

ORIGINAL ARTICLE 



Year : 2011  Volume
: 36
 Issue : 4  Page : 220229 

Dose volume histogram analysis and comparison of different radiobiological models using inhouse developed software
Arun S Oinam^{1}, Lakhwant Singh^{2}, Arvind Shukla^{1}, Sushmita Ghoshal^{1}, Rakesh Kapoor^{1}, Suresh C Sharma^{1}
^{1} Department of Radiotherapy, PGIMER, Chandigarh, India ^{2} Department of Physics, Guru Nanak Dev University, Amritsar, Punjab, India
Date of Submission  18Jan2011 
Date of Decision  28Aug2011 
Date of Acceptance  10Sep2011 
Date of Web Publication  18Nov2011 
Correspondence Address: Arun S Oinam Department of Radiotherapy, Post Graduate Institute and Medical Education and Research, Chandigarh India
Source of Support: None, Conflict of Interest: None  Check 
DOI: 10.4103/09716203.89971
Abstract   
The purpose of this study is to compare LymanKutcherBurman (LKB) model versus Niemierko model for normal tissue complication probability (NTCP) calculation and Niemierko model versus Poissonbased model for tumor control probability (TCP) calculation in the ranking of different treatment plans for a patient undergoing radiotherapy. The standard normal tissue tolerance data were used to test the NTCP models. LKB model can reproduce the same complication probability data of normal tissue response on radiation, whereas Niemierko model cannot reproduce the same complication probability. Both Poissonbased and Niemierko models equally reproduce the same standard TCP data in testing of TCP. In case of clinical data generated from treatment planning system, NTCP calculated using LKB model was found to be different from that calculated using Niemierko model. When the fractionation effect was considered in LKB model, the calculated values of NTCPs were different but comparable with those of Niemierko model. In case of TCP calculation using these models, Poissonbased model calculated marginally higher control probability as compared to Niemierko model.
Keywords: Niemierko model, normal tissue complication probability, Poissonbased model and LymanKutcherBurman model, tumor control probability
How to cite this article: Oinam AS, Singh L, Shukla A, Ghoshal S, Kapoor R, Sharma SC. Dose volume histogram analysis and comparison of different radiobiological models using inhouse developed software. J Med Phys 2011;36:2209 
How to cite this URL: Oinam AS, Singh L, Shukla A, Ghoshal S, Kapoor R, Sharma SC. Dose volume histogram analysis and comparison of different radiobiological models using inhouse developed software. J Med Phys [serial online] 2011 [cited 2020 Jan 23];36:2209. Available from: http://www.jmp.org.in/text.asp?2011/36/4/220/89971 
Introduction   
Evaluation of treatment plans for the determination of best plan among the different plans is done by analysis of dose volume histogram (DVH) as well as twodimensional and threedimensional spatial dose distributions. These plans are further evaluated by calculating the tumor control probability (TCP) and normal tissue complication probability (NTCP) of the treatment plans to determine the radiobiological ranking of different plans amongst them. ^{[1],[2],[3]} This final evaluation of treatment plans can be done by using both cumulative and differential DVH generated by treatment planning system (TPS). Various researchers developed their own inhouse evaluation software for TCP and NTCP calculation. ^{[3],[4],[5],[6]} Some of these models do not consider the fractionation effect in NTCP calculations, ^{[2],[7]} whereas some of the models use the effect of fractionation in radiotherapy treatment in NTCP ^{[5],[6],[8]} and TCP ^{[5],[6],[9]} calculation. The purpose of this study is to develop a comprehensive and userfriendly inhouse computer program for DVH analysis and clinical implementation of NTCP calculation based on LymanKutcherBurman (LKB) model and Poisson distribution model based TCP calculation and its comparison with those of calculations based on Niemierko models. Further, the incorporation of different dose per fraction sizes in LKB model will be tested.
Materials and Methods   
Software requirements and data input/output
A MATLAB^{®} software version 7.1 was used to develop this program. The differential and cumulative DVH data were exported from Eclipse TPS of Varian Medical System, Palo Alto, USA, in ASCII format in dose bin size of 20 cGy and these DVH data were imported in MATLAB software for the estimation of different DVH parameters, TCP and NTCP.
Normal tissue complication probability based on dose response curve
LymanKutcherBurman model
Lyman's formula models the sigmoidshaped dose response curve of NTCP as a function of dose (D) to a uniformly irradiated fractional reference volume (v _{ref} ). The parameters used in this model are TD _{50/5} (dose at which probability of complication becomes 50% in 5 years), m (tissuespecific parameter inversely proportional to the slope of response curve) and n [parameter to find the equivalent uniform dose (EUD) of inhomogeneous irradiation using DVH reduction method proposed by KutcherBurman model]. ^{[10],[11]} The expression of this NTCP is given as
The volumedependent parameter TD _{50/5} (v) for fractional volume v can be expressed in terms of TD _{50/5} (1) of full volume irradiation as
where 0 < n < 1 for all tissues fitted by Burman et al. ^{[7]} The above parameters are fitted on this model by Burman et al. ^{[7]} for the normal tissue tolerance data of highgrade complications associated with full or partial organ irradiation, compiled by Emami et al. ^{[12]} The values used in this study are summarized in [Table 1]. The dose response data of Emami et al. are derived mostly from nominal doses near to 2 Gy per fraction. Dose fractionation effects are not explicitly taken into account in this LKB model calculation of NTCP.  Table 1: Parameters of sigmoidal dose response curve and dose volume histogram reduction scheme used in normal tissue complication probability calculation (LKB and Niemierko model)
Click here to view 
Application of fractionation in LymanKutcherBurman model
The raw data obtained from TPS are of different dose per fraction. The radiobiological effects of such different dose per fraction size are different from those of 2 Gy per fraction for the same radiation dose distribution in an organ. In order to consider the effect of fractionation and size of dose per fraction in the NTCP calculation, the DVH of different doses per fraction is converted into biologically equivalent physical dose of 2 Gy per fraction (EQD _{2} ) using the linear quadratic (LQ) model as
where n_{f} and d_{f} = D/n_{f} are the number of fractions and dose per fraction size of the treatment course, respectively. α/β are the tissuespecific LQ parameters of the organ being exposed. EQD _{2} DVH data obtained using equation (4) were used to calculate the LKB model based NTCP by Kuperman et al., ^{[13]} using equations (1)(3).
Niemierko model
In this model also, the raw data from TPS are converted into the biological equivalent physical EQD _{2} DVH using equation (4). Then, this DVH is converted into the DVH of the whole volume of the organ receiving an EUD, using the DVH reduction method proposed by Kutcher et al. ^{[10]} The EUD, obtained from the conversion of inhomogeneous dose distribution of different partial volume v_{i} receiving the dose D_{i}, is given as
The value of a is equal to 1 when EUD is equal to mean dose. The "a" is a large negative value for tumor as the tumor control depends on the minimum dose received by the tumor. In case of normal tissues such as serial and parallel architectures, the values of a are large positive and small positive values depending on small and large volume effects, respectively. Then, the NTCP of such organ is determined using a logistic function as
where γ_{50} is the slope of sigmoidal dose response curve of normal tissue at 50% complication probability
The tissuespecific parameters given in [Table 1] are used for NTCP calculation based on Niemierko model. ^{[8]}
Tumor control probability
Poisson's model of cell killing
Survival of cell killing by radiation exposure follows the Poisson's distributions. ^{[14]} The probability of survival of clonogenic cell that does not receive any hit (N = 0) after the exposure of radiation dose D is given by
where N_{c}.p(D) is the average number of hits on N_{c} (clonogenic cells) due to small p(D) (probability of hit per cell). If it is assumed that cell killing follows twotarget model of singletrack and multiple track events, the probability of survivability of clonogenic cells after N_{f}, number of exposures of dose per fraction d, is given by
Similarly, TCP depends on the number of survived clonogenic cells N_{s} and small survival fraction p_{s}(D), and TCP is given by the probability of average number of clonogenic cells survived (N_{s} = 0 = N_{c}.p_{s}(D)) as
The number of clonogenic cells can be found out using the following relation according to Niemeirko and Goiten ^{[9]} and Stavrev et al. ^{[15],[16]} [Appendix A]. If the clonogenic cell data are not available, the expression of TCP in equation (10) can also be rewritten in terms of sigmoidal dose response parameters according to Warkentin et al. ^{[4]} and Stavrev et al. ^{[15],[16]} as
where TCD _{50} is the tumor dose required to produce 50% TCP and γ_{50} is the slope of dose response at 50% TCP, which is . For a heterogeneous irradiation of independent subvolumes v_{i} of tumors with dose D_{i}, the overall TCP is given by
Using equation (11), the TCP using Poissonbased model is given by
The tumorspecific parameters used in this study are given in [Table 2]. ^{[17]}  Table 2: Parameters of sigmoidal dose response curve of tumor from Okunieff et al data for TCP calculation
Click here to view 
Niemierko model based on equivalent uniform dose
After converting the tumor DVH data of different dose per fraction size into equivalent physical DVH of 2 Gy per fraction using equation (4), the inhomogeneous dose distribution of different dose bin D_{i} irradiating small volume v_{i} is reduced into an EUD of the whole volume of the tumor using equation (5). The TCP of the tumor ^{[9]} of such dose distribution is given by
Results and Discussion   
Dose volume analysis
The flow charts of MATLAB programs for dose volume analysis and TCP and NTCP calculation software are shown in Appendix B. For DVH analysis and LKB model based NTCP calculation software, the required input data is cumulative DVH, whereas Poisson's model based TCP calculation software uses the differential DVH. In NTCP and TCP calculation using Niemierko model, differential DVHs are used. This software is compatible for any type of DVH. It can convert any type of DVH into a particular DVH depending on the requirement of model to be used for analysis. [Figure 1] shows the output of cumulative DVH of this software, reconstructed from the differential DVH of TPS. This figure also shows percentage difference of calculated cumulative DVH from that of original DVH. The deviations of both the calculated DVHs from those of original DVHs are less than 0.006% except a small spike of −2.35% at an initial dose bin of differential DVH, reconstructed from cumulative DVH. The output of DVH analysis parameters is shown in [Table 3]. The DVH parameters calculated using this software are D _{100} , D _{95} , D _{2/3} , D _{1/2} , D _{1/3} , and D _{1cc} , (dose to 100%, 95%, 66.66%, 50%, 33.33%, 1 cc volume of the organ, respectively). Mean, maximum and minimum dose (D _{mean} , D _{max} and D _{min} ) to the organ are also calculated by it.  Table 3: The difference of MATLAB calculated DVH parameters of an organ from those of TPS
Click here to view 
 Figure 1: Dose volume histogram comparison of TPS calculated cumulative DVH and MATLAB calculated cumulative DVH from differential DVH for bowel. Fractional volume difference between the TPS calculated and MATLAB calculated DVHs
Click here to view 
Validity checking of NTCP calculation using Emami et al.'s data
The output of this comprehensive inhouse developed mfile program of MATLAB software for NTCP and TCP calculation is shown in [Figure 2]. [Table 4] shows the validity checking of normal tissue tolerance data of Emami et al. ^{[12]} NTCP calculation of LKB model for bladder using normal tissue tolerance dose data points of TD _{5/5} (normal tissue tolerance dose of 80 Gy and 65 Gy to 2/3 volume and whole volume of bladder, respectively, for 5% complication occurrence within 5 years of radiation exposure) of Emami et al. ^{[12]} was found as 4.76%, which is approximately equal to 5%, whereas Niemierko model calculated it to be 40.96%. 50% complication of bladder for the data of tolerance dose (TD _{50/5} of 85 Gy and 80 Gy to 2/3 volume and whole volume of bladder, respectively) was found exactly as NTCP of 50% was obtained using LKB model, whereas Niemierko model calculated higher complication probability of 70.12%. In selecting the data point of dose corresponding to volume lesser than 2/3 volume of bladder, it is assumed that any volume lesser than 2/3 volume of bladder receiving the dose corresponding to 2/3 volume of bladder will produce the same radiobiological effects.  Table 4: Validity checking of normal tissue complication probability calculation using Emami et al. (1994) data
Click here to view 
 Figure 2: Output of NTCP and TCP calculation software based on LymanKutcherBurman, Niemierko and Poissonbased model
Click here to view 
Similarly, in case of rectum, NTCP calculation of LKB model using TD _{5/5} and TD _{50/5} of rectum was found to be 4.78% and 50%, respectively, whereas Niemierko model underestimated NTCP to be 0.99% for TD _{5/5} and 50% complication was exactly calculated for TD _{50/5} . The complication probability calculation of spine using LKB model corresponding to TD _{5/5} and TD _{50/5} was found as 6.63% and 45.44%, respectively, whereas those calculated using Niemierko model were found to be 0.40% and 48.17%, respectively. Both TD _{5/5} and TD _{50/5} were overestimated by Niemierko model in case of lung and heart. The overestimations of lung were 86.48% and 99.12% for TD _{5/5} and TD _{50/5} , respectively. Similarly, for heart, TD _{5/5} and TD _{50/5} are calculated as 49.60% and 90.29%, respectively. The values for parotid, ^{[18],[19]} spine and rectum were found to be underestimated as 0.25%, 0.40% and 0.99%, respectively, for TD _{5/5} . However NTCPs of bladder and brainstem were overestimated as 37.91% and 13.58%, respectively, corresponding to TD _{5/5} . In all cases of normal tissues, LKB model reproduces the same complication probabilities of normal tissue tolerance data of Emami et al. ^{[12]}
NTCP calculation output using TPS data
A few brief examples of the output of this software are shown in [Table 5]. These consist of DVH parameters and NTCPs calculated by this software using the normal tissue dose response and tumor dose response parameters. [Figure 3] and [Table 5] show DVH calculation of rectum for four different prostate adenocarcinoma treatment plans. According to relative cumulative DVHs and DVH parameters of rectum, plan (2) has to produce the minimum NTCP and NTCP has to be increased in the order: plan (2), plan (4), plan (3) and plan (1). The NTCPs calculated using LKB models are 2.73%, 2.88%, 3.07% and 4.66%, respectively, in the increasing order for the above order of plans, whereas Niemierko models calculated the NTCPs to be 16.48%, 15.84%, 3.17% and 5.76%, respectively. The first two plans used the number of fractions of 27, whereas the last two plans used the number of fractions of 37. Since the fractionation effect is not taken into account in the LKB model, the first two plans produce lesser NTCPs as compared to the last two plans. But when the fractionation effect is taken into account using equation (4) by converting the cumulative dose of different dose per fraction into the equivalent dose of 2 Gy per fraction, the first two plans predict NTCPs of 12.10% and 12.25%, respectively, whereas the last two plans are estimated to predict 3.04% and 4.95%, respectively, which are approximately predicted by Niemierko model.  Table 5: Normal tissue complication probability for the treatment of different sites from tumor control probability data
Click here to view 
 Figure 3: Cumulative dose volume histograms of rectum of four different plans showing the different dose delivery to rectum
Click here to view 
NTCPs of different organs at risk (bowel and bladder for four different cases of prostate adenocarcinoma treatments; spinal cord, brainstem, ipsilateral parotid, larynx and contralateral parotid for two cases of a head and neck radiotherapy treatment, and spinal cord, heart, liver and lung for two treatment cases of squamous cell carcinoma of esophagus) are also shown in [Table 5]. Similarly, the DVH parameters [Table 5] and cumulative DVH [Figure 4] and [Figure 5] of these organs can predict NTCPs in LKB model. Considering the fractionation effect by Niemierko and LKB models, the calculated NTCPs were comparable to each other in all organs at risk.  Figure 4: Cumulative dose volume histograms of bowel of four different plans showing the different dose delivery to bowel
Click here to view 
 Figure 5: Cumulative dose volume histograms of bladder of four different plans showing the different dose delivery to bladder
Click here to view 
The complication probabilities of ipsilateral parotids were found to be 94.38%, 99.84% and 93.55% for plan (1) and 54.87%, 98.44% and 38.90% for plan (2), when they were calculated using LKB, Niemierko and LKB fractionation models, respectively. DVH parameters also showed relatively larger volume of parotid irradiated to higher dose in plan (1) as compared to plan (2). The magnitudes of NTCPs amongst these three models were comparable in plan (1) but varied largely. Both the LKB models calculated smaller than that of Niemierko model in case of plan (2). This is occrred due to the use of a single value of EUD for the whole volume of organ, derived using KutcherBurman DVH reduction method in Niemierko model. ^{[5]} The decrease in the values of NTCPs of both the LKB models ^{ [2,7]} is due to the considerations of every fractional volumes and the corresponding equivalent doses reduced from physical doses using the same DVH reduction method. Complication probability calculated using LKB fractionation model was lesser than that of LKB model due to the reduction of the physical dose of parotid into a relatively lesser dose of EQD _{2} . But in case of plan (1), EQD _{2} dose of different fractional volumes of DVH was approximately equal to the physical dose.
TCP calculation
[Table 6] presents the calculated values of TCPs of TPS DVH data using Poissonbased model and Niemierko model for the treatment of adenocarcinoma of prostate, squamous cell carcinoma of oropharynx and esophagus tumor. The TCP values calculated using Poissonbased model were marginally larger than those of Niemierko model (within 5%), except the lesser estimation (within 0.6%) for macroscopic tumor of oropharynx and esophagus tumor and microscopic tumor of adenocarcinoma of prostate (within 0.06%). When the DVHs reconstructed from Okunieff et al.'s data ^{[17]} were used for TCP calculation, 50% TCPs of microscopic ^{[20]} and macroscopic tumor of adenocarcinoma ^{[17],[21]} of prostate were reproduced as 48.31% and 50.25% by both Poisson and Niemierko models. Both the TCP calculation models calculated the same TCP values of 49.32% for all microscopic tumors of squamous cell carcinoma. ^{[17]} In case of squamous cell carcinoma of macroscopic tumor of head and neck ^{[22],[23],[24],[25]} and esophagus, ^{[26],[27],[28]} TCP values were calculated as 49.86% and 49.32%, respectively, by both Poisson and Niemierko TCP calculation models.
Conclusion   
This software developed using MATLAB platform can be used as a userfriendly program to estimate the DVH parameters, TCP and NTCP values, for the ranking of different plans. From the above discussion, it can be concluded that Niemierko model cannot predict the same normal tissue complication data of Emami et al., ^{[12]} whereas LKB model can predict the same complication data. Both Poissonbased model and Niemierko model for TCP calculation equally reproduced the same TCP of Okunieff et al.'s data. ^{[17]} But in case of clinical data generated from TPS, NTCPs calculated using LKB model were found to be different from those of Niemierko model. When the fractionation effect is considered in LKB model, the calculated NTCPs were lesser than those of LKB model which does not take into account fractionation, but both LKB and Niemierko models were comparable to each other. In case of TCP calculation using these models, Poissonbased model calculated marginally higher control probability as compared to Niemierko model.
References   
1.  Langer M, Morrill SS, Lane R. A test of the claim that plan rankings are determined by relative complication and TCP. Int J Radiat Oncol Biol Phys 1998;41:4517. [PUBMED] [FULLTEXT] 
2.  Lyman JT. Complication probability as assessed from dose volume histogram. Radiat Res Suppl 1985;8: S139. [PUBMED] 
3.  Wu Q, Mohan R, Niemierko A, SchmidthUllrich R. Optimization of IMRT plans based on equivalent uniform dose. Int J Radiat Oncol Biol Phys 2002;52:22435. 
4.  Warkentin B, Stavrev P, Stavreva N, Field C, Fallone BG. A TCP and NTCP estimation module using DVHs and known radiobiological models and parameter sets. J Appl Clin Med Phys 2004;5:5063. [PUBMED] 
5.  Gay H, Niemierko A. A free program for calculating EUDbased NTCP and TCP calculation in external beam radiotherapy. Physica Medica 2007;2:11525. 
6.  SanchezNieto B, Nahum AE. BIOPLAN: Software for biological evaluation of radiotherapy treatment plans. Med Dosim 2000;25:716. [PUBMED] [FULLTEXT] 
7.  Burman C, Kutcher GJ, Emami, Goiten M. Fitting of normal tissue tolerance data to an analyticfunction. Int J Radiat Oncol Biol Phys 1991;21:12335. 
8.  Niemierko A, Goiten M. Modeling of normal tissue response to radiation critical volume model. Int J Radiat Oncol Biol Phys 1993;25:13545. 
9.  Niemierko A, Goiten M. Implementation of a model for estimating TCP for an inhomogeneously irradiated tumor. Radiother Oncol 1993;29:1407. 
10.  Kutcher GJ, Burman C, Brewster L. Histogram reduction method for calculating complication probabilities for three dimensional treatment planning evaluations. Int J Radiat Oncol Biol Phys 1991;21:13746. 
11.  Kutcher GJ, Burman C. Calculation of complication probability factors for nonuniform normal tissue irradiation: The effective volume method. Int J Radiat Oncol Biol Phys 1989;16:162330. [PUBMED] 
12.  Emami B, Lyman, Brown A. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1994;21:10922. 
13.  Kuperman VY. General properties of different models used to predict normal tissue complications due to radiation. Med Phys 2008;35:48316. 
14.  Feller W. An introduction to probability theory and its applications. Vol. 1, 2 ^{nd} ed. New York: NY: Wiley and Sons; 1957. p. 1423. 
15.  Stavrev N, Stavrev P, Warkentin B, Fallone BG. Derivation of the expression for g50 and D50 for different individual TCP and NTCP models. Phys Med Biol 2002;47:3591604. 
16.  Stavrev P, Stavrev N, Niemierko A, Goiten M. Generalization of a model of tissue response to radiation based on the idea of functional subunits and binomial statistics. Phys Med Biol 2001;46:150118. 
17.  Okunieff P, Morgan D, Niemierko A, Suit HD. Radiation doseresponse of human tumors. Int J Radiat Oncol Biol Phys 1995;32:122737. [PUBMED] [FULLTEXT] 
18.  Eisbruch A, Ten Haken RK, Kim HM, Marsh LH, Ship JA. Dose, volume, and function relationships in parotid salivary glands following conformal and intensitymodulated irradiation of head and neck cancer. Int J Radiat Oncol Biol Phys 1999;45:57787. [PUBMED] [FULLTEXT] 
19.  Chao KS, Deasy JO, Markman J, Haynie J, Perez CA, Purdy JA. A prospective study of salivary function sparing in patients with headandneck cancers receiving intensitymodulated or threedimensional radiation therapy: Initial results. Int J Radiat Oncol Biol Phys 2001;49:90716. 
20.  Chu FC, Lin FJ, Kim JH, Huh SH, Garmatis CJ. Locally recurrent carcinoma of the breast. Cancer 1976;37:267781. [PUBMED] 
21.  Burstein FD, Calcaterra TC. Supraglottic laryngectomy: Series report and analysis of results. Laryngoscope 1995;95:8336. 
22.  Hanks GE. Optimizing the radiation treatment and outcome of prostate cancer. Int J Radiat Oncol Biol Phys 1985;11:123545. [PUBMED] 
23.  Khafif RA, Rafla S, Tepper P. Effectiveness of radiotherapy with radical neck dissection in cancers of the head and neck. Arch Otolaryngol Head Neck Surg 1990;117:19609. 
24.  North CA, Lee DJ, Piantadosi S, Zahurak M, Johns ME. Carcinoma of the major salivary glands treated by surgery or surgery plus postoperative radiotherapy. Int J Radiat Oncol Biol Phys 1990;18:131926. [PUBMED] 
25.  Fletcher GH. Clinical doseresponse curves of human malignant epithelial tumours. Br J Cancer 1973;46:112. 
26.  Akakura I, Nakamura Y, Kakegawa T, Nakayama R, Watanabe H, Yamashita H. Surgery of carcinoma with preoperative radiation. Chest 1970;57:4757. [PUBMED] [FULLTEXT] 
27.  Kasai M, Mori S, Watanabe T. Followup results after resection of thoracic esophageal carcinoma. World J Surg 1978;2:54351. [PUBMED] 
28.  Whittington R, Coia LR, Haller DG, Rubenstein JH, Rosato EF. Adenocarcinoma of the esophagus and esophagogastric junction: The effects of single and combined modalities on the survival and patterns of failure following treatment. Int J Radiat Oncol Biol Phys 1990;19:593603. [PUBMED] 
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
This article has been cited by  1 
Transformation of Physical DVHs to Radiobiologically Equivalent Ones in Hypofractionated Radiotherapy Analyzing Dosimetric and Clinical Parameters: A Practical Approach for Routine Clinical Practice in Radiation Oncology 

 Zoi Thrapsanioti,Irene Karanasiou,Kalliopi Platoni,Efstathios P. Efstathopoulos,George Matsopoulos,Maria Dilvoi,George Patatoukas,Demetrios Chaldeopoulos,Nikolaos Kelekis,Vassilis Kouloulias   Computational and Mathematical Methods in Medicine. 2013; 2013: 1   [Pubmed]  [DOI]   2 
Dosimetric comparison of standard threedimensional conformal radiotherapy followed by intensitymodulated radiotherapy boost schedule (sequential IMRT plan) with simultaneous integrated boostIMRT (SIB IMRT) treatment plan in patients with localized carcinoma prostate 

 Bansal, A., Kapoor, R., Singh, S.K., Kumar, N., Oinam, A.S., Sharma, S.C.   Indian Journal of Urology. 2012; 28(3): 300306   [Pubmed]  


