Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences
Purpose: With single-photon emission computed tomography, simultaneous imaging of two physiological processes relies on discrimination of the energy of the emitted gamma rays, whereas the application of dual-tracer imaging to positron emission tomography (PET) imaging has been limited by the charact...
| Main Authors: | , , , , |
|---|---|
| Format: | Journal Article |
| Published: |
Springer New York LLC
2013
|
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1007/s11307-013-0631-1 http://hdl.handle.net/20.500.11937/13354 |
| _version_ | 1848748325155635200 |
|---|---|
| author | El Fakhri, G. Trott, Cathryn Sitek, A. Bonab, A. Alpert, N. |
| author_facet | El Fakhri, G. Trott, Cathryn Sitek, A. Bonab, A. Alpert, N. |
| author_sort | El Fakhri, G. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Purpose: With single-photon emission computed tomography, simultaneous imaging of two physiological processes relies on discrimination of the energy of the emitted gamma rays, whereas the application of dual-tracer imaging to positron emission tomography (PET) imaging has been limited by the characteristic 511-keV emissions.Procedures: To address this limitation, we developed a novel approach based on generalized factor analysis of dynamic sequences (GFADS) that exploits spatio-temporal differences between radiotracers and applied it to near-simultaneous imaging of 2-deoxy-2-[18F]fluoro-D-glucose (FDG) (brain metabolism) and 11C-raclopride (D2) with simulated human data and experimental rhesus monkey data. We show theoretically and verify by simulation and measurement that GFADS can separate FDG and raclopride measurements that are made nearly simultaneously. Results: The theoretical development shows that GFADS can decompose the studies at several levels: (1) It decomposes the FDG and raclopride study so that they can be analyzed as though they were obtained separately. (2) If additional physiologic/anatomic constraints can be imposed, further decomposition is possible. (3) For the example of raclopride, specific and nonspecific binding can be determined on a pixel-by-pixel basis. We found good agreement between the estimated GFADS factors and the simulated ground truth time activity curves (TACs), and between the GFADS factor images and the corresponding ground truth activity distributions with errors less than 7.3±1.3 %. Biases in estimation of specific D2 binding and relative metabolism activity were within 5.9±3.6 % compared to the ground truth values. We also evaluated our approach in simultaneous dual-isotope brain PET studies in a rhesus monkey and obtained accuracy of better than 6 % in a mid-striatal volume, for striatal activity estimation. Conclusions: Dynamic image sequences acquired following near-simultaneous injection of two PET radiopharmaceuticals can be separated into components based on the differences in the kinetics, provided their kinetic behaviors are distinct. |
| first_indexed | 2025-11-14T07:03:15Z |
| format | Journal Article |
| id | curtin-20.500.11937-13354 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:03:15Z |
| publishDate | 2013 |
| publisher | Springer New York LLC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-133542017-02-28T01:33:33Z Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences El Fakhri, G. Trott, Cathryn Sitek, A. Bonab, A. Alpert, N. Brain imaging Quantitation Dynamic PET Purpose: With single-photon emission computed tomography, simultaneous imaging of two physiological processes relies on discrimination of the energy of the emitted gamma rays, whereas the application of dual-tracer imaging to positron emission tomography (PET) imaging has been limited by the characteristic 511-keV emissions.Procedures: To address this limitation, we developed a novel approach based on generalized factor analysis of dynamic sequences (GFADS) that exploits spatio-temporal differences between radiotracers and applied it to near-simultaneous imaging of 2-deoxy-2-[18F]fluoro-D-glucose (FDG) (brain metabolism) and 11C-raclopride (D2) with simulated human data and experimental rhesus monkey data. We show theoretically and verify by simulation and measurement that GFADS can separate FDG and raclopride measurements that are made nearly simultaneously. Results: The theoretical development shows that GFADS can decompose the studies at several levels: (1) It decomposes the FDG and raclopride study so that they can be analyzed as though they were obtained separately. (2) If additional physiologic/anatomic constraints can be imposed, further decomposition is possible. (3) For the example of raclopride, specific and nonspecific binding can be determined on a pixel-by-pixel basis. We found good agreement between the estimated GFADS factors and the simulated ground truth time activity curves (TACs), and between the GFADS factor images and the corresponding ground truth activity distributions with errors less than 7.3±1.3 %. Biases in estimation of specific D2 binding and relative metabolism activity were within 5.9±3.6 % compared to the ground truth values. We also evaluated our approach in simultaneous dual-isotope brain PET studies in a rhesus monkey and obtained accuracy of better than 6 % in a mid-striatal volume, for striatal activity estimation. Conclusions: Dynamic image sequences acquired following near-simultaneous injection of two PET radiopharmaceuticals can be separated into components based on the differences in the kinetics, provided their kinetic behaviors are distinct. 2013 Journal Article http://hdl.handle.net/20.500.11937/13354 http://link.springer.com/article/10.1007/s11307-013-0631-1 Springer New York LLC restricted |
| spellingShingle | Brain imaging Quantitation Dynamic PET El Fakhri, G. Trott, Cathryn Sitek, A. Bonab, A. Alpert, N. Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences |
| title | Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences |
| title_full | Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences |
| title_fullStr | Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences |
| title_full_unstemmed | Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences |
| title_short | Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences |
| title_sort | dual-tracer pet using generalized factor analysis of dynamic sequences |
| topic | Brain imaging Quantitation Dynamic PET |
| url | http://link.springer.com/article/10.1007/s11307-013-0631-1 http://hdl.handle.net/20.500.11937/13354 |