Phantom, clinical, and texture indices evaluation and optimization of a penalized-likelihood image reconstruction method (Q.Clear) on a BGO PET/CT scanner

Medical Physics
Gabriel Reynés-LlompartJosep M Martí-Climent

Abstract

The aim of this study was to evaluate the behavior of a penalized-likelihood image reconstruction method (Q.Clear) under different count statistics and lesion-to-background ratios (LBR) on a BGO scanner, in order to obtain an optimum penalization factor (β value) to study and optimize for different acquisition protocols and clinical goals. Both phantom and patient images were evaluated. Data from an image quality phantom were acquired using different Lesion-to-Background ratios and acquisition times. Then, each series of the phantom was reconstructed using β values between 50 and 500, at intervals of 50. Hot and cold contrasts were obtained, as well as background variability and contrast-to-noise ratio (CNR). Fifteen 18 F-FDG patients (five brain scans and 10 torso acquisitions) were acquired and reconstructed using the same β values as in the phantom reconstructions. From each lesion in the torso acquisition, noise, contrast, and signal-to-noise ratio (SNR) were computed. Image quality was assessed by two different nuclear medicine physicians. Additionally, the behaviors of 12 different textural indices were studied over 20 different lesions. Q.Clear quantification and optimization in patient studies depends on the activity co...Continue Reading

References

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Mar 18, 2017·Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine·Gabriel Reynés-LlompartJosep M Martí-Climent

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Citations

Nov 13, 2018·Medical Physics·Kenneth J NicholsChristopher J Palestro
Jan 7, 2020·Annals of Nuclear Medicine·Ewa Witkowska-PatenaAgata Walęcka-Mazur
Jun 25, 2019·Nuclear Medicine and Molecular Imaging·Antonella MattiStefano Fanti
Oct 14, 2021·Journal of Applied Clinical Medical Physics·Kenneth J NicholsChristopher J Palestro

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