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Validation of magnetic resonance imaging‑based automatic high‑grade glioma segmentation accuracy via 11C‑methionine positron emission tomography

  • Authors:
    • Tomohiko Ozaki
    • Manabu Kinoshita
    • Hideyuki Arita
    • Naoki Kagawa
    • Yasunori Fujimoto
    • Yonehiro Kanemura
    • Mio Sakai
    • Yoshiyuki Watanabe
    • Katsuyuki Nakanishi
    • Eku Shimosegawa
    • Jun Hatazawa
    • Haruhiko Kishima
  • View Affiliations / Copyright

    Affiliations: Department of Neurosurgery, Osaka International Cancer Institute, Osaka 5418567, Japan, Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan, Department of Biomedical Research and Innovation, Institute for Clinical Research, Osaka National Hospital, National Hospital Organization, Osaka 5400006, Japan, Department of Radiology, Osaka International Cancer Institute, Osaka 5418567, Japan, Department of Radiology, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan, Department of Nuclear Medicine and Tracer Kinetics, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan
    Copyright: © Ozaki et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 4074-4081
    |
    Published online on: August 8, 2019
       https://doi.org/10.3892/ol.2019.10734
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Abstract

Brain Tumor Image Analysis (BraTumIA) is a fully automated segmentation tool dedicated to detecting brain tumors imaged by magnetic resonance imaging (MRI). BraTumIA has recently been applied to several clinical investigations; however, the validity of this novel method has not yet been fully examined. The present study was conducted to validate the quality of tumor segmentation with BraTumIA in comparison with results from 11C‑methionine positron emission tomography (MET‑PET). A total of 45 consecutive newly diagnosed high‑grade gliomas imaged by MRI and MET‑PET were analyzed. Automatic tumor segmentation was conducted by BraTumIA and the resulting segmentation images were registered to MET‑PET. Three‑dimensional conformal association between these two modalities was calculated, considering MET‑PET as the gold standard. High underestimation and overestimation errors were observed in tumor segmentation calculated by BraTumIA compared with MET‑PET. Furthermore, when the tumor/normal ratio threshold was set at 1.3 from MET‑PET, the BraTumIA false‑positive fraction was ~0.4 and the false‑negative fraction was 0.9. By tightening this threshold to 2.0, the BraTumIA false‑positive fraction was 0.6 and the false‑negative fraction was 0.6. Following comparison of segmentation performance with BraTumIA with regard to glioblastoma (GBM) and World Health Organization (WHO) grade III glioma, GBM exhibited better segmentation compared with WHO grade III glioma. Although BraTumIA may be able to detect enhanced tumors, non‑enhancing tumors and necrosis, the spatial concordance rate with MET‑PET was relatively low. Careful interpretation is therefore required when using this technique.
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Copy and paste a formatted citation
Spandidos Publications style
Ozaki T, Kinoshita M, Arita H, Kagawa N, Fujimoto Y, Kanemura Y, Sakai M, Watanabe Y, Nakanishi K, Shimosegawa E, Shimosegawa E, et al: Validation of magnetic resonance imaging‑based automatic high‑grade glioma segmentation accuracy via 11C‑methionine positron emission tomography. Oncol Lett 18: 4074-4081, 2019.
APA
Ozaki, T., Kinoshita, M., Arita, H., Kagawa, N., Fujimoto, Y., Kanemura, Y. ... Kishima, H. (2019). Validation of magnetic resonance imaging‑based automatic high‑grade glioma segmentation accuracy via 11C‑methionine positron emission tomography. Oncology Letters, 18, 4074-4081. https://doi.org/10.3892/ol.2019.10734
MLA
Ozaki, T., Kinoshita, M., Arita, H., Kagawa, N., Fujimoto, Y., Kanemura, Y., Sakai, M., Watanabe, Y., Nakanishi, K., Shimosegawa, E., Hatazawa, J., Kishima, H."Validation of magnetic resonance imaging‑based automatic high‑grade glioma segmentation accuracy via 11C‑methionine positron emission tomography". Oncology Letters 18.4 (2019): 4074-4081.
Chicago
Ozaki, T., Kinoshita, M., Arita, H., Kagawa, N., Fujimoto, Y., Kanemura, Y., Sakai, M., Watanabe, Y., Nakanishi, K., Shimosegawa, E., Hatazawa, J., Kishima, H."Validation of magnetic resonance imaging‑based automatic high‑grade glioma segmentation accuracy via 11C‑methionine positron emission tomography". Oncology Letters 18, no. 4 (2019): 4074-4081. https://doi.org/10.3892/ol.2019.10734
Copy and paste a formatted citation
x
Spandidos Publications style
Ozaki T, Kinoshita M, Arita H, Kagawa N, Fujimoto Y, Kanemura Y, Sakai M, Watanabe Y, Nakanishi K, Shimosegawa E, Shimosegawa E, et al: Validation of magnetic resonance imaging‑based automatic high‑grade glioma segmentation accuracy via 11C‑methionine positron emission tomography. Oncol Lett 18: 4074-4081, 2019.
APA
Ozaki, T., Kinoshita, M., Arita, H., Kagawa, N., Fujimoto, Y., Kanemura, Y. ... Kishima, H. (2019). Validation of magnetic resonance imaging‑based automatic high‑grade glioma segmentation accuracy via 11C‑methionine positron emission tomography. Oncology Letters, 18, 4074-4081. https://doi.org/10.3892/ol.2019.10734
MLA
Ozaki, T., Kinoshita, M., Arita, H., Kagawa, N., Fujimoto, Y., Kanemura, Y., Sakai, M., Watanabe, Y., Nakanishi, K., Shimosegawa, E., Hatazawa, J., Kishima, H."Validation of magnetic resonance imaging‑based automatic high‑grade glioma segmentation accuracy via 11C‑methionine positron emission tomography". Oncology Letters 18.4 (2019): 4074-4081.
Chicago
Ozaki, T., Kinoshita, M., Arita, H., Kagawa, N., Fujimoto, Y., Kanemura, Y., Sakai, M., Watanabe, Y., Nakanishi, K., Shimosegawa, E., Hatazawa, J., Kishima, H."Validation of magnetic resonance imaging‑based automatic high‑grade glioma segmentation accuracy via 11C‑methionine positron emission tomography". Oncology Letters 18, no. 4 (2019): 4074-4081. https://doi.org/10.3892/ol.2019.10734
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