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Proceedings Paper

Evaluation of radiation dose reduction via myocardial frame reduction in dynamic cardiac CT for perfusion quantitation
Author(s): Michael Bindschadler; Kelley R. Branch; Adam M. Alessio
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Paper Abstract

Dynamic contrast enhanced cardiac CT acquisitions can quantify myocardial blood flow (MBF) in absolute units (ml/min/g), but repeated scans increase X-ray radiation dose to the patient. We propose a novel approach using high temporal sampling of the input function with reduced temporal sampling of the myocardial tissue response. This type of data could be acquired with current bolus tracking acquisitions or with new acquisition sequences offering reduced radiation dose and potentially easier data processing and flow estimation. To evaluate this type of data, we prospectively acquired a full dynamic series [12 -18 frames (mean 14.5±1.4) over 23 to 44 seconds (mean 31.3±5.0 sec)] on 28 patients at rest and stress (N=56 studies) and examined the relative performance of myocardial perfusion estimation when the myocardial data is subsampled down to 8, 4, 2 or 1 frame(s). Unlike previous studies, for all frame rates, we consider a well-sampled input function. As expected, subsampling linearly reduces radiation dose while progressively decreasing estimation accuracy, with the typical absolute error in MBF (as compared to the full-length series) increasing from 0.22 to 0.30 to 0.35 to 1.12 ml/min/g as the number of frames used for estimation decreases from 8 to 4 to 2 to 1, respectively. These results suggest that high temporal sampling of the input function with low temporal sampling of the myocardial response can provide much of the benefit of dynamic CT for MBF quantification with dramatic reductions in the required number of myocardial acquisitions and the associated radiation dose (e.g. 77% dose reduction for 2-frame case).

Paper Details

Date Published: 9 March 2018
PDF: 7 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105731W (9 March 2018); doi: 10.1117/12.2294556
Show Author Affiliations
Michael Bindschadler, Univ. of Washington (United States)
Kelley R. Branch, Univ. of Washington (United States)
Adam M. Alessio, Univ. of Washington (United States)


Published in SPIE Proceedings Vol. 10573:
Medical Imaging 2018: Physics of Medical Imaging
Joseph Y. Lo; Taly Gilat Schmidt; Guang-Hong Chen, Editor(s)

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