Abstract
Abstract
Purpose
New total-body PET scanners with a long axial field of view (LAFOV) allow for higher temporal resolution due to higher sensitivity, which facilitates perfusion estimation by model-free deconvolution. Fundamental tracer kinetic theory predicts that perfusion can be estimated for all tracers despite their different fates given sufficiently high temporal resolution of 1 s or better, bypassing the need for compartment modelling. The aim of this study was to investigate whether brain perfusion could be estimated using model-free Tikhonov generalized deconvolution for five different PET tracers, [15O]H2O, [11C]PIB, [18F]FE-PE2I, [18F]FDG and [18F]FET. To our knowledge, this is the first example of a general model-free approach to estimate cerebral blood flow (CBF) from PET data.
Methods
Twenty-five patients underwent dynamic LAFOV PET scanning (Siemens, Quadra). PET images were reconstructed with an isotropic voxel resolution of 1.65 mm3. Time framing was 40 × 1 s during bolus passage followed by increasing framing up to 60 min. AIF was obtained from the descending aorta. Both voxel- and region-based calculations of perfusion in the thalamus were performed using the Tikhonov method. The residue impulse response function was used to estimate the extraction fraction of tracer leakage across the blood–brain barrier.
Results
CBF ranged from 37 to 69 mL blood min−1 100 mL of tissue−1 in the thalamus. Voxelwise calculation of CBF resulted in CBF maps in the physiologically normal range. The extraction fractions of [15O]H2O, [18F]FE-PE2I, [11C]PIB, [18F]FDG and [18F]FET in the thalamus were 0.95, 0.78, 0.62, 0.19 and 0.03, respectively.
Conclusion
The high temporal resolution and sensitivity associated with LAFOV PET scanners allow for noninvasive perfusion estimation of multiple tracers. The method provides an estimation of the residue impulse response function, from which the fate of the tracer can be studied, including the extraction fraction, influx constant, volume of distribution and transit time distribution, providing detailed physiological insight into normal and pathologic tissue.
Funder
Royal Library, Copenhagen University Library
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine,Radiology, Nuclear Medicine and imaging,General Medicine
Reference32 articles.
1. Vestergaard MB, Calvo OP, Hansen AE, Rosenbaum S, Larsson HBW, Henriksen OM, Law I. Validation of kinetic modeling of [15O]H2O PET using an image derived input function on hybrid PET/MRI. Neuroimage. 2021;233: 117950. https://doi.org/10.1016/j.neuroimage.2021.117950.
2. Meier P, Zierler KL. On the theory of the indicator-dilution method for measurement of blood flow and volume. J Appl Physiol. 1954;6(12):731–44. https://doi.org/10.1152/jappl.1954.6.12.731.
3. Bassingthwaighte JB, Chinard FP, Crone C, Goresky CA, Lassen NA, Reneman RS, Zierler KL. Terminology for mass transport and exchange. Am J Physiol. 1986;250(4 Pt 2):H539–45. https://doi.org/10.1152/ajpheart.1986.250.4.H539.
4. Kety SS. The theory and applications of the exchange of inert gas at the lungs and tissues. Pharmacol Rev. 1951;3(1):1–41.
5. Hastie T, Tibshirani R, Friedman J, editors. The elements of statistical learning. Data mining, inference and prediction. 1st ed. Springer: New York; 2001. p. 160.