Assessment of different quantification metrics of [¹⁸F]-NaF PET/CT images of patients with abdominal aortic aneurysm

Background: We aim to assess the spill-in effect and the benefit in quantitative accuracy for [18F]-NaF PET/CT imaging of abdominal aortic aneurysms (AAA) using the background correction (BC) technique. Methods: Seventy-two datasets of patients diagnosed with AAA were reconstructed with ordered subset expectation maximization algorithm incorporating point spread function (PSF). Spill-in effect was investigated for the entire aneurysm (AAA), and part of the aneurysm excluding the region close to the bone (AAAexc). Quantifications of PSF and PSF+BC images using different thresholds (% of max. SUV in target regions-of-interest) to derive target-to-background (TBR) values (TBRmax, TBR90, TBR70 and TBR50) were compared at 3 and 10 iterations. Results: TBR differences were observed between AAA and AAAexc due to spill-in effect from the bone into the aneurysm. TBRmax showed the highest sensitivity to the spill-in effect while TBR50 showed the least. The spill-in effect was reduced at 10 iterations compared to 3 iterations, but at the expense of reduced contrast-to-noise ratio (CNR). TBR50 yielded the best trade-off between increased CNR and reduced spill-in effect. PSF+BC method reduced TBR sensitivity to spill-in effect, especially at 3 iterations, compared to PSF (P-value ≤ 0.05). Conclusion: TBR50 is robust metric for reduced spill-in and increased CNR

Iterative reconstruction incorporating background correction improves quantification of [18F]-NaF PET/CT images of patients with abdominal aortic aneurysm

Background A confounding issue in [18F]-NaF PET/CT imaging of abdominal aortic aneurysms (AAA) is the spill in contamination from the bone into the aneurysm. This study investigates and corrects for this spill in contamination using the background correction (BC) technique without the need to manually exclude the part of the AAA region close to the bone. Methods Seventy-two (72) datasets of patients with AAA were reconstructed with the standard ordered subset expectation maximization (OSEM) algorithm incorporating point spread function (PSF) modelling. The spill in effect in the aneurysm was investigated using two target regions of interest (ROIs): one covering the entire aneurysm (AAA), and the other covering the aneurysm but excluding the part close to the bone (AAAexc). ROI analysis was performed by comparing the maximum SUV in the target ROI (SUVmax(T)), the corrected cSUVmax (SUVmax(T) − SUVmean(B)) and the target-to-blood ratio (TBR = SUVmax(T)/SUVmean(B)) with respect to the mean SUV in the right atrium region. Results There is a statistically significant higher [18F]-NaF uptake in the aneurysm than normal aorta and this is not correlated with the aneurysm size. There is also a significant difference in aneurysm uptake for OSEM and OSEM + PSF (but not OSEM + PSF + BC) when quantifying with AAA and AAAexc due to the spill in from the bone. This spill in effect depends on proximity of the aneurysms to the bone as close aneurysms suffer more from spill in than farther ones. Conclusion The background correction (OSEM + PSF + BC) technique provided more robust AAA quantitative assessments regardless of the AAA ROI delineation method, and thus it can be considered as an effective spill in correction method for [18F]-NaF AAA studies

Analytical Quantification of Aortic Valve 18F-Sodium Fluoride PET Uptake

BackgroundChallenges to cardiac PET-CT include patient motion, prolonged image acquisition and a reduction of counts due to gating. We compared two analytical tools, FusionQuant and OsiriX, for quantification of gated cardiac 18F-sodium fluoride (18F-fluoride) PET-CT imaging.MethodsTwenty-seven patients with aortic stenosis were included, 15 of whom underwent repeated imaging 4 weeks apart. Agreement between analytical tools and scan-rescan reproducibility was determined using the Bland-Altman method and Lin's concordance correlation coefficients (CCC).ResultsImage analysis was faster with FusionQuant [median time (IQR) 7:10 (6:40-8:20) minutes] compared with OsiriX [8:30 (8:00-10:10) minutes, p = .002]. Agreement of uptake measurements between programs was excellent, CCC = 0.972 (95% CI 0.949-0.995) for mean tissue-to-background ratio (TBRmean) and 0.981 (95% CI 0.965-0.997) for maximum tissue-to-background ratio (TBRmax). Mean noise decreased from 11.7% in the diastolic gate to 6.7% in motion-corrected images (p = .002); SNR increased from 25.41 to 41.13 (p = .0001). Aortic valve scan-rescan reproducibility for TBRmax was improved with FusionQuant using motion correction compared to OsiriX (error ± 36% vs ± 13%, p < .001) while reproducibility for TBRmean was similar (± 10% vs ± 8% p = .252).Conclusion18F-fluoride PET quantification with FusionQuant and OsiriX is comparable. FusionQuant with motion correction offers advantages with respect to analysis time and reproducibility of TBRmax values