1. A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning.
- Author
-
C Guthier, K P Aschenbrenner, D Buergy, M Ehmann, F Wenz, and J W Hesser
- Subjects
PROSTATE cancer treatment ,CANCER radiotherapy ,RADIOTHERAPY treatment planning ,COMPRESSED sensing ,LOW dose rate brachytherapy ,REAL-time computing ,MEDICAL physics - Abstract
This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed.An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data.The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning.The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
- View/download PDF