English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Online adaptive radiation therapy (ART) has great promise to significantlyreduce normal tissue toxicity and/or improve tumor control through real-timetreatment adaptations based on the current patient anatomy. However, the majortechnical obstacle for clinical realization of online ART, namely the inabilityto achieve real-time efficiency in treatment re-planning, has yet to be solved.To overcome this challenge, this paper presents our work on the implementationof an intensity modulated radiation therapy (IMRT) direct aperture optimization(DAO) algorithm on graphics processing unit (GPU) based on our previous work onCPU. We formulate the DAO problem as a large-scale convex programming problem,and use an exact method called column generation approach to deal with itsextremely large dimensionality on GPU. Five 9-field prostate and five 5-fieldhead-and-neck IMRT clinical cases with 5\times5 mm2 beamlet size and2.5\times2.5\times2.5 mm3 voxel size were used to evaluate our algorithm onGPU. It takes only 0.7~2.5 seconds for our implementation to generate optimaltreatment plans using 50 MLC apertures on an NVIDIA Tesla C1060 GPU card. Ourwork has therefore solved a major problem in developing ultra-fast(re-)planning technologies for online ART.

GPU-based ultra-fast direct aperture optimization for online adaptive radiation therapy