Rationale and Objectives
Magnetic resonance elastography (MRE) images the propagation of mechanical shear waves in tissue and uses that information to generate quantitative measures of tissue stiffness. Hepatic MRE has been successfully performed in thousands of patients, with good correlation between histologic grade of fibrosis and tissue stiffness. There has been no prior investigation of the utility of MRE for the assessment of kidney transplants. The aims of this study were to prospectively evaluate the feasibility of MRE in a small group of kidney transplant recipients and to correlate the measured magnetic resonance elastographic stiffness values with biopsy-proven histopathologic fibrosis.
Materials and Methods
MRE of renal transplants was performed in 11 patients returning for protocol allograft biopsies. Calculated tissue stiffness values were compared to histologic degree of fibrosis in nine of the 11 patients.
Results
The mean stiffness of two patients with moderate interstitial fibrosis was higher than the mean of six patients with mild interstitial fibrosis, but not significantly so (90 Hz, P = .12; 120 Hz, P = .17; 150 Hz, P = .26). The mean stiffness of the two patients with moderate interstitial fibrosis was slightly greater than the mean of one patient with no significant interstitial fibrosis at 90 Hz ( P = .78) and slightly less at 120 and 150 Hz ( P = .88 and P = .76). The mean stiffness of the six patients with mild interstitial fibrosis did not differ significantly from that of the one patient with no interstitial fibrosis (90 Hz, P = .35; 120 Hz, P = .22; 150 Hz, P = .16).
Conclusions
Preliminary results demonstrate feasibility and support known multifactorial influences on renal stiffness.
The incidence of renal allograft rejection has been considerably reduced by the introduction of immunosuppressive drugs. However, it remains difficult to optimize antirejection therapy for transplant recipients, because of the lack of noninvasive biomarkers for rejection. Kidney transplant (KTx) biopsy with histopathologic examination is therefore frequently necessary to guide therapy in patients with diminishing renal function. Ultrasound-guided KTx biopsies for interval histopathologic assessment are obtained 4 months, 1 year, 2 years, and 5 years after transplantation at our institution. Because of strict criteria for tissue adequacy outlined in the Banff 97 classification , an international schema developed in the early 1990s for classifying renal allograft pathology, three 18-gauge core biopsy specimens are typically acquired, but the number of specimens can range from one (usually in the setting of an immediate complication) to five. As would be expected, the value of this histopathologic gold standard is heavily dependent on the biopsy specimen. Investigations of specimen inadequacy have been highly variable, with one study of 1171 biopsies reporting 23% inadequate biopsies using a 16-gauge device and 47% inadequate biopsies using an 18-gauge device , another study of 345 biopsies reporting 5.2% nondiagnostic biopsies using a 14-gauge biopsy device , and yet another study of 294 biopsies reporting only 5% inadequate biopsies using an 18-gauge device and a cortical tangential approach . The rate of major complications requiring additional intervention beyond observation, such as blood transfusion, surgery, or embolization for large perirenal hematomas, arteriovenous fistulas, or urinomas, also varies greatly, ranging from <1% to <3% . Loss of the allograft and death have also been described.
Magnetic resonance (MR) elastography (MRE) is a noninvasive, phase contrast–based technique that images the propagation of mechanical shear waves in tissue and uses that information to generate quantitative measures of tissue stiffness in kilopascals. Hepatic MRE has been successfully performed in thousands of patients, including liver transplant recipients, in whom good correlation between histologic grade of fibrosis and tissue stiffness measured with MRE has been established . Recent investigations now suggest that changes in the viscoelastic properties of tissue may reflect derangements in the extracellular matrix, which can be a harbinger of developing pathology .
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Materials and methods
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Imaging Technique
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Data Analysis
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Pathology
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Results
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Table 1
Patient Characteristics
Patient Age (y)/Sex Transplant History eGFR (mL/min/1.73 m 2 ) BP (mm Hg) 1 31/M First transplant, living related
44 103/69 2 53/M First transplant, living unrelated
58 123/79 3 63/F First transplant, living donor
45 117/69 4 40/M Fourth transplant, deceased donor
27 124/87 5 56/M First transplant, living donor
25 126/84 6 55/M First transplant, living related
53 136/81 7 58/F First transplant, living donor
46 142/77 8 31/F First transplant, living related
31 102/67 9 33/F First transplant, living related
26 115/77 10 71/M First transplant, living related
27 128/61
BP, blood pressure; eGFR, estimated glomerular filtration rate; IgA, immunoglobulin A; MPGN, membranoproliferative glomerulonephritis; PCKD, polycystic kidney disease.
The most common etiology for renal failure requiring transplantation was proliferative glomerulonephritis (four of 10 patients). One patient (patient 4) had received multiple transplants; the others still had their initial transplants. One patient presented for the first annual protocol biopsy, four patients for the 2-year protocol biopsy, one patient for a 4-year posttransplant biopsy, and four patients for the 5-year protocol biopsy.
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Table 2
Pathology
Patient Pathologic Diagnosis Banff Classification and Scoring ∗ g i t v ah cg ci ct cv mm ptc c4d 1 Mild interstitial fibrosis; patchy tubular atrophy 0 0 0 0 2 0 1 1 1 1 0 0 2 Moderate interstitial fibrosis; tubular atrophy 0 1–2 0 0 0 2 2 2 2 1 0 0 3 Inadequate biopsy sample consisting of mostly renal medulla (on LM comment, tubules showed no significant interstitial changes) NA NA NA NA NA NA NA NA NA NA NA NA 4 Moderate interstitial fibrosis; tubular atrophy >30% cortex 2 0 0 0 3 2 2 2 1 0 3 0 5 Mild interstitial fibrosis and tubular atrophy 0 0 0 0 0 0 0 1 1 0 0 0 6 Mild interstitial fibrosis and tubular atrophy (additional comment: borderline cellular rejection, except severe tubulitis in inflamed area) 0 1 3 0 0 0 1 0 0 NR 0 0 7 No significant interstitial fibrosis or tubular atrophy; minimal focal inflammation 0 0 0 0 0 0 0 0 0 NR 0 NR 8 Mild interstitial fibrosis and tubular atrophy 0 0 0 0 1 0 1 1 2 0 0 NR 9 Mild tubular atrophy and interstitial fibrosis (15% cortex) 0 0 0 0 2 3 1 1 2 NR 0 0 10 Mild interstitial fibrosis and tubular atrophy 0 0 0 0 0 0 1 1 1 NR 0 NR
NA, not available; NR, not reported.
Pathologic reports including the Banff scores yielded six patients with diagnoses of mild interstitial fibrosis, two patients with moderate interstitial fibrosis, one patient with no significant interstitial fibrosis, and one patient with an inadequate tissue specimen for pathologic evaluation. Some of the Banff scores were not directly reported in the pathologic reports and are noted.
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Table 3
Tissue Stiffness Values for Each Patient at 90-Hz, 120-Hz, and 150-Hz Vibrations
Fibrosis Patient Renal Tissue Stiffness (kPa) 90 Hz 120 Hz 150 Hz Mean Mean Mean Not significant 7 6.9 6.9 9.4 9.4 11.6 11.6 Mild 1 6.7 6.0 8.1 7.9 ∗ NA 9.1 ∗ 5 6.2 8.1 9.7 6 6.9 9.3 10.4 8 4.4 6.0 6.9 9 5.9 8.0 9.0 10 5.9 8.1 9.4 Moderate 2 7.4 7.2 9.6 9.2 NA 11.0 4 7.0 8.8 11.0 Nondiagnostic 3 6.4 6.4 8.5 8.5 12 12
NA, not available.
Tissue stiffness values were determined using a 3 × 3 × 3 direct inversion directional filter algorithm. The level of pathologic fibrosis on the basis of the Banff criteria is noted for each patient. Magnetic resonance elastography at 150-Hz vibrations was not performed on patients 1 and 2.
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Table 4
Repeatability Results for Patient 5 Returning 22 Months Later
Repeatability Results Renal Tissue Stiffness (kPa) 90 Hz 120 Hz 150 Hz MRE First exam 5.2 ± 1.9 7.0 ± 2.3 8.9 ± 2.9 (8.9 ± 2.3) Second exam 5.5 ± 1.7 7.5 ± 2.1 9.7 ± 2.5 (9.7 ± 2.2) Third exam 5.4 ± 1.7 7.3 ± 4.5 9.5 ± 36.2 (8.8 ± 2.1) ∗ Mean 5.4 7.3 9.4 (9.1) Standard deviation 0.2 0.3 0.4 (0.5) Coefficient of variation 2.9% 3.5% 4.4% (5.4%)
MRE, magnetic resonance elastography.
MRE was repeated three times with complete disassembly and reassembly of the apparatus between each repetition for patient 5, who returned for clinical follow-up 22 months later.
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Discussion
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Conclusions
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Acknowledgment
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References
1. Racusen L.C., Solez K., Colvin R.B., et. al.: The Banff 97 working classification of renal allograft pathology. Kidney Int 1999; 55: pp. 713-723.
2. Schwarz A., Gwinner W., Hiss M., et. al.: Safety and adequacy of renal transplant protocol biopsies. Am J Transplant 2005; 5: pp. 1992-1996.
3. Preda A., Van Dijk L.C., Van Oostaijen J.A., et. al.: Complication rate and diagnostic yield of 515 consecutive ultrasound-guided biopsies of renal allografts and native kidneys using a 14-gauge Biopty gun. Eur Radiol 2003; 13: pp. 527-530.
4. Patel M.D., Phillips C.J., Young S.W., et. al.: US-guided renal transplant biopsy: efficacy of a cortical tangential approach. Radiology 2010; 256: pp. 290-296.
5. Furness P.N., Philpott C.M., Chorbadjian M.T., et. al.: Protocol biopsy of the stable renal transplant: a multicenter study of methods and complication rates. Transplantation 2003; 76: pp. 969-973.
6. Venkatesh S.K., Yin M., Glockner J.F., et. al.: MR elastography of liver tumors: preliminary results. AJR Am J Roentgenol 2008; 190: pp. 1534-1540.
7. Domire Z.J., McCullough M.B., Chen Q., et. al.: Wave attenuation as a measure of muscle quality as measured by magnetic resonance elastography: initial results. J Biomech 2009; 42: pp. 537-540.
8. Park W.D., Griffin M.D., Cornell L.D., et. al.: Fibrosis with inflammation at one year predicts tranplant functional decline. J Am Soc Nephrol 2010; 21: pp. 1-11.
9. Yin M., Talwalkar J.A., Glaser K.J., et. al.: Assessment of hepatic fibrosis with magnetic resonance elastography. Clin Gastroenterol Hepatol 2007; 5: pp. 1207-1213.
10. Chen J, Stanley D, Glaser K, et al. Ergonomic Flexible Drivers for Hepatic MR Elastography. In: 18 th Annual Meeting of the ISMRM, Stockholm, Sweden; 2010. p. 1052.
11. Glaser K, Ehman RL. MR Elastography Inversions Without Phase Unwrapping. In: 17 th Annual Meeting of the ISMRM, Honolulu, Hawaii; 2009. p. 4669.
12. Manduca A., Lake D.S., Kruse S.A., et. al.: Spatio-temporal directional filtering for improved inversion of MR elastography images. Med Image Anal 2003; 7: pp. 465-473.
13. Solez K., Colvin R.B., Racusen L.C., et. al.: Banff ’05 meeting report: differential diagnosis of chronic allograft injury and elimination of chronic allograft nephropathy (“CAN”). Am J Transplant 2007; 7: pp. 518-526.
14. Arani A, Plewes D, Krieger A, et al. The feasibility of endorectal MR elastrography for prostate cancer localization. Magn Reson Med. In press.
15. Kolipaka A., McGee K.P., Manduca A., et. al.: In vivo assessment of MR elastography-derived effective end-diastolic myocardial stiffness under different loading conditions. J Magn Reson Imaging 2011; 33: pp. 1224-1228.
16. Li S., Chen M., Wang W., et. al.: A feasibility study of MR elastography in the diagnosis of prostate cancer at 3.0T. Acta Radiol 2011; 52: pp. 254-258.
17. Mariappan Y.K., Glaser K., Hubmayr R.D., et. al.: MR elastography of human lung parenchyma: technical development, theoretical modeling and in vivo validation. J Magn Reson Imaging 2011; 33: pp. 1351-1361.
18. Nedredal GI, Yin M, McKenzie T, et al. Portal hypertension correlates wih splenic stiffness as measured with MR elastography. J Magn Reson Imaging. In press.
19. Murphy M.C., Glaser K.J., Manduca A., et. al.: Analysis of time reduction methods for magnetic resonance elastography of the brain. Magn Reson Imaging 2010; 28: pp. 1514-1524.
20. Granger J.P.: Pressure natriuresis: role of renal interstitial hydrostatic pressure. Hypertension 1992; 19: pp. I-9-I-17.
21. Granger J.P., Scott J.W.: Effects of renal artery pressure on interstitial pressure and Na excretion during renal vasodilation. Am J Physiol 1988; 255: pp. F828-F833.
22. Nakamura T., Sakamaki T., Kurashina T., et. al.: Effect of renal perfusion pressure on renal interstitial hydrostatic pressure and sodium excretion. Hypertension 1995; 25: pp. 866-871.
23. Warner L., Yin M., Glaser K.J., et. al.: Noninvasive in vivo assessment of renal tissue elasticity during graded renal ischemia using MR elastography. Invest Radiol 2011; 46: pp. 509-514.
24. Glodny B., Unterholzner V., Taferner B., et. al.: Normal kidney size and its influencing factors—a 64-slice MDCT study of 1.040 asymptomatic patients. BMC Urol 2009; 9:
25. Blondin D., Lanzman R.S., Mathys C., et. al.: Functional MRI of transplanted kidneys using diffusion-weighted imaging. [article in German] Rofo 2009; 181: pp. 1162-1167.
26. Eisenberger U., Thoeny H.C., Binser T., et. al.: Evaluation of renal allograft function early after transplantation with diffusion-weighted MR imaging. Eur Radiol 2010; 20: pp. 1374-1383.
27. Notohamiprodjo M., Reiser M.F., Sourbron S.P.: Diffusion and perfusion of the kidney. Eur J Radiol 2010; 76: pp. 337-347.
28. Palmucci S., Mauro L.A., Veroux P., et. al.: Magnetic resonance with diffusion-weighted imaging in the evaluation of transplanted kidneys: preliminary findings. Transplant Proc 2011; 43: pp. 960-966.
29. Thoeny H.C., Zumstein D., Simon-Zoula S., et. al.: Functional evaluation of transplanted kidneys with diffusion-weighted and BOLD MR imaging: initial experience. Radiology 2006; 241: pp. 812-821.
30. Xu J.J., Xiao W.B., Zhang L., et. al.: Value of diffusion-weighted MR imaging in diagnosis of acute rejection after renal transplantation. [article in Chinese] Zhejiang Da Xue Xue Bao Yi Xue Ban 2010; 39: pp. 163-167.
31. de Priester J.A., den Boer J.A., Christiaans M.H., et. al.: Automated quantitative evaluation of diseased and nondiseased renal transplants with MR renography. J Magn Reson Imaging 2003; 17: pp. 95-103.
32. de Priester J.A., Kessels A.G., Giele E.L., et. al.: MR renography by semiautomated image analysis: performance in renal transplant recipients. J Magn Reson Imaging 2001; 14: pp. 134-140.
33. Sadowski E.A., Djamali A., Wentland A.L., et. al.: Blood oxygen level-dependent and perfusion magnetic resonance imaging: detecting differences in oxygen bioavailability and blood flow in transplanted kidneys. Magn Reson Imaging 2010; 28: pp. 56-64.
34. Wang J.J., Hendrich K.S., Jackson E.K., et. al.: Perfusion quantitation in transplanted rat kidney by MRI with arterial spin labeling. Kidney Int 1998; 53: pp. 1783-1791.
35. Cutajar M., Clayden J.D., Clark C.A., et. al.: Test-retest reliability and repeatability of renal diffusion tensor MRI in healthy subjects. Eur J Radiol 2011; 80: pp. e263-e268.
36. Gurses B., Kilickesmez O., Tasdelen N., et. al.: Diffusion tensor imaging of the kidney at 3 Tesla: normative values and repeatability of measurements in healthy volunteers. Diagn Interv Radiol 2010; 45: pp. 1-6.
37. Kataoka M., Kido A., Yamamoto A., et. al.: Diffusion tensor imaging of kidneys with respiratory triggering: optimization of parameters to demonstrate anisotropic structures on fraction anisotropy maps. J Magn Reson Imaging 2009; 29: pp. 736-744.
38. Kido A., Kataoka M., Yamamoto A., et. al.: Diffusion tensor MRI of the kidney at 3.0 and 1.5 Tesla. Acta Radiol 2010; 51: pp. 1059-1063.
39. Stock K.F., Klein B.S., Vo Cong M.T., et. al.: ARFI-based tissue elasticity quantification in comparison to histology for the diagnosis of renal transplant fibrosis. Clin Hemorheol Microcirc 2010; 46: pp. 139-148.
40. Syversveen T., Brabrand K., Midtvedt K., et. al.: Assessment of renal allograft fibrosis by acoustic radiation force impulse quantification—a pilot study. Transpl Int 2011; 24: pp. 100-105.
41. Arndt R., Schmidt S., Loddenkemper C., et. al.: Noninvasive evaluation of renal allograft fibrosis by transient elastography—a pilot study. Transpl Int 2010; 23: pp. 871-877.