TY - JOUR

T1 - Single-voxel delay map from long-axial field-of-view PET scans

AU - Nielsen, Frederik Bay

AU - Lindberg, Ulrich

AU - Bordallo, Heloisa N.

AU - Johnbeck, Camilla Bardram

AU - Law, Ian

AU - Fischer, Barbara Malene

AU - Andersen, Flemming Littrup

AU - Andersen, Thomas Lund

N1 - Publisher Copyright: 2024 Nielsen, Lindberg, Bordallo, Johnbeck, Law, Fischer, Andersen and Andersen.

PY - 2024

Y1 - 2024

N2 - Objective: We present an algorithm to estimate the delay between a tissue time activity curve and a blood input curve at a single-voxel level tested on whole-body data from a long-axial field-of-view scanner with tracers of different noise characteristics. Methods: Whole-body scans of 15 patients divided equally among three tracers: [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, were used in development and testing of the algorithm. Delay time were estimated by fitting the cumulatively summed input function and tissue time activity curve with special considerations for noise. To evaluate the performance of the algorithm, it was compared against two other algorithms also commonly applied in delay estimation, name cross-correlation and a one-tissue compartment model with incorporated delay. All algorithms were tested on both synthetic time activity curves produced with the one-tissue compartment model with increasing levels of noise and delays between the tissue activity curve and the blood input curve. Whole-body delay maps were also calculated for each of the three tracers with data acquired on a long-axial field-of-view scanner with high time resolution. Results: Our proposed model performs better for low signal-to-noise ratio time activity curves compared to both cross-correlation and the one-tissue compartment models for non-[15O]H2O tracers. Testing on synthetically produced time activity curves it displays only a small and even residual delay, while the one-tissue compartment model with included delay showed varying residual delays. Conclusion: The algorithm is robust to noise and proves applicable on a range of tracers as tested on [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, and hence is a viable option offering the ability for delay correction across various organs and tracers in use with kinetic modeling.

AB - Objective: We present an algorithm to estimate the delay between a tissue time activity curve and a blood input curve at a single-voxel level tested on whole-body data from a long-axial field-of-view scanner with tracers of different noise characteristics. Methods: Whole-body scans of 15 patients divided equally among three tracers: [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, were used in development and testing of the algorithm. Delay time were estimated by fitting the cumulatively summed input function and tissue time activity curve with special considerations for noise. To evaluate the performance of the algorithm, it was compared against two other algorithms also commonly applied in delay estimation, name cross-correlation and a one-tissue compartment model with incorporated delay. All algorithms were tested on both synthetic time activity curves produced with the one-tissue compartment model with increasing levels of noise and delays between the tissue activity curve and the blood input curve. Whole-body delay maps were also calculated for each of the three tracers with data acquired on a long-axial field-of-view scanner with high time resolution. Results: Our proposed model performs better for low signal-to-noise ratio time activity curves compared to both cross-correlation and the one-tissue compartment models for non-[15O]H2O tracers. Testing on synthetically produced time activity curves it displays only a small and even residual delay, while the one-tissue compartment model with included delay showed varying residual delays. Conclusion: The algorithm is robust to noise and proves applicable on a range of tracers as tested on [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, and hence is a viable option offering the ability for delay correction across various organs and tracers in use with kinetic modeling.

KW - delay correction

KW - delay map

KW - dynamic whole-body PET

KW - kinetic modeling

KW - one-tissue compartmental modeling

U2 - 10.3389/fnume.2024.1360326

DO - 10.3389/fnume.2024.1360326

M3 - Journal article

AN - SCOPUS:85192108699

VL - 4

JO - Frontiers in Nuclear Medicine

JF - Frontiers in Nuclear Medicine

SN - 2673-8880

M1 - 1360326

ER -