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Phys Med Biol ; 60(19): 7671-94, 2015 Oct 07.
Article in English | MEDLINE | ID: mdl-26389637

ABSTRACT

CT dose optimization is typically guided by pixel noise or contrast-to-noise ratio that does not delineate low contrast details adequately. We utilized the statistically defined low contrast detectability to study its relationship to dose and lesion size in abdominal CT. A realistically shaped medium sized abdomen phantom was customized to contain a cylindrical void of 4 cm diameter. The void was filled with a low contrast (1% and 2%) insert containing six groups of cylindrical targets ranging from 1.2 mm to 7 mm in size. Helical CT scans were performed using a Siemens 64-slice mCT and a GE Discovery 750 HD at various doses. After the subtractions between adjacent slices, the uniform sections of the filtered backprojection reconstructed images were partitioned to matrices of square elements matching the sizes of the targets. It was verified that the mean values from all the elements in each matrix follow a Gaussian distribution. The minimum detectable contrast (MDC), quantified by the mean signal to background difference equal to the distribution's standard deviation multiplied by 3.29, corresponding to 95% confidence level, was found to be related to the phantom specific dose and the element size by a power law (R^2 > 0.990). Independent readings on the 5 mm and 7 mm targets were compared to the measured contrast to the MDC ratios. The results showed that 93% of the cases were detectable when the measured contrast exceeds the MDC. The correlation of the MDC to the pixel noise and target size was also identified and the relationship was found to be the same for the scanners in the study. To quantify the impact of iterative reconstructions to the low contrast detectability, the noise structure was studied in a similar manner at different doses and with different ASIR blending fractions. The relationship of the dose to the blending fraction and low contrast detectability is presented.


Subject(s)
Abdomen/pathology , Algorithms , Image Processing, Computer-Assisted/methods , Phantoms, Imaging/standards , Radiography, Abdominal/methods , Tomography, X-Ray Computed/methods , Humans , Signal-To-Noise Ratio
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