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Year : 2017  |  Volume : 13  |  Issue : 2  |  Page : 175-185

An overview on small-field dosimetry in photon beam radiotherapy: Developments and challenges

1 Radiation and Wave Research Center, AJA University of Medical Sciences, Tehran, Iran
2 Department of Medical Physics, Tabriz Medical School, Tabriz University of Medical Sciences, Tabriz, Iran
3 Department of Paramedical, Medical School, Tabriz University of Medical Sciences, Tabriz, Iran
4 Department of Radiation Oncology, Imam Hospital, Tabriz, Iran
5 Department of Radiology, AJA University, Tehran, Iran
6 Department of Pediatric Nephrology, AJA University of Medical Sciences, Tehran, Iran
7 Department of Medical Physics, RAZAVI Hospital, Mashhad, Iran

Date of Web Publication23-Jun-2017

Correspondence Address:
Habib Alah Dadgar
Department of Medical Physics, RAZAVI Hospital, Mashhad
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0973-1482.199444

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 > Abstract 

Small fields are more repeatedly used for radiation therapy as small segments in intensity-modulated radiotherapy or as in the form of independent fields in stereotactic radiosurgery and other novel equipment such as cyberknife and tomotherapy. Nevertheless, the application of small fields for radiotherapy of lung makes the dose calculation and planning inaccurate due to the existence of electronic disequilibrium and intrinsic deficiencies within most of the analytical dose calculation algorithms. The current review attempts to gather the information in this regard and focuses on the current progresses and retaining issues associated with this type of photon beams.

Keywords: Monte Carlo simulation, radiotherapy of lung, small field dosimetry

How to cite this article:
Bagheri H, Soleimani A, Gharehaghaji N, Mesbahi A, Manouchehri F, Shekarchi B, Dormanesh B, Dadgar HA. An overview on small-field dosimetry in photon beam radiotherapy: Developments and challenges. J Can Res Ther 2017;13:175-85

How to cite this URL:
Bagheri H, Soleimani A, Gharehaghaji N, Mesbahi A, Manouchehri F, Shekarchi B, Dormanesh B, Dadgar HA. An overview on small-field dosimetry in photon beam radiotherapy: Developments and challenges. J Can Res Ther [serial online] 2017 [cited 2022 Nov 26];13:175-85. Available from: https://www.cancerjournal.net/text.asp?2017/13/2/175/199444

 > Introduction Top

Intensity-modulated radiotherapy (IMRT) and stereotactic radiosurgery and stereotactic body radiation therapy (SBRT) are becoming promising techniques for more accurate dose delivery methods in radiation therapy of all solid tumors.[1],[2],[3] Of course, the common feature of all these techniques is application of small fields of photons by means of multi-leaf collimator or special collimators which allow them to tailor the desired dose distribution for planning target volume (PTV).[4] On the other hand, in most of these techniques, the dose distribution inside PTV or other volumes is not necessarily homogeneous, and heterogeneous dose distributions are being used for the most desirable clinical outcomes. Hence, more small and irregular beamlets or segments are required for complex dose distributions, and the accuracy of planned dose distribution and its dosimetric validation turns out to be a very challenging task for physicists working in radiation therapy. Regarding accelerator design, source size can be different and collimation system can also decrease field sizes, as well. Electronic equilibrium depends on the range of secondary particles, beam energy, and homogeneous/inhomogeneous regions, especially in the lung.

Several studies have demonstrated that the erroneous dose calculations inside, beside of tumors and also in the vicinity of low-density in-homogeneities in lung and air regions lead to under dosage of target volume and poor outcomes for patients. Experimental dosimetry for small field has been challenging due to finite source size, lack of electronic equilibrium, size of detectors, and changes in energy spectrum with the associated dosimetric parameters. However, the application of new small dosimeters and enhancing the accuracy of methods such as gel dosimetry with promising potential to help for more reliable measurements in small fields will be the new approach to overcome the problems in this regard. For calculation point of view, on the other hand, several studies on the different algorithms used in commercial treatment planning systems (TPSs) have showed that they were not capable to model the secondary electron transport, especially in inhomogeneities existing in the patient's body.[5],[6] Recently, new algorithms such as collapse cone convolution (CCC) and analytical anisotropic algorithm and also Monte Carlo (MC) methods have illustrated more desirable results in small fields' calculations in new TPSs used in radiation therapy. In this review, we will try to address the associated difficulties with small-field dosimetry from both experimental and calculation perspectives. We also discuss the new methods and potential methods available to tackle the problem in both practical and theoretical approaches.

 > Small Fields in Radiotherapy Top

The use of small part photon radiation fields, normally in the presence of low-density heterogeneous substances, may become a complicated scenario to be studied by the TPS to resolve dose portions. The small radiation field areas of beams require a detector with a good spatial resolution. Several studies have assessed the dosimetry of narrow photon beams in a homogeneous medium.[7],[8],[9],[10],[11],[12] On the other hand, various authors studied this effect in the dose calculation of lung-equivalent materials exposed to such small region beams that will be discussed later.[13],[14],[15],[16],[17] The presence of inhomogeneities such as bone, lung, and air cavities also modifies the dose uniformity. Lung tissue is one of the most important low-density inhomogeneities that has an effect on the output of radiation therapy. A photon beam may have been lateral electronic equilibrium in tissue-equivalent media but may fail it entering to an inhomogeneity and vice versa. That heterogeneity is considered not only because of the lack of electronic equilibrium, but also due to the breathing movement of the lungs that is an issue of complexity during the therapeutic dose management.[18] Although despite being described as early as 1952 by Leksell, there is even now concern in the use of small fields (in general under around 3 cm × 3 cm) because of a lack of detailed information about the characteristics of the radiation fields. To deliver small-field treatments with precise and accurate measurement of the dose profiles, percent depth-dose curves and output factors for small fields are required for input clinical planning software. The shape of the dose profile due to lateral electronic nonequilibrium depends on the energy and the bony scattering of the secondary electrons issued by the photons and cannot be changed by reducing the source size or improving the collimator plan.[19] Using small radiation fields permits the dose to be placed very correctly in the target volume. Dose evaluations in the existence of pencil radiation beams are not easy. The expected inhomogeneity correction factors may not be applicable in lateral electronic nonequilibrium. Even dose in lateral electronic nonequilibrium can be exactly calculated with Monte Carlo N-Particle (MCNP) code. The presence of a dosimeter in a medium interrupts the charged particle distribution in the medium apart from the dosimeter, and the medium is equivalent with approbation to atomic composition and density. Consequently, the reply of a dosimeter depends on the geometry, structure, and the neighboring medium.[20] New physics play a significant role and the approximation features such as the volume averaging effect or lack of secondary electron equilibrium begin to classical radiation physics such as the Bragg–Gray conditions tend to be valid to a lower expand compared to larger fields. Accurate dosimetry in small fields is still a matter of scientific research; international standards are being developed.[21] There are essentially three “symmetry factors” that verify a radiation field to be considered as small or not: (1) Viewable part size of beam source as projected from the detector position during the beam hole, (2) used detector size in the measurements, and (3) electron range in the irradiated medium.

 > Challenges in Small-Field Dosimetry Top

There are different challenges in small fields for radiotherapy. The historical limitations in the small fields can have included technical difficulties of small target localization and the addition of diagnostic and therapeutic processes, and also lack of dosimetric data for small fields. Under such positions of small-field geometries, the electronic equilibrium can be lost, making it testing for the dose calculation algorithm to accurately predict the dose, especially in the presence of tissue heterogeneities. This can result in error calculation of dose distributions, mainly in the surrounding area of inhomogeneities and with small fields.[22],[23]

A high degree of spatial resolution detector with a very small sensitive volume is required. The use of a detector of limited size leads to a detector volume averaging effect. In ultra-small fields, large errors can take place if the size of the field approaches the active volume of the detector. A prominent effect is expansion of the penumbra of the dose profiles.[12],[18],[24],[25] It also leads to the mistake of dose volume histograms as well as tumor control and normal tissue difficulty probabilities. If the dose varies over the volume of the detector, this averaging can acquiesce a diverse signal compared to the signal an ultra-small detector would measure in the center of the area of the large detector. This so-called volume averaging effect or short volume effect leads to two distinct aspects: (1) The dose in the center of a small field is underestimated and (2) the penumbra is washed out.[26] In general, the volume effect is relative to the curvature of the dose profile but not to the slope.[27] The current technology in the field of radiotherapy has overcome many of these technical limitations. Some dosimetric challenges due to this affinity are lack of charged particle equilibrium (CPE).[16],[17] CPE is a meaning for the small fields employed in stereotactic radiotherapy and describes the condition in which the energies, figure, and direction of charged particles are steady during the volume of interest (ICRU, 1980). Otherwise, lateral equilibrium exists in the length of the central axis of the beam because electrons emitted of the volume are replaced by an approximately equal number of electrons from neighboring volumes. Electronic equilibrium is related with the range of secondary particles and therefore dependent on the beam energy, the structure of the medium, and mainly the density of the medium. However, MC simulations cannot be supposed a gold standard without suitable experimental corroboration, so these points confront the traditional way of performing dosimetric measurement and treatment planning.[28] The algorithms used to calculate dose in modern radiotherapy treatment plans classically suppose electronic equilibrium. Nevertheless, the extent of forward electronic disequilibrium (FED) has changed with density of materials at the interfaces and photon energies. FED takes place at the media interfaces with dissimilar material densities. Therefore, the number of electrons produced in one side may be either more or less than the electrons generated on the other side.[29] Nevertheless, this effect is foremost for higher photon energies and lung–soft tissue and air–soft tissue interfaces.[30]

Hence, lack of both lateral and forward electronic equilibriums to take place when the dimensions of the radiation field are smaller than the maximum range of secondary electrons and lateral disequilibrium is more important for higher energy photons.[30] Consequently, small fields can be intrinsically complicated because, unlike broad beams, the doses within small fields are less well known. The range of electrons is inversely relative to the density of the medium, in which they pass through, for low-density media; disequilibrium will be present even for relatively large field sizes. These comparatively large areas of electronic disequilibrium in such narrow photon beam fields make accurate dosimetry more difficult than with conventional radiotherapy beams. This disequilibrium effect can be aggravated in the areas of tissue heterogeneity. When calculating the dose in a low-density medium such as lung using pencil beams, tissue density variations can introduce major perturbations that are energy- and density-dependent and affect the accuracy of the dose calculation. This problem is more pronounced when the TPS uses simple one-dimensional density scaling.[31],[32],[33] More accurate dose calculation for small fields and nonequilibrium position develops with the use of more sophisticated treatment planning algorithms.[22], 23, [34],[35],[36],[37],[38],[39],[40],[41] It has been illustrated that the precision of small-field dosimetry is greatly improved when MC calculations are used, particularly for beam with apertures <3 cm × 3 cm in homogeneous media.[42],[43]

 > Dosimetry in Small Field Top

The dosimetry of small field sizes is considerably unlike from that for standard radiotherapy field sizes. In low-density medium similar to the lung, small fields have important perturbations that are energy and density dependent. However, errors in dose measurement and calculation can direct not only to overdosage of healthy tissues, but also to tumor underdosage. The complexities of small-field dosimetry are explained in terms of the routine supposition of electronic equilibrium, which breaks down for small fields. The computation of dose delivered to a patient is of vital significance to assess the best possible treatment result. Considered to be the most precise means of calculating dose and other significant quantities, MC radiation transport modeling is described in an important aspect.[14] As we told in the previous section, the range of the secondary electrons, which is a result of the photon energy spectrum, plays an essential role in the form of the beam profile. A variety of types of radiation detectors are used to calculate relative dose distributions for therapeutic electron and photon beams.[26] There are a number of dosimeters with its own limitations as applied to small-field dosimetry. Furthermore, gel dosimeters show great agree, assemble many of the requirements of the ideal dosimeter for small fields (in particular three dimensionality). Nevertheless, there are a number of useful difficulties encountered with gels. Hence, gel dosimeters are treated in many aspects. The radiation communication properties of gel dosimeters obviously vary from water and tissue because of the differences in their essential composition. The water correspondence of gel dosimeters under calibration situations was investigated using MC simulation.

The MC method is the most precise way to analyze dose under any radiation field geometry. Although it requires the incidence photon spectrum for the simulation geometry, fields are continuously adjusted throughout the treatment planning stage to assess different plans and therefore, MC simulations are not completely useful for usual clinical use. Recently, a primary and scatter dose has been extended to examine dose in lateral nonequilibrium conditions by including the electron transfer from the MC estimation.[29] It can simulate physical interactions of photons, electrons, and neutrons with material.[44],[45] Clear radiation transfer calculations based on MC or other methods will increasingly play a significant role in nonequilibrium dosimetry. It has been shown that even when the trial measurements were accurate, ends drawn from the measured data could be wrong because the results may be misunderstood due to the lack of information of the perturbation from the existence of a detector.[46] In addition, the MC simulated beams can be calibrated opposed to measurements under controlled conditions where the measurements can be determined precisely. Since the geometry of the accelerator head can be modeled in detail, the yield or the whole practical beam of any field size can be accurately determined by radiation transfer calculations. Then, the nonequilibrium dosimetry for the small field in heterogeneous media can be examined and well understood. These types of calculations will play a rising role in dose confirmation, beam examination, and for straight control of dose distribution in treatment planning and treatment delivery. It is not completely practical to utilize the MC algorithms in clinically realistic situations due to long computation time-consuming calculations.[47]

 > Discussion Top

The previous investigations were comparable on the subject of small fields in radiotherapy of lung cancer. However, there were small discrepancies about dose reduction percentages in lung region with and without tumor.[48],[49] These small differences can be attributed to the differences in the geometry simulated with various MC software and applied algorithms. For example, Jones et al. studied the effect of lung heterogeneity on small beamlets for 6, 15, and 24 MV photon beams by the EGSnrc MC code.[13] These simulations showed that for small fields, a dose decreasing in the presence of low-density media due to the lack of lateral electronic equilibrium is observed. As the density and field size increase, the dose reduction is less pronounced. This study suggests that the current TPS may dramatically over or underestimate the dose in inhomogeneous media for small field sizes that are used for IMRT. Jones and Das studied depth-dose information from the MC simulations and evaluated them to the results given by heterogeneity algorithms for a 6 MV beam.[14] In their study, depth-dose data from the MC simulations are compared to the results of the convolution superposition, Batho, and equivalent path length (EPL) algorithms. The dose perturbation factor (DPF) is defined as the ratio of dose to a point within the inhomogeneity to the same point in a homogeneous phantom. The dose correction factor is defined as the ratio of dose calculated by an algorithm at a point to the MC derived dose at the same point. DPF is noted to be significant for small fields and low density for all algorithms. Batho and EPL algorithms differ significantly from MC simulation for most field sizes and densities. Convolution superposition showed better agreement with MC data versus the Batho or EPL corrections. For a 6 MV photon beam, electronic equilibrium is restored at field sizes above 3 cm diameter, and all the algorithms predict dose in and beyond the inhomogeneous region equally well. For accurate dosimetry of small fields within and near inhomogeneities, however, simple algorithms such as Batho and EPL should be avoided. For dose buildup inside the tumor, the reason is electrons generated at the edge of beam are coming from unit density material, not from the lung. Hence, their number could be more enough to produce higher dose buildup inside the tumor. In water–lung interface, the absorbed dose fluctuates because of the density variations and secondary electron generation rates in different areas. This phenomenon is exacerbated in conditions of small fields and high-energy photon beams currently being used in radiotherapy. On the other hand, in lung–water interface, the dose buildup region is generated due to more secondary electron productions in unit density medium. A study by Brugmans et al. has compared dosimetric measurements, MC, and TPS calculations.[2] The measured depth dose values were in good agreement with MC results and a difference <2% was observed. A large dose reduction was seen in lung for field size of 2 cm × 2 cm due to the lateral electronic disequilibrium (LED) and it reached up to 16.2% and 33.3% for 6 and 18 MV beams, respectively. Dose buildup and down at interfaces was predicted by MC method. Their study showed that the dose reductions with small fields in lung and dose variations at interfaces were considerable, and inaccurate prediction of absorbed dose in lung using small fields and photon beams may lead to critical consequences for patients. Arnfield et al. examined the results of lung heterogeneities on depth dose and lateral beam profiles for 6 and 18 MV photon beams for field sizes 4 cm × 4 cm and 10 cm × 10 cm.[15] Dose calculations were done with a generalized Batho model, the Pinnacle CCC model, and the Peregrine MC dose calculation algorithm. Absolute central axis and off axis dose data at various depths relative to interfaces of inhomogeneities were compared. Their results confirmed that for a Batho correction, dose errors in the calculated depth dose arise from the neglect of electron transport. This effect increased as the field size decreased, as the density of the inhomogeneity decreased, and with the energy of incident photons. The CCC calculations were closer to measurements than the Batho model, but significant discrepancies remain. Carrasco et al. assessed the absorbed dose by measurements, MC simulations, and TPS calculations for 10 cm × 10 cm, 5 cm × 5 cm, 2 cm × 2 cm, and 1 cm × 1 cm field sizes and X-ray spectrum of 6 and 10 MV; where, the collapsed cone overestimated the dose inside the lung heterogeneity by about 3%–5%. In a similar study by da Rosa et al., they compared the accuracy of different inhomogeneity correction methods in a lung phantom.[28] Analyzing their pertinent data on the MC and the curves without correction revealed that the dose reduction inside the lung at the depth of 10 cm was 50% and 90%, respectively, for 2 cm × 2 cm and 1 cm × 1 cm field sizes, respectively, for 15 MV photon beam. In a study by Mesbahi et al. on the Eclipse TPS for 8 and 15 MV photon beams, a great dose reduction in low-density material was seen for 4 cm × 4 cm field size. The results illustrated the errors of up to 33% and 28% in the lung (15 MV beam) for TPS estimations using modified Batho and equivalent tissue-air ratio methods, respectively.[50] In a study by Arnfield et al. on the accuracy of lung dose calculations by CCC, Batho, and MC methods, they showed that the CCC were sensitive to the absorbed dose changes due to electronic disequilibrium at interfaces and LED in the lung for small fields.[15] Several studies on the TPSs have showed that they were not capable to model the secondary electrons, especially in inhomogeneities existing in the patient's body.[5],[6],[50] To sum up, Arnfield et al. and Jones et al. at their studies illustrated that CCC method and MC simulations have been better results for dose calculation of small fields in lung region instead of other methods. Stathakis et al. assess MC calculation on a similar geometry with lung thickness of 5 cm. The BEAMnrc/DOSXYZnrc code calculations were used in their study and two other analytical algorithms were assessed against MC results. The dose reduction inside lung was obtained for 1 cm × 1 cm, 2 cm × 2 cm, and 3 cm × 3 cm field sizes. Its maximum value was approximately 50%, 16%, and 11%, respectively. As we can deduce from these results, the obtained dose reductions were approximately consistent together, and like other cases, the observed discrepancies can be attributed to the small differences in MC code and geometries.

In a recent study, MC calculation of LED for small fields in ultra-low density lung ranging from 0.001 to 4 g/cm 3 was assessed.[51] They studied selected depth dose and transverse dose profiles for various lung densities of 1.25, 6, and 18 MV at 3 cm × 3 cm and 10 cm × 10 cm field sizes. Photon distribution was generally enhanced by decreasing lung density. For the above energy beams and 10 cm × 10 cm field size, there were dose reduction percentages about 24%, 31%, and 42%, respectively. On the other hand, for same energies and 3 cm × 3 cm field size, dose reduction percentages were approximately 35%, 39%, and 48%, respectively. Their study showed that several LED small fields in ultra-low density of lung can lead to a significant dose reduction inside lung and cause large underdosage of solid tumor inside the lung. In the latest study by Mesbahi et al., the schematic representation of simulated linac head and phantom used for dose scoring and also percent depth dose (PDD) plots were illustrated [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5].
Figure 1: Schematic representation of simulated linac head and phantom used for dose scoring

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Figure 2: Comparison of depth dose calculations for homogeneous water phantom and lung phantom. The Monte Carlo calculations were performed for field sizes of (a) 0.5 cm × 0.5 cm, (b) 1 cm × 1 cm, (c) 2 cm × 2 cm, and (d) 3 cm × 3 cm for 6 MV photon beam

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Figure 3: Comparison of depth dose calculations for homogeneous water phantom and lung phantom. The Monte Carlo calculations were performed for field sizes of (a) 0.5 cm × 0.5 cm, (b) 1 cm × 1 cm, (c) 2 cm × 2 cm, and (d) 3 cm × 3 cm for 18 MV photon beam

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Figure 4: Comparison of depth dose calculations for homogeneous water phantom and lung phantom containing a solid cubic tumor with dimension of 1 cm × 1 cm × 1 cm. The Monte Carlo calculations were performed for field sizes of (a) 0.5 cm × 0.5 cm, (b) 1 cm × 1 cm, (c) 2 cm × 2 cm, and (d) 3 cm × 3 cm for 6 MV photon beam

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Figure 5: Comparison of depth dose calculations for homogeneous water phantom and lung phantom containing a solid cubic tumor with dimension of 1 cm × 1 cm × 1 cm. The Monte Carlo calculations were performed for field sizes of (a) 0.5 cm × 0.5 cm, (b) 1 cm × 1 cm, (c) 2 cm × 2 cm, and (d) 3 cm × 3 cm for 18 MV photon beam

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In this study, we applied MCNPX simulation for obtaining PDD in lung phantom with and without tumor. PDD curves for both energies 6 and 18 MV and field sizes 0.5 cm × 0.5 cm, 1 cm × 1 cm, 2 cm × 2 cm, and 3 cm × 3 cm were calculated. In [Figure 2],[Figure 3],[Figure 4],[Figure 5], the effect of water–lung interface is apparent, while its dosimetric magnitude and spatial spread differ considerably for different photon energies and field sizes. In other words, the dose begins to drop off at water–lung interface and decreases steadily with depth inside lung, then at the second lung–water interface; the dose builds up and reaches to its second maximum in water. However, this pattern of dose variation with depth becomes very pronounced with decreasing the field size. Otherwise, the dose beyond the lung increases significantly compared to homogeneous water phantom. The dose reduction in lung compared to water was obtained to be 44%, 39%, 13%, and 7% for 0.5 cm × 0.5 cm, 1 cm × 1 cm, 2 cm × 2 cm, and 3 cm × 3 cm field sizes, respectively. Meanwhile, it can be noticed that the dose inside lung is getting similar to water dose in the field size of 3 cm × 3 cm. The dose reduction percentage was calculated at 10 cm depth for 18 MV beam, and there were higher dose reductions in lung relative to water with 82%, 70%, 46%, and 26% for 0.5 cm × 0.5 cm, 1 cm × 1 cm, 2 cm × 2 cm, and 3 cm × 3 cm field sizes, respectively.

For the 18 MV beam, due to the higher range of secondary electrons, the FED becomes more pronounced relative to 6 MV beam, and consequently, the depth dose reduces considerably for smaller fields sizes. As it can be seen, all beams were capable to cover the tumor except 0.5 cm × 0.5 cm. However, it was found that the tumor underdosage was higher for larger field sizes, and the maximum value of 35% was seen for 2 cm × 2 cm and the minimum value of 17% underdosage was seen for 0.5 cm × 0.5 cm field size. The dose reduction percentages for 1 cm × 1 cm and 3 cm × 3 cm were 32% and 20%, respectively. Recent studies by Mesbahi et al. and Disher et al. by different MC codes showed that their results have close agreement together with about approximately 2% discrepancy. For better comparison and over understanding of obtained results from authors, we decided to illustrate these consequences at comparative plots [Figure 6],[Figure 7],[Figure 8],[Figure 9],[Figure 10].
Figure 6: Comparison of Monte Carlo calculated depth doses and ionization chamber measurements for the 6 MV (left) and 18 MV (right) photon beams[30]

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Figure 7: Percent depth dose curves for three different inhomogeneities for various small fields (published by Stathakis et al., 2012)

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Figure 8: Percent depth dose curves calculated through the radiotherapy Eclipse planning system algorithms, Batho, modified Batho, equivalent TAR, and anisotropic analytical algorithm; measured with thermoluminescent dosimetry and simulated using EGSnrc Monte Carlo code for an irradiation field of (a) 10 cm × 10 cm, (b) 5 cm × 5 cm, (c) 2 cm × 2 cm, and (d) 1 cm × 1 cm[28]

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Figure 9: Percent depth doses comparison in the heterogeneous layer phantom with water- and lung-equivalent materials in, predicted by anisotropic analytical algorithm (solid curve), calculated by Monte Carlo N-Particle (open circles), and measured with cylindrical ionization chamber (closed circles). (a) 6 MV in 4 cm × 4 cm field size, (b) 6 MV in 10 cm × 10 cm field size, (c) 10 MV in 4 cm × 4 cm field size, and (d) 10 MV photon beams in 10 cm × 10 cm field size (published by Kaoru Ono, 2010)

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Figure 10: Percent depth doses comparison in the heterogeneous layer phantom with water-, lung-, and bone-equivalent materials in, predicted by anisotropic analytical algorithm (solid curve), calculated by Monte Carlo N-Particle (open circles), and measured with cylindrical ionization chamber (closed circles). (a) 6 MV in 4 cm × 4 cm field size, (b) 6 MV in 10 cm × 10 cm field size, (c) 10 MV in 4 cm × 4 cm field size, and (d) 10 MV photon beams in 10 cm × 10 cm field size (published by Kaoru Ono, 2010)

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Consequently, in accordance to previous studies, application of more accurate dose calculation engines seems an essential prerequisite for lung cancer treatment to lower the uncertainty associated with delivered dose to the small solid tumor.

 > Conclusion Top

The accuracy of PDDs calculated in a heterogeneous region including lung was verified by MCNP MC calculation. In the lung region, we observed four build up and build down interfaces such as water–lung, lung–tumor, tumor–lung, and lung–water. However, these are more significant in water–lung and vice versa regions. Hence, dosimetry in the small fields needs greater precise for calculation. The LED and FED effects were studied using an inhomogeneous solid phantom resembling the lung region. The erroneous calculations in low-density inhomogeneities such as lung could have led to the underdosage of target volume and fatal outcomes for patients. MC code predicted the effect of LED, due to electron transport modeling in the MC code of MCNP4C. Of course, the calculations in small field sizes were inaccurate enough to exclude them from dose calculations in treatments involving small fields such as IMRT and three-dimensional conformal radiotherapy. The absorbed dose on beam central axis in unit density and low-density materials was measured and calculated using MC method. The findings showed that the absorption in lung tissue was decreased significantly in a small field of 0.5 cm × 0.5 cm where LED did not exist. The prediction of the absorbed dose in small field needed algorithms which modeled the transport of secondary electrons in the irradiated medium. MCNP4C MC code was capable to calculate the dose in the regions with FED and LED conditions.

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 > References Top

Brugmans MJ, van der Horst A, Lebesque JV, Mijnheer BJ. Beam intensity modulation to reduce the field sizes for conformal irradiation of lung tumors: A dosimetric study. Int J Radiat Oncol Biol Phys 1999;43:893-904.  Back to cited text no. 1
Calcina CS, de Oliveira LN, de Almeida CE, de Almeida A. Dosimetric parameters for small field sizes using Fricke xylenol gel, thermoluminescent and film dosimeters, and an ionization chamber. Phys Med Biol 2007;52:1431-9.  Back to cited text no. 2
De Jaeger K, Hoogeman MS, Engelsman M, Seppenwoolde Y, Damen EM, Mijnheer BJ, et al. Incorporating an improved dose-calculation algorithm in conformal radiotherapy of lung cancer: Re-evaluation of dose in normal lung tissue. Radiother Oncol 2003;69:1-10.  Back to cited text no. 3
Houdek PV, JM, Fayos JV. Dosimetry of small radiation fields for 10-MVxrays. Med Phys 1983;10:333-6.  Back to cited text no. 4
Vanderstraeten B, Reynaert N, Paelinck L, Madani I, De Wagter C, De Gersem W, et al. Accuracy of patient dose calculation for lung IMRT: A comparison of Monte Carlo, convolution/superposition, and pencil beam computations. Med Phys 2006;33:3149-58.  Back to cited text no. 5
Kan MW, Wong TP, Young EC, Chan CL, Yu PK. A comparison of two photon planning algorithms for 8 MV and 25 MV x-ray beams in lung. Australas Phys Eng Sci Med 1995;18:95-103.  Back to cited text no. 6
Westermark M, Arndt J, Nilsson B, Brahme A. Comparative dosimetry in narrow high-energy photon beams. Phys Med Biol 2000;45:685-702.  Back to cited text no. 7
Martens C, De Wagter C, De Neve W. The value of the PinPoint ion chamber for characterization of small field segments used in intensity-modulated radiotherapy. Phys Med Biol 2000;45:2519-30.  Back to cited text no. 8
Verhaegen F, Das IJ, Palmans H. Monte Carlo dosimetry study of a 6 MV stereotactic radiosurgery unit. Phys Med Biol 1998;43:2755-68.  Back to cited text no. 9
Rustgi SN, Frye DM. Dosimetric characterization of radiosurgical beams with a diamond detector. Med Phys 1995;22:2117-21.  Back to cited text no. 10
Bjärngard BE, Tsai JS, Rice RK. Doses on the central axes of narrow 6-MV x-ray beams. Med Phys 1990;17:794-9.  Back to cited text no. 11
Rice RK, Hansen JL, Svensson GK, Siddon RL. Measurements of dose distributions in small beams of 6 MV x-rays. Phys Med Biol 1987;32:1087-99.  Back to cited text no. 12
Jones AO, Das IJ, Jones FL Jr. A Monte Carlo study of IMRT beamlets in inhomogeneous media. Med Phys 2003;30:296-300.  Back to cited text no. 13
Jones AO, Das IJ. Comparison of inhomogeneity correction algorithms in small photon fields. Med Phys 2005;32:766-76.  Back to cited text no. 14
Arnfield MR, Siantar CH, Siebers J, Garmon P, Cox L, Mohan R. The impact of electron transport on the accuracy of computed dose. Med Phys 2000;27:1266-74.  Back to cited text no. 15
Duch MA, Carrasco P, Ginjaume M, Jornet N, Ortega X, Ribas M. Dose evaluation in lung-equivalent media in high-energy photon external radiotherapy. Radiat Prot Dosimetry 2006;120:43-7.  Back to cited text no. 16
Carrasco P, Jornet N, Duch MA, Panettieri V, Weber L, Eudaldo T, et al. Comparison of dose calculation algorithms in slab phantoms with cortical bone equivalent heterogeneities. Med Phys 2007;34:3323-33.  Back to cited text no. 17
Rosu M, Chetty IJ, Tatro DS, Ten Haken RK. The impact of breathing motion versus heterogeneity effects in lung cancer treatment planning. Med Phys 2007;34:1462-73.  Back to cited text no. 18
Dutreix J, Dutreix A, Tubiana M. Electronic equilibrium and transition stages. Phys Med Biol 1965;10:177-90.  Back to cited text no. 19
Haider JA. Dosimetric Study of Small Fields in Homogeneous and Inhomogeneous Media for High Energy Photons. Thesis (Ph. D.), University of British Columbia, 1995.  Back to cited text no. 20
Alfonso R, Andreo P, Capote R, Huq MS, Kilby W, Kjäll P, et al. A new formalism for reference dosimetry of small and nonstandard fields. Med Phys 2008;35:5179-86.  Back to cited text no. 21
Zhu TC, Bjärngard BE. The head-scatter factor for small field sizes. Med Phys 1994;21:65-8.  Back to cited text no. 22
Zhu TC, Bjärngard BE. The fraction of photons undergoing head scatter in x-ray beams. Phys Med Biol 1995;40:1127-34.  Back to cited text no. 23
Moskvin V, Timmerman R, DesRosiers C, Randall M, DesRosiers P, Dittmer P, et al. Monte carlo simulation of the Leksell Gamma Knife: II. Effects of heterogeneous versus homogeneous media for stereotactic radiosurgery. Phys Med Biol 2004;49:4879-95.  Back to cited text no. 24
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.  Back to cited text no. 25
Laub WU, Wong T. The volume effect of detectors in the dosimetry of small fields used in IMRT. Med Phys 2003;30:341-7.  Back to cited text no. 26
Wuerfel JU. Dose measurements in small fields. Med Phys Int J 2013;1.  Back to cited text no. 27
da Rosa LA, Cardoso SC, Campos LT, Alves VG, Batista DV, Facure A. Percentage depth dose evaluation in heterogeneous media using thermoluminescent dosimetry. J Appl Clin Med Phys 2010 28;11:2947.  Back to cited text no. 28
Woo MK, Cunningham JR, Jezioranski JJ. Extending the concept of primary and scatter separation to the condition of electronic disequilibrium. Med Phys 1990;17:588-95.  Back to cited text no. 29
Mesbahi A. The effect of electronic disequilibrium on the received dose by lung in small fields with photon beams: Measurements and Monte Carlo study. IJRR 2008;6:70-6.  Back to cited text no. 30
Chetty IJ, Charland PM, Tyagi N, McShan DL, Fraass BA, Bielajew AF. Photon beam relative dose validation of the DPM Monte Carlo code in lung-equivalent media. Med Phys 2003;30:563-73.  Back to cited text no. 31
Al-Hallaq HA, Reft CS, Roeske JC. The dosimetric effects of tissue heterogeneities in intensity-modulated radiation therapy (IMRT) of the head and neck. Phys Med Biol 2006;51:1145-56.  Back to cited text no. 32
Mackie TR, Scrimger JW, Battista JJ. A convolution method of calculating dose for 15-MVxrays. Med Phys 1985;12:188-96.  Back to cited text no. 33
Tillikainen L, Helminen H, Torsti T, Siljamäki S, Alakuijala J, Pyyry J, et al. A 3D pencil-beam-based superposition algorithm for photon dose calculation in heterogeneous media. Phys Med Biol 2008;53:3821-39.  Back to cited text no. 34
Scholz C, Schulze C, Oelfke U, Bortfeld T. Development and clinical application of a fast superposition algorithm in radiation therapy. Radiother Oncol 2003;69:79-90.  Back to cited text no. 35
Kunieda E, Deloar HM, Kishitani N, Fujisaki T, Kawase T, Seki S, et al. Variation of dose distribution of stereotactic radiotherapy for small-volume lung tumors under different respiratory conditions. Phys Med 2008;24:204-11.  Back to cited text no. 36
García-Vicente F, Miñambres A, Jerez I, Modolell I, Pérez L, Torres JJ. Experimental validation tests of fast Fourier transform convolution and multigrid superposition algorithms for dose calculation in low-density media. Radiother Oncol 2003;67:239-49.  Back to cited text no. 37
Gagné IM, Zavgorodni S. Evaluation of the analytical anisotropic algorithm in an extreme water-lung interface phantom using Monte Carlo dose calculations. J Appl Clin Med Phys 2006;8:33-46.  Back to cited text no. 38
Craig J, Oliver M, Gladwish A, Mulligan M, Chen J, Wong E. Commissioning a fast Monte Carlo dose calculation algorithm for lung cancer treatment planning. J Appl Clin Med Phys 2008;9:2702.  Back to cited text no. 39
Bragg CM, Conway J. Dosimetric verification of the anisotropic analytical algorithm for radiotherapy treatment planning. Radiother Oncol 2006;81:315-23.  Back to cited text no. 40
Boyer AL, Mok EC. Calculation of photon dose distributions in an inhomogeneous medium using convolutions. Med Phys 1986;13:503-9.  Back to cited text no. 41
Ding GX. Dose discrepancies between Monte Carlo calculations and measurements in the buildup region for a high-energy photon beam. Med Phys 2002;29:2459-63.  Back to cited text no. 42
Ahnesjö A. Collimator scatter in photon therapy beams. Med Phys 1995;22:267-78.  Back to cited text no. 43
Haryanto F, Fippel M, Laub W, Dohm O, Nüsslin F. Investigation of photon beam output factors for conformal radiation therapy – Monte Carlo simulations and measurements. Phys Med Biol 2002;47:N133-43.  Back to cited text no. 44
Heydarian M, Asnaashari K, Allahverdi M, Jaffray DA. Dosimetric evaluation of a dedicated stereotactic linear accelerator using measurement and Monte Carlo simulation. Med Phys 2008;35:3943-54.  Back to cited text no. 45
García-Vicente F, Béjar MJ, Pérez L, Torres JJ. Clinical impact of the detector size effect in 3D-CRT. Radiother Oncol 2005;74:315-22.  Back to cited text no. 46
Ma CM, Mok E, Kapur A, Pawlicki T, Findley D, Brain S, et al. Clinical implementation of a Monte Carlo treatment planning system. Med Phys 1999;26:2133-43.  Back to cited text no. 47
Fogliata A, Nicolini G, Clivio A, Vanetti E, Cozzi L. On the dosimetric impact of inhomogeneity management in the acuros XB algorithm for breast treatment. Radiat Oncol 2011;6:103.  Back to cited text no. 48
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.  Back to cited text no. 49
Mesbahi A, Thwaites D, Reilly A. Experimental and Monte Carlo evaluation of Eclipse treatment planning system for lung dose calculations. Reports of practical oncology and Radiotherapy 2006;11:1-11.  Back to cited text no. 50
Disher B, Hajdok G, Gaede S, Battista JJ. An in-depth Monte Carlo study of lateral electron disequilibrium for small fields in ultra-low density lung: Implications for modern radiation therapy. Phys Med Biol 2012;57:1543-59.  Back to cited text no. 51


  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8], [Figure 9], [Figure 10]

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