T Pyka1, J Gempt2, F Ringel2, S Hüttinger3, S van Marwick4, S Nekolla4, H-J Wester5, M Schwaiger4, S Förster4. 1. From the Departments of Nuclear Medicine (T.P., S.v.M., S.N., M.S., S.F) thomas.pyka@tum.de. 2. Neurosurgery (J.G., F.R.). 3. Neuroradiology (S.H.). 4. From the Departments of Nuclear Medicine (T.P., S.v.M., S.N., M.S., S.F). 5. Pharmaceutical Radiochemistry (H.-J.W.), Technical University Munich, Munich, Germany.
Abstract
BACKGROUND AND PURPOSE: Inter- and intratumor heterogeneity and the variable course of disease in patients with glioma motivate the investigation of new prognostic factors to optimize individual treatment. Here we explore the usefulness of standard static and more sophisticated dynamic (18)F-fluoroethyltyrosine-PET imaging for the assessment of patient prognosis. MATERIALS AND METHODS: Thirty-four consecutive patients with untreated, first-diagnosed, histologically proved glioma were included in this retrospective study. All patients underwent dynamic PET scans before surgery (± standard treatment) and were followed up clinically and by MR imaging. Static and dynamic tumor-to-background ratio, TTP, and slope-to-peak were obtained and correlated with progression-free survival. RESULTS: Twenty of 34 patients experienced progression, with a median progression-free survival of 28.0 ± 11.1 months. Dynamic TTP was highly prognostic for recurrent disease, showing a strong correlation with progression-free survival (hazard ratio, 6.050; 95% CI, 2.11-17.37; P < .001). Most interesting, this correlation also proved significant in the subgroup of low-grade glioma (hazard ratio, 5.347; 95% CI, 1.05-27.20; P = .044), but not when using established static imaging parameters, such as maximum tumor-to-background ratio and mean tumor-to-background ratio. In the high-grade glioma subgroup, both dynamic and static parameters correlated with progression-free survival. The best results were achieved by defining ROIs around "hot spots" in earlier timeframes, underlining the concept of intratumor heterogeneity. CONCLUSIONS: (18)F-fluoroethyltyrosine-PET can predict recurrence in patients with glioma, with dynamic analysis showing advantages over static imaging, especially in the low-grade subgroup.
BACKGROUND AND PURPOSE: Inter- and intratumor heterogeneity and the variable course of disease in patients with glioma motivate the investigation of new prognostic factors to optimize individual treatment. Here we explore the usefulness of standard static and more sophisticated dynamic (18)F-fluoroethyltyrosine-PET imaging for the assessment of patient prognosis. MATERIALS AND METHODS: Thirty-four consecutive patients with untreated, first-diagnosed, histologically proved glioma were included in this retrospective study. All patients underwent dynamic PET scans before surgery (± standard treatment) and were followed up clinically and by MR imaging. Static and dynamic tumor-to-background ratio, TTP, and slope-to-peak were obtained and correlated with progression-free survival. RESULTS: Twenty of 34 patients experienced progression, with a median progression-free survival of 28.0 ± 11.1 months. Dynamic TTP was highly prognostic for recurrent disease, showing a strong correlation with progression-free survival (hazard ratio, 6.050; 95% CI, 2.11-17.37; P < .001). Most interesting, this correlation also proved significant in the subgroup of low-grade glioma (hazard ratio, 5.347; 95% CI, 1.05-27.20; P = .044), but not when using established static imaging parameters, such as maximum tumor-to-background ratio and mean tumor-to-background ratio. In the high-grade glioma subgroup, both dynamic and static parameters correlated with progression-free survival. The best results were achieved by defining ROIs around "hot spots" in earlier timeframes, underlining the concept of intratumor heterogeneity. CONCLUSIONS: (18)F-fluoroethyltyrosine-PET can predict recurrence in patients with glioma, with dynamic analysis showing advantages over static imaging, especially in the low-grade subgroup.
Authors: Nathalie L Jansen; Vera Graute; Lena Armbruster; Bogdana Suchorska; Juergen Lutz; Sabina Eigenbrod; Paul Cumming; Peter Bartenstein; Jörg-Christian Tonn; Friedrich Wilhelm Kreth; Christian la Fougère Journal: Eur J Nucl Med Mol Imaging Date: 2012-04-11 Impact factor: 9.236
Authors: Walter Rachinger; Claudia Goetz; Gabriele Pöpperl; Franz Josef Gildehaus; Friedrich Wilhelm Kreth; Markus Holtmannspötter; Jochen Herms; Walter Koch; Klaus Tatsch; Jörg-Christian Tonn Journal: Neurosurgery Date: 2005-09 Impact factor: 4.654
Authors: M J van den Bent; J S Wefel; D Schiff; M J B Taphoorn; K Jaeckle; L Junck; T Armstrong; A Choucair; A D Waldman; T Gorlia; M Chamberlain; B G Baumert; M A Vogelbaum; D R Macdonald; D A Reardon; P Y Wen; S M Chang; A H Jacobs Journal: Lancet Oncol Date: 2011-04-05 Impact factor: 41.316
Authors: Nauman S Chaudhry; Ashish H Shah; Nicholas Ferraro; Brian M Snelling; Amade Bregy; Karthik Madhavan; Ricardo J Komotar Journal: Cancer Invest Date: 2013-04-24 Impact factor: 2.176
Authors: Gabriele Pöpperl; Friedrich W Kreth; Jochen Herms; Walter Koch; Jan H Mehrkens; Franz J Gildehaus; Hans A Kretzschmar; Jörg C Tonn; Klaus Tatsch Journal: J Nucl Med Date: 2006-03 Impact factor: 10.057
Authors: David N Louis; Hiroko Ohgaki; Otmar D Wiestler; Webster K Cavenee; Peter C Burger; Anne Jouvet; Bernd W Scheithauer; Paul Kleihues Journal: Acta Neuropathol Date: 2007-07-06 Impact factor: 17.088
Authors: T K Yanagihara; J Grinband; J Rowley; K A Cauley; A Lee; M Garrett; M Afghan; A Chu; T J C Wang Journal: AJNR Am J Neuroradiol Date: 2016-07-14 Impact factor: 3.825
Authors: Wynton B Overcast; Korbin M Davis; Chang Y Ho; Gary D Hutchins; Mark A Green; Brian D Graner; Michael C Veronesi Journal: Curr Oncol Rep Date: 2021-02-18 Impact factor: 5.075