View Item 

Show simple item record

Correction of arterial input function in dynamic contrast‐enhanced MRI of the liver
dc.contributor.authorWang, Heshengen_US
dc.contributor.authorCao, Yueen_US
dc.date.accessioned2012-08-09T14:55:00Z
dc.date.available2013-10-01T17:06:31Zen_US
dc.date.issued2012-08en_US
dc.identifier.citationWang, Hesheng; Cao, Yue (2012). "Correction of arterial input function in dynamic contrast‐enhanced MRI of the liver." Journal of Magnetic Resonance Imaging 36(2): 411-421. <http://hdl.handle.net/2027.42/92374>en_US
dc.identifier.issn1053-1807en_US
dc.identifier.issn1522-2586en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/92374
dc.description.abstractPurpose: To develop a postprocessing method to correct saturation of arterial input function (AIF) in T1‐weighted dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) for quantification of hepatic perfusion. Materials and Methods: The saturated AIF is corrected by parameterizing the first pass of the AIF as a smooth function with a single peak and minimizing a least‐squares error in fitting the liver DCE‐MRI data to a dual‐input single‐compartment model. Sensitivities of the method to the degree of saturation in the AIF first‐pass peak and the image contrast‐to‐noise ratio were assessed. The method was also evaluated by correlating portal venous perfusion with an independent overall liver function measurement. Results: The proposed method corrects the distorted AIF with a saturation ratio up to 0.45. The corrected AIF improved hepatic arterial perfusion by −23.4% and portal venous perfusion by 26.9% in a study of 12 patients with liver cancers. The correlation between the mean voxelwise portal venous perfusion and overall liver function measurement was improved by using the corrected AIFs (R 2 = 0.67) compared with the saturated AIFs (R 2 = 0.39). Conclusion: The method is robust for correcting AIF distortion and has the potential to improve quantification of hepatic perfusion for assessment of liver tissue response to treatment in patients with hepatic cancers. J. Magn. Reson. Imaging 2012;36:411–421. © 2012 Wiley Periodicals, Inc.en_US
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.subject.otherAIF Saturationen_US
dc.subject.otherCorrectionen_US
dc.subject.otherLiveren_US
dc.subject.otherDual‐Input Single Compartment Modelen_US
dc.subject.otherDCE‐MRIen_US
dc.titleCorrection of arterial input function in dynamic contrast‐enhanced MRI of the liveren_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMedicine (General)en_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Radiology, University of Michigan, Ann Arbor, Michigan, USAen_US
dc.contributor.affiliationumDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USAen_US
dc.contributor.affiliationotherArgus 1 Building, 519 W. William St., Ann Arbor, MI, 48103en_US
dc.identifier.pmid22392876en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/92374/1/23636_ftp.pdf
dc.identifier.doi10.1002/jmri.23636en_US
dc.identifier.sourceJournal of Magnetic Resonance Imagingen_US
dc.identifier.citedreferenceYang C, Karczmar GS, Medved M, Stadler WM. Multiple reference tissue method for contrast agent arterial input function estimation. Magn Reson Med 2007; 58: 1266 – 1275.en_US
dc.identifier.citedreferenceBrunecker P, Villringer A, Schultze J, et al. Correcting saturation effects of the arterial input function in dynamic susceptibility contrast‐enhanced MRI: a Monte Carlo simulation. Magn Reson Imaging 2007; 25: 1300 – 1311.en_US
dc.identifier.citedreferenceArfken G. Gram‐Schmidt orthogonalization. Orlando, FL: Academic Press; 1985.en_US
dc.identifier.citedreferenceCao Y, Alspaugh J, Shen Z, Balter JM, Lawrence TS, Ten Haken RK. A practical approach for quantitative estimates of voxel‐by‐voxel liver perfusion using DCE imaging and a compartmental model. Med Phys 2006; 33: 3057 – 3062.en_US
dc.identifier.citedreferenceCao Y, Platt JF, Francis IR, et al. The prediction of radiation‐induced liver dysfunction using a local dose and regional venous perfusion model. Med Phys 2007; 34: 604 – 612.en_US
dc.identifier.citedreferenceYorke ED, Kutcher GJ, Jackson A, Ling CC. Probability of radiation‐induced complications in normal tissues with parallel architecture under conditions of uniform whole or partial organ irradiation. Radiother Oncol 1993; 26: 226 – 237.en_US
dc.identifier.citedreferenceWithers HR, Taylor JM, Maciejewski B. Treatment volume and tissue tolerance. Int J Radiat Oncol Biol Phys 1988; 14: 751 – 759.en_US
dc.identifier.citedreferenceJackson A, Ten Haken RK, Robertson JM, Kessler ML, Kutcher GJ, Lawrence TS. Analysis of clinical complication data for radiation hepatitis using a parallel architecture model. Int J Radiat Oncol Biol Phys 1995; 31: 883 – 891.en_US
dc.identifier.citedreferenceJackson A, Kutcher GJ, Yorke ED. Probability of radiation‐induced complications for normal tissues with parallel architecture subject to non‐uniform irradiation. Med Phys 1993; 20: 613 – 625.en_US
dc.identifier.citedreferenceShukla‐Dave A, Lee N, Stambuk H, et al. Average arterial input function for quantitative dynamic contrast enhanced magnetic resonance imaging of neck nodal metastases. BMC Med Phys 2009; 9: 4.en_US
dc.identifier.citedreferenceAhearn TS, Staff RT, Redpath TW, Semple SI. The effects of renal variation upon measurements of perfusion and leakage volume in breast tumours. Phys Med Biol 2004; 49: 2041 – 2051.en_US
dc.identifier.citedreferenceMeng R, Chang SD, Jones EC, Goldenberg SL, Kozlowski P. Comparison between population average and experimentally measured arterial input function in predicting biopsy results in prostate cancer. Acad Radiol 2010; 17: 520 – 525.en_US
dc.identifier.citedreferenceKovar DF, Lewis M, Karczmar GS. A new method for imaging perfusion and contrast extraction fraction: input functions derived from reference tissues. J Magn Reson Imaging 1998; 8: 1126 – 1134.en_US
dc.identifier.citedreferenceFan X, Haney CR, Mustafi D, et al. Use of a reference tissue and blood vessel to measure the arterial input function in DCEMRI. Magn Reson Med 2010; 64: 1821 – 1826.en_US
dc.identifier.citedreferenceHeisen M, Fan X, Buurman J, van Riel NA, Karczmar GS, ter Haar Romeny BM. The use of a reference tissue arterial input function with low‐temporal‐resolution DCE‐MRI data. Phys Med Biol 2010; 55: 4871 – 4883.en_US
dc.identifier.citedreferenceKuperman VY, Karczmar GS, Blomley MJ, Lewis MZ, Lubich LM, Lipton MJ. Differentiating between T1 and T2* changes caused by gadopentetate dimeglumine in the kidney by using a double‐echo dynamic MR imaging sequence. J Magn Reson Imaging 1996; 6: 764 – 768.en_US
dc.identifier.citedreferenceUematsu H, Maeda M. Double‐echo perfusion‐weighted MR imaging: basic concepts and application in brain tumors for the assessment of tumor blood volume and vascular permeability. Eur Radiol 2006; 16: 180 – 186.en_US
dc.identifier.citedreferenceBleeker EJ, van Buchem MA, Webb AG, van Osch MJ. Phase‐based arterial input function measurements for dynamic susceptibility contrast MRI. Magn Reson Med 2010; 64: 358 – 368.en_US
dc.identifier.citedreferenceCron GO, Foottit C, Yankeelov TE, Avruch LI, Schweitzer ME, Cameron I. Arterial input functions determined from MR signal magnitude and phase for quantitative dynamic contrast‐enhanced MRI in the human pelvis. Magn Reson Med 2011; 66: 498 – 504.en_US
dc.identifier.citedreferenceKorporaal JG, van den Berg CA, van Osch MJ, Groenendaal G, van Vulpen M, van der Heide UA. Phase‐based arterial input function measurements in the femoral arteries for quantification of dynamic contrast‐enhanced (DCE) MRI and comparison with DCE‐CT. Magn Reson Med 2011; 66: 1267 – 1274.en_US
dc.identifier.citedreferenceKnutsson L, Börjesson S, Larsson EM, et al. Absolute quantification of cerebral blood flow in normal volunteers: correlation between Xe‐133 SPECT and dynamic susceptibility contrast MRI. J Magn Reson Imaging 2007; 26: 913 – 920.en_US
dc.identifier.citedreferenceSchabel MC, DiBella EV, Jensen RL, Salzman KL. A model‐constrained Monte Carlo method for blind arterial input function estimation in dynamic contrast‐enhanced MRI: II. In vivo results. Phys Med Biol 2010; 55: 4807 – 4823.en_US
dc.identifier.citedreferenceSchabel MC, Fluckiger JU, DiBella EV. A model‐constrained Monte Carlo method for blind arterial input function estimation in dynamic contrast‐enhanced MRI: I. Simulations. Phys Med Biol 2010; 55: 4783 – 4806.en_US
dc.identifier.citedreferenceMurase K, Shinohara M, Yamazaki Y. Accuracy of deconvolution analysis based on singular value decomposition for quantification of cerebral blood flow using dynamic susceptibility contrast‐enhanced magnetic resonance imaging. Phys Med Biol 2001; 46: 3147 – 3159.en_US
dc.identifier.citedreferenceThng CH, Koh TS, Collins DJ, Koh DM. Perfusion magnetic resonance imaging of the liver. World J Gastroenterol 2010; 16: 1598 – 1609.en_US
dc.identifier.citedreferenceVan 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. AJR Am J Roentgenol 2001; 176: 667 – 673.en_US
dc.identifier.citedreferenceMiyazaki 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: 790 – 800.en_US
dc.identifier.citedreferenceDonahue KM, Burstein D, Manning WJ, Gray ML. Studies of Gd‐DTPA relaxivity and proton exchange rates in tissue. Magn Reson Med 1994; 32: 66 – 76.en_US
dc.identifier.citedreferenceLandis CS, Li X, Telang FW, et al. Determination of the MRI contrast agent concentration time course in vivo following bolus injection: effect of equilibrium transcytolemmal water exchange. Magn Reson Med 2000; 44: 563 – 574.en_US
dc.identifier.citedreferenceLandis CS, Li X, Telang FW, et al. Equilibrium transcytolemmal water‐exchange kinetics in skeletal muscle in vivo. Magn Reson Med 1999; 42: 467 – 478.en_US
dc.identifier.citedreferenceStanisz GJ, Henkelman RM. Gd‐DTPA relaxivity depends on macromolecular content. Magn Reson Med 2000; 44: 665 – 667.en_US
dc.identifier.citedreferenceWeinmann HJ, Brasch RC, Press WR, Wesbey GE. Characteristics of gadolinium‐DTPA complex: a potential NMR contrast agent. AJR Am J Roentgenol 1984; 142: 619 – 624.en_US
dc.identifier.citedreferencede Bazelaire C, Rofsky NM, Duhamel G, et al. Combined T2* and T1 measurements for improved perfusion and permeability studies in high field using dynamic contrast enhancement. Eur Radiol 2006; 16: 2083 – 2091.en_US
dc.identifier.citedreferenceCao Y, Brown SL, Knight RA, Fenstermacher JD, Ewing JR. Effect of intravascular‐to‐extravascular water exchange on the determination of blood‐to‐tissue transfer constant by magnetic resonance imaging. Magn Reson Med 2005; 53: 282 – 293.en_US
dc.identifier.citedreferenceEwing JR, Knight RA, Nagaraja TN, et al. Patlak plots of Gd‐DTPA MRI data yield blood‐brain transfer constants concordant with those of 14C‐sucrose in areas of blood‐brain opening. Magn Reson Med 2003; 50: 283 – 292.en_US
dc.identifier.citedreferenceKuperman VY, Alley MT. Differentiation between the effects of T1 and T2* shortening in contrast‐enhanced MRI of the breast. J Magn Reson Imaging 1999; 9: 172 – 176.en_US
dc.identifier.citedreferenceCheng HL. Investigation and optimization of parameter accuracy in dynamic contrast‐enhanced MRI. J Magn Reson Imaging 2008; 28: 736 – 743.en_US
dc.identifier.citedreferenceEllinger R, Kremser C, Schocke MF, et al. The impact of peak saturation of the arterial input function on quantitative evaluation of dynamic susceptibility contrast‐enhanced MR studies. J Comput Assist Tomogr 2000; 24: 942 – 948.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Name:
23636_ftp.pdf
Size:
2.448MB
Format:
PDF
View/Open

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe its collections in a way that respects the people and communities who create, use, and are represented in them. We encourage you to Contact Us anonymously if you encounter harmful or problematic language in catalog records or finding aids. More information about our policies and practices is available at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.