1
|
Zhu Y, Tran Q, Wang Y, Badawi RD, Cherry SR, Qi J, Abbaszadeh S, Wang G. Optimization-derived blood input function using a kernel method and its evaluation with total-body PET for brain parametric imaging. Neuroimage 2024; 293:120611. [PMID: 38643890 PMCID: PMC11251003 DOI: 10.1016/j.neuroimage.2024.120611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 04/11/2024] [Accepted: 04/12/2024] [Indexed: 04/23/2024] Open
Abstract
Dynamic PET allows quantification of physiological parameters through tracer kinetic modeling. For dynamic imaging of brain or head and neck cancer on conventional PET scanners with a short axial field of view, the image-derived input function (ID-IF) from intracranial blood vessels such as the carotid artery (CA) suffers from severe partial volume effects. Alternatively, optimization-derived input function (OD-IF) by the simultaneous estimation (SIME) method does not rely on an ID-IF but derives the input function directly from the data. However, the optimization problem is often highly ill-posed. We proposed a new method that combines the ideas of OD-IF and ID-IF together through a kernel framework. While evaluation of such a method is challenging in human subjects, we used the uEXPLORER total-body PET system that covers major blood pools to provide a reference for validation. METHODS The conventional SIME approach estimates an input function using a joint estimation together with kinetic parameters by fitting time activity curves from multiple regions of interests (ROIs). The input function is commonly parameterized with a highly nonlinear model which is difficult to estimate. The proposed kernel SIME method exploits the CA ID-IF as a priori information via a kernel representation to stabilize the SIME approach. The unknown parameters are linear and thus easier to estimate. The proposed method was evaluated using 18F-fluorodeoxyglucose studies with both computer simulations and 20 human-subject scans acquired on the uEXPLORER scanner. The effect of the number of ROIs on kernel SIME was also explored. RESULTS The estimated OD-IF by kernel SIME showed a good match with the reference input function and provided more accurate estimation of kinetic parameters for both simulation and human-subject data. The kernel SIME led to the highest correlation coefficient (R = 0.97) and the lowest mean absolute error (MAE = 10.5 %) compared to using the CA ID-IF (R = 0.86, MAE = 108.2 %) and conventional SIME (R = 0.57, MAE = 78.7 %) in the human-subject evaluation. Adding more ROIs improved the overall performance of the kernel SIME method. CONCLUSION The proposed kernel SIME method shows promise to provide an accurate estimation of the blood input function and kinetic parameters for brain PET parametric imaging.
Collapse
Affiliation(s)
- Yansong Zhu
- Department of Radiology, University of California Davis Medical Center, Sacramento, CA 95817, USA.
| | - Quyen Tran
- Department of Radiology, University of California Davis Medical Center, Sacramento, CA 95817, USA
| | - Yiran Wang
- Department of Radiology, University of California Davis Medical Center, Sacramento, CA 95817, USA; Department of Biomedical Engineering, University of California at Davis, Davis, CA 95616, USA
| | - Ramsey D Badawi
- Department of Radiology, University of California Davis Medical Center, Sacramento, CA 95817, USA; Department of Biomedical Engineering, University of California at Davis, Davis, CA 95616, USA
| | - Simon R Cherry
- Department of Radiology, University of California Davis Medical Center, Sacramento, CA 95817, USA; Department of Biomedical Engineering, University of California at Davis, Davis, CA 95616, USA
| | - Jinyi Qi
- Department of Biomedical Engineering, University of California at Davis, Davis, CA 95616, USA
| | - Shiva Abbaszadeh
- Department of Electrical and Computer Engineering, University of California at Santa Cruz, Santa Cruz, CA 95064, USA
| | - Guobao Wang
- Department of Radiology, University of California Davis Medical Center, Sacramento, CA 95817, USA
| |
Collapse
|
2
|
Bartlett EA, Lesanpezeshki M, Anishchenko S, Shkolnik I, Ogden RT, Mann JJ, Beylin D, Miller JM, Zanderigo F. Dynamic Human Brain Imaging with a Portable PET Camera: Comparison to a Standard Scanner. J Nucl Med 2024; 65:320-326. [PMID: 38124218 PMCID: PMC10858383 DOI: 10.2967/jnumed.122.265309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 10/19/2023] [Indexed: 12/23/2023] Open
Abstract
Portable, cost-effective PET cameras can radically expand the applicability of PET. We present here a within-participant comparison of fully quantified [18F]FDG dynamic scans in healthy volunteers using the standard Biograph mCT scanner and portable CerePET scanner. Methods: Each of 20 healthy volunteers underwent dynamic [18F]FDG imaging with both scanners (1-154 d apart) and concurrent arterial blood sampling. Tracer SUV, net influx rate (Ki), and the corresponding cerebral metabolic rate of glucose (CMRglu) were quantified at regional and voxel levels. Results: At the regional level, CerePET outcome measure estimates within participants robustly correlated with Biograph mCT estimates in the neocortex, wherein the average Pearson correlation coefficients across participants ± SD were 0.83 ± 0.07 (SUV) and 0.85 ± 0.08 (Ki and CMRglu). There was also strong agreement between CerePET and Biograph mCT estimates, wherein the average regression slopes across participants were 0.84 ± 0.17 (SUV), 0.83 ± 0.17 (Ki), and 0.85 ± 0.18 (CMRglu). There was similar bias across participants but higher correlation and less variability in subcortical regions than in cortical regions. Pearson correlation coefficients for subcortical regions equaled 0.97 ± 0.02 (SUV) and 0.97 ± 0.03 (Ki and CMRglu), and average regression slopes equaled 0.79 ± 0.14 (SUV), 0.83 ± 0.11 (Ki), and 0.86 ± 0.11 (CMRglu). In voxelwise assessment, CerePET and Biograph mCT estimates across outcome measures were significantly different only in a cluster of left frontal white matter. Conclusion: Our results indicate robust correlation and agreement between semi- and fully quantitative brain glucose metabolism measurements from portable CerePET and standard Biograph mCT scanners. The results obtained with a portable PET scanner in this comparison in humans require follow-up but lend confidence to the feasibility of more flexible and portable brain imaging with PET.
Collapse
Affiliation(s)
- Elizabeth A Bartlett
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, New York;
- Department of Psychiatry, Columbia University Medical Center, New York, New York
| | - Mohammad Lesanpezeshki
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, New York
| | | | | | - R Todd Ogden
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, New York
- Department of Psychiatry, Columbia University Medical Center, New York, New York
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York; and
| | - J John Mann
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, New York
- Department of Psychiatry, Columbia University Medical Center, New York, New York
- Department of Radiology, Columbia University Medical Center, New York, New York
| | | | - Jeffrey M Miller
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, New York
- Department of Psychiatry, Columbia University Medical Center, New York, New York
| | - Francesca Zanderigo
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, New York
- Department of Psychiatry, Columbia University Medical Center, New York, New York
| |
Collapse
|
3
|
Cumming P, Dias AH, Gormsen LC, Hansen AK, Alberts I, Rominger A, Munk OL, Sari H. Single time point quantitation of cerebral glucose metabolism by FDG-PET without arterial sampling. EJNMMI Res 2023; 13:104. [PMID: 38032409 PMCID: PMC10689590 DOI: 10.1186/s13550-023-01049-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 11/01/2023] [Indexed: 12/01/2023] Open
Abstract
BACKGROUND Until recently, quantitation of the net influx of 2-[18F]fluorodeoxyglucose (FDG) to brain (Ki) and the cerebrometabolic rate for glucose (CMRglc) required serial arterial blood sampling in conjunction with dynamic positron emission tomography (PET) recordings. Recent technical innovations enable the identification of an image-derived input function (IDIF) from vascular structures, but are frequently still encumbered by the need for interrupted sequences or prolonged recordings that are seldom available outside of a research setting. In this study, we tested simplified methods for quantitation of FDG-Ki by linear graphic analysis relative to the descending aorta IDIF in oncology patients examined using a Biograph Vision 600 PET/CT with continuous bed motion (Aarhus) or using a recently installed Biograph Vision Quadra long-axial field-of-view (FOV) scanner (Bern). RESULTS Correlation analysis of the coefficients of a tri-exponential decomposition of the IDIFs measured during 67 min revealed strong relationships among the total area under the curve (AUC), the terminal normalized arterial integral (theta(52-67 min)), and the terminal image-derived arterial FDG concentration (Ca(52-67 min)). These relationships enabled estimation of the missing AUC from late recordings of the IDIF, from which we then calculated FDG-Ki in brain by two-point linear graphic analysis using a population mean ordinate intercept and the single late frame. Furthermore, certain aspects of the IDIF data from Aarhus showed a marked age-dependence, which was not hitherto reported for the case of FDG pharmacokinetics. CONCLUSIONS The observed interrelationships between pharmacokinetic parameters in the IDIF measured during the PET recording support quantitation of FDG-Ki in brain using a single averaged frame from the interval 52-67 min post-injection, with minimal error relative to calculation from the complete dynamic sequences.
Collapse
Affiliation(s)
- Paul Cumming
- Department of Nuclear Medicine, Bern University Hospital, Freiburgstrasse 18, INO B 214.C, 3010, Bern, Switzerland.
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, Australia.
| | - André H Dias
- Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark
| | - Lars C Gormsen
- Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Allan K Hansen
- Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark
| | - Ian Alberts
- Department of Nuclear Medicine, Bern University Hospital, Freiburgstrasse 18, INO B 214.C, 3010, Bern, Switzerland
| | - Axel Rominger
- Department of Nuclear Medicine, Bern University Hospital, Freiburgstrasse 18, INO B 214.C, 3010, Bern, Switzerland
| | - Ole L Munk
- Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Hasan Sari
- Department of Nuclear Medicine, Bern University Hospital, Freiburgstrasse 18, INO B 214.C, 3010, Bern, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| |
Collapse
|