Paper
22 March 2016 kV x-ray dual digital tomosynthesis for image guided lung SBRT
Larry Partain, Douglas Boyd, Namho Kim, Andrew Hernandez, Megan Daly, John Boone
Author Affiliations +
Abstract
Two simulated sets of digital tomosynthesis images of the lungs, each acquired at a 90 degree angle from the other, with 19 projection images used for each set and SART iterative reconstructed, gives dual tomosynthesis slice image quality approaching that of spiral CT, and with a data acquisition time that is 3% of that of cone beam CT. This fast kV acquisition, should allow near real time tracking of lung tumors in patients receiving SBRT, based on a novel TumoTrakTM multi-source X-ray tube design. Until this TumoTrakTM prototype is completed over the next year, its projected performance was simulated from the DRR images created from a spiral CT data set from a lung cancer patient. The resulting dual digital tomosynthesis reconstructed images of the lung tumor were exceptional and approached that of the gold standard Feldkamp CT reconstruction of breath hold, diagnostic, spiral, multirow, CT data. The relative dose at 46 mAs was less than 10% of what it would have been if the digital tomosynthesis had been done at the 472 mAs of the CT data set. This is for a 0.77 fps imaging rate sufficient to resolve respiratory motion in many free breathing patients during SBRT. Such image guidance could decrease the magnitudes of targeting error margins by as much as 20 mm or more in the craniocaudal direction for lower lobe lesions while markedly reducing dose to normal lung, heart and other critical structures. These initial results suggest a wide range of topics for future work.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Larry Partain, Douglas Boyd, Namho Kim, Andrew Hernandez, Megan Daly, and John Boone "kV x-ray dual digital tomosynthesis for image guided lung SBRT", Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 978361 (22 March 2016); https://doi.org/10.1117/12.2216437
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Digital imaging

Lung

X-ray computed tomography

Lung cancer

Image quality

Tumors

X-rays

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