Milan Grkovski1, Nancy Y Lee2, Heiko Schöder3, Sean D Carlin3, Bradley J Beattie4, Nadeem Riaz2, Jonathan E Leeman2, Joseph A O'Donoghue4, John L Humm4. 1. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA. grkovskm@mkscc.org. 2. Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 3. Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 4. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Abstract
PURPOSE: There is growing recognition that biologic features of the tumor microenvironment affect the response to cancer therapies and the outcome of cancer patients. In head and neck cancer (HNC) one such feature is hypoxia. We investigated the utility of 18F-fluoromisonidazole (FMISO) dynamic positron emission tomography (dPET) for monitoring the early microenvironmental response to chemoradiotherapy in HNC. EXPERIMENTAL DESIGN: Seventy-two HNC patients underwent FMISO dPET scans in a customized immobilization mask (0-30 min dynamic acquisition, followed by 10 min static acquisitions starting at ∼95 min and ∼160 min post-injection) at baseline and early into treatment where patients have already received one cycle of chemotherapy and anywhere from five to ten fractions of 2 Gy per fraction radiation therapy. Voxelwise pharmacokinetic modeling was conducted using an irreversible one-plasma two-tissue compartment model to calculate surrogate biomarkers of tumor hypoxia (k 3 and Tumor-to-Blood Ratio (TBR)), perfusion (K 1 ) and FMISO distribution volume (DV). Additionally, Tumor-to-Muscle Ratios (TMR) were derived by visual inspection by an experienced nuclear medicine physician, with TMR > 1.2 defining hypoxia. RESULTS: One hundred and thirty-five lesions in total were analyzed. TBR, k 3 and DV decreased on early response scans, while no significant change was observed for K 1 . The k 3 -TBR correlation decreased substantially from baseline scans (Pearson's r = 0.72 and 0.76 for mean intratumor and pooled voxelwise values, respectively) to early response scans (Pearson's r = 0.39 and 0.40, respectively). Both concordant and discordant examples of changes in intratumor k 3 and TBR were identified; the latter partially mediated by the change in DV. In 13 normoxic patients according to visual analysis (all having lesions with TMR = 1.2), subvolumes were identified where k 3 indicated the presence of hypoxia. CONCLUSION: Pharmacokinetic modeling of FMISO dynamic PET reveals a more detailed characterization of the tumor microenvironment and assessment of response to chemoradiotherapy in HNC patients than a single static image does. In a clinical trial where absence of hypoxia in primary tumor and lymph nodes would lead to de-escalation of therapy, the observed disagreement between visual analysis and pharmacokinetic modeling results would have affected patient management in <20% cases. While simple static PET imaging is easily implemented for clinical trials, the clinical applicability of pharmacokinetic modeling remains to be investigated.
PURPOSE: There is growing recognition that biologic features of the tumor microenvironment affect the response to cancer therapies and the outcome of cancer patients. In head and neck cancer (HNC) one such feature is hypoxia. We investigated the utility of 18F-fluoromisonidazole (FMISO) dynamic positron emission tomography (dPET) for monitoring the early microenvironmental response to chemoradiotherapy in HNC. EXPERIMENTAL DESIGN: Seventy-two HNC patients underwent FMISO dPET scans in a customized immobilization mask (0-30 min dynamic acquisition, followed by 10 min static acquisitions starting at ∼95 min and ∼160 min post-injection) at baseline and early into treatment where patients have already received one cycle of chemotherapy and anywhere from five to ten fractions of 2 Gy per fraction radiation therapy. Voxelwise pharmacokinetic modeling was conducted using an irreversible one-plasma two-tissue compartment model to calculate surrogate biomarkers of tumor hypoxia (k 3 and Tumor-to-Blood Ratio (TBR)), perfusion (K 1 ) and FMISO distribution volume (DV). Additionally, Tumor-to-Muscle Ratios (TMR) were derived by visual inspection by an experienced nuclear medicine physician, with TMR > 1.2 defining hypoxia. RESULTS: One hundred and thirty-five lesions in total were analyzed. TBR, k 3 and DV decreased on early response scans, while no significant change was observed for K 1 . The k 3 -TBR correlation decreased substantially from baseline scans (Pearson's r = 0.72 and 0.76 for mean intratumor and pooled voxelwise values, respectively) to early response scans (Pearson's r = 0.39 and 0.40, respectively). Both concordant and discordant examples of changes in intratumor k 3 and TBR were identified; the latter partially mediated by the change in DV. In 13 normoxic patients according to visual analysis (all having lesions with TMR = 1.2), subvolumes were identified where k 3 indicated the presence of hypoxia. CONCLUSION: Pharmacokinetic modeling of FMISO dynamic PET reveals a more detailed characterization of the tumor microenvironment and assessment of response to chemoradiotherapy in HNC patients than a single static image does. In a clinical trial where absence of hypoxia in primary tumor and lymph nodes would lead to de-escalation of therapy, the observed disagreement between visual analysis and pharmacokinetic modeling results would have affected patient management in <20% cases. While simple static PET imaging is easily implemented for clinical trials, the clinical applicability of pharmacokinetic modeling remains to be investigated.
Entities:
Keywords:
18F-FMISO; Dynamic PET; Head and neck cancer; Hypoxia; Treatment response
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: Paul A DiSilvestro; Shamshad Ali; Peter S Craighead; Joseph A Lucci; Yi-Chun Lee; David E Cohn; Nicola M Spirtos; Krishnasu S Tewari; Carolyn Muller; Walter H Gajewski; Margaret M Steinhoff; Bradley J Monk Journal: J Clin Oncol Date: 2014-01-06 Impact factor: 44.544
Authors: Annette M Lim; Danny Rischin; Richard Fisher; Hongbin Cao; Kathleen Kwok; Daniel Truong; Grant A McArthur; Richard J Young; Amato Giaccia; Lester Peters; Quynh-Thu Le Journal: Clin Cancer Res Date: 2011-11-17 Impact factor: 12.531
Authors: Ludwig J Dubois; Raymon Niemans; Simon J A van Kuijk; Kranthi M Panth; Nanda-Kumar Parvathaneni; Sarah G J A Peeters; Catharina M L Zegers; Nicolle H Rekers; Marike W van Gisbergen; Rianne Biemans; Natasja G Lieuwes; Linda Spiegelberg; Ala Yaromina; Jean-Yves Winum; Marc Vooijs; Philippe Lambin Journal: Radiother Oncol Date: 2015-08-28 Impact factor: 6.280
Authors: Nancy Lee; Heiko Schoder; Brad Beattie; Ryan Lanning; Nadeem Riaz; Sean McBride; Nora Katabi; Duan Li; Brett Yarusi; Susie Chan; Lindsey Mitrani; Zhigang Zhang; David G Pfister; Eric Sherman; Shrujal Baxi; Jay Boyle; Luc G T Morris; Ian Ganly; Richard Wong; John Humm Journal: Int J Radiat Oncol Biol Phys Date: 2016-05-07 Impact factor: 7.038
Authors: Mireia Crispin-Ortuzar; Aditya Apte; Milan Grkovski; Jung Hun Oh; Nancy Y Lee; Heiko Schöder; John L Humm; Joseph O Deasy Journal: Radiother Oncol Date: 2017-12-19 Impact factor: 6.280
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: Nils H Nicolay; Nicole Wiedenmann; Michael Mix; Wolfgang A Weber; Martin Werner; Anca L Grosu; Gian Kayser Journal: Eur J Nucl Med Mol Imaging Date: 2019-12-07 Impact factor: 9.236
Authors: Nadeem Riaz; Eric Sherman; Xin Pei; Heiko Schöder; Milan Grkovski; Ramesh Paudyal; Nora Katabi; Pier Selenica; Takafumi N Yamaguchi; Daniel Ma; Simon K Lee; Rachna Shah; Rahul Kumar; Fengshen Kuo; Abhirami Ratnakumar; Nathan Aleynick; David Brown; Zhigang Zhang; Vaios Hatzoglou; Lydia Y Liu; Adriana Salcedo; Chiaojung J Tsai; Sean McBride; Luc G T Morris; Jay Boyle; Bhuvanesh Singh; Daniel S Higginson; Rama R Damerla; Arnaud da Cruz Paula; Katharine Price; Eric J Moore; Joaquin J Garcia; Robert Foote; Alan Ho; Richard J Wong; Timothy A Chan; Simon N Powell; Paul C Boutros; John L Humm; Amita Shukla-Dave; David Pfister; Jorge S Reis-Filho; Nancy Lee Journal: J Natl Cancer Inst Date: 2021-06-01 Impact factor: 13.506
Authors: Edward Taylor; Jennifer Gottwald; Ivan Yeung; Harald Keller; Michael Milosevic; Neesha C Dhani; Iram Siddiqui; David W Hedley; David A Jaffray Journal: EJNMMI Res Date: 2017-12-22 Impact factor: 3.138
Authors: Constantin Lapa; Ursula Nestle; Nathalie L Albert; Christian Baues; Ambros Beer; Andreas Buck; Volker Budach; Rebecca Bütof; Stephanie E Combs; Thorsten Derlin; Matthias Eiber; Wolfgang P Fendler; Christian Furth; Cihan Gani; Eleni Gkika; Anca-L Grosu; Christoph Henkenberens; Harun Ilhan; Steffen Löck; Simone Marnitz-Schulze; Matthias Miederer; Michael Mix; Nils H Nicolay; Maximilian Niyazi; Christoph Pöttgen; Claus M Rödel; Imke Schatka; Sarah M Schwarzenboeck; Andrei S Todica; Wolfgang Weber; Simone Wegen; Thomas Wiegel; Constantinos Zamboglou; Daniel Zips; Klaus Zöphel; Sebastian Zschaeck; Daniela Thorwarth; Esther G C Troost Journal: Strahlenther Onkol Date: 2021-07-14 Impact factor: 3.621
Authors: Oliver J Gurney-Champion; Faisal Mahmood; Marcel van Schie; Robert Julian; Ben George; Marielle E P Philippens; Uulke A van der Heide; Daniela Thorwarth; Kathrine R Redalen Journal: Radiother Oncol Date: 2020-02-27 Impact factor: 6.280