Title: Role of Perfusion Computed Tomography in the Characterization of Lung Cancers

Authors: Dr Aniket Mondal, Dr Gaurav Pradhan, Dr Alpana Manchanda, Dr Anju Garg, Dr M.K Daga, Dr Shyam Lata Jain

 DOI:  https://dx.doi.org/10.18535/jmscr/v6i7.114

Abstract

Purpose: Aim of our study is the evaluation of CT perfusion parameters in lung cancers according to their histopatholgical subtypes, size, location and necrosis.

Method and Materials: We performed CT perfusion in 28 patients of lung cancers on 128 slice CT scanners and calculated blood flow (BF), blood volume (BV), permeability (PMB) and mean transit time (MTT).

Statistical Analysis: Depending on the distribution of data, unpaired t-test and Mann Whitney U test were used to compare CT perfusion parameters of lung cancers. P value <0.05 was accepted statistically significant.

Results: Histology revealed squamous cell cancer (SCC) in 16 patients, adenocarcinoma (Adeno) in 10 patients and small cell lung cancer (SCLC) in 2 patients. We found that BF and PMB were significantly higher in Adenocarinoma than SCC (p <0.05). BV and MTT were not significantly differ according to lung cancer subtypes (p>0.05). Tumour of less than 3 cm in size showed significantly higher BF and PMB than tumour size greater than 3 cm (p<0.05). CT perfusion parameters were not significantly differ according lung cancer location (central versus peripheral and upper lobe versus lower lobe). BF, PMB and MTT were found significantly different between non-necrotic tumour and necrotic tumour (p<0.05).

Conclusions: In conclusion, CT perfusion parameters of lung cancer using 128-multi-detector row CT could reflects the underlying extent of tumour angiogenesis in relation to lung cancer subtypes, size and necrosis.

Keywords: Lung cancer, perfusion CT, Tumour angiogenesis.

References

  1. Jermal A, Siegel R, Ward E, Hao Y, Xu J, Murray T, et al. Cancer statistics,2008. CA Cancer J Clin 2008;58(2): 71-96.
  2. Sandler A, Gray R, Perry MC, et al. Paclitaxel-carboplatin alone or with bevacizumab for non-small-cell lung cancer. N Engl J Med 2006; 355:2542–2550.
  3. Holash J, Maisonpierre PC, Compton D, et al. Vessel cooption, regres­sion, and growth in tumors mediated by angiopoietins and VEGF. Science. 1999;284:1994–1998.
  4. Veikkola T, Karkkainen M, Claesson-Welsh L, Alitalo K. Regulation of angiogenesis via vascular endothelial growth factor receptors. Cancer Res. 2000;60:2203–2212.
  5. Miles KA. Perfusion CT for the assessment of tumor vascularity: which protocol? Br J Radiol 2003; 76:S36-42.
  6. Kiessling F, Boese J, Corvinus C, Ederle JR, Zuna I, Schoenberg SO, et al. Perfusion CT in patients with advanced bronchial carcinomas: a novel chance for characterization and treatment monitoring? Eur Radiol 2004; 14: 1226-1233.
  7. Tateishi U, Kusumoto M, Nishihara H, Nagashima K, Morikawa T, Moriyama Noriyuki. Contrast-enhanced dynamic computed tomography for the evaluation of tumor angiogenesis in patients with lung carcinoma. Cancer 2002; 95:835-42.
  8. Shi J, Schmid-Bindert G, Fink C, Apfaltrer P, Pilz LR, et al. Dynamic volume perfusion CT in patients with lung cancer: Baseline perfusion characteristics of different histological subtypes. Eur J Radiol 2013 Sep 11.
  9. Spira D, Neumeister H, Spira SM, Hetzel J, Spengler W, Von Weyhern CH, et al. Assessment of tumor vascularity in lung cancer using volume perfusion CT (VPCT) with histopathologic comparison: a further step toward an individualized tumor characterization. J Comput Assist Tomogr 2013 Jan-Feb;37(1):15-21.
  10. O Yildrim, T Baysal, M R Cellik. The evaluation of MDCT and quantitative first-pass perfusion in lung cancers. Eur Rev Med Pharmacol Sci 2013;17:2390-95.
  11. Huellner MW, Collen TD, Gut P, Winterhalder R, Pauli C, Diebold J, et al. Multiparametric PET/CT-perfusion does not add significant additional information for initial staging in lung cancer compared with standard PET/CT. EJNMMI Res 2014 Jan 22;4(1):6.
  12. Ovali GY, Sakar A, Goktan C, Celik P, Yorgancioglu A, Nese N, Pabuscu Y. Thorax perfusion CT in non-small cell lung cancer. Comput Med Imaging Graph 2007; 31:686-91.
  13. Goh V, Halligan S, Bartram C. Quantitative tumor perfusion assessment with multidetector CT: Are measurements from two commercial software packages interchangeable? Radiology 2007;241(3): 277-82.
  14. Ippolito D, Capraro C, Guerra L, De Ponti E, Messa C, Sironi S. Feasibility of perfusion CT technique integrated into conventional 18 FDG/PET-CT studies in lung cancer patients: Clinical staging and functional information ina single study. Eur J Nucl Med Mol Imaging 2013 Jan;40(2):156-65.
  15. Li Y, Yang ZG, Chen TW, Deng YP, Yu JQ, Li ZI. Whole tumor perfusion of peripheral lung carcinoma: evaluation with first-pass CT perfusion imaging at 64-detector row CT. Clinical Radiology 2008; 63:629-35.
  16. Ketelsen D, Horger M, Buchgeister M, Fenchel M, Thomas C, Boehringer N, et al. Estimation of radiation exposure of 128-slice 4D perfusion CT for the assessment of tumor vascularity. Korean J Radiol 2010 Sep-Oct; 11(5):547-52.

Corresponding Author

Dr Aniket Mondal, MD, DNB (Radiodiagnosis)

Senior Resident, Department of Radiodiagnosis, Maulana Azad Medical College, New Delhi -110002, India

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