Milan Grkovski1, Sally-Ann Emmas2, Sean D Carlin3. 1. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York. 2. Imaging Team, Personalised Healthcare and Biomarkers, AstraZeneca, Macclesfield, United Kingdom; and. 3. Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York carlins@mail.med.upenn.edu.
Abstract
Multiparametric imaging of tumor perfusion and hypoxia with dynamic 18F-fluoromisonidazole (18F-FMISO) PET may allow for an improved response assessment to antiangiogenic therapies. Cediranib (AZD2171) is a potent inhibitor of tyrosine kinase activity associated with vascular endothelial growth factor receptors 1, 2, and 3, currently in phase II/III clinical trials. Serial dynamic 18F-FMISO PET was performed to investigate changes in tumor biomarkers of perfusion and hypoxia after cediranib treatment. Methods: Twenty-one rats bearing HT29 colorectal xenograft tumors were randomized into a vehicle-treated control group (0.5% methylcellulose daily for 2 d [5 rats] or 7 d [4 rats]) and a cediranib-treated test group (3 mg/kg daily for 2 or 7 d; 6 rats in both groups). All rats were imaged before and after treatment, using a 90-min dynamic PET acquisition after administration of 42.1 ± 3.9 MBq of 18F-FMISO by tail vein injection. Tumor volumes were delineated manually, and the input function was image-derived (abdominal aorta). Kinetic modeling was performed using an irreversible 1-plasma 2-tissue compartmental model to estimate the kinetic rate constants K1, K1/k2, and k3-surrogates for perfusion, 18F-FMISO distribution volume, and hypoxia-mediated entrapment, respectively. Tumor-to-blood ratios (TBRs) were calculated on the last dynamic frame (80-90 min). Tumors were assessed ex vivo by digital autoradiography and immunofluorescence for microscopic visualization of perfusion (pimonidazole) and hypoxia (Hoechst 33342). Results: Cediranib treatment resulted in significant reduction of mean voxelwise 18F-FMISO TBR, K1, and K1/k2 in both the 2-d and the 7-d groups (P < 0.05). The k3 parameter was increased in both groups but reached significance only in the 2-d group. In the vehicle-treated groups, no significant change in TBR, K1, K1/k2, or k3 was observed (P > 0.2). Ex vivo tumor analysis confirmed the presence of hypoxic tumor regions that nevertheless exhibited relatively lower 18F-FMISO uptake. Conclusion: 18F-FMISO kinetic modeling reveals a more detailed response to antiangiogenic treatment than a single static image is able to reveal. The reduced mean K1 reflects a reduction in tumor vascular perfusion, whereas the increased k3 reflects a rise in hypoxia-mediated entrapment of the radiotracer. However, if only late static images are analyzed, the observed reduction in 18F-FMISO uptake after treatment with cediranib may be mistakenly interpreted as a global decrease, rather than an increase, in tumor hypoxia. These findings support the use of 18F-FMISO kinetic modeling to more accurately characterize the response to treatments that have a direct effect on tumor vascularization and perfusion.
Multiparametric imaging of tumor perfusion and hypoxia with dynamic 18F-fluoromisonidazole (18F-FMISO) PET may allow for an improved response assessment to antiangiogenic therapies. Cediranib (AZD2171) is a potent inhibitor of tyrosine kinase activity associated with vascular endothelial growth factor receptors 1, 2, and 3, currently in phase II/III clinical trials. Serial dynamic 18F-FMISO PET was performed to investigate changes in tumor biomarkers of perfusion and hypoxia after cediranib treatment. Methods: Twenty-one rats bearing HT29 colorectal xenograft tumors were randomized into a vehicle-treated control group (0.5% methylcellulose daily for 2 d [5 rats] or 7 d [4 rats]) and a cediranib-treated test group (3 mg/kg daily for 2 or 7 d; 6 rats in both groups). All rats were imaged before and after treatment, using a 90-min dynamic PET acquisition after administration of 42.1 ± 3.9 MBq of 18F-FMISO by tail vein injection. Tumor volumes were delineated manually, and the input function was image-derived (abdominal aorta). Kinetic modeling was performed using an irreversible 1-plasma 2-tissue compartmental model to estimate the kinetic rate constants K1, K1/k2, and k3-surrogates for perfusion, 18F-FMISO distribution volume, and hypoxia-mediated entrapment, respectively. Tumor-to-blood ratios (TBRs) were calculated on the last dynamic frame (80-90 min). Tumors were assessed ex vivo by digital autoradiography and immunofluorescence for microscopic visualization of perfusion (pimonidazole) and hypoxia (Hoechst 33342). Results: Cediranib treatment resulted in significant reduction of mean voxelwise 18F-FMISO TBR, K1, and K1/k2 in both the 2-d and the 7-d groups (P < 0.05). The k3 parameter was increased in both groups but reached significance only in the 2-d group. In the vehicle-treated groups, no significant change in TBR, K1, K1/k2, or k3 was observed (P > 0.2). Ex vivo tumor analysis confirmed the presence of hypoxic tumor regions that nevertheless exhibited relatively lower 18F-FMISO uptake. Conclusion: 18F-FMISO kinetic modeling reveals a more detailed response to antiangiogenic treatment than a single static image is able to reveal. The reduced mean K1 reflects a reduction in tumor vascular perfusion, whereas the increased k3 reflects a rise in hypoxia-mediated entrapment of the radiotracer. However, if only late static images are analyzed, the observed reduction in 18F-FMISO uptake after treatment with cediranib may be mistakenly interpreted as a global decrease, rather than an increase, in tumor hypoxia. These findings support the use of 18F-FMISO kinetic modeling to more accurately characterize the response to treatments that have a direct effect on tumor vascularization and perfusion.
Authors: W J Koh; J S Rasey; M L Evans; J R Grierson; T K Lewellen; M M Graham; K A Krohn; T W Griffin Journal: Int J Radiat Oncol Biol Phys Date: 1992 Impact factor: 7.038
Authors: J S Rasey; W J Koh; M L Evans; L M Peterson; T K Lewellen; M M Graham; K A Krohn Journal: Int J Radiat Oncol Biol Phys Date: 1996-09-01 Impact factor: 7.038
Authors: Rakesh K Jain; Dan G Duda; Christopher G Willett; Dushyant V Sahani; Andrew X Zhu; Jay S Loeffler; Tracy T Batchelor; A Gregory Sorensen Journal: Nat Rev Clin Oncol Date: 2009-06 Impact factor: 66.675
Authors: Elena Hernández-Agudo; Tamara Mondejar; Maria Luisa Soto-Montenegro; Diego Megías; Silvana Mouron; Jesus Sanchez; Manuel Hidalgo; Pedro Pablo Lopez-Casas; Francisca Mulero; Manuel Desco; Miguel Quintela-Fandino Journal: Mol Oncol Date: 2015-12-22 Impact factor: 6.603
Authors: Daniela Thorwarth; Stefan Welz; David Mönnich; Christina Pfannenberg; Konstantin Nikolaou; Matthias Reimold; Christian La Fougère; Gerald Reischl; Paul-Stefan Mauz; Frank Paulsen; Markus Alber; Claus Belka; Daniel Zips Journal: J Nucl Med Date: 2019-05-10 Impact factor: 10.057
Authors: Alanna R Kaplan; Susan E Gueble; Yanfeng Liu; Sebastian Oeck; Hoon Kim; Zhong Yun; Peter M Glazer Journal: Sci Transl Med Date: 2019-05-15 Impact factor: 17.956
Authors: Milan Grkovski; Nancy Y Lee; Heiko Schöder; Sean D Carlin; Bradley J Beattie; Nadeem Riaz; Jonathan E Leeman; Joseph A O'Donoghue; John L Humm Journal: Eur J Nucl Med Mol Imaging Date: 2017-05-24 Impact factor: 9.236