SU-GG-T-112: Segment-Modulated Arc Radiation Therapy: Single Arc Inverse Planning with Binary Programming and Exact Leaf-Sequencing Algorithm

2010 ◽  
Vol 37 (6Part17) ◽  
pp. 3210-3210
Author(s):  
Y Ma ◽  
L Xing
Keyword(s):  
Radiation Therapy ◽  
Inverse Planning ◽  
Binary Programming ◽  
Sequencing Algorithm ◽  
Leaf Sequencing ◽  
Single Arc

GEOMETRIC ALGORITHMS FOR STATIC LEAF SEQUENCING PROBLEMS IN RADIATION THERAPY

2004 ◽  
Vol 14 (04n05) ◽  
pp. 311-339 ◽  
Author(s):  
DANNY Z. CHEN ◽  
XIAOBO S. HU ◽  
SHUANG (SEAN) LUAN ◽  
CHAO WANG ◽  
XIAODONG WU
Keyword(s):  
Radiation Therapy ◽  
Polynomial Time ◽  
Geometric Algorithms ◽  
Planning System ◽  
Treatment Planning System ◽  
Polygonal Domain ◽  
Steiner Points ◽  
Delivery Times ◽  
Leaf Sequencing ◽  
Monotone Polygons

The static leaf sequencing (SLS) problem arises in radiation therapy for cancer treatments, aiming to accomplish the delivery of a radiation prescription to a target tumor in the minimum amount of delivery time. Geometrically, the SLS problem can be formulated as a 3-D partition problem for which the 2-D problem of partitioning a polygonal domain (possibly with holes) into a minimum set of monotone polygons is a special case. In this paper, we present new geometric algorithms for a basic case of the 3-D SLS problem (which is also of clinical value) and for the general 3-D SLS problem. Our basic 3-D SLS algorithm, based on new geometric observations, produces guaranteed optimal quality solutions using O(1) Steiner points in polynomial time; the previously best known basic 3-D SLS algorithm gives optimal outputs only for the case without considering any Steiner points, and its time bound involves a multiplicative factor of a factorial function of the input. Our general 3-D SLS algorithm is based on our basic 3-D SLS algorithm and a polynomial time algorithm for partitioning a polygonal domain (possibly with holes) into a minimum set of x-monotone polygons, and has a fast running time. Experiments of our SLS algorithms and software in clinical settings have shown substantial improvements over the current most popular commercial treatment planning system and the most well-known SLS algorithm in medical literature. The radiotherapy plans produced by our software not only take significantly shorter delivery times, but also have a much better treatment quality. This proves the feasibility of our software and has led to its clinical applications at the Department of Radiation Oncology at the University of Maryland Medical Center. Some of our techniques and geometric procedures (e.g., for partitioning a polygonal domain into a minimum set of x-monotone polygons) are interesting in their own right.

Arc-modulated radiation therapy (AMRT): a single-arc form of intensity-modulated arc therapy

2008 ◽  
Vol 53 (22) ◽  
pp. 6291-6303 ◽  
Author(s):  
Chao Wang ◽  
Shuang Luan ◽  
Grace Tang ◽  
Danny Z Chen ◽  
Matt A Earl ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Intensity Modulated ◽  
Arc Therapy ◽  
Single Arc

Comparison of three IMRT inverse planning techniques that allow for partial esophagus sparing in patients receiving thoracic radiation therapy for lung cancer

2004 ◽  
Vol 29 (3) ◽  
pp. 210-216 ◽  
Author(s):  
Ying Xiao ◽  
Maria Werner-Wasik ◽  
D. Michalski ◽  
C. Houser ◽  
G. Bednarz ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Radiation Therapy ◽  
Planning Techniques ◽  
Inverse Planning ◽  
Thoracic Radiation
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