Skip to main content
banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
1.G. A. Ezzell, J. M. Galvin, D. Low, J. R. Palta, I. Rosen, M. B. Sharpe, P. Xia, Y. Xiao, L. Xing, and C. X. Yu, “Guidance document on delivery, treatment planning, and clinical implementation of IMRT: Report of the IMRT Subcommittee of the AAPM Radiation Therapy Committee,” Med. Phys. 30, 20892115 (2003).
2.A. Mans, M. Wendling, L. N. McDermott, J. J. Sonke, R. Tielenburg, R. Vijlbrief, B. Mijnheer, M. van Herk, and J. C. Stroom, “Catching errors with in vivo EPID dosimetry,” Med. Phys. 37, 26382644 (2010).
3.G. J. Kutcher et al., “Comprehensive QA for radiation oncology: Report of AAPM Radiation Therapy Committee Task Group 40,” Med. Phys. 21, 581618 (1994).
4.International Atomic Energy Agency, International Basic Safety Standards for Protection Against Ionizing Radiation and for the Safety of Radiation Sources (IAEA, Vienna, Austria, 2014).
5.J. Van Dam and G. Marinello, “Methods for in vivo dosimetry in external radiotherapy,” in Physics for Clinical Radiotherapy, ESTRO Booklet No. 1 (ESTRO, Brussels, Belgium, 1994).
6.International Atomic Energy Agency, “Development of procedures for in vivo dosimetry in radiotherapy,” IAEA Human Health Report No. 8, 2013.
7.Report of Task Group 62 of the Radiation Therapy Committee, “Diode in vivo dosimetry for patients receiving external beam radiation therapy,” AAPM Report No. 87, 2005.
8.W. van Elmpt, L. McDermott, S. Nijsten, M. Wendling, P. Lambin, and B. Mijnheer, “A literature review of electronic portal imaging for radiotherapy dosimetry,” Radiother. Oncol. 88, 289309 (2008).
9.M. Hussein, P. Rowshanfarzad, M. A. Ebert, A. Nisbet, and C. H. Clark, “A comparison of the gamma index analysis in various commercial IMRT/VMAT QA systems,” Radiother. Oncol. 109, 370376 (2013).
10.P. Rowshanfarzad, M. Sabet, M. P. Barnes, D. J. O’Connor, and P. B. Greer, “EPID-based verification of the MLC performance for dynamic IMRT and VMAT,” Med. Phys. 39, 61926207 (2012).
11.J. J. Gordon, J. K. Gardner, S. Wang, and J. V. Siebers, “Reliable detection of fluence anomalies in EPID-based IMRT pretreatment quality assurance using pixel intensity deviations,” Med. Phys. 39, 49594975 (2012).
12.J. J. Kruse, “On the insensitivity of single field planar dosimetry to IMRT inaccuracies,” Med. Phys. 37, 25162524 (2010).
13.Y. L. Kim, J. B. Chung, J. S. Kim, J. W. Lee, and K. S. Choi, “Comparison of the performance between portal dosimetry and a commercial two-dimensional array system on pretreatment quality assurance for volumetric-modulated arc and intensity-modulated radiation therapy,” J. Korean Phys. Soc. 64, 12071212 (2014).
14.A. Rangel, G. Palte, and P. Dunscombe, “The sensitivity of patient specific IMRT QC to systematic MLC leaf bank offset errors,” Med. Phys. 37, 38623867 (2010).
15.L. N. McDermott, M. Wendling, J. J. Sonke, M. van Herk, and B. J. Mijnheer, “Replacing pretreatment verification with in vivo EPID dosimetry for prostate IMRT,” Int. J. Radiat. Oncol., Biol., Phys. 67, 15681577 (2007).
16.L. N. McDermott, M. Wendling, B. van Asselen, J. Stroom, J. J. Sonke, M. van Herk, and B. J. Mijnheer, “Clinical experience with EPID dosimetry for prostate IMRT pre-treatment dose verification,” Med. Phys. 33, 39213930 (2006).
17.M. Wendling, R. J. Louwe, L. N. McDermott, J. J. Sonke, M. van Herk, and B. J. Mijnheer, “Accurate two-dimensional IMRT verification using a back-projection EPID dosimetry method,” Med. Phys. 33, 259273 (2006).
18.M. Wendling, L. N. McDermott, A. Mans, I. Olaciregui-Ruiz, R. Pecharroman-Gallego, J. J. Sonke, J. Stroom, M. van Herk, and B. J. Mijnheer, “In aqua vivo EPID dosimetry,” Med. Phys. 39, 367377 (2012).
19.L. C. Persoon, S. M. Nijsten, F. J. Wilbrink, M. Podesta, J. A. Snaith, T. Lustberg, W. J. van Elmpt, F. van Gils, and F. Verhaegen, “Interfractional trend analysis of dose differences based on 2D transit portal dosimetry,” Phys. Med. Biol. 57, 64456458 (2012).
20.L. C. Persoon, A. G. Egelmeer, M. C. Ollers, S. M. Nijsten, E. G. Troost, and F. Verhaegen, “First clinical results of adaptive radiotherapy based on 3D portal dosimetry for lung cancer patients with atelectasis treated with volumetric-modulated arc therapy (VMAT),” Acta Oncol. 52, 14841489 (2013).
21.I. Olaciregui-Ruiz, R. Rozendaal, B. Mijnheer, M. van Herk, and A. Mans, “Automatic in vivo portal dosimetry of all treatments,” Phys. Med. Biol. 58, 82538264 (2013).
22.E. C. Ford, S. Terezakis, A. Souranis, K. Harris, H. Gay, and S. Mutic, “Quality control quantification (QCQ): A tool to measure the value of quality control checks in radiation oncology,” Int. J. Radiat. Oncol., Biol., Phys. 84, e263e269 (2012).
23.C. Bojechko, A. Kalet, M. H. Phillps, and E. C. Ford, “A quantification of the effectiveness of EPID dosimetry and software-based plan verification systems in detecting incidents in radiotherapy,” Med. Phys. 42, 53635369 (2015).
24.M. Carlone, C. Cruje, A. Rangel, R. McCabe, M. Nielsen, and M. Macpherson, “ROC analysis in patient specific quality assurance,” Med. Phys. 40, 042103 (7pp.) (2013).
25.P. Munro and D. C. Bouius, “X-ray quantum limited portal imaging using amorphous silicon flat-panel arrays,” Med. Phys. 25, 689702 (1998).
26.Y. El-Mohri, L. E. Antonuk, J. Yorkston, K. W. Jee, M. Maolinbay, K. L. Lam, and J. H. Siewerdsen, “Relative dosimetry using active matrix flat-panel imager (AMFPI) technology,” Med. Phys. 26, 15301541 (1999).
27.B. M. C. McCurdy, K. B. Luchka, and S. Pistorius, “Dosimetric investigation and portal dose image prediction using an amorphous silicon electronic portal imaging device,” Med. Phys. 28, 911924 (2001).
28.L. N. McDermott, R. J. Louwe, J. J. Sonke, M. B. van Herk, and B. J. Mijnheer, “Dose–response and ghosting effects of an amorphous silicon electronic portal imaging device,” Med. Phys. 31, 285295 (2004).
29.M. Wendling, L. N. McDermott, A. Mans, J. J. Sonke, M. van Herk, and B. J. Mijnheer, “A simple backprojection algorithm for 3D in vivo EPID dosimetry of IMRT treatments,” Med. Phys. 36, 33103321 (2009).
30.D. A. Low, W. B. Harms, S. Mutic, and J. A. Purdy, “A technique for the quantitative evaluation of dose distributions,” Med. Phys. 25, 656661 (1998).
31.K. Pulliam, J. Kerns, R. M. Howell, D. S. Followill, J. O’Daniel, and S. F. Kry, “A survey of IMRT QA practices for more than 800 institutions,” Med. Phys. 41, 432 (2014).
32.E. M. McKenzie, P. A. Balter, F. C. Stingo, J. Jones, D. S. Followill, and S. F. Kry, “Toward optimizing patient-specific IMRT QA techniques in the accurate detection of dosimetrically acceptable and unacceptable patient plans,” Med. Phys. 41, 121702 (15pp.) (2014).
33.N. A. Obuchowski, “ROC analysis,” AJR, Am. J. Roentgenol. 184, 364372 (2005).
34.S. Dische, M. I. Saunders, C. Williams, A. Hopkins, and E. Aird, “Precision in reporting the dose given in a course of radiotherapy,” Radiother. Oncol. 29, 287293 (1993).
35.J. L. Bedford, I. M. Hanson, and V. N. Hansen, “Portal dosimetry for VMAT using integrated images obtained during treatment,” Med. Phys. 41, 021725 (14pp.) (2014).
36.B. E. Nelms, H. Zhen, and W. A. Tome, “Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors,” Med. Phys. 38, 10371044 (2011).

Data & Media loading...


Article metrics loading...



To quantify the ability of electronic portal imaging device(EPID)dosimetry used during treatment () in detecting variations that can occur in the course of patient treatment.

Images of transmitted radiation from EPID measurements were converted to a 2D planar dose at isocenter and compared to the treatment planningdose using a prototype software system. Using the treatment planning system (TPS), four different types of variability were modeled: overall dose scaling, shifting the positions of the multileaf collimator(MLC) leaves, shifting of the patient position, and changes in the patient body contour. The gamma pass rate was calculated for the modified and unmodified plans and used to construct a receiver operator characteristic (ROC) curve to assess the detectability of the different parameter variations. The detectability is given by the area under the ROC curve (AUC). The TPS was also used to calculate the impact of the variations on the target dose–volume histogram.

Nine intensity modulation radiation therapy plans were measured for four different anatomical sites consisting of 70 separate fields. Results show that EPIDdosimetry was most sensitive to variations in the machine output, AUC = 0.70 − 0.94, changes in patient body habitus, AUC = 0.67 − 0.88, and systematic shifts in the MLC bank positions, AUC = 0.59 − 0.82. These deviations are expected to have a relatively small clinical impact [planning target volume (PTV) change <7%]. Larger variations have even higher detectability. Displacements in the patient’s position and random variations in MLC leaf positions were not readily detectable, AUC < 0.64. The of the PTV changed by up to 57% for the patient position shifts considered here.

EPIDdosimetry is able to detect relatively small variations in overall dose, systematic shifts of the MLC’s, and changes in the patient habitus. Shifts in the patient’s position which can introduce large changes in the target dose coverage were not readily detected.


Full text loading...


Access Key

  • FFree Content
  • OAOpen Access Content
  • SSubscribed Content
  • TFree Trial Content
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd