Optimization of PET/CT image quality using the GE 'Sharp IR' point-spread function reconstruction algorithm. Issue 6 (June 2017)

• Record Type: Journal Article
• Authors: Vennart, Nicholas J.; Bird, Nicholas; Buscombe, John; Cheow, Heok K.; Nowosinska, Ewa; Heard, Sarah
• Is Part Of: Nuclear medicine communications. Volume 38:Issue 6(2017:Jun.)
• Publication Date: 2017-06
• Subjects: contrast -- Discovery 690 -- image quality -- PET/CT -- point-spread function -- signal-to-noise -- time-of-flight; Nuclear medicine -- Periodicals; 616.07575
• DOI: 10.1097/MNM.0000000000000669
• Languages: English
• ISSNs: 0143-3636

Abstract

Abstract : Objective: The objective of this study was to quantify any improvement with the GE 'Sharp IR' point-spread function (PSF) reconstruction algorithm in addition to ordered subsets expectation maximum (OSEM) and time-of-flight (TOF) reconstruction algorithms and establish the optimum parameters to be used in clinical studies. Materials and methods: We conducted a range of experiments using the National Electrical Manufacturers Association image quality phantom filled with a 4 : 1 signal-to-background ratio. We scanned the phantom using the GE Discovery 690 PET/CT scanner. We varied iteration number and Gaussian filtration. Results were compared for OSEM, OSEM+TOF and OSEM+TOF+PSF reconstructions. A sample of 15 whole-body fluorine-18-fluorodeoxyglucose were reconstructed with OSEM+TOF and OSEM+TOF+PSF using a selection of optimum reconstruction parameters determined in phantom studies. Clinicians qualitatively ranked their preferred images to choose optimum parameters. Results: The addition of PSF improved signal-to-noise ratios (SNRs), contrast, hot contrast recovery coefficients and noise over OSEM and OSEM+TOF reconstruction algorithms. SNRs were the highest at two iterations and with 0 or 2 mm filters with OSEM+TOF+PSF reconstruction in all phantom studies. Clinicians generally favoured OSEM+TOF+PSF reconstruction with three iterations and a 2 mm filter. Conclusion: PSF reconstruction significantly improved image quality for both clinical and phantom studies. We recommended the optimum reconstruction parameters using three iterations, 24 subsets and a 2 mm filter, which improved SNRs by up to 28.8% for small lesions ( P <0.05).