The Use Of Radiotherapy Biology Essay

Published:

This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.

1.1. Introduction:

Recently, the use of radiotherapy has grown rapidly due to increasing demand. One of the most utilised fields is in treating cancer because radiotherapy has the advantage in that it has been claimed to be superior to other cancer treatments such as chemotherapy and surgery. However, one of the main issues related to radiation treatment is the level of uncertainty which is still challenging radiotherapists. This is partly related to the prescribed dose and treatment results, as the uncertainty of the delivered dose is agreed to be up to 3%. Although much of the uncertainty has been overcome by applying a modern 3D treatment planning system, too many dose calculation errors occur in the surrounding heterogenic tissues. The most common cause of these errors is the approximations of the calculation algorithm used (Krieger and Sauer 2005).

Several novel techniques have been introduced to this field to overcome these problems, such as Photon beams, pencil beams (PB) and superposition/convolution techniques, such as collapsed cone, and are the most contemporary calculation algorithms used in 3D planning systems. However, In the case of PB algorithms, it has been shown that incompetence sometimes occurs when using PB algorithms in inhomogeneous tissues. One explanation for this is that in PB algorithms, one dimension is usually used to correct the density, which obviously does not take into account exactly the distribution of secondary electrons in the area of inhomogeneous tissues. In the delivered beam, the calculation considers the percentage depth dose from the radiation source to the target, while the consequences of scatter or side radiation are not taken into consideration (Krieger and Sauer 2005). Therefore, further investigations and understanding of the effect of the radiation on the tissues is still greatly required. This study aims to explore the effect of the ionising radiation beam on the meiotic oocyte spindles.

The massive developments in computer technology have introduced further advances in the medical field. One of the main applications of the computer is the Monte Carlo technique, which has been agreed upon as being one of the best methods for dose calculations in the radiotherapy planning system. It has been claimed that using the Monte Carlo simulation mainly for intensity modulated radiotherapy could improve the accuracy of radiotherapy treatment. Currently, the Monte Carlo codes can be used for many different purposes, including for radiotherapy simulation such as Electron Gamma shower version4 (EGS4). The EGS4 code system is well known as a very accurate tool for dosimetry in radiation treatment. (Li and et al. 2000).

This study was carried out firstly, by employing Monte Carlo code simulation to validate the procedures which are confirmed to be the very best standard in dose calculation (Krieger and Sauer, 2005). A phantom with the point source from the front with rectangular collimation was used. Next, the phantom was constructed based upon the proposed real phantom by using graphical user interface 1.1 GUI software. Later on, after achieving satisfactory validations and construction, preparations were made for the oocytes to be irradiated. They were then examined under a confocal laser scanning microscope (CLSM) to examine the effect of the prescribed doses on the oocytes spindles. Generally, it has been reported that any dose above 0.5 Gy could cause cell proliferation and induce cell apoptosis, while less than 0.5 Gy could possibly enhance the proliferation (see fig 1 ). (Li and et al. 2000; Liu 2002)

Figure (1) Proliferation of cells after irradiation

Prior studies note the effect of the radiation on the spindle, and state that the ionising radiation may prevent the synthesis of a protein that forming the mitotic spindle (Walters & Petersen, 1968; Rustad et al., 1975; Dubravsky et al., 1976; Dubravsky & Withers, 1976, 1978). In contrast, Noland et al. (1974) suggest that there is no clear effect on protein synthesis, shown by microtubules of Chinese hamster ovary cells irradiated by X-radiation. Another report explains that the formation of the microtubules does not necessitate protein production, other than playing a dynamic equilibrium role between the microtubule and a pool of its subunit. As a result, the depolymerisation of the microtubules occurs when the radiation strikes the microtubular protein that appears in the pool, which could lead to dynamic imbalance. Further investigation has shown that the radiation does not result in obvious damage in causing microtubular protein degradation on molecular level. A study carried out by Zaremba and Irwin (1981) has shown that irradiation of the tubule spindles by gamma radiation leads to conformational alteration through reducing the capability of the tubulin dimmer to contribute to the nucleation and elongation process of polymerisation (Zaremba and Irwin 1981).

Furthermore, it has been suggested that if microtubules have been broken by radiation, then compared with the control microtubules sample, the following variations can be noticed. The length of the irradiated microtubules should be shorter than the control. Furthermore differences in the viscosity level are possibly more in the unirradiated sample (Coss, Bamburg et al. 1981).

Outline of the dissertation:

This project has been divided into four chapters. The first chapter is the Introduction; The Monte Carlo method follows next, and includes background, methodology, results and discussion sections. The third chapter will cover cell irradiation in the same layout as the previous chapter, and in the final chapter, a conclusion will be given.

Chapter two

Monte Carlo method

Section one

2.1. The Background of the Monte Carlo code

2.1.1 History of DOSXYZnrc

DOSXYZ started out as a code, in March 1986, when Dave Rogers wrote it to demonstrate to Ralph Nelson that coding of rectilinear voxels could be performed faster than with Ralph's more general macros. The main aim of Dave Roger's demonstration was to perform an estimation of the time needed to completely run a Monte Carlo treatment planning estimation, and this went on to be published in a book. That was considered to be the foundation of the Monte Carlo code. Later on, it was modified and updated frequently and became accessible via one website until 2000. Next, the code was taken up by the MMEGA project which added more adaptations and updated source routines. Updating the code went still further, such as reducing the array space used by the code and introducing beam feature input. Blake Walter made great efforts to develop the code; in 1996, he added CT reading ability and the DOSXYZ code was made smaller by separating out the ctcreate code in 1997. Another option which was added in 1998 was to minimise the modelling period for depth dose curve and dose profiles dose, in addition to inserting a code for parallel simulation.

In 2001, DOSXYZ code was ported by Blake Walters with assistance of Iwan Kawrakow on the EGSnrc system- then called DOSXYZnrc. Also, the standard batch approach was replaced with much developed statistical analysis routines.

In 2004, to use DOSXYZnrc in a Windows based operating system for the first time, while it was exclusively run under Linux/Unix after porting of DOSXYZnrc to the EGSnrcMP system by Blake Walters and Iwan Kawrakow.

2.1.2. Radiation Dosimetry

Any radiation dosimetry in a patient requires consideration of a number of factors that are involved in the whole process; for instance, distribution of the energy charge, location and direction of the beam.

There are many ways that have been used to characterise the distribution of the particles: "use of empirical or semiempirical source models with parameters determined from measurements only; use of compact representations of phase-space data obtained from full treatment head simulations, possibly containing free parameters adjustable to match measurements; and direct use of the full phase-space data from treatment head simulations typically stored in phase-space files"(Kawrakow and Walters 2006)

A further method, which may have the most accurate beam features, is by following the settings of the electron beam hitting the bremsstrahlung target or vacuum exit window, and this has been detected by comparing the experiments.

Nevertheless, the utilising of phase-space files is unmanageable in a practical sense for many reasons. First, there is a need for huge disk space to store particle data when more than one source of particles is required, for example to achieve low uncertainty when selecting small voxels. Secondly, when making any changes in the geometry, such as jaws or multileaf collimator, it is necessary to recreate phase-space files. One of the most challenging issues involves retrieving phase-space data through a network file system.(Kawrakow and Walters 2006).

2.1.3. Use of Megavoltage Beams

The use of megavoltage beams in radiotherapy has become widely used. With such energy beams, it is crucial to know about the energy spectra and angular distribution of the beam. This awareness is essential for radiation dosimetry. One of the main advanced methods for dosimetry purposes is the use of the Monte Carlo code. The Monte Carlo method enables the radiotherapist to obtain angular quantities and distributions which cannot be measured in experiment. Also, it facilitates generating an energy spectrum in an area away from the centre of the beam, rather than the central area. Another important feature of applying Monte Carlo is the fact that it has been possible to achieve savings in the labour force due to much of the work being carried out on a PC. For instance, installing Monte Carlo software on a computer means it can be used for all accelerators with the same geometries.

In fact, it is possible to obtain accurate energy spectra by relying on the Monte Carlo method, and the shape of the treatment head can be accurately simulated. Monte Carlo software can be used to generate energy spectra and angular distributions, and then to calculate dose distributions. Accuracy is obtained in dose calculations by considering the transportation of the photon and electron. (Mohan, Chui et al. 1985)

Furthermore, one of the most accurate tools for ionising radiation dosimetry is the Monte Carlo simulation. Hence, it has been extensively considered and used by radiotherapist for clinical radiation treatments.

2.1.4. Advantages of Monte Carlo

The invention of new novel dose measurement methods is very much needed because of the drawbacks of analytical methods when using 3-D implementation of the pencil beam algorithm, as it suffers from unacceptable uncertainty (about 10%) from a radiotherapist's point view- particularly in heterogeneous tissues. Therefore, there is a tendency to utilise Monte Carlo codes for radiation dosimetry. There are two main stages involved in using Monte Carlo simulation in radiotherapy treatments. These are simulation of the linear accelerator head, and simulation of the patient. The modelling of the linear accelerator head varies because each machine has different detailed devices, and the electron beam features may vary as well. Consequently, these variations could play an important role in the final beam characterisation and dose distribution.

The National Research Council of Canada has developed a code which is an EGS4 user code (Rogers et al., 1995,(Lin, Chu et al. 2001)and (Mesbahi 2007)

2.1.5. Limitation of DOSXYZ code

The DOSXYZ code does not support advanced multiple-source models to be used as a source input for electrons and photons. Also, the number of beam modifiers in patient simulation excludes, for example, wedge, compensator and jaws. There is no variety for choosing the geometry coordinates from two definitions as in the MCDOSE code. Furthermore, the DOSXYZ code cannot make dose volume histograms. Monte Carlo inverse planning cannot be achieved by the DOSXYZ code, either for photon or electron beams(Li and et al. 2000).

2.1.6. Types of the Monte Carlo code

One of the main codes based on EGS4 Monte Carlo simulation is DOSXYZ. Also, it is considered to be a very useful method for the calculation of dose distribution in phantom rectilinear voxels. However, the main disadvantage of the DOSXYZ code is that the simulations are not fast enough on current PCs' hardware; therefore, it takes a long time for a simulation to be completed. Even so, there are many codes that have been introduced and are available to enhance the DOSXYZ code speed, for instance Voxel Monte Carlo (VMC and XVMC) and Super Monte Carlo (SMC), although more careful confirmation and development might be required for radiation treatment dosimetry. The main features of the DOSXYZ code are the capability to simulate the transfer of both the electron and photon beams in a three dimensional phantom. The volume of the phantom is counted in voxel units, which is rectilinear, and the shape of the phantom can vary in three dimension. Also, the material of the phantom can be determined by the user, and the source model is supported in DOSXYZ code simulation. Several researches have involved using the Monte Carlo code for examining the influence of the linac head components on the beam features. Monte Carlo simulation has proved to be a reliable method in radiation treatment dosimetry. (Li and et al. 2000)

2.1.7. Compiling and running DOSXYZnrc

The DOSXYZnrc files are mainly located in the directory $HEN HOUSE/user codes/dosxyznrc. It is possible to compile and run DOSXYZnrc code from graphical user interface (GUI) by selecting Compile from the Run menu, but before running the code, it has to load create an input file. Also, there is an option to carry out an individual run or parallel run by selecting run or submitting queue (Walter and et al. 2009).

2.1.8. DOSXYZnrc Input Parameters

2.1.8.1. Descriptions in DOSXYZnrc Source Code

2.1.8.1.1. Point Source Rectangular Beam Incident from Front

The radiation point source is located on the Z-axis. The incident of the beam is assumed to be from the front side of the phantom. However, it is allowed to set the distance between the source and the phantom and it can be either symmetric or asymmetric. In Monte Carlo code simulation, the media between the source and the phantom is assumed to be a vacuum for the source. Fig 2 illustrates the simulation of incident for the point source beam on the phantom(Walter and et al. 2009)..

Figure (2) Point source incident from the front (isource=3). The isotropically-radiating point source is located on the Z-axis at distance ssd above the phantom. The source is collimated to a rectangular field(Walter and et al. 2009)..

2.1.9. Other Input Variables

This section provides descriptions of main DOSXYZnrc input variables not covered above.

2.1.9.1. IPHANT

The DOSXYZnrc creates phantom data to an egsphant file if the IPHANT is set to one. After choosing a CT phantom, this option is unavailable because the option is an input file from ctcreate(Walter and et al. 2009)..

2.1.9.2. MAX20

To output a summery on the screen of a maximum 20 doses in the phantom then MAX20 has to be set to one. This option is useful for timing/efficiency studies(Walter and et al. 2009)..

2.1.9.3. NCASE

This option shows the value of the histories for running a simulation where the minimum number for simulation is 100, which is the default(Walter and et al. 2009)..

2.1.9.4. IWATCH

This option controls results to the display during implementation of the beam. The input can be from zero to four(Walter and et al. 2009)..

2.1.9.5. TIMMAX

This selection is to set the maximum simulation time allowed to run in hours by CPU time(Walter and et al. 2009)..

2.1.9.6. INSEED1, INSEED2

These fields refer to random value seeds utilised to compute the random number creator(Walter and et al. 2009)..

2.1.9.7. ESAVE GLOBAL

This option is the highest megavolts energy to be run. This is useful when it is possible to create bremsstrahlung from high energy electrons as it can prevent cessation of such high energy(Walter and et al. 2009)..

2.1.9.8. n split

This is used to manage the photon splitting option.

2.1.9.9. ihowfarless

HOWFAR is the geometric coding part of EGS4 (Nelson et al., 1985) from a Monte Carlo simulation of a clinical linear accelerator.

It is recommended to use HOWFARLESS in all non heterogonous phantom calculations. To use the HOWFARLESS algorithm for transport in the phantom, it is necessary to set ihowfarless to one. The benefit of using the algorithm is to improve the efficiency of dose calculations. However, this efficiency is influenced by many factors, such as energy phantom voxel size and the source type. For instance, the effectiveness could reach 30% when using photon beams(Walter and et al. 2009)..

2.1.9.10. ECUTIN

This is utilised beside the global ECUT input to determine the global electron cut-off energy in MeV.

Setting of ECUT varies depending on the type of calculation needed. In the case of radiotherapy, for treatment beams due to low energy electrons using a small dose in the phantom, the ECUT can be very high. For most work considered, it uses ECUT=0.700 MeV, but a lower number can be used when the dose of the monitor chamber is crucial in calculation(Walter and et al. 2009).

2.1.9.11. PCUTIN

Similar to ECUTIN, this is utilised beside the Global PCUT to specify the global photon cutoff energy in MeV. It is the photon equal of ECUTIN. Nevertheless, it may neglect the exact number of the global PCUT because such low amounts do not take long. It is recommended to use the value 0.01MEv (Walter and et al. 2009).

2.1.9.12. Dose Normalisation

This depends on the type of source that is being used. For any source (such as point source from the front with rectangular collimation) with a well-defined beam field size on the phantom surface side, dose normalisation can be calculated by the incident particles fluence (Ainflu) by:

Ainflu = (NCASE + ncaseold − nmissm) / ((xinu − xinl) * (yinu − yinl))

Where:

NCASE: value of the current histories.

ncaseold: value of the previous histories.

nmissm: the total amount any missed particles from the source, as well as in any previous runs.

(xinu - xinl)*(yinu - yinl) is the beam size.

However, if the incident beam size is equal to zero, dose normalisation is calculated by: NCASE+ncaseold-nmissm (Walter and et al. 2009)..

2.1.9.13. Cross-Section Data - PEGS4

"Cross-section data for many commonly-used media are included in EGSnrc installation in the files 521icru.pegs4dat and 700icru.pegs4dat, both located in the $HEN_HOUSE/pegs4/data directory. The file 521icru.pegs4dat consists of cross-section data from a lower electron energy, AE, of 0.521 MeV to an upper electron energy, UE, of 55 MeV, while 700icru.pegs4dat contains data from AE=0.700 MeV to UE=55 MeV. In both files the lower photon energy, AP, is 0.01 MeV and the upper photon energy, UP, is 55 MeV. These data are based on the density effect corrections in ICRU Report 37" (Walter and et al. 2009).

2.1.9.14. Photon splitting

This algorithm technique was proposed by Kawrakow and Fippel and is found to enhance the efficiency of photon beam simulation by a factor of about 5, using xVMC. Also, a photon splitting algorithm has been utilised in DOSXYZnrc in 2002 and found to improve the dose efficiency by around 20%.(Kawrakow and Walters 2006)

Efficiency Calculations

The efficiency of a Monte Carlo simulation is defined as:

E= 1/(S2 * T)

Where:

S: the uncertainty on the quantity of interest.

T: the CPU time required to achieve this uncertainty.

Section Two

Methodology

All Monte Carlo simulations were carried out on a 2.2 GHz Intel Core 2 Duo CPU supplied with 3.00 GB RAM under Microsoft Windows 7 Ultimate 64-bit version. The hardware used was Fujitsu Siemens AMILO Si 2636 notebook produced by Fujitsu Siemens computer.

2.2.1. Validation of point source model:

As a part of any scientific experiment, it is vital to validate the procedure. There is no exception in radiotherapy research. Therefore, one of the main parts of this research is to validate the procedure. The validation process was carried out by using the Monte Carlo simulations and then comparing the depth dose profile for 20 * 20 cm2 filed with real data (Table no. ), which was obtained from Singleton hospital Medical Physics and Clinical engineering quality system.

Depth (cm)

Equivalent square Field size at surface (cm) 20

Depth (cm)

Equivalent square Field size at surface (cm) 20

1.5

100

11

67.2

2

98.6

12

64.1

3

95.3

13

61.2

4

91.5

14

58.2

5

87.9

15

55.5

6

84.2

16

52.8

7

80.7

17

50.3

8

77.1

18

47.9

9

73.7

19

45.6

10

70.4

20

43.4

Table (1)Central Axis percent depth dose (%DD) for open (Plain) fields at 100cm SSD 6MV X

In brief, the calculation for 6MV photons was carried out using the DOSXYZnrc code. The source surface distance (SSD) was set at 100cm, and point source was used in this simulation.

The Dosxyznrc graphical user interface 1.1software was used to run this validation. After running the software, a new inputs file was started as follows:

a. Selection of 512icru.pegs.4dat from Browse Hen_House PEGS4 date

b. Naming of the files with titles such as "validation"

c. Defining the Phantom:

A water media was used as a phantom, along with air media in this simulation. The phantom dimensions (X,Y ,Z, where X is the length, Y is the width and Z is the depth) are 30 * 30 *40 cm3 where for field size they are 20 * 20 cm2.

i. Global electron cutoff energy : 0.521 MeV

ii. Global photon cutoff energy : 0.001 MeV

iii. Print summery of highest 20 doses: no

iv. Non CT data input

v. Define the phantom by:

1. defining x voxel individually. Number of X voxel 3. Then entering the x voxel spacing in cm as follow :-20:-1:1:20

2. defining y voxel as individually. Number of Y voxel 3. Then entering the y voxel spacing in cm as follow :-20:-1:1:20

3. defining Z voxel as individually. Number of Z voxel 4. Then entering the minimum z value (= zero) and entering the width of each group spacing in cm as follows table (2):

Z width

Number in group

1

2

0.5

1

1

28

9.5

1

vi. Define medium :

1. selection of media number: 1

2. choosing medium type: H2O521ICRU

3. Set media of voxels table (3) :

From x

To x

From y

To y

From z

To z

Density

1

20

1

20

1

20

1.0

vii. Output: Select the voxel for which to this list the dose table (4) :

From x

To x

From y

To y

From z

To z

Scan

2

2

2

2

1

20

Y scan per page

d. Source parameter:

i. Incident particles : photon

ii. Source type: point source from the front with rectangular collimation:

1. Lower x bound : -10 cm

2. Upper x bound : 10 cm

3. Lower y bound : -10 cm

4. Upper y bound : 10 cm

5. Source to surface distance SSD : 100 cm

6. Then choosing spectrum file name: mohan6.spectrum

e. Simulation parameter:

i. Number of histories: It was changed until 2% uncertainty was obtained in the results file in the z bound number 10. To get 2 % uncertainty, the % in the z bound number 10 was divided by 2 % before multiplying the results with the current histories. Repeated if necessary to get 2 % uncertainty.

ii. IWATCH output: none

iii. Maxim CPU time (hour): 0.99

iv. RNG seed1: 33

v. RNG seed2:97

vi. Incident beam size : 100.0

vii. Run option: first time

viii. Howfarless: off

ix. Output restart data: after every patch:

x. Range rejection: off

xi. Photon splitting number: 1

xii. Run job parallel: no

2- Running the simulation after saving the input parameter.

3- After finishing the run: Open the file named validation with MS excel and look at the results in the z bound number

4- After that Normalisation was done.

5- Then the depth value was plotted against the equivalent square field size at the surface

6- Plot the data obtained from Singleton Hospital in the same graph to see the validation.

2.2.2. Construction of the phantom

After completing the validation process, the task began to construct the phantom. It was first made using a manual drawing of a phantom, including dividing the phantom and the media by voxels unit in x, y and axis (attached in the appendices). It then used in Dosxyznrc graphical user interface 1.1software for the construction.

The calculation of 6MV photons was performed using DOSXYZnrc code. The source surface distance (SSD) was set at 95cm. The point source on the z-axis was used to perform the simulation of the original beam.

The details of the construction were carried out after starting with creating new input files, as follows:

a. Selection of 512icru.pegs.4dat from Browse Hen_House PEGS4 date

b. Naming of the file titles "construction"

c. Defining the Phantom:

A water media was used as a phamtom, as well as air media, in this simulation. The phantom dimensions (X,Y ,Z, where X is the length, Y is the width and Z is the depth) are 40 * 40 * 17.5 cm3 where for field size they are 30 * 30 cm2.

i. Global electron cutoff energy : 0.521 MeV

ii. Global photon cutoff energy : 0.001 MeV

iii. Print summery of highest 20 doses: no

iv. Non CT data input

v. Define the phantom by:

1. Defining x voxel as groups . Number of X voxel 3. Then entering the minimum x value (-15) and entering the width of each group spacing in cm as follows table (5) :

X width

Number in group

13

1

1

4

13

1

2. Defining y voxel as groups. Number of Y voxel 3. Then entering the minimum y value (-15) and entering the width of each group spacing in cm as follows table (6):

Y width

Number in group

11

1

1

8

11

1

3. Defining Z voxel as groups. Number of Z voxel 4. Then entering the minimum z value ( zero) and entering the width of each group spacing in cm as follows table (7):

Z width

Number in group

5

1

2

1

0.25

2

10

1

vi. Define medium:

1. selection of media number: 2

2. choosing medium type: H2O521ICRU and AIR521ICRU

3. Set media of voxels table (8) :

From x

To x

From y

To y

From z

To z

Medium

Density

1

6

1

10

1

4

H2O521ICRU

0

2

5

1

10

1

1

AIR521ICRU

0

2

5

1

1

2

3

AIR521ICRU

0

2

5

10

10

2

3

AIR521ICRU

0

vii. Output: Select the voxel for which to list the dose table (9):

From x

To x

From y

To y

From z

To z

Scan

2

5

2

9

3

4

z-scan per page

d. Source parameter:

i. Incident particles : photon

ii. Source type: 3-point source from the front with rectangular collimation:

1. Lower x bound : -9.5 cm

2. Upper x bound : 9.5 cm

3. Lower y bound : -9.5 cm

4. Upper y bound : 9.5 cm

5. Source to surface distance ssd : 95 cm

6. Then choosing spectrum file name: mohan6.spectrum

e. Simulation parameter:

i. Number of histories: This was changed until 2% uncertainty was obtained in the results. To get 2% uncertainty, the % in the y bound number 10 was divided by 2% then the results were multiplied with the current histories. Repeat if necessary to get 2 % uncertainty.

ii. IWATCH output: none

iii. Maxim CPU time (hour): 0.99

iv. RNG seed1: 33

v. RNG seed2:97

vi. Incident beam size : 100.0

vii. Run option: first time

viii. Howfarless: off

ix. Output restart data: after every patch :

x. Range rejection: off

xi. Photon splitting number: 1

xii. Run job parallel: no

7- Running the simulation after saving the input parameter.

8- After finishing the run, open the file named construction with MS excel and look at the results in the y bound number.

9- Plot the results to get the dose distribution.

Figure (3) shows a simple schematic of the DOSXYZnrc phantom geometry

Section three

Results and discussion

Depth (cm)

Measured data by Med.Phys

M C simulation of

Percentage depth dose

Depth (cm)

Measured data by Med.Phys

M C simulation of

Percentage depth dose

1.5

100.00%

100.00%

11

67.20%

69.14%

2.25

99%

106.35%

12

64.10%

65.98%

3

95.30%

99.46%

13

61.20%

62.94%

4

91.50%

93.44%

14

58.20%

57.79%

5

87.90%

94.09%

15

55.50%

58.76%

6

84.20%

84.69%

16

52.80%

54.10%

7

80.70%

83.80%

17

50.30%

52.35%

8

77.10%

79.09%

18

47.90%

48.56%

9

73.70%

75.63%

19

45.60%

47.82%

10

70.40%

73.16%

Table (10) Comparison of percentage depth dose of MC simulation with measured data by Singleton Hospital medical physics for Central Axis percent depth dose (%DD) for open (Plain) fields at 100cm SSD 6MV X

Figure (10)Comparison of percentage depth dose of MC simulation with measured data by Singleton hospital medical physics for Central Axis percent depth dose (%DD) for open (Plain) fields at 100cm SSD 6MV X

These results could suggest that , evaluation of measured and calculated data shows acceptable agreement. Also, Monte Carlo simulation has been reported as a gold standard for radiation dosimetry. These results agreed with previous studies that considered a MC as one of the most accurate tool for radiation measurements (Li and et al. 2000).

Figure (11) Dose distribution calculated by Monte Carlo.

The results of dose distribution the relationship between measured and calculated data. The MC shows acceptable results compared with measured data because the deviations were in the required percentage.

Writing Services

Essay Writing
Service

Find out how the very best essay writing service can help you accomplish more and achieve higher marks today.

Assignment Writing Service

From complicated assignments to tricky tasks, our experts can tackle virtually any question thrown at them.

Dissertation Writing Service

A dissertation (also known as a thesis or research project) is probably the most important piece of work for any student! From full dissertations to individual chapters, we’re on hand to support you.

Coursework Writing Service

Our expert qualified writers can help you get your coursework right first time, every time.

Dissertation Proposal Service

The first step to completing a dissertation is to create a proposal that talks about what you wish to do. Our experts can design suitable methodologies - perfect to help you get started with a dissertation.

Report Writing
Service

Reports for any audience. Perfectly structured, professionally written, and tailored to suit your exact requirements.

Essay Skeleton Answer Service

If you’re just looking for some help to get started on an essay, our outline service provides you with a perfect essay plan.

Marking & Proofreading Service

Not sure if your work is hitting the mark? Struggling to get feedback from your lecturer? Our premium marking service was created just for you - get the feedback you deserve now.

Exam Revision
Service

Exams can be one of the most stressful experiences you’ll ever have! Revision is key, and we’re here to help. With custom created revision notes and exam answers, you’ll never feel underprepared again.