Literature DB >> 18293562

Leaf-sequencing for intensity-modulated arc therapy using graph algorithms.

Shuang Luan1, Chao Wang, Daliang Cao, Danny Z Chen, David M Shepard, Cedric X Yu.   

Abstract

Intensity-modulated arc therapy (IMAT) is a rotational IMRT technique. It uses a set of overlapping or nonoverlapping arcs to create a prescribed dose distribution. Despite its numerous advantages, IMAT has not gained widespread clinical applications. This is mainly due to the lack of an effective IMAT leaf-sequencing algorithm that can convert the optimized intensity patterns for all beam directions into IMAT treatment arcs. To address this problem, we have developed an IMAT leaf-sequencing algorithm and software using graph algorithms in computer science. The input to our leaf-sequencing software includes (1) a set of (continuous) intensity patterns optimized by a treatment planning system at a sequence of equally spaced beam angles (typically 10 degrees apart), (2) a maximum leaf motion constraint, and (3) the number of desired arcs, k. The output is a set of treatment arcs that best approximates the set of optimized intensity patterns at all beam angles with guaranteed smooth delivery without violating the maximum leaf motion constraint. The new algorithm consists of the following key steps. First, the optimized intensity patterns are segmented into intensity profiles that are aligned with individual MLC leaf pairs. Then each intensity profile is segmented into k MLC leaf openings using a k-link shortest path algorithm. The leaf openings for all beam angles are subsequently connected together to form 1D IMAT arcs under the maximum leaf motion constraint using a shortest path algorithm. Finally, the 1D IMAT arcs are combined to form IMAT treatment arcs of MLC apertures. The performance of the implemented leaf-sequencing software has been tested for four treatment sites (prostate, breast, head and neck, and lung). In all cases, our leaf-sequencing algorithm produces efficient and highly conformal IMAT plans that rival their counterpart, the tomotherapy plans, and significantly improve the IMRT plans. Algorithm execution times ranging from a few seconds to 2 min are observed on a laptop computer equipped with a 2.0 GHz Pentium M processor.

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Year:  2008        PMID: 18293562     DOI: 10.1118/1.2818731

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  12 in total

1.  Multicriteria VMAT optimization.

Authors:  David Craft; Dualta McQuaid; Jeremiah Wala; Wei Chen; Ehsan Salari; Thomas Bortfeld
Journal:  Med Phys       Date:  2012-02       Impact factor: 4.071

2.  Comparing radiation treatments using intensity-modulated beams, multiple arcs, and single arcs.

Authors:  Grace Tang; Matthew A Earl; Shuang Luan; Chao Wang; Majid M Mohiuddin; Cedric X Yu
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-04       Impact factor: 7.038

3.  Exploring trade-offs between VMAT dose quality and delivery efficiency using a network optimization approach.

Authors:  Ehsan Salari; Jeremiah Wala; David Craft
Journal:  Phys Med Biol       Date:  2012-08-14       Impact factor: 3.609

4.  Simultaneous beam sampling and aperture shape optimization for SPORT.

Authors:  Masoud Zarepisheh; Ruijiang Li; Yinyu Ye; Lei Xing
Journal:  Med Phys       Date:  2015-02       Impact factor: 4.071

5.  Optimization approaches to volumetric modulated arc therapy planning.

Authors:  Jan Unkelbach; Thomas Bortfeld; David Craft; Markus Alber; Mark Bangert; Rasmus Bokrantz; Danny Chen; Ruijiang Li; Lei Xing; Chunhua Men; Simeon Nill; Dávid Papp; Edwin Romeijn; Ehsan Salari
Journal:  Med Phys       Date:  2015-03       Impact factor: 4.071

6.  Analyzing the performance of ArcCHECK diode array detector for VMAT plan.

Authors:  Rajesh Thiyagarajan; Arunai Nambiraj; Sujit Nath Sinha; Girigesh Yadav; Ashok Kumar; Vikraman Subramani
Journal:  Rep Pract Oncol Radiother       Date:  2015-12-02

7.  Rotational IMRT techniques compared to fixed gantry IMRT and tomotherapy: multi-institutional planning study for head-and-neck cases.

Authors:  Tilo Wiezorek; Tim Brachwitz; Dietmar Georg; Eyck Blank; Irina Fotina; Gregor Habl; Matthias Kretschmer; Gerd Lutters; Henning Salz; Kai Schubert; Daniela Wagner; Thomas G Wendt
Journal:  Radiat Oncol       Date:  2011-02-21       Impact factor: 3.481

8.  Optimal partial-arcs in VMAT treatment planning.

Authors:  Jeremiah Wala; Ehsan Salari; Wei Chen; David Craft
Journal:  Phys Med Biol       Date:  2012-09-05       Impact factor: 3.609

9.  Deep learning-based inverse mapping for fluence map prediction.

Authors:  Lin Ma; Mingli Chen; Xuejun Gu; Weiguo Lu
Journal:  Phys Med Biol       Date:  2020-11-27       Impact factor: 3.609

10.  Applications of IMAT in cervical esophageal cancer radiotherapy: a comparison with fixed-field IMRT in dosimetry and implementation.

Authors:  Yong Yin; Jinhu Chen; Ligang Xing; Xiaoling Dong; Tonghai Liu; Jie Lu; Jinming Yu
Journal:  J Appl Clin Med Phys       Date:  2011-01-13       Impact factor: 2.102

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