Perfusion and T
S-AKI
T1 and T2 relaxation time
multiparametric MRI
perfusion
sepsis
Journal
Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850
Informations de publication
Date de publication:
12 2023
12 2023
Historique:
revised:
13
03
2023
received:
28
07
2022
accepted:
14
03
2023
medline:
9
11
2023
pubmed:
8
4
2023
entrez:
7
4
2023
Statut:
ppublish
Résumé
Preventing sepsis-associated acute kidney injury (S-AKI) can be challenging because it develops rapidly and is often asymptomatic. Probability assessment of disease progression for therapeutic follow-up and outcome are important to intervene and prevent further damage. To establish a noninvasive multiparametric MRI (mpMRI) tool, including T Preclinical randomized prospective study. One hundred and forty adult female SD rats (65 control and 75 sepsis). 9.4T; T Experiment 1: To identify renal injury in relation to sepsis severity, serum creatinine levels were determined (31 control and 35 sepsis). Experiment 2: Animals underwent mpMRI (T Mann-Whitney U test, Spearman/Pearson correlation (r), P < 0.05 was considered statistically significant. Severely ill septic animals exhibited significantly increased serum creatinine levels compared to controls (70 ± 30 vs. 34 ± 9 μmol/L, P < 0.0001). Cortical perfusion (480 ± 80 vs. 330 ± 140 mL/100 g tissue/min, P < 0.005), and cortical and medullary T This preclinical study suggests combined T 2 TECHNICAL EFFICACY STAGE: 2.
Sections du résumé
BACKGROUND
Preventing sepsis-associated acute kidney injury (S-AKI) can be challenging because it develops rapidly and is often asymptomatic. Probability assessment of disease progression for therapeutic follow-up and outcome are important to intervene and prevent further damage.
PURPOSE
To establish a noninvasive multiparametric MRI (mpMRI) tool, including T
STUDY TYPE
Preclinical randomized prospective study.
ANIMAL MODEL
One hundred and forty adult female SD rats (65 control and 75 sepsis).
FIELD STRENGTH/SEQUENCE
9.4T; T
ASSESSMENT
Experiment 1: To identify renal injury in relation to sepsis severity, serum creatinine levels were determined (31 control and 35 sepsis). Experiment 2: Animals underwent mpMRI (T
STATISTICAL TESTS
Mann-Whitney U test, Spearman/Pearson correlation (r), P < 0.05 was considered statistically significant.
RESULTS
Severely ill septic animals exhibited significantly increased serum creatinine levels compared to controls (70 ± 30 vs. 34 ± 9 μmol/L, P < 0.0001). Cortical perfusion (480 ± 80 vs. 330 ± 140 mL/100 g tissue/min, P < 0.005), and cortical and medullary T
DATA CONCLUSION
This preclinical study suggests combined T
LEVEL OF EVIDENCE
2 TECHNICAL EFFICACY STAGE: 2.
Substances chimiques
Creatinine
AYI8EX34EU
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1954-1963Informations de copyright
© 2023 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.
Références
Singer M, Deutschman CS, Seymour CW, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA 2016;315:801-810.
Levy MM, Evans LE, Rhodes A. The surviving sepsis campaign bundle: 2018 update. Intensive Care Med 2018;44:925-928.
Cavaillon JM, Singer M, Skirecki T. Sepsis therapies: Learning from 30 years of failure of translational research to propose new leads. EMBO Mol Med 2020;12:e10128.
Peerapornratana S, Manrique-Caballero CL, Gomez H, Kellum JA. Acute kidney injury from sepsis: Current concepts, epidemiology, pathophysiology, prevention and treatment. Kidney Int 2019;96:1083-1099.
Mehta RL, Bouchard J, Soroko SB, et al. Sepsis as a cause and consequence of acute kidney injury: Program to improve care in acute renal disease. Intensive Care Med 2011;37:241-248.
Adhikari NK, Fowler RA, Bhagwanjee S, Rubenfeld GD. Critical care and the global burden of critical illness in adults. Lancet 2010;376:1339-1346.
Kellum JA, Prowle JR. Paradigms of acute kidney injury in the intensive care setting. Nat Rev Nephrol 2018;14:217-230.
Gómez H, Kellum JA. Sepsis-induced acute kidney injury. Critical Care Nephrology. Philadelphia, PA: Elsevier; 2019;524-533.
Post EH, Kellum JA, Bellomo R, Vincent J-L. Renal perfusion in sepsis: From macro-to microcirculation. Kidney Int 2017;91:45-60.
Thongprayoon C, Cheungpasitporn W, Harrison AM, et al. The comparison of the commonly used surrogates for baseline renal function in acute kidney injury diagnosis and staging. BMC Nephrol 2016;17:1-8.
Gonnert FA, Recknagel P, Seidel M, et al. Characteristics of clinical sepsis reflected in a reliable and reproducible rodent sepsis model. J Surg Res 2011;170:e123-e134.
Herrmann K-H, Hung LY, Reichenbach JR. Fast 3D isotropic high-resolution MRI of mouse brain using a variable Flip angle RARE sequence with T2 compensation @9.4T. Proceedings of 30th Annual Meeting ISMRM. London: ISMRM; 2022.
Schweser F, Krumbein I, Herrmann K-H, Mentzel H-J, Reichenbach JR. Which one is most accurate and has highest precision?-a comprehensive analysis of T2 (*) estimation techniques. Proceedings of 22th Annual Meeting ISMRM. Milan, Italy: ISMRM; 2014.
Dobre MC, Ugurbil K, Marjanska M. Determination of blood longitudinal relaxation time (T1) at high magnetic field strengths. Magn Reson Imaging 2007;25:733-735.
Hueper K, Gutberlet M, Rong S, et al. Acute kidney injury: Arterial spin labeling to monitor renal perfusion impairment in mice-comparison with histopathologic results and renal function. Radiology 2014;270:117-124.
Detre JA, Leigh JS, Williams DS, Koretsky AP. Perfusion imaging. Magn Reson Med 1992;23:37-45.
Milford D, Rosbach N, Bendszus M, Heiland S. Mono-exponential fitting in T2-relaxometry: Relevance of offset and first Echo. PLoS One 2015;10:e0145255.
Jenkinson M, Smith S. A global optimisation method for robust affine registration of brain images. Med Image Anal 2001;5:143-156.
McKinney W. Data structures for statistical computing in python. Proceedings of the 9th Python in Science Conference. Austin, TX: Python in Science Conference (SciPy); 2010. p 51-56.
Harris CR, Millman KJ, Van Der Walt SJ, et al. Array programming with NumPy. Nature 2020;585:357-362.
Virtanen P, Gommers R, Oliphant TE, et al. SciPy 1.0: Fundamental algorithms for scientific computing in python. Nat Methods 2020;17:261-272.
Pedregosa F, Varoquaux G, Gramfort A, et al. Scikit-learn: Machine learning in python. J Mach Learn Res 2011;12:2825-2830.
Fluss R, Faraggi D, Reiser B. Estimation of the Youden index and its associated cutoff point. Biom J 2005;47:458-472.
Ruopp MD, Perkins NJ, Whitcomb BW, Schisterman EF. Youden index and optimal cut-point estimated from observations affected by a lower limit of detection. Biom J 2008;50:419-430.
Li XC, Leite APO, Zheng X, et al. Proximal tubule-specific deletion of angiotensin II Type 1a receptors in the kidney attenuates circulating and intratubular angiotensin II-induced hypertension in PT-Agtr1a(−/−) mice. Hypertension 2021;77:1285-1298.
Ostermann M, Joannidis M. Acute kidney injury 2016: Diagnosis and diagnostic workup. Crit Care 2016;20:299.
Hueper K, Gutberlet M, Brasen JH, et al. Multiparametric functional MRI: Non-invasive imaging of inflammation and edema formation after kidney transplantation in mice. PLoS One 2016;11:e0162705.
Evans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: International guidelines for Management of Sepsis and Septic Shock 2021. Crit Care Med 2021;49:e1063-e1143.
Lankadeva YR, Okazaki N, Evans RG, Bellomo R, May CN. Renal medullary hypoxia: A new therapeutic target for septic acute kidney injury. Semin Nephrol 2019;39:543-553.
Doi K, Leelahavanichkul A, Yuen PS, Star RA. Animal models of sepsis and sepsis-induced kidney injury. J Clin Invest 2009;119:2868-2878.
Zolfaghari PS, Pinto BB, Dyson A, Singer M. The metabolic phenotype of rodent sepsis: Cause for concern. Intensive Care Med Exp 2013;1:25.
Car BD, Eng VM, Everds NE, Bounous DI. The laboratory rat. Second edition: Academic Press; 2006. p 127-146.
Prasad PV. Evaluation of intra-renal oxygenation by BOLD MRI. Nephron Clin Pract 2006;103:c58-c65.
Li L-P, Hack B, Seeliger E, Prasad PV. Preclinical MRI of the kidney: Methods and protocols. New York, NY: Humana; 2021. p 171-185.
Michaely HJ, Metzger L, Haneder S, Hansmann J, Schoenberg SO, Attenberger UI. Renal BOLD-MRI does not reflect renal function in chronic kidney disease. Kidney Int 2012;81:684-689.
Jerome NP, Caroli A, Ljimani A. Intravoxel incoherent motion (IVIM), and diffusion tensor imaging (DTI): Basic concepts. Preclinical MRI of the kidney. New York, NY: Humana; 2021. p 187-204.