Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice
dc.contributor.author | Rosenkrantz, Andrew B. | en_US |
dc.contributor.author | Padhani, Anwar R. | en_US |
dc.contributor.author | Chenevert, Thomas L. | en_US |
dc.contributor.author | Koh, Dow‐mu | en_US |
dc.contributor.author | De Keyzer, Frederik | en_US |
dc.contributor.author | Taouli, Bachir | en_US |
dc.contributor.author | Le Bihan, Denis | en_US |
dc.date.accessioned | 2015-11-12T21:04:04Z | |
dc.date.available | 2017-01-03T16:21:17Z | en |
dc.date.issued | 2015-11 | en_US |
dc.identifier.citation | Rosenkrantz, Andrew B.; Padhani, Anwar R.; Chenevert, Thomas L.; Koh, Dow‐mu ; De Keyzer, Frederik; Taouli, Bachir; Le Bihan, Denis (2015). "Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice." Journal of Magnetic Resonance Imaging 42(5): 1190-1202. | en_US |
dc.identifier.issn | 1053-1807 | en_US |
dc.identifier.issn | 1522-2586 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/115942 | |
dc.publisher | Wiley Periodicals, Inc. | en_US |
dc.subject.other | diffusion weighted imaging | en_US |
dc.subject.other | diffusion kurtosis imaging | en_US |
dc.subject.other | apparent diffusion coefficient | en_US |
dc.subject.other | MRI | en_US |
dc.subject.other | tissue structure | en_US |
dc.subject.other | cancer | en_US |
dc.title | Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Medicine (General) | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/115942/1/jmri24985.pdf | |
dc.identifier.doi | 10.1002/jmri.24985 | en_US |
dc.identifier.source | Journal of Magnetic Resonance Imaging | en_US |
dc.identifier.citedreference | Huang Y, Chen X, Zhang Z, et al. MRI quantification of non‐Gaussian water diffusion in normal human kidney: a diffusional kurtosis imaging study. NMR Biomed 2015; 28: 154 – 161. | en_US |
dc.identifier.citedreference | Lewis S, Kamath A, Chatterji M, et al. Diffusion‐weighted imaging of the liver in patients with chronic liver disease: comparison of monopolar and bipolar diffusion gradients for image quality and lesion detection. AJR Am J Roentgenol 2015; 204: 59 – 68. | en_US |
dc.identifier.citedreference | Goshima S, Kanematsu M, Noda Y, Kondo H, Watanabe H, Bae KT. Diffusion kurtosis imaging to assess response to treatment in hypervascular hepatocellular carcinoma. AJR Am J Roentgenol 2015; 204: W543 – 549. | en_US |
dc.identifier.citedreference | American College of Radiology. Magnetic Resonance Prostate Imaging Reporting and Data System (MR PI‐RADS). http://www.acr.org/Quality‐Safety/Resources/PIRADS Accessed December 29, 2014. | en_US |
dc.identifier.citedreference | Pentang G, Lanzman RS, Heusch P, et al. Diffusion kurtosis imaging of the human kidney: a feasibility study. Magn Reson Imaging 2014; 32: 413 – 420. | en_US |
dc.identifier.citedreference | Rosenkrantz AB, Kong X, Niver BE, et al. Prostate cancer: comparison of tumor visibility on trace diffusion‐weighted images and the apparent diffusion coefficient map. AJR Am J Roentgenol 2011; 196: 123 – 129. | en_US |
dc.identifier.citedreference | Quentin M, Blondin D, Klasen J, et al. Comparison of different mathematical models of diffusion‐weighted prostate MR imaging. Magn Reson Imaging 2012; 30: 1468 – 1474. | en_US |
dc.identifier.citedreference | Rosenkrantz AB, Prabhu V, Sigmund EE, Babb JS, Deng FM, Taneja SS. Utility of diffusional kurtosis imaging as a marker of adverse pathologic outcomes among prostate cancer active surveillance candidates undergoing radical prostatectomy. AJR Am J Roentgenol 2013; 201: 840 – 846. | en_US |
dc.identifier.citedreference | Mazzoni LN, Lucarini S, Chiti S, Busoni S, Gori C, Menchi I. Diffusion‐weighted signal models in healthy and cancerous peripheral prostate tissues: comparison of outcomes obtained at different b‐values. J Magn Reson Imaging JMRI 2014; 39: 512 – 518. | en_US |
dc.identifier.citedreference | Suo S, Chen X, Wu L, et al. Non‐Gaussian water diffusion kurtosis imaging of prostate cancer. Magn Reson Imaging 2014; 32: 421 – 427. | en_US |
dc.identifier.citedreference | Jambor I, Merisaari H, Taimen P, et al. Evaluation of different mathematical models for diffusion‐weighted imaging of normal prostate and prostate cancer using high b‐values: a repeatability study. Magn Reson Med 2015; 73: 1988 – 1998. | en_US |
dc.identifier.citedreference | Roethke MC, Kuder TA, Kuru TH, et al. Evaluation of diffusion kurtosis imaging versus standard diffusion imaging for detection and grading of peripheral zone prostate cancer. Invest Radiol 2015 [Epub ahead of print]. | en_US |
dc.identifier.citedreference | Merisaari H, Jambor I. Optimization of b‐value distribution for four mathematical models of prostate cancer diffusion‐weighted imaging using b values up to 2000 s/mm (2): Simulation and repeatability study. Magn Reson Med 2015; 73: 1954 – 1969. | en_US |
dc.identifier.citedreference | Lu Y, Jansen JF, Mazaheri Y, Stambuk HE, Koutcher JA, Shukla‐Dave A. Extension of the intravoxel incoherent motion model to non‐Gaussian diffusion in head and neck cancer. J Magn Reson Imaging JMRI 2012; 36: 1088 – 1096. | en_US |
dc.identifier.citedreference | Yuan J, Yeung DK, Mok GS, et al. Non‐Gaussian analysis of diffusion weighted imaging in head and neck at 3T: a pilot study in patients with nasopharyngeal carcinoma. PLoS One 2014; 9: e87024. | en_US |
dc.identifier.citedreference | Chen Y, Ren W, Zheng D, et al. Diffusion kurtosis imaging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients. J Magn Reson Imaging JMRI 2015 [Epub ahead of print]. | en_US |
dc.identifier.citedreference | Nogueira L, Brandao S, Matos E, et al. Application of the diffusion kurtosis model for the study of breast lesions. Eur Radiol 2014; 24: 1197 – 1203. | en_US |
dc.identifier.citedreference | Wu D, Li G, Zhang J, Chang S, Hu J, Dai Y. Characterization of Breast Tumors Using Diffusion Kurtosis Imaging (DKI). PLoS One 2014; 9: e113240. | en_US |
dc.identifier.citedreference | Trampel R, Jensen JH, Lee RF, Kamenetskiy I, McGuinness G, Johnson G. Diffusional kurtosis imaging in the lung using hyperpolarized 3He. Magn Reson Med 2006; 56: 733 – 737. | en_US |
dc.identifier.citedreference | Heusch P, Kohler J, Wittsack HJ, et al. Hybrid [(1) (8)F]‐FDG PET/MRI including non‐Gaussian diffusion‐weighted imaging (DWI): preliminary results in non‐small cell lung cancer (NSCLC). Eur J Radiol 2013; 82: 2055 – 2060. | en_US |
dc.identifier.citedreference | Marschar AM, Kuder TA, Stieltjes B, Nagel AM, Bachert P, Laun FB. In vivo imaging of the time‐dependent apparent diffusional kurtosis in the human calf muscle. J Magn Reson Imaging JMRI 2015; 41: 1581 – 1590. | en_US |
dc.identifier.citedreference | Lohezic M, Teh I, Bollensdorff C, et al. Interrogation of living myocardium in multiple static deformation states with diffusion tensor and diffusion spectrum imaging. Prog Biophys Mol Biol 2014; 115: 213 – 225. | en_US |
dc.identifier.citedreference | Yamada I, Hikishima K, Miyasaka N, et al. Esophageal carcinoma: Evaluation with q‐space diffusion‐weighted MR imaging ex vivo. Magn Reson Med 2015; 73: 2262 – 2273. | en_US |
dc.identifier.citedreference | Li SP, Padhani AR. Tumor response assessments with diffusion and perfusion MRI. J Magn Reson Imaging JMRI 2012; 35: 745 – 763. | en_US |
dc.identifier.citedreference | Padhani AR, Miles KA. Multiparametric imaging of tumor response to therapy. Radiology 2010; 256: 348 – 364. | en_US |
dc.identifier.citedreference | Koh DM, Collins DJ. Diffusion‐weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 2007; 188: 1622 – 1635. | en_US |
dc.identifier.citedreference | Padhani AR, Liu G, Koh DM, et al. Diffusion‐weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009; 11: 102 – 125. | en_US |
dc.identifier.citedreference | Le Bihan D. Apparent diffusion coefficient and beyond: what diffusion MR imaging can tell us about tissue structure. Radiology 2013; 268: 318 – 322. | en_US |
dc.identifier.citedreference | Katahira K, Takahara T, Kwee TC, et al. Ultra‐high‐b‐value diffusion‐weighted MR imaging for the detection of prostate cancer: evaluation in 201 cases with histopathological correlation. Eur Radiol 2011; 21: 188 – 196. | en_US |
dc.identifier.citedreference | Raab P, Hattingen E, Franz K, Zanella FE, Lanfermann H. Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences. Radiology 2010; 254: 876 – 881. | en_US |
dc.identifier.citedreference | Chabert S, Mecca CC, Le Bihan DJ. Relevance of the information about the diffusion distribution in invo given by kurtosis in q‐space imaging. In: Proc 12th Annual Meeting ISMRM, Kyoto; 2004. p 1238. | en_US |
dc.identifier.citedreference | Jensen JH, Helpern JA, Ramani A, Lu H, Kaczynski K. Diffusional kurtosis imaging: the quantification of non‐Gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med 2005; 53: 1432 – 1440. | en_US |
dc.identifier.citedreference | Wu EX, Cheung MM. MR diffusion kurtosis imaging for neural tissue characterization. NMR Biomed 2010; 23: 836 – 848. | en_US |
dc.identifier.citedreference | Fieremans E, Jensen JH, Helpern JA. White matter characterization with diffusional kurtosis imaging. NeuroImage 2011; 58: 177 – 188. | en_US |
dc.identifier.citedreference | Rosenkrantz AB, Sigmund EE, Johnson G, et al. Prostate cancer: feasibility and preliminary experience of a diffusional kurtosis model for detection and assessment of aggressiveness of peripheral zone cancer. Radiology 2012; 264: 126 – 135. | en_US |
dc.identifier.citedreference | Jansen JF, Stambuk HE, Koutcher JA, Shukla‐Dave A. Non‐Gaussian analysis of diffusion‐weighted MR imaging in head and neck squamous cell carcinoma: a feasibility study. AJNR Am J Neuroradiol 2010; 31: 741 – 748. | en_US |
dc.identifier.citedreference | Iima M, Yano K, Kataoka M, et al. Quantitative non‐Gaussian diffusion and intravoxel incoherent motion magnetic resonance imaging: differentiation of malignant and benign breast lesions. Invest Radiol 2015; 50: 205 – 211. | en_US |
dc.identifier.citedreference | Anderson SW, Barry B, Soto J, Ozonoff A, O'Brien M, Jara H. Characterizing non‐Gaussian, high b‐value diffusion in liver fibrosis: stretched exponential and diffusional kurtosis modeling. J Magn Reson Imaging JMRI 2014; 39: 827 – 834. | en_US |
dc.identifier.citedreference | Metens T, Miranda D, Absil J, Matos C. What is the optimal b value in diffusion‐weighted MR imaging to depict prostate cancer at 3T? Eur Radiol 2012; 22: 703 – 709. | en_US |
dc.identifier.citedreference | Vural M, Ertas G, Onay A, et al. Conspicuity of peripheral zone prostate cancer on computed diffusion‐weighted imaging: comparison of cDWI1500, cDWI2000, and cDWI3000. BioMed Res Int 2014; 2014: 768291. | en_US |
dc.identifier.citedreference | Tamada T, Kanomata N, Sone T, et al. High b value (2,000 s/mm2) diffusion‐weighted magnetic resonance imaging in prostate cancer at 3 Tesla: comparison with 1,000 s/mm2 for tumor conspicuity and discrimination of aggressiveness. PLoS One 2014; 9: e96619. | en_US |
dc.identifier.citedreference | Ahn SJ, Choi SH, Kim YJ, et al. Histogram analysis of apparent diffusion coefficient map of standard and high B‐value diffusion MR imaging in head and neck squamous cell carcinoma: a correlation study with histological grade. Acad Radiol 2012; 19: 1233 – 1240. | en_US |
dc.identifier.citedreference | Kitajima K, Kaji Y, Kuroda K, Sugimura K. High b‐value diffusion‐weighted imaging in normal and malignant peripheral zone tissue of the prostate: effect of signal‐to‐noise ratio. Magn Reson Med Sci 2008; 7: 93 – 99. | en_US |
dc.identifier.citedreference | Kim CK, Park BK, Kim B. High‐b‐value diffusion‐weighted imaging at 3 T to detect prostate cancer: comparisons between b values of 1,000 and 2,000 s/mm2. AJR Am J Roentgenol 2010; 194: W33 – 37. | en_US |
dc.identifier.citedreference | Bourne RM, Panagiotaki E, Bongers A, Sved P, Watson G, Alexander DC. Information theoretic ranking of four models of diffusion attenuation in fresh and fixed prostate tissue ex vivo. Magn Reson Med 2014; 72: 1418 – 1426. | en_US |
dc.identifier.citedreference | Toivonen J, Merisaari H, Pesola M, et al. Mathematical models for diffusion‐weighted imaging of prostate cancer using b values up to 2000 s/mm: Correlation with Gleason score and repeatability of region of interest analysis. Magn Reson Med 2014 [Epub ahead of print]. | en_US |
dc.identifier.citedreference | Grinberg F, Farrher E, Ciobanu L, Geffroy F, Le Bihan D, Shah NJ. Non‐Gaussian diffusion imaging for enhanced contrast of brain tissue affected by ischemic stroke. PLoS One 2014; 9: e89225. | en_US |
dc.identifier.citedreference | Padhani AR, Makris A, Gall P, Collins DJ, Tunariu N, de Bono JS. Therapy monitoring of skeletal metastases with whole‐body diffusion MRI. J Magn Reson Imaging JMRI 2014; 39: 1049 – 1078. | en_US |
dc.identifier.citedreference | Nonomura Y, Yasumoto M, Yoshimura R, et al. Relationship between bone marrow cellularity and apparent diffusion coefficient. J Magn Reson Imaging JMRI 2001; 13: 757 – 760. | en_US |
dc.identifier.citedreference | Le Bihan D. The 'wet mind': water and functional neuroimaging. Phys Med Biol 2007; 52: R57 – 90. | en_US |
dc.identifier.citedreference | Jensen JH, Helpern JA. MRI quantification of non‐Gaussian water diffusion by kurtosis analysis. NMR Biomed 2010; 23: 698 – 710. | en_US |
dc.identifier.citedreference | White NS, Dale AM. Distinct effects of nuclear volume fraction and cell diameter on high b‐value diffusion MRI contrast in tumors. Magn Reson Med 2014; 72: 1435 – 1443. | en_US |
dc.identifier.citedreference | Lawrence E, Goldman D, Gallagher F, et al. Evaluating the Relationship between Gleason Score, Tumor Tissue Composition, and Diffusion Kurtosis Imaging in Intermediate/High‐risk Prostate Cancer Whole‐mount Specimens. Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, Chicago IL. http://archive.rsna.org/2014/14003112.html. Accessed April 26, 2015. | en_US |
dc.identifier.citedreference | Panagiotaki E, Chan RW, Dikaios N, et al. Microstructural characterization of normal and malignant human prostate tissue with vascular, extracellular, and restricted diffusion for cytometry in tumours magnetic resonance imaging. Invest Radiol 2015; 50: 218 – 227. | en_US |
dc.identifier.citedreference | Rosenkrantz AB, Hindman N, Lim RP, et al. Diffusion‐weighted imaging of the prostate: comparison of b1000 and b2000 image sets for index lesion detection. J Magn Reson Imaging JMRI 2013; 38: 694 – 700. | en_US |
dc.identifier.citedreference | Maas MC, Futterer JJ, Scheenen TW. Quantitative evaluation of computed high B value diffusion‐weighted magnetic resonance imaging of the prostate. Invest Radiol 2013; 48: 779 – 786. | en_US |
dc.identifier.citedreference | Ueno Y, Takahashi S, Kitajima K, et al. Computed diffusion‐weighted imaging using 3‐T magnetic resonance imaging for prostate cancer diagnosis. Eur Radiol 2013; 23: 3509 – 3516. | en_US |
dc.identifier.citedreference | Rosenkrantz AB, Sigmund EE, Winnick A, et al. Assessment of hepatocellular carcinoma using apparent diffusion coefficient and diffusion kurtosis indices: preliminary experience in fresh liver explants. Magn Reson Imaging 2012; 30: 1534 – 1540. | en_US |
dc.identifier.citedreference | Lu H, Jensen JH, Ramani A, Helpern JA. Three‐dimensional characterization of non‐Gaussian water diffusion in humans using diffusion kurtosis imaging. NMR Biomed 2006; 19: 236 – 247. | en_US |
dc.identifier.citedreference | Assaf Y, Ben‐Bashat D, Chapman J, et al. High b‐value q‐space analyzed diffusion‐weighted MRI: application to multiple sclerosis. Magn Reson Med 2002; 47: 115 – 126. | en_US |
dc.identifier.citedreference | Filli L, Wurnig M, Nanz D, Luechinger R, Kenkel D, Boss A. Whole‐body diffusion kurtosis imaging: initial experience on non‐Gaussian diffusion in various organs. Invest Radiol 2014; 49: 773 – 778. | en_US |
dc.identifier.citedreference | Tamura C, Shinmoto H, Soga S, et al. Diffusion kurtosis imaging study of prostate cancer: preliminary findings. J Magn Reson Imaging JMRI 2014; 40: 723 – 729. | en_US |
dc.identifier.citedreference | Suo S, Chen X, Ji X, et al. Investigation of the non‐Gaussian water diffusion properties in bladder cancer using diffusion kurtosis imaging: a preliminary study. J Comput Assist Tomogr 2015; 39: 281 – 285. | en_US |
dc.identifier.citedreference | Koh DM, Collins DJ, Orton MR. Intravoxel incoherent motion in body diffusion‐weighted MRI: reality and challenges. AJR Am J Roentgenol 2011; 196: 1351 – 1361. | en_US |
dc.identifier.citedreference | Pyatigorskaya N, Le Bihan D, Reynaud O, Ciobanu L. Relationship between the diffusion time and the diffusion MRI signal observed at 17.2 Tesla in the healthy rat brain cortex. Magn Reson Med 2014; 72: 492 – 500. | en_US |
dc.identifier.citedreference | Glenn GR, Tabesh A, Jensen JH. A simple noise correction scheme for diffusional kurtosis imaging. Magn Reson Imaging 2015; 33: 124 – 133. | en_US |
dc.identifier.citedreference | Choi JS, Kim MJ, Chung YE, et al. Comparison of breathhold, navigator‐triggered, and free‐breathing diffusion‐weighted MRI for focal hepatic lesions. J Magn Reson Imaging JMRI 2013; 38: 109 – 118. | en_US |
dc.identifier.citedreference | Veraart J, Poot DH, Van Hecke W, et al. More accurate estimation of diffusion tensor parameters using diffusion kurtosis imaging. Magn Reson Med 2011; 65: 138 – 145. | en_US |
dc.identifier.citedreference | Quentin M, Pentang G, Schimmoller L, et al. Feasibility of diffusional kurtosis tensor imaging in prostate MRI for the assessment of prostate cancer: preliminary results. Magn Reson Imaging 2014; 32: 880 – 885. | en_US |
dc.identifier.citedreference | Kyriazi S, Blackledge M, Collins DJ, Desouza NM. Optimising diffusion‐weighted imaging in the abdomen and pelvis: comparison of image quality between monopolar and bipolar single‐shot spin‐echo echo‐planar sequences. Eur Radiol 2010; 20: 2422 – 2431. | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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