Feasibility study on the verification of actual beam delivery in a treatment room using EPID transit dosimetry
© Baek et al.; licensee BioMed Central Ltd. 2014
Received: 7 July 2014
Accepted: 24 September 2014
Published: 4 December 2014
The aim of this study is to evaluate the ability of transit dosimetry using commercial treatment planning system (TPS) and an electronic portal imaging device (EPID) with simple calibration method to verify the beam delivery based on detection of large errors in treatment room.
Methods and materials
Twenty four fields of intensity modulated radiotherapy (IMRT) plans were selected from four lung cancer patients and used in the irradiation of an anthropomorphic phantom. The proposed method was evaluated by comparing the calculated dose map from TPS and EPID measurement on the same plane using a gamma index method with a 3% dose and 3 mm distance-to-dose agreement tolerance limit.
In a simulation using a homogeneous plastic water phantom, performed to verify the effectiveness of the proposed method, the average passing rate of the transit dose based on gamma index was high enough, averaging 94.2% when there was no error during beam delivery. The passing rate of the transit dose for 24 IMRT fields was lower with the anthropomorphic phantom, averaging 86.8% ± 3.8%, a reduction partially due to the inaccuracy of TPS calculations for inhomogeneity. Compared with the TPS, the absolute value of the transit dose at the beam center differed by −0.38% ± 2.1%. The simulation study indicated that the passing rate of the gamma index was significantly reduced, to less than 40%, when a wrong field was erroneously irradiated to patient in the treatment room.
This feasibility study suggested that transit dosimetry based on the calculation with commercial TPS and EPID measurement with simple calibration can provide information about large errors for treatment beam delivery.
KeywordsTransit dose EPID Intensity modulated radiation therapy Gamma index
The goal of radiotherapy is to deliver a therapeutic dose to a tumor volume while minimizing doses to surrounding organs -. Efforts to achieve this goal have led to increasingly complex radiation delivery and dose calculation algorithms. In addition, more advanced treatment techniques, including intensity-modulated radiotherapy (IMRT), helical tomotherapy (TOMO), volumetric modulated arc therapy (VMAT) and heavy ion therapy, have been developed to overcome the disadvantages of conventional three-dimensional conformal radiotherapy (3D-CRT). Although highly technological treatment methods are important to achieve the goal of radiotherapy, these methods can be useless or even harmful to patients if the therapeutic dose is not accurately delivered as planned. For example, an IMRT planning error in New York in 2005 caused a fatal radiation overdose resulting in the death of the patient . This accident suggests that accurate verification of the dose delivered to the patient is essential for maximum treatment efficacy and to prevent accidental overdoses.
Accidental exposure during radiotherapy may be avoided by learning from previous accidents -. Most of these accidents were due to human errors, including mistakes, procedural violations and inadequate procedures, all of which should be expected. These kinds of errors may be prevented by the application of several types of preventive actions during radiation treatment. One of the most important is patient-specific quality assurance (QA), which is generally performed to assure that there is no difference between the dose calculated by the TPS and the actual measured dose. Conventional patient-specific QA for IMRT involves measuring the absolute dose as well as measuring the two-dimensional dose distribution using a homogeneous phantom. EPID based portal dosimetry has recently become popular for patient-specific IMRT dose verification in radiotherapy, although EPID is the primary tool used to verify patient positioning in the treatment room ,.
Good agreement based on conventional QA, however, does not guarantee the accuracy of the actual dose distribution to the patient in the treatment room. In general, unexpected errors during beam delivery are difficult to detect by conventional QA, since the latter is basically pretreatment verification. A possible approach to detect errors during treatment is a transit dosimetry acquired using EPID in the treatment room. So far, various studies have been carried out for the transit dosimetry at the position of the EPID behind a patient -. Among them the use of the TPS can be considered as one of the simple ways to conduct the 2D transit dosimetry since the transit dose is easily calculated by commercial software. McNutt et al. used the convolution/superposition method to predict the dose at the level of imaging device and found that the calculated doses at the EPID level were within 4% of the measured doses in the central region of the field . More recently, Reich et al. investigated the calculation of transit dose maps using commercial TPS (Pinnacle Version 6.2b, Phillips Medical System, Milpitas, USA) and reported that the calculated transit dose maps agrees well with the measured dose maps showing less than 2% of dose difference on the central beam axis .
Although the previous studies showed that 2D transit dosimetry based on TPS calculation and EPID measurement is simple and advantageous, more studies are needed for this method due to several reasons. First, the accurate calibration of EPID for various factors is still too complex to be adapted easily in clinic. Second, as time goes on, various TPSs are available and the algorithm of TPS becomes more accurate. Therefore, it is meaningful to test the recent TPS for the use of transit dosimetry. Third, only limited clinical cases were examined in previous studies suggesting the need of more research for the use of TPS in 2D transit dosimetry. In this study, we used EPID to measure the transit dose passing through an anthropomorphic phantom in the treatment room based on simple calibration method and evaluated the ability of transit dosimetry using commercial TPS to verify the beam delivery during treatment in radiotherapy.
Methods and materials
Patient characteristics, prescribed radiation dose and fraction size
Number of fields
Number of fractions
Prescribed dose (cGy)
The transit dose maps passing through the phantoms were calculated by Eclipse TPS. To do that, we first built the artificial phantom (see arrows in Figure 1(c), (d)) at the location of EPID from TPS and ran the calculation to get the dose map in the EPID plane. In the treatment room, the radiation fields of the IMRT QA plans were delivered using a Varian Clinac iX linear accelerator (Varian Medical Systems, Palo Alto, CA) equipped with an aS1000 EPID. The EPID system is an amorphous silicon flat panel imager, with an active imaging area of 30 × 40 cm2 with a matrix size of 1024 × 768 pixels.
where, and are the position vectors of the pixel in the reference image and the evaluation image, respectively; represents the distance between the positions; and denotes the difference in dose at each position .
Gamma index (3%/3 mm)-based passing rates for transit dose measured with an homogeneous phantom
Patient 1 (%)
Patient 2 (%)
Patient 3 (%)
Patient 4 (%)
92.6 (8.6 × 7 cm2)
96.6 (6.8 × 4.5 cm2)
92.0 (8.6 × 6.1 cm2)
95.6 (6.6 × 5 cm2)
92.7 (8.3 × 7 cm2)
95.5 (6.3 × 4.8 cm2)
95.0 (7.8 × 6.3 cm2)
95.1 (6.3 × 5 cm2)
90.8 (8.7 × 7 cm2)
95.7 (6.6 × 4.8 cm2)
96.5 (6.6 × 6.3 cm2)
95.6 (5.6 × 5 cm2)
91.3 (9.3 × 7 cm2)
95.3 (6.6 × 4.8 cm2)
93.6 (6.5 × 6.3 cm2)
95.3 (5.9 × 5 cm2)
92.7 (8.6 × 7 cm2)
95.4 (7.1 × 4.8 cm2)
93.1 (8.3 × 6.1 cm2)
95.4 (6.6 × 5 cm2)
91.9 (8.6 × 7 cm2)
97.4 (6.3 × 4.8 cm2)
90.1 (8.3 × 6.1 cm2)
95.8 (5.8 × 5 cm2)
Comparison of absolute and relative transit doses measured with EPID and the lung region of an anthropomorphic phantom
Comparison of relative transit doses measured with EPID and the pelvic region of an anthropomorphic phantom
Passing rate (%) of patient 1
Passing rate (%) of patient 2
We have measured the transit doses of 24 IMRT fields with EPID and compared them with the doses calculated from the TPS. Comparisons of absolute doses with the anthropomorphic phantom showed good agreement between measured and calculated doses at the beam center. Although the relative doses of the measured and calculated transit beams passing through a homogeneous phantom were well matched, the average passing rate was reduced to 86.8% when using an inhomogeneous anthropomorphic phantom.
In general, the EPID response is a function of various factors such as field size, phantom thickness, lateral scatter in the EPID, phantom-to-EPID scatter and the measured dose will generally have relatively large uncertainties if one omits corrections for all these effects. The dependence of EPID response on various factors and corresponding calibration method were studied previously and discussed extensively by Nijsten et al. . Although many research groups have reported and suggested the calibration methods of EPID for various factors, it is still too complex to apply this method clinically and need more simple way to do it. Our experimental results suggest that, based on the TPS and EPID measurement with simple calibration, we can monitor (or verify) whether the desired beam (or dose fluence) was delivered to the patient without large error during treatment. If one is interested in detection for this kind of large error, rough calibration of EPID seems to work well.
Gamma index (3%/3 mm)-based passing rates for transit dose measured with EPID and an anthropomorphic phantom following selection of the wrong fields instead of field 1 of patient 2
Patient 1 (%)
Patient 2 (%)
Patient 3 (%)
Patient 4 (%)
We have compared EPID measurements of transit dose for 24 IMRT fields with doses calculated from TPS. Our feasibility study suggests that EPID based transit dose monitoring in the treatment room can provide information about the accuracy of beam delivery.
This work was supported by the National Nuclear R&D Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education, Science and Technology (NRF-2013M2A2A7067089).
- Langer M, Brown R, Urie M, Leong J, Stracher M, Shapiro J: Large scale optimization of beam weights under dose-volume restrictions. Int J Radiat Oncol Biol Phys 1990, 18: 887-893. 10.1016/0360-3016(90)90413-EView ArticlePubMedGoogle Scholar
- Langer M, Leong J: Optimization of beam weights under dose-volume restrictions. Int J Radiat Oncol Biol Phys 1987, 13: 1255-1260. 10.1016/0360-3016(87)90203-3View ArticlePubMedGoogle Scholar
- Morrill SM, Lane RG, Wong JA, Rosen II: Dose‐volume considerations with linear programming optimization. Med Phys 1991, 18: 1201-1210. 10.1118/1.596592View ArticleGoogle Scholar
- ORH information notice 2005-01; 005. [http://www.health.ny.gov/environmental/radiological/radon/radioactive_material_licensing/docs/berp2005_1.pdf] ORH information notice 2005-01; 005. 
- Williams M: Radiotherapy near misses, incidents and errors: radiotherapy incident at Glasgow. Clin Oncol 2007, 19: 1-3. 10.1016/j.clon.2006.12.004View ArticleGoogle Scholar
- Commission USNR: Gamma knife treatment to wrong side of brain. Event Notification Report 2007, 43746.Google Scholar
- Ash D: Lessons from epinal. Clin Oncol 2007, 19: 614-615. 10.1016/j.clon.2007.06.011View ArticleGoogle Scholar
- Van Esch A, Depuydt T, Huyskens DP: The use of an aSi-based EPID for routine absolute dosimetric pre-treatment verification of dynamic IMRT fields. Radiother Oncol 2004, 71: 223-234. 10.1016/j.radonc.2004.02.018View ArticlePubMedGoogle Scholar
- Van Esch A, Vanstraelen B, Verstraete J, Kutcher G, Huyskens D: Pre-treatment dosimetric verification by means of a liquid-filled electronic portal imaging device during dynamic delivery of intensity modulated treatment fields. Radiother Oncol 2001, 60: 181-190. 10.1016/S0167-8140(01)00305-XView ArticlePubMedGoogle Scholar
- Essers M, Boellaard R, van Herk M, Lanson H, Mijnheer B: Transmission dosimetry with a liquid-filled electronic portal imaging device. Int J Radiat Oncol Biol Phys 1996, 34: 931-941. 10.1016/0360-3016(95)02191-4View ArticlePubMedGoogle Scholar
- Reich P, Bezak E, Mohammadi M, Fog L: The prediction of transmitted dose distributions using a 3D treatment planning system. Australas Phys Eng Sci Med 2006, 29: 18-29. 10.1007/BF03178824View ArticlePubMedGoogle Scholar
- Mohammadi M, Bezak E: Two-dimensional transmitted dose measurements using a scanning liquid ionization chamber EPID. Phys Med Biol 2006, 51: 2971-2985. 10.1088/0031-9155/51/11/019View ArticlePubMedGoogle Scholar
- McNutt TR, Mackie TR, Reckwerdt P, Papanikolaou N, Paliwal BR: Calculation of portal dose using the convolution/superposition method. Med Phys 1996, 23: 527-535. 10.1118/1.597810View ArticlePubMedGoogle Scholar
- Mohammadi M, Bezak E, Reich P: Comparison of two-dimensional transmitted dose maps: evaluation of existing algorithms. Australas Phys Eng Sci Med 2006, 29: 179-187. 10.1007/BF03178891View ArticlePubMedGoogle Scholar
- van Elmpt W, McDermott L, Nijsten S, Wendling M, Lambin P, Mijnheer B: A literature review of electronic portal imaging for radiotherapy dosimetry. Radiother Oncol 2008, 88: 289-309. 10.1016/j.radonc.2008.07.008View ArticlePubMedGoogle Scholar
- Rowshanfarzad P, McCurdy BM, Sabet M, Lee C, O’Connor DJ, Greer PB: Measurement and modeling of the effect of support arm backscatter on dosimetry with a Varian EPID. Med Phys 2010, 37: 2269-2278. 10.1118/1.3369445View ArticlePubMedGoogle Scholar
- Vinall A, Williams A, Currie V, Van Esch A, Huyskens D: Practical guidelines for routine intensity-modulated radiotherapy verification: pre-treatment verification with portal dosimetry and treatment verification with in vivo dosimetry. Br J Radiol 2010, 83: 949-957. 10.1259/bjr/31573847PubMed CentralView ArticlePubMedGoogle Scholar
- Low DA, Harms WB, Mutic S, Purdy JA: A technique for the quantitative evaluation of dose distributions. Med Phys 1998, 25: 656-661. 10.1118/1.598248View ArticlePubMedGoogle Scholar
- Nijsten S, Van Elmpt W, Jacobs M, Mijnheer B, Dekker A, Lambin P, Minken A: A global calibration model for a‐Si EPIDs used for transit dosimetry. Med Phys 2007, 34: 3872-3884. 10.1118/1.2776244View ArticlePubMedGoogle Scholar
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