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Quantification of the impact of TOF and PSF on PET images using the noise-matching concept: clinical and phantom study 被引量:1

Quantification of the impact of TOF and PSF on PET images using the noise-matching concept:clinical and phantom study
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摘要 This study was to assess quantitatively the accuracy of ^(18)F-FDG PET/CT images reconstructed by TOF+PSF and TOF only, considering the noise-matching concept to minimize probable bias in evaluating algorithm performance caused by noise. PET images of similar noise level were considered. Measurements were made on an inhouse phantom with hot inserts of Φ10–37 mm, and oncological images of 14 patients were analyzed. The PET images were reconstructed using the OSEM, OSEM+TOF and OSEM+TOF+PSF algorithms. Optimal reconstruction parameters including iteration, subset, and FWHM of post-smoothing filter were chosen for both the phantom and patient data. In terms of quantitative accuracy, the recovery coefficient(RC) was calculated for the phantom PET images. The signal-to-noise ratio(SNR),lesion-to-background ratio(LBR), and SUV_(max)were evaluated from the phantom and clinical data. The smallest hot insert(Ф10 mm) with 2:1 activity concentration ratio could be detected in the PET image reconstructed using the TOF and TOF+PSF algorithms, but not the OSEM algorithm. The relative difference for SNR between the TOF+PSF and OSEM showed significantly higher values for smaller sizes, while SNR change was smaller for Ф22–37 mm inserts both 2:1 and 4:1 activity concentration ratio. In the clinical study, SNR gains were 1.6 ± 0.53 and 2.7 ± 0.74 for the TOF and TOF+PSF, while the relative difference of contrast was 17 ± 1.05 and 41.5 ± 1.85% for the TOF only and TOF+PSF, respectively. The impact of TOF+PSF is more significant than that of TOF reconstruction, in smaller inserts with low activity concentration ratio. In the clinical PET/CT images, the use of the TOF+PSF algorithm resulted in better SNR and contrast for lesions, and the highest SUV_(max)was also seen for images reconstructed with the TOF+PSF algorithm. This study was to assess quantitatively the accuracy of ^(18)F-FDG PET/CT images reconstructed by TOF+PSF and TOF only, considering the noise-matching concept to minimize probable bias in evaluating algorithm performance caused by noise. PET images of similar noise level were considered. Measurements were made on an inhouse phantom with hot inserts of Φ10–37 mm, and oncological images of 14 patients were analyzed. The PET images were reconstructed using the OSEM, OSEM+TOF and OSEM+TOF+PSF algorithms. Optimal reconstruction parameters including iteration, subset, and FWHM of post-smoothing filter were chosen for both the phantom and patient data. In terms of quantitative accuracy, the recovery coefficient(RC) was calculated for the phantom PET images. The signal-to-noise ratio(SNR),lesion-to-background ratio(LBR), and SUV_(max)were evaluated from the phantom and clinical data. The smallest hot insert(Ф10 mm) with 2:1 activity concentration ratio could be detected in the PET image reconstructed using the TOF and TOF+PSF algorithms, but not the OSEM algorithm. The relative difference for SNR between the TOF+PSF and OSEM showed significantly higher values for smaller sizes, while SNR change was smaller for Ф22–37 mm inserts both 2:1 and 4:1 activity concentration ratio. In the clinical study, SNR gains were 1.6 ± 0.53 and 2.7 ± 0.74 for the TOF and TOF+PSF, while the relative difference of contrast was 17 ± 1.05 and 41.5 ± 1.85% for the TOF only and TOF+PSF, respectively. The impact of TOF+PSF is more significant than that of TOF reconstruction, in smaller inserts with low activity concentration ratio. In the clinical PET/CT images, the use of the TOF+PSF algorithm resulted in better SNR and contrast for lesions, and the highest SUV_(max)was also seen for images reconstructed with the TOF+PSF algorithm.
出处 《Nuclear Science and Techniques》 SCIE CAS CSCD 2017年第11期258-265,共8页 核技术(英文)
基金 supported by the Tehran University of Medical Sciences,Tehran,Iran(No.24166) the Masih Daneshvari Hospital,Shahid Beheshti University of Medical Sciences,Tehran,Iran
关键词 Time of FLIGHT (TOF) Point SPREAD function(PSF) LESION DETECTABILITY PET Quantification Image reconstruction SUV Time of flight(TOF) Point spread function(PSF) Lesion detectability PET Quantification Image reconstruction SUV
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