Skip to main content

Advertisement

Log in

Can perfusion CT assessment of primary colorectal adenocarcinoma blood flow at staging predict for subsequent metastatic disease? A pilot study

  • Gastrointestinal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

We aimed to determine whether perfusion CT measurements at colorectal cancer staging may predict for subsequent metastatic relapse. Fifty two prospective patients underwent perfusion CT at staging to estimate tumour blood flow, blood volume, mean transit time, and permeability surface area product. Patients considered metastasis free and suitable for surgery underwent curative resection subsequently. At final analysis, a median of 48.6 months post-surgery, patients were divided into those who remained disease free, and those with subsequent metastases. Vascular parameters for these two groups were compared using t-testing, and receiver operator curve analysis was performed to determine the sensitivity and specificity of these vascular parameters for predicting metastases. Thirty seven (71%) patients underwent curative surgery; data were available for 35: 26 (74%) remained disease free; 9 (26%) recurred (8 metastatic, 1 local). Tumour blood flow differed significantly between disease-free and metastatic patients (76.0 versus 45.7 ml/min/100 g tissue; p = 0.008). With blood flow <64 ml/min/100 g tissue, sensitivity and specificity (95% CI) for development of metastases were 100% (60–100%) and 73% (53–87%), respectively. Our preliminary findings suggest that primary tumour blood flow might potentially be a useful predictor warranting further study.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. McArdle CS, Hole D, Hansell D et al (1990) Prospective study of colorectal cancer in the west of Scotland: 10-year follow-up. Br J Surg 77:280–282

    Article  PubMed  CAS  Google Scholar 

  2. Sargent DJ, Waiend HS, Haller DG et al (2005) Disease-free survival versus overall survival as a primary end point for adjuvant colon studies: individual patient data from 20,898 patients on 18 randomized trials. J Clin Oncol 23:8664–8670

    Article  PubMed  Google Scholar 

  3. Sargent DJ, Patiyil S, Yothers G et al (2007) End points for colon cancer adjuvant trials: observations and recommendations based on individual patient data from 20,898 patients enrolled onto 18 randomized trials from the ACCENT group. J Clin Oncol 25:4569–4574

    Article  PubMed  Google Scholar 

  4. Punt CJ (2004) New options and old dilemmas in the treatment of patients with advanced colorectal cancer. Ann Oncol 15:1453–1459

    Article  PubMed  CAS  Google Scholar 

  5. Goldberg RM, Hurwitz HI, Fuchs CS (2006) The role of targeted therapy in the treatment of colorectal cancer. Clin Adv Hematol Oncol 4(8 Supl 17):1–10

    PubMed  Google Scholar 

  6. Ogura O, Takebayashi Y, Sameshima T et al (2001) Pre-operative assessment of vascularity by color Doppler ultrasonography in human rectal carcinoma. Dis Colon Rectum 44:538–548

    Article  PubMed  CAS  Google Scholar 

  7. Chen CN, Cheng YM, Liang JT et al (2000) Color Doppler vascularity index can predict distant metastasis and survival in colon cancer patients. Cancer Res 60:2892–2897

    PubMed  CAS  Google Scholar 

  8. Leen E, Angerson WJ, Wotherspoon H et al (1995) Detection of colorectal liver metastases: comparison of laparotomy, CT, US, and Doppler perfusion index and evaluation of postoperative follow-up results. Radiology 195:113–116

    PubMed  CAS  Google Scholar 

  9. Leen E, Goldberg JA, Angerson WJ et al (2000) Potential role of doppler perfusion index in selection of patients with colorectal cancer for adjuvant chemotherapy. Lancet 355:34–37

    Article  PubMed  CAS  Google Scholar 

  10. Fowler RC, Harris KM, Swift SE et al (1998) Doppler perfusion index: measurement in nine healthy volunteers. Radiology 209:867–871

    PubMed  CAS  Google Scholar 

  11. 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 

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

    Article  PubMed  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  14. Ng QS, Goh V, Carnell D et al (2007) Tumor antivascular 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 

  15. Tateishi U, Kusumoto M, Nishihara H, Nagashima K, Morikawa T, Moriyama N (2002) Contrast enhanced dynamic computed tomography for the evaluation of angiogenesis in patients with lung carcinoma. Cancer 95:835–842

    Article  PubMed  Google Scholar 

  16. Wang JH, Min PQ, Wang PJ et al (2006) Dynamic CT evaluation of tumor vascularity in renal cell carcinoma. AJR Am J Roentgenol 186:1423–1430

    Article  PubMed  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  Google Scholar 

  19. Goh V, Halligan S, Hugill JA et al (2005) Quantitative colorectal cancer perfusion measurements using MDCT: inter and intra-observer agreement. AJR Am J Roentogenol 185:225–231

    Google Scholar 

  20. St Lawrence KS, Lee TY (1998) An adiabatic approximation to the tissue homogeneity model for water exchange in the brain: I. Theoretical derivation. J Cereb Blood Flow Metab 18:1365–1377

    Article  PubMed  CAS  Google Scholar 

  21. Moertel CG, Fleming TR, MacDonald JS et al (1990) Levamisole and fluorouracil for adjuvant therapy of resected colon carcinoma. N Engl J Med 322:352–358

    PubMed  CAS  Google Scholar 

  22. Andre T, Boni C, Mounedji-Boudiaf L et al (2004) Oxaliplatin, flurouracil and leucovorin as adjuvant treatment for colon cancer. N Engl J Med 350:2343–2351

    Article  PubMed  CAS  Google Scholar 

  23. Benson AB 3rd, Schrag D, Somerfield MR et al (2004) American Society of Clinical Oncology recommendations on adjuvant chemotherapy for stage II colon cancer. J Clin Oncol 22:3408–3419

    Article  PubMed  Google Scholar 

  24. Andre T, Sargent D, Tabernero J et al (2006) Current issues in adjuvant treatment of stage II colon cancer. Ann Surg Oncol 13:887–898

    Article  PubMed  Google Scholar 

  25. Efficacy of adjuvant flurouracil and folinic acid in B2 colon cancer (1999) International multicentre pooled analysis of B2 colon cancer trials (IMPACT B2) investigators. J Clin Oncol 17:1356–1363

    Google Scholar 

  26. Des Guetz G, Uzzan B, Nicolas P et al (2006) Microvessel density and VEGF expression are prognostic factors in colorectal cancer. Meta-analysis of the literature. Br J Cancer 94:1823–1832

    Article  PubMed  CAS  Google Scholar 

  27. Werther K, Christensen IJ, Brunner N et al (2000) Soluble vascular endothelial growth factor levels in patients with primary colorectal carcinoma. The Danish RANX05 Colorectal Cancer Study Group. Eur J Surg Oncol 26:657–662

    Article  PubMed  CAS  Google Scholar 

  28. Cascinu S, Staccioli MP, Gasparini G et al (2000) Expression of vascular endothelial growth factor can predict event-free survival in stage II colon cancer. Clin Cancer Res 6:2803–2807

    PubMed  CAS  Google Scholar 

  29. Vermeulen PB, Van den Eynden GG, Huget P et al (1999) Prospective study of intratumoral microvessel density, p53 expression, and survival in colorectal cancer. Br J Cancer 79:316–322

    Article  PubMed  CAS  Google Scholar 

  30. Furudoi A, Tanaka S, Haruma K et al (2002) Clinical significance of vascular endothelial growth factor C expression and angiogenesis at the deepest invasive site of advanced colorectal carcinoma. Oncology 62:157–166

    Article  PubMed  CAS  Google Scholar 

  31. Frank RE, Saclarides TJ, Leurgens S et al (1995) Tumor angiogenesis as predictor of recurrence and survival in patients with node negative colon cancer. Ann Surg 222:695–699

    Article  PubMed  CAS  Google Scholar 

  32. Graziano F, Cascinu S (2003) Prognostic molecular markers for planning adjuvant chemotherapy trials in Dukes’ B colorectal cancer patients: how much evidence is enough? Ann Oncol 14:1026–1038

    Article  PubMed  CAS  Google Scholar 

  33. Miles KA, Hayball M, Dixon AK (1991) Colour perfusion imaging: a new application of computed tomography. Lancet 337:643–645

    Article  PubMed  CAS  Google Scholar 

  34. Miles KA (1991) Measurement of tissue perfusion by dynamic computed tomography. Br J Radiol 64:409–412

    Article  PubMed  CAS  Google Scholar 

  35. Haider MA, Milosevic M, Fyles A et al (2005) Assessment of the tumor microenvironment in cervix cancer using dynamic contrast enhanced CT, interstitial fluid pressure and oxygen measurements. Int J Radiat Oncol Biol Phys 62:1100–1107

    PubMed  Google Scholar 

  36. Graeber TG, Osmanian C, Jacks T et al (1996) Hypoxia mediated selection of cells with diminished apoptotic potential in solid tumours. Nature 379:88–91

    Article  PubMed  CAS  Google Scholar 

  37. Reynolds TY, Rockwell S, Glazer PM (1996) Genetic instability induced by the tumor microenvironment. Cancer Res 56:5754–5757

    PubMed  CAS  Google Scholar 

  38. Hockel M, Schlenger K, Aral B et al (1996) Association between tumor hypoxia and malignant progression in advanced cancer of the uterine cervix. Cancer Res 56:4509–4515

    PubMed  CAS  Google Scholar 

  39. Sundfor K, Lyng H, Rofstad EK (1998) Tumour hypoxia and vascular density as predictors of metastasis in squamous cell carcinoma of the uterine cervix. Br J Cancer 78:822–827

    PubMed  CAS  Google Scholar 

  40. Brizel DM, Scully SP, Harrelson JM et al (1996) Tumor oxygenation predicts the likelihood of distant metastases in human soft tissue sarcoma. Cancer Res 56:941–943

    PubMed  CAS  Google Scholar 

  41. Hockel M, Vaupel P (2001) Tumor hypoxia: definitions, and current clinical, biological, and molecular aspects. J Natl Canc Inst 93:266–276

    Article  CAS  Google Scholar 

  42. Goethals L, Debucquoy A, Perneel C et al (2006) Hypoxia in human colorectal adenocarcinoma: comparison between extrinsic and potential intrinsic hypoxia markers. Int J Radiation Oncology Biol Phys 65:246–254

    CAS  Google Scholar 

  43. Shweiki D, Itin A, Soffer D et al (1992) Vascular endothelial growth factor induced by hypoxia may mediate hypoxia initiated angiogenesis. Nature 359:843–845

    Article  PubMed  CAS  Google Scholar 

  44. Yao K, Gietama JA, Shida S et al (2005) In vitro hypoxia-conditioned colon cancer cell lines derived from HCT116 and HT29 exhibit altered apoptosis susceptibility and a more angiogenic profile in vivo. Br J Cancer 93:1356–1363

    Article  PubMed  CAS  Google Scholar 

  45. 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 

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

    Article  PubMed  Google Scholar 

  47. Hermans R, Meijerink M, Van den Bogaert W et al (2003) Tumor perfusion rate determined noninvasively 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 

  48. Mooteri S, Rubin D, Leurgans S et al (1996) Tumor angiogenesis in primary and metastatic colorectal cancers. Dis Colon Rectum 39:1073–1080

    Article  PubMed  CAS  Google Scholar 

  49. Berney CR, Yang YL, Fisher RJ et al (1998) Vascular endothelial growth factor expression is reduced in liver metastasis from colorectal cancer and correlates with urokinase-type plasminogen activator. Anticancer Res 18:973–977

    PubMed  CAS  Google Scholar 

  50. De Lussanet QG, Backes WH, Griffioen AW et al (2005) Dynamic contrast-enhanced magnetic resonance imaging of radiation therapy-induced microcirculation changes in rectal cancer. Int J Radiat Oncol Biol 63:1309–1315

    Article  Google Scholar 

  51. DeVries AF, Griebel J, Kremser C et al (2001) Tumor microcirculation evaluated by dynamic contrast enhanced magnetic resonance imaging predicts therapy outcome for primary rectal carcinoma. Cancer Res 61:2513–2516

    PubMed  CAS  Google Scholar 

  52. De Vries A, Griebel J, Kremser C et al (2000) Monitoring of tumor microcirculation during fractionated radiation therapy in patients with rectal carcinoma: preliminary results and implications for therapy. Radiology 217:385–391

    PubMed  Google Scholar 

  53. Altman DG, Royston P (2000) What do we mean by validating a prognostic model? Stat Med 53:219–221

    Google Scholar 

  54. Goh V, Halligan S, Bartram CI (2007) Quantitative tumor perfusion assessment using MDCT: Are measurements from two different commercial software packages interchangeable? Radiology 242:777–782

    Article  PubMed  Google Scholar 

  55. Ng QS, Goh V, Fichte H et al (2006) Lung cancer perfusion at multidetector row CT: reproducibility of whole tumor quantitative measurements. Radiology 239:547–553

    Article  PubMed  Google Scholar 

  56. Ng QS, Goh V, Klotz E et al (2006) Quantitative assessment of lung cancer perfusion using MDCT:does measurement reproducibility improve with greater tumor volume coverage? AJR Am J Roentgenol 187:1079–1084

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank GE Healthcare Technologies (Waukesha, WI, USA) for providing the software for analysis. Authors retained control of all data collected, and information submitted for publication.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Steve Halligan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Goh, V., Halligan, S., Wellsted, D.M. et al. Can perfusion CT assessment of primary colorectal adenocarcinoma blood flow at staging predict for subsequent metastatic disease? A pilot study. Eur Radiol 19, 79–89 (2009). https://doi.org/10.1007/s00330-008-1128-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-008-1128-1

Keywords

Navigation