The value of Bayesian penalized likelihood reconstruction for improving lesion conspicuity of malignant lung tumors on 18 F-FDG PET/CT: comparison with ordered subset expectation maximization reconstruction incorporating time-of-flight model and point spread function correction

AbstractObjectiveTo evaluate the value of Bayesian penalized likelihood (BPL) reconstruction for improving lesion conspicuity of malignant lung tumors on18F-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography computed tomography (PET/CT) as compared with the ordered subset expectation maximization (OSEM) reconstruction incorporating time-of-flight (TOF) model and point-spread-function (PSF) correction.MethodsTwenty-nine patients with primary or metastatic lung cancers who underwent18F-FDG PET/CT were retrospectively studied. PET images were reconstructed with OSEM  + TOF, OSEM + TOF + PSF, and BPL with noise penalty strengthβ-value of 200, 400, 600, and 800. The signal-to-noise ratio (SNR) was determined in normal liver parenchyma. Lung lesion conspicuity was evaluated in 50 lung lesions by using a 4-point scale (0, no visible; 1, poor; 2, good; 3, excellent conspicuity). Two observers were independently asked to choose the most preferred reconstruction for detecting the lung lesions on a per-patient level. The maximum standardized uptake value (SUVmax) was measured in each of the 50 lung lesions.ResultsLiver SNR on the images reconstructed by BPL withβ-value of 600 and 800 (17.8  ± 3.7 and 22.5 ± 4.6, respectively) was significantly higher than that by OSEM + TOF + PSF (15.0 ± 3.4,p 
Source: Annals of Nuclear Medicine - Category: Nuclear Medicine Source Type: research

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