Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
권호 표지
DOI QR코드

DOI QR Code

Intravoxel Incoherent Motion MR Imaging in the Head and Neck: Correlation with Dynamic Contrast-Enhanced MR Imaging and Diffusion-Weighted Imaging

  • Xu, Xiao Quan (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Choi, Young Jun (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Sung, Yu Sub (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Yoon, Ra Gyoung (Department of Radiology, Catholic Kwandong University International St. Mary's Hospital, Catholic Kwandong University College of Medicine) ;
  • Jang, Seung Won (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Park, Ji Eun (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Heo, Young Jin (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Baek, Jung Hwan (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Lee, Jeong Hyun (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center)
  • Received : 2015.03.21
  • Accepted : 2016.05.17
  • Published : 2016.09.01
⟨ Previous Next ⟩

Abstract

Objective: To investigate the correlation between perfusion- and diffusion-related parameters from intravoxel incoherent motion (IVIM) and those from dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted imaging in tumors and normal muscles of the head and neck. Materials and Methods: We retrospectively enrolled 20 consecutive patients with head and neck tumors with MR imaging performed using a 3T MR scanner. Tissue diffusivity (D), pseudo-diffusion coefficient ($D^*$), and perfusion fraction (f) were derived from bi-exponential fitting of IVIM data obtained with 14 different b-values in three orthogonal directions. We investigated the correlation between D, f, and $D^*$ and model-free parameters from the DCE-MRI (wash-in, $T_{max}$, $E_{max}$, initial $AUC_{60}$, whole AUC) and the apparent diffusion coefficient (ADC) value in the tumor and normal masseter muscle using a whole volume-of-interest approach. Pearson's correlation test was used for statistical analysis. Results: No correlation was found between f or $D^*$ and any of the parameters from the DCE-MRI in all patients or in patients with squamous cell carcinoma (p > 0.05). The ADC was significantly correlated with D values in the tumors (p < 0.001, r = 0.980) and muscles (p = 0.013, r = 0.542), despite its significantly higher value than D. The difference between ADC and D showed significant correlation with f values in the tumors (p = 0.017, r = 0.528) and muscles (p = 0.003, r = 0.630), but no correlation with $D^*$ (p > 0.05, respectively). Conclusion: Intravoxel incoherent motion shows no significant correlation with model-free perfusion parameters derived from the DCE-MRI but is feasible for the analysis of diffusivity in both tumors and normal muscles of the head and neck.

Keywords

References

  1. Sakamoto J, Imaizumi A, Sasaki Y, Kamio T, Wakoh M, Otonari-Yamamoto M, et al. Comparison of accuracy of intravoxel incoherent motion and apparent diffusion coefficient techniques for predicting malignancy of head and neck tumors using half-Fourier single-shot turbo spin-echo diffusion-weighted imaging. Magn Reson Imaging 2014;32:860-866 https://doi.org/10.1016/j.mri.2014.05.002
  2. Hwang I, Choi SH, Kim YJ, Kim KG, Lee AL, Yun TJ, et al. Differentiation of recurrent tumor and posttreatment changes in head and neck squamous cell carcinoma: application of high b-value diffusion-weighted imaging. AJNR Am J Neuroradiol 2013;34:2343-2348 https://doi.org/10.3174/ajnr.A3603
  3. Lim HK, Lee JH, Baek HJ, Kim N, Lee H, Park JW, et al. Is diffusion-weighted MRI useful for differentiation of small non-necrotic cervical lymph nodes in patients with head and neck malignancies? Korean J Radiol 2014;15:810-816 https://doi.org/10.3348/kjr.2014.15.6.810
  4. Chawla S, Kim S, Dougherty L, Wang S, Loevner LA, Quon H, et al. Pretreatment diffusion-weighted and dynamic contrast-enhanced MRI for prediction of local treatment response in squamous cell carcinomas of the head and neck. AJR Am J Roentgenol 2013;200:35-43 https://doi.org/10.2214/AJR.12.9432
  5. Ng SH, Lin CY, Chan SC, Yen TC, Liao CT, Chang JT, et al. Dynamic contrast-enhanced MR imaging predicts local control in oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiotherapy. PLoS One 2013;8:e72230 https://doi.org/10.1371/journal.pone.0072230
  6. Driessen JP, Caldas-Magalhaes J, Janssen LM, Pameijer FA, Kooij N, Terhaard CH, et al. Diffusion-weighted MR imaging in laryngeal and hypopharyngeal carcinoma: association between apparent diffusion coefficient and histologic findings. Radiology 2014;272:456-463 https://doi.org/10.1148/radiol.14131173
  7. Furukawa M, Parvathaneni U, Maravilla K, Richards TL, Anzai Y. Dynamic contrast-enhanced MR perfusion imaging of head and neck tumors at 3 Tesla. Head Neck 2013;35:923-929 https://doi.org/10.1002/hed.23051
  8. Jahng GH, Li KL, Ostergaard L, Calamante F. Perfusion magnetic resonance imaging: a comprehensive update on principles and techniques. Korean J Radiol 2014;15:554-577 https://doi.org/10.3348/kjr.2014.15.5.554
  9. Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 1988;168:497-505 https://doi.org/10.1148/radiology.168.2.3393671
  10. Zhang SX, Jia QJ, Zhang ZP, Liang CH, Chen WB, Qiu QH, et al. Intravoxel incoherent motion MRI: emerging applications for nasopharyngeal carcinoma at the primary site. Eur Radiol 2014;24:1998-2004 https://doi.org/10.1007/s00330-014-3203-0
  11. Bisdas S, Braun C, Skardelly M, Schittenhelm J, Teo TH, Thng CH, et al. Correlative assessment of tumor microcirculation using contrast-enhanced perfusion MRI and intravoxel incoherent motion diffusion-weighted MRI: is there a link between them? NMR Biomed 2014;27:1184-1191 https://doi.org/10.1002/nbm.3172
  12. Patel J, Sigmund EE, Rusinek H, Oei M, Babb JS, Taouli B. Diagnosis of cirrhosis with intravoxel incoherent motion diffusion MRI and dynamic contrast-enhanced MRI alone and in combination: preliminary experience. J Magn Reson Imaging 2010;31:589-600 https://doi.org/10.1002/jmri.22081
  13. Lee EY, Hui ES, Chan KK, Tse KY, Kwong WK, Chang TY, et al. Relationship between intravoxel incoherent motion diffusion-weighted MRI and dynamic contrast-enhanced MRI in tissue perfusion of cervical cancers. J Magn Reson Imaging 2015;42:454-459 https://doi.org/10.1002/jmri.24808
  14. Jia QJ, Zhang SX, Chen WB, Liang L, Zhou ZG, Qiu QH, et al. Initial experience of correlating parameters of intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging at 3.0 T in nasopharyngeal carcinoma. Eur Radiol 2014;24:3076-3087 https://doi.org/10.1007/s00330-014-3343-2
  15. Fujima N, Yoshida D, Sakashita T, Homma A, Tsukahara A, Tha KK, et al. Intravoxel incoherent motion diffusion-weighted imaging in head and neck squamous cell carcinoma: assessment of perfusion-related parameters compared to dynamic contrast-enhanced MRI. Magn Reson Imaging 2014;32:1206-1213 https://doi.org/10.1016/j.mri.2014.08.009
  16. Chung WJ, Kim HS, Kim N, Choi CG, Kim SJ. Recurrent glioblastoma: optimum area under the curve method derived from dynamic contrast-enhanced T1-weighted perfusion MR imaging. Radiology 2013;269:561-568 https://doi.org/10.1148/radiol.13130016
  17. Galbraith SM, Lodge MA, Taylor NJ, Rustin GJ, Bentzen S, Stirling JJ, et al. Reproducibility of dynamic contrast-enhanced MRI in human muscle and tumours: comparison of quantitative and semi-quantitative analysis. NMR Biomed 2002;15:132-142 https://doi.org/10.1002/nbm.731
  18. Suh CH, Kim HS, Lee SS, Kim N, Yoon HM, Choi CG, et al. Atypical imaging features of primary central nervous system lymphoma that mimics glioblastoma: utility of intravoxel incoherent motion MR imaging. Radiology 2014;272:504-513 https://doi.org/10.1148/radiol.14131895
  19. Le Bihan D, Turner R, MacFall JR. Effects of intravoxel incoherent motions (IVIM) in steady-state free precession (SSFP) imaging: application to molecular diffusion imaging. Magn Reson Med 1989;10:324-337 https://doi.org/10.1002/mrm.1910100305
  20. Kim DY, Kim HS, Goh MJ, Choi CG, Kim SJ. Utility of intravoxel incoherent motion MR imaging for distinguishing recurrent metastatic tumor from treatment effect following gamma knife radiosurgery: initial experience. AJNR Am J Neuroradiol 2014;35:2082-2090 https://doi.org/10.3174/ajnr.A3995
  21. Cox RW. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 1996;29:162-173 https://doi.org/10.1006/cbmr.1996.0014
  22. Evelhoch JL, LoRusso PM, He Z, DelProposto Z, Polin L, Corbett TH, et al. Magnetic resonance imaging measurements of the response of murine and human tumors to the vascular-targeting agent ZD6126. Clin Cancer Res 2004;10:3650-3657 https://doi.org/10.1158/1078-0432.CCR-03-0417
  23. Kim HS, Suh CH, Kim N, Choi CG, Kim SJ. Histogram analysis of intravoxel incoherent motion for differentiating recurrent tumor from treatment effect in patients with glioblastoma: initial clinical experience. AJNR Am J Neuroradiol 2014;35:490-497 https://doi.org/10.3174/ajnr.A3719
  24. Federau C, O'Brien K, Meuli R, Hagmann P, Maeder P. Measuring brain perfusion with intravoxel incoherent motion (IVIM): initial clinical experience. J Magn Reson Imaging 2014;39:624-632 https://doi.org/10.1002/jmri.24195
  25. Zhu L, Cheng Q, Luo W, Bao L, Guo G. A comparative study of apparent diffusion coefficient and intravoxel incoherent motion-derived parameters for the characterization of common solid hepatic tumors. Acta Radiol 2015;56:1411-1418 https://doi.org/10.1177/0284185114559426
  26. Federau C, Hagmann P, Maeder P, Muller M, Meuli R, Stuber M, et al. Dependence of brain intravoxel incoherent motion perfusion parameters on the cardiac cycle. PLoS One 2013;8:e72856 https://doi.org/10.1371/journal.pone.0072856
  27. Lee Y, Lee SS, Kim N, Kim E, Kim YJ, Yun SC, et al. Intravoxel incoherent motion diffusion-weighted MR imaging of the liver: effect of triggering methods on regional variability and measurement repeatability of quantitative parameters. Radiology 2015;274:405-415 https://doi.org/10.1148/radiol.14140759
  28. Marzi S, Piludu F, Vidiri A. Assessment of diffusion parameters by intravoxel incoherent motion MRI in head and neck squamous cell carcinoma. NMR Biomed 2013;26:1806-1814 https://doi.org/10.1002/nbm.3020
  29. Guin JA. Modification of the complex method of constrained optimization. Comput J 1968;10:416-417 https://doi.org/10.1093/comjnl/10.4.416

Cited by

  1. Histogram analysis of diffusion kurtosis imaging of nasopharyngeal carcinoma: Correlation between quantitative parameters and clinical stage vol.8, pp.29, 2017, https://doi.org/10.18632/oncotarget.17591
  2. Correlation between Intravoxel Incoherent Motion Magnetic Resonance Imaging Derived Metrics and Serum Soluble CD40 Ligand Level in an Embolic Canine Stroke Model vol.18, pp.5, 2016, https://doi.org/10.3348/kjr.2017.18.5.835
  3. Early Changes in Glutamate Metabolism and Perfusion in Basal Ganglia following Hypoxia-Ischemia in Neonatal Piglets: A Multi-Sequence 3.0T MR Study vol.8, pp.None, 2016, https://doi.org/10.3389/fphys.2017.00237
  4. Utility of a Hybrid IVIM-DKI Model to Predict the Development of Distant Metastasis in Head and Neck Squamous Cell Carcinoma Patients vol.17, pp.1, 2016, https://doi.org/10.2463/mrms.mp.2016-0136
  5. Diffusion-Weighted MR Imaging of Unicystic Odontogenic Tumors for Differentiation of Unicystic Ameloblastomas from Keratocystic Odontogenic Tumors vol.19, pp.1, 2016, https://doi.org/10.3348/kjr.2018.19.1.79
  6. Early Changes in Apparent Diffusion Coefficient for Salivary Glands during Radiotherapy for Nasopharyngeal Carcinoma Associated with Xerostomia vol.19, pp.2, 2018, https://doi.org/10.3348/kjr.2018.19.2.328
  7. A Whole-Tumor Histogram Analysis of Apparent Diffusion Coefficient Maps for Differentiating Thymic Carcinoma from Lymphoma vol.19, pp.2, 2018, https://doi.org/10.3348/kjr.2018.19.2.358
  8. Intravoxel incoherent motion magnetic resonance imaging of the normal-appearing parotid glands in patients with differentiated thyroid cancer after radioiodine therapy vol.59, pp.2, 2018, https://doi.org/10.1177/0284185117709037
  9. Differentiation between orbital malignant and benign tumors using intravoxel incoherent motion diffusion-weighted imaging : Correlation with dynamic contrast-enhanced magnetic resonance imaging vol.98, pp.12, 2016, https://doi.org/10.1097/md.0000000000014897
  10. Correlation and Characteristics of Intravoxel Incoherent Motion and Arterial Spin Labeling Techniques Versus Multiple Parameters Obtained on Dynamic Susceptibility Contrast Perfusion MRI for Brain Tum vol.66, pp.3, 2019, https://doi.org/10.2152/jmi.66.308
  11. The Value of IVIM DWI in Combination with Conventional MRI in Identifying the Residual Tumor After Cone Biopsy for Early Cervical Carcinoma vol.26, pp.8, 2016, https://doi.org/10.1016/j.acra.2018.09.027
  12. Evaluation of Xerostomia in Patients with Head and Neck Squamous Cell Carcinoma Treated with Radiotherapy vol.11, pp.2, 2016, https://doi.org/10.4236/jct.2020.112009
  13. Diffusion Kurtosis Imaging and Intravoxel Incoherent Motion in Differentiating Nasal Malignancies vol.130, pp.12, 2016, https://doi.org/10.1002/lary.28424
  14. Perfusion-based functional magnetic resonance imaging for differentiating serous borderline ovarian tumors from early serous ovarian cancers in a rat model vol.62, pp.1, 2021, https://doi.org/10.1177/0284185120913711
  15. Multiparametric functional MRI and 18 F-FDG-PET for survival prediction in patients with head and neck squamous cell carcinoma treated with (chemo)radiation vol.31, pp.2, 2021, https://doi.org/10.1007/s00330-020-07163-3
  16. Exercise-induced muscle damage: multi-parametric MRI quantitative assessment vol.22, pp.1, 2021, https://doi.org/10.1186/s12891-021-04085-z