Local validation of the use of Evolution for Bone for bone SPECT imaging. Issue 9 (September 2015)

• Record Type: Journal Article
• Authors: Ashton, Ceri E.; Doyle, Susan C.; Redman, Stewart; Graham, Richard; Taylor, Gordon J.; Evans, Martyn J.
• Is Part Of: Nuclear medicine communications. Volume 36:Issue 9(2015:Sep.)
• Publication Date: 2015-09
• Subjects: bone -- image quality -- resolution recovery -- single-photon emission computed tomography; Nuclear medicine -- Periodicals; 616.07575
• DOI: 10.1097/MNM.0000000000000343
• Languages: English
• ISSNs: 0143-3636

Abstract

Abstract : Purpose: In order to locally validate the technique, a retrospective review of a cohort of randomly selected single-photon emission computed tomography (SPECT) bone scans reconstructed with ordered subsets expectation maximization (OSEM) and Evolution for Bone was undertaken. Materials and methods: Thirty consecutive bone SPECT patient data sets (17 spine, nine pelvis, and four spine and pelvis) were chosen. Poisson resampling was used to simulate reduced count data at 50, 75, and 100% of the original number of counts. Evolution for Bone applied resolution recovery to the reduced count images. All images were compared with the original OSEM images, currently used as the standard for clinical use. A qualitative blinded assessment was made by two independent observers, who assessed for noise, contrast, and resolution. Results: Both radiologists saw an improvement in resolution ( P =0.776), noise ( P =0.007), and image quality with all data sets, compared with images processed purely with OSEM and viewed in Volumetrix. However, they completely disagreed on contrast, as the two radiologists scored contrast differently; however, the results are understandable. Conclusion: Images with 50, 75, and 100% of the original counts viewed using Evolution for Bone have improved image quality compared with images processed purely with OSEM and viewed in Volumetrix. Evolution for Bone therefore has great potential in departments for reducing either patient doses, waiting lists, or both.