Practical Radiation Oncology (2013) 3, 91–92
www.practicalradonc.org
Commentary
Comment on “Catching errors with patient-specific pretreatment machine log file analysis” Jon J. Kruse PhD ⁎, Charles S. Mayo PhD Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota Received 18 May 2012; accepted 21 May 2012
We read, with great interest, the recent article by Rangaraj et al 1 regarding their analysis of Dynalog files as a component of an intensity modulated radiation therapy quality assurance (IMRT QA) program. They describe an IMRT QA program consisting of 3 components: (1) ion chamber based point dose measurements; (2) a single plane dose array measurement carried out on a field by field basis; and (3) comparison of DICOM [Digital Imaging and Communications in Medicine] RT files manually exported from the planning system with Dynalog files recorded on the accelerator during QA measurements. In the normal course of preparation, a combination of manual and automated steps are used in the copying of data from the treatment planning to the record and verify and to the linear accelerator delivery systems. The third item in their program backs up the first two and, nominally, cross checks that no errors were introduced in the copy to the record and verify system. They argue that the Dynalog file analysis cannot replace physics second checks of the plan or weekly chart checks. We agree. The majority of errors tabulated in their analysis could have been caught as part of a second check of a plan. While they indicate that these errors were undetectable, perhaps the more accurate representation is that they were simply undetected. In application of the Dynalog files to compare predicted with delivered (calculated from multileaf collimator [MLC] positions in the Dynalog file) fluence patterns, See Related Article on page 80. Conflicts of interest: None. ⁎ Corresponding author. Department of Radiation Oncology, Radiation Oncology, Mayo Clinic, 200 First St SW, Rochester, MN 55901. E-mail address: [email protected] (J.J. Kruse).
they indicate selecting the condition for passing to be agreement of 90% of the pixels. The authors note that there is no dosimetric basis for this selection. In their discussion they point out that they have noted that the machine MLC log files sometimes “contain incomplete data and other defects such as missing data for an entire MLC carriage.” However, in their discussion the authors argue that “Compared with the IC and MapCHECK technique,… that Dynalog file analysis is much more sensitive and would catch any deviation from the treatment plan.” Use of the Dynalog process in addition to the measurement is reasonable. The suggestion of using it in place of the measurement gives us pause. A condition of no errors is most desirable. Detecting errors that can have significant dosimetric consequences is most essential. There are many places in a process (among vendor systems, etc) where errors that affect dose can be made. The advantage of a dose measurement is that it minimizes dependence on the assumption that all potential sources of error in a process are well understood and controlled. If something occurs that would not be noticed in an electronic process because the model of what matters failed, the dose measurement provides a tangible limit on how big the error could be. The closer the measurement comes to the conditions in the patient, the lower the probability of missing a dose significant error. In our experience, the authors’ premise of a thorough commissioning of an IMRT planning system is very difficult to achieve and a perfect commissioning may be impossible. With 3-dimensional (3D) planning systems, the data that are put into the system at commissioning (dose distributions from relatively large open fields) are very similar to the desired output (dose distributions from relatively large open fields). Using an intelligent suite of
1879-8500/$ – see front matter © 2013 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.prro.2012.05.007
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test plans, one can confirm with a high level of confidence that a 3D system will perform as expected under normal clinical use. This confidence has led physicists, generally, to rely upon simple independent monitor unit calculations to QA 3D plans. Conversely, the output of an IMRT system, dose distributions sometimes delivered from tiny, dynamic MLC motions, are much different from the data entered during commissioning. An intelligent QA program should anticipate the most likely problems in a process and identify those problems with high sensitivity. In our experience, modeling dose deposition from miniscule MLC openings with relatively large photon pencil beams is a difficult problem that is not uniformly accomplished by commercial planning systems. The authors note that common approaches, point dose measurements of the composite plan and 2D analysis of individual fields, both suffer from shortcomings. The difficulty in making and analyzing these measurements has been noted here and elsewhere. 2-4 However, planar 2D measurements within a composite IMRT plan provide easily interpretable results over a large volume. We note that other measurements, described by the authors as in vivo (in patient) really are not; they are ex vivo. A back calculation based on these measurements, to project what the dose in the patient might have been, could be valuable but it is susceptible to the potential sources of error in dose calculations. Actual 3D dosimetry measurements may not be far off. 5 Design of a QA process is about reducing the probability of a significant error occurring within the limits of
Practical Radiation Oncology: April-June 2013
our resources to carry out the process. Our knowledge is always incomplete but we can be cautious in distinguishing the limits of what we know. Despite widespread clinical use of IMRT for over 10 years, and many very bright people considering the problem, there is still no general consensus on the details of appropriate, effective measures for IMRT QA. 4 Automated, routine Dynalog analysis could provide robust consistency checks throughout a course of treatment and augment careful pretreatment dosimetric verification. However, from our point of view, physical dosimetric checks of IMRT plans should continue to be a mainstay of IMRT QA programs.
References 1. Rangaraj D, Zhu M, Yang D, et al. Catching errors with patient-specific pretreatment machine log file analysis. Practical Radiat Oncol. 2013;3: 80-90. 2. Smith JC, Dieterich S, Orton CG. Point/counterpoint. It is still necessary to validate each individual IMRT treatment plan with dosimetric measurements before delivery. Med. Phys. 2011;38:553-555. 3. Kruse JJ. On the insensitivity of single field planar dosimetry to IMRT inaccuracies. Med Phys. 2010;37:2516-2524. 4. Nelms BE, Zhen H, Tomé WA. Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors. Med Phys. 2011;38:1037-1044. 5. Lopatiuk-Tirpak O, Langen KM, Meeks SL, Kupelian PA, Zeidan OA, Maryanski MJ. Performance evaluation of an improved optical computed tomography polymer gel dosimeter system for 3D dose verification of static and dynamic phantom deliveries. Med Phys. 2008;35:3847-3859.
www.practicalradonc.org
Commentary
Comment on “Catching errors with patient-specific pretreatment machine log file analysis” Jon J. Kruse PhD ⁎, Charles S. Mayo PhD Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota Received 18 May 2012; accepted 21 May 2012
We read, with great interest, the recent article by Rangaraj et al 1 regarding their analysis of Dynalog files as a component of an intensity modulated radiation therapy quality assurance (IMRT QA) program. They describe an IMRT QA program consisting of 3 components: (1) ion chamber based point dose measurements; (2) a single plane dose array measurement carried out on a field by field basis; and (3) comparison of DICOM [Digital Imaging and Communications in Medicine] RT files manually exported from the planning system with Dynalog files recorded on the accelerator during QA measurements. In the normal course of preparation, a combination of manual and automated steps are used in the copying of data from the treatment planning to the record and verify and to the linear accelerator delivery systems. The third item in their program backs up the first two and, nominally, cross checks that no errors were introduced in the copy to the record and verify system. They argue that the Dynalog file analysis cannot replace physics second checks of the plan or weekly chart checks. We agree. The majority of errors tabulated in their analysis could have been caught as part of a second check of a plan. While they indicate that these errors were undetectable, perhaps the more accurate representation is that they were simply undetected. In application of the Dynalog files to compare predicted with delivered (calculated from multileaf collimator [MLC] positions in the Dynalog file) fluence patterns, See Related Article on page 80. Conflicts of interest: None. ⁎ Corresponding author. Department of Radiation Oncology, Radiation Oncology, Mayo Clinic, 200 First St SW, Rochester, MN 55901. E-mail address: [email protected] (J.J. Kruse).
they indicate selecting the condition for passing to be agreement of 90% of the pixels. The authors note that there is no dosimetric basis for this selection. In their discussion they point out that they have noted that the machine MLC log files sometimes “contain incomplete data and other defects such as missing data for an entire MLC carriage.” However, in their discussion the authors argue that “Compared with the IC and MapCHECK technique,… that Dynalog file analysis is much more sensitive and would catch any deviation from the treatment plan.” Use of the Dynalog process in addition to the measurement is reasonable. The suggestion of using it in place of the measurement gives us pause. A condition of no errors is most desirable. Detecting errors that can have significant dosimetric consequences is most essential. There are many places in a process (among vendor systems, etc) where errors that affect dose can be made. The advantage of a dose measurement is that it minimizes dependence on the assumption that all potential sources of error in a process are well understood and controlled. If something occurs that would not be noticed in an electronic process because the model of what matters failed, the dose measurement provides a tangible limit on how big the error could be. The closer the measurement comes to the conditions in the patient, the lower the probability of missing a dose significant error. In our experience, the authors’ premise of a thorough commissioning of an IMRT planning system is very difficult to achieve and a perfect commissioning may be impossible. With 3-dimensional (3D) planning systems, the data that are put into the system at commissioning (dose distributions from relatively large open fields) are very similar to the desired output (dose distributions from relatively large open fields). Using an intelligent suite of
1879-8500/$ – see front matter © 2013 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.prro.2012.05.007
92
J.J. Kruse, C.S. Mayo
test plans, one can confirm with a high level of confidence that a 3D system will perform as expected under normal clinical use. This confidence has led physicists, generally, to rely upon simple independent monitor unit calculations to QA 3D plans. Conversely, the output of an IMRT system, dose distributions sometimes delivered from tiny, dynamic MLC motions, are much different from the data entered during commissioning. An intelligent QA program should anticipate the most likely problems in a process and identify those problems with high sensitivity. In our experience, modeling dose deposition from miniscule MLC openings with relatively large photon pencil beams is a difficult problem that is not uniformly accomplished by commercial planning systems. The authors note that common approaches, point dose measurements of the composite plan and 2D analysis of individual fields, both suffer from shortcomings. The difficulty in making and analyzing these measurements has been noted here and elsewhere. 2-4 However, planar 2D measurements within a composite IMRT plan provide easily interpretable results over a large volume. We note that other measurements, described by the authors as in vivo (in patient) really are not; they are ex vivo. A back calculation based on these measurements, to project what the dose in the patient might have been, could be valuable but it is susceptible to the potential sources of error in dose calculations. Actual 3D dosimetry measurements may not be far off. 5 Design of a QA process is about reducing the probability of a significant error occurring within the limits of
Practical Radiation Oncology: April-June 2013
our resources to carry out the process. Our knowledge is always incomplete but we can be cautious in distinguishing the limits of what we know. Despite widespread clinical use of IMRT for over 10 years, and many very bright people considering the problem, there is still no general consensus on the details of appropriate, effective measures for IMRT QA. 4 Automated, routine Dynalog analysis could provide robust consistency checks throughout a course of treatment and augment careful pretreatment dosimetric verification. However, from our point of view, physical dosimetric checks of IMRT plans should continue to be a mainstay of IMRT QA programs.
References 1. Rangaraj D, Zhu M, Yang D, et al. Catching errors with patient-specific pretreatment machine log file analysis. Practical Radiat Oncol. 2013;3: 80-90. 2. Smith JC, Dieterich S, Orton CG. Point/counterpoint. It is still necessary to validate each individual IMRT treatment plan with dosimetric measurements before delivery. Med. Phys. 2011;38:553-555. 3. Kruse JJ. On the insensitivity of single field planar dosimetry to IMRT inaccuracies. Med Phys. 2010;37:2516-2524. 4. Nelms BE, Zhen H, Tomé WA. Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors. Med Phys. 2011;38:1037-1044. 5. Lopatiuk-Tirpak O, Langen KM, Meeks SL, Kupelian PA, Zeidan OA, Maryanski MJ. Performance evaluation of an improved optical computed tomography polymer gel dosimeter system for 3D dose verification of static and dynamic phantom deliveries. Med Phys. 2008;35:3847-3859.
