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Quantitative Analysis of [18F]FMISO PET for Tumor Hypoxia: Correlation of Modeling Results with Immunohistochemistry

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Abstract

Purpose

Quantitative evaluation of tumor hypoxia based on H-1-(3-[18F]fluoro-2-hydroxypropyl)-2-nitroimidazole ([18F]FMISO) positron emission tomography (PET) can deliver important information for treatment planning in radiotherapy. However, the merits and limitations of different analysis methods in revealing the underlying physiological feature are not clear. This study aimed to assess these quantitative analysis methods with the support of immunohistological data.

Procedures

Sixteen nude mice bearing xenografted human squamous cell carcinomas (FaDu or CAL-33) were scanned using 2-h dynamic [18F]FMISO PET. Tumors were resected and sliced, and the hypoxia marker pimonidazole was immunostained followed by H&E staining. The pimonidazole signal was segmented using a k-means clustering algorithm, and the hypoxic fraction (HF) was calculated as the hypoxic area/viable tumor-tissue-area ratio pooled over three tissue slices from the apical, center, and basal layers. PET images were analyzed using various methods including static analysis [standard uptake value (SUV), tumor-to-blood ratio (T/B), tumor-to-muscle ratio (T/M)] and kinetic modeling (Casciari αk A , irreversible and reversible two-tissue compartment k 3, Thorwarth w A k 3, Patlak K i , Logan V d , Cho K), and correlated with HF.

Results

No significant correlation was found for static analysis. A significant correlation between k 3 of the irreversible two-tissue compartment model and HF was observed (r = 0.61, p = 0.01). The correlation between HF and αk A of the Casciari model could be improved through reducing local minima by testing more sets of initial values (r = 0.59, p = 0.02) or by reducing the model complexity by fixing three parameters (r = 0.63, p = 0.0008).

Conclusions

With support of immunohistochemistry data, this study shows that various analysis methods for [18F]FMISO PET perform differently for assessment of tumor hypoxia. A better fitting quality does not necessarily mean a higher physiological correlation. Hypoxia PET analysis needs to consider both the mathematical stability and physiological fidelity. Based on the results of this study, preference should be given to the irreversible two-tissue compartment model as well as the Casciari model with reduced parameters.

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Authors and Affiliations

  1. Department of Nuclear Medicine, Klinikum rechts der Isar, Technische Universität München, Ismaningerstrasse. 22, 81675, Munich, Germany

    Kuangyu Shi, Florian C. Gaertner, Markus Schwaiger & Sibylle I. Ziegler

  2. Department of Radiooncology and Radiotherapy, Klinikum rechts der Isar, Technische Universität München, Munich, Germany

    Christine Bayer, Sabrina T. Astner & Peter Vaupel

  3. Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA

    Sung-Cheng Huang

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  1. Kuangyu Shi
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  2. Christine Bayer
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  3. Sabrina T. Astner
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Correspondence to Kuangyu Shi.

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Shi, K., Bayer, C., Astner, S.T. et al. Quantitative Analysis of [18F]FMISO PET for Tumor Hypoxia: Correlation of Modeling Results with Immunohistochemistry. Mol Imaging Biol 19, 120–129 (2017). https://doi.org/10.1007/s11307-016-0975-4

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