UNLABELLED: Quantification of tumor perfusion using radioactive water (H(2)(15)O) and PET is a promising method for monitoring treatment with antiangiogenic agents. However, use of dynamic H(2)(15)O scans together with a fully 3-dimensional clinical PET/CT scanner needs to be validated. The purpose of the present study was to assess validity and reproducibility of dynamic H(2)(15)O PET/CT scans for measuring tumor perfusion and validate the quantitative accuracy of parametric perfusion images. METHODS: Eleven patients with non-small cell lung cancer were included in this study. Patients underwent 2 dynamic H(2)(15)O (370 MBq) PET scans on the same day. During the first scan, arterial blood was withdrawn continuously. Input functions were derived from blood sampler data and the ascending aorta as seen in the images themselves (image-derived input function [IDIF]). Parametric perfusion images were computed using a basis function implementation of the standard single-tissue-compartment model. Volumes of interest (VOIs) were delineated on low-dose CT (LD-CT) and parametric perfusion images. RESULTS: VOIs could be accurately delineated on both LD-CT and parametric perfusion images. These parametric perfusion images had excellent image quality and quantitative accuracy when compared with perfusion values determined by nonlinear regression. Good correlation between perfusion values derived from the blood sampler input function and IDIF was found (Pearson correlation coefficient, r = 0.964; P < 0.001). Test-retest variability of tumor perfusion was 16% and 20% when delineated on LD-CT and parametric perfusion images, respectively. CONCLUSION: The use of ascending aorta IDIFs is an accurate alternative to arterial blood sampling for quantification of tumor perfusion. Image quality obtained with a clinical PET/CT scanner enables generation of accurate parametric perfusion images. VOIs delineated on LD-CT have the highest reproducibility, and changes of more than 16% in tumor perfusion are likely to represent treatment effects.
UNLABELLED: Quantification of tumor perfusion using radioactive water (H(2)(15)O) and PET is a promising method for monitoring treatment with antiangiogenic agents. However, use of dynamic H(2)(15)O scans together with a fully 3-dimensional clinical PET/CT scanner needs to be validated. The purpose of the present study was to assess validity and reproducibility of dynamic H(2)(15)O PET/CT scans for measuring tumor perfusion and validate the quantitative accuracy of parametric perfusion images. METHODS: Eleven patients with non-small cell lung cancer were included in this study. Patients underwent 2 dynamic H(2)(15)O (370 MBq) PET scans on the same day. During the first scan, arterial blood was withdrawn continuously. Input functions were derived from blood sampler data and the ascending aorta as seen in the images themselves (image-derived input function [IDIF]). Parametric perfusion images were computed using a basis function implementation of the standard single-tissue-compartment model. Volumes of interest (VOIs) were delineated on low-dose CT (LD-CT) and parametric perfusion images. RESULTS: VOIs could be accurately delineated on both LD-CT and parametric perfusion images. These parametric perfusion images had excellent image quality and quantitative accuracy when compared with perfusion values determined by nonlinear regression. Good correlation between perfusion values derived from the blood sampler input function and IDIF was found (Pearson correlation coefficient, r = 0.964; P < 0.001). Test-retest variability of tumor perfusion was 16% and 20% when delineated on LD-CT and parametric perfusion images, respectively. CONCLUSION: The use of ascending aorta IDIFs is an accurate alternative to arterial blood sampling for quantification of tumor perfusion. Image quality obtained with a clinical PET/CT scanner enables generation of accurate parametric perfusion images. VOIs delineated on LD-CT have the highest reproducibility, and changes of more than 16% in tumor perfusion are likely to represent treatment effects.
Authors: Lars P Tolbod; Maria M Nielsen; Bodil G Pedersen; Søren Høyer; Hendrik J Harms; Michael Borre; Per Borghammer; Kirsten Bouchelouche; Jørgen Frøkiær; Jens Sørensen Journal: Am J Nucl Med Mol Imaging Date: 2018-10-20
Authors: Hendrik J Harms; Paul Knaapen; Stefan de Haan; Rick Halbmeijer; Adriaan A Lammertsma; Mark Lubberink Journal: Eur J Nucl Med Mol Imaging Date: 2011-01-27 Impact factor: 9.236
Authors: Gerbrand M Kramer; Maqsood Yaqub; Herbert A Vargas; Robert C Schuit; Albert D Windhorst; Alfonsus J M van den Eertwegh; Astrid A M van der Veldt; Andries M Bergman; Eva M Burnazi; Jason S Lewis; Sua Chua; Kevin D Staton; Brad J Beattie; John L Humm; Ian D Davis; Andrew J Weickhardt; Andrew M Scott; Michael J Morris; Otto S Hoekstra; Adriaan A Lammertsma Journal: J Nucl Med Date: 2019-03-08 Impact factor: 10.057
Authors: Otto Muzik; Thomas J Mangner; William R Leonard; Ajay Kumar; James Janisse; James G Granneman Journal: J Nucl Med Date: 2013-01-29 Impact factor: 10.057
Authors: I Apostolova; F Hofheinz; R Buchert; I G Steffen; R Michel; C Rosner; V Prasad; C Köhler; T Derlin; W Brenner; S Marnitz Journal: Strahlenther Onkol Date: 2014-02-18 Impact factor: 3.621