Quantification of Tumor Hypoxic Fractions Using Positron Emission Tomography with [18F]Fluoromisonidazole ([18F]FMISO) Kinetic Analysis and Invasive Oxygen Measurements

Abstract

The purpose of this study is to use dynamic [18F]fluoromisonidazole ([18F]FMISO) positron emission tomography (PET) to compare estimates of tumor hypoxic fractions (HFs) derived by tracer kinetic modeling, tissue-to-blood ratios (TBR), and independent oxygen (pO2) measurements. BALB/c mice with EMT6 subcutaneous tumors were selected for PET imaging and invasive pO2 measurements. Data from 120-min dynamic [18F]FMISO scans were fit to two-compartment irreversible three rate constant (K 1, k 2, k 3) and Patlak models (K i). Tumor HFs were calculated and compared using K i, k 3, TBR, and pO2 values. The clinical impact of each method was evaluated on [18F]FMISO scans for three non-small cell lung cancer (NSCLC) radiotherapy patients. HFs defined by TBR (≥1.2, ≥1.3, and ≥1.4) ranged from 2 to 85 % of absolute tumor volume. HFs defined by K i (>0.004 ml min cm−3) and k 3 (>0.008 min−1) varied from 9 to 85 %. HF quantification was highly dependent on metric (TBR, k 3, or K i) and threshold. HFs quantified on human [18F]FMISO scans varied from 38 to 67, 0 to 14, and 0.1 to 27 %, for each patient, respectively, using TBR, k 3, and K i metrics. [18F]FMISO PET imaging metric choice and threshold impacts hypoxia quantification reliability. Our results suggest that tracer kinetic modeling has the potential to improve hypoxia quantification clinically as it may provide a stronger correlation with direct pO2 measurements.

DOI: 10.1007/s11307-017-1083-9

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Cite this paper

@article{Kelada2017QuantificationOT, title={Quantification of Tumor Hypoxic Fractions Using Positron Emission Tomography with [18F]Fluoromisonidazole ([18F]FMISO) Kinetic Analysis and Invasive Oxygen Measurements}, author={Olivia J. Kelada and Sara Rockwell and Ming-Qiang Zheng and Yiyun Huang and Yanfeng Liu and Carmen J Booth and Roy H. Decker and Uwe Oelfke and Richard E. Carson and David J. Carlson}, journal={Molecular Imaging and Biology}, year={2017}, volume={19}, pages={893-902} }