Assessment of Liver Function With MRI: Where Do We Stand?

被引:18
作者
Rio Bartulos, Carolina [1 ]
Senk, Karin [2 ]
Schumacher, Mona [3 ]
Plath, Jan [3 ]
Kaiser, Nico [3 ]
Bade, Ragnar [3 ]
Woetzel, Jan [3 ]
Wiggermann, Philipp [1 ]
机构
[1] Inst Rontgendiagnost & Nuklearmedizin, Stadt Klinikum Braunschweig gGmbH, Braunschweig, Germany
[2] Universtitatsklinikum Regensburg, Inst Rontgendiagnost, Regensburg, Germany
[3] MeVis Med Solut AG, Bremen, Germany
关键词
liver function; MRI; T1; relaxometry; deep learning; artificial intelligence; GD-EOB-DTPA; INDOCYANINE GREEN CLEARANCE; CONVOLUTIONAL NEURAL-NETWORK; HEPATOCELLULAR-CARCINOMA; HEPATOBILIARY PHASE; ENHANCED MRI; SIGNAL-INTENSITY; HEPATIC-FUNCTION; HEPATECTOMY; MODEL;
D O I
10.3389/fmed.2022.839919
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Liver disease and hepatocellular carcinoma (HCC) have become a global health burden. For this reason, the determination of liver function plays a central role in the monitoring of patients with chronic liver disease or HCC. Furthermore, assessment of liver function is important, e.g., before surgery to prevent liver failure after hepatectomy or to monitor the course of treatment. Liver function and disease severity are usually assessed clinically based on clinical symptoms, biopsy, and blood parameters. These are rather static tests that reflect the current state of the liver without considering changes in liver function. With the development of liver-specific contrast agents for MRI, noninvasive dynamic determination of liver function based on signal intensity or using T1 relaxometry has become possible. The advantage of this imaging modality is that it provides additional information about the vascular structure, anatomy, and heterogeneous distribution of liver function. In this review, we summarized and discussed the results published in recent years on this technique. Indeed, recent data show that the T1 reduction rate seems to be the most appropriate value for determining liver function by MRI. Furthermore, attention has been paid to the development of automated tools for image analysis in order to uncover the steps necessary to obtain a complete process flow from image segmentation to image registration to image analysis. In conclusion, the published data show that liver function values obtained from contrast-enhanced MRI images correlate significantly with the global liver function parameters, making it possible to obtain both functional and anatomic information with a single modality.
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页数:10
相关论文
共 109 条
[1]   Post-hepatectomy liver failure after major hepatic surgery: not only size matters [J].
Asenbaum, Ulrika ;
Kaczirek, Klaus ;
Ba-Ssalamah, Ahmed ;
Ringl, Helmut ;
Schwarz, Christoph ;
Waneck, Fredrik ;
Fitschek, Fabian ;
Loewe, Christian ;
Nolz, Richard .
EUROPEAN RADIOLOGY, 2018, 28 (11) :4748-4756
[2]   Burden of liver diseases in the world [J].
Asrani, Sumeet K. ;
Devarbhavi, Harshad ;
Eaton, John ;
Kamath, Patrick S. .
JOURNAL OF HEPATOLOGY, 2019, 70 (01) :151-171
[3]   Does the Functional Liver Imaging Score Derived from Gadoxetic Acid-enhanced MRI Predict Outcomes in Chronic Liver Disease? [J].
Bastati, Nina ;
Beer, Lucian ;
Mandorfer, Mattias ;
Poetter-Lang, Sarah ;
Tamandl, Dietmar ;
Bican, Yesim ;
Elmer, Michael Christoph ;
Einspieler, Henrik ;
Semmler, Georg ;
Simbrunner, Benedikt ;
Weber, Michael ;
Hodge, Jacqueline C. ;
Vernuccio, Federica ;
Sirlin, Claude ;
Reiberger, Thomas ;
Ba-Ssalamah, Ahmed .
RADIOLOGY, 2020, 294 (01) :98-107
[4]   Assessment of Orthotopic Liver Transplant Graft Survival on Gadoxetic Acid-Enhanced Magnetic Resonance Imaging Using Qualitative and Quantitative Parameters [J].
Bastati, Nina ;
Wibmer, Andreas ;
Tamandl, Dietmar ;
Einspieler, Henrik ;
Hodge, Jacqueline C. ;
Poetter-Lang, Sarah ;
Rockenschaub, Susanne ;
Berlakovich, Gabriela A. ;
Trauner, Michael ;
Herold, Christian ;
Ba-Ssalamah, Ahmed .
INVESTIGATIVE RADIOLOGY, 2016, 51 (11) :728-734
[5]   Inter- and intra-reader agreement for gadoxetic acid-enhanced MRI parameter readings in patients with chronic liver diseases [J].
Beer, Lucian ;
Mandorfer, Mattias ;
Bastati, Nina ;
Poetter-Lang, Sarah ;
Tamandl, Dietmar ;
Stoyanova, Dilyana Plamenova ;
Elmer, Michael Christoph ;
Semmler, Georg ;
Simbrunner, Benedikt ;
Hodge, Jacqueline C. ;
Sirlin, Claude B. ;
Reiberger, Thomas ;
Ssalamah, Ahmed .
EUROPEAN RADIOLOGY, 2019, 29 (12) :6600-6610
[6]   Transporter Expression in Noncancerous and Cancerous Liver Tissue from Donors with Hepatocellular Carcinoma and Chronic Hepatitis C Infection Quantified by LC-MS/MS Proteomics [J].
Billington, Sarah ;
Ray, Adrian S. ;
Salphati, Laurent ;
Xiao, Guangqing ;
Chu, Xiaoyan ;
Humphreys, W. Griffith ;
Liao, Mingxiang ;
Lee, Caroline A. ;
Mathias, Anita ;
Hop, Cornelis E. C. A. ;
Rowbottom, Christopher ;
Evers, Raymond ;
Lai, Yurong ;
Kelly, Edward J. ;
Prasad, Bhagwat ;
Unadkat, Jashvant D. .
DRUG METABOLISM AND DISPOSITION, 2018, 46 (02) :189-196
[7]   Liver enhancement during hepatobiliary phase after Gd-BOPTA administration: correlation with liver and renal function [J].
Bonatti, Matteo ;
Valletta, Riccardo ;
Avesani, Giacomo ;
Lombardo, Fabio ;
Cannone, Federico ;
Zamboni, Giulia A. ;
Mansueto, Giancarlo ;
Manfredi, Riccardo ;
Ferro, Federica .
EUROPEAN RADIOLOGY, 2021, 31 (04) :2490-2496
[8]   Automated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learning [J].
Bousabarah, Khaled ;
Letzen, Brian ;
Tefera, Jonathan ;
Savic, Lynn ;
Schobert, Isabel ;
Schlachter, Todd ;
Staib, Lawrence H. ;
Kocher, Martin ;
Chapiro, Julius ;
Lin, MingDe .
ABDOMINAL RADIOLOGY, 2021, 46 (01) :216-225
[9]  
Child C G, 1964, Major Probl Clin Surg, V1, P1
[10]   Reducing inter-observer variability and interaction time of MR liver volumetry by combining automatic CNN-based liver segmentation and manual corrections [J].
Chlebus, Grzegorz ;
Meine, Hans ;
Thoduka, Smita ;
Abolmaali, Nasreddin ;
van Ginneken, Bram ;
Hahn, Horst Karl ;
Schenk, Andrea .
PLOS ONE, 2019, 14 (05)