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Contrast Media & Molecular Imaging
Volume 2018, Article ID 5063285, 8 pages
https://doi.org/10.1155/2018/5063285
Research Article

Cervical Cancer: Associations between Metabolic Parameters and Whole Lesion Histogram Analysis Derived from Simultaneous 18F-FDG-PET/MRI

1Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
2Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany

Correspondence should be addressed to Hans-Jonas Meyer; ed.bew@reyem.09sanoj

Received 17 April 2018; Revised 12 June 2018; Accepted 25 June 2018; Published 30 July 2018

Academic Editor: Elena Bonanno

Copyright © 2018 Hans-Jonas Meyer et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. Jemal, F. Bray, M. M. Center et al., “Global cancer statistics,” Cancer Journal for Clinician, vol. 61, no. 2, pp. 69–90, 2011. View at Publisher · View at Google Scholar · View at Scopus
  2. E. Sala, S. Wakely, E. Senior, and D. Lomas, “MRI of malignant neoplasms of the uterine corpus and cervix,” American Journal of Roentgenology, vol. 188, no. 6, pp. 1577–1587, 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. A. R. Padhani, G. Liu, D. M. Koh et al., “Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations,” Neoplasia: an International Journal for Oncology Research, vol. 11, no. 2, pp. 102–125, 2009. View at Publisher · View at Google Scholar · View at Scopus
  4. A. Surov, H. J. Meyer, and A. Wienke, “Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis,” Oncotarget, vol. 8, no. 35, pp. 59492–59499, 2017. View at Publisher · View at Google Scholar · View at Scopus
  5. H. H. Chung, S. Y. Kang, S. Ha et al., “Prognostic value of preoperative intratumoral FDG uptake heterogeneity in early stage uterine cervical cancer,” Journal of Gynecologic Oncology, vol. 27, no. 2, p. e15, 2016. View at Publisher · View at Google Scholar · View at Scopus
  6. M. S. Jo, O. H. Choi, D. S. Suh et al., “Correlation between expression of biological markers and Ffluorodeoxyglucose uptake in endometrial cancer,” Oncology Research and Treatment, vol. 37, no. 1-2, pp. 30–34, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. H. J. Im, T. Bradshaw, M. Solaiyappan, and S. Y. Cho, “Current methods to define metabolic tumor volume in positron emission tomography: which one is better,” Nuclear Medicine and Molecular Imaging, vol. 52, no. 1, pp. 5–15, 2018. View at Publisher · View at Google Scholar · View at Scopus
  8. J. H. Hong, K. J. Min, J. K. Lee et al., “Prognostic value of the sum of metabolic tumor volume of primary tumor and lymph nodes using 18F-FDG PET/CT in patients with cervical cancer,” Medicine, vol. 95, no. 9, Article ID e2992, 2016. View at Publisher · View at Google Scholar · View at Scopus
  9. G. Shen, H. Ma, B. Liu et al., “Correlation of the apparent diffusion coefficient and the standardized uptake value in neoplastic lesions: a meta-analysis,” Nuclear Medicine Communications, vol. 38, no. 12, pp. 1076–1084, 2017. View at Publisher · View at Google Scholar · View at Scopus
  10. P. Brandmaier, S. Purz, K. Bremicker et al., “Simultaneous [18F]FDG-PET/MRI: correlation of apparent diffusion coefficient (ADC) and standardized uptake value (SUV) in primary and recurrent cervical cancer,” PLoS One, vol. 10, no. 11, Article ID e0141684, 2015. View at Publisher · View at Google Scholar · View at Scopus
  11. L. Goense, S. E. Heethuis, P. S. N. van Rossum et al., “Correlation between functional imaging markers derived from diffusion-weighted MRI and 18F-FDG PET/CT in esophageal cancer,” Nuclear Medicine Communications, vol. 39, no. 1, pp. 60–67, 2018. View at Publisher · View at Google Scholar · View at Scopus
  12. K. A. Zukotynski, S. Vajapeyam, F. H. Fahey et al., “Correlation of 18F-FDG PET and MRI apparent diffusion coefficient histogram metrics with survival in diffuse intrinsic pontine glioma: a report from the pediatric brain tumor consortium,” Journal of Nuclear Medicine, vol. 58, no. 8, pp. 1264–1269, 2017. View at Publisher · View at Google Scholar · View at Scopus
  13. K. Kitajima, T. Yamano, K. Fukushima et al., “Correlation of the SUVmax of FDG-PET and ADC values of diffusion-weighted MR imaging with pathologic prognostic factors in breast carcinoma,” European Journal of Radiology, vol. 85, no. 5, pp. 943–949, 2016. View at Publisher · View at Google Scholar · View at Scopus
  14. A. Surov, H. J. Meyer, S. Schob et al., “Parameters of simultaneous 18F-FDG-PET/MRI predict tumor stage and several histopathological features in uterine cervical cancer,” Oncotarget, vol. 8, no. 27, pp. 28285–28296, 2017. View at Publisher · View at Google Scholar · View at Scopus
  15. K. C. Ho, G. Lin, J. J. Wang et al., “Correlation of apparent diffusion coefficients measured by 3T diffusion-weighted MRI and SUV from FDG PET/CT in primary cervical cancer,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 36, no. 2, pp. 200–208, 2009. View at Publisher · View at Google Scholar · View at Scopus
  16. H. Sun, J. Xin, S. Zhang et al., “Anatomical and functional volume concordance between FDG PET, and T2 and diffusion-weighted MRI for cervical cancer: a hybrid PET/MR study,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 41, no. 5, pp. 898–905, 2014. View at Publisher · View at Google Scholar · View at Scopus
  17. N. Just, “Improving tumour heterogeneity MRI assessment with histograms,” British Journal of Cancer, vol. 111, no. 12, pp. 2205–2213, 2014. View at Publisher · View at Google Scholar · View at Scopus
  18. W. Liu, X. H. Liu, W. Tang et al., “Histogram analysis of stretched-exponential and monoexponential diffusion-weighted imaging models for distinguishing low and intermediate/high gleason scores in prostate carcinoma,” Journal of Magnetic Resonance Imaging, 2018, In press. View at Publisher · View at Google Scholar · View at Scopus
  19. T. Shindo, Y. Fukukura, T. Umanodan et al., “Histogram analysis of apparent diffusion coefficient in differentiating pancreatic adenocarcinoma and neuroendocrine tumor,” Medicine, vol. 95, no. 4, Article ID e2574, 2016. View at Publisher · View at Google Scholar · View at Scopus
  20. Y. Ueno, R. Lisbona, T. Tamada et al., “Comparison of FDG PET metabolic tumour volume versus ADC histogram: prognostic value of tumour treatment response and survival in patients with locally advanced uterine cervical cancer,” British Journal of Radiology, vol. 90, no. 1075, Article ID 20170035, 2017. View at Publisher · View at Google Scholar · View at Scopus
  21. H. J. Choi, J. W. Roh, S. S. Seo et al., “Comparison of the accuracy of magnetic resonance imaging and positron emission tomography/computed tomography in the presurgical detection of lymph node metastases in patients with uterine cervical carcinoma: a prospective study,” Cancer, vol. 106, no. 4, pp. 914–922, 2006. View at Publisher · View at Google Scholar · View at Scopus
  22. T. Sarabhai, B. M. Schaarschmidt, A. Wetter et al., “Comparison of 18F-FDG PET/MRI and MRI for pre-therapeutic tumor staging of patients with primary cancer of the uterine cervix,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 45, no. 1, pp. 67–76, 2018. View at Publisher · View at Google Scholar · View at Scopus
  23. H. J. Yang, W. J. Xu, Y. H. Guan et al., “Expression of Glut-1 and HK-II in pancreatic cancer and their impact on prognosis and FDG accumulation,” Translational Oncology, vol. 9, no. 6, pp. 583–591, 2016. View at Publisher · View at Google Scholar · View at Scopus
  24. S. Kyriazi, D. J. Collins, C. Messiou et al., “Metastatic ovarian and primary peritoneal cancer: assessing chemotherapy response with diffusion-weighted MR imaging–value of histogram analysis of apparent diffusion coefficients,” Radiology, vol. 261, no. 1, pp. 182–192, 2011. View at Publisher · View at Google Scholar · View at Scopus
  25. Y. Guan, W. Li, Z. Jiang et al., “Whole-lesion apparent diffusion coefficient-based entropy-related parameters for characterizing cervical cancers: initial findings,” Academic Radiology, vol. 23, no. 12, pp. 1559–1567, 2016. View at Publisher · View at Google Scholar · View at Scopus
  26. Y. Guan, W. Li, Z. Jiang et al., “Value of whole-lesion apparent diffusion coefficient (ADC) first-order statistics and texture features in clinical staging of cervical cancers,” Clinical Radiology, vol. 72, no. 11, pp. 951–958, 2017. View at Publisher · View at Google Scholar · View at Scopus
  27. S. Schob, H. J. Meyer, N. Pazaitis et al., “ADC histogram analysis of cervical cancer aids detecting lymphatic metastases-a preliminary study,” Molecular Imaging and Biology, vol. 19, no. 6, pp. 953–962, 2017. View at Publisher · View at Google Scholar · View at Scopus
  28. J. Meng, L. Zhu, L. Zhu et al., “Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT,” Oncotarget, vol. 8, no. 54, pp. 92442–92453, 2017. View at Publisher · View at Google Scholar · View at Scopus
  29. Y. Lin, H. Li, Z. Chen et al., “Correlation of histogram analysis of apparent diffusion coefficient with uterine cervical pathologic finding,” American Journal of Roentgenology, vol. 204, no. 5, pp. 1125–1131, 2015. View at Publisher · View at Google Scholar · View at Scopus
  30. S. Cima, A. M. Perrone, P. Castellucci et al., “Prognostic impact of pretreatment fluorodeoxyglucose positron emission tomography/computed tomography SUVmax in patients with locally advanced cervical cancer,” International Journal of Gynecological Cancer, vol. 28, no. 3, pp. 575–580, 2018. View at Publisher · View at Google Scholar · View at Scopus
  31. G. O. Chong, W. K. Lee, S. Y. Jeong et al., “Prognostic value of intratumoral metabolic heterogeneity on F-18 fluorodeoxyglucose positron emission tomography/computed tomography in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy,” Oncotarget, vol. 8, no. 52, pp. 90402–90412, 2017. View at Publisher · View at Google Scholar · View at Scopus
  32. Y. Liang, X. Li, H. Wan et al., “Prognostic value of volume-based metabolic parameters obtained by 18F-FDG-PET/CT in patients with locally advanced squamous cell cervical carcinoma,” Journal of Computer Assisted Tomography, vol. 42, no. 3, pp. 429–434, 2018. View at Publisher · View at Google Scholar
  33. D. O. Driscoll, D. Halpenny, C. Johnston et al., “18F-FDG-PET/CT is of limited value in primary staging of early stage cervical cancer,” Abdominal Imaging, vol. 40, no. 1, pp. 127–133, 2015. View at Publisher · View at Google Scholar · View at Scopus
  34. M. Scimeca, N. Urbano, R. Bonfiglio et al., “Management of oncological patients in the digital era: anatomic pathology and nuclear medicine teamwork,” Future Oncology, vol. 14, no. 11, pp. 1013–1015, 2018. View at Publisher · View at Google Scholar
  35. P. Y. Wang, J. Xin, H. Z. Sun et al., “Observation on correlation of ADC value and SUV in primary squamous cell cervical cancer with hybrid 18F-FDG PET/MR,” Chinese Journal of Medical Imaging Technology, vol. 30, pp. 603–607, 2014. View at Google Scholar
  36. K. Pinker, P. Andrzejewski, P. Baltzer et al., “Multiparametric [18F]fluorodeoxyglucose/[18F]fluoromisonidazole positron emission tomography/magnetic resonance imaging of locally advanced cervical cancer for the non-invasive detection of tumor heterogeneity: a pilot study,” PLoS One, vol. 11, no. 5, Article ID e0155333, 2016. View at Publisher · View at Google Scholar · View at Scopus
  37. A. Y. T. Lai, J. A. U. Perucho, X. Xu et al., “Concordance of FDG PET/CT metabolic tumour volume versus DW-MRI functional tumour volume with T2-weighted anatomical tumour volume in cervical cancer,” BMC Cancer, vol. 17, no. 1, p. 825, 2017. View at Publisher · View at Google Scholar · View at Scopus