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BioMed Research International
Volume 2015, Article ID 120749, 6 pages
http://dx.doi.org/10.1155/2015/120749
Research Article

CT Perfusion Characteristics Identify Metastatic Sites in Liver

1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
2Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA

Received 4 April 2015; Revised 29 May 2015; Accepted 7 June 2015

Academic Editor: Franco M. Buonaguro

Copyright © 2015 Yuan Wang 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. K. Miles, C. Charnsangavej, F. Lee, E. Fishman, K. Horton, and T.-Y. Lee, “Application of CT in the investigation of angiogenesis in oncology,” Academic Radiology, vol. 7, no. 10, pp. 840–850, 2000. View at Publisher · View at Google Scholar · View at Scopus
  2. A. K. Dixon and F. J. Gilbert, “Standardising measurement of tumour vascularity by imaging: recommendations for ultrasound, computed tomography, magnetic resonance imaging and positron emission tomography,” European Radiology, vol. 22, no. 7, pp. 1427–1429, 2012. View at Publisher · View at Google Scholar · View at Scopus
  3. K. A. Miles, T.-Y. Lee, V. Goh et al., “Current status and guidelines for the assessment of tumour vascular support with dynamic contrast-enhanced computed tomography,” European Radiology, vol. 22, no. 7, pp. 1430–1441, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Bisdas, M. Baghi, J. Wagenblast et al., “Differentiation of benign and malignant parotid tumors using deconvolution-based perfusion CT imaging: feasibility of the method and initial results,” European Journal of Radiology, vol. 64, no. 2, pp. 258–265, 2007. View at Publisher · View at Google Scholar · View at Scopus
  5. D. V. Sahani, S. P. Kalva, L. M. Hamberg et al., “Assessing tumor perfusion and treatment response in rectal cancer with multisection CT: initial observations,” Radiology, vol. 234, no. 3, pp. 785–792, 2005. View at Publisher · View at Google Scholar · View at Scopus
  6. S. H. Kim, A. Kamaya, and J. K. Willmann, “CT perfusion of the liver: principles and applications in oncology,” Radiology, vol. 272, no. 2, pp. 322–344, 2014. View at Publisher · View at Google Scholar
  7. V. Goh, S. Halligan, F. Daley, D. M. Wellsted, T. Guenther, and C. I. Bartram, “Colorectal tumor vascularity: quantitative assessment with multidetector CT—do tumor perfusion measurements reflect angiogenesis?” Radiology, vol. 249, no. 2, pp. 510–517, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. K. A. Miles, “Functional computed tomography in oncology,” European Journal of Cancer, vol. 38, no. 16, pp. 2079–2084, 2002. View at Publisher · View at Google Scholar · View at Scopus
  9. A. Guyennon, M. Mihaila, J. Palma, C. Lombard-Bohas, J. A. Chayvialle, and F. Pilleul, “Perfusion characterization of liver metastases from endocrine tumors: computed tomography perfusion,” World Journal of Radiology, vol. 2, no. 11, pp. 449–454, 2010. View at Google Scholar
  10. C. S. Reiner, R. Goetti, I. A. Burger et al., “Liver perfusion imaging in patients with primary and metastatic liver malignancy: prospective comparison between 99mTc-MAAspect and dynamic CT perfusion,” Academic Radiology, vol. 19, no. 5, pp. 613–621, 2012. View at Publisher · View at Google Scholar · View at Scopus
  11. C. S. Ng, B. P. Hobbs, A. G. Chandler et al., “Metastases to the liver from neuroendocrine tumors: effect of duration of scan acquisition on CT perfusion values,” Radiology, vol. 269, no. 3, pp. 758–767, 2013. View at Publisher · View at Google Scholar · View at Scopus
  12. T. Y. Lee, “Functional CT: physiological models,” Trends in Biotechnology, vol. 20, no. 8, pp. S3–S10, 2002. View at Publisher · View at Google Scholar · View at Scopus
  13. C. S. Ng, A. G. Chandler, W. Wei et al., “Effect of duration of scan acquisition on CT perfusion parameter values in primary and metastatic tumors in the lung,” European Journal of Radiology, vol. 82, no. 10, pp. 1811–1818, 2013. View at Publisher · View at Google Scholar · View at Scopus
  14. C. S. Ng, B. P. Hobbs, W. Wei et al., “Effect on perfusion values of sampling interval of computed tomographic perfusion acquisitions in neuroendocrine liver metastases and normal liver,” Journal of Computer Assisted Tomography, vol. 39, no. 3, pp. 373–382, 2015. View at Google Scholar
  15. P. C. Sanelli, M. H. Lev, J. D. Eastwood, R. G. Gonzalez, and T. Y. Lee, “The effect of varying user-selected input parameters on quantitative values in CT perfusion maps,” Academic Radiology, vol. 11, no. 10, pp. 1085–1092, 2004. View at Publisher · View at Google Scholar · View at Scopus
  16. C. S. Ng, A. G. Chandler, J. C. Yao et al., “Effect of pre-enhancement set point on computed tomographic perfusion values in normal liver and metastases to the liver from neuroendocrine tumors,” Journal of Computer Assisted Tomography, vol. 38, no. 4, pp. 526–534, 2014. View at Publisher · View at Google Scholar · View at Scopus
  17. Y. Wang, B. P. Hobbs, J. Hu, C. S. Ng, and K. A. Do, “Predictive classification of correlated targets with application to detection of metastatic cancer using functional CT imaging,” Biometrics, 2015. View at Publisher · View at Google Scholar