期刊论文详细信息
BMC Research Notes
Robustness to noise of arterial blood flow estimation methods in CT perfusion
Mario Cesarelli2  Francesco Fiore1  Paolo Bifulco2  Michela D’Antò1  Maria Romano2 
[1] National Cancer Institute “Pascale Foundation”, Naples, Italy;Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Rome, Italy
关键词: Noise robustness;    Dual-input one-compartment model;    Maximum slope method;    Liver perfusion;    Computed tomography (CT);   
Others  :  1130423
DOI  :  10.1186/1756-0500-7-540
 received in 2014-07-27, accepted in 2014-08-01,  发布年份 2014
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【 摘 要 】

Background

Perfusion CT is a technology which allows functional evaluation of tissue vascularity. Due to this potential, it is finding increasing utility in oncology. Although since its introduction continuous advances have interested CT technique, some issues have to be still defined, concerning both clinical and technical aspects. In this study, we dealt with the comparison of two widely employed mathematical models (dual input one compartment model – DOCM - and maximum slope – SM -) analyzing their robustness to the noise.

Methods

We carried out a computer simulation process to quantify effect of noise on the evaluation of an important perfusion parameter (Arterial Blood Flow – BFa) in liver tumours. A total of 4500 liver TAC, corresponding to 3 fixed BFa values, were simulated using different arterial and portal TAC (computed from 5 real CT images) at 10 values of signal to noise ratio (SNR). BFa values were calculated by applying four different algorithms, specifically developed, to these noisy simulated curves. Three algorithms were developed to implement SM (one semiautomatic, one automatic and one automatic with filtering) and the last for the DOCM method.

Results

In all the simulations, DOCM provided the best results, i.e., those with the lowest percentage error compared to the reference value of BFa. Concerning SM, the results are variable. Results obtained with the automatic algorithm with filtering are close to the reference value, but only if SNR is higher than 50. Vice versa, results obtained by means of the semiautomatic algorithm gave, in all simulations, the lowest results with the lowest standard deviation of the percentage error.

Conclusions

Since the use of DOCM is limited by the necessity that portal vein is visible in CT scans, significant restriction for patients’ follow-up, we concluded that SM can be reliably employed. However, a proper software has to be used and an estimation of SNR would be carried out.

【 授权许可】

   
2014 Romano et al.; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]Murase K, Miyazaki S, Yang X: An efficient method for calculating kinetic parameters in a dual-input single-compartment model. Br J Radiol 2007, 80(953):371-375.
  • [2]Materne R, Van Beers BE, Smith AM, Leconte I, Jamart J, Dehoux JP, Keyeux A, Horsmans Y: Non-invasive quantification of liver perfusion with dynamic computed tomography and a dual-input one-compartmental model. Clin Sci (Lond) 2000, 99(6):517-525.
  • [3]Miles KA: Perfusion CT for the assessment of tumour vascularity: which protocol? Br J Radiol 2003, 76:S36-S42.
  • [4]Miles KA: Functional computed tomography in Oncology. Eur J Cancer 2002, 38(16):2079-2084.
  • [5]Miles KA, Griffiths MR: Perfusion CT: a worthwhile enhancement? Br J Radiol 2003, 76:220-231.
  • [6]D’Antò M, Cesarelli M, Fiore F, Romano M, Bifulco P: Sources of variability in the use of standardized perfusion value for HCC studies. OJMI 2012, 2(2):33-40.
  • [7]Bae KT: Intravenous contrast medium administration and scan timing at CT: considerations and approaches. Radiology 2010, 256(1):32-61.
  • [8]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. Elsevier Ireland Ltd
  • [9]Dushyant Sahani V: Perfusion CT: An Overview of Technique And Clinical Applications. Proc Intl Soc Mag Reson Med 2010., 18
  • [10]Miles KA, Hayball MP, Dixon AK: Functional images of hepatic perfusion obtained with dynamic CT. Radiology 1993, 188(2):405-411.
  • [11]Miyazaki M, Tsushima Y, Miyazaki A, Paudyal B, Amanuma M, Endo K: Quantification of hepatic arterial and portal perfusion with dynamic computed tomography: comparison of maximum-slope and dual-input one-compartment model methods. Jpn J Radiol 2009, 27:143-150.
  • [12]Cuenod CA, Leconte I, Siauve N, Frouin F, Dromain C, Clément O, Frija G: Deconvolution technique for measuring tissue perfusion by dynamic CT: application to normal and metastatic liver. Acad Radiol 2002, 9(Suppl 1):S205-S211.
  • [13]Miyazaki S, Murase K, Yoshikawa T, Morimoto S, Ohno Y, Sugimura K: A quantitative method for estimating hepatic blood flow using a dual-input single-compartment model. Br J Radiol 2008, 81(970):790-800.
  • [14]Kim KW, Lee JM, Klotz E, Park HS, Lee DH, Kim JY, Kim SJ, Kim SH, Lee JY, Han JK, Choi BI: Quantitative CT color mapping of the arterial enhancement fraction of the liver to detect hepatocellular carcinoma. Radiology 2009, 250(2):425-434.
  • [15]Tsushima Y, Blomley MJK, Kusano S, Endo K: Measuring portal venous perfusion with contrast-enhanced CT: comparison of direct and indirect methods. Acad Radiol 2002, 9:276-282.
  • [16]Ruan C, Yang S, Clarke GD, Amurao MR, Partyka SR, Bradley YC, Cusi K: First-pass contrast-enhanced myocardial perfusion MRI using a maximum up-slope parametric map. IEEE Trans Inf Technol Biomed 2006, 10(3):574-580.
  • [17]Bader TR, Grabenwöger F, Prokesch RW, Krause W: Measurement of hepatic perfusion with dynamic computed tomography: assessment of normal values and comparison of two methods to compensate for motion artifacts. Invest Radiol 2000, 35(9):539-547.
  • [18]D’Antò M, Cesarelli M, Bifulco P, Romano M, Cerciello V, Fiore F, Vecchione A: Study of different Time Attenuation Curve processing in Liver CT Perfusion. In 10th IEEE International Conference on Information Technology and Applications in Biomedicine. Corfu, Greece: paper N; 2010:101.
  • [19]Van Beers BE, Leconte I, Materne R, Smith AM, Jamart J, Horsmans Y: Hepatic perfusion parameters in chronic liver disease: dynamic CT measurements correlated with disease severity. Am J Roentgenol 2001, 176(3):667-673.
  • [20]Cesarelli M, Bifulco P, Cerciello T, Romano M, Paura L: X-ray fluoroscopy noise in modeling for filter design. Int J Comput Assist Radiol Surg 2012, 2012:1-10.
  • [21]Presidente A, Romano M, D’Angelo R, Ronza FM, Cesarelli M, Fiore F, D’Antò M: A new procedure to obtain Standardized Perfusion Value to assess HCC vascularization: early clinical experience. Vienna: European Congress of Radiology; 2011.
  • [22]D’Antò M, Cesarelli M, Bifulco P, Romano M, Fiore F, Cerciello V, Cerciello T: Perfusion CT of the liver: slope method analysis. In II Congresso Nazionale di Bioingegneria. Torino. Atti Pàtron editore; 2010:467-468. 8–10 luglio
  • [23]Tsushima Y, Funabasama S, Sanada S, Aoki J, Endo K: Development of perfusion CT software for personal computers. Acad Radiol 2002, 9(8):922-926.
  • [24]Pandharipande PV, Krinsky GA, Rusinek H, Lee V: Perfusion imaging of the liver: current challenges and future goals. Radiology 2005, 234:661-673.
  • [25]Kamel IR, Liapi E, Fishman EK: Multidetector CT of Hepatocellular Carcinoma. Best Pract Res Clin Gastroenterol 2005, 19(1):63-89.
  • [26]Sansone M, Cesarelli M, Pepino A, Bifulco P, Romano M, De Rimini ML, Muto P: Assessment of Standardised Uptake Values in PET Imaging Using Different Software Packages. J Med Imaging Radiat Sc 2013, 44(4):188-196. in press
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