Liver Biliary Function Evaluation on a 1.5T Magnetic Resonance Imaging Scan by T1 Reduction Rate Assessment Using Variable-Flip-Angle Sequences.


Journal

Journal of computer assisted tomography
ISSN: 1532-3145
Titre abrégé: J Comput Assist Tomogr
Pays: United States
ID NLM: 7703942

Informations de publication

Date de publication:
12 Feb 2024
Historique:
medline: 13 2 2024
pubmed: 13 2 2024
entrez: 12 2 2024
Statut: aheadofprint

Résumé

Magnetic resonance (MR) relaxometry is an absolute and reproducible quantitative method, compared with signal intensity for the evaluation of liver biliary function. This is obtainable by the T1 reduction rate (T1RR), as it carries a smaller systematic error than the pre/post contrast agent T1 measurement. We aimed to develop and test an MR T1 relaxometry tool tailored for the evaluation of liver T1RR after gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid administration on 1.5T MR. In vitro/vivo (liver) T1RR values with two 3D FLASH variable-flip-angle sequences were calculated by a MATLAB algorithm. In vitro measurements were done by 2 physicists, in consensus. The prospective in vivo study was approved by the local ethical committee and performed on 13 normal/26 cirrhotic livers. A supplemental test in 5 normal/5 cirrhotic livers, out of the studied series, was done to compare the results of our method (without B1 inhomogeneity correction) and those of a standardized commercial tool (with B1 inhomogeneity correction). All in vivo evaluations were performed by 2 radiologists with 7 years of experience in abdominal imaging. Open-source Java-based software ImageJ was used to draw the free-hand regions of interest on liver section and for the measurement of hepatic T1RR values. The T1RR values of each group of patients were compared to assess statistically significant differences. All statistical analyses were performed with IBM-SPSS Statistics. In vivo evaluations, the intrareader and interreader reliability was assessed by intraclass correlation coefficient. Our method showed good accuracy in evaluating in vitro T1RR with a maximum percentage error of 9% (constant at various time points) with T1 values in the 200- to 1400-millisecond range. In vivo, a high concordance between the T1RR evaluated with the proposed method and that calculated from the standardized commercial software was verified (P < 0.05). The median T1RRs were 74.8, 67.9, and 52.1 for the normal liver, Child-Pugh A, and Child-Pugh B cirrhotic groups, respectively. A very good agreement was found, both within intrareader and interreader reliability, with intraclass correlation coefficient values ranging from 0.88 to 0.95 and from 0.85 to 0.90, respectively. The proposed method allowed accurate reliable in vitro/vivo T1RR assessment evaluation of the liver biliary function after gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid administration.

Identifiants

pubmed: 38346811
doi: 10.1097/RCT.0000000000001582
pii: 00004728-990000000-00286
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

Références

Bansal R, Nagórniewicz B, Prakash J. Clinical advancements in the targeted therapies against liver fibrosis. Mediators Inflamm. 2016;2016:7629724.
Haimerl M, Verloh N, Zeman F, et al. Assessment of clinical signs of liver cirrhosis using T1m on Gd-EOB-DTPA–enhanced 3T MRI. PLoS One. 2013;8:e85658.
Katsube T, Okada M, Kumano S, et al. Estimation of liver function using T1m on Gd-EOB-DTPA–enhanced magnetic resonance imaging. Invest Radiol. 2011;46:277–283.
Kamimura K, Fukukura Y, Yoneyama T, et al. Quantitative evaluation of liver function with T1 relaxation time index on Gd-EOB-DTPA-enhanced MRI: comparison with signal intensity–based indices. J Magn Reson Imaging. 2014;40:884–888.
Haimerl M, Verloh N, Zeman F, et al. Gd-EOB-DTPA–enhanced MRI for evaluation of liver function: comparison between signal-intensity–based indices and T1 relaxometry. Sci Rep. 2017;7:43347.
Obmann VC, Catucci D, Berzigotti A, et al. T1 reduction rate with Gd-EOB-DTPA determines liver function on both 1.5T and 3T MRI. Sci Rep. 2022;12:4716.
Tamada T, Ito K, Higaki A, et al. Gd-EOB-DTPA–enhanced MR imaging: evaluation of hepatic enhancement effects in normal and cirrhotic livers. Eur J Radiol. 2011;80:e311–e316.
Tsuda N, Okada M, Murakami T. Potential of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) for differential diagnosis of nonalcoholic steatohepatitis and fatty liver in rats using MRI. Invest Radiol. 2007;42:242–247.
Besa C, Bane O, Jajamovich C, et al. 3D T1 relaxometry pre/post gadoxetic acid injection for the assessment of liver cirrhosis and liver function. Magn Reson Imaging. 2015;33:1075–1082.
Bi XJ, Zhang XQ, Zhang T, et al. Quantitative assessment of liver function with hepatocyte fraction: comparison with T1 relaxation-based indices. Eur J Rad. 2021;141:109779.
Papastergiou V, Tsochatzis EA, Burroughs AK. Non-invasive assessment of liver fibrosis. Ann Gastroenterol. 2012;25:218–231.
Crossan C, Tsochatzis EA, Longworth L, et al. Cost-effectiveness of non-invasive methods for assessment and monitoring of liver fibrosis and cirrhosis in patients with chronic liver disease: systematic review and economic evaluation. Health Technol Assess. 2015;19:1–409. doi:10.3310/hta19090.
doi: 10.3310/hta19090
Cheng HLM, Wright A. Rapid high-resolution T1m by variable flip angles: accurate and precise measurements in the presence of radiofrequency field inhomogeneity. Magn Reson Med. 2006;55:566–574.
Ding Y, Rao SX, Chen C, et al. Assessing liver function in patients with HBV-related HCC: a comparison of T1m on Gd-EOB-DTPA–enhanced MR imaging with DWI. Eur Radiol. 2015;25:1392–1398.
Obmann VC, Mertineit N, Marx C, et al. Liver MR relaxometry at 3T—segmental normal T1 and T2* values in patients without focal or diffuse liver disease and in patients with increased liver fat and elevated liver stiffness. Sci Rep. 2019;9:8106.
Colagrande S, Pasquinelli F, Mazzoni LN, et al. MR-diffusion weighted imaging of healthy liver parenchyma: repeatability and reproducibility of apparent diffusion coefficient measurement. J Magn Reson Imaging. 2010;31:912–920.
Malhi H, Gores GJ. Cellular and molecular mechanisms of liver injury. Gastroenterology. 2008:134, 1641–1654.
Geier A, Dietrich CG, Voigt S, et al. Effects of proinflammatory cytokines on rat organic anion transporters during toxic liver injury and cholestasis. Hepatology. 2003;38:345–354.
Piccinino F, Sagnelli E, Pasquale G, et al. Complications following percutaneous liver biopsy. A multicenter retrospective study on 68 276 biopsies. J Hepatol. 1986;2:165–173.
The French METAVIR Cooperative Study Group. Intraobserver and interobserver variations in liver biopsy interpretation in patients with chronic hepatitis C. Hepatology. 1994;20:15–20.
Wagner M, Corcuera-Solano I, Lo G, et al. Technical failure of MR A: experience from a large single-center study. Radiology. 2017;284:401–412.
Dulai PS, Sirlin CB, Loomba R. MRI and MRE for non-invasive quantitative assessment of hepatic steatosis and fibrosis in NAFLD and NASH: clinical trials to clinical practice. J Hepatol. 2016;65:1006–1016.
Tirkes T, Zhao X, Lin C, et al. Evaluation of variable flip angle, MOLLI, SASHA, and IR-SNAPSHOT pulse sequences for T1 relaxometry and extracellular volume imaging of the pancreas and liver. MAGMA. 2019;32:559–566.
QIBA Profile: 4 DCE-MRI Quantification (DCEMRI-Q), in the RSNA Abstract Book: Quantitative Imaging Biomarkers Alliance. 2017. Available at: https://qibawiki.rsna.org/images/1/1f/QIBA_DCE-MRI_Profile-Stage_1-Public_Comment.pdf. Accessed January 31, 2024.
Tadimalla S, Wilson DJ, Shelley D, et al. Bias, repeatability and reproducibility of liver T1 mapping with variable flip angles. J Magn Reson Imaging. 2022;56:1042–1052. doi:10.1002/jmri.28127.
doi: 10.1002/jmri.28127

Auteurs

Marco Di Stasio (M)

From the Department of Experimental and Clinical Biomedical Sciences, University of Florence-Azienda Ospedaliero-Universitaria Careggi.

Cesare Cordopatri (C)

From the Department of Experimental and Clinical Biomedical Sciences, University of Florence-Azienda Ospedaliero-Universitaria Careggi.

Cosimo Nardi (C)

From the Department of Experimental and Clinical Biomedical Sciences, University of Florence-Azienda Ospedaliero-Universitaria Careggi.

Simone Busoni (S)

Department of Health Physics, UOC Fisica Sanitaria, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.

Linhsia Noferini (L)

Department of Health Physics, UOC Fisica Sanitaria, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.

Stefano Colagrande (S)

From the Department of Experimental and Clinical Biomedical Sciences, University of Florence-Azienda Ospedaliero-Universitaria Careggi.

Linda Calistri (L)

From the Department of Experimental and Clinical Biomedical Sciences, University of Florence-Azienda Ospedaliero-Universitaria Careggi.

Classifications MeSH