Computed Tomography (CT) Perfusion is an evolving method to visualize perfusion in organs and tissue. With the introduction of multidetector CT scanners, it is now possible to cover up to 16 cm in one rotation, and thereby making it possible to scan entire organs such as the liver with a fixed table position. Advances in reconstruction algorithms make it possible to reduce the radiation dose for each examination to acceptable levels. Regarding abdominal imaging, CT perfusion is still considered a research tool, but several studies have proven it as a reliable non-invasive technique for assessment of vascularity. CT perfusion has also been used for tumor characterization, staging of disease, response evaluation of newer drugs targeted towards angiogenesis and as a method for early detection of recurrence after radiation and embolization. There are several software solutions available on the market today based on different perfusion algorithms. However, there is no consensus on which protocol and algorithm to use for specific organs. In this article, the authors give an introduction to CT perfusion in abdominal imaging introducing technical aspects for calculation of perfusion parameters, and considerations on patient preparation. This article also contains clinical cases to illustrate the use of CT perfusion in abdominal imaging.
References
[1]
Kim, J.W.; Jeong, Y.Y.; Chang, N.K.; Heo, S.H.; Shin, S.S.; Lee, J.H.; Hur, Y.H.; Kang, H.K. Perfusion CT in colorectal cancer: Comparison of perfusion parameters with tumor grade and microvessel density. Korean J. Radiol. 2012, 13, S89–S97.
Petralia, G.; Bonello, L.; Viotti, S.; Preda, L.; D’ Andrea, G.; Bellomi, M. CT perfusion in oncology: How to do it. Cancer Imag. 2010, 10, 8–19.
[4]
Wintermark, M.; Flanders, A.E.; Velthuis, B.; Meuli, R.; van Leeuwen, M.; Goldsher, D.; Pineda, C.; Serena, J.; van der Schaaf, I.; Waaijer, A.; et al. Perfusion-CT assessment of infarct core and penumbra: Receiver operating characteristic curve analysis in 130 patients suspected of acute hemispheric stroke. Stroke 2006, 37, 979–985, doi:10.1161/01.STR.0000209238.61459.39.
[5]
Kambadakone, A.R.; Sahani, D.V. Body perfusion CT: Technique, clinical applications, and advances. Radiol. Clin. N. Am. 2009, 47, 161–178, doi:10.1016/j.rcl.2008.11.003.
[6]
Goh, V.; Liaw, J.; Bartram, C.I.; Halligan, S. Effect of temporal interval between scan acquisitions on quantitative vascular parameters in colorectal cancer: Implications for helical volumetric perfusion CT techniques. Am. J. Roentgenol. 2008, 191, W288–W292, doi:10.2214/AJR.07.3985.
[7]
Goh, V.; Dattani, M.; Farwell, J.; Shekhdar, J.; Tam, E.; Patel, S.; Juttla, J.; Simcock, I.; Stirling, J.; Mandeville, H.; et al. Radiation dose from volumetric helical perfusion CT of the thorax, abdomen or pelvis. Eur. Radiol. 2011, 21, 974–981, doi:10.1007/s00330-010-1997-y.
[8]
Gervaise, A.; Osemont, B.; Lecocq, S.; Noel, A.; Micard, E.; Felblinger, J.; Blum, A. CT image quality improvement using adaptive iterative dose reduction with wide-volume acquisition on 320-detector CT. Eur. Radiol. 2012, 22, 295–301, doi:10.1007/s00330-011-2271-7.
[9]
Hara, A.K.; Paden, R.G.; Silva, A.C.; Kujak, J.L.; Lawder, H.J.; Pavlicek, W. Iterative reconstruction technique for reducing body radiation dose at CT: Feasibility study. Am. J. Roentgenol. 2009, 193, 764–771, doi:10.2214/AJR.09.2397.
[10]
Negi, N.; Yoshikawa, T.; Ohno, Y.; Somiya, Y.; Sekitani, T.; Sugihara, N.; Koyama, H.; Kanda, T.; Kanata, N.; Murakami, T.; et al. Hepatic CT perfusion measurements: A feasibility study for radiation dose reduction using new image reconstruction method. Eur. J. Radiol. 2012, 81, 3048–3054, doi:10.1016/j.ejrad.2012.04.024.
[11]
Miles, K.A. Tumour angiogenesis and its relation to contrast enhancement on computed tomography: A review. Eur. J. Radiol. 1999, 30, 198–205, doi:10.1016/S0720-048X(99)00012-1.
[12]
Tsuji, Y.; Takahashi, N.; Tsutomu, C. Pancreatic perfusion CT in early stage of severe acute pancreatitis. Int. J. Inflamm. 2012, 2012, doi:10.1155/2012/497386.
[13]
Miles, K.A. Perfusion CT for the assessment of tumour vascularity: Which protocol? Br. J. Radiol. 2003, 76, S36–S42, doi:10.1259/bjr/18486642.
[14]
Stewart, E.E.; Chen, X.; Hadway, J.; Lee, T.-Y. Hepatic perfusion in a tumor model using DCE-CT: An accuracy and precision study. Phys. Med. Biol. 2008, 53, 4249–4267, doi:10.1088/0031-9155/53/16/003.
[15]
Miles, K.A.; Hayball, M.P.; Dixon, A.K. Functional images of hepatic perfusion obtained with dynamic CT. Radiology 1993, 188, 405–411.
[16]
Cenic, A.; Nabavi, D.G.; Craen, R.A.; Gelb, A.W.; Lee, T.-Y. Dynamic CT measurement of cerebral blood flow: A validation study. Am. J. Neuroradiol. 1999, 20, 63–73.
[17]
Nabavi, D.G.; Cenic, A.; Dool, J.; Smith, R.M.; Espinosa, F.; Craen, R.A.; Gelb, A.W.; Lee, T.Y. Quantitative assessment of cerebral hemodynamics using CT: Stability, accuracy, and precision studies in dogs. J. Comput. Assist. Tomogr. 1999, 23, 506–515, doi:10.1097/00004728-199907000-00003.
[18]
Grüner, J.M.; Paamand, R.; H？jgaard, L.; Law, I. Brain perfusion CT compared with 15O-H2O-PET in healthy subjects. EJNMMI Res. 2011, 1, 1691–1701.
[19]
Miles, K.A.; Griffiths, M.R. Perfusion CT: A worthwhile enhancement? Br. J. Radiol. 2003, 76, 220–231, doi:10.1259/bjr/13564625.
[20]
Miles, K.A. Measurement of tissue perfusion by dynamic computed tomography. Br. J. Radiol. 1991, 64, 409–412, doi:10.1259/0007-1285-64-761-409.
[21]
Miles, K.A. Tumour angiogenesis and its relation to contrast enhancement on computed tomography: A review. Eur. J. Radiol. 1999, 30, 198–205, doi:10.1016/S0720-048X(99)00012-1.
[22]
Fieselmann, A.; Kowarschik, M.; Ganguly, A.; Hornegger, J.; Fahrig, R. Deconvolution-based CT and MR brain perfusion measurement: Theoretical model revisited and practical implementation details. Int. J. Biomed. Imag. 2011, 2011, doi:10.1155/2011/467563.
[23]
Kandel, S.; Meyer, H.; Hein, P.; Lembcke, A.; Rueckert, J.-C.; Rogalla, P. Comparison of free breathing versus breath-hold in perfusion imaging using dynamic volume CT. Insights Imag. 2012, 3, 323–328, doi:10.1007/s13244-012-0169-9.
[24]
Bellomi, M.; Petralia, G.; Sonzogni, A.; Zampino, M.G.; Rocca, A. CT perfusion for the monitoring of neoadjuvant chemotherapy and radiation therapy in rectal carcinoma: Initial experience. Radiology 2007, 244, 486–493, doi:10.1148/radiol.2442061189.
[25]
Petralia, G.; Bonello, L.; Viotti, S.; Preda, L.; D’ Andrea, G.; Bellomi, M. CT perfusion in oncology: How to do it. Canc. Imag. 2010, 10, 8–19.
[26]
Kandel, S.; Kloeters, C.; Meyer, H.; Hein, P.; Hilbig, A.; Rogalla, P. Whole-organ perfusion of the pancreas using dynamic volume CT in patients with primary pancreas carcinoma: Acquisition technique, post-processing and initial results. Eur. Radiol. 2009, 19, 2641–2646, doi:10.1007/s00330-009-1453-z.
[27]
Fiorella, D.; Heiserman, J.; Prenger, E.; Partovi, S. Assessment of the reproducibility of postprocessing dynamic CT perfusion data. Am. J. Neuroradiol. 2004, 25, 97–107.
[28]
Sanelli, P.C.; Lev, M.H.; Eastwood, J.D.; Gonzalez, R.G.; Lee, T.Y. The effect of varying user-selected input parameters on quantitative values in CT perfusion maps1. Acad. Radiol. 2004, 11, 1085–1092, doi:10.1016/j.acra.2004.07.002.
[29]
Ng, C.S.; Chandler, A.G.; Wei, W.; Herron, D.H.; Anderson, E.F.; Kurzrock, R.; Charnsangavej, C. Reproducibility of CT perfusion parameters in liver tumors and normal liver. Radiology 2011, 260, 762–770, doi:10.1148/radiol.11110331.
[30]
Goh, V.; Halligan, S.; Hugill, J.-A.; Bassett, P.; Bartram, C.I. Quantitative assessment of colorectal cancer perfusion using MDCT: Inter- and intraobserver agreement. Am. J. Roentgenol. 2005, 185, 225–231, doi:10.2214/ajr.185.1.01850225.
[31]
Goh, V.; Halligan, S.; Gharpuray, A.; Wellsted, D.; Sundin, J.; Bartram, C.I. Quantitative assessment of colorectal cancer tumor vascular parameters by using perfusion CT: Influence of tumor region of interest1. Radiology 2008, 247, 726–732, doi:10.1148/radiol.2473070414.
[32]
Yao, J.; Yang, Z.-G.; Chen, H.-J.; Chen, T.-W.; Huang, J. Gastric adenocarcinoma: Can perfusion CT help to noninvasively evaluate tumor angiogenesis? Abdom. Imag. 2011, 36, 15–21, doi:10.1007/s00261-010-9609-5.
Satoh, A.; Shuto, K.; Okazumi, S.; Ohira, G.; Natsume, T.; Hayano, K.; Narushima, K.; Saito, H.; Ohta, T.; Nabeya, Y.; et al. Role of Perfusion CT in assessing tumor blood flow and malignancy level of gastric cancer. Dig. Surg. 2010, 27, 253–260, doi:10.1159/000288703.
[35]
Li, Z.-P.; Meng, Q.-F.; Sun, C.-H.; Xu, D.-S.; Fan, M.; Yang, X.-F.; Chen, D.-Y. Tumor angiogenesis and dynamic CT in colorectal carcinoma: Radiologic-pathologic correlation. World J. Gastroenterol. 2005, 11, 1287–1291.
[36]
Goh, V.; Halligan, S.; Wellsted, D.M.; Bartram, C.I. Can perfusion CT assessment of primary colorectal adenocarcinoma blood flow at staging predict for subsequent metastatic disease? A pilot study. Eur. Radiol. 2009, 19, 79–89, doi:10.1007/s00330-008-1128-1.
[37]
Cao, Y. The promise of dynamic contrast-enhanced imaging in radiation therapy. Semin. Radiat. Oncol. 2011, 21, 147–156, doi:10.1016/j.semradonc.2010.11.001.
[38]
Kanda, T.; Yoshikawa, T.; Ohno, Y.; Kanata, N.; Koyama, H.; Takenaka, D.; Sugimura, K. CT hepatic perfusion measurement: Comparison of three analytic methods. Eur. J. Radiol. 2012, 81, 2075–2079, doi:10.1016/j.ejrad.2011.07.003.
[39]
Miles, K.A.; Hayball, M.P.; Dixon, A.K. Functional images of hepatic perfusion obtained with dynamic CT. Radiology 1993, 188, 405–411.
[40]
Blomley, M.J.; Coulden, R.; Dawson, P.; Kormano, M.; Donlan, P.; Bufkin, C.; Lipton, M.J. Liver perfusion studied with ultrafast CT. J. Comput. Assist. Tomogr. 1995, 19, 424–433, doi:10.1097/00004728-199505000-00016.
[41]
Ippolito, D.; Bonaffini, P.A.; Ratti, L.; Antolini, L.; Corso, R.; Fazio, F.; Sironi, S. Hepatocellular carcinoma treated with transarterial chemoembolization: Dynamic perfusion-CT in the assessment of residual tumor. World J. Gastroenterol. 2010, 16, 5993–6000.
[42]
Delrue, L.; Blanckaert, P.; Mertens, D.; Cesmeli, E.; Ceelen, W.P.; Duyck, P. Assessment of tumor vascularization in pancreatic adenocarcinoma using 128-slice perfusion computed tomography imaging. J. Comput. Assist. Tomogr. 2011, 35, 434–438, doi:10.1097/RCT.0b013e318223f0c5.
