A clinical evaluation of the impact of the Bayesian penalized likelihood reconstruction algorithm on PET FDG metrics. Issue 11 (November 2017)

• Record Type: Journal Article
• Authors: Vallot, Delphine; Caselles, Olivier; Chaltiel, Leonor; Fernandez, Anthony; Gabiache, Erwan; Dierickx, Lawrence; Zerdoud, Slimane; Bauriaud, Mathilde; Courbon, Frédéric
• Is Part Of: Nuclear medicine communications. Volume 38:Issue 11(2017:Nov.)
• Publication Date: 2017-11
• Subjects: Bayesian penalized likelihood algorithm -- image quality enhancement -- image reconstruction -- medical oncology -- positron emission tomography; Nuclear medicine -- Periodicals; 616.07575
• DOI: 10.1097/MNM.0000000000000729
• Languages: English
• ISSNs: 0143-3636

Abstract

Abstract : Purpose: The aim of this study was to evaluate the impact of using the Bayesian penalized likelihood (BPL) algorithm on a bismuth germanium oxide positron emission tomography (PET)/computed tomography (CT) system for 18 F-FDG PET/CT exams in case of low injected activity and scan duration. Materials and methods: 18 F-FDG respiratory gated PET/CT performed on 102 cancer patients, injected with ∼2 MBq/kg of 18 F-FDG, were reconstructed using two algorithms: ordered subset expectation maximization (OSEM) and BPL. The signal-to-noise ratio (SNR) was calculated as the ratio of mean standard uptake value (SUV) over the standard deviation in a reference volume defined automatically in the liver. The peak SUV and volumes were also measured in lesions larger than 2 cm 3 thanks to the automated segmentation method. Results: On 85 respiratory gated patients, the median SNR was significantly higher with BPL ( P <0.0001) and it is even better when the BMI of the patient increases (odds ratio=1.26). For the 55 lesions, BPL significantly increased the SUVpeak [difference: (−0.5; 1.4), median=0.4, P <0.0001] compared with OSEM in 83.6% of the cases. With BPL, the volume was lower in 61.8% of the cases compared with OSEM, but this was not statistically significant. Conclusion: The BPL algorithm improves the image quality and lesion contrast and appears to be particularly appropriate for patients with a high BMI as it improves the SNR. However, it will be important for patient follow-up or multicenter studies to use the same algorithm and preferably BPL.