Milan Grkovski1, Jazmin Schwartz2, Mithat Gönen3, Heiko Schöder4, Nancy Y Lee5, Sean D Carlin4, Pat B Zanzonico2, John L Humm2, Sadek A Nehmeh2. 1. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York grkovskm@mkscc.org. 2. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York. 3. Department of Epidemiology-Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York. 4. Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York; and. 5. Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York.
Abstract
UNLABELLED: (18)F-fluoromisonidazole dynamic PET (dPET) is used to identify tumor hypoxia noninvasively. Its routine clinical implementation, however, has been hampered by the long acquisition times required. We investigated the feasibility of kinetic modeling using shortened acquisition times in (18)F-fluoromisonidazole dPET, with the goal of expediting the clinical implementation of (18)F-fluoromisonidazole dPET protocols. METHODS: Six patients with squamous cell carcinoma of the head and neck and 10 HT29 colorectal carcinoma-bearing nude rats were studied. In addition to an (18)F-FDG PET scan, each patient underwent a 45-min (18)F-fluoromisonidazole dPET scan, followed by 10-min acquisitions at 96 ± 4 and 163 ± 17 min after injection. Ninety-minute (18)F-fluoromisonidazole dPET scans were acquired in animals. Intratumor voxels were classified into 4 clusters based on their kinetic behavior using k-means clustering. Kinetic modeling was performed using the foregoing full datasets (FD) and repeated for each of 2 shortened datasets corresponding to the first approximately 100 min (SD1; patients only) or the first 45 min (SD2) of dPET data. The kinetic rate constants (KRCs) as calculated with a 2-compartment model for both SD1 and SD2 were compared with those derived from FD by correlation (Pearson), regression (Passing-Bablok), deviation (Bland-Altman), and classification (area-under-the-receiver-operating characteristic curve) analyses. Simulations were performed to assess uncertainties due to statistical noise. RESULTS: Strong correlation (r ≥ 0.75, P < 0.001) existed between all KRCs deduced from both SD1 and SD2, and from FD. Significant differences between KRCs were found only for FD-SD2 correlations in patient studies. K1 and k3 were reproducible to within approximately 6% and approximately 30% (FD-SD1; patients) and approximately 4% and approximately 75% (FD-SD2; animals). Area-under-the-receiver-operating characteristic curve values for classification of patient clusters as hypoxic, using a tumor-to-blood ratio greater than 1.2, were 0.91 (SD1) and 0.86 (SD2). The percentage SD in estimating K1 and k3 from 45-min shortened datasets due to noise was less than 1% and between 2% and 12%, respectively. CONCLUSION: Using single-session 45-min shortened (18)F-fluoromisonidazole dPET datasets appears to be adequate for the identification of intratumor regions of hypoxia. However, k3 was significantly overestimated in the clinical cohort. Further studies are necessary to evaluate the clinical significance of differences between the results as calculated from full and shortened datasets.
UNLABELLED: (18)F-fluoromisonidazole dynamic PET (dPET) is used to identify tumor hypoxia noninvasively. Its routine clinical implementation, however, has been hampered by the long acquisition times required. We investigated the feasibility of kinetic modeling using shortened acquisition times in (18)F-fluoromisonidazole dPET, with the goal of expediting the clinical implementation of (18)F-fluoromisonidazole dPET protocols. METHODS: Six patients with squamous cell carcinoma of the head and neck and 10 HT29 colorectal carcinoma-bearing nude rats were studied. In addition to an (18)F-FDG PET scan, each patient underwent a 45-min (18)F-fluoromisonidazole dPET scan, followed by 10-min acquisitions at 96 ± 4 and 163 ± 17 min after injection. Ninety-minute (18)F-fluoromisonidazole dPET scans were acquired in animals. Intratumor voxels were classified into 4 clusters based on their kinetic behavior using k-means clustering. Kinetic modeling was performed using the foregoing full datasets (FD) and repeated for each of 2 shortened datasets corresponding to the first approximately 100 min (SD1; patients only) or the first 45 min (SD2) of dPET data. The kinetic rate constants (KRCs) as calculated with a 2-compartment model for both SD1 and SD2 were compared with those derived from FD by correlation (Pearson), regression (Passing-Bablok), deviation (Bland-Altman), and classification (area-under-the-receiver-operating characteristic curve) analyses. Simulations were performed to assess uncertainties due to statistical noise. RESULTS: Strong correlation (r ≥ 0.75, P < 0.001) existed between all KRCs deduced from both SD1 and SD2, and from FD. Significant differences between KRCs were found only for FD-SD2 correlations in patient studies. K1 and k3 were reproducible to within approximately 6% and approximately 30% (FD-SD1; patients) and approximately 4% and approximately 75% (FD-SD2; animals). Area-under-the-receiver-operating characteristic curve values for classification of patient clusters as hypoxic, using a tumor-to-blood ratio greater than 1.2, were 0.91 (SD1) and 0.86 (SD2). The percentage SD in estimating K1 and k3 from 45-min shortened datasets due to noise was less than 1% and between 2% and 12%, respectively. CONCLUSION: Using single-session 45-min shortened (18)F-fluoromisonidazole dPET datasets appears to be adequate for the identification of intratumor regions of hypoxia. However, k3 was significantly overestimated in the clinical cohort. Further studies are necessary to evaluate the clinical significance of differences between the results as calculated from full and shortened datasets.
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
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Authors: Jazmin Schwartz; Milan Grkovski; Andreas Rimner; Heiko Schöder; Pat B Zanzonico; Sean D Carlin; Kevin D Staton; John L Humm; Sadek A Nehmeh Journal: J Nucl Med Date: 2017-02-23 Impact factor: 10.057
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