Robustness of quantitative hypoxia PET image analysis for predicting local tumor control

Authors

  • David Mönnich Section for Biomedical Physics, Department of Radiation Oncology, Eberhard Karls University Tübingen, Germany; German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
  • Stefan Welz Department of Radiation Oncology, Eberhard Karls University Tübingen, Germany
  • Daniela Thorwarth Section for Biomedical Physics, Department of Radiation Oncology, Eberhard Karls University Tübingen, Germany
  • Christina Pfannenberg Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tübingen, Germany
  • Gerald Reischl Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen, Germany
  • Paul-Stefan Mauz Department of Otorhinolaryngology, Head and Neck Surgery, Eberhard Karls University Tübingen, Germany
  • Konstantin Nikolaou Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tübingen, Germany
  • Christian la Fougère Department of Nuclear Medicine, Eberhard Karls University Tübingen, Germany
  • Daniel Zips Department of Radiation Oncology, Eberhard Karls University Tübingen, Germany

DOI:

https://doi.org/10.3109/0284186X.2015.1071496

Abstract

Background. Previous studies suggested the maximum tumor to background ratio (TBRmax) in FMISO PET images as a potentially predictive parameter for local control after radio-chemotherapy (CRT) in head and neck squamous cell carcinomas (HNSCC). However, different TBRmax thresholds for stratification were reported, implying that a common threshold cannot readily be used among different institutions without the risk of reducing prediction accuracy. Therefore, this study investigated the robustness of using a common pre-defined TBRmax, simulating a multicenter clinical trial.

Material and methods. FMISO PET/CT was performed four hours post-injection in 22 patients with advanced HNSCC in a phase II FMISO dose escalation study. PET background regions of interest (ROIs) were manually defined in deep neck muscles. TBRmax was calculated as the mean of the highest-valued voxels within the high risk RT planning target volume. Its predictive power with respect to local control was tested, classifying patients using median TBRmax as threshold. The influence of systematically varying quantification between institutions was studied in silico by applying offsets of ± 10% and ± 20% to the TBRmax of all patients, while the threshold remained constant. The effect was analyzed using a receiver operating characteristic (ROC). True positive and false positive rates (TPR/FPR) as well as positive and negative predictive values (PPV/NPV) were evaluated.

Results. For the reference condition without an offset the median TBRmax was 2.0 (1.4–3.5). Patients were classified using this threshold and TPR = 0.7, FPR = 0.4, PPV = 0.5 and NPV = 0.8 were observed. Accuracy declined with increasing offsets. Negative offsets of -10% and -20% resulted in TPR = 0.43 and 0.14, FPR = 0.20 and 0.13, PPV = 0.50 and 0.33 and NPV = 0.75 and 0.68, respectively. Positive offsets of + 10% and + 20% resulted in TPR = 1.00 and 1.00, FPR = 0.53 and 0.67, PPV = 0.47 and 0.41 and NPV = 1.00 and 1.00, respectively.

Conclusions. Using a common pre-defined TBRmax threshold in multicenter trials requires careful standardization and harmonization of all steps from patient preparation to image analysis. Our results indicate that TBRmax should deviate less than 10% from reference conditions (absolute value in this dataset ± 0.2). This conclusion likely applies to all low contrast nitroimidazole hypoxia PET tracers.

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Published

2015-10-21

How to Cite

Mönnich, D., Welz, S., Thorwarth, D., Pfannenberg, C., Reischl, G., Mauz, P.-S., … Zips, D. (2015). Robustness of quantitative hypoxia PET image analysis for predicting local tumor control. Acta Oncologica, 54(9), 1364–1369. https://doi.org/10.3109/0284186X.2015.1071496