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Chronic Kidney Disease and Progression

Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis

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Article: 2367021 | Received 01 May 2024, Accepted 06 Jun 2024, Published online: 28 Jun 2024

References

  • Drawz P, Rahman M. Chronic kidney disease. Ann Intern Med. 2015;162(11):1–15. doi: 10.7326/AITC201506020.
  • Wu Q, Sun S, Wei L, et al. Twist1 regulates macrophage plasticity to promote renal fibrosis through galectin-3. Cell Mol Life Sci. 2022;79(3):137. doi: 10.1007/s00018-022-04137-0.
  • Luyckx VA, Cherney DZI, Bello AK. Preventing CKD in developed countries. Kidney Int Rep. 2019;5(3):263–277. doi: 10.1016/j.ekir.2019.12.003.
  • von Stillfried S, Apitzsch JC, Ehling J, et al. Contrast-enhanced CT imaging in patients with chronic kidney disease. Angiogenesis. 2016;19(4):525–535. doi: 10.1007/s10456-016-9524-7.
  • Triantopoulou C, Rizos S, Bourli A, et al. Localized unilateral perirenal fibrosis: CT and MRI appearances. Eur Radiol. 2002;12(11):2743–2746. doi: 10.1007/s00330-001-1184-2.
  • Weitzel WF, Kim K, Rubin JM, et al. Feasibility of applying ultrasound strain imaging to detect renal transplant chronic allograft nephropathy. Kidney Int. 2004;65(2):733–736. doi: 10.1111/j.1523-1755.2004.00435.x.
  • Nassar MK, Khedr D, Abu-Elfadl HG, et al. Diffusion tensor imaging in early prediction of renal fibrosis in patients with renal disease: functional and histopathological correlations. Int J Clin Pract. 2021;75(4):e13918. doi: 10.1111/ijcp.13918.
  • Andersen UB, Haddock B, Asmar A. Multiparametric magnetic resonance imaging: a robust tool to test pathogenesis and pathophysiology behind nephropathy in humans. Clin Physiol Funct Imaging. 2023;43(4):207–210. doi: 10.1111/cpf.12818.
  • Grams ME, Sang Y, Ballew SH, et al. A meta-analysis of the association of estimated GFR, albuminuria, age, race, and sex with acute kidney injury. Am J Kidney Dis. 2015;66(4):591–601. doi: 10.1053/j.ajkd.2015.02.337.
  • Poggio ED, McClelland RL, Blank KN, et al. Systematic review and meta-analysis of native kidney biopsy complications. Clin J Am Soc Nephrol. 2020;15(11):1595–1602. doi: 10.2215/CJN.04710420.
  • Corapi KM, Chen JL, Balk EM, et al. Bleeding complications of native kidney biopsy: a systematic review and meta-analysis. Am J Kidney Dis. 2012;60(1):62–73. doi: 10.1053/j.ajkd.2012.02.330.
  • Jaber BL. Clinical nephrology. Curr Opin Nephrol Hypertens. 2017;26(2):105. doi: 10.1097/MNH.0000000000000307.
  • Maurer MH, Härmä KH, Thoeny H. Diffusion-weighted genitourinary imaging. Radiol Clin North Am. 2017;55(2):393–411. doi: 10.1016/j.rcl.2016.10.014.
  • Saritas T, Kramann R. Kidney allograft fibrosis: diagnostic and therapeutic strategies. Transplantation. 2021;105(10):e114–e130. doi: 10.1097/TP.0000000000003678.
  • Li J, An C, Kang L, et al. Recent advances in magnetic resonance imaging assessment of renal fibrosis. Adv Chronic Kidney Dis. 2017;24(3):150–153. doi: 10.1053/j.ackd.2017.03.005.
  • Li S, Wang F, Sun D. The renal microcirculation in chronic kidney disease: novel diagnostic methods and therapeutic perspectives. Cell Biosci. 2021;11(1):90. doi: 10.1186/s13578-021-00606-4.
  • McInnes MDF, Moher D, Thombs BD, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. JAMA. 2018;319(4):388–396. doi: 10.1001/jama.2017.19163.
  • Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–536. doi: 10.7326/0003-4819-155-8-201110180-00009.
  • Chen Z, Chen J, Chen H, et al. A nomogram based on shear wave elastography for assessment of renal fibrosis in patients with chronic kidney disease. J Nephrol. 2023;36(3):719–729. doi: 10.1007/s40620-022-01521-8.
  • Chen Z, Chen J, Chen H, et al. Evaluation of renal fibrosis in patients with chronic kidney disease by shear wave elastography: a comparative analysis with pathological findings. Abdom Radiol. 2022;47(2):738–745. doi: 10.1007/s00261-021-03351-x.
  • Chen Z, Ying MTC, Wang Y, et al. Ultrasound-based radiomics analysis in the assessment of renal fibrosis in patients with chronic kidney disease. Abdom Radiol. 2023;48(8):2649–2657. doi: 10.1007/s00261-023-03965-3.
  • Yang X, Hou FL, Zhao C, et al. The role of real-time shear wave elastography in the diagnosis of idiopathic nephrotic syndrome and evaluation of the curative effect. Abdom Radiol. 2020;45(8):2508–2517. doi: 10.1007/s00261-020-02460-3.
  • He L, Dan G, Yuanbo S, et al. The diagnostic efficacy of diffusion tensor imaging generated by gadolinium-based magnetic resonance imaging for patients with chronic kidney disease. Medicine. 2022;101(27):e29291. doi: 10.1097/MD.0000000000029291.
  • Leong SS, Wong JHD, Md Shah MN, et al. Shear wave elastography accurately detects chronic changes in renal histopathology. Nephrology. 2021;26(1):38–45. doi: 10.1111/nep.13805.
  • Cui G, Yang Z, Zhang W, et al. Evaluation of acoustic radiation force impulse imaging for the clinicopathological typing of renal fibrosis. Exp Ther Med. 2014;7(1):233–235. doi: 10.3892/etm.2013.1377.
  • Mohamed Osman NM, Abdel Kader M, Aziz Nasr TAEL, et al. The role of diffusion-weighted MRI and apparent diffusion coefficient in assessment of diabetic kidney disease: preliminary experience study. Int J Nephrol Renovasc Dis. 2021;14:1–10. doi: 10.2147/IJNRD.S254022.
  • Chen Z, Ying TC, Chen J, et al. Using elastography-based multilayer perceptron model to evaluate renal fibrosis in chronic kidney disease. Ren Fail. 2023;45(1):2202755. doi: 10.1080/0886022X.2023.2202755.
  • Hua C, Qiu L, Zhou L, et al. Value of multiparametric magnetic resonance imaging for evaluating chronic kidney disease and renal fibrosis. Eur Radiol. 2023;33(8):5211–5221. doi: 10.1007/s00330-023-09674-1.
  • Samir AE, Allegretti AS, Zhu Q, et al. Shear wave elastography in chronic kidney disease: a pilot experience in native kidneys. BMC Nephrol. 2015;16(1):119. doi: 10.1186/s12882-015-0120-7.
  • Zhu M, Ma L, Yang W, et al. Elastography ultrasound with machine learning improves the diagnostic performance of traditional ultrasound in predicting kidney fibrosis. J Formos Med Assoc. 2022;121(6):1062–1072. doi: 10.1016/j.jfma.2021.08.011.
  • Friedli I, Crowe LA, de Perrot T, et al. Comparison of readout-segmented and conventional single-shot for echo-planar diffusion-weighted imaging in the assessment of kidney interstitial fibrosis. J Magn Reson Imaging. 2017;46(6):1631–1640. doi: 10.1002/jmri.25687.
  • Radulescu D, Peride I, Petcu LC, et al. Supersonic shear wave ultrasonography for assessing tissue stiffness in native kidney. Ultrasound Med Biol. 2018;44(12):2556–2568. doi: 10.1016/j.ultrasmedbio.2018.07.001.
  • Wang L, Xia P, Lv K, et al. Assessment of renal tissue elasticity by acoustic radiation force impulse quantification with histopathological correlation: preliminary experience in chronic kidney disease. Eur Radiol. 2014;24(7):1694–1699. doi: 10.1007/s00330-014-3162-5.
  • Wei CG, Zeng Y, Zhang R, et al. Native T1 mapping for non-invasive quantitative evaluation of renal function and renal fibrosis in patients with chronic kidney disease. Quant Imaging Med Surg. 2023;13(8):5058–5071. doi: 10.21037/qims-22-1304.
  • Wu J, Shi Z, Zhang Y, et al. Native T1 mapping in assessing kidney fibrosis for patients with chronic glomerulonephritis. Front Med. 2021;8:772326. doi: 10.3389/fmed.2021.772326.
  • Liu Y, Zhang GM, Peng X, et al. Diffusion kurtosis imaging as an imaging biomarker for predicting prognosis in chronic kidney disease patients. Nephrol Dial Transplant. 2022;37(8):1451–1460. doi: 10.1093/ndt/gfab229.
  • Yang X, Yu N, Yu J, et al. Virtual touch tissue quantification for assessing renal pathology in idiopathic nephrotic syndrome. Ultrasound Med Biol. 2018;44(7):1318–1326. doi: 10.1016/j.ultrasmedbio.2018.02.012.
  • Bob F, Grosu I, Sporea I, et al. Ultrasound-based shear wave elastography in the assessment of patients with diabetic kidney disease. Ultrasound Med Biol. 2017;43(10):2159–2166. doi: 10.1016/j.ultrasmedbio.2017.04.019.
  • Barr RG. US-targeted microbubbles to assess liver fibrosis. Radiology. 2022;304(2):483–484. doi: 10.1148/radiol.220595.
  • Cè M, Felisaz PF, Alì M, et al. Ultrasound elastography in chronic kidney disease: a systematic review and meta-analysis. J Med Ultrason (2001). 2023;50(3):381–415. doi: 10.1007/s10396-023-01304-z.
  • Cao H, Ke B, Lin F, et al. Shear wave elastography for assessment of biopsy-proven renal fibrosis: a systematic review and meta-analysis. Ultrasound Med Biol. 2023;49(5):1037–1048. doi: 10.1016/j.ultrasmedbio.2023.01.003.
  • Mo XL, Meng HY, Wu YY, et al. Shear wave elastography in the evaluation of renal parenchymal stiffness in patients with chronic kidney disease: a meta-analysis. J Clin Med Res. 2022;14(2):95–105. doi: 10.14740/jocmr4621.
  • Sasaki Y, Hirooka Y, Kawashima H, et al. Measurements of renal shear wave velocities in chronic kidney disease patients. Acta Radiol. 2018;59(7):884–890. doi: 10.1177/0284185117734417.
  • Ozturk A, Olson MC, Samir AE, et al. Liver fibrosis assessment: MR and US elastography. Abdom Radiol. 2022;47(9):3037–3050. doi: 10.1007/s00261-021-03269-4.
  • Yu YM, Wang W, Wen J, et al. Detection of renal allograft fibrosis with MRI: arterial spin labeling outperforms reduced field-of-view IVIM. Eur Radiol. 2021;31(9):6696–6707. doi: 10.1007/s00330-021-07818-9.
  • Mao W, Zhou J, Zeng M, et al. Chronic kidney disease: pathological and functional evaluation with intravoxel incoherent motion diffusion-weighted imaging. J Magn Reson Imaging. 2018;47(5):1251–1259. doi: 10.1002/jmri.25861.
  • Wang Y, Zhang X, Wang B, et al. Evaluation of renal pathophysiological processes induced by an iodinated contrast agent in a diabetic rabbit model using intravoxel incoherent motion and blood oxygenation level-dependent magnetic resonance imaging. Korean J Radiol. 2019;20(5):830–843. doi: 10.3348/kjr.2018.0757.
  • Zhang JL, Lee VS. Renal perfusion imaging by MRI. J Magn Reson Imaging. 2020;52(2):369–379. doi: 10.1002/jmri.26911.
  • Selvaraj EA, Mózes FE, Jayaswal ANA, et al. Diagnostic accuracy of elastography and magnetic resonance imaging in patients with NAFLD: a systematic review and meta-analysis. J Hepatol. 2021;75(4):770–785. doi: 10.1016/j.jhep.2021.04.044.
  • Sangha K, Chang ST, Cheung R, et al. Cost-effectiveness of MRE versus VCTE in staging fibrosis for nonalcoholic fatty liver disease (NAFLD) patients with advanced fibrosis. Hepatology. 2023;77(5):1702–1711. doi: 10.1097/HEP.0000000000000262.
  • Ajmera V, Cepin S, Tesfai K, et al. A prospective study on the prevalence of NAFLD, advanced fibrosis, cirrhosis and hepatocellular carcinoma in people with type 2 diabetes. J Hepatol. 2023;78(3):471–478. doi: 10.1016/j.jhep.2022.11.010.
  • Korsmo MJ, Ebrahimi B, Eirin A, et al. Magnetic resonance elastography noninvasively detects in vivo renal medullary fibrosis secondary to swine renal artery stenosis. Invest Radiol. 2013;48(2):61–68. doi: 10.1097/RLI.0b013e31827a4990.
  • Zhang J, Yu Y, Liu X, et al. Evaluation of renal fibrosis by mapping histology and magnetic resonance imaging. Kidney Dis. 2021;7(2):131–142. doi: 10.1159/000513332.
  • Bandara MS, Gurunayaka B, Lakraj G, et al. Ultrasound based radiomics features of chronic kidney disease. Acad Radiol. 2022;29(2):229–235. doi: 10.1016/j.acra.2021.01.006.
  • Zhao D, Wang W, Tang T, et al. Current progress in artificial intelligence-assisted medical image analysis for chronic kidney disease: a literature review. Comput Struct Biotechnol J. 2023;21:3315–3326. doi: 10.1016/j.csbj.2023.05.029.
  • Li LP, Leidner AS, Wilt E, et al. Radiomics-based image phenotyping of kidney apparent diffusion coefficient maps: preliminary feasibility & efficacy. J Clin Med. 2022;11(7):1972. doi: 10.3390/jcm11071972.
  • Yu Q, Liu Y, Xie X, et al. Radiomics-based method for diagnosis of calciphylaxis in patients with chronic kidney disease using computed tomography. Quant Imaging Med Surg. 2021;11(11):4617–4626. doi: 10.21037/qims-20-1211.
  • Meng N, Fang T, Feng P, et al. Amide proton transfer-weighted imaging and multiple models diffusion-weighted imaging facilitates preoperative risk stratification of early-stage endometrial carcinoma. J Magn Reson Imaging. 2021;54(4):1200–1211. doi: 10.1002/jmri.27684.
  • Li J, Lin L, Gao X, et al. Amide proton transfer weighted and intravoxel incoherent motion imaging in evaluation of prognostic factors for rectal adenocarcinoma. Front Oncol. 2021;11:783544. doi: 10.3389/fonc.2021.783544.
  • Nishie A, Asayama Y, Ishigami K, et al. Amide proton transfer imaging to predict tumor response to neoadjuvant chemotherapy in locally advanced rectal cancer. J Gastroenterol Hepatol. 2019;34(1):140–146. doi: 10.1111/jgh.14315.