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Quantitative [18F]-Naf-PET-MRI Analysis for the Evaluation of Dynamic Bone Turnover in a Patient with Facetogenic Low Back Pain
Published on: August 8, 2019
Volume-normalized uptake rates with robust transportability from PET dual-time and Patlak analyses
1University of Tennessee, 12334 Bluff Shore Dr., Knoxville, TN 37922, USA. jathie@utk.edu
Purpose:
The intention here is to enhance the usefulness of the Gjedde-Patlak plot of dynamic positron emission tomography (PET) tracer uptake. Two additional parameters closely related to the physiologically significant and diagnostically useful phosphorylation rate k (3) are therefore studied. Additionally, their inter-institutional transportability is examined.
Methods:
The two traditional parameters obtained from a Patlak plot are its slope Ki and its usually ignored tissue/plasma (=Q/Cp) axis intercept V. As a useful result, a normalized uptake rate may be defined as k=Ki /V. This is can be theoretically close to k (3). Similar to this an alternative normalized uptake rate is defined as k (3)' =Ki /V '. Here, V ' would be a composite of model rate constants, reasonably known a priori, and the measured V so as to depend less on errors in the latter. Parameter determination demonstrations utilize data from the 2-deoxy-2-[F-18]fluoro-D-glucose(FDG)-PET literature.
Results:
Using median k (i) values from 24 FDG dynamic studies and algebraic relationships, on average: k=1.07 k (3)(r=0.97), and k (3)' =0.95k (3) (r=0.91). A skeletal muscle case also demonstrates agreements with k (3). For liver malignancies k and k (3)' can be diagnostically slightly superior to Ki. Unaffected by institutionally dependent Q and Cp calibrations and methods, these can be more robust than Ki in a number of circumstances.
Conclusion:
Two studied physiologically meaningful parameters, close to the diagnostically important k (3), can supplement Ki and enhance Patlak analysis by appropriately utilizing normally ignored information. Hitherto, k (3) was obtainable only by complex nonlinear least squares compartmental model analysis. The additional parameters can have more robust inter-institutional transportability than Ki.
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