim 2 (SA2) – Characterize the IC PROFILER™: The IC PROFILER™ is a multi-axis ion chamber array and therefore does not suffer from the undesirable detector characteristics that diode detectors possess. However, it’s potential as a water tank alternative underlies the importance of fully understanding the device and how it reacts in a radiation environment. The purpose of this aim is to do just that; extensively characterize the IC PROFILER™ in a radiation environment and establish its ability to measure LINAC beam parameters. Specific Aim 3 (SA3) – Increase the reproducibility of the wide field calibration theory for use in unstable beams: The wide field calibration theory has become a prominent fixture in the radiation oncology environment. It is used to correct the intra- detector-sensitivity-variation in a wide variety of detector arrays, including the MapCHECK™, PROFILER 2™, and IC PROFILER™. Accurate measurements with these systems require confidence in the individual detectors’ calibrations. However, the calibration theory requires a perfectly reproducible LINAC beam; otherwise unacceptable error levels are encountered. The purpose of this specific aim is to minimize the effects of beam instability in the wide field calibration theory. Specific Aim 4 (SA4) – Establish a quality assurance program for the IC PROFILER™: The potential importance of the data provided by the IC PROFILER™ (i.e. annual QA and LINAC commissioning) requires the highest level of confidence in the array and it’s measured data. The purpose of this specific aim is to develop a series of field tests that indicate proper function of the IC PROFILER™ and detector arrays in general. In summary, this dissertation is organized into four specific aims: 21

22 SA1: Create an efficient MLC calibration method using detector arrays (Chapter 2). SA2: Characterize the IC PROFILER™ in the radiation environment (Chapter 3). SA3: Increase the reproducibility of the Wide Field Calibration theory when operated in beams with micro instabilities (Chapter 4). SA4: Establish a QA program for the IC PROFILER™ and detector arrays in general (Chapter 5).

CHAPTER 2 MLC CALIBRATION USING A DETECTOR ARRAY Introduction Intensity modulated radiation therapy (IMRT) is a treatment modality that is used to deliver a dose prescription to a tumor site while minimizing the exposure to surrounding healthy tissues. A popular method of implementing IMRT is to superpose a series of irregular fields that are shaped with a multi leaf collimator (MLC) to create a complex radiation fluence map. The principles of radiation transport then govern the conversion of the fluence map to a dose map. The correct placement of high-gradient dose regions in and near the target volume is dependent on an accurate positioning of the MLC leaves during the delivery of the IMRT fields. In a recent study, Mu et al. demonstrated that a systematic leaf positioning error of 1 mm in IMRT plans can result in dose errors of up to 7.6 % and 12.2 % for the target and critical structures, respectively. 29 Errors of this size can have a biologically significant effect on the outcome of the therapy. 30 For this reason the MLC must be accurately calibrated and periodically tested. MLC calibration requires the ability to precisely measure individual leaf positions. Traditional methods of calibration are time consuming and/or non-reproducible in nature. These methods include the use of graph paper, 31 radiosensitive film, 31, 32

scanning water tanks, electronic portal imaging devices (EPID)’s, 33-35 detector arrays, 36

and manufacturer’s proprietary methods. While each of these techniques has advantages and disadvantages, the current trend is toward more efficient and reproducible methods. 23

Recent publications have shown a refinement in measurement and calibration techniques. In 2006 Parent et al. used an EPID to measure and predict the positions of individual leaves on an Elekta MLC. 33 In 2007 Lopes et al. used an ion-chamber array mounted in a water tank to calibrate the individual leaf positions for a Siemens MLC. 36

While both of these techniques are an improvement on the traditional methods, they still require a significant investment of time. Using an EPID to measure leaf positions requires mechanical and/or software corrections as well as user-written code. The ion chamber array-based approach is susceptible to the volume averaging of the ion chambers and requires the setup of a scanning water tank along with ancillary equipment. An integrated technique for MLC calibration exists as a proprietary method for Elekta MLCs. The AutoCAL (Elekta Oncology Systems, Crawley, UK) software suite uses EPID measurements to calibrate various machine items. This software has only recently become available and is used exclusively with the Elekta EPID. While it represents an important step toward more efficient and quantitative calibration techniques, our initial uses have shown that it is prone to delays and calibrations with unacceptable leaf positions. The purpose of our research was to develop a more efficient and reproducible method for calibrating an MLC. Materials and Methods Materials Linear accelerator and MLC All tests were performed with an Elekta Synergy (Elekta Oncology Systems, Crawley, UK) linear accelerator (LINAC) using the 6 MV photon beam. The LINAC’s 24

MLC is a 40 leaf-pair device that has been described in detail. 37, 38 Each leaf projects to a width of 1 cm at the isocentric plane (100 cm from source). Each MLC leaf bank is located above a backup jaw that aids in beam collimation and reduces MLC radiation transmission. An MLC leaf bank and its’ associated backup jaw have parallel leading edges that travel in the cross-plane direction when the collimator is set to 0 degrees (IEC 1217 convention). 39

Elekta leaf positions are controlled through an optical system that uses field light reflected from a marker on top of each leaf. Reference reflectors are located in the machine head outside of the largest obtainable field and are used to define the MLC coordinate system. The reflected light rays trace through a series of mirrors to a charge coupled device (CCD) camera that is interfaced to a control computer. Detector arrays The PROFILER 2™ is a two-axis detector array (Sun Nuclear Corporation, Melbourne, FL) that consists of 139 diode detectors. The y-axis of the device contains 83 detectors over a length of 32.8 cm and the x-axis contains 57 detectors over a length of 22.4 cm. Both axes have a detector spacing of 4 mm and share a central detector. The inherent buildup of the device is 1 g/cm 2 of water-equivalent material. The device was chosen due to the detector spacing and the spatial measurement resolution of each detector (0.8 × 0.8 mm 2 ). Data collected using the PROFILER 2™ software can be transferred (using copy and paste) to a spreadsheet program such as Excel (Microsoft, Redmond, Washington) for analysis. The EPID used in this study is an Elekta iView GT. It has a pixel dimension of 0.4 × 0.4 mm 2 and a sensitive area of 41 × 41 cm 2 . It operates at a fixed source to surface distance (SSD) of 160 cm. The iView software automatically projects collected images 25

to the isocentric plane by scaling the pixel and field dimensions to 0.25 × 0.25 mm 2 and 25.6 × 25.6 cm 2 , respectively. Since an MLC leaf bank projects to a maximum length of 40 cm at isocenter, it is necessary to shift the EPID in order to fully image one MLC bank. The method described herein is specific to the Elekta MLC. However, the principle is general and can be applied to other manufacturers’ MLCs provided that appropriate conditions for measurements are met. Methods We have termed this measurement technique the radiation defined reference line (RDRL) method. Application of the method operates under three assumptions. First, the leading edge of an MLC leaf bank is parallel to its backup jaw’s leading edge. Second, the backup jaw can provide a reproducible and uniform radiation field edge. This field edge defines the RDRL. Third, the measured radiation field edge created by each leaf end is representative of that leaf’s position. The third assumption of the RDRL method requires detectors with a spatial measurement resolution that does not suffer from signal averaging in the high spatial frequency of the penumbra. Dempsey has shown that measurements with a detector size of 2 mm or smaller is sufficient for IMRT fields shaped with MLCs. 40 The PROFILER 2™’s detector size satisfies this requirement, but the detector location must also be known with a precision better than the desired leaf position accuracy. Elekta MLC leaf banks have traditionally been calibrated using standard measurement tools, e.g. film and scanning water tanks, to determine what are termed major and minor leaf offsets, as illustrated in Fig. 2-1. A reference leaf pair, leaf pair 20, is used in the control of the MLC. The major leaf offset (MALO) is a calibration value 26

that defines the field size created by the reference leaf pair. Minor leaf offsets (MILO) are the position alignment errors of the other leaves in relation to the reference leaf and are the first focus of this method. Measuring minor leaf offsets The method described below uses the jaw edge to precisely locate all of the y-axis detectors’ offsets relative to the reference detector, as illustrated in Fig. 2-2A; the reference detector is located in the reference leaf’s direction of travel. These relative detector positions are termed RDO j , where ‘j’ is the y-axis diode number 1 ≤ j ≤ 83; they effectively create a uniform RDRL. Once these detector positions are known, the detector array is used to measure the position of each leaf that results in a field edge at detector ‘j’ as seen in Fig. 2-2B. PROFILER 2™ The procedure that follows describes measuring the minor leaf offsets for the X1 leaf bank; the procedure is repeated for the X2 leaf bank but with appropriate collimator configurations. Three main steps were required to measure the minor leaf offsets with the PROFILER 2™ and the RDRL method: device setup, detector offset correction, and MLC measurement. Step 1- Device setup: The collimator is rotated to 180° and the PROFILER 2™ is set on the treatment table at a source to surface distance, SSD, of 79 cm and a corresponding source to detector distance (SDD) of 80 cm. The PROFILER 2™’s x and y axes are then aligned with the collimator crosshair shadow such that the positive y- axis of the PROFILER 2™ points toward the gantry. This orientation places the y-axis column of 83 detectors perpendicular to the direction of leaf movement. The orientation also directionally matches the ascending 27

Full document contains 136 pages
Abstract: The complexity of radiation therapy is continually increasing as new treatment modalities are implemented in the clinic. While these advances often benefit tumor dose localization, they also increase pressure on departmental resources as the new modality is adopted. This driving force comes at a time of increased pressure to perform quality assurance (QA) of the entire treatment process. The effect is a work force with too many measurements to do and not enough time in which to do them. The purpose of this work is to establish the use of detector arrays to improve the automation and efficiency of linear accelerator (LINAC) quality assurance and radiation data collection. Two traditionally time consuming measurement processes were evaluated for the potential for increased efficiency and automation: multi-leaf collimator (MLC) calibration and scanning water tank measurements. Using traditional measurement techniques, MLC calibration can take hours to accomplish with mixed results or require a significant investment of time to write in-house software. We developed a quantitative and efficient (less than 30 minutes for both leaf banks) MLC calibration method that we termed the radiation defined reference line (RDRL) method. The method uses a detector array [PROFILER 2(TM); Sun Nuclear Corporation (SNC), Melbourne, FL USA] to measure the penumbral position of each leaf relative to a known reference point (or line). Profile measurements are typically obtained with a scanning water tank. While time tested, the system requires above average skill and time to properly setup and acquire data. We extensively characterized and assessed the potential of a multi-axis ionization chamber array (IC PROFILER(TM); SNC) to measure water tank equivalent profiles. The IC PROFILER(TM) had an error spread of approximately (±) 0.75% relative to a water scan, with the potential of a positive offset in that error. During the characterization, the array calibration method was found to be susceptible to the LINACs symmetry stability. Symmetry variations of (±) 0.1% can cause calibration errors of (±) 2%. The cause was investigated and corrective measures were developed. Finally, a time efficient QA program was developed to determine the operation of the detector arrays.