Comparison of maximum slope and deconvolution algorithms on perfusion parameters in pancreatic CT perfusion

PAN Ke-hua; CAO Guo-quan; SUN Hou-chang; CHEN Xiao; LIN Xiao-min

Journal of China Clinic Medical Imaging ›› 2018, Vol. 29 ›› Issue (1) : 23-27.

PAN Ke-hua, CAO Guo-quan, SUN Hou-chang, CHEN Xiao, LIN Xiao-min

Author information +

History +

Abstract

Objective: To investigate the effects of maximum slope(MS) and deconvolution(DC) approach on perfusion parameters in pancreatic CT perfusion. Methods: The data of 57 patients who underwent pancreatic CT perfusion examination by 320-slice CT with good image quality were retrospectively analyzed using MS and DC algorithms respectively. Images were illustrated by two certified radiologists using double blind method and perfusion parameters including blood flow(BF), blood volume(BV) were obtained in 30 cases of normal pancreatic heads, bodies and tails(including 90 ROIs) and 27 cases of acute pancreatitis with interstitial edema(including 81 ROIs). The intraclass correlation coefficient(ICC) was used to assess the reproducibility between two radiologists and paired t test was used to evaluate the differences of CT perfusion parameters between the two algorithms. Pearson linear correlation analysis and Bland-Altman analysis were used to estimate the correlation and consistency of the CT perfusion parameters between the two algorithms. Results: There was good agreement(ICC≥0.9) between the two radiologists. There were no significant differences in BF or BV in different regions of the pancreas in either normal pancreas or acute pancreatitis through the same algorithm(P>0.05). In comparison with corresponding values obtained from DC algorithm, the values of pancreatic BV and BF obtained from MS algorithm were higher(P<0.05) in both normal pancreatic body and acute pancreatitis. In addition, there was a significant positive but inconsistent correlation between BF and BV values of different pancreatic regions in both normal pancreas and acute pancreatitis with interstitial edema through the same algorithm(r>0.9, P<0.01). Conclusions: Perfusion parameters obtained from MS and DC algorithms show good, but inconsistent correlation. Thus, the data cannot be used interchangeably between algorithms.

Key words

Pancreatic diseases / Pancreatic neoplasms / Tomography, spiral computed

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

PAN Ke-hua, CAO Guo-quan, SUN Hou-chang, CHEN Xiao, LIN Xiao-min. Comparison of maximum slope and deconvolution algorithms on perfusion parameters in pancreatic CT perfusion[J]. Journal of China Clinic Medical Imaging. 2018, 29(1): 23-27

References

[1]Miles KA, Hayball MP, Dixon AK. Measurement of human pancreatic perfusion using dynamic computed tomography with perfusion imaging[J]. Br J Radiol, 1995, 68(809): 471-475.
[2]Tsuji Y, Yamamoto H, Yazumi S, et al. Perfusion computerized tomography can predict pancreatic necrosis in early stages of severe acute pancreatitis[J]. Clin Gastroenterol Hepatol, 2007, 5(12): 1484-1492.
[3]Abo H, Murakami T, Kubota M, et al. Quantitative tissue blood flow evaluation of pancreatic tumor: comparison between xenon CT technique based on deconvolution analysis[J]. Radiat Med, 2005, 23(5): 364-370.
[4]Arikawa S, Uchida M, Kunou Y, et al. Assessment of Chronic Pancreatitis: Use of Whole Pancreas Perfusion With 256-Slice Computed Tomography[J]. Pancreas, 2012, 41(4): 535-540.
[5]Bize PE, Alexandra P, Becker CD, et al. Perfusion measurement in acute pancreatitis using dynamic perfusion MDCT[J]. AJR, 2006, 186(1): 114-118.
[6]Xie Q, Wu J, Tang Y, et al. Whole-Organ CT Perfusion of the Pancreas: Impact of Iterative Reconstruction on Image Quality, Perfusion Parameters and Radiation Dose in 256-Slice CT-Preliminary Findings [J]. PLoS One, 2013, 8(11): e80468.
[7]Whitcomb DC. Clinical practice. Acute pancreatitis [J]. New Engl J Med, 2006, 354(20): 2142-2150.
[8]Goh V, Halligan S, Bartram CI, et al. Quantitative tumor perfusion assessment with multidetector CT: are measurements from two commercial software packages Interchangeable?[J]. Radiology, 2007, 242(3): 777-782.
[9]Cenic A, Nabavi DG, Craen RA, et al. Dynamic CT measurement of cerebral blood flow: a validation study[J]. Am J Neuroradiol, 1999, 20(1): 63-73.
[10]Miyazaki M, Tsushima Y, Miyazaki A, et al. Quantification of hepatic arterial and portal perfusion with dynamic computed tomography: comparison of maximum-slope and dual-input one-compartment model methods[J]. Jpn J Radiol, 2009, 27(3): 143-150.
[11]Tomonori K, Takeshi Y, Yoshiharu O, et al. CT hepatic perfusion measurement: comparison of three analytic methods[J]. Eur J Radiol, 2012, 81(9): 2075-2079.
[12]Zhu L, Xue HD, He Y, et al. Low-dose whole-organ CT perfusion of the pancreas: comparison of regional blood flow in MEN1, sporadic endocrine tumour and tumour-free patients[J]. Annales De Géographie, 1962, 71(8): 39-47.
[13]Delrue L, Blanckaert P, Mertens D, et al. Assessment of Tumor Vascularization in Pancreatic Adenocarcinoma Using 128-Slice Perfusion Computed Tomography Imaging[J]. J Comput Assist Tomogr, 2011, 35(4): 434-438.
[14]Kishimoto M, Tsuji Y, Katabami N, et al. Measurement of canine pancreatic perfusion using dynamic computed tomography: influence of input-output vessels on deconvolution and maximum slope methods[J]. Eur J Radiol, 2011, 77(1): 175-181.