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Updated: Feb 8, 2026

Functional Imaging of Brown Fat in Mice with 18F-FDG micro-PET/CT
Published on: November 23, 2012
Optimization of reconstruction and quantification of motion-corrected coronary PET-CT
Mhairi K Doris1,2, Yuka Otaki2, Sandeep K Krishnan2
1BHF Centre for Cardiovascular Science, Clinical Research Imaging Centre, Edinburgh Heart Centre, University of Edinburgh, 49 Little France Crescent, Edinburgh, Scotland, EH16 4SB, UK.
Background:
Coronary PET shows promise in the detection of high-risk atherosclerosis, but there remains a need to optimize imaging and reconstruction techniques. We investigated the impact of reconstruction parameters and cardiac motion-correction in 18F Sodium Fluoride (18F-NaF) PET.
Methods:
Twenty-two patients underwent 18F-NaF PET within 22 days of an acute coronary syndrome. Optimal reconstruction parameters were determined in a subgroup of six patients. Motion-correction was performed on ECG-gated data of all patients with optimal reconstruction. Tracer uptake was quantified in culprit and reference lesions by computing signal-to-noise ratio (SNR) in diastolic, summed, and motion-corrected images.
Results:
Reconstruction using 24 subsets, 4 iterations, point-spread-function modelling, time of flight, and 5-mm post-filtering provided the highest median SNR (31.5) compared to 4 iterations 0-mm (22.5), 8 iterations 0-mm (21.1), and 8 iterations 5-mm (25.6; all P < .05). Motion-correction improved SNR of culprit lesions (n = 33) (24.5[19.9-31.5]) compared to diastolic (15.7[12.4-18.1]; P < .001) and summed data (22.1[18.9-29.2]; P < .001). Motion-correction increased the SNR difference between culprit and reference lesions (10.9[6.3-12.6]) compared to diastolic (6.2[3.6-10.3]; P = .001) and summed data (7.1 [4.8-11.6]; P = .001).
Conclusions:
The number of iterations and extent of post-filtering has marked effects on coronary 18F-NaF PET quantification. Cardiac motion-correction improves discrimination between culprit and reference lesions.
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