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Rapid Whole-Body FDG PET/MRI in Oncology Patients: Utility of Combining Bayesian Penalised Likelihood PET Reconstruction and Abbreviated MRI.

Authors :
Inukai, Junko Inoue
Nogami, Munenobu
Tachibana, Miho
Zeng, Feibi
Nishitani, Tatsuya
Kubo, Kazuhiro
Murakami, Takamichi
Source :
Diagnostics (2075-4418). Jun2023, Vol. 13 Issue 11, p1871. 16p.
Publication Year :
2023

Abstract

This study evaluated the diagnostic value of a rapid whole-body fluorodeoxyglucose (FDG) positron emission tomography (PET)/magnetic resonance imaging (MRI) approach, combining Bayesian penalised likelihood (BPL) PET with an optimised β value and abbreviated MRI (abb-MRI). The study compares the diagnostic performance of this approach with the standard PET/MRI that utilises ordered subsets expectation maximisation (OSEM) PET and standard MRI (std-MRI). The optimal β value was determined by evaluating the noise-equivalent count (NEC) phantom, background variability, contrast recovery, recovery coefficient, and visual scores (VS) for OSEM and BPL with β100–1000 at 2.5-, 1.5-, and 1.0-min scans, respectively. Clinical evaluations were conducted for NECpatient, NECdensity, liver signal-to-noise ratio (SNR), lesion maximum standardised uptake value, lesion signal-to-background ratio, lesion SNR, and VS in 49 patients. The diagnostic performance of BPL/abb-MRI was retrospectively assessed for lesion detection and differentiation in 156 patients using VS. The optimal β values were β600 for a 1.5-min scan and β700 for a 1.0-min scan. BPL/abb-MRI at these β values was equivalent to OSEM/std-MRI for a 2.5-min scan. By combining BPL with optimal β and abb-MRI, rapid whole-body PET/MRI could be achieved in ≤1.5 min per bed position, while maintaining comparable diagnostic performance to standard PET/MRI. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20754418
Volume :
13
Issue :
11
Database :
Academic Search Index
Journal :
Diagnostics (2075-4418)
Publication Type :
Academic Journal
Accession number :
164214297
Full Text :
https://doi.org/10.3390/diagnostics13111871