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EJNMMI Research
Published in: EJNMMI Research 1/2020

Open Access 01-12-2020 | NSCLC | Original research

18F-FDG PET and DCE kinetic modeling and their correlations in primary NSCLC: first voxel-wise correlative analysis of human simultaneous [18F]FDG PET-MRI data

Authors: Florent L. Besson, Brice Fernandez, Sylvain Faure, Olaf Mercier, Andrei Seferian, Xavier Mignard, Sacha Mussot, Cecile le Pechoux, Caroline Caramella, Angela Botticella, Antonin Levy, Florence Parent, Sophie Bulifon, David Montani, Delphine Mitilian, Elie Fadel, David Planchard, Benjamin Besse, Maria-Rosa Ghigna-Bellinzoni, Claude Comtat, Vincent Lebon, Emmanuel Durand

Published in: EJNMMI Research | Issue 1/2020

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Abstract

Objectives

To decipher the correlations between PET and DCE kinetic parameters in non-small-cell lung cancer (NSCLC), by using voxel-wise analysis of dynamic simultaneous [18F]FDG PET-MRI.

Material and methods

Fourteen treatment-naïve patients with biopsy-proven NSCLC prospectively underwent a 1-h dynamic [18F]FDG thoracic PET-MRI scan including DCE. The PET and DCE data were normalized to their corresponding T1-weighted MR morphological space, and tumors were masked semi-automatically. Voxel-wise parametric maps of PET and DCE kinetic parameters were computed by fitting the dynamic PET and DCE tumor data to the Sokoloff and Extended Tofts models respectively, by using in-house developed procedures. Curve-fitting errors were assessed by computing the relative root mean square error (rRMSE) of the estimated PET and DCE signals at the voxel level. For each tumor, Spearman correlation coefficients (rs) between all the pairs of PET and DCE kinetic parameters were estimated on a voxel-wise basis, along with their respective bootstrapped 95% confidence intervals (n = 1000 iterations).

Results

Curve-fitting metrics provided fit errors under 20% for almost 90% of the PET voxels (median rRMSE = 10.3, interquartile ranges IQR = 8.1; 14.3), whereas 73.3% of the DCE voxels showed fit errors under 45% (median rRMSE = 31.8%, IQR = 22.4; 46.6). The PET-PET, DCE-DCE, and PET-DCE voxel-wise correlations varied according to individual tumor behaviors. Beyond this wide variability, the PET-PET and DCE-DCE correlations were mainly high (absolute rs values > 0.7), whereas the PET-DCE correlations were mainly low to moderate (absolute rs values < 0.7). Half the tumors showed a hypometabolism with low perfused/vascularized profile, a hallmark of hypoxia, and tumor aggressiveness.

Conclusion

A dynamic “one-stop shop” procedure applied to NSCLC is technically feasible in clinical practice. PET and DCE kinetic parameters assessed simultaneously are not highly correlated in NSCLC, and these correlations showed a wide variability among tumors and patients. These results tend to suggest that PET and DCE kinetic parameters might provide complementary information. In the future, this might make PET-MRI a unique tool to characterize the individual tumor biological behavior in NSCLC.
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Metadata
Title
18F-FDG PET and DCE kinetic modeling and their correlations in primary NSCLC: first voxel-wise correlative analysis of human simultaneous [18F]FDG PET-MRI data
Authors
Florent L. Besson
Brice Fernandez
Sylvain Faure
Olaf Mercier
Andrei Seferian
Xavier Mignard
Sacha Mussot
Cecile le Pechoux
Caroline Caramella
Angela Botticella
Antonin Levy
Florence Parent
Sophie Bulifon
David Montani
Delphine Mitilian
Elie Fadel
David Planchard
Benjamin Besse
Maria-Rosa Ghigna-Bellinzoni
Claude Comtat
Vincent Lebon
Emmanuel Durand
Publication date
01-12-2020
Publisher
Springer Berlin Heidelberg
Published in
EJNMMI Research / Issue 1/2020
Electronic ISSN: 2191-219X
DOI
https://doi.org/10.1186/s13550-020-00671-9

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