Program Information
Structured Noise Index as An Automated Quality Control for Nuclear Medicine: A Two Year Experience
J Nelson1*, O Christianson1 , E Samei1 , (1) Duke University Medical Center, Durham, NC
Presentations
SU-C-9A-2 Sunday 1:00PM - 1:55PM Room: 9APurpose:
Flood-field uniformity evaluation is an essential element in the assessment of nuclear medicine (NM) gamma cameras. It serves as the central element of the quality control (QC) program, acquired and analyzed on a daily basis prior to clinical imaging. Uniformity images are traditionally analyzed using pixel value-based metrics which often fail to capture subtle structure and patterns caused by changes in gamma camera performance requiring additional visual inspection which is subjective and time demanding. The goal of this project was to develop and implement a robust QC metrology for NM that is effective in identifying non-uniformity issues, reporting issues in a timely manner for efficient correction prior to clinical involvement, all incorporated into an automated effortless workflow, and to characterize the program over a two year period.
Methods:
A new quantitative uniformity analysis metric was developed based on 2D noise power spectrum metrology and confirmed based on expert observer visual analysis. The metric, termed Structured Noise Index (SNI) was then integrated into an automated program to analyze, archive, and report on daily NM QC uniformity images. The effectiveness of the program was evaluated over a period of 2 years.
Results:
The SNI metric successfully identified visually apparent non-uniformities overlooked by the pixel value-based analysis methods. Implementation of the program has resulted in non-uniformity identification in about 12% of daily flood images. In addition, due to the vigilance of staff response, the percentage of days exceeding trigger value shows a decline over time.
Conclusion:
The SNI provides a robust quantification of the NM performance of gamma camera uniformity. It operates seamlessly across a fleet of multiple camera models. The automated process provides effective workflow within the NM spectra between physicist, technologist, and clinical engineer. The reliability of this process has made it the preferred platform for NM uniformity analysis.
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