Paper
17 March 2007 Application of time sampling in brain CT perfusion imaging for dose reduction
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Abstract
The purpose of this study is to determine a stable sampling rate not to be affected by sampling shift for reducing radiation exposure with time sampling and interpolation in cerebral perfusion CT examination. Original images were obtained every 1 second for 40 time series from 3 patients, respectively. Time sampling was performed with sampling intervals (SI) from 2 to 10 seconds. Sampling shift was applied from +1 to SI-1 for each sampling rate. For each patient, 30 tissue concentration time-course data were collected, and arterial input curves were fitted by gamma-variate function. The sinc function was introduced for interpolation. Deconvolution analysis based on SVD was performed for quantifying perfusion parameters. The perfusion values through time-varying sampling and interpolation were statistically compared with the original perfusion values. The mean CBF values with increase of sampling interval and shift magnitude from the collected data had a wider fluctuation pattern centering around the original mean CBF. The mean CBV values had a similar tendency to the mean CBF values, but a relatively narrower deviation. The mean MTT values were fluctuated reversely to the trend of the mean CBF values. The stable sampling interval for quantifying perfusion parameters with lower radiation exposure was statistically acceptable up to 4 seconds. These results indicate that sampling shift limits sampling rate for acquiring acceptable perfusion values. This study will help in selecting more reasonable sampling rate for low-radiation-dose CT examination.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. H. Lee, J. H. Kim, K. G. Kim, S. J. Park, and Jung Gi Im "Application of time sampling in brain CT perfusion imaging for dose reduction", Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 65102P (17 March 2007); https://doi.org/10.1117/12.713529
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Cited by 2 scholarly publications.
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KEYWORDS
Tissues

Computed tomography

Brain

Neuroimaging

Deconvolution

Convolution

Statistical analysis

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