A Prospective, Matched Comparison Study of SUV Measurements From Time-of-Flight Versus Non–Time-of-Flight PET/CT Scanners

2016 ◽  
Vol 41 (7) ◽  
pp. e323-e326 ◽  
Author(s):  
Holly M. Thompson ◽  
Ryogo Minamimoto ◽  
Mehran Jamali ◽  
Amir Barkhodari ◽  
Rie von Eyben ◽  
...  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhifang Wu ◽  
Binwei Guo ◽  
Bin Huang ◽  
Xinzhong Hao ◽  
Ping Wu ◽  
...  

AbstractTo evaluate the quantification accuracy of different positron emission tomography-computed tomography (PET/CT) reconstruction algorithms, we measured the recovery coefficient (RC) and contrast recovery (CR) in phantom studies. The results played a guiding role in the partial-volume-effect correction (PVC) for following clinical evaluations. The PET images were reconstructed with four different methods: ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), OSEM with TOF and point spread function (PSF), and Bayesian penalized likelihood (BPL, known as Q.Clear in the PET/CT of GE Healthcare). In clinical studies, SUVmax and SUVmean (the maximum and mean of the standardized uptake values, SUVs) of 75 small pulmonary nodules (sub-centimeter group: < 10 mm and medium-size group: 10–25 mm) were measured from 26 patients. Results show that Q.Clear produced higher RC and CR values, which can improve quantification accuracy compared with other methods (P < 0.05), except for the RC of 37 mm sphere (P > 0.05). The SUVs of sub-centimeter fludeoxyglucose (FDG)-avid pulmonary nodules with Q.Clear illustrated highly significant differences from those reconstructed with other algorithms (P < 0.001). After performing the PVC, highly significant differences (P < 0.001) still existed in the SUVmean measured by Q.Clear comparing with those measured by the other algorithms. Our results suggest that the Q.Clear reconstruction algorithm improved the quantification accuracy towards the true uptake, which potentially promotes the diagnostic confidence and treatment response evaluations with PET/CT imaging, especially for the sub-centimeter pulmonary nodules. For small lesions, PVC is essential.


2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Jakob W. Kist ◽  
Manfred van der Vlies ◽  
Otto S. Hoekstra ◽  
Henri N. J. M. Greuter ◽  
Bart de Keizer ◽  
...  

2017 ◽  
Vol 128 (3) ◽  
pp. 750-755 ◽  
Author(s):  
Andre M. Wineland ◽  
Jareen Meinzen-Derr ◽  
Paul Willging

2010 ◽  
Vol 51 (2) ◽  
pp. 237-245 ◽  
Author(s):  
C. Lois ◽  
B. W. Jakoby ◽  
M. J. Long ◽  
K. F. Hubner ◽  
D. W. Barker ◽  
...  
Keyword(s):  
Pet Ct ◽  

2018 ◽  
Vol 63 (23) ◽  
pp. 235010 ◽  
Author(s):  
Alice Ferretti ◽  
Sotirios Chondrogiannis ◽  
Lucia Rampin ◽  
Elena Bellan ◽  
Maria Cristina Marzola ◽  
...  

Author(s):  
Miri Weiss Cohen ◽  
John A. Kennedy ◽  
Archil Pirmisashvili ◽  
Gleb Orlikov

This paper describes an automatic system for analyzing phantom images from two types of PET/CT scanners. The system was developed for the purpose of obtaining tomographic image quality parameters, which determine a number of different performance parameters, primarily scanner sensitivity, tomographic uniformity, contrast and spatial resolution. The system provides a method for generating and altering image masks used for the analysis of PET images, which are then automatically aligned with the PET data. The system automatically generates Quality Control (QC) reports and is currently being used at clinical PET/CT center.


Author(s):  
B. W. Jakoby ◽  
Y. Bercier ◽  
M. Conti ◽  
M. Casey ◽  
T. Gremillion ◽  
...  
Keyword(s):  

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