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OBJECTIVES: Investigate the effect of a novel Bayesian penalised likelihood (BPL) reconstruction algorithm on analysis of pulmonary nodules examined with 18F-FDG PET/CT, and to determine its effect on small, sub-10-mm nodules. METHODS: 18F-FDG PET/CTs performed for nodule evaluation in 104 patients (121 nodules) were retrospectively reconstructed using the new algorithm, and compared to time-of-flight ordered subset expectation maximisation (OSEM) reconstruction. Nodule and background parameters were analysed semi-quantitatively and visually. RESULTS: BPL compared to OSEM resulted in statistically significant increases in nodule SUVmax (mean 5.3 to 8.1, p < 0.00001), signal-to-background (mean 3.6 to 5.3, p < 0.00001) and signal-to-noise (mean 24 to 41, p < 0.00001). Mean percentage increase in SUVmax (%ΔSUVmax) was significantly higher in nodules ≤10 mm (n = 31, mean 73%) compared to >10 mm (n = 90, mean 42 %) (p = 0.025). Increase in signal-to-noise was higher in nodules ≤10 mm (224%, mean 12 to 27) compared to >10 mm (165%, mean 28 to 46). When applying optimum SUVmax thresholds for detecting malignancy, the sensitivity and accuracy increased using BPL, with the greatest improvements in nodules ≤10 mm. CONCLUSION: BPL results in a significant increase in signal-to-background and signal-to-noise compared to OSEM. When semi-quantitative analyses to diagnose malignancy are applied, higher SUVmax thresholds may be warranted owing to the SUVmax increase compared to OSEM. KEY POINTS: • Novel Bayesian penalised likelihood PET reconstruction was applied for lung nodule evaluation. • This was compared to current standard of care OSEM reconstruction. • The novel reconstruction generated significant increases in lung nodule signal-to-background and signal-to-noise. • These increases were highest in small, sub-10-mm pulmonary nodules. • Higher SUV max thresholds may be warranted when using semi-quantitative analyses to diagnose malignancy.

Original publication

DOI

10.1007/s00330-015-3832-y

Type

Journal article

Journal

Eur Radiol

Publication Date

02/2016

Volume

26

Pages

576 - 584

Keywords

Image quality enhancement, Image reconstruction, Positron-emission tomography, Signal-to-noise ratio, Solitary pulmonary nodule, Adult, Aged, Aged, 80 and over, Algorithms, Bayes Theorem, Female, Fluorodeoxyglucose F18, Humans, Image Processing, Computer-Assisted, Lung, Lung Neoplasms, Male, Middle Aged, Multimodal Imaging, Positron-Emission Tomography, Radiopharmaceuticals, Retrospective Studies, Solitary Pulmonary Nodule, Tomography, X-Ray Computed, Young Adult