|Year : 2019 | Volume
| Issue : 4 | Page : 173-179
Dosimetric validation of Acuros XB photon dose calculation algorithm on an indigenously fabricated low-density heterogeneous phantom
Lalit Kumar1, Girigesh Yadav2, Vimal Kishore3, Manindra Bhushan2
1 Department of Applied Science and Humanities, Dr. A.P.J Abdul Kalam Technical University, Lucknow, Uttar Pradesh; Department of Radiation Oncology, Division of Medical Physics, Rajiv Gandhi Cancer Institute and Research Centre, New Delhi, India
2 Department of Radiation Oncology, Division of Medical Physics, Rajiv Gandhi Cancer Institute and Research Centre, New Delhi, India
3 Department of Applied Science and Humanities, Bundelkhand Institute of Engineering and Technology, Jhansi, Uttar Pradesh, India
|Date of Submission||16-May-2019|
|Date of Decision||13-Sep-2019|
|Date of Acceptance||22-Oct-2019|
|Date of Web Publication||27-Jan-2020|
Mr. Lalit Kumar
Department of Radiation Oncology, Medical Physics Division, Rajiv Gandhi Cancer Institute & Research Centre, New Delhi
Source of Support: None, Conflict of Interest: None
The aim of this study was to validate Acuros XB (AXB) algorithm for photon dose calculation on an indigenously fabricated low-density heterogeneous phantom. Phantom was fabricated using poly (methyl methacrylate) (PMMA) and racemosa wood. The measured Hounsfield units, relative electron density, and mass density were 726.5, 0.273, and 0.212 g/cc and 201.8, 1.201, and 1.175 g/cc for racemosa and PMMA, respectively. AXB results were compared against anisotropic analytical algorithm (AAA) and ion chamber (IC) measured data for 3 cm × 3 cm and 10 cm × 10 cm field size of 6 megavolts beam. AXB results were in better agreement with IC measured data at all measuring points in comparison to AAA. The discrepancies between AXB and IC measured data were 1.3%–2.2% for 3 cm × 3 cm, −1.5%–−0.9% for 10 cm × 10 cm at low-density region, and −3.6%–−1.6% for 3 cm × 3 cm, and −1.4%–−0.8% for 10 cm × 10 cm at secondary buildup region, whereas discrepancies between AAA and measured data were 1.6%–3.6% for 3 cm × 3 cm, −4.6%–−3.4% for 10 cm × 10 cm at low-density region, and within −5.3%–−2.1% for 3 cm × 3 cm and −1.5%–1.0% for 10 cm × 10 cm at the secondary build-up region. Therefore, AXB is more appropriate in dealing with low-density heterogeneity in comparison to AAA.
Keywords: Acuros XB, anisotropic analytical algorithm, poly (methyl methacrylate), racemosa
|How to cite this article:|
Kumar L, Yadav G, Kishore V, Bhushan M. Dosimetric validation of Acuros XB photon dose calculation algorithm on an indigenously fabricated low-density heterogeneous phantom. Radiat Prot Environ 2019;42:173-9
|How to cite this URL:|
Kumar L, Yadav G, Kishore V, Bhushan M. Dosimetric validation of Acuros XB photon dose calculation algorithm on an indigenously fabricated low-density heterogeneous phantom. Radiat Prot Environ [serial online] 2019 [cited 2020 Feb 20];42:173-9. Available from: http://www.rpe.org.in/text.asp?2019/42/4/173/276917
| Introduction|| |
In modern times, radiation is delivered to the tumor using either intensity-modulated radiotherapy in static mode or in rotational mode using volumetric modulated arc therapy dose delivery technique. These developments in radiotherapy delivery techniques facilitate dose escalation to the tumor with effective sparing of the nearby critical organs. Accurate dose calculation and precise treatment delivery become all the more indispensable with current treatment demands. The complex photon fluence modulation of a radiation beam used in these techniques calls for more sophisticated dose calculation algorithms. One important aspect in dose calculation is to accurately deal with the complex heterogeneous medium encountered by radiation beam. Several publications had reported the limitation of dose calculation algorithms in heterogeneous medium.,, Therefore, it is of paramount importance to predict the dose accurately when calculating radiation dose in a heterogeneous patient medium, in order to maximize therapeutic benefits to cancer patients. There can be 10%–20% change in local tumor control probability and up to 30% change reported in normal tissue complication probability for a change of 5% in local tumor dose. The International Commission on Radiation Units and Measurements also stated that the major causes of radiation therapy treatment failure are associated with geographical target miss due to inaccurate target delineation and dosimetric variation of more than 3%. For an early stage tumor, it has been reported that 1% improvement in overall accuracy of beam delivery will result in an increased cure rate of 2%. Therefore, it is highly desirable to verify dose calculation in a medium which can closely mimic the heterogeneity of human body such as in thoracic region, where the difference between planned and actual dose delivered may alter the clinical outcome significantly due to clinically significant beam profile degradation. This may occur due to increased range of secondary electron (penumbra broadening) and lack of electronic charged particle equilibrium in lung region., Precise confirmation of accuracy in dose calculation is an important aspect of quality assurance (QA) procedure in radiotherapy. Slab phantom of uniform density (water equivalent, i.e., 1 g/cc) is used for patient-specific QA in most of the radiotherapy departments. Owing to known effect of tissue heterogeneity on dose distribution pattern and dose calculation, there is a need to fabricate a cost-effective, low-density heterogeneous phantom for dose verification keeping in mind those radiotherapy facilities across the globe which run tight on budget. This can truly evaluate the accuracy of dose calculation engine in low-density heterogeneous medium.
The aim of the present study is to fabricate a cost-effective, low-density heterogeneous QA phantom using the combination of poly (methyl methacrylate) (PMMA) and racemosa wood. This study aims to evaluate the radiological properties of racemosa wood for simulating the human lung. Racemosa wood was examined for photon transmission using 6 megavolts (MV) photon beam. The Hounsfield units (HU), relative electron density, and mass density were also studied for racemosa wood. This study also aims to validate the Acuros XB (AXB) dose calculation algorithm in low-density heterogeneous medium of this fabricated phantom. This study evaluates and compares the AXB calculated central axis depth dose against the anisotropic analytical algorithm (AAA) calculated and IC measured doses in a fabricated, low-density heterogeneous phantom.
| Materials and Methods|| |
Phantom material and its radiological attributes
It is a common practice to use materials which have physical properties consonant with human body (tissue equivalent materials) for dose measurement and verification. The dosimetry protocol of Technical Report Series No. 398 of the International Atomic Energy Agency recommends the use of water as the phantom material for radiotherapy dose measurement as human body is nearly made of 65% of water. The solid tissue substitute used to simulate the human body had a similar set of physical characteristics such as photon transmission and mass density.
In the present study, a cost-effective, low-density phantom using combination of racemosa wood and PMMA was developed, which can simulate the thoracic region in the human body. Adequacies of racemosa and PMMA for phantom material were assessed by experimentally measuring the photon transmission, relative electron density, and HU numbers. The following equations were used for deriving the radiological properties of the phantom:
For a monoenergetic photon beam of intensity (I0), the transmitted intensity (I) through a material of thickness t is given by,
Where, μeff is the linear effective attenuation coefficient of the attenuating material, which is a function of the incident photon energy and nature of material. Although X-rays are not discrete energy beam, 6 MV photon beam used under this study may be treated as monoenergetic and intensity variation of these X-rays may behave according to Eq.(1)., The schematic experimental setup for the measurement of transmitted intensity of X-ray photon is shown in [Figure 1]. In air, the measurements were carried out at source-to-surface distance of 110 cm with collimator opening of 3 cm × 3 cm. Photon transmission was measured using a thimble ion chamber (IC) CC-13 S (IBA Dosimetry, Germany) having an effective volume of 0.13 cm3. For air measurements, a brass buildup cap was used on ionization chamber placed on the beam's central axis with different slab thicknesses of racemosa and PMMA. The mass density of phantom materials was also measured by determining the mass and volume of a small sample of these materials. The experimentally measured dosimetric parameters were validated against the data obtained from the computed tomography (CT) images of the materials.
|Figure 1: Schematic diagram of the experimental setup used for the measurement in air|
Click here to view
For derivation of HU numbers and relative electron density, the following equations were used:
Where, μx is the linear attenuation coefficient of material x and μw is the linear attenuation coefficient of water.
Phantom preparation and computed tomography scan
A cost-effective, low-density heterogeneous phantom of dimension 30 cm × 30 cm × 28 cm was fabricated using the combination of PMMA slabs and racemosa wood. This phantom consists of three layers: (1) first 5.0 cm of PMMA slab (each of 1 cm thickness), (2) mid 11.0 cm of racemosa slab (each of 2.2 cm thickness), and (3) last 12.0 cm of PMMA slab (each of 1 cm thickness). This fabricated phantom is shown in [Figure 2] and abbreviated as PMMA-racemosa-PMMA (PRP) phantom.
|Figure 2: Image of poly (methyl methacrylate)-racemosa-poly (methyl methacrylate) phantom (dimension 30 cm × 30 cm × 28 cm) along with ion chamber place at measurement point|
Click here to view
The PRP phantom was scanned on a Siemens SOMATOM Sensation 64-slice CT scanner (Siemens Medical System, Germany). The CT scan of 2 mm slice thickness was acquired using thorax protocol at tube voltage of 120 kVp with scan time of 24.5 s. All CT images were transferred to Eclipse (Varian Medical System, Palo Alto, USA) treatment planning system (TPS) in DICOM format.
Photon dose calculation engines
The Eclipse TPS system is equipped with two dose calculation engines: (1) AAA, version 11 and (2) AXB, version 11. The AXB can report dose in two different modes either dose-to-medium (Dm) or dose-to-water (Dw). The Dm was used for AXB dose reporting in this study. For AAA, dose is reported in Dw mode only as AAA dose calculations are based on the electron density scaled to water. On the contrary, AXB utilizes the macroscopic energy deposition cross-section and atomic density based on the material composition of local voxel for Dm mode. The grid resolution of 2.5 mm × 2.5 mm × 2.5 mm was used for photon dose calculations.
Central axis depth dose
On CT data of PRP phantom, the central axis depth dose was computed using AAA and AXB for 100 monitor units for field size 3 cm × 3 cm and 10 cm × 10 cm for photon beam of 6 MV energy. This photon beam was generated using Clinac-iX (2300CD) (Varian Medical System, Palo Alto, USA) linear accelerator equipped with a Millennium 120 multileaf collimator. Keeping identical field geometries and beam parameters, central axis dose was measured using a calibrated IC CC 13S (IBA Dosimetry, Germany) with Dose 1 (IBA Dosimetry, Germany) electrometer. The racemosa wood with mass density of 0.202 g/cc and PMMA with mass density of 1.124 g/cc were assigned as surrogates for lung tissue and mixed material of cartilage and bone.
The percentage difference between the calculated and measured dose, relative to measured dose, was determined using the following formula in PRP phantom.
| Results|| |
According to the data shown in [Figure 3], it is perceived that the graph between log I and t is a straight line for racemosa and PMMA, respectively. The photon beam maximum intensity (I0) and linear effective attenuation coefficient (μeff) have been estimated from intercept and slope obtained from linear fitting of log I versus t graph, respectively, and the values are listed in [Table 1]. Based on the value presented in [Table 1], it is observed that I0 and I′0 are comparable; therefore, assumptions of applicability of Eq. 1 for 6 MV photon beam are valid. The physical and measured radiological properties of racemosa and PMMA are listed in [Table 2], and these measured values are comparable to the values obtained from the CT images.
|Figure 3: Variation of transmitted intensity (i) with thickness (t) of attenuating material for field sizes 3 cm × 3 cm at 110 cm source-to-surface distance|
Click here to view
|Table 1: Variation of experimentally measured maximum intensity (Io), maximum intensity obtained from log I versus t graph (I'o), linear effective attenuation coefficient (μeff), and best fit parameter (R2) with field sizes of 3 cm × 3 cm for 110 cm source-to-surface distance|
Click here to view
|Table 2: Measured radiological properties against the values derived from the computed tomography scan images|
Click here to view
Central axis depth dose
AXB results were in better agreement with IC measured data at all measuring points in comparison to AAA. [Figure 4] and [Figure 5] show the central axis depth dose patterns using IC measurements, AAA and AXB-calculations for 3 cm × 3 cm and 10 cm × 10 cm field size, respectively for a 6 MV photon beam. [Table 3] shows the AAA and AXB calculated central axis depth dose against IC measured data in regard to 3 cm × 3 cm and 10 cm × 10 cm field sizes.
|Figure 4: Ion chamber measured dose on the central axis of 6 megavolts photon beam and dose calculated using anisotropic analytical algorithm and Acuros XB for 3 cm × 3 cm field size|
Click here to view
|Figure 5: Ion chamber measured dose on the central axis of 6 megavolts photon beam and dose calculated using anisotropic analytical algorithm and Acuros XB for 10 cm × 10 cm field size|
Click here to view
|Table 3: The anisotropic analytical algorithm and Acuros XB calculated depth dose on the central axis of the photon beam against ion chamber measured data for 3 cm×3 cm and 10 cm×10 cm field sizes|
Click here to view
In first 5 cm of PMMA region, for 3 cm × 3 cm field size, the calculated depth dose was in agreement with the measured depth dose ranging −2.1%–−1.2% and −0.5%–1.2% for AAA and AXB algorithms, respectively. Whereas, for the field size of 10 cm × 10 cm, the calculated depth dose was in agreement with the measured depth dose ranging −1.5%–−1.3% and −1.0%–−0.1% for AAA and AXB algorithms, respectively.
In low-density region (racemosa), for 3 cm × 3 cm field size, the calculated depth dose was in agreement with the measured depth dose ranging 1.6%–3.6% and 1.3%–2.2% for AAA and AXB algorithms, respectively, and for 10 cm × 10 cm field size, the calculated depth dose was in agreement with the measured depth dose ranging −4.6%–−3.4% and −1.5%–−0.9% for AAA and AXB algorithms, respectively.
Again, in PMMA (postracemosa) region, for 3 cm × 3 cm field size, the calculated depth dose was in agreement with the measured depth dose ranging −5.3%–−2.1% and −3.6%–−1.6% for AAA and AXB algorithms at distance depth from racemosa-PMMA interface, respectively, and for 10 cm × 10 cm field size, the calculated depth dose was in agreement with measured depth dose ranging −1.5%–1.0% and −1.4%–−0.8% for AAA and AXB algorithms at distance depth from racemosa-PMMA interface, respectively. Furthermore, the deviation between AAA calculated dose and measured dose was increasing with increase in depth from racemosa-PMMA interface for both field geometries. This trend was not observed between AXB calculations and measurements with depth from racemosa-PMMA interface. This can be attributed due to the lateral spread of scattered radiation in low-density racemosa region; there is reduction in scattered radiation reaching to the measurement point at depth from racemosa-PMMA interface. Therefore, the deviation between AAA calculated and measured dose increases with increase in depth due to inefficacy of AAA algorithm to approximate the scattered radiation contribution to the measurement points.
| Discussion|| |
The present study engineered a low-density heterogeneity phantom to mimic thorax region of human body. The measured mass density for racemosa wood and PMMA was 0.212 g/cc and 1.175 g/cc, respectively. Racemosa wood density was comparable to the density of kailwood (ρ = 0.379 g/cc) and pine wood (ρ = 0.329 g/cc) reported by Gurjar et al., Thus, racemosa wood is less dense and also comparable to lung tissue density reported in literature, ranging from 0.2 to 0.5 g/cc., Similarly, PMMA has mass density comparable to soft tissue density (1.002 g/cc) reported in literature., The radiological properties of racemosa and PMMA were also comparable to the values reported by Gurjar et al. (HUlung: −709.8 ± 119.1, HUsofttissue: 1.70 ± 31.31, ρlung: 0.291 ± 0.012, and ρsofttissue: 1.002 ± 0.03). Therefore, racemosa in combination with PMMA can be used to mimic the thorax region of human body.
The present study also investigates the dosimetric validation of AXB algorithm on this indigenously constructed low-density heterogeneous phantom. The accuracy of AXB algorithm has been analyzed with respect to IC measurements in fabricated phantom. This study reveals that AXB calculations were superior to AAA in low-density region as well as in predicting doses beyond racemosa-PMMA interface, rebuild-up region. Similar results have been reported by Rana and Rogers. As per their study in rebuild-up region, the discrepancies between AXB and measured data were from −3.81% to + 0.9%, whereas the AAA differences with measurement were from −3.1% to −10.9% up to 5 cm depth from air/solid–water interface in rebuild-up region. Kroon et al. reported that AXB was acceptably consistent with measurements in predicting the depth dose on central axis for 6 MV beam on a phantom containing low-density (ρ = 0.030 g/cc) region. Hirata et al. found that AXB calculations were in agreement with measurement within 0.5% at low-density (ρ =0.277 g/cc) region and within 1.5% at the rebuild-up region, whereas the greatest differences between the AAA and PBC calculations and measurement were 2.7% and 3.6%, respectively, at low-density region, and more than 5.5% and 3.5%, respectively, at rebuild-up region. Several publications had reported that AXB is more accurate than AAA in dealing with heterogeneous medium.,
Bulski et al. had reported in a multicenter dosimetric audit of TPS that the differences between doses calculated by TPS (using different dose calculation algorithms) and measured with Thermoluminescent dosimeter (TLD) did not exceed 4% for bone and polystyrene equivalent materials. Under the lung equivalent material, on the beam axis, the differences were lower than 5%, whereas inside the lung equivalent materials, off the beam axis, in some cases, the differences were of around 7%.
In summary, this study reveals that racemosa wood is a better choice for mimicking in lung tissue of human body. AXB calculated results showed that AXB calculation was in better agreement with IC measured doses in low-density region and beyond racemosa-wood interface (secondary build-up) regions, compared to AAA calculations.
| Conclusions|| |
Based on the physical and radiological properties studied for racemosa, it can be concluded that racemosa can simulate lung region of a human body. It can be used to construct a cost-effective, low-density heterogeneous phantom in combination with PMMA and other suitable materials to simulate the heterogeneity present in thoracic region. The dosimetric validation of AXB concludes that AXB is more appropriate for dose calculations in dealing with low-density heterogeneity in comparison to AAA.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Gray A, Oliver LD, Johnston PN. The accuracy of the pencil beam convolution and anisotropic analytical algorithms in predicting the dose effects due to attenuation from immobilization devices and large air gaps. Med Phys 2009;36:3181-91.
Robinson D. Inhomogeneity correction and the analytic anisotropic algorithm. J Appl Clin Med Phys 2008;9:2786.
Van Esch A, Tillikainen L, Pyykkonen J, Tenhunen M, Helminen H, Siljamäki S, et al.
Testing of the analytical anisotropic algorithm for photon dose calculation. Med Phys 2006;33:4130-48.
Chetty IJ, Curran B, Cygler JE, DeMarco JJ, Ezzell G, Faddegon BA, et al.
Report of the AAPM task group no 105: Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning. Med Phys 2007;34:4818-53.
International Commission on Radiation Units and Measurements. ICRU Report 83. Prescribing, Recording, and Reporting Photon-Beam Intensity-Modulation Radiation Therapy (IMRT). Bethesda: International Commission on Radiation Units and Measurements; 2010.
Boyer AL, Schultheiss T. Effects of dosimetric and clinical uncertainty on complication-free local tumor control. Radiother Oncol 1988;11:65-71.
Ekstrand KE, Barnes WH. Pitfalls in the use of high energy X rays to treat tumors in the lung. Int J Radiat Oncol Biol Phys 1990;18:249-52.
Young ME, Kornelsen RO. Dose corrections for low-density tissue inhomogeneities and air channels for 10-MVxrays. Med Phys 1983;10:450-5.
Xing L, Curran B, Hill R, Holmes T, Ma L, Forster KM, et al.
Dosimetric verification of a commercial inverse treatment planning system. Phys Med Biol 1999;44:463-78.
International Atomic Energy Agency. An International Code of Practice for Dosimetry based on absorbed dose to Water, IAEA Tech. Series No. 398, Absorbed dose Determination in External Beam Radiotherapy. Vienna: International Atomic Energy Agency; 2000.
Watson PE, Watson ID, Batt RD. Total body water volumes for adult males and females estimated from simple anthropometric measurements. Am J Clin Nutr 1980;33:27-39.
Kaushik S, Punia R, Tyagi A, Singh MP. Dosimetric studies of cadmium free alloy used in compensator based intensity modulated radiotherapy. Radiat Phys Chem 2017;139:184-9.
Khan FM. The Physics of Radiation Therapy. 4th
ed. Philadelphia: Lippincott Williams and Wilkins; 2010.
Gurjar OP, Mishra PK, Singh N, Bagdare P, Mishra SP. Dosimetric study for the development of heterogeneous chest phantom for the purpose of patient-specific quality assurance. Radiat Prot Environ 2015;38:139-43. [Full text]
Gurjar OP, Paliwal RK, Mishra SP. A dosimetric study on slab-pinewood-slab phantom for developing the heterogeneous chest phantom mimicking actual human chest. J Med Phys 2017;42:80-5.
] [Full text]
Ravikumar B, Lakshminarayana S. Determination of the tissue inhomogeneity correction in high dose rate brachytherapy for iridium-192 source. J Med Phys 2012;37:27-31.
] [Full text]
Attix FH. Introduction to Radiological Physics and Radiation Dosimetry. Hoboken: John Wiley and Sons; 1986.
Kumar A, Sharma SD, Arya AK, Gupta S, Shrotriya D. Effect of low-density heterogeneities in telecobalt therapy and validation of dose calculation algorithm of a treatment planning system. J Med Phys 2011;36:198-204.
] [Full text]
Rana S, Rogers K. Dosimetric evaluation of acuros XB dose calculation algorithm with measurements in predicting doses beyond different air gap thickness for smaller and larger field sizes. J Med Phys 2013;38:9-14.
] [Full text]
Kroon PS, Hol S, Essers M. Dosimetric accuracy and clinical quality of acuros XB and AAA dose calculation algorithm for stereotactic and conventional lung volumetric modulated arc therapy plans. Radiat Oncol 2013;8:149.
Hirata K, Nakamura M, Yoshimura M, Mukumoto N, Nakata M, Ito H, et al.
Dosimetric evaluation of the acuros XB algorithm for a 4 MV photon beam in head and neck intensity-modulated radiation therapy. J Appl Clin Med Phys 2015;16:52-64.
Han T, Mikell JK, Salehpour M, Mourtada F. Dosimetric comparison of acuros XB deterministic radiation transport method with Monte Carlo and model-based convolution methods in heterogeneous media. Med Phys 2011;38:2651-64.
Vassiliev ON, Wareing TA, McGhee J, Failla G, Salehpour MR, Mourtada F, et al.
Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beams. Phys Med Biol 2010;55:581-98.
Bulski W, Chełmiński K, Rostkowska J. Dosimetry audit of radiotherapy treatment planning systems. Radiat Prot Dosimetry 2015;165:472-6.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2], [Table 3]