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Title: A Novel Fast Helical 4D-CT Acquisition Technique to Generate Low-Noise Sorting Artifact–Free Images at User-Selected Breathing Phases

Journal Article · · International Journal of Radiation Oncology, Biology and Physics
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  1. Department of Radiation Oncology, University of California, Los Angeles, California (United States)
  2. Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania (United States)
  3. Department of Radiological Sciences, University of California, Los Angeles, California (United States)

Purpose: To develop a novel 4-dimensional computed tomography (4D-CT) technique that exploits standard fast helical acquisition, a simultaneous breathing surrogate measurement, deformable image registration, and a breathing motion model to remove sorting artifacts. Methods and Materials: Ten patients were imaged under free-breathing conditions 25 successive times in alternating directions with a 64-slice CT scanner using a low-dose fast helical protocol. An abdominal bellows was used as a breathing surrogate. Deformable registration was used to register the first image (defined as the reference image) to the subsequent 24 segmented images. Voxel-specific motion model parameters were determined using a breathing motion model. The tissue locations predicted by the motion model in the 25 images were compared against the deformably registered tissue locations, allowing a model prediction error to be evaluated. A low-noise image was created by averaging the 25 images deformed to the first image geometry, reducing statistical image noise by a factor of 5. The motion model was used to deform the low-noise reference image to any user-selected breathing phase. A voxel-specific correction was applied to correct the Hounsfield units for lung parenchyma density as a function of lung air filling. Results: Images produced using the model at user-selected breathing phases did not suffer from sorting artifacts common to conventional 4D-CT protocols. The mean prediction error across all patients between the breathing motion model predictions and the measured lung tissue positions was determined to be 1.19 ± 0.37 mm. Conclusions: The proposed technique can be used as a clinical 4D-CT technique. It is robust in the presence of irregular breathing and allows the entire imaging dose to contribute to the resulting image quality, providing sorting artifact–free images at a patient dose similar to or less than current 4D-CT techniques.

OSTI ID:
22416563
Journal Information:
International Journal of Radiation Oncology, Biology and Physics, Vol. 89, Issue 1; Other Information: Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0360-3016
Country of Publication:
United States
Language:
English