title: A multi-GPU real-time dose simulation software framework for lung radiotherapy.
abstract: OBJECTIVE
  Medical simulation frameworks facilitate both the preoperative and postoperative analysis of the patient's pathophysical condition. Of particular importance is the simulation of radiation dose delivery for real-time radiotherapy monitoring and retrospective analyses of the patient's treatment.
  
  
  METHODS
  In this paper, a software framework tailored for the development of simulation-based real-time radiation dose monitoring medical applications is discussed. A multi-GPU-based computational framework coupled with inter-process communication methods is introduced for simulating the radiation dose delivery on a deformable 3D volumetric lung model and its real-time visualization. The model deformation and the corresponding dose calculation are allocated among the GPUs in a task-specific manner and is performed in a pipelined manner. Radiation dose calculations are computed on two different GPU hardware architectures. The integration of this computational framework with a front-end software layer and back-end patient database repository is also discussed.
  
  
  RESULTS
  Real-time simulation of the dose delivered is achieved at once every 120 ms using the proposed framework. With a linear increase in the number of GPU cores, the computational time of the simulation was linearly decreased. The inter-process communication time also improved with an increase in the hardware memory. Variations in the delivered dose and computational speedup for variations in the data dimensions are investigated using D70 and D90 as well as gEUD as metrics for a set of 14 patients. Computational speed-up increased with an increase in the beam dimensions when compared with a CPU-based commercial software while the error in the dose calculation was <1%.
  
  
  CONCLUSIONS
  Our analyses show that the framework applied to deformable lung model-based radiotherapy is an effective tool for performing both real-time and retrospective analyses.
authors.affiliation: University of California, Los Angeles, CA, USA. asanthanam@mednet.ucla.edu
authors.forename: A P
authors.initials: AP
authors.lastname: Santhanam
authors.forename: Y
authors.initials: Y
authors.lastname: Min
authors.forename: H
authors.initials: H
authors.lastname: Neelakkantan
authors.forename: N
authors.initials: N
authors.lastname: Papp
authors.forename: S L
authors.initials: SL
authors.lastname: Meeks
authors.forename: P A
authors.initials: PA
authors.lastname: Kupelian
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D003196:Computer Graphics; D003205:Computing Methodologies; D056973:Four-Dimensional Computed Tomography; D006801:Humans; D021621:Imaging, Three-Dimensional; D008175:Lung Neoplasms / Q000532:radiotherapy*; D011879:Radiotherapy Dosage