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ORIGINAL ARTICLE
Year : 2015  |  Volume : 11  |  Issue : 1  |  Page : 94-97

Dose enhancement in gold nanoparticle-aided radiotherapy for the therapeutic photon beams using Monte Carlo technique


Radiological Physics and Advisory Division, Bhabha Atomic Research Centre, Anushakti Nagar, Mumbai, Maharashtra, India

Date of Web Publication16-Apr-2015

Correspondence Address:
Sunil Dutt Sharma
Radiological Physics and Advisory Division, Bhabha Atomic Research Centre, CTCRS, Building, Anushakti Nagar, Mumbai - 400 094, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0973-1482.147691

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 > Abstract 

Background: Gold nanoparticle (GNP)-aided radiation therapy (RT) is useful to make the tumor more sensitive to radiation damage because of the enhancement in the dose inside the tumor region. Polymer gel dosimeter (PGD) can be a good choice for the physical measurement of dose enhancement produced by GNP inside the gel.
Materials and Methods: The present study uses EGSnrc Monte Carlo code to estimate dose enhancement factor (DEF) due to the introduction of GNPs inside the PGD at different concentrations (7 and 18 mg Au/g of gel) when irradiated by therapeutic X-rays of energy 100 kVp, 150 kVp, 6 MV, and 15 MV. The simulation was also carried out to quantify the dose enhancement in PAGAT gel and tumor for 100 kVp X-rays.
Results: For 100 kVp X-rays, average DEF of 1.86 and 2.91 is observed in the PAGAT gel dosimeter with 7 and 18 mg Au/g of gel, respectively. Average DEF of 1.69 and 2.61 is recorded for 150 kVp X-rays with 7 and 18 mg Au/g of gel, respectively. No clinically meaningful DEF was observed for 6 and 15 MV photon beams. Furthermore, the dose enhancement within the PAGAT gel dosimeter and tumor closely matches with each other.
Conclusion: The polymer gel dosimetry can be a suitable method of dose estimation and verification for clinical implementation of GNP-aided RT. GNP-aided RT has the potential of delivering high localized tumoricidal dose with significant sparing of normal structures when the treatment is delivered with low energy X-rays.

Keywords: Dose enhancement factor, gel dosimeter, gold nanoparticle, Monte Carlo, radiation therapy


How to cite this article:
Kakade NR, Sharma SD. Dose enhancement in gold nanoparticle-aided radiotherapy for the therapeutic photon beams using Monte Carlo technique. J Can Res Ther 2015;11:94-7

How to cite this URL:
Kakade NR, Sharma SD. Dose enhancement in gold nanoparticle-aided radiotherapy for the therapeutic photon beams using Monte Carlo technique. J Can Res Ther [serial online] 2015 [cited 2019 Nov 19];11:94-7. Available from: http://www.cancerjournal.net/text.asp?2015/11/1/94/147691


 > Introduction Top


External beam radiotherapy (RT) is currently one of the most common and effective treatment modalities used for the treatment of cancer. The objective of RT is to deliver an adequate dose to the tumor while sparing surrounding normal tissue. The accurate dose measurement with the help of suitable dosimetry tools is the main requirement for success of RT. Historically, orthovoltage X-rays were used for treating superficial lesions. However, with the availability of state of the art medical electron linear accelerator deep-seated tumor could well be managed by highly penetrating X-rays. Following the work by Hainfeld et al., [1] there has been considerable interest in the use of gold and other heavy-atom containing nanoparticles to enhance the dose delivered to tumors. Gold nanoparticle (GNP)-aided RT is useful to make the tumor more sensitive to radiation damage because of the enhancement in the dose inside the tumor region. The enhancement in the tumor region primarily occurs due to enhancement in photoelectric cross section because of the introduction of GNPs (Z = 79) into the tumor volume. [2]

The dosimetric suitability of GNP-aided RT is very crucial to justify its feasibility and applicability in clinical practice. Polymer gel dosimeter (PGD) with tissue like elemental composition have the unique advantage of providing three-dimensional dose information with high spatial resolution. [3] PGD used to quantify absorbed dose via measuring the polymerization of the monomer by radiation. PGD can be read out with a magnetic resonance imaging scanner [4] or optical computed tomography scanner. [5] The effects of contrast agents can be easily quantified using polymer gels. [6] They are very good choice for the physical measurement of the dose enhancement produced by high Z GNP inside the gel dosimeter.

Hainfeld et al. reported in vivo study of using gold as a radiosensitive agent. Irradiation using 250 kVp X-rays resulted in 66% increase in 1-year survival rates of cancer-bearing mice when compared to irradiation without the implanted gold. Cho et al. [7] quantified dose enhancement factor (DEF) with the infusion of GNPs with various concentrations using photon-emitting brachytherapy sources. Khadem-Abolfazli et al. [6] investigated dose enhancement due to GNP in MAGICA polymer gel both experimentally and by simulation for 18 MV X-rays. Zhang et al. [8] studied the dose enhancement with an uniform distribution of 100 nm diameter GNPs irradiated by 192 Ir brachytherapy source using the GEANT4 Monte Carlo (MC) code.

To our knowledge, limited information is available on the use of PGD for possible dose enhancement due to the use of GNPs. The goal of the present study was to use EGSnrc MC [9] code for estimating DEF due to the introduction of GNPs in the PGD at concentration levels of 7 and 18 mg Au/g of gel respectively. The DEF within the PAGAT gel dosimeter was estimated when it is irradiated by therapeutic X-rays of energy 100 kVp, 150 kVp, 6 MV, and 15 MV. Also to see the dosimetric suitability of PAGAT gel dosimeter, the dose enhancement in PAGAT gel and tumor is quantified for 100 kVp X-rays at the above mentioned concentration levels.


 > materials and methods Top


EGSnrc Monte Carlo code system

The EGSnrc MC code system is a general purpose package for the MC simulation for the coupled transport of electrons and photons in arbitrary geometry for particles with energies above a few kiloelectronvolt up to several hundreds of gigaelectronvolt. EGSnrc uses material cross section created by the companion code PEGS4. The electron cut-off energy and photon cut-off energy of 0.521 MeV and 0.01 MeV respectively were chosen, during the use of PEGS4 and EGSnrc codes. The low energy threshold for the production of knock-on electrons (AE) is set to 0.521 MeV, and the threshold for the secondary Bremsstrahlung photon (AP) were set to 10 keV.

Geometry and dose enhancement factor estimation

PAGAT is a normoxic polyacrylamide and gelatine type gel that uses tetrakis (hydroxymethyl) phosphonium chloride to scavenge contaminating oxygen-free radicals. The chemical and elemental compositions of PAGAT gel were taken from the literature. [10] The material composition of the tumor and normal tissue was assumed to be the same having 10.1% hydrogen, 11.1% carbon, 2.6% nitrogen, and 76.2% oxygen defined by the International Commission on Radiation Units and Measurements (ICRU). [11] The composition and density of the PAGAT gel were altered by varying the concentration levels of GNPs (7 and 18 mg Au/g gel) inside the gel medium as indicated in the study by Hainfeld et al. Furthermore, the composition and density of the tumor were altered by varying the concentration levels of GNPs (7 and 18 mg Au/g tumor) inside the tumor. In each of the simulation case, it was considered that the GNPs were uniformly distributed throughout the gel and tumor.

For the MC simulation, a cylindrical water phantom of radius 15 cm and height 30 cm was used. The PGD was taken as a cylinder of 0.5 cm radius and 5 cm height. [Figure 1] presents the setup geometry used in MC simulation. A field size of 5 × 5 cm 2 was defined at a source-to-surface distance of 20 and 100 cm for kilovoltage and megavoltage X-rays, respectively. The DEFs (the ratio of dose with and without GNP) were computed by placing the gel dosimeter at a depth of 1 cm and 5 cm from the phantom surface, respectively, for kilovoltage and megavoltage X-rays. In the second case, the gel dosimeter was replaced by the tumor and the surrounding water was replaced by the ICRU four component tissues. The MC simulation was repeated for 100 kVp X-rays to verify the dosimetric suitability of polymer gel dosimetry.
Figure 1: Schematic diagram showing the geometry used in the Monte Carlo simulation

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 > Results Top


Variation of dose enhancement factor with gold nanoparticle concentration

The average DEF within the gel dosimeter with different concentrations of GNPs for the therapeutic X-rays are summarized in [Table 1]. For 100 kVp X-rays, average DEF of 1.86 and 2.91 is observed in the gel dosimeter with 7 and 18 mg GNP concentration, respectively. On the other hand, average DEF of 1.69 and 2.61 is recorded for 150 kVp X-rays with 7 and 18 mg GNP concentration, respectively. It is also observed from the data in this table that the DEF increases with the increasing GNP concentration in the gel dosimeter for kilovoltage X-rays. However, no observable dose enhancement is observed for 6 and 15 MV photon beams either for average DEF or DEF at different depths [Figure 2] and [Figure 3].
Figure 2: Variation of dose enhancement factor with depth for 6 MV X-rays at two different gold nanoparticle concentrations

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Figure 3: Variation of dose enhancement factor with depth for 15 MV X-rays at two different gold nanoparticle concentrations

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Table 1: Average DEF for two different concentrations of GNP in gel dosimeter for kilovoltage and megavoltage therapeutic X-rays

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Variation of dose enhancement factor with depth in the gel dosimeter

[Figure 4] shows the comparison of DEF for 7 and 18 mg GNP concentration at 100 and 150 kVp X-rays, respectively. It is observed from this figure that the dose enhancement occurs in the gel dosimeter loaded with GNP while dose reduction takes place in the water region beyond the gel region infused with GNPs. The dose reduction in the water region is proportional to the photon energy and the GNPs concentration in gel dosimeter.
Figure 4: A comparison of dose enhancement factor for 100 and 150 kVp X-rays at different gold nanoparticle concentrations

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Over the gel dosimeter region for 100 kVp X-rays, the DEF decreases by 8.75 and 21% for 7 and 18 mg GNP concentration, respectively. On the other hand, for 150 kVp X-rays, the DEF decreases moderately by 1 and 11% for 7 and 18 mg GNP concentration, respectively. This indicates that the fall-off of DEF over the gel volume is more for 100 kVp X-rays.

Dose enhancement factor in PAGAT gel and tumor for 100 kVp X-ray

The DEF within the PAGAT gel dosimeter and tumor are quantified for 100 kVp X-rays at different GNP concentration levels, and results are presented in [Table 2]. The percentage variation of 0.54 and 1% is observed in the DEF for GNP concentration of 7 and 18 mg. [Figure 5] and [Figure 6] show the variation of DEF within gel dosimeter and tumor at GNP concentration of 7 and 18 mg, respectively. In this figure, the factors shown beyond 6 cm are not the DEFs but show a decrease in the doses behind the gel and tumor loaded with GNPs. This result indicates that the dose enhancement within gel dosimeter and tumor closely matches with each other.
Figure 5: A comparison of dose enhancement factor for polymer gel and tumor at 7 mg gold nanoparticle concentration for 100 kVp X-rays

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Figure 6: A comparison of dose enhancement factor for polymer gel and tumor at 18 mg gold nanoparticle concentration for 100 kVp X-rays

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Table 2: A comparison of average DEF for two different GNP concentrations in gel dosimeter and tumor at 100 kVp X-ray

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 > Discussion Top


Average DEF in the gel dosimeter region with the infusion of GNPs was estimated by MC simulations for therapeutic kilovoltage and megavoltage photon beams. The results show that 100 and 150 kVp X-rays provides dose enhancement by a factor of 2-3 for GNP concentration considered in this study. On the other hand, it would be difficult to achieve such a dose enhancement with high energy photon beams because of the predominance of Compton effect. Furthermore, it is observed that dose enhancement in the gel dosimeter and tumor region are in good agreement with each other. This shows that the polymer gel dosimetry can be very good method of dose estimation and verification for clinical implementation of GNP aided RT.

The aim of the current study was to provide impetus for further investigation, and clinical implementation of GNP-aided RT for many types of tumor that can be treated with external beam therapy. The tumor dose enhancement for this treatment situation would be significant especially when the delivery of a tumor dose becomes difficult due to the limitation of normal tissue tolerance dose. Experimental work to validate such a dose enhancement by GNPs using PGD is currently under investigation.


 > Conclusion Top


The MC simulation was carried out to estimate the dose enhancement in the PGD containing different concentration of GNPs when irradiated with various X-ray beams commonly used in clinical practice. The PGD, PAGAT gel with tissue like elemental composition can be used for the dosimetric feasibility of the GNP-aided RT. This study indicates that GNP aided RT has the potential of delivering very high localized tumoricidal dose with significant sparing of normal structures and organs at risk when the treatment is delivered with low energy X-rays after an introduction of GNPs into the tumor.


 > Acknowledgments Top


The authors are grateful to Dr. D. N. Sharma, Director, Health, Safety and Environment Group, Bhabha Atomic Research Centre (BARC) and Shri D. A. R. Babu, Head, Radiological Physics and Advisory Division (RPAD), BARC for their constant encouragement.

 
 > References Top

1.
Hainfeld JF, Slatkin DN, Smilowitz HM. The use of gold nanoparticles to enhance radiotherapy in mice. Phys Med Biol 2004;49:N309-15.  Back to cited text no. 1
    
2.
Cho SH. Estimation of tumour dose enhancement due to gold nanoparticles during typical radiation treatments: A preliminary Monte Carlo study. Phys Med Biol 2005;50:N163-73.  Back to cited text no. 2
    
3.
De Deene Y, De Wagter C, Van Duyse B, Derycke S, Mersseman B, De Gersem W, et al. Validation of MR-based polymer gel dosimetry as a preclinical three-dimensional verification tool in conformal radiotherapy. Magn Reson Med 2000;43:116-25.  Back to cited text no. 3
    
4.
Vandecasteele J, De Deene Y. Evaluation of radiochromic gel dosimetry and polymer gel dosimetry in a clinical dose verification. Phys Med Biol 2013;58:6241-62.  Back to cited text no. 4
    
5.
Institute of Physics Publishing Journal of Physics: Conference Series 3. Third International Conference on Radiotherapy Gel Dosimetry; 2004. p. 115-21.  Back to cited text no. 5
    
6.
Khadem-Abolfazli M, Mahdavi M, Mahdavi S, Ataei G. Dose enhancement effect of gold nanoparticles on MAGICA polymer gel in mega voltage radiation therapy. Int J Radiat Res 2013;11:55-61.  Back to cited text no. 6
    
7.
Cho SH, Jones BL, Krishnan S. The dosimetric feasibility of gold nanoparticle-aided radiation therapy (GNRT) via brachytherapy using low-energy gamma-/x-ray sources. Phys Med Biol 2009;54:4889-905.  Back to cited text no. 7
    
8.
Zhang SX, Gao J, Buchholz TA, Wang Z, Salehpour MR, Drezek RA, et al. Quantifying tumor-selective radiation dose enhancements using gold nanoparticles: A Monte Carlo simulation study. Biomed Microdevices 2009;11:925-33.  Back to cited text no. 8
    
9.
Kawrakow I, Rogers DW. The EGSnrc Code System, Monte Carlo Simulation of Electron and Photon Transport. Ottawa, Canada: Technical Report No. PIRS -701, National Research Council of Canada; 2006.  Back to cited text no. 9
    
10.
Venning AJ, Hill B, Brindha S, Healy BJ, Baldock C. Investigation of the PAGAT polymer gel dosimeter using magnetic resonance imaging. Phys Med Biol 2005;50:3875-88.  Back to cited text no. 10
    
11.
International Commission on Radiation Units and Measurements (ICRU). Tissue Substitutes in Radiation Units and Measurement, ICRU Report No. 44, Bethesda, USA; 1989.  Back to cited text no. 11
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
 
 
    Tables

  [Table 1], [Table 2]



 

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