Journal of Medical Physics
ORIGINAL ARTICLE
Year
: 2011  |  Volume : 36  |  Issue : 2  |  Page : 85--94

A hybrid algorithm for instant optimization of beam weights in anatomy-based intensity modulated radiotherapy: A performance evaluation study


Ranganathan Vaitheeswaran1, VK Sathiya Narayanan2, Janhavi R Bhangle2, Amit Nirhali2, Namita Kumar2, Sumit Basu2, Vikram Maiya2 
1 Siemens Ltd., HealthCare Sector, Pune, India
2 Department of Radiation Oncology, Ruby Hall Clinic, Pune, India

Correspondence Address:
Ranganathan Vaitheeswaran
Healthcare Sector, Siemens Ltd., 403A, ICC Trade Tower, Tower B, Senapati Bapat Road, Pune - 411 016
India

The study aims to introduce a hybrid optimization algorithm for anatomy-based intensity modulated radiotherapy (AB-IMRT). Our proposal is that by integrating an exact optimization algorithm with a heuristic optimization algorithm, the advantages of both the algorithms can be combined, which will lead to an efficient global optimizer solving the problem at a very fast rate. Our hybrid approach combines Gaussian elimination algorithm (exact optimizer) with fast simulated annealing algorithm (a heuristic global optimizer) for the optimization of beam weights in AB-IMRT. The algorithm has been implemented using MATLAB software. The optimization efficiency of the hybrid algorithm is clarified by (i) analysis of the numerical characteristics of the algorithm and (ii) analysis of the clinical capabilities of the algorithm. The numerical and clinical characteristics of the hybrid algorithm are compared with Gaussian elimination method (GEM) and fast simulated annealing (FSA). The numerical characteristics include convergence, consistency, number of iterations and overall optimization speed, which were analyzed for the respective cases of 8 patients. The clinical capabilities of the hybrid algorithm are demonstrated in cases of (a) prostate and (b) brain. The analyses reveal that (i) the convergence speed of the hybrid algorithm is approximately three times higher than that of FSA algorithm; (ii) the convergence (percentage reduction in the cost function) in hybrid algorithm is about 20% improved as compared to that in GEM algorithm; (iii) the hybrid algorithm is capable of producing relatively better treatment plans in terms of Conformity Index (CI) [~ 2% - 5% improvement] and Homogeneity Index (HI) [~ 4% - 10% improvement] as compared to GEM and FSA algorithms; (iv) the sparing of organs at risk in hybrid algorithm-based plans is better than that in GEM-based plans and comparable to that in FSA-based plans; and (v) the beam weights resulting from the hybrid algorithm are about 20% smoother than those obtained in GEM and FSA algorithms. In summary, the study demonstrates that hybrid algorithms can be effectively used for fast optimization of beam weights in AB-IMRT.


How to cite this article:
Vaitheeswaran R, Sathiya Narayanan V K, Bhangle JR, Nirhali A, Kumar N, Basu S, Maiya V. A hybrid algorithm for instant optimization of beam weights in anatomy-based intensity modulated radiotherapy: A performance evaluation study.J Med Phys 2011;36:85-94


How to cite this URL:
Vaitheeswaran R, Sathiya Narayanan V K, Bhangle JR, Nirhali A, Kumar N, Basu S, Maiya V. A hybrid algorithm for instant optimization of beam weights in anatomy-based intensity modulated radiotherapy: A performance evaluation study. J Med Phys [serial online] 2011 [cited 2019 Oct 16 ];36:85-94
Available from: http://www.jmp.org.in/article.asp?issn=0971-6203;year=2011;volume=36;issue=2;spage=85;epage=94;aulast=Vaitheeswaran;type=0