Intravoxel incoherent motion

Intravoxel incoherent motion (IVIM) imaging is a concept and a method initially introduced and developed by Le Bihan et al.[1][2] to quantitatively assess all the microscopic translational motions that could contribute to the signal acquired with diffusion MRI. In biological tissue, these motions essentially are molecular diffusion of water and microcirculation of blood in the capillary network (perfusion). The concept introduced by D. Le Bihan is that water flowing in randomly oriented capillaries (at the voxel level) mimics a random walk (“pseudo-diffusion” [2]) (Fig.1).

Fig. 1.

It is responsible for a signal attenuation in diffusion MRI, which depends on the velocity of the flowing blood and the vascular architecture. Similarly to molecular diffusion, the effect of pseudodiffusion on the signal attenuation depends on the b value. However, the rate of signal attenuation resulting from pseudodiffusion is typically an order of magnitude greater than molecular diffusion in tissues, so its relative contribution to the diffusion-weighted MRI signal becomes significant only at very low b values, allowing diffusion and perfusion effects to be separated.[2][3]

Model

In the presence of the magnetic field gradient pulses of a diffusion MRI sequence, the MRI signal gets attenuated due to diffusion and perfusion effects. In a simple model, this signal attenuation, S/So, can be written as:[2]

[1]

where is the volume fraction of incoherently flowing blood in the tissue (“flowing vascular volume”), the signal attenuation from the IVIM effect and is the signal attenuation from molecular diffusion in the tissue.

Assuming blood water flowing in the randomly oriented vasculature changes several times direction (at least 2) during the measurement time (model 1), one has for  :

[2]

where is the diffusion-sensitization of the MRI sequence, is the sum of the pseudo-diffusion coefficient associated to the IVIM effect and , the diffusion coefficient of water in blood:

[3]

where is the mean capillary segment length and is the blood velocity.[2][4]

If blood water flows without changing direction (either because flow is slow or measurement time is short) while capillary segments are randomly and isotropically oriented (model 2), becomes:

[4]

where is a parameter linked to the gradient pulse amplitude and time course (similar to the b value).[2][4]

In both cases, the perfusion effect results in a curvature of the diffusion attenuation plot towards b=0 (Fig.2).

Fig. 2.

In a simple approach and under some approximations, the ADC calculated from 2 diffusion-weighted images acquired with b0=0 and b1, as ADC = ln(S(b0)/S (b1)), is:[2][4]

[5]

where is the tissue diffusion coefficient. The ADC thus only depends on the flowing vascular volume (tissue vascularity) and not on the blood velocity and capillary geometry, which is a strong advantage. The contribution of perfusion to the ADC is larger when using small b values. On the other hand, set of data obtained from images acquired with a multiple b values can be fitted with Eq.[1] using either model 1 (Eq.[2,3]) or model 2(Eq.[4]) to estimate and/or blood velocity. The late part of the curve (towards high b values, generally above 1000 s/mm²) also presents some degree of curvature (Fig.2). This is because diffusion in biological tissues is not free (Gaussian), but hindered by many obstacles (in particular cell membranes). Several models have been proposed to describe this curvature, mainly the “biexponential” model which assumes the presence of 2 water compartments with fast and slow diffusion [5][6] and the “kurtosis” model which quantifies the deviation from free (Gaussian) diffusion.[7][8]

Biexponential model:

[6]

Where and are the relative fractions and diffusion coefficients of the fast and slow compartments.

Kurtosis model:

[7]

where is the tissue intrinsic diffusion coefficient and the Kurtosis parameter (deviation from Gaussian diffusion). Both models can be related assuming some hypotheses about the tissue structure and the measurement conditions. Separation of perfusion from diffusion requires good signal-to-noise ratios[9][10] and there are some technical challenges to overcome (artifacts, influence of other bulk flow phonemena, etc.).[3][11][12] Also the “perfusion” parameters accessible with the IVIM method somewhat differs from the “classical” perfusion parameters obtained with tracer methods: “Perfusion” can be seen with the physiologist eyes (blood flow) or the radiologist eyes (vascular density).[13][14] Indeed, there is room to improve the IVIM model and understand better its relationship with the functional vascular architecture and its biological relevance.

Applications

IVIM MRI was initially introduced to evaluate perfusion and produce maps of brain perfusion, for brain activation studies (before the introduction of BOLD fMRI) and clinical applications (stroke, brain tumors).[10][15][16][17][18][19] Recent work has proven the validity of the IVIM concept from fMRI, with an increase in the IVIM perfusion parameters in brain activated regions, and the potential of the approach to aid in our understanding of the different vascular contributions to the fMRI signal.[20][21][22][23] IVIM MRI has also been used in the context of fMRI in a negative way.

A limitation of BOLD fMRI is its spatial resolution, as flow increase in somewhat large arteries or veins feed or drain large neuronal territories. By inserting “diffusion” gradient pulses in the MRI sequence (corresponding to low b-values), one may crush the contribution of the largest vessels (with high D* values associated with fast flow) in the BOLD signal and improve the spatial resolution of the activation maps.[24][25][26][27][28] Several groups have relied on this trick, though not always considering referring to the IVIM concept. This IVIM concept has also been borrowed to improve other applications, for instance, arterial spin labeling (ASL) [29][30] or to suppress signal from extracellular flowing fluid in perfused cell systems.[31][32]

However, IVIM MRI has recently undergone a striking revival for applications not in the brain, but throughout the body as well.[33] Following earlier encouraging results in the kidneys,[34][35][36] or even the heart,[37] IVIM MRI really took off for liver applications. For instance, Luciani et al.[38] found that D* was significantly reduced in cirrhotic patients, which, according to the IVIM model, points out to reduce blood velocity (and flow). (Another theoretical, rather unlikely interpretation would be that capillary segments become longer or more straight in those patients with liver fibrosis). The perfusion fraction, f, which is linked to blood volume in the IVIM model, remained normal, confirming earlier results by Yamada et al.[39] Though, blood volume is expected to be reduced in liver cirrhosis.

One has to keep in mind that IVIM imaging has a differential sensitivity to vessel types, according to the range of motion sensitization (b values) which are used.[40][41] Signal from large vessels with rapid flow disappears quickly with very low b values, while smaller vessels with slower flow might still contribute to the IVIM signal acquired with b values larger than 200 s/mm². Many more applications are now under investigation, especially for imaging of patients suspected of cancer in the body (prostate, liver, kidney, pancreas, etc.) [12] and human placenta.[42][43] A key feature of IVIM diffusion MRI is that it does not involve contrast agents, and it may appear as an interesting alternative for perfusion MRI in some patients at risk for Nephrogenic Systemic Fibrosis (NSF).

References

  1. Le Bihan, D; Breton, E; Lallemand, D; Grenier, P; Cabanis, E; Laval-Jeantet, M (1986). "MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders". Radiology. 161 (2): 401–7. doi:10.1148/radiology.161.2.3763909. PMID 3763909.
  2. 1 2 3 4 5 6 7 Le Bihan, D; Breton, E; Lallemand, D; Aubin, ML; Vignaud, J; Laval-Jeantet, M (1988). "Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging". Radiology. 168 (2): 497–505. doi:10.1148/radiology.168.2.3393671. PMID 3393671.
  3. 1 2 Le Bihan, D. (1990). "Magnetic resonance imaging of perfusion". Magnetic Resonance in Medicine. 14 (2): 283–292. doi:10.1002/mrm.1910140213.
  4. 1 2 3 Le Bihan, D; Turner, R (1992). "The capillary network: a link between IVIM and classical perfusion.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 27 (1): 171–8. doi:10.1002/mrm.1910270116. PMID 1435202.
  5. Karger, J; Pfeifer, H.; Heink,W. (1988). "Principles and applications of self-diffusion measurements by nuclear magnetic resonance". Advances in Magnetic Resonance In Advances in Magnetic Resonance. 12: 1–89. doi:10.1016/b978-0-12-025512-2.50004-x.
  6. Niendorf, T; Dijkhuizen, RM; Norris, DG; van Lookeren Campagne, M; Nicolay, K (Dec 1996). "Biexponential diffusion attenuation in various states of brain tissue: implications for diffusion-weighted imaging.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 36 (6): 847–57. doi:10.1002/mrm.1910360607. PMID 8946350.
  7. Chabert, S; Meca, C.C.; Le Bihan, D. "Relevance of the information about the diffusion distribution in vivo given by kurtosis in q-space imaging". Proceedings, 12th ISMRM annual meeting: 1238.
  8. Jensen, Jens H.; Helpern, Joseph A. (2010). "MRI quantification of non-Gaussian water diffusion by kurtosis analysis". NMR in Biomedicine. 23 (7): 698–710. doi:10.1002/nbm.1518.
  9. Pekar, James; Moonen, Chrit T. W.; van Zijl, Peter C. M. (1992). "On the precision of diffusion/perfusion imaging by gradient sensitization". Magnetic Resonance in Medicine. 23 (1): 122–129. doi:10.1002/mrm.1910230113.
  10. 1 2 Wirestam, R; Brockstedt, S; Lindgren, A; Geijer, B; Thomsen, C; Holtås, S; Ståhlberg, F (1997). "The perfusion fraction in volunteers and in patients with ischaemic stroke.". Acta radiologica. 38 (6): 961–4. doi:10.1080/02841859709172110. PMID 9394649.
  11. Le Bihan, D; Turner, R; Moonen, CT; Pekar, J (1991). "Imaging of diffusion and microcirculation with gradient sensitization: design, strategy, and significance.". Journal of magnetic resonance imaging : JMRI. 1 (1): 7–28. doi:10.1002/jmri.1880010103. PMID 1802133.
  12. 1 2 Koh, DM; Collins, DJ; Orton, MR (2011). "Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges.". AJR. American journal of roentgenology. 196 (6): 1351–61. doi:10.2214/AJR.10.5515. PMID 21606299.
  13. Henkelman, RM (1990). "Does IVIM measure classical perfusion?". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 16 (3): 470–5. doi:10.1002/mrm.1910160313. PMID 2077337.
  14. Le Bihan, D; Turner, R (1992). "The capillary network: a link between IVIM and classical perfusion.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 27 (1): 171–8. doi:10.1002/mrm.1910270116. PMID 1435202.
  15. Le Bihan, D (1988). "Intravoxel incoherent motion imaging using steady-state free precession". Magnetic Resonance in Medicine. 7 (3): 346–351. doi:10.1002/mrm.1910070312.
  16. Le Bihan, D; Moonen, CT; van Zijl, PC; Pekar, J; DesPres, D (1991). "Measuring random microscopic motion of water in tissues with MR imaging: a cat brain study.". Journal of computer assisted tomography. 15 (1): 19–25. doi:10.1097/00004728-199101000-00002. PMID 1987198.
  17. Le Bihan, D; Douek, P; Argyropoulou, M; Turner, R; Patronas, N; Fulham, M (1993). "Diffusion and perfusion magnetic resonance imaging in brain tumors.". Topics in magnetic resonance imaging : TMRI. 5 (1): 25–31. doi:10.1097/00002142-199300520-00005. PMID 8416686.
  18. Chenevert, TL; Pipe, JG (1991). "Effect of bulk tissue motion on quantitative perfusion and diffusion magnetic resonance imaging.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 19 (2): 261–5. doi:10.1002/mrm.1910190212. PMID 1881313.
  19. Neil, JJ; Bosch, CS; Ackerman, JJ (1994). "An evaluation of the sensitivity of the intravoxel incoherent motion (IVIM) method of blood flow measurement to changes in cerebral blood flow.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 32 (1): 60–5. doi:10.1002/mrm.1910320109. PMID 8084238.
  20. Song, AW; Wong, EC; Tan, SG; Hyde, JS (Feb 1996). "Diffusion weighted fMRI at 1.5 T.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 35 (2): 155–8. doi:10.1002/mrm.1910350204. PMID 8622577.
  21. Gangstead, SL; Song, AW (Aug 2002). "On the timing characteristics of the apparent diffusion coefficient contrast in fMRI.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 48 (2): 385–8. doi:10.1002/mrm.10189. PMID 12210948.
  22. Jin, T; Zhao, F; Kim, SG (2006). "Sources of functional apparent diffusion coefficient changes investigated by diffusion-weighted spin-echo fMRI.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 56 (6): 1283–92. doi:10.1002/mrm.21074. PMID 17051530.
  23. Song, AW; Woldorff, MG; Gangstead, S; Mangun, GR; McCarthy, G (2002). "Enhanced spatial localization of neuronal activation using simultaneous apparent-diffusion-coefficient and blood-oxygenation functional magnetic resonance imaging.". NeuroImage. 17 (2): 742–50. doi:10.1006/nimg.2002.1217. PMID 12377149.
  24. Boxerman, JL; Bandettini, PA; Kwong, KK; Baker, JR; Davis, TL; Rosen, BR; Weisskoff, RM (1995). "The intravascular contribution to fMRI signal change: Monte Carlo modeling and diffusion-weighted studies in vivo.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 34 (1): 4–10. doi:10.1002/mrm.1910340103. PMID 7674897.
  25. Lee, SP; Silva, AC, Kim, SG (2002). "Comparison of diffusion-weighted high-resolution CBF and spin-echo BOLD fMRI at 9.4 T.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 47 (4): 736–41. doi:10.1002/mrm.10117. PMID 11948735.
  26. Duong, TQ; Yacoub, E; Adriany, G; Hu, X; Ugurbil, K; Kim, SG (2003). "Microvascular BOLD contribution at 4 and 7 T in the human brain: gradient-echo and spin-echo fMRI with suppression of blood effects.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 49 (6): 1019–27. doi:10.1002/mrm.10472. PMID 12768579.
  27. Song, AW; Li, T (2003). "Improved spatial localization based on flow-moment-nulled and intra-voxel incoherent motion-weighted fMRI.". NMR in biomedicine. 16 (3): 137–43. doi:10.1002/nbm.819. PMID 12884357.
  28. Michelich, CR; Song, AW; Macfall, JR (2006). "Dependence of gradient-echo and spin-echo BOLD fMRI at 4 T on diffusion weighting.". NMR in biomedicine. 19 (5): 566–72. doi:10.1002/nbm.1035. PMID 16598695.
  29. Kim, T; Kim, SG (2006). "Quantification of cerebral arterial blood volume using arterial spin labeling with intravoxel incoherent motion-sensitive gradients.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 55 (5): 1047–57. doi:10.1002/mrm.20867. PMID 16596632.
  30. Silva, AC; Williams, DS; Koretsky, AP (1997). "Evidence for the exchange of arterial spin-labeled water with tissue water in rat brain from diffusion-sensitized measurements of perfusion.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 38 (2): 232–7. doi:10.1002/mrm.1910380211. PMID 9256102.
  31. Van Zijl, PC; Moonen, CT; Faustino, P; Pekar, J; Kaplan, O; Cohen, JS (1991). "Complete separation of intracellular and extracellular information in NMR spectra of perfused cells by diffusion-weighted spectroscopy.". Proceedings of the National Academy of Sciences of the United States of America. 88 (8): 3228–32. doi:10.1073/pnas.88.8.3228. PMC 51419Freely accessible. PMID 2014244.
  32. Zhao, L; Sukstanskii, AL; Kroenke, CD; Song, J; Piwnica-Worms, D; Ackerman, JJ; Neil, JJ (2008). "Intracellular water specific MR of microbead-adherent cells: HeLa cell intracellular water diffusion.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 59 (1): 79–84. doi:10.1002/mrm.21440. PMC 2730972Freely accessible. PMID 18050315.
  33. Le Bihan, D. (2008). "Intravoxel Incoherent Motion Perfusion MR Imaging: A Wake-Up Call". Radiology. 249 (3): 748–752. doi:10.1148/radiol.2493081301. PMID 19011179.
  34. Powers, TA; Lorenz, CH; Holburn, GE; Price, RR (1991). "Renal artery stenosis: in vivo perfusion MR imaging.". Radiology. 178 (2): 543–8. doi:10.1148/radiology.178.2.1987621. PMID 1987621.
  35. Pickens DR, 3rd; Jolgren, DL; Lorenz, CH; Creasy, JL; Price, RR (1992). "Magnetic resonance perfusion/diffusion imaging of the excised dog kidney.". Investigative radiology. 27 (4): 287–92. doi:10.1097/00004424-199204000-00005. PMID 1601618.
  36. Tsuda, K; Murakami, T; Sakurai, K; Harada, K; Kim, T; Takahashi, S; Tomoda, K; Narumi, Y; Nakamura, H; Izumi, M; Tsukamoto, T (1997). "[Preliminary evaluation of the apparent diffusion coefficient of the kidney with a spiral IVIM sequence].". Nihon Igaku Hoshasen Gakkai zasshi. Nippon acta radiologica. 57 (1): 19–22. PMID 9038058.
  37. Callot, Virginie; Bennett, Eric; Decking, Ulrich K.M.; Balaban, Robert S.; Wen, Han (2003). "In vivo study of microcirculation in canine myocardium using the IVIM method". Magnetic Resonance in Medicine. 50 (3): 531–540. doi:10.1002/mrm.10568.
  38. Luciani, A.; Vignaud, A.; Cavet, M.; Tran Van Nhieu, J.; Mallat, A.; Ruel, L.; Laurent, A.; Deux, J.-F.; Brugieres, P.; Rahmouni, A. (2008). "Liver Cirrhosis: Intravoxel Incoherent Motion MR Imaging--Pilot Study". Radiology. 249 (3): 891–899. doi:10.1148/radiol.2493080080.
  39. Yamada, I; Aung, W; Himeno, Y; Nakagawa, T; Shibuya, H (1999). "Diffusion coefficients in abdominal organs and hepatic lesions: evaluation with intravoxel incoherent motion echo-planar MR imaging.". Radiology. 210 (3): 617–23. doi:10.1148/radiology.210.3.r99fe17617. PMID 10207458.
  40. Lorenz, Christine H.; Pickens, David R.; Puffer, Donald B.; Price, Ronald R. (1991). "Magnetic resonance diffusion/perfusion phantom experiments". Magnetic Resonance in Medicine. 19 (2): 254–260. doi:10.1002/mrm.1910190211.
  41. Kennan, RP; Gao, JH; Zhong, J; Gore, JC (1994). "A general model of microcirculatory blood flow effects in gradient sensitized MRI.". Medical physics. 21 (4): 539–45. doi:10.1118/1.597170. PMID 8058020.
  42. Moore, RJ; Strachan, BK; Tyler, DJ; Duncan, KR; Baker, PN; Worthington, BS; Johnson, IR; Gowland, PA (2000). "In utero perfusing fraction maps in normal and growth restricted pregnancy measured using IVIM echo-planar MRI.". Placenta. 21 (7): 726–32. doi:10.1053/plac.2000.0567. PMID 10985977.
  43. Moore, RJ; Issa, B; Tokarczuk, P; Duncan, KR; Boulby, P; Baker, PN; Bowtell, RW; Worthington, BS; Johnson, IR; Gowland, PA (2000). "In vivo intravoxel incoherent motion measurements in the human placenta using echo-planar imaging at 0.5 T.". Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. 43 (2): 295–302. doi:10.1002/(sici)1522-2594(200002)43:2<295::aid-mrm18>3.0.co;2-2. PMID 10680695.
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