title: GPU-based ultrafast IMRT plan optimization.
abstract: The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California, San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity-modulated radiation therapy (IMRT) optimization algorithm on graphics processing units (GPUs). We adopt a penalty-based quadratic optimization model, which is solved by using a gradient projection method with Armijo's line search rule. Our optimization algorithm has been implemented in CUDA for parallel GPU computing as well as in C for serial CPU computing for comparison purpose. A prostate IMRT case with various beamlet and voxel sizes was used to evaluate our implementation. On an NVIDIA Tesla C1060 GPU card, we have achieved speedup factors of 20-40 without losing accuracy, compared to the results from an Intel Xeon 2.27 GHz CPU. For a specific nine-field prostate IMRT case with 5 x 5 mm(2) beamlet size and 2.5 x 2.5 x 2.5 mm(3) voxel size, our GPU implementation takes only 2.8 s to generate an optimal IMRT plan. Our work has therefore solved a major problem in developing online re-planning technologies for adaptive radiotherapy.
authors.affiliation: Department of Radiation Oncology, University of California San Diego, La Jolla, CA 92037, USA.
authors.forename: Chunhua
authors.initials: C
authors.lastname: Men
authors.forename: Xuejun
authors.initials: X
authors.lastname: Gu
authors.forename: Dongju
authors.initials: D
authors.lastname: Choi
authors.forename: Amitava
authors.initials: A
authors.lastname: Majumdar
authors.forename: Ziyi
authors.initials: Z
authors.lastname: Zheng
authors.forename: Klaus
authors.initials: K
authors.lastname: Mueller
authors.forename: Steve B
authors.initials: SB
authors.lastname: Jiang
mesh_terms: D000465:Algorithms; D003201:Computers; D003205:Computing Methodologies; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009369:Neoplasms / Q000532:radiotherapy*; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D018787:Radiation Oncology / Q000379:methods; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000295:instrumentation* / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods