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Automated Phantom Analysis for Gamma Cameras - An Efficient, Accessible, Consistent, and Sensitive Method for Quality Control

T Tazegul1*, A Polemi2 , A Snyder1 , C Snyder1 , A Goode2 , P Collins2 , (1) Atirix Medical Systems, Inc, Minneapolis, MN, (2) University of Virginia Health System, Charlottesville, VA

Presentations

(Sunday, 7/14/2019) 4:00 PM - 6:00 PM

Room: 304ABC

Purpose: To introduce and test the consistency of a simple yet quantitative image analysis package for efficiently assessing gamma camera image quality in a busy clinical setting.

Methods: Four Siemens Symbia gamma cameras were used to acquire planar images of a 4-quadrant bar phantom and tomographic reconstructions of a Jaszczak phantom as part of a standard gamma camera quality assurance program. Images were sent to QC-Track (Atirix, Minneapolis), which automatically placed predetermined regions of interest (ROIs) and performed analysis. For the bar phantom, a standard deviation (SD)-based modulation transfer function (MTF) was calculated for an ROI in each quadrant. The bar widths at MTF values of 0.15 and 0.1 were reported using linear interpolation across the three largest bars. For the Jaszczak phantom, the contrast to noise ratio (CNR) for each sphere and a modulation for each rods section was calculated. Spheres corresponding to a CNR ≥3, and the rod size at modulations 0.5 and 0.2 were also reported. Visual analysis was performed by two medical physicists to evaluate inter-observer variability and correlation to quantitative values.

Results: Bar phantom images returned mean bar width of 3.04 ± 0.04 mm (MTF = 0.15) and 2.70 ± 0.05 mm (MTF = 0.1). Jaszczak phantom acquisitions ranged in quality; the sphere corresponding to a CNR value of 3 ranged from 6.54 - 12.52 mm (mean: 9.3 mm, std. dev: 2.0 mm) over 6 acquisitions and the rods with modulation values of 0.5 and 0.2 were 12.2 ± 0.4 mm and 8.4 ± 0.7 mm respectively. Results of automated QC correlated well with visual analysis.

Conclusion: Our method for quantitative image analysis is consistent. Thresholds set correspond well with visual analysis, making our framework suitable for use in a busy nuclear medicine department.

Funding Support, Disclosures, and Conflict of Interest: I am an intern at Atirix Medical Systems, Inc. Atirix sells the QC-Track system for imaging QC and provided funding for this research. All image analysis was performed in QC-Track.

Keywords

Quality Control, Nuclear Medicine, Software

Taxonomy

IM- Nuclear Medicine General: Gamma Camera or other (other than PET/SPECT)

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