Program Information
Detection of Low Contrast Objects: Optimization of CT Simulation Reconstruction Protocol Parameters
s alani*, A Schlocker , N Honig , B Corn , tel aviv medical center, Tel Aviv, israel
Presentations
SU-F-J-185 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall
Purpose:
CT simulation has become an integral component of modern RT planning and therefore must be continually optimized. We evaluated the detection of small and low-contrast regions in images obtained during CT simulation.
Methods:
A CT phantom containing a contrast detail modulus for detection of low-contrast structures was used to optimize the CT reconstruction protocol for abdomen. The parameters (A) Pitch, (B) Reconstruction Filter, and (C) Rotation Time type were varied for assessment of image quality.
Three factors, three levels, and nine experiments were identified. According to the Taguchi approach an L9 orthogonal array was selected. The reconstruction parameters of the CT scanner (Brilliance Big Bore), Pitch, Reconstruction Filter type, and Rotation Time, were iteratively scanned according to the orthogonal array. 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 (61.4%) had the most significant influence on low contrast resolution, followed by the Reconstruction Filter type (29.7%). The optimal setting level is A1-B1-C3, 0.68 pitch, smooth filter, 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.
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