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Session: Professional General ePoster Viewing [Return to Session]

Utilization of Response Surface Methodology in Optimization of CT Low-Contrast Detectability

s alani*, ziv medical center Sefed IL


PO-GePV-P-16 (Sunday, 7/10/2022)   [Eastern Time (GMT-4)]

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Purpose: To evaluated the detection of small and low contrast regions in images obtained during CT simulation.

Methods: A CT phantom containing a contrast detail module for detection of low-contrast structures was used to optimize the CT protocol. Response Surface Methodology (RSM), using a three-factor, three-level Box–Behnken statistical design and digital image processing, were used to optimize the factors affecting image quality, which include (A) Pitch, (B) slice thinness, and (C) Rotation Time type were varied for assessment of image quality. parameter combinations used to perform CT scanning for each of the 15 runs The scanning parameters of the CT scanner (TOSHIBA Aquillion), Pitch, slice thickness, and Rotation Time, were iteratively scanned according to the runs. A Catphan 604 CT phantom was used to characterize low-contrast resolution (CPT730 module). All CT scan images were analyzed by IMAGE-OWL software. The objective of the study was to identify parameters that maximize the low-contrast resolution of the images. The ANOVA and F-tests were used to analyze results using JMP statistical software

Results: The optimal settings and predicted optimal values for low-contrast resolution were determined. The ANOVA was used to determine the optimum combination of process parameters more accurately by investigating the relative importance of each process parameter. We determined that Pitch (63.2%) had the most significant influence on low contrast resolution, followed by the slice thickness (31%). The optimal setting l is 0.68 pitch, 0.1mm slice thickness., and gantry rotation time 1.5sec.,respectively. Additional measurements were made to confirm the prediction error model is justified and the results are validated.

Conclusion: These experiments have several implications for CT imaging, especially for clinical detection of small, low-contrast lesions in liver or pancreas. In the phantom model of this study, optimal Contrast Detail Values were determined to be:1% contrast, 2mm; 0.5% contrast, 4mm; 0.3% contrast, 7mm.


Not Applicable / None Entered.


Not Applicable / None Entered.

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