×
Home Current Archive Editorial board
News Contact
Review paper

Possibilities of differentiation of solitary focal liver lesions by computed tomography perfusion

By
Irmina Sefić Pašić ,
Irmina Sefić Pašić
Contact Irmina Sefić Pašić

Radiology Clinic, Clinical Center of University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Anes Pašić ,
Anes Pašić

Oncology Clinic, Clinical Center of Sarajevo University, Sarajevo, Bosnia and Herzegovina

Spomenka Kristić ,
Spomenka Kristić

Radiology Clinic, Clinical Center of University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Adnan Beganović ,
Adnan Beganović

Radiology Clinic, Clinical Center of University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Aladin Čarovac ,
Aladin Čarovac

Radiology Clinic, Clinical Center of University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Amra Dzananovic ,
Amra Dzananovic

Radiology Clinic, Clinical Center of University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Lidija Lincender ,
Lidija Lincender

Academy of Sciences and Arts of Bosnia and Herzegovina, Sarajevo, Bosnia and Herzegovina

Sandra Vegar Zubović
Sandra Vegar Zubović

Radiology Clinic, Clinical Center of University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Abstract

Aim
To evaluate possibilities of computed tomography (CT) perfusion in differentiation of solitary focal liver lesions based on
their characteristic vascularization through perfusion parameters analysis.
Methods
Prospective study was conducted on 50 patients in the period 2009-2012. Patients were divided in two groups: benign
and malignant lesions. The following CT perfusion parameters were analyzed: blood flow (BF), blood volume (BV), mean transit time (MTT), capillary permeability surface area product (PS), hepatic arterial fraction (HAF), and impulse residual function (IRF). During the study another perfusion parameter was analyzed: hepatic perfusion index (HPI). All patients were examined on Multidetector 64-slice CT machine (GE) with application of perfusion protocol for liver with i.v. administration of contrast agent.
Results
In both groups an increase of vascularization and arterial blood flow was noticed, but there was no significant statistical
difference between any of 6 analyzed parameters. Hepatic perfusion index values were increased in all lesions in comparison with normal liver parenchyma.
Conclusion
Computed tomography perfusion in our study did not allow differentiation of benign and malignant liver lesions based
on analysis of functional perfusion parameters. Hepatic perfusion index should be investigated in further studies as a parameter for detection of possible presence of micro-metastases in visually homogeneous liver in cases with no lesions found during standard CT protocol

References

1.
Leen E. The detection of occult liver metastases of colorectal carcinoma. J Hepatobiliary Pancreat Surg. 1999. p. 7–15.
2.
Seto S, Onodera H, Kaido T, Yoshikawa A, Ishigami S, Arii S, et al. Tissue factor expression in human colorectal carcinoma: correlation with hepatic metastasis and impact on prognosis. Cancer. 2000. p. 295–301.
3.
Kinkel K, Lu Y, Both M, Warren R, Thoeni R. Detection of hepatic metastases from cancers of the gastrointestinal tract by using noninvasive imaging methods (US, CT, MR imaging, PET): a meta-analysis. Radiology. 2002. p. 748–56.
4.
Miles K, Hayball M, Dixon A. Functional images of hepatic perfusion obtained with dynamic CT. Radiology. 1993. p. 405–11.
5.
Smith J, Sorensen A, Thrall J. Biomarkers in imaging: realizing radiology’s future. Radiology. 2003. p. 633–8.
6.
Miles K, Hayball M, Dixon A. Colour perfusion imaging : a new application of computed tomography. Lancet. 1993. p. 643–5.
7.
Ronot M, Asselah T, Paradis V, Michoux N, Dorvillius M, Baron G, et al. Liver fibrosis in chronic hepatitis C virus infections: differentiating minimal from intermediate fibrosis with perfusion CT. Radiology. 2010. p. 135–42.
8.
Sahani D, Holalhere N, Mueller P, Zhu A. Advanced hepatocellular carcinoma: CT perfusion of liver and tumor tissue-initial experience. Radiology. 2007. p. 736–43.
9.
Hayano K, Desai G, Kambadakone R, Fuentes J, Tanabe K, Sahani D. Quantitative characterisation of hepatocellular carcinoma and metastatic liver tumor by CT perfusion. Cancer Imaging. 2013. p. 512–9.
10.
Ippolito D, Capraro C, Casiraghi A, Cestari C, Sironi S. Quantitative assesment of tumour associated neovascularisation in patients with liver cirrhosis and hepatocellular carcinoma : role of dynamic-CT perfusion imaging. Eur Radiol. 2012. p. 803–11.
11.
Jiang T, Kambadakone A, Kuikarni N, Zhu A, Sahani D. Monitoring response to antiangiogenic treatment and predicting outcomes in advanced hepatocellular carcinoma using image biomarkers, CT perfusion, tumor density and tumor size (RECIST). Invest Radiol. 2012. p. 11–7.
12.
Miles K. Measurement of tissue perfusion by dynamic computed tomography. Br J Radiol. 1991. p. 409–12.
13.
Cuenod C, Leconte I, Siauve N, Resten A, Dromain C, Poulet B, et al. Early changes in liver perfusion caused by occult metastases in rats: detection with quantitative CT. Radiology. 2001. p. 556–61.
14.
Fournier L, Cuenod C, De Bazelaire C, Siauve N, Rosty C, Tran P. Early modifications of hepatic perfusion measured by functional CT in a rat model of hepatocellular carcinoma using a blood pool contrast agent. Eur Radiol. 2004. p. 2125–33.
15.
Materne R, Beers V, Smith B, Leconte A, Jamart I, Dehoux J, et al. Non-invasive quantification of liver perfusion with dynamic computed tomography and a dual-input onecompartmental model. Clin Sci (Lond). 2000. p. 517–25.
16.
Beers V, Leconte B, Materne I, Smith R, Jamart A, Horsmans J, et al. Hepatic perfusion parameters in chronic liver disease: dynamic CT measurements correlated with disease severity. AJR Am J Roentgenol. 2001. p. 667–73.
17.
Pari P, V, Glenn K, Rusinek A, H, Vivian L, et al. Perfusion imaging of the liver: current challenges and future goals. Radiology. 2005. p. 661–73.
18.
Dugdale P, Miles K. Hepatic metastases: the value of quantitative assessment of contrast enhancement on computed tomography. Eur J Radiol. 1999. p. 206–13.
19.
Miles K, Leggett D, Kelley B, Hayball M, Sinnatamby R, Bunce I. In vivo assessment of neovascularization of liver metastases using perfusion CT. Br J Radiol. 1998. p. 276–81.
20.
Miles K, Kelley B. Altered perfusion adjacent to hepatic metastases. Clin Radiol. 1997. p. 162–3.
21.
Blomley M, Coulden R, Dawson P. Liver perfusion studied with ultrafast CT. J Comput Assist Tomogr. 1995. p. 424–33.
22.
Kinkel K, Lu Y, Both M, Warren R, Thoeni R. Detection of hepatic metastases from cancers of the gastrointestinal tract by using noninvasive imaging methods (US, CT, MR imaging, PET): a meta-analysis. Radiology. 2002. p. 748–56.
23.
Semelka R, Sofka C. Hepatic hemangiomas. Magn Reson Imaging Clin N Am. 1997. p. 241–53.
24.
Smith J, Sorensen A, Thrall J. Biomarkers in imaging: realizing radiology’s future. Radiology. 2003. p. 633–8.
25.
Cuenod C, Leconte I, Siauve N, Frouin F, Dromain C, Clément O, et al. Deconvolution technique for measuring tissue perfusion by dynamic CT: application to normal and metastatic liver. Acad Radiol. 2002. p. 205–11.
26.
Kapanen M, Halavaara J, Hakkinen A. Assessment of vascular physiology of tumorous livers: comparison of two different methods. Acad Radiol. 2003. p. 1021–9.
27.
Kapanen M, Halavaara J, Hakkinen A. Open four-compartment model in the measurement of liver perfusion. Acad Radiol. 2005. p. 1542–50.
28.
Smith J, Sorensen A, Thrall J. Biomarkers in imaging: realizing radiology’s future. Radiology. 2003. p. 633–8.
29.
Jeffrey G, Hickey B, Hider P. Follow-up strategies for patients treated for non-metastatic colorectal cancer (Cochrane Review). The Cochrane Library. Issue. Update Software; 2003.
30.
Desch C, Benson Ab 3rd, Somerfield M, Flynn P, Krause C, Loprinzi C, et al. Colorectal cancer surveillance: 2005 update of an American Society of Clinical Oncology practice guideline. J Clin Oncol. 2005. p. 8512–9.
31.
Hayashi K, Tozaki M, Sugisaki M, Yoshida N, Fukuda K, Tanabe H. Dynamic multislice helical CT of ameloblastoma and odontogenic keratocyst: correlation between contrast enhancement and angiogenesis. J Comput Assist Tomogr. 2002. p. 922–6.
32.
Jinzaki M, Tanimoto A, Mukai M, Ikeda E, Kobayashi S, Yuasa Y, et al. Double-phase helical CT of small renal parenchymal neoplasms: correlation with pathologic findings and tumor angiogenesis. J Comput Assist Tomogr. 2000. p. 835–42.
33.
Wang Z, Li J, Lu G. Correlation of CT enhancement, tumor angiogenesis and pathologic grading of pancreatic carcinoma. World J Gastroenterol. 2003. p. 2100–4.
34.
Zhong L, Wang W, Xu J. Clinical application of hepatic CT perfusion. World J Gastroenterolol. 2009. p. 907–11.

Citation

Authors retain copyright. This work is licensed under a Creative Commons Attribution 4.0 International License. Creative Commons License

 

Article metrics

Google scholar: See link

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.