|Year : 2017 | Volume
| Issue : 2 | Page : 297-303
Quick, efficient and effective patient-specific intensity-modulated radiation therapy quality assurance using log file and electronic portal imaging device
Rajesh Kumar1, HI Amols2, M Lovelock3, SD Sharma1, D Datta1
1 Radiological Physics and Advisory Division, Bhabha Atomic Research Centre, CTCRS, Mumbai, Maharashtra, India
2 Department of Medical Physics, Ex-Memorial Sloan Kettering Cancer Centre, New York, USA
3 Department of Medical Physics, Memorial Sloan Kettering Cancer Centre, New York, USA
|Date of Web Publication||23-Jun-2017|
Radiological Physics and Advisory Division, Bhabha Atomic Research Centre, Mumbai - 400 094, Maharashtra
Source of Support: None, Conflict of Interest: None
Aim: The aim of work is to explore a quick, efficient, and effective patient-specific intensity-modulated radiation therapy (IMRT) quality assurance (QA).
Materials and Methods: Software tools were developed to extract and analyze the multi-leaf collimator (MLC) leaf positions (LPs) from electronic portal imaging device (EPID) images for Varian C-series machine and TrueBeam, to extract useful data from MLC log file of C-series linear accelerator (LINAC), to extract useful information from the trajectory log binary file of TrueBeam LINAC, to compare LPs derived from EPID images with log file/trajectory log data, and to analyze IMRT treatment files using the MATLAB programming language. The difference in LP determined from the trajectory log and EPID images was proposed for patient-specific QA.
Results: It was found that the differences in LP for regular radiation fields generated using stationary leaves are <0.5 mm for all the field sizes while for regular radiation fields generated using the moving leaves are more but <2 mm. The differences in LPs for IMRT field were also determined and found to be <2 mm.
Conclusions: The methodology demonstrated can be used for establishing the accuracy of trajectory log data and for independent routine IMRT QA by generating single number like gamma index to indicate pass or fail of an IMRT treatment plan. The QA indices such as numbers of occurrences of ≥2 mm error in LPS are found more than 5% of total number of occurrences; the dosimetric review of planned treatment is advisable.
Keywords: Electronic portal imaging device, intensity-modulated radiation therapy, patient-specific quality assurance, trajectory log
|How to cite this article:|
Kumar R, Amols H I, Lovelock M, Sharma S D, Datta D. Quick, efficient and effective patient-specific intensity-modulated radiation therapy quality assurance using log file and electronic portal imaging device. J Can Res Ther 2017;13:297-303
|How to cite this URL:|
Kumar R, Amols H I, Lovelock M, Sharma S D, Datta D. Quick, efficient and effective patient-specific intensity-modulated radiation therapy quality assurance using log file and electronic portal imaging device. J Can Res Ther [serial online] 2017 [cited 2022 Nov 30];13:297-303. Available from: https://www.cancerjournal.net/text.asp?2017/13/2/297/207067
| > Introduction|| |
Intensity-modulated radiation therapy (IMRT) is an advanced radiotherapy technique that allows the radiation dose precisely conform to the shape of complex tumors while minimizing the dose to the surrounding normal tissue. Currently, the use of IMRT is focused on conformal avoidance of organs at risk or dose escalation strategies to the planning target volume aimed at increasing tumor control. Because of the complex nature of treatment planning and delivery of IMRT, a stringent quality assurance (QA) program has been recommended for its safe and effective implementation in clinical practice.,,,,,,,,,, QA process for IMRT implementation in clinical practice can be divided into three groups: (1) commissioning of the IMRT system that includes planning system parameter adjustment, dosimetric tests with different phantoms, adjustment of the delivery system, and tests of the data transfer; (2) regular machine-related QA procedures that comprise mechanical precision of static test fields or mechanical and dosimetric precision of dynamic test fields; and (3) regular patient-related QA procedures that involve dosimetric plan verification, dosimetric field by field verification, and independent monitor unit (MU) checks. The first two QA programs are standard in nature and must be followed even without IMRT/volumetrically modulated arc therapy. The most common IMRT errors can be either physical errors (e.g., calibration/commissioning of treatment planning and delivery system) or catastrophic errors (e.g., wrong field data transfer). Patient-specific QA focuses on potential clinical errors. Measurement-based patient-specific IMRT QA is performed only for limited number of times and requires considerable time of delivery system as well as of medical physicist. However, catastrophic type of errors can occur at any time during treatment. If the treatment planning system has been commissioned suitably for IMRT and adequate periodic machine QA for IMRT are in place, measurement-based patient-specific IMRT QA can be replaced with software-based IMRT QA. Trajectory log file which is “free information” can be harvested to document individual patient treatments. Data in log files do not require any additional time or dose to the patient. An accident in New York City, a few years ago, where a head and neck patient getting IMRT was killed because the multi-leaf collimator (MLC) was in static mode and accident might have been prevented with such a QA technique., Log file analysis is being used as a primary tool for such documentation from several years at hospitals such as Memorial Sloan Kettering Cancer Centre, New York. Litzenberg et al., Ramsey et al., and Dinesh Kumar et al. have utilized directly or indirectly log file data for patient-specific IMRT QA. Log file data, however, are not independent as miscalibration of leaf positions (LPs) or failures in MLC positioning pots can result in erroneous command from MLC controller as signal for both positioning and monitoring of LP is coming from the same erroneous source. Such a system, however, is not completely “foolproof” as the LP data in the log/trajectory files are produced by the MLC controller itself. There is no independent verification of these data as the same MLC controller that moves the leaves also monitors LPs and writes the log/trajectory files. The images acquired by an electronic portal imaging device (EPID), on the other hand, can monitor MLC LP completely independent of the MLC controller and MLC position pots. Confirmation of MLC LPs independently with the EPID can therefore be a useful commissioning tool for IMRT capable medical electron linear accelerators (LINACs) and can be used for routine verification of each patient's IMRT treatment plan and treatment delivery without extra dose to patient or physics QA time on the LINAC. Although numerous reports exist on EPID dosimetry for IMRT, we believe that no one has specifically addressed the issue of using EPID for verification of log file data. This paper describes the methodology to compare LPs as measured from EPID images for IMRT treatment to the data in the log/trajectory files and use them as tools for quick, efficient, and effective patient-specific IMRT QA.
| > Materials and Methods|| |
The experiments were performed using a TrueBeam Medical LINAC (Varian Medical Systems, Palo Alto, CA, USA) equipped with 120 leaves MLC and flat panel-based MV/kV imaging system. The EPID attached with Varian TrueBeam LINAC is Portal Vision aS1000 (Varian Medical Systems, Palo Alto, CA, USA) amorphous silicon flat panel imaging device.
Trajectory Log/Dynalog file
TrueBeam control system generates a trajectory log file which records the actual axis position and delivers MUs at periodic intervals of 20 ms along with their expected values. The system is configured to record 60,000 data sets for 20 min at an interval of 20 ms. The trajectory log file stores data in a binary format which needs to be converted into a readable format for intended application. A single binary file generated includes information about expected and actual values of gantry angle, collimator angle, jaws positions, couch position, delivered dose in MU, beam status, control points, carriage position, and MLC LPs. The file records the linear dimensions in centimeter, rotational scale in degree, and dose in MU. The LPs stored in the trajectory log file are the position of leaves at isocenter. After each dynamic MLC field delivery, the trajectory log file for that particular field is written to a file on the control system computer automatically in treatment mode and on activation in research mode operation of the TrueBeam LINAC. There is no trajectory log file record when the beam is paused either due to minor fault or user interruption by pressing beam off button. A complete file description may be found elsewhere. Varian MLC logs in C-series machine are known as “dynalog” files. These are captured on most Varian C-series LINAC through the MLC-to-Clinac communication terminal. Two ASCII files, one each for A Bank and B Bank of MLC, are generated at the completion of every treatment field delivery. These files contain mechanical information of the LINAC throughout the treatment delivery captured at 55 ms intervals. At every instance of information capture, data on MLC actual and planned positions, gantry, jaw, and collimator positions and beam on/hold states and current dose fraction are acquired.
Initial experiments were carried out with Clinac 6EX (C-Series Machine, Varian Oncology System, USA). The EPID images (without averaging) and corresponding log files were acquired. EPID system without averaging acquires images in cine mode. There is no reliable time or dose stamp on the EPID images; this makes it difficult to synchronize the EPID images with the corresponding log file record in such machine. Moreover, in C-series machine, EPID system does not capture the image in beam hold-off condition which further complicates the synchronization of EPID image with log file records. Because of this synchronization problem on the C-series machine, to demonstrate proof of the principle with the right tools, EPID can be used to confirm accuracy of LOG files; experiment was transferred to a TrueBeam. Hence, the experimental measurements were conducted on TrueBeam LINAC where EPID system records timestamp and also captures the image frame in beam hold-off condition, in addition to the better positioning of EPID system.
Afterward, all the measurements were performed in research mode option of TrueBeam LINAC. In the research mode operation of LINAC, patient treatment is not allowed. The treatment plan files need to be converted into XML format to run in the research mode. An in-house program was developed to convert the leaf motion file (.DVA file, a proprietary file format used to run dynamic treatment file by Varian Medical System) into XML file without modification of any beam parameters, except the addition of movie MV imaging acquisition sequence. The XML file was loaded on a Varian TrueBeam LINAC in research mode with the Mega Voltage(MV) detector panel positioned at the isocenter plane. After beam delivery, the EPID images were exported in XIM format (a proprietary image format used by Varian) and were analyzed with the library supplied by Varian using an in-house developed program in MATLAB. In addition to the raw data (image intensity at each pixel), the EPID also records the start time, MV dose start, MV dose stop, MV detector longitudinal, MV detector lateral, MV detector vertical, pixel width, and pixel height indices along with other information for each image and stores them in the XIM header. These parameters were used in data analysis. However, if we import the images in DICOM format, information such as start time, MV dose start, and MV dose stop is not available in the header file. These data are very important for synchronizing the EPID images with trajectory log data.
The trajectory log binary file after each irradiation is stored in the network drive system. An in-house MATLAB code was developed to convert the binary file into text file to extract the required information from trajectory log.
Calibration and determination of the center of electronic portal imaging device detector system
The DVA file for field sizes 1 × 1, 2 × 2, 3 × 3, 4 × 4, 6 × 6, 10 × 10, 14 × 14 and 20 × 20 cm 2 was converted into the XML file and run in the research mode. The dose and dose rate were 100 MU and 300 MU/min, respectively. The images and log files were acquired. The images of these fields were used for locating the center of the detector system (pixel position/coordinates). Once the center was located, A Bank and B Bank LPs from the center were determined using the number of pixel from the center, 50% of center pixel intensity, and pixels size information from the header file. Higher field sizes due to round edge of leaves were taken care during the calibration process. These images were also used to study the variation in LP determined from the EPID images and trajectory log file. The difference in LP was determined using the following formulae:
Difference in LP = LP from trajectory log − LP from EPID Images(1)
All the differences were given in centimeter. These data were also used to study the difference in LP in the stationary field.
Effect of leaf velocity
The DVA files with A Bank leaves moving and B Bank leaves fixed and vice versa were prepared and later converted into XML format to produce a sweeping field using A Bank/B Bank leaves. While doing so, changing fields were produced by moving A Bank/B Bank leaves. The speed of leaves was changed by modifying MU for a set dose rate. The EPID images and trajectory log were acquired with 50 and 100 MU for a dose rate of 600 MU/min so that accuracy for different leaf speeds can be investigated. EPID images were synchronized with trajectory log record as depicted in [Figure 1]. The time start stamp with some modification was used to synchronize the EPID images with trajectory log records. A modified time stamp was introduced for each trajectory log by taking care of time for creation of one EPID image and one trajectory log record. The differences in LPs for stationary and moving leaves were determined.
|Figure 1: Schematic diagram for synchronization of trajectory log records and electronic portal imaging device images. Only selected trajectory/log records were used to synchronize with electronic portal imaging device images|
Click here to view
Intensity-modulated radiation therapy cases
Ten IMRT treatment files were randomly selected and their DVA files were converted into XML format. The IMRT plan was generated using dose rate of 300 MU/min, and dose per field was taken automatically from the planned files. The EPID images and trajectory log file data were acquired and processed as mentioned above. Data of each field were analyzed separately.
Software tools were developed to extract and analyze the following data:
(i) to extract MLC LPs from EPID images for C-series machine and TrueBeam, (ii) to extract useful data from MLC log file of C-Series LINAC, (iii) to extract useful information from the trajectory log binary file of TrueBeam LINAC, (iv) to compare LPs derived from EPID images with log file/trajectory log data, and (v) to analyze IMRT treatment files using the MATLAB programming language.
| > Results and Discussion|| |
[Table 1] shows the number of record/frame in log file and acquired EPID images while either A Bank or B Bank leaves were moving with set dose of 50, 100, and 1000 MU at dose rate of 600 MU/min. It can be inferred from the data in this table that for dose of 100 MU and 1000 MU, number of acquired images and log file records are almost constant for both situations, while for 50 MU, number of frames/records varies significantly. [Figure 2] shows the plot of beam hold-off flag obtained from log file during A Bank and B Bank moving conditions for dose of 50 MU and dose rate of 600 MU/min while no beam hold-off flag was noticed during delivery of 100 MU and 1000 MU dose. Beam hold-off flag 1 indicates that the beam is off during that particular instance. Lesser number of records and frames for lower MU is attributed to significant beam hold-off during which neither log file record nor EPID images getting recorded. Control computer does this whenever an MLC leaf cannot move fast enough to be in correct position, so beam is halted until leaf “catches up” and is in correct position. This occurs more frequently for small number of MUs because there is less time required for treatment delivery. EPID should be capable of acquiring at least 15 frames/s, but in real treatment, fewer frames are acquired because of timing problems, beam hold-offs, etc.
|Table 1: Number of record/frame generated in log file/electronic portal imaging device images on Varian C-series medical electron linear accelerator|
Click here to view
|Figure 2: Plot of beam hold-off flag during leaves of A Bank and B Bank moving condition for dose of 50 MU and dose rate of 600 MU/min|
Click here to view
[Figure 3]a and [Figure 3]b shows the plot of LP information derived from log file record and EPID images, respectively. It can be inferred from these figures that due to improper synchronization and absence of EPID images during beam hold-off condition, correct LPs of moving leaves are difficult to derive. It was also observed that differences in LP derived from log file record and EPID images were more for moving leaves. Further differences increase with speed of leaves.
|Figure 3: Plot of leaf position information (a) derived from log file record (50 and 600 MU/min) (b) derived from electronic portal imaging device images (50 and 600 MU/min)|
Click here to view
[Figure 4]a and [Figure 4]b shows the plots of LP information while leaves of Bank A were moving and leaves of Bank B are stationary. These LPs were derived from log file [Figure 4]a record and EPID images [Figure 4]b for 1000 MU dose and 600 MU/min dose rate. There was no beam hold during irradiation of 1000 MU with 600 MU/min. It can be inferred from this figure that moving leaves with no beam hold-off can be synchronized. However, in real practice to encounter a situation without beam hold-off is rare.
|Figure 4: Plot of leaf position information (a) derived from log file record (1000 and 600 MU/min) (b) derived from electronic portal imaging device images (1000 and 600 MU/min)|
Click here to view
[Figure 5] shows the difference in LPs determined from log file record and EPID images for A Bank and B Bank for a sliding window IMRT treatment field in the form of graphics [Figure 5]a and [Figure 5]c and histogram [Figure 5]b and [Figure 5]d. [Figure 5]a and [Figure 5]c is the plot of difference in LPs with time. The color indicates the magnitudes of error in [Figure 5]a and [Figure 5]c and the frame number in [Figure 5]b and [Figure 5]d.
|Figure 5: Matrix and error histogram showing difference in leaf positions determined from log file record and electronic portal imaging device images for A Bank and B Bank for an intensity modulated radiation therapy treatment field (C-Series Machine; for (a and c) color indicate magnitude of error while for (b and d) different frame number)|
Click here to view
For sliding window IMRT, at the beginning of each treatment beam, both A Bank and B Bank of MLC leaves are positioned at extreme left edge of the beam (−y position) and almost completely closed. As soon as the beam is turned on, first A Bank leaves start to move in extreme right side (+y) direction, followed by B Bank leaves moving toward extreme right side (+y). At the end of treatment, the MLC leaves are again almost completely closed, with both A Bank and B Bank leaves positioned at the extreme right side (+y) of the field. During treatment, if any MLC leaf cannot move fast enough to be in correct position, then a beam hold-off is automatically initiated. Beam holds are recorded in the log file. It can be observed that, at beginning, error in leaves of B Bank is fewer as leaves are either stationary or moving very slow, and later (at about frame number 100), error is more as leaves start moving fast or in beam hold-off situation. Similarly, for the A Bank, error at earlier stage (at about frame number 60) is more due to reason mentioned above. On the analysis of log file data, it was observed that corresponding to these frame numbers, there was few beam hold-off flag and so frames of EPID images were missed. However, occurrence of beam hold-off was not significant. [Figure 5]b and [Figure 5]d is the error histograms of differences in LPs determined from log file record and EPID images for A Bank and B Bank, respectively, for an IMRT treatment field. It can be observed from [Figure 5] that most of the time the error in LPs is within 2 mm for A Bank and within 3 mm for B Bank, except at locations of beam hold-off. The frequency of occurrence of error of more than 2 or 3 mm is very less. On the basis of this study, we can conclude that if beam hold-off is not present during the treatment (which is not practical), method can be used for determining difference in LPs from log file record and EPID images in C-series LINAC by synchronizing the log file record with EPID images on distributing them in equal intervals. However, due to the presence of beam hold and nonavailability of time and dose stamp on the EPID images, above-discussed methods are not suitable to make a patient-specific IMRT QA tool for Varian C-series LINAC.
TrueBeam linear accelerator
Differences in LPs were determined from trajectory log record and EPID images for leaves of Bank A and Bank B for stationary fields of 1 × 1, 2 × 2, 3 × 3, 4 × 4, 6 × 6, 10 × 10, 14 × 14, and 20 × 20 cm 2. It was found that the differences for stationary fields are lesser than 0.5 mm for all the field sizes. For stationary field, LP recorded in trajectory log is more reliable as leaves are stationary. The field sizes were determined precisely from EPID images for the stationary fields. This result indicates that the methodology used for detecting error in LP is satisfactory and reliable. The difference in LPs determined from trajectory log records and EPID images for leaves of Bank A and Bank B while leaves of A Bank are moving and leaves of B Bank are stationary and vice versa. It is observed that magnitudes of errors are more when speed of leaves is higher as observed in C-series LINAC. The errors in moving leaves are more than the stationary leaves but <2 mm. The larger error in moving leaves can be attributed to the synchronization error of EPID images for <20 ms and error in the log file data. It is worth mentioning that the tolerance for radiation field size for stationary field is 2 mm.
For TrueBeam LINAC, trajectory log and EPID images can be well synchronized (within error of distance traveled in <20 ms) with time stamp available in the header file of XIM images. The EPID images can be used for verification of LP during the dynamic treatment. [Figure 6] shows error histogram of differences in LPs determined from trajectory log record and EPID images for A Bank and B Bank, respectively, for a five-field IMRT case. It can be seen from this figure that the errors for all the fields are within 2 mm.
|Figure 6: Error histograms of differences in leaf positions determined from trajectory log record and electronic portal imaging device images for A Bank and B Bank for all five fields of an intensity-modulated radiation therapy case (Color indicates frame number) (a) Field 1 Bank A (b) Field 1 Bank B (c) Field 2 Bank A (d) Field 2 Bank B (e) Field 3 Bank A (f) Field 3 Bank B (g) Field 4 Bank A (h) Field 4 Bank 4 (i) Field 5 Bank A (j) Field 5 Bank B|
Click here to view
Similar results were obtained for all the ten IMRT cases. From [Figure 5] and [Figure 6], it can be seen that results for TrueBeam LINAC are better than C-series LINAC which can be attributed to the fewer beam holds on TrueBeam because TrueBeam precalculates required dose rate and MLC leaf speeds before treatment begins so that, during treatment, dose rate and leaf speed are continuously adjusted to ensure that leaves are always in correct position, and hence, no beam holds are required. Positioning accuracy of MLC leaves is better for TrueBeam LINAC than C-series LINAC. EPID images on TrueBeam have time stamp in header file, so it is easy to match EPID images with correct data line in log file. Analysis of trajectory log data also reveals that there is no beam hold-off throughout the study for TrueBeam in contrast to significant beam hold-off for C-Series LINAC. In addition, mechanical positioning of EPID for TrueBeam is much better than C-series LINAC. Therefore, above-discussed method is found to be more appropriate for TrueBeam LINAC.
For high leaf speeds and fewer MUs, there is more beam hold-off for C-series LINAC that complicates the synchronization between log records and EPID images while this situation does not occur for TrueBeam LINAC. Although we have not demonstrated this technique of QA for other medical LINAC, it is felt that this QA method may be applied to other medical LINACS as well with little modification. The medical LINAC of Elekta operates in the step and shoot mode, and hence, the issue of leaf speed and synchronization of log record and EPID images does not arise because each segment corresponds to easily recognized EPID image.
All the selected IMRT cases were passed the conventional pretreatment dosimetry QA. The passing criteria were 3% dose difference and 3 mm distance to agreement.
The measurement-based patient-specific IMRT QA is being debated and log file analysis based IMRT QA is thought to be more accurate and considerably less time-consuming to perform. The log file analysis method of IMRT QA is software based rather than hardware. Measurement-based patient-specific IMRT QA is both time-consuming and potentially inaccurate since the measurements are made in phantoms rather than actual patients. Neal et al. have been clinically observed that log file-derived LPs can differ from their actual position by >1 mm and therefore cannot be considered to be the actual LPs. This cautions the use of log-based methods for MLC or patient QA without independent confirmation of log integrity. Frequent verification of MLC positions through independent means is a necessary precondition to trust log file records. Agnew et al. have also demonstrated that trajectory log files may not detect errors in MLC position due to t-nut or motor faults. Independent means of support must be in place.
The QA methodology demonstrated in this work can be used for establishing the accuracy of trajectory log data where trajectory log files are used as QA tool for IMRT verification as well as for independent routine IMRT QA by generating single number like gamma index to indicate pass or fail of an IMRT treatment plan. Error of 2 mm in LP during dynamic treatment may be acceptable. The QA indices such as numbers of occurrences of ≥2 mm error in LPs are found more than 5% of total number of occurrences; the dosimetric review of planned treatment is advisable and needs to be introduced in routine practice.
| > Conclusions|| |
The positions of MLC leaves recorded in the log files were imaged through the EPID to investigate the authenticity of data recorded in the log files for stationary, moving, and IMRT treatment portals. The results of the study indicated that MLC positions indicated in the log files are comparable to MLC positions recorded by EPID within 2 mm. Thus, this study establishes that comparing the log files with EPID images is a quick, efficient, and effective patient-specific IMRT QA tool. This QA methodology can also be utilized for routine real-time QA of IMRT delivery.
Financial support and sponsorship
This study was partially supported by the International Atomic Energy Agency (IAEA).
Conflicts of interest
There are no conflicts of interest.
| > References|| |
Taylor A, Powell ME. Intensity-modulated radiotherapy - What is it? Cancer Imaging 2004;4:68-73.
Molineu A, Followill DS, Balter PA, Hanson WF, Gillin MT, Huq MS, et al
. Design and implementation of an anthropomorphic quality assurance phantom for intensity-modulated radiation therapy for the Radiation Therapy Oncology Group. Int J Radiat Oncol Biol Phys 2005;63:577-83.
Ibbott GS, Molineu A, Followill DS. Independent evaluations of IMRT through the use of an anthropomorphic phantom. Technol Cancer Res Treat 2006;5:481-7.
Palta JR, Kim S, Li JG, Liu C. Tolerance limits and action levels for planning and delivery of IMRT. In: Intensity-Modulated Radiation Therapy: The State of The Art: American Association of Physicists in Medicine Medical Physics Monograph No. 29. Madison, WI, USA: Medical Physics Publishing; 2003. p. 593-612.
McDermott LN, Wendling M, Sonke JJ, van Herk M, Mijnheer BJ. Replacing pretreatment verification with in vivo
EPID dosimetry for prostate IMRT. Int J Radiat Oncol Biol Phys 2007;67:1568-77.
Stock M, Kroupa B, Georg D. Interpretation and evaluation of the gamma index and the gamma index angle for the verification of IMRT hybrid plans. Phys Med Biol 2005;50:399-411.
Ezzell GA. Quality assurance. When and what is enough for IMRT? In: Intensity-Modulated Radiation Therapy: The State of the Art: American Association of Physicists in Medicine Medical Physics Monograph No. 29. Madison, WI, USA: Medical Physics Publishing; 2003. p. 613-6.
Escude L, Linero D, Molla M, Maralbell R. Quality assurance for radiotherapy in prostate cancer: Point dose measurements in intensity modulated fields with large dose gradients. Int J Radiat Oncol Biol Phys 2006;66:S136-40.
Alber M, Broggi S, De Wagter C, Eichwurzel I, Engstrom P, Fiorino C, et al
. Guidelines for the Verification of IMRT. ESTRO Booklet No. 9. ESTRO Mounierlaan 83/12 – 1200 Brussels (Belgium); 2008.
Ezzell GA, Galvin JM, Low D, Palta JR, Rosen I, Sharpe MB, et al
. Guidance document on delivery, treatment planning, and clinical implementation of IMRT: Report of the IMRT subcommittee of the AAPM Radiation Therapy Committee. Med Phys 2003;30:2089-115.
Galvin JM, Ezzell G, Eisbruch A, Yu C, Butler B, Xiao Y, et al
. Implementing IMRT in clinical practice: A joint 113 document of the American Society for Therapeutic Radiology and Oncology and the American Association of Physicists in Medicine. Int J Radiat Oncol Biol Phys 2004;58:1616-34.
Litzenberg DW, Moran JM, Fraass BA. Verification of dynamic and segmental IMRT delivery by dynamic log file analysis. J Appl Clin Med Phys 2002;3:63-72.
Ramsey CR, Spencer KM, Alhakeem R, Oliver AL. Leaf position error during conformal dynamic arc and intensity modulated arc treatments. Med Phys 2001;28:67-72.
Dinesh Kumar M, Thirumavalavan N, Venugopal Krishna D, Babaiah M. QA of intensity-modulated beams using dynamic MLC log files. J Med Phys 2006;31:36-41.
Technical Specification of TrueBeam Trajectory Log File. Varian Medical Systems; 2011.
Siochi RA, Molineu A, Orton CG. Point/Counterpoint. Patient-specific QA for IMRT should be performed using software rather than hardware methods. Med Phys 2013;40:070601.
Neal B, Ahmed M, Kathuria K, Watkins T, Wijesooriya K, Siebers J. A clinically observed discrepancy between image-based and log-based MLC positions. Med Phys 2016;43:2933.
Agnew A, Agnew CE, Grattan MW, Hounsell AR, McGarry CK. Monitoring daily MLC positional errors using trajectory log files and EPID measurements for IMRT and VMAT deliveries. Phys Med Biol 2014;59:N49-63.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
|This article has been cited by|
||Insensitivity of machine log files to MLC leaf backlash and effect of MLC backlash on clinical dynamic MLC motion: An experimental investigation
| ||Michael Barnes, Dennis Pomare, Marcus Doebrich, Therese S. Standen, Joshua Wolf, Peter Greer, John Simpson |
| ||Journal of Applied Clinical Medical Physics. 2022; |
|[Pubmed] | [DOI]|
||Serum cholinesterase may independently predict prognosis in non-small-cell lung cancer
| ||Hailiang Ran, Jie Ma, Le Cai, Hai Zhou, Zhongqin Yuan, Ying Chen, Wei Chang, Yunchao Huang, Yuanyuan Xiao |
| ||BMC Cancer. 2022; 22(1) |
|[Pubmed] | [DOI]|
||The Unmet Needs in the Management of Vulvar Cancer and a Review of Indian Literature
| ||Satinder Kaur, Hemlata Garg, Megha Nandwani |
| ||JCO Global Oncology. 2022; (8) |
|[Pubmed] | [DOI]|
||Sensitivity evaluation of two commercial quality assurance systems to organ-dose variations of patient-specific VMAT plans
| ||Oluwaseyi M. Oderinde, Freek Du Plessis |
| ||Journal of Radiation Research and Applied Sciences. 2019; 12(1): 132 |
|[Pubmed] | [DOI]|