Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 
ORIGINAL ARTICLE
Year : 2020  |  Volume : 16  |  Issue : 6  |  Page : 1323-1330

Ipsilateral lung normal tissue complication probability parameters for different dose calculation algorithms in radiotherapy of breast cancer


1 Department of Medical Physic,Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
2 Radiation Oncology Research Center, Cancer Institute; Department of Medical Physics and Medical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
3 Radiation Oncology Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
4 Department of Medical Physics and Medical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran

Correspondence Address:
Somayeh Gholami
Radiation Oncology Research Center, Cancer Institute, Tehran University of Medical Sciences, Keshavarz Blvd., Poursina Ave., Tehran 141556447
Iran
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jcrt.JCRT_1149_19

Rights and Permissions

Purpose: Different dose calculation algorithms (DCAs) predict different dose distributions for the same treatment. Awareness of optimal model parameters is vital for estimating normal tissue complication probability (NTCP) for different algorithms. The aim is to determine the NTCP parameter values for different DCAs in left-sided breast radiotherapy, using the Lyman-Kutcher-Burman (LKB) model. Materials and Methods: First, the methodology recommended by International Atomic Energy Agency TEC-DOC 1583 was used to establish the accuracy of dose calculations of different DCAs including: Monte Carlo (MC) and collapsed cone algorithms implemented in Monaco, pencil beam convolution (PBC) and analytical anisotropic algorithm (AAA) implemented in Eclipse, and superposition and Clarkson algorithms implemented in PCRT3D treatment planning systems (TPSs). Then, treatment planning of 15 patients with left-sided breast cancer was performed by the mentioned DCAs and NTCP of the left-lung normal tissue were calculated for each patient individually, using the LKB model. For the PB algorithm, the NTCP parameters were taken from previously published values and new model parameters obtained for each DCA, using the iterative least squares methods. Results: For all cases and DCAs, NTCP computation with the same model parameters resulted in >15% deviation in NTCP values. The new NTCP model parameters were classified according to the algorithm type. Thus, the discrepancy of NTCP computations was reduced up to 5% after utilizing adjusted model parameters. Conclusions: This paper confirms that the NTCP values for a given treatment type are different for the different DCAs. Thus, it is essential to introduce appropriate NTCP parameter values according to DCA adopted in TPS, to obtain a more precise estimation of lung NTCP. Hence, new parameter values, classified according to the DCAs, must be determined before introducing NTCP estimation in clinical practice.


[FULL TEXT] [PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed782    
    Printed18    
    Emailed0    
    PDF Downloaded85    
    Comments [Add]    

Recommend this journal