Skip to main content

Advertisement

Log in

Assessment of the spatial pattern of colorectal tumour perfusion estimated at perfusion CT using two-dimensional fractal analysis

  • Computed Tomography
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

The aim was to evaluate the feasibility of fractal analysis for assessing the spatial pattern of colorectal tumour perfusion at dynamic contrast-enhanced CT (perfusion CT). Twenty patients with colorectal adenocarcinoma underwent a 65-s perfusion CT study from which a perfusion parametric map was generated using validated commercial software. The tumour was identified by an experienced radiologist, segmented via thresholding and fractal analysis applied using in-house software: fractal dimension, abundance and lacunarity were assessed for the entire outlined tumour and for selected representative areas within the tumour of low and high perfusion. Comparison was made with ten patients with normal colons, processed in a similar manner, using two-way mixed analysis of variance with statistical significance at the 5% level. Fractal values were higher in cancer than normal colon (p ≤ 0.001): mean (SD) 1.71 (0.07) versus 1.61 (0.07) for fractal dimension and 7.82 (0.62) and 6.89 (0.47) for fractal abundance. Fractal values were lower in ‘high’ than ‘low’ perfusion areas. Lacunarity curves were shifted to the right for cancer compared with normal colon. In conclusion, colorectal cancer mapped by perfusion CT demonstrates fractal properties. Fractal analysis is feasible, potentially providing a quantitative measure of the spatial pattern of tumour perfusion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Hurwitz H, Fehrenbacher L, Novotny W et al (2004) Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic colorectal cancer. N Engl J Med 350:2335–2342

    Article  PubMed  CAS  Google Scholar 

  2. Willett CG, Boucher Y, di Tomaso E et al (2004) Direct evidence that the VEGF-specific antibody bevacizumab has antivascular effects in human rectal cancer. Nat Med 10:145–147

    Article  PubMed  CAS  Google Scholar 

  3. Ng QS, Goh V, Milner J et al (2007) Effect of nitric oxide synthesis on tumour blood volume and vascular activity in cancer patients: a phase I study. Lancet Oncology 8:111–118

    Article  PubMed  CAS  Google Scholar 

  4. Ng QS, Goh V, Milner J et al (2007) Tumour anti-vascular effects of radiotherapy combined with combretastatin A4 phosphate in human non-small cell lung cancer. Int J Radiat Oncol Biol Phys 67:1375–1380

    PubMed  CAS  Google Scholar 

  5. Meijerink MR, Van Cruijsen H, Hoekman K et al (2007) The use of perfusion CT for the evaluation of therapy combining AZD2171 with gefinitib in cancer patients. Eur Radiol 17:1700–1713

    Article  PubMed  Google Scholar 

  6. Koukourakis MI, Mavanis I, Kouklakis G et al (2007) Early anti-vascular effects of bevacizumab anti-VEGF monoclonal antibody on colorectal carcinomas assessed with functional CT imaging. Am J Clin Oncol 30:315–318

    Article  PubMed  CAS  Google Scholar 

  7. Meijerink MR, van Waesberghe JHTM, van der Weide L et al (2008) Total liver volume perfusion CT using 3D image fusion to improve detection and characterization of liver metastases. Eur Radiol 18(10):2345–54

    Article  PubMed  Google Scholar 

  8. Bisdas S, Baghi M, Wagenblast J et al (2007) Differentiation of benign and malignant parotid tumors using deconvolution-based perfusion CT imaging: feasibility of the method and initial results. Eur J Radiol 64:258–265

    Article  PubMed  CAS  Google Scholar 

  9. Goh V, Halligan S, Taylor SA et al (2007) Differentiation of diverticulitis and colorectal cancer: quantitative CT perfusion measurements versus morphological criteria–initial experience. Radiology 242:456–462

    Article  PubMed  Google Scholar 

  10. Sitartchouk I, Roberts HC, Pereira AM et al (2008) Computed tomography perfusion using first pass methods for lung nodule characterization. Invest Radiol 43:349–358

    Article  PubMed  Google Scholar 

  11. Liu Y, Bellomi M, Gatti G, Ping X (2007) Accuracy of computed tomography perfusion in assessing metastatic involvement of enlarged axillary lymph nodes in patients with breast cancer. Breast Cancer Res 9:R40

    Article  PubMed  Google Scholar 

  12. Goh V, Halligan S, Welsted DM, Bartram CI (2008) Can perfusion CT assessment of primary colorectal adenocarcinoma blood flow at staging predict for subsequent metastatic disease? A pilot study. Eur Radiol. doi:10.1007/s00330-008-1128-1

  13. Hermans R, Meijerink M, Van den Bogaert W et al (2003) Tumor perfusion rate determined non-invasively by dynamic computed tomography predicts outcome in head-and-neck cancer after radiotherapy. Int J Radiat Oncol Biol Phys 57:1351–1356

    PubMed  Google Scholar 

  14. Sahani DV, Kalva SP, Hamberg LM et al (2005) Assessing tumor perfusion and treatment response in rectal cancer with multisection CT: initial observations. Radiology 234:785–792

    Article  PubMed  Google Scholar 

  15. Bellomi M, Petralia G, Sonzogni A et al (2007) CT perfusion for the monitoring of neo-adjuvant chemoradiation therapy in rectal carcinoma. Radiology 244:486–493

    Article  PubMed  Google Scholar 

  16. Gandhi D, Chepeha DB, Miller T et al (2006) Correlation between initial and early follow-up CT perfusion parameters with endoscopic tumor response in patients with advanced squamous cell carcinomas of the oropharynx treated with organ-preservation therapy. AJNR Am J Neuroradiol 27:101–106

    PubMed  CAS  Google Scholar 

  17. Purdie TG, Henderson E, Lee TY (2001) Functional CT imaging of angiogenesis in rabbit VX2 soft-tissue tumor. Phys Med Biol 46:3161–3175

    Article  PubMed  CAS  Google Scholar 

  18. Goh V, Halligan S, Hugill JA, Bartram CI (2006) Quantitative assessment of tissue perfusion using MDCT: comparison of colorectal cancer and skeletal muscle reproducibility. AJR Am J of Roentgenol 187:164–169

    Article  Google Scholar 

  19. Bisdas S, Surlan-Popovic K, Didanovic V, Vogl TJ (2008) Functional CT of squamous cell carcinoma in the head and neck: repeatability of tumor and muscle quantitative measurements, inter and intra-observer agreement. Eur Radiol 18:2241–2250

    Article  PubMed  Google Scholar 

  20. Stewart EE, Chen X, Hadway J, Lee TY (2008) Hepatic perfusion in a tumor model using DCE-CT: an accuracy and precision study. Phys Med Biol 53:4249–4267

    Article  PubMed  Google Scholar 

  21. Hakime A, Peddi H, Hines-Peralta AU et al (2007) CT Perfusion for determination of pharmacologically mediated blood flow changes in an animal tumor model. Radiology 243:712–719

    Article  PubMed  Google Scholar 

  22. Mandelbrot BB (1983) The fractal geometry of nature. WH Freeman and Co, San Francisco, CA

    Google Scholar 

  23. Baish JW, Jain RK (2000) Fractals and cancer. Cancer Res 60:3683–3688

    PubMed  CAS  Google Scholar 

  24. Cross SS (1997) Fractals in pathology. J Path 182:1–8

    Article  PubMed  CAS  Google Scholar 

  25. Smith TG Jr, Lange GD, Marks WB (1996) Fractal methods and results in cellular morphology – dimensions, lacunarity and multifractals. J Neuroscience Methods 69:123–136

    Article  Google Scholar 

  26. Plotnick RE, Gardner RH, Hargrove WW et al (1996) Lacunarity analysis: a general technique for the analysis of spatial patterns. Phys Rev E Stat Phys Plasma Fluids and Related Interdisciplinary Topics 53:5461–5468

    CAS  Google Scholar 

  27. Goh V, Halligan S, Gharpuray A et al (2008) Quantitative assessment of tumor vascular parameters using perfusion CT: influence of tumor region of interest (ROI). Radiology 247:726–732

    Article  PubMed  Google Scholar 

  28. Gazit Y, Baish JW, Safabakhsh N et al (1997) Fractal characteristics of tumor vascular architecture during tumor growth and regression. Microcirculation 4:395–402

    Article  PubMed  CAS  Google Scholar 

  29. Kido S, Kuriyama K, Higashiyama M et al (2003) Fractal analysis of internal and peripheral textures of small peripheral bronchogenic carcinomas in thin-section computed tomography: comparison of bronchioloalveolar cell carcinomas with nonbronchioloalveolar cell carcinomas. J Comput Assist Tomogr 27:56–61

    Article  PubMed  Google Scholar 

  30. Kido S, Kuriyama K, Higashiyama M et al (2002) Fractal analysis of small peripheral pulmonary nodules in thin section CT: evaluation of lung-nodule interfaces. J Comput Assist Tomogr 26:573–578

    Article  PubMed  Google Scholar 

  31. Dougherty G, Henebry GM (2002) Lacunarity analysis of spatial pattern in CT images of vertebral trabecular bone for assessing osteoporosis. Med Eng Phys 24:129–138

    Article  PubMed  Google Scholar 

  32. Craciunescu OI, Das SK, Clegg ST (1999) Dynamic contrast-enhanced MRI and fractal characteristics of percolation clusters in two-dimensional tumor blood perfusion. J Biomech Eng 121:480–486

    Article  PubMed  CAS  Google Scholar 

  33. Wintermark M, Smith WS, Ko NU et al (2004) Dynamic perfusion CT: optimizing the temporal resolution and contrast volume for calculation of perfusion CT parameters in stroke patients. AJNR Am J Neuroradiol 25:720–729

    PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank GE Healthcare for providing the Perfusion CT software used in this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vicky Goh.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Goh, V., Sanghera, B., Wellsted, D.M. et al. Assessment of the spatial pattern of colorectal tumour perfusion estimated at perfusion CT using two-dimensional fractal analysis. Eur Radiol 19, 1358–1365 (2009). https://doi.org/10.1007/s00330-009-1304-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-009-1304-y

Keywords

Navigation