Journal: European Journal of Nuclear Medicine and Molecular Imaging

Article Title: Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients

doi: 10.1007/s00259-013-2391-1

Figure Lengend Snippet: Recovery coefficients for mean ( a ) and maximum ( b ) values for OSEM 3-D reconstruction algorithm, PSF reconstruction algorithm without filtering (PSF allpass ) and PSF reconstruction algorithm with a 7-mm Gaussian filter (PSF EANM ). Corresponding NEMA NU-2 transverse images through the hot spheres ( c ). Phantom images are scaled on the same maximum value

Article Snippet: For the purpose of this study, raw data were also reconstructed with the OSEM 3-D reconstruction algorithm (4 iterations and 8 subsets) and the PSF reconstruction algorithm (HD; TrueX, Siemens Medical Solutions; 3 iterations and 21 subsets) using a Gaussian filter and an increasing kernel ranging from 6 to 8 mm with a 0.5-mm increment.

Techniques:

Journal: European Journal of Nuclear Medicine and Molecular Imaging

Article Title: Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients

doi: 10.1007/s00259-013-2391-1

Figure Lengend Snippet: Relationship between quantitative values extracted from PSF allpass or PSF EANM and OSEM images, assessed using linear regression analysis and Bland-Altman plots for SUV max ( a ) and SUV mean ( b )

Article Snippet: For the purpose of this study, raw data were also reconstructed with the OSEM 3-D reconstruction algorithm (4 iterations and 8 subsets) and the PSF reconstruction algorithm (HD; TrueX, Siemens Medical Solutions; 3 iterations and 21 subsets) using a Gaussian filter and an increasing kernel ranging from 6 to 8 mm with a 0.5-mm increment.

Techniques:

Journal: European Journal of Nuclear Medicine and Molecular Imaging

Article Title: Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients

doi: 10.1007/s00259-013-2391-1

Figure Lengend Snippet: Impact of the size of the lesion ( a ), the BMI ( b ), the location of the lesion ( c ), tumour homogeneity ( d ) and emission scan duration ( e ) on the ratio between PSF EANM PET and OSEM PET quantitative values ( left panels SUV max , right panels SUV mean ). Note that 30 lesions were not measurable and are therefore not included in the “per size” analysis ( a )

Article Snippet: For the purpose of this study, raw data were also reconstructed with the OSEM 3-D reconstruction algorithm (4 iterations and 8 subsets) and the PSF reconstruction algorithm (HD; TrueX, Siemens Medical Solutions; 3 iterations and 21 subsets) using a Gaussian filter and an increasing kernel ranging from 6 to 8 mm with a 0.5-mm increment.

Techniques:

Journal: European Journal of Nuclear Medicine and Molecular Imaging

Article Title: Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients

doi: 10.1007/s00259-013-2391-1

Figure Lengend Snippet: Representative coronal slices for OSEM, PSF allpass and PSF EANM reconstructions in a patient with a lung tumour in the left upper lobe, bilateral nodal involvement ( a ) and distant metastases (lung, bone and liver) ( b ). Images have been scaled on the same maximum value. Note the improvement in activity recovery visible in a small lung metastasis on the PSF allpass image ( arrow )

Article Snippet: For the purpose of this study, raw data were also reconstructed with the OSEM 3-D reconstruction algorithm (4 iterations and 8 subsets) and the PSF reconstruction algorithm (HD; TrueX, Siemens Medical Solutions; 3 iterations and 21 subsets) using a Gaussian filter and an increasing kernel ranging from 6 to 8 mm with a 0.5-mm increment.

Techniques: Activity Assay

Journal: European Journal of Nuclear Medicine and Molecular Imaging

Article Title: Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients

doi: 10.1007/s00259-013-2391-1

Figure Lengend Snippet: Flow chart for the evaluation of the level of agreement when using PSF EANM or PSF allpass reconstructions for response monitoring (EORTC criteria) either pre- or post-treatment as compared to the exclusive use of OSEM reconstruction (current standard)

Article Snippet: For the purpose of this study, raw data were also reconstructed with the OSEM 3-D reconstruction algorithm (4 iterations and 8 subsets) and the PSF reconstruction algorithm (HD; TrueX, Siemens Medical Solutions; 3 iterations and 21 subsets) using a Gaussian filter and an increasing kernel ranging from 6 to 8 mm with a 0.5-mm increment.

Techniques:

Journal: European Journal of Nuclear Medicine and Molecular Imaging

Article Title: Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients

doi: 10.1007/s00259-013-2391-1

Figure Lengend Snippet: Impact of PSF EANM on response evaluation

Article Snippet: For the purpose of this study, raw data were also reconstructed with the OSEM 3-D reconstruction algorithm (4 iterations and 8 subsets) and the PSF reconstruction algorithm (HD; TrueX, Siemens Medical Solutions; 3 iterations and 21 subsets) using a Gaussian filter and an increasing kernel ranging from 6 to 8 mm with a 0.5-mm increment.

Techniques:

Journal: EJNMMI Research

Article Title: Assessing the impact of different penalty factors of the Bayesian reconstruction algorithm Q.Clear on in vivo low count kinetic analysis of [ 11 C]PHNO brain PET-MR studies

doi: 10.1186/s13550-022-00883-1

Figure Lengend Snippet: Multicomparison analysis of the BP ND results obtained for all structures when images reconstructed the standard OSEM 6iterations 16subsets and 5 mm filter and with the Q.Clear reconstructions with different β values. Note the statistically significant results included on the graphs

Article Snippet: Bias and the Repeatability Coefficient (RC) between the OSEM algorithm (6iterations, 16subsets, 5 mm filter reconstruction under low counts, defined as standard reconstruction for the purposes of this study) and the Q.Clear reconstructions ( n = 10, with differing β values), were produced using MedCalc® version 18 (MedCalc Software, Belgium), computing the standard deviation of the BP ND results obtained for the healthy subjects.

Techniques: