Introduction
Magnetic resonance imaging (MRI) has become an increasingly important imaging technique for assessment of patients with chronic liver disease and for liver cancer evaluation. The use of multiparametric imaging and recent technologic advances in MRI, aligned with the lack of ionizing radiation, have established MRI as one of the most powerful imaging tools for assessing liver disease (1, 2). However, these advances usually entail complex, time-consuming and costly protocols.
Based on the benefits of diagnostic MRI and attempting to minimize the disadvantages, abbreviated MRI (AMRI) protocols have been proposed as potential alternatives for liver disease evaluation. The purpose of AMRI protocols is to minimize the length of full MRI exams by using a reduced number of MRI sequences in order to decrease acquisition and interpretation times, and to reduce costs without losing diagnostic sensitivity and accuracy (3).
Compared to a complete MRI protocol, AMRI approaches have shown important reductions in study acquisitions times (4, 5), enabling the possibility to schedule and evaluate more patients in a shorter period of time. Furthermore, these abbreviated studies would improve radiologists workflow with a smaller number of sequences to review and interpret (6). Moreover, shorter reports could be obtained and delivery times to the clinicians would be reduced also, potentially improving healthcare quality.
In terms of cost saving and cost-effectiveness, several studies suggest that AMRI protocols may be consider as a valid alternative to the current evaluation methods for assessing liver disease. A study carried out by Lima et al. (7) demonstrated that AMRI may be a cost-effective strategy for liver cancer surveillance rather than ultrasound (US) examination.
AMRI protocols have been already successfully tested in different organs as breast (8), liver (9), pancreas (10), and prostate (11), among others. Specifically, AMRI protocols in liver are mainly focused on hepatocellular carcinoma (HCC) screening and surveillance, and in diffuse liver disease (3, 9).
Clinical Applications
HCC screening and surveillance
Current guidelines for HCC screening and surveillance.
HCC has been the most rapidly rising cause of cancer-related death in the United States over the last 20 years and is currently the third cause of cancer-related mortality worldwide (12). To improve overall survival of at-risk population (adult patients with cirrhosis and/or chronic hepatitis B virus [HBV]), the American Association for the Study of Liver Disease (AASLD) and the European Association for the Study of the Liver (EASL) Guidelines recommends surveillance using US every 6 months (13, 14) with or without alpha-fetoprotein (AFP).
Despite the practice guidelines recommending the use of standard US for surveillance of individuals at risk of developing HCC, some caveats should be mentioned. The ability of US examinations to fully image the liver parenchyma may be limited due to several factors such as obesity, advanced liver cirrhosis, alcohol or non-alcoholic fatty liver disease (NAFLD) related cirrhosis and other technical factors (15–18). Moreover, recent studies suggest that US has low sensitivity for early-stage tumors, with only 63% for detecting early HCC and 20% for very early stage HCC (19, 20). More sensitive surveillance techniques should be investigated. Regarding the added value of AFP to US, according to the EASL guidelines, the data available show that tumor biomarkers, including AFP, are suboptimal in terms of cost-effectiveness for routine surveillance of early HCC (14). On the other hand, the AASLD guidelines state that AFP could be optionally combined with US in surveillance strategies (13). Other emerging blood biomarkers for HCC have been explored with promising results. The GALAD score (a serum biomarker-based model combining gender, age, Lens culinaris agglutinin-reactive AFP [AFP-L3], total AFP, and des-γ-carboxyprothrombin [DCP]) (21) and liquid biopsy/circulating tumor DNA (22, 23) have shown promising results and may have a role in surveillance protocols in the future.
AMRI protocols for HCC screening and surveillance
Conventional contrast-enhanced MRI has shown superior diagnostic sensitivity for HCC detection compared to US, particularly for early stage tumors (17, 24, 25). However, MRI is more expensive, longer examination times are required, and imaging review and interpretation are more challenging and time-consuming for radiologists. These facts question the suitability of conventional MRI for HCC surveillance. AMRI protocols represent a potential alternative because it solves some of these disadvantages of full MRI protocols.
Several AMRI protocols, combining different sequences with and without contrast agents, have been described for HCC screening (Figure 1). Most of these studies have retrospectively evaluated the performance of simulated/ reconstructed AMRI protocols, extracting the relevant sequences from complete MRI exams, while prospective studies using real AMRI protocols are lacking (Table 1):
Fig. 1:


56-year-old male with HCV cirrhosis with hepatocellular carcinoma in segment 8. Complete gadoxetate-enhanced MRI study is divided into 3 AMRI protocols: a) Noncontrast-AMRI: including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), b) Dynamic-AMRI: including T1WI dynamic (pre-, arterial phase, portal venous phase, and transitional phase), c) Hepatobiliary phase-AMRI: including T1WI hepatobiliary phase (HBP) post gadoxetate, T2WI and DWI. Axial T2WI FS shows a mildly hyperintense lesion in the hepatic dome, with no fat in T1wi IP/OP, with corresponding mild hyperintensity in diffusion weighted images (b800) and hypointensity in ADC map (arrows). Axial T1WI pre-contrast, arterial phase, portal venous phase, transitional phase and hepatobiliary phase demonstrates a 10mm lesion with arterial hyperenhancement, washout in portal venous phase, and hypointensity in hepatobiliary phase (arrows).
Table 1:
Summary of published AMRI studies for HCC detection.
| Study | Year | Screening population | Study design | Sample HCC size prevalence | Reference standards | AMRI sequences | Sens. | Spec. | |
|---|---|---|---|---|---|---|---|---|---|
| NC-AMRI | |||||||||
| Sutherland (26) | 2017 | Yes | P | 192 | 3.0% | Combined* | DWI | 83.0% | 98.0% |
| Besa (27) | 2017 | No | R | 174 | 35.6% | Pathology | DWI | 87.1% | 93.8% |
| McNamara (28) | 2018 | No | R | 37 | 54.1% | Pathology | DWI | 78.0% | 88.0% |
| Vietti Violi (29) | 2020 | Yes | R | 237 | 5.5% | Combined* | T2WI + DWI | 61.5% | 95.5% |
| Park (30) | 2020 | Yes | P | 382 | 11.3% | Combined* | T2WI + DWI | 79.1% | 97.9% |
| Kim (31) | 2014 | No | R | 157 | 85.9% | Pathology | T2WI + DWI + T1WI | 92.5% | NA |
| Han (32) | 2018 | No | R | 247 | 70.8% | Combined* | T2WI + DWI + T1WI | 84.6% | 81.9% |
| Chan (33) | 2019 | No | R | 188 | NA | Radiology | T2WI + DWI | 84.5% | 92.7% |
| Whang (34) | 2020 | No | R | 263 | 53.2% | Combined* | + T1WI T2WI + DWI + T1IP/OP | 86.1% | 92.7% |
| DYN-AMRI | |||||||||
| Besa (27) | 2017 | No | R | 174 | 35.6% | Pathology | CE-T1WI | 88.7% | 100% |
| Lee (37) | 2018 | No | R | 156 | Unclear | Radiology | CE-T1WI | High LI-RADS concordance with full MRI | |
| Khatri (38) | 2020 | No | R | 86 | 32.6% | Combined* | CE-T1WI + T2WI | 92.1% | 88.6% |
| Vietti Violi (29) | 2020 | Yes | R | 237 | 5.5% | Combined* | CE-T1WI + T2WI + DWI | 84.6% | 99.8% |
| HBP-AMRI | |||||||||
| Besa (27) | 2017 | No | R | 174 | 35.6% | Pathology | HBP | 91.9% | 91.1% |
| HBP + DWI | 83.9% | 94.6% | |||||||
| Brunsing (35)) | 2019 | Yes | R | 141 | 8.5% | Combined* | HBP | 92.0% | 91.0% |
| Marks (40) | 2014 | No | R | 298 | 16.4% | Combined* | HBP + T2WI | 82.6% | 93.2% |
| HBP + T2WI + DWI | 83.7% | 93.2% | |||||||
| Tillman (4) | 2018 | No | R | 79 | 16.5% | Combined* | HBP + T2WI | 85.2% | NA |
| Vietti Violi (29) | 2020 | Yes | R | 237 | 5.5% | Combined* | HBP + T2WI + DWI | 80.8% | 94.9% |
| Whang (34) | 2020 | No | R | 263 | 53.2% | Combined* | HBP + T2WI + DWI | 89.7% | 92.7% |
Combined under “Reference standards” refers to pathology and/or imaging assessment; AMRI: abbreviated magnetic resonance; Sens: sensitivity; Spec: specificity; PPV: positive predictive value; NPV: negative predictive value; P: prospective design; R: retrospective design; DWI: diffusion weighted imaging; T2WI: T2 weighted imaging; T1WI: T1 weighted imaging; T1 IP/OP: T1 in-phase/out of phase; CE-T1WI: contrast-enhanced T1WI; HBP: hepatobiliary phase post gadoxetate administration.
Non-contrast AMRI (NC-AMRI):
Non-contrast AMRI (NC-AMRI): these protocols are simpler and cheaper than the contrast-enhanced approaches avoiding the potential risks of using gadolinium-based contrast agents. They consist in diffusion-weighted imaging (DWI) with/without T2-weighted imaging (T2WI) (26–30). Some studies explored also the combination of T2WI and DWI with T1WI sequences (31–34). According to the current literature, per-patient sensitivity on NC-AMRI showed a wide range between 61.5% and 92.5% with high specificity (88.0%−97.9%) (26–34). A retrospective study by Vietti-Violi et al. (29) in at-risk patients reported low sensitivity (61.5%) for HCC screening using a combination on T2WI and DWI. However, two prospective studies performed in at-risk patients showed that NC-AMRI protocols had similar to better sensitivity than US (AMRI vs US sensitivity: 83% vs 100%, and 79.1% vs 27.9) (26, 30). In case of positive findings, a recall study using multiphasic CT or MRI is needed in order to characterize the observations applying the Liver Imaging Reporting and Data System (LI-RADS) criteria, devised to standardize imaging analysis for HCC screening and surveillance, diagnosis and treatment response assessment (35).
Dynamic AMRI (DYN-AMRI):
Dynamic AMRI (DYN-AMRI): these protocols are based on dynamic contrast-enhanced (CE) T1WI sequences (unenhanced, arterial, portal venous and delayed/transitional phases) after the administration of a contrast agent (typically extracellular, but gadoxetate disodium can also be used). The main advantage of DYN-AMRI protocols is that in case of positive findings, no further confirmation is generally required as major LI-RADS criteria can be applied to multiphasic imaging. Different studies have used CE-T1WI sequences alone (27, 36, 37) or in combination with T2WI (36, 38) or T2WI and DWI (29). DYN-AMRI protocols, based on CE-T1WI sequences, have shown high per-patient sensitivity (84.6.6%−92.1%) and specificity (88.6%−100%) (27, 29, 38). Furthermore, a study carried out by Lee et al. (37), showed high concordance in LI-RADS categorization of liver observations between the complete MRI exploration and the DYN-AMRI.
Gadoxetate-enhanced hepatobiliary phase AMRI (HBP-AMRI):
Gadoxetate-enhanced hepatobiliary phase AMRI (HBP-AMRI): protocols that are based on the T1WI hepatobiliary phase (HBP) obtained approximately 20 min after gadoxetate disodium administration. For the HBP-AMRI, the contrast agent is injected outside the MRI room with no need for automated injector or dynamic sequences which reduces study time and simplifies the study. Several authors have assessed T1WI HBP alone (27, 39), and in combination with T2WI (4, 40), DWI (27), or both (29, 34, 40). Reported per-patient diagnostic performance of HBP-AMRI protocols showed higher sensitivity (80.8%- 92.0%) and specificity (92.8% to 96.1%) compared to other AMRI approaches, however not consistently in screening populations (4, 27, 29, 34, 39, 40).
Screening and assessment of liver fat and fibrosis
Current evaluation method
Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease in adults, with a prevalence of up to 20–30% in developed countries (41). This entity represents a wide spectrum of pathologies ranging from simple steatosis to non-alcoholic steatohepatitis (NASH) (42). Moreover, with late diagnosis and lack of treatment this entity may lead to a progressive liver fibrosis and cirrhosis (43). Iron overload can be another important cofactor for developing liver fibrosis in patients with NALFD and NASH so its evaluation is also important (44). Currently, standard of reference for assessing derived complications of the disease like steatohepatitis, fibrosis and iron overload is percutaneous biopsy. However, it does have considerable limitations and complications, some of which, though infrequent, are potentially fatal (45). In the recent years, different non-invasive methods as serum biomarkers and elastography techniques, have been proposed as potential alternatives for evaluation of NAFLD, grading of steatosis, diagnosis of NASH and staging of liver fibrosis (46). Furthermore, MRI has shown potential in evaluating iron overload within the liver, using specific MRI methods including relaxometry techniques (47).
AMRI protocol for assessing liver fat and fibrosis
Multiparametric MRI, including MR elastography (MRE) examination, proton-density fat fraction (PDFF), and T2* sequences has emerged as powerful noninvasive methods to assess liver fibrosis, steatosis and iron overload (2, 46) (Figure 2). To the best of our knowledge, only one study carried out by Cunha et al. (48) has evaluated an abbreviated protocol combining different MRI sequences to assess different characteristics of NAFLD. They prospectively evaluated an AMRI protocol to assess quantitative imaging features of patients with obesity and NAFLD, and tested its use during treatment. The AMRI protocol consisted in the combination of T2WI single-shot fast spin-echo (SSFSE), volumetric 3D 3-point Dixon images with water and fat separation for manual visceral adipose tissue measurements, iterative decomposition of water and fat with echo asymmetry and least-squares estimation sequence (IDEAL IQ®) for liver fat fraction and iron overload estimations, and liver 2D gradient-echo MRE sequence for liver stiffness analysis. They concluded that this abbreviated approach was a feasible, cheaper and accessible option for screening and monitoring patients with obesity and NAFLD.
Fig. 2:

63-year-old male with non-alcoholic steatohepatitis (NASH) and stage 3 fibrosis. AMRI protocol performed for liver fat/iron/fibrosis assessment demonstrates liver steatosis on the proton-density fat fraction (PDFF) map (TR: 15.6ms/TE: 2.38ms, 4.76ms, 7.14ms, 9.52ms, 11.90ms, 14.28ms) with regions of interest measuring PDFF at 24%, T2* map (TR: 1.93ms/TE: 2.38ms, 4.76ms, 7.15ms, 9.53ms, 11.91ms, 14.29ms, 16.67ms, 19.06ms) performed for iron quantification showing no iron overload (T2* 22.1ms) and elastogram obtained with 2D EPI MRE sequence showing elevated liver stiffness (4.3 kPa).
Limitations and future perspectives
There is still limited data on diagnostic accuracy of different AMRI approaches and these protocols are not yet supported by professional societies guidelines. In addition, in order to gain clinical adoption, a CPT code and insurance reimbursement for these studies should be obtained. Prospective and multicenter studies comparing AMRI protocols vs the standards of reference for each disease are lacking. Furthermore, cost-effectiveness analysis should be performed.
Conclusion/Summary
AMRI is emerging as a potential alternative for HCC surveillance and for diffuse liver disease assessment. AMRI protocols are faster and may represent a low-cost alternative to a complete MRI protocol. However, the most accurate, time-effective and cost-effective protocol, as well as the target population in each scenario, need to be defined. Prospective and multicentric studies, exploring different AMRI protocols versus the current standard of reference for each should be performed.
Clinics Care Points
AMRI protocols represent a cheaper and less time-consuming alternative to full MRI protocols in HCC surveillance/screening, and evaluation of liver fat, fibrosis, and iron overload.
There are three different AMRI protocols for HCC screening including non-contrast AMRI (NC-AMRI), dynamic AMRI (dyn-AMRI), and hepatobiliary AMRI (HBP-AMRI), each one with their pros and cons.
There is still limited data and larger studies are necessary.
Key points.
Abbreviated magnetic resonance imaging (AMRI) protocols represent a cheaper and less time-consuming alternative to full MRI protocols in HCC surveillance/screening and for evaluation of diffuse liver disease.
There are three different AMRI protocols used for HCC screening/surveillance including non-contrast AMRI (NC-AMRI), dynamic AMRI (Dyn-AMRI), and hepatobiliary AMRI (HBP-AMRI), each one with their pros and cons.
More data on the diagnostic value of AMRI protocols is needed.
Synopsis.
Magnetic resonance imaging (MRI) has been risen as a powerful tool for assessing liver disease and liver cancer, however it entails complex, time-consuming and costly protocols. Abbreviated MRI (AMRI) is emerging as a simpler, faster and low-cost alternative to full-abdominal MRI protocols. Different AMRI approaches have been successfully tested in hepatocellular carcinoma detection and for assessment of diffuse liver disease. However, the most accurate, time and cost-effective protocol, as well as the target population need to be defined. Prospective and multicentric studies, exploring different AMRI protocols versus the current standard of reference should be performed.
Acknowledgments
Grant support: Bayer Healthcare, Takeda, Regeneron
Abbreviation/Glossary list
- AASLD
American Association for the Study of Liver Disease
- AFP
alpha-fetoprotein
- AFP-L3
Lens culinaris agglutinin-reactive AFP
- AMRI
abbreviated magnetic resonance imaging
- CE
contrast-enhanced
- DWI
diffusion weighted imaging
- DYN-AMRI
dynamic AMRI
- EASL
European Association for the Study of the Liver
- GALAD
gender, age, AFP-L3, total AFP, and des-γ-carboxyprothrombin
- HBP
hepatobiliary phase
- HBP-AMRI
hepatobiliary AMRI
- HBV
hepatitis B virus
- HCC
hepatocellular carcinoma
- IDEAL Q®
iterative decomposition of water and fat with echo asymmetry and least-squares estimation sequence
- LI-RADS
Liver Imaging Reporting and Data System
- MRE
magnetic resonance elastography
- MRI
magnetic resonance imaging
- NAFLD
non-alcoholic fatty liver disease
- NASH
non-alcoholic steatohepatitis
- NC-AMRI
non contrast AMRI
- SSFSE
single shot fast spin echo
- T1WI
T1 weighted imaging
- T1 IP/OP
T1 in phase/out of phase
- T2WI
T2 weighted imaging
- US
ultrasound
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
References
- 1.Taouli B, Ehman RL, Reeder SB. Advanced MRI methods for assessment of chronic liver disease. AJR Am J Roentgenol. 2009;193(1):14–27. Epub 2009/06/23. doi: 10.2214/AJR.09.2601. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Yin M, Glaser KJ, Talwalkar JA, Chen J, Manduca A, Ehman RL. Hepatic MR elastography: clinical performance in a series of 1377 consecutive examinations. Radiology. 2016;278(1):114–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Canellas R, Rosenkrantz AB, Taouli B, Sala E, Saini S, Pedrosa I, et al. Abbreviated MRI protocols for the abdomen. Radiographics. 2019;39(3):744–58. [DOI] [PubMed] [Google Scholar]
- 4.Tillman BG, Gorman JD, Hru JM, Lee MH, King MC, Sirlin CB, et al. Diagnostic per-lesion performance of a simulated gadoxetate disodium-enhanced abbreviated MRI protocol for hepatocellular carcinoma screening. Clinical radiology. 2018;73(5):485–93. [DOI] [PubMed] [Google Scholar]
- 5.Weiss J, Martirosian P, Notohamiprodjo M, Kaufmann S, Othman AE, Grosse U, et al. Implementation of a 5-minute magnetic resonance imaging screening protocol for prostate cancer in men with elevated prostate-specific antigen before biopsy. Investigative radiology. 2018;53(3):186–90. [DOI] [PubMed] [Google Scholar]
- 6.Oldrini G, Derraz I, Salleron J, Marchal F, Henrot P. Impact of an abbreviated protocol for breast MRI in diagnostic accuracy. Diagnostic and Interventional Radiology. 2018;24(1):12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Lima PH, Fan B, Bérubé J, Cerny M, Olivié D, Giard J-M, et al. Cost-utility analysis of imaging for surveillance and diagnosis of hepatocellular carcinoma. American Journal of Roentgenology. 2019;213(1):17–25. [DOI] [PubMed] [Google Scholar]
- 8.Mango VL, Morris EA, Dershaw DD, Abramson A, Fry C, Moskowitz CS, et al. Abbreviated protocol for breast MRI: are multiple sequences needed for cancer detection? European journal of radiology. 2015;84(1):65–70. [DOI] [PubMed] [Google Scholar]
- 9.Brunsing RL, Fowler KJ, Yokoo T, Cunha GM, Sirlin CB, Marks RM. Alternative approach of hepatocellular carcinoma surveillance: abbreviated MRI. Hepatoma Research. 2020;6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Macari M, Lee T, Kim S, Jacobs S, Megibow AJ, Hajdu C, et al. Is gadolinium necessary for MRI follow-up evaluation of cystic lesions in the pancreas? Preliminary results. American Journal of Roentgenology. 2009;192(1):159–64. [DOI] [PubMed] [Google Scholar]
- 11.Polanec SH, Lazar M, Wengert GJ, Bickel H, Spick C, Susani M, et al. 3D T2-weighted imaging to shorten multiparametric prostate MRI protocols. European radiology. 2018;28(4):1634–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Marrero JA, Kulik LM, Sirlin CB, Zhu AX, Finn RS, Abecassis MM, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases. Hepatology. 2018;68(2):723–50. [DOI] [PubMed] [Google Scholar]
- 13.Heimbach JK, Kulik LM, Finn RS, Sirlin CB, Abecassis MM, Roberts LR, et al. AASLD guidelines for the treatment of hepatocellular carcinoma. Hepatology. 2018;67(1):358–80. [DOI] [PubMed] [Google Scholar]
- 14.European Association For The Study Of The L. EASL clinical practice guidelines: management of hepatocellular carcinoma. Journal of hepatology. 2018;69(1):182–236. [DOI] [PubMed] [Google Scholar]
- 15.Simmons O, Fetzer DT, Yokoo T, Marrero JA, Yopp A, Kono Y, et al. Predictors of adequate ultrasound quality for hepatocellular carcinoma surveillance in patients with cirrhosis. Alimentary pharmacology & therapeutics. 2017;45(1):169–77. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Nam CY, Chaudhari V, Raman SS, Lassman C, Tong MJ, Busuttil RW, et al. CT and MRI improve detection of hepatocellular carcinoma, compared with ultrasound alone, in patients with cirrhosis. Clinical Gastroenterology and Hepatology. 2011;9(2):161–7. [DOI] [PubMed] [Google Scholar]
- 17.Colli A, Fraquelli M, Casazza G, Massironi S, Colucci A, Conte D, et al. Accuracy of ultrasonography, spiral CT, magnetic resonance, and alpha-fetoprotein in diagnosing hepatocellular carcinoma: a systematic review. American Journal of Gastroenterology. 2006;101(3):513–23. [DOI] [PubMed] [Google Scholar]
- 18.Samoylova ML, Mehta N, Roberts JP, Yao FY. Predictors of ultrasound failure to detect hepatocellular carcinoma. Liver Transplantation. 2018;24(9):1171–7. [DOI] [PubMed] [Google Scholar]
- 19.Singal A, Volk ML, Waljee A, Salgia R, Higgins P, Rogers MAM, et al. Meta-analysis: surveillance with ultrasound for early-stage hepatocellular carcinoma in patients with cirrhosis. Alimentary pharmacology & therapeutics. 2009;30(1):37–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Tzartzeva K, Obi J, Rich NE, Parikh ND, Marrero JA, Yopp A, et al. Surveillance imaging and alpha fetoprotein for early detection of hepatocellular carcinoma in patients with cirrhosis: a meta-analysis. Gastroenterology. 2018;154(6):1706–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Yang JD, Addissie BD, Mara KC, Harmsen WS, Dai J, Zhang N, et al. GALAD score for hepatocellular carcinoma detection in comparison with liver ultrasound and proposal of GALADUS score. Cancer Epidemiology and Prevention Biomarkers. 2019;28(3):531–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Cai J, Chen L, Zhang Z, Zhang X, Lu X, Liu W, et al. Genome-wide mapping of 5-hydroxymethylcytosines in circulating cell-free DNA as a non-invasive approach for early detection of hepatocellular carcinoma. Gut. 2019;68(12):2195–205. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Xu R-h, Wei W, Krawczyk M, Wang W, Luo H, Flagg K, et al. Circulating tumour DNA methylation markers for diagnosis and prognosis of hepatocellular carcinoma. Nature materials. 2017;16(11):1155–61. [DOI] [PubMed] [Google Scholar]
- 24.Yu NC, Chaudhari V, Raman SS, Lassman C, Tong MJ, Busuttil RW, et al. CT and MRI improve detection of hepatocellular carcinoma, compared with ultrasound alone, in patients with cirrhosis. Clin Gastroenterol Hepatol. 2011;9(2):161–7. Epub 2010/10/06. doi: 10.1016/j.cgh.2010.09.017. [DOI] [PubMed] [Google Scholar]
- 25.Hanna RF, Miloushev VZ, Tang A, Finklestone LA, Brejt SZ, Sandhu RS, et al. Comparative 13-year meta-analysis of the sensitivity and positive predictive value of ultrasound, CT, and MRI for detecting hepatocellular carcinoma. Abdominal Radiology. 2016;41(1):71–90. [DOI] [PubMed] [Google Scholar]
- 26.Sutherland T, Watts J, Ryan M, Galvin A, Temple F, Vuong J, et al. Diffusion-weighted MRI for hepatocellular carcinoma screening in chronic liver disease: Direct comparison with ultrasound screening. Journal of medical imaging and radiation oncology. 2017;61(1):34–9. [DOI] [PubMed] [Google Scholar]
- 27.Besa C, Lewis S, Pandharipande PV, Chhatwal J, Kamath A, Cooper N, et al. Hepatocellular carcinoma detection: diagnostic performance of a simulated abbreviated MRI protocol combining diffusion-weighted and T1-weighted imaging at the delayed phase post gadoxetic acid. Abdominal Radiology. 2017;42(1):179–90. [DOI] [PubMed] [Google Scholar]
- 28.McNamara MM, Thomas JV, Alexander LF, Little MD, Bolus DN, Li YE, et al. Diffusion-weighted MRI as a screening tool for hepatocellular carcinoma in cirrhotic livers: correlation with explant data—a pilot study. Abdominal Radiology. 2018;43(10):2686–92. [DOI] [PubMed] [Google Scholar]
- 29.Violi NV, Lewis S, Liao J, Hulkower M, Hernandez-Meza G, Smith K, et al. Gadoxetate-enhanced abbreviated MRI is highly accurate for hepatocellular carcinoma screening. European Radiology. 2020:1–11. [DOI] [PubMed] [Google Scholar]
- 30.Park HJ, Jang HY, Kim SY, Lee SJ, Won HJ, Byun JH, et al. Non-enhanced magnetic resonance imaging as a surveillance tool for hepatocellular carcinoma: comparison with ultrasound. Journal of hepatology. 2020;72(4):718–24. [DOI] [PubMed] [Google Scholar]
- 31.Kim YK, Kim YK, Park HJ, Park MJ, Lee WJ, Choi D. Noncontrast MRI with diffusion-weighted imaging as the sole imaging modality for detecting liver malignancy in patients with high risk for hepatocellular carcinoma. Magnetic resonance imaging. 2014;32(6):610–8. [DOI] [PubMed] [Google Scholar]
- 32.Han S, Choi J-I, Park MY, Choi MH, Rha SE, Lee YJ. The diagnostic performance of liver MRI without intravenous contrast for detecting hepatocellular carcinoma: a case-controlled feasibility study. Korean journal of radiology. 2018;19(4):568–77. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Chan MV, McDonald SJ, Ong Y-Y, Mastrocostas K, Ho E, Huo YR, et al. HCC screening: assessment of an abbreviated non-contrast MRI protocol. European radiology experimental. 2019;3(1):49. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Whang S, Choi MH, Choi J-I, Youn SY, Kim DH, Rha SE. Comparison of diagnostic performance of non-contrast MRI and abbreviated MRI using gadoxetic acid in initially diagnosed hepatocellular carcinoma patients: a simulation study of surveillance for hepatocellular carcinomas. European Radiology. 2020:1–14. [DOI] [PubMed] [Google Scholar]
- 35.Chernyak V, Fowler KJ, Kamaya A, Kielar AZ, Elsayes KM, Bashir MR, et al. Liver Imaging Reporting and Data System (LI-RADS) version 2018: imaging of hepatocellular carcinoma in at-risk patients. Radiology. 2018;289(3):816–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Hecht EM, Holland AE, Israel GM, Hahn WY, Kim DC, West AB, et al. Hepatocellular carcinoma in the cirrhotic liver: gadolinium-enhanced 3D T1-weighted MR imaging as a stand-alone sequence for diagnosis. Radiology. 2006;239(2):438–47. [DOI] [PubMed] [Google Scholar]
- 37.Lee JY, Huo EJ, Weinstein S, Santos C, Monto A, Corvera CU, et al. Evaluation of an abbreviated screening MRI protocol for patients at risk for hepatocellular carcinoma. Abdominal Radiology. 2018;43(7):1627–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Khatri G, Pedrosa I, Ananthakrishnan L, de Leon AD, Fetzer DT, Leyendecker J, et al. Abbreviated-protocol screening MRI vs. complete-protocol diagnostic MRI for detection of hepatocellular carcinoma in patients with cirrhosis: An equivalence study using LI-RADS v2018. Journal of Magnetic Resonance Imaging. 2020;51(2):415–25. [DOI] [PubMed] [Google Scholar]
- 39.Brunsing RL, Chen DH, Schlein A, Wolfson T, Gamst A, Mamidipalli A, et al. Gadoxetate-enhanced Abbreviated MRI for Hepatocellular Carcinoma Surveillance: Preliminary Experience. Radiology: Imaging Cancer. 2019;1(2):e190010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Marks RM, Ryan A, Heba ER, Tang A, Wolfson TJ, Gamst AC, et al. Diagnostic per-patient accuracy of an abbreviated hepatobiliary phase gadoxetic acid–enhanced MRI for hepatocellular carcinoma surveillance. American Journal of Roentgenology. 2015;204(3):527–35. [DOI] [PubMed] [Google Scholar]
- 41.Angulo P Nonalcoholic fatty liver disease. New England Journal of Medicine. 2002;346(16):1221–31. [DOI] [PubMed] [Google Scholar]
- 42.Hashimoto E, Taniai M, Tokushige K. Characteristics and diagnosis of NAFLD/NASH. Journal of gastroenterology and hepatology. 2013;28:64–70. [DOI] [PubMed] [Google Scholar]
- 43.Bataller R, Brenner DA. Liver fibrosis. The Journal of clinical investigation. 2005;115(2):209–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.George DK, Goldwurm S, Macdonald GA, Cowley LL, Walker NI, Ward PJ, et al. Increased hepatic iron concentration in nonalcoholic steatohepatitis is associated with increased fibrosis. Gastroenterology. 1998;114(2):311–8. [DOI] [PubMed] [Google Scholar]
- 45.Rockey DC, Caldwell SH, Goodman ZD, Nelson RC, Smith AD. Liver biopsy. Hepatology. 2009;49(3):1017–44. [DOI] [PubMed] [Google Scholar]
- 46.Castera L, Vilgrain V, Angulo P. Noninvasive evaluation of NAFLD. Nature reviews Gastroenterology & hepatology. 2013;10(11):666–75. [DOI] [PubMed] [Google Scholar]
- 47.Hernando D, Levin YS, Sirlin CB, Reeder SB. Quantification of liver iron with MRI: state of the art and remaining challenges. Journal of Magnetic Resonance Imaging. 2014;40(5):1003–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Cunha GM, Villela-Nogueira CA, Bergman A, Lopes FPPL. Abbreviated mpMRI protocol for diffuse liver disease: a practical approach for evaluation and follow-up of NAFLD. Abdominal Radiology. 2018;43(9):2340–50. [DOI] [PubMed] [Google Scholar]
