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Loss of Image Sharpness in CT Bone Imaging Due to Positioning Within the Scan Field of View - Possible Solutions

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F Ranallo

F Ranallo*, T Szczykutowicz , University of Wisconsin, Madison, WI


SU-F-18C-3 Sunday 4:00PM - 6:00PM Room: 18C

Purpose: To demonstrate how both the positioning of an object in the scan field of view (SFOV) and the size of the reconstructed field of view (RFOV) can both significantly affect and degrade the image sharpness.

Methods:Clinical CT scans of the shoulders and elbows were inspected for image sharpness. GE scanners were used for the imaging with a “Bone Plus” reconstruction algorithm. In all scans the anatomy of interest was significantly displaced from the center of the SFOV (away from the scanner iso-center). Radial and azimuthal image sharpness measurements using the Modulation Transfer Function (MTF) were made using the same RFOV at the center of the SFOV and at varying distances from the center. These MTF measurements were also made with varying values of the RFOV.

Results: Clinical images with the bone anatomy of interest positioned farther from the center of the SFOV showed increasing image softness occasionally to the point of being non-diagnostic. The MTF measurements showed that the resolution degraded significantly, by more than a factor of 2, moving from the center toward the periphery of the SFOV: from 12 cycles/cm to less than 6 cycles/cm at distances of 15 cm or more from the center of the SFOV. Increasing the RFOV beyond 20 cm also degraded the resolution, though less significantly.

Conclusion: When preservation of bone detail is important one must not only use the proper bone reconstruction algorithm, but also must keep the body part as close to the center of the SFOV as possible. Though this may be difficult with some imaging tasks, such as imaging of the shoulder and elbow, every effort should be made to this end. For the best resolution, the RFOV should also be kept small, ideally to 20 cm or less.

Funding Support, Disclosures, and Conflict of Interest: Partial research funding from GE HealthCare.

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