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Cetinic I, de Lange C, Lagerstrand K, Kindblom JM, Sjögren L, Hebelka H. Applicability of multiple quantitative ultrasound liver biomarkers in children and adolescents with severe obesity. BMC Pediatr 2025; 25:390. [PMID: 40380181 DOI: 10.1186/s12887-025-05750-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2024] [Accepted: 05/07/2025] [Indexed: 05/19/2025] Open
Abstract
BACKGROUND Obesity is associated with chronic liver disease, which is why improved non-invasive diagnostic assessment of liver affection is desirable. The ultrasound-based biomarkers Attenuation Imaging coefficient (ATI), Shear Wave Elastography (SWE), and Shear Wave Dispersion (SWD) have the potential to assess liver steatosis, fibrosis and inflammation/oedema respectively. The aim was therefore to evaluate the feasibility of applying ultrasound-based liver biomarkers in children and adolescents with severe obesity. METHODS Ultrasound was performed, before treatment, in 56 patients with childhood obesity (< 18 years) referred for bariatric surgery or treatment with glucagon-like peptide-1 receptor agonists. An ultrasound visualisation score (A: no limitations - D: severe limitations) was used. ATI, SWE and SWD were measured, irrespective of visualisation score, and compared to clinical data, serological measures and depth of measurement. Scan-rescan reproducibility measurements were performed, both for continuous measures using intraclass correlation coefficient (ICC) and for kappa coefficient using proposed reference thresholds for elevated/pathological values in children during fasting and free-breathing: > ATI 0.56 dB/cm/MHz, > SWE 4.9 kPa and > SWD 11.9 (m/s)/kHz. RESULTS The median (min-max) age of the 56 patients (51.8% male) was 16.2 years (9.9; 18) and the median BMI standard deviation score (SDS) was 4.4 (2.7; 7.3). The distribution of the visibility score was A 5.5%, B 50%, C 41% and D 3.5%. The median (min-max) ATI, SWE and SWD values were 0.58 dB/cm/MHz (0.32; 0.97), 7.2 kPa (4.3; 19.6) and 14.3 (m/s)/kHz (8.9; 24.3) respectively. Both ATI (β = -4.2; r2 = 0.3; p < 0.0001) and SWD (β = 0.14; r2 = 0.17; p = 0.0033) were influenced by depth of measurement. A weak association was found between ATI and serum triglycerides (β = 0.07; r2 = 0.12; p = 0.015). SWE was associated with BMI-SDS (β = 0.71; r2 = 0.09; p = 0.035). No other significant associations were found. ICC was moderate for ATI (0.61), fair for SWE (0.46) and fair for SWD (0.51). Kappa coefficient was substantial for ATI (0.77), excellent for SWE (1.0) and moderate for SWD (0.53). CONCLUSION When accounting for visualization score, multiple ultrasound liver biomarkers appear applicable in most children and adolescents with severe obesity. Median ATI, SWE and SWD values were all increased, compared to currently known paediatric normal values. However, median ATI was likely underestimated due to depth dependence of measurement. Although caution is advised in clinical decision-making due to fair-moderate reproducibility between scans, most importantly, the biomarkers appear capable of differentiating between non-affected and affected liver in children with severe obesity.
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Affiliation(s)
- Ivan Cetinic
- Department of Radiology, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden.
- Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
| | - Charlotte de Lange
- Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Paediatric Radiology, Queen Silvia Children's Hospital, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
| | - Kerstin Lagerstrand
- Department of Radiology, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
| | - Jenny M Kindblom
- Department of Paediatrics, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
- Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Lovisa Sjögren
- Department of Paediatrics, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
- Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Hanna Hebelka
- Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Paediatric Radiology, Queen Silvia Children's Hospital, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
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Seif El Dahan K, Yokoo T, Daher D, Davenport MS, Fetzer DT, Mendiratta-Lala M, Rich NE, Yang E, Parikh ND, Singal AG. Multicenter evaluation of abbreviated MRI and ultrasound for detecting early-stage hepatocellular carcinoma. JHEP Rep 2025; 7:101357. [PMID: 40321196 PMCID: PMC12048809 DOI: 10.1016/j.jhepr.2025.101357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 02/06/2025] [Accepted: 02/10/2025] [Indexed: 05/08/2025] Open
Abstract
Background & aims Abbreviated MRI (AMRI) has been proposed as an alternative to ultrasound for hepatocellular carcinoma (HCC) surveillance; however, comparative data for AMRI and ultrasound are needed. Thus, we evaluated the sensitivity and specificity of dynamic contrast-enhanced (DCE)-AMRI and ultrasound for early-stage HCC detection in patients with cirrhosis. Methods We conducted a multicenter retrospective case-control study among patients with cirrhosis (cases with early-stage HCC as per Milan Criteria; controls without HCC) who underwent an ultrasound and a DCE-MRI within a 6-month period between 2012 and 2019. HCC diagnosis was confirmed by imaging alone in 85% and by histopathology in 15% of patients. Dynamic AMRI examinations were simulated from the full MRI by selecting relevant sequences. Independent, blinded interpretations of ultrasounds and AMRI results were performed using Liver Imaging Reporting and Data System algorithms. Ultrasounds were considered positive if US-3 observations were detected. AMRI was considered positive if LR-4, LR-5, or LR-M were detected. Per-patient sensitivity and specificity for early-stage HCC detection were estimated, and cross-modality differences were tested. Results We included 216 cases and 432 controls. Patient-level sensitivity and specificity of AMRI were significantly higher compared with ultrasound: 80.1% (95% CI 76.1-83.6) vs. 71.1% (95% CI 66.6-75.2), p <0.001, and 91.9% (95% CI 89.9-93.5) vs. 72.3% (95% CI 69.3-75.2), p <0.001, respectively. AMRI sensitivity was significantly higher compared with ultrasound among patients with Child-Pugh B cirrhosis (80.8% vs. 57.4%, p <0.001) but not among those with Child-Pugh A (84.7% vs. 78.6%, p = 0.07) or Child-Pugh C cirrhosis (52.6% vs. 68.4%, p = 0.18). Conclusions Dynamic AMRI may be more sensitive and specific for early-stage HCC detection in patients with cirrhosis compared with ultrasound, although its relative benefit might be smaller in patients with Child-Pugh A cirrhosis. Larger direct comparative data sets are needed, particularly among patients with Child-Pugh C cirrhosis who may benefit from alternative surveillance strategies. Impact and implications Abbreviated MRI (AMRI) is increasingly recognized as an alternative to ultrasound for hepatocellular carcinoma (HCC) surveillance. However, existing data are limited by single-center samples, spectrum bias, and lack of comparative data for AMRI vs. ultrasound. We found that AMRI had significantly higher per-patient sensitivity and specificity compared with ultrasound for the detection of early-stage HCC, although its relative benefit might be smaller in patients with Child-Pugh A cirrhosis, and both modalities underperformed in patients with Child-Pugh C cirrhosis. If sufficiently validated, AMRI could be adopted into practice guidelines for HCC surveillance and serve as a preferred alternative in select subgroups of patients.
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Affiliation(s)
- Karim Seif El Dahan
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Takeshi Yokoo
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Darine Daher
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Matthew S. Davenport
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Urology, University of Michigan, Ann Arbor, MI, USA
| | - David T. Fetzer
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | | | - Nicole E. Rich
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Edward Yang
- Division of Gastroenterology, Kaiser Permanente Medical Group, Riverside, CA, USA
| | - Neehar D. Parikh
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Amit G. Singal
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
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Seif El Dahan K, Yokoo T, Mendiratta-Lala M, Fetzer D, Davenport M, Daher D, Rich NE, Yang E, Parikh ND, Singal AG. Exam quality of ultrasound and dynamic contrast-enhanced abbreviated MRI and impact on early-stage HCC detection. Abdom Radiol (NY) 2025; 50:2097-2109. [PMID: 39542949 DOI: 10.1007/s00261-024-04674-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2024] [Revised: 10/31/2024] [Accepted: 11/02/2024] [Indexed: 11/17/2024]
Abstract
PURPOSE MRI is a potential alternative to ultrasound for hepatocellular carcinoma (HCC) detection. We evaluated the impact of ultrasound and dynamic abbreviated MRI (AMRI) exam quality on early-stage HCC detection. METHODS We conducted a multicenter case-control study among patients with cirrhosis (cases with early-stage HCC per Milan Criteria; controls without HCC) who underwent both a liver ultrasound and dynamic contrast-enhanced (DCE) AMRI within 6 months in 2012-2019. Two radiologists performed independent, blinded interpretations of both exams for HCC detection and scored exam quality as no/mild, moderate, or severe limitations. Associations between exam quality, patient characteristics, and HCC detection were assessed by odds ratios (OR). RESULTS Of 216 cases and 432 controls, severe limitations were reported in 7% and 8% of ultrasounds and DCE-AMRIs, respectively. Severe limitations at ultrasound were associated with obesity (OR 2.08, 95%CI [1.32-3.32]) and metabolic dysfunction-associated steatotic liver disease (MASLD) (OR 1.98 [1.12-3.44]) but not for DCE-AMRI. Decompensated cirrhosis (Child-Pugh C) was associated with severe limitations for both ultrasound (OR 2.54 [1.37-4.58]) and DCE-AMRI (OR 3.96 [2.36-6.58]). Compared to exams with no/mild limitations, exams with severe limitations had lower sensitivity for ultrasound (79.6% vs. 21.7%, P < 0.001) and AMRI (86.1% vs. 50.0%, P = 0.001). In patients in whom ultrasound was severely limited, DCE-AMRI had significantly higher odds of early-stage HCC detection than ultrasound (OR 8.23 [1.25-54.02]). CONCLUSIONS HCC detection by DCE-AMRI may be preferred in patients with severe limitations at ultrasound due to obesity and MASLD. Both modalities remain limited for patients with decompensated cirrhosis, for whom alternative strategies may be needed.
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Affiliation(s)
| | - Takeshi Yokoo
- The University of Texas Southwestern Medical Center, Dallas, USA
| | | | - David Fetzer
- The University of Texas Southwestern Medical Center, Dallas, USA
| | | | - Darine Daher
- The University of Texas Southwestern Medical Center, Dallas, USA
| | - Nicole E Rich
- The University of Texas Southwestern Medical Center, Dallas, USA
| | - Edward Yang
- The University of Texas Southwestern Medical Center, Dallas, USA
| | | | - Amit G Singal
- The University of Texas Southwestern Medical Center, Dallas, USA.
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Rafati I, Yazdani L, Barat M, Karam E, Fohlen A, Nguyen BN, Castel H, Tang A, Cloutier G. Ultrasound shear wave viscoelastography to characterize liver nodules. Phys Med Biol 2025; 70:075022. [PMID: 40127537 DOI: 10.1088/1361-6560/adc4b8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2024] [Accepted: 03/24/2025] [Indexed: 03/26/2025]
Abstract
Purpose. To investigate the diagnostic performance of ultrasound (US)-based shear wave speed (SWS), shear wave attenuation (SWA), and combination of them as shear wave viscoelastography (SWVE) methods in patients undergoing US to characterize focal liver nodules.Materials and methods. In this prospective cross-sectional study, 70 patients with 72 nodules were enrolled. Investigational US and clinical magnetic resonance imaging (MRI) examinations were performed in all participants. The composite reference standard included MRI or histopathology to differentiate benign and malignant nodules. A linear discriminant analysis (LDA) was used to assess the combination of SWVE methods. Analyzes included Mann-WhitneyUtest, receiver operating characteristic analysis, and computation of sensitivity and specificity at the point that maximized the Youden index.Results. Mean SWS was significantly higher in malignant than benign nodules (2.49 ± 0.76 m s-1vs. 1.72 ± 0.70,p< 0.001), whereas SWA was lower (0.56 ± 0.30 vs. 1.10 ± 0.43 Np/m/Hz,p< 0.001). To differentiate between malignant and benign nodules, SWS with a threshold of 2.43 m s-1achieved a sensitivity of 0.54 (95% confidence interval (CI): 0.38-0.69) and a specificity of 0.88 (CI: 0.74-0.95). SWA with a threshold of 0.81 Np/m/Hz yielded a sensitivity of 0.81 (CI: 0.66-0.90) and a specificity of 0.74 (CI: 0.58-0.86). Combining these SWVE methods using a LDA resulted in a sensitivity of 0.81 (CI: 0.66-0.91) and a specificity of 0.86 (CI: 0.71-0.94).Conclusion. Malignant nodules had higher SWS and lower SWA than benign ones. The combination of SWS and SWA in a LDA classification algorithm increased the diagnostic performance.
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Affiliation(s)
- Iman Rafati
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center, Montréal, Québec, Canada
- Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada
| | - Ladan Yazdani
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center, Montréal, Québec, Canada
- Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada
| | - Maxime Barat
- Department of Radiology, University of Montreal Hospital, Montréal, Québec, Canada
| | - Elige Karam
- Department of Radiology, University of Montreal Hospital, Montréal, Québec, Canada
| | - Audrey Fohlen
- Department of Radiology, University of Montreal Hospital, Montréal, Québec, Canada
| | - Bich N Nguyen
- Department of Pathology, University of Montreal Hospital, Montréal, Québec, Canada
| | - Hélène Castel
- Departments of Hepatology and Liver Transplantation, University of Montreal Hospital, Montréal, Québec, Canada
| | - An Tang
- Department of Radiology, University of Montreal Hospital, Montréal, Québec, Canada
- Department of Radiology, Radiation Oncology and Nuclear Medicine, University of Montreal, Montréal, Québec, Canada
- Laboratory of Clinical Image Processing, University of Montreal Hospital Research Center, Montréal, Québec, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center, Montréal, Québec, Canada
- Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada
- Department of Radiology, Radiation Oncology and Nuclear Medicine, University of Montreal, Montréal, Québec, Canada
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Lockhart ME. Editorial Comment: Updated LI-RADS Ultrasound Surveillance Version 2024 Detects More Hepatocellular Carcinomas Than Version 2017 in Patients With Cirrhosis. AJR Am J Roentgenol 2025; 224:e2532695. [PMID: 39878412 DOI: 10.2214/ajr.25.32695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2025]
Affiliation(s)
- Mark E Lockhart
- Department of Radiology, University of Alabama at Birmingham, JTN 344, 619 19th St S, Birmingham, AL 35249
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Lee DH. Recent advances and issues in imaging modalities for hepatocellular carcinoma surveillance. JOURNAL OF LIVER CANCER 2025; 25:31-40. [PMID: 40007309 PMCID: PMC12010830 DOI: 10.17998/jlc.2025.02.16] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2024] [Revised: 02/05/2025] [Accepted: 02/16/2025] [Indexed: 02/27/2025]
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide. Early detection via surveillance plays a crucial role in enabling curative treatment and improving survival rates. Since the initial randomized controlled trial, biannual ultrasound (US) has been established as the standard surveillance method because of its accessibility, safety, and low cost. However, US has some limitations, including operator dependency, suboptimal sensitivity for early-stage HCC, and challenges such as a limited sonic window that may result in inadequate examination. Alternative imaging modalities, including contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI), have demonstrated higher sensitivity for detecting very early-stage HCC. Recent advancements, such as low-dose CT with deep learning-based reconstruction, have enhanced the safety and feasibility of CT-based surveillance by reducing radiation exposure and amount of contrast media. MRI, particularly with gadoxetic acid or abbreviated protocols, offers superior tissue contrast and sensitivity, although its accessibility and cost remain challenges. Tailored surveillance strategies based on individual risk profiles and integration of advanced imaging technologies have the potential to enhance the detection performance and cost-effectiveness. This review highlights the recent developments in imaging technologies for HCC surveillance, focusing on their respective strengths and limitations.
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Affiliation(s)
- Dong Ho Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
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Lee S, Yoon JK, Shin J, Shin H, Aslam A, Kamaya A, Rodgers SK, Sirlin CB, Chernyak V. US Liver Imaging Reporting and Data System Version 2017: A Systematic Review and Meta-Analysis. Radiology 2025; 314:e240450. [PMID: 40067102 DOI: 10.1148/radiol.240450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2025]
Abstract
Background The US Liver Imaging Reporting and Data System (LI-RADS) includes an assessment category (US-1, negative; US-2, subthreshold; and US-3, positive) and a visualization score reflecting image quality (VIS-A, no or minimal limitations; VIS-B, moderate limitations; and VIS-C, severe limitations). The US-3 and VIS-C impact patient treatment. Purpose To establish the distributions of categories and visualization scores, estimate the proportions of hepatocellular carcinoma (HCC) and overall malignancy in the US-3 category, and identify variables associated with the VIS-C score by conducting a meta-analysis. Materials and Methods A systematic search of articles published between January 1, 2017, and September 17, 2023, identified studies reporting distributions of US LI-RADS version 2017 categories or visualization scores. Characteristics of the study design, patient cohorts, and outcomes of interest (distributions of US categories and visualization scores, percentages of probable or definite HCC and malignancy in US-3 category, and variables associated with VIS-C) were extracted. For the meta-analysis, estimates were established with random-effects models. Results Fifteen studies comprising 39 166 US examinations were included. Of all examinations, 89.7% (95% CI: 86.8, 91.8) were categorized US-1; 4.4% (95% CI: 2.8, 6.2), US-2; and 5.9% (95% CI: 4.1, 8.0), US-3. Of the US-3 examinations, 25.9% (95% CI: 17.1, 34.7) had probable or definite HCC and 26.4% (95% CI: 18.4, 34.5) had overall malignancy. Among all examinations, 59.7% (95% CI: 46.9, 67.8) were assigned VIS-A; 32.5% (95% CI: 21.9, 41.6), VIS-B; and 7.8% (95% CI: 2.8, 14.3), VIS-C. Obesity (odds ratio [OR], 2.37; 95% CI: 1.57, 3.59), nonalcoholic fatty liver disease (NAFLD) (OR, 2.24; 95% CI: 1.64, 3.06), and Child-Pugh B or C (OR, 2.41; 95% CI: 1.43, 4.06) were associated with VIS-C score. Conclusion Overall, 90% of surveillance US results were negative (US-1), and 92% were of adequate quality (VIS-A or VIS-B); 26% of patients with US-3 results had HCC. VIS-C was associated with obesity, NAFLD, and cirrhosis. Systemic review registry no. CRD42022384925 © RSNA, 2025 Supplemental material is available for this article.
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Affiliation(s)
- Sunyoung Lee
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Ja Kyung Yoon
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jaeseung Shin
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hyejung Shin
- Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Anum Aslam
- Department of Radiology, University of Michigan Medicine, Ann Arbor, Mich
| | - Aya Kamaya
- Department of Radiology, Stanford University School of Medicine, Stanford, Calif
| | - Shuchi K Rodgers
- Department of Radiology, University of Pennsylvania, Philadelphia, Pa
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif
| | - Victoria Chernyak
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
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Barr RG. US Screening for Liver Lesions in Patients at Risk for HCC: How Well Does LI-RADS US Scoring System Perform? Radiology 2025; 314:e250596. [PMID: 40131116 DOI: 10.1148/radiol.250596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2025]
Affiliation(s)
- Richard G Barr
- Northeastern Ohio Medical University, Rootstown, Ohio
- Southwoods Imaging, 7623 Market St, Youngstown, OH 44512
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Vutien P, Kim NJ, Nguyen MH. The Diagnosis and Staging of Hepatocellular Carcinoma: A Review of Current Practices. Clin Liver Dis 2025; 29:33-48. [PMID: 39608956 DOI: 10.1016/j.cld.2024.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2024]
Abstract
Promoting the early detection and diagnosis of hepatocellular carcinoma (HCC) is a critical strategy to improve patient outcomes as this can lead to greater access to curative treatments. This review highlights the diagnostic tests for HCC, including the use of the Liver Imaging Reporting and Data System systems and histopathology. Staging is essential for informing prognosis and guiding treatment decisions; this review also covers a widely used and well-validated staging system called the Barcelona-Clinic Liver Cancer (BCLC) algorithm. The BCLC incorporates tumor status, liver function, and patient performance to stage patients with newly diagnosed HCC.
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Affiliation(s)
- Philip Vutien
- Division of Gastroenterology and Hepatology, University of Washington Medical Center, 1536 North 115th Street, Suite 105, Box 358811, Seattle, WA 98133, USA.
| | - Nicole J Kim
- Division of Gastroenterology and Hepatology, University of Washington Medical Center, 1536 North 115th Street, Suite 105, Box 358811, Seattle, WA 98133, USA
| | - Mindie H Nguyen
- Division of Gastroenterology and Hepatology, University of Washington Medical Center, 325 9th Avenue, Box 359773, Seattle, WA 98104, USA; Stanford University Medical Center, 780 Welch Road, Suite CJ250K, Palo Alto, CA 94304, USA
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Sangro B, Argemi J, Ronot M, Paradis V, Meyer T, Mazzaferro V, Jepsen P, Golfieri R, Galle P, Dawson L, Reig M. EASL Clinical Practice Guidelines on the management of hepatocellular carcinoma. J Hepatol 2025; 82:315-374. [PMID: 39690085 DOI: 10.1016/j.jhep.2024.08.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2024] [Accepted: 08/29/2024] [Indexed: 12/19/2024]
Abstract
Liver cancer is the third leading cause of cancer-related deaths worldwide, with hepatocellular carcinoma (HCC) accounting for approximately 90% of primary liver cancers. Advances in diagnostic and therapeutic tools, along with improved understanding of their application, are transforming patient treatment. Integrating these innovations into clinical practice presents challenges and necessitates guidance. These clinical practice guidelines offer updated advice for managing patients with HCC and provide a comprehensive review of pertinent data. Key updates from the 2018 EASL guidelines include personalised surveillance based on individual risk assessment and the use of new tools, standardisation of liver imaging procedures and diagnostic criteria, use of minimally invasive surgery in complex cases together with updates on the integrated role of liver transplantation, transitions between surgical, locoregional, and systemic therapies, the role of radiation therapies, and the use of combination immunotherapies at various stages of disease. Above all, there is an absolute need for a multiparametric assessment of individual risks and benefits, considering the patient's perspective, by a multidisciplinary team encompassing various specialties.
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Bae SM, Kim DH, Kang JH. Inter-reader reliability of Ovarian-Adnexal Reporting and Data System US: a systematic review and meta-analysis. Abdom Radiol (NY) 2025:10.1007/s00261-025-04813-2. [PMID: 39841229 DOI: 10.1007/s00261-025-04813-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2024] [Revised: 01/12/2025] [Accepted: 01/17/2025] [Indexed: 01/23/2025]
Abstract
PURPOSE Ovarian-Adnexal Reporting and Data System (O-RADS) US provides a standardized lexicon for ovarian and adnexal lesions, facilitating risk stratification based on morphological features for malignancy assessment, which is essential for proper management. However, systematic determination of inter-reader reliability in O-RADS US categorization remains unexplored. This study aimed to systematically determine the inter-reader reliability of O-RADS US categorization and identify the factors that affect it. METHODS Original articles reporting the inter-reader reliability of O-RADS US in lesion categorization were identified in the MEDLINE, EMBASE, and Web of Science databases from January 2018 to December 2023. DerSimonian-Laird random-effects models were used to determine the meta-analytic pooled inter-reader reliability of the O-RADS US categorization. Subgroup meta-regression analysis was performed to identify the factors causing study heterogeneity. RESULTS Fourteen original articles with 5139 ovarian and adnexal lesions were included. The inter-reader reliability of O-RADS US in lesion categorization ranged from 0.71 to 0.99, with a meta-analytic pooled estimate of 0.83 (95% CI, 0.78-0.88), indicating almost perfect reliability. Substantial study heterogeneity was observed in the inter-reader reliability of the O-RADS US categorization (I2 = 96.9). In subgroup meta-regression analysis, reader experience was the only factor associated with study heterogeneity. Pooled inter-reader reliability of the O-RADS US categorization was higher in studies with all experienced readers (0.86; 95% CI, 0.81-0.91) compared to those with multiple readers including trainees (0.74; 95% CI, 0.70-0.78; P = 0.009). The inter-reader reliability of US descriptors ranged from 0.39 to 0.97, with ascites and peritoneal nodules showing almost perfect reliability (0.79- 0.97). CONCLUSION The O-RADS US risk stratification system demonstrated almost perfect inter-reader reliability in lesion categorization. Our results highlight the importance of targeted training and descriptor simplification to improve inter-reader reliability and clinical adoption.
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Affiliation(s)
- Sang Min Bae
- Hanyang University Guri Hospital, Guri-si, Korea, Republic of
| | | | - Ji Hun Kang
- Hanyang University Guri Hospital, Guri-si, Korea, Republic of.
- Hanyang University, Seoul, Republic of Korea.
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Kamaya A, Fetzer DT, Seow JH, Burrowes DP, Choi HH, Dawkins AA, Fung C, Gabriel H, Hong CW, Khurana A, McGillen KL, Morgan TA, Sirlin CB, Tse JR, Rodgers SK. LI-RADS US Surveillance Version 2024 for Surveillance of Hepatocellular Carcinoma: An Update to the American College of Radiology US LI-RADS. Radiology 2024; 313:e240169. [PMID: 39625378 DOI: 10.1148/radiol.240169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2024]
Abstract
In 2017, the American College of Radiology introduced the US Liver Imaging Reporting and Data System (LI-RADS) as a framework for US surveillance of patients at risk for developing hepatocellular carcinoma. This has aided in the standardization of technique, clinical reporting, patient management, data collection, and research. Emerging evidence has helped inform changes to the algorithm, now released as LI-RADS US Surveillance version 2024. The updated algorithm, the rationale for changes, and its alignment with the 2023 American Association for the Study of Liver Diseases Practice Guidance are presented.
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Affiliation(s)
- Aya Kamaya
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - David T Fetzer
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - James H Seow
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - David P Burrowes
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Hailey H Choi
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Adrian A Dawkins
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Christopher Fung
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Helena Gabriel
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Cheng William Hong
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Aman Khurana
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Kathryn L McGillen
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Tara A Morgan
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Claude B Sirlin
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Justin R Tse
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
| | - Shuchi K Rodgers
- From the Department of Radiology, Stanford University, 300 Pasteur Dr, Palo Alto, CA 94304 (A. Kamaya, J.R.T.); The University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, Royal Perth Hospital, Perth, Western Australia, Australia (J.H.S.); Department of Radiology, University of Calgary, Calgary, Alberta, Canada (D.P.B.); Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, Calif (H.H.C., C.W.H.); Department of Radiology, University of Kentucky, Lexington, Ky (A.A.D.); MIC Medical Imaging, Edmonton, Alberta, Canada (C.F.); Department of Radiology, Northwestern University, Chicago, Ill (H.G.); Department of Radiology, University of California at San Diego, UC San Diego Medical Center, San Diego, Calif (A. Khurana); Liver Imaging Group, Department of Radiology, UC San Diego, San Diego, Calif (C.B.S.); Penn State Health Milton S. Hershey Medical Center, Hershey, Pa (K.L.M.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (T.A.M.); and Department of Radiology, Thomas Jefferson University, Cherry Hill, NJ (S.K.R.)
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Shanbhogue K, Chandarana H. Imaging of Cirrhosis and Hepatocellular Carcinoma: Current Evidence. Radiol Clin North Am 2024; 62:1013-1023. [PMID: 39393847 DOI: 10.1016/j.rcl.2024.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/13/2024]
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide. Early detection of HCC is a key factor in enabling curative therapies and improving overall survival. Worldwide, several guidelines are available for surveillance of at-risk populations and diagnosis of HCC. This article provides a current comprehensive update on screening and diagnosis of HCC.
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Affiliation(s)
- Krishna Shanbhogue
- Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY 10016, USA.
| | - Hersh Chandarana
- Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY 10016, USA
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14
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Kazi IA, Jahagirdar V, Kabir BW, Syed AK, Kabir AW, Perisetti A. Role of Imaging in Screening for Hepatocellular Carcinoma. Cancers (Basel) 2024; 16:3400. [PMID: 39410020 PMCID: PMC11476228 DOI: 10.3390/cancers16193400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Revised: 09/22/2024] [Accepted: 09/26/2024] [Indexed: 10/20/2024] Open
Abstract
Primary liver cancer is among the most common cancers globally. It is the sixth-most common malignancy encountered and the third-most common cause of cancer-related death. Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, accounting for about 90% of primary liver cancers. The majority of HCCs occur in patients with underlying cirrhosis, which results from chronic liver diseases such as fatty liver, hepatitis B and hepatitis C infections, and chronic alcohol use, which are the leading causes. The obesity pandemic has led to an increased prevalence of nonalcoholic fatty liver disease (NAFLD), which leads to nonalcoholic steatohepatitis and could progress to cirrhosis. As HCC is among the most common cancers and occurs in the setting of chronic liver disease in most patients, screening the population at risk could help in early diagnosis and management, leading to improved survival. Screening for HCC is performed using biochemical marker testing such as α-fetoprotein (AFP) and cross-sectional imaging. It is critical to emphasize that HCC could potentially occur in patients without cirrhosis (non-cirrhotic HCC), which can account for almost 20% of all HCCs. The lack of cirrhosis can cause a delay in surveillance, which could potentially lead to diagnosis at a later stage, worsening the prognosis for such patients. In this article, we discuss the diagnosis of cirrhosis in at-risk populations with details on the different modalities available for screening HCC in patients with cirrhosis, emphasizing the role of abdominal ultrasounds, the primary imaging modality in HCC screening.
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Affiliation(s)
- Irfan A. Kazi
- Department of Radiology, University of Missouri Columbia, Columbia, MO 65212, USA;
| | - Vinay Jahagirdar
- Division of Gastroenterology, Hepatology and Nutrition, Virginia Commonwealth University, Richmond, VA 23298, USA;
| | - Bareen W. Kabir
- Department of Internal Medicine, University of Missouri Columbia, Columbia, MO 65212, USA;
| | - Almaan K. Syed
- Blue Valley Southwest High School, Overland Park, KS 6622, USA;
| | | | - Abhilash Perisetti
- Division of Gastroenterology and Hepatology, Kansas City Veteran Affairs, Kansas City, MO 64128, USA
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Maung ST, Tanpowpong N, Satja M, Treeprasertsuk S, Chaiteerakij R. MRI for hepatocellular carcinoma and the role of abbreviated MRI for surveillance of hepatocellular carcinoma. J Gastroenterol Hepatol 2024; 39:1969-1981. [PMID: 38899804 DOI: 10.1111/jgh.16643] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 05/16/2024] [Accepted: 05/24/2024] [Indexed: 06/21/2024]
Abstract
INTRODUCTION Hepatocellular carcinoma (HCC) constitutes the majority of liver cancers and significantly impacts global cancer mortality. While ultrasound (US) with or without alpha-fetoprotein is the mainstay for HCC surveillance, its limitations highlight the necessity for more effective surveillance tools. Therefore, this review explores evolving imaging modalities and abbreviated magnetic resonance imaging (MRI) (AMRI) protocols as promising alternatives, addressing challenges in HCC surveillance. AREAS COVERED This comprehensive review delves into the evaluation and challenges of HCC surveillance tools, focusing on non-contrast abbreviated MRI (NC-AMRI) and contrast-enhanced abbreviated MRI protocols. It covers the implementation of AMRI for HCC surveillance, patient preferences, adherence, and strategies for optimizing cost-effectiveness. Additionally, the article provides insights into prospects for HCC surveillance by summarizing meta-analyses, prospective studies, and ongoing clinical trials evaluating AMRI protocols. EXPERT OPINION The opinions underscore the transformative impact of AMRI on HCC surveillance, especially in overcoming US limitations. Promising results from NC-AMRI protocols indicate its potential for high-risk patient surveillance, though prospective studies in true surveillance settings are essential for validation. Future research should prioritize risk-stratified AMRI protocols and address cost-effectiveness for broader clinical implementation, alongside comparative analyses with US for optimal surveillance strategies.
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Affiliation(s)
- Soe Thiha Maung
- Division of Gastroenterology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Ma Har Myaing Hospital, Yangon, Myanmar
| | - Natthaporn Tanpowpong
- Division of Diagnostic Radiology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Minchanat Satja
- Division of Diagnostic Radiology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Sombat Treeprasertsuk
- Division of Gastroenterology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Roongruedee Chaiteerakij
- Division of Gastroenterology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence for Innovation and Endoscopy in Gastrointestinal Oncology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
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16
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Vithayathil M, Qurashi M, Vicente PR, Alsafi A, Naik M, Graham A, Khan S, Lewis H, Dhar A, Smith B, Selvapatt N, Manousou P, Possamai L, Izadi H, Lim A, Tait P, Sharma R. Prospective Study of Non-Contrast, Abbreviated MRI for Hepatocellular Carcinoma Surveillance in Patients with Suboptimal Hepatic Visualisation on Ultrasound. Cancers (Basel) 2024; 16:2709. [PMID: 39123437 PMCID: PMC11312001 DOI: 10.3390/cancers16152709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Accepted: 07/26/2024] [Indexed: 08/12/2024] Open
Abstract
BACKGROUND Biannual ultrasound (US) is recommended for hepatocellular carcinoma (HCC) surveillance in patients with cirrhosis. However, US has limited sensitivity for early-stage HCC, particularly in overweight cohorts, where hepatic visualisation is often inadequate. Currently there are no robust imaging surveillance strategies in patients with inadequate US visualisation. We investigated the ability of non-contrast, abbreviated magnetic resonance imaging (aMRI) to adequately visualise the liver for HCC surveillance in patients with previously inadequate US. METHODS Patients undergoing US surveillance, where liver visualisation was inadequate (LI-RADS VIS-B and VIS-C), were prospectively recruited. Patients underwent non-contrast T2-weighted and diffusion-weighted aMRI. The images were reviewed and reported by an expert liver radiologist. Three independent, blinded radiologists assessed the aMRI visualisation quality using a binary score assessing five parameters (parenchymal definition, vascular definition, coverage of the liver, uniformity of liver appearance and signal-to-noise ratio). RESULTS Thirty patients completed the aMRI protocol. The majority (90%) had underlying cirrhosis and were overweight (93.3%), with 50% obese and 20% severely obese. A total of 93.3% of the aMRI scans were of satisfactory quality. Six patients (20%) had hepatic abnormalities detected with aMRI that were not seen on their US: one HCC, one haemangioma and three clinically insignificant lesions. For the aMRI visualisation quality assessment, the coverage of the liver, vascular definition and parenchymal definition were consistently rated to be of sufficient quality by all three radiologists. CONCLUSIONS Non-contrast aMRI provided good visualisation of the liver and detection of abnormalities in patients with inadequate US. aMRI should be further explored in a larger, prospective study as an alternative surveillance strategy in patients with inadequate US.
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Affiliation(s)
- Mathew Vithayathil
- Department of Surgery and Cancer, Imperial College London, London W12 0NN, UK; (M.V.)
| | - Maria Qurashi
- Department of Surgery and Cancer, Imperial College London, London W12 0NN, UK; (M.V.)
| | | | - Ali Alsafi
- Department of Interventional Radiology, Imperial College Healthcare NHS Trust, London W12 0HS, UK
| | - Mitesh Naik
- Department of Nuclear Medicine, Imperial College Healthcare NHS Trust, London W12 0HS, UK;
| | - Alison Graham
- Department of Interventional Radiology, Imperial College Healthcare NHS Trust, London W12 0HS, UK
| | - Shahid Khan
- Department of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK (A.D.); (N.S.)
| | - Heather Lewis
- Department of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK (A.D.); (N.S.)
| | - Ameet Dhar
- Department of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK (A.D.); (N.S.)
| | - Belinda Smith
- Department of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK (A.D.); (N.S.)
| | - Nowlan Selvapatt
- Department of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK (A.D.); (N.S.)
| | - Pinelopi Manousou
- Department of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK (A.D.); (N.S.)
| | - Lucia Possamai
- Department of Hepatology, Imperial College Healthcare NHS Trust, London W12 0HS, UK (A.D.); (N.S.)
| | - Hooshang Izadi
- School of Engineering, Computing and Mathematics, Oxford Brookes University, Oxford OX3 0BP, UK
| | - Adrian Lim
- Department of Radiology, Imperial College Healthcare NHS Trust, London W12 0HS, UK
| | - Paul Tait
- Department of Interventional Radiology, Imperial College Healthcare NHS Trust, London W12 0HS, UK
| | - Rohini Sharma
- Department of Surgery and Cancer, Imperial College London, London W12 0NN, UK; (M.V.)
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17
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Mendiratta-Lala M, Fetzer D, Kamaya A, Parikh ND, Singal AG. The Future Role of Abdominal US in Hepatocellular Carcinoma Surveillance. Radiology 2024; 311:e232624. [PMID: 38742973 PMCID: PMC11140528 DOI: 10.1148/radiol.232624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 12/16/2023] [Accepted: 12/26/2023] [Indexed: 05/16/2024]
Abstract
Abdominal US is currently the best-validated surveillance strategy for hepatocellular carcinoma (HCC) in at-risk patients. It is the only modality shown to have completed all five phases of validation and can achieve high sensitivity and specificity for HCC detection, especially when conducted by expert sonographers in high-volume centers. However, US also has limitations, including operator dependency and varying sensitivity in clinical practice. Further, the sensitivity of US for early-stage HCC detection is lower in patients with obesity or nonviral liver disease, increasingly common populations undergoing surveillance. Imaging-based and blood-based surveillance strategies, including abbreviated MRI and biomarker panels, may overcome some limitations of US-based surveillance. Both strategies have promising test performance in phase II and phase III biomarker studies and are undergoing prospective validation. Considering the variation in HCC risk and test performance between patients, there will likely be a shift away from a one-size-fits-all approach and toward precision screening, in which the "best" test is selected based on individual patient characteristics. In this upcoming era of precision HCC screening among patients with cirrhosis, US will likely continue to have an important, albeit reduced, surveillance role.
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Affiliation(s)
| | | | - Aya Kamaya
- From the Departments of Radiology (M.M.L.) and Internal Medicine
(N.D.P.), University of Michigan, Ann Arbor, Mich; Department of Radiology
(D.F.) and Department of Internal Medicine, Division of Digestive and Liver
Diseases (A.G.S.), University of Texas Southwestern Medical Center, 5959 Harry
Hines Blvd, Ste 420, POB 1, Dallas, TX 75390-8887; and Department of Radiology,
Stanford University School of Medicine, Stanford, Calif (A.K.)
| | - Neehar D. Parikh
- From the Departments of Radiology (M.M.L.) and Internal Medicine
(N.D.P.), University of Michigan, Ann Arbor, Mich; Department of Radiology
(D.F.) and Department of Internal Medicine, Division of Digestive and Liver
Diseases (A.G.S.), University of Texas Southwestern Medical Center, 5959 Harry
Hines Blvd, Ste 420, POB 1, Dallas, TX 75390-8887; and Department of Radiology,
Stanford University School of Medicine, Stanford, Calif (A.K.)
| | - Amit G. Singal
- From the Departments of Radiology (M.M.L.) and Internal Medicine
(N.D.P.), University of Michigan, Ann Arbor, Mich; Department of Radiology
(D.F.) and Department of Internal Medicine, Division of Digestive and Liver
Diseases (A.G.S.), University of Texas Southwestern Medical Center, 5959 Harry
Hines Blvd, Ste 420, POB 1, Dallas, TX 75390-8887; and Department of Radiology,
Stanford University School of Medicine, Stanford, Calif (A.K.)
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18
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Takada H, Komiyama Y, Osawa L, Muraoka M, Suzuki Y, Sato M, Kobayashi S, Yoshida T, Takano S, Maekawa S, Enomoto N. Usefulness of Body Position Change during Local Ablation Therapies for the High-Risk Location Hepatocellular Carcinoma. Cancers (Basel) 2024; 16:1036. [PMID: 38473393 DOI: 10.3390/cancers16051036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 02/25/2024] [Accepted: 03/01/2024] [Indexed: 03/14/2024] Open
Abstract
Local ablation therapies are important treatment options for early-stage hepatocellular carcinoma (HCC). Various techniques have been used to perform these therapies efficiently and safely. However, few reports have discussed the usefulness of body position change (BPC). This study aimed to investigate the usefulness of BPC during local ablation therapies in patients with HCC. We evaluated 283 HCC nodules that underwent local ablation therapy. These nodules were categorized into high- or low-risk locations on the basis of their proximity to large vessels, adjacent extrahepatic organs, or poor visibility under ultrasound (US) guidance. The technical success rates, procedure time, and prognosis were evaluated. In this study, 176 (62%) nodules were classified in the high-risk location group. The high-risk location group was treated with techniques such as BPC, artificial pleural fluid, artificial ascites, fusion imaging, and contrast-enhanced US more frequently than the low-risk location group. The technical success rates were 96% and 95% for the high- and low-risk location groups, respectively. Within the high-risk location group, those without BPC had a lower success rate than those with BPC (91% vs. 99%, p = 0.015). Notably, BPC emerged as the sole contributing factor to the technical success rate in the high-risk location group (OR = 10, 95% CI 1.2-86, p = 0.034). In contrast, no differences were found in the procedure time, local tumor progression rates, intrahepatic distant recurrence rates, and overall survival between the groups with and without BPC in the high-risk location group. In conclusion, BPC during local ablation therapy in patients with HCC in high-risk locations was safe and efficient. The body position should be adjusted for HCC in high-risk locations to maintain good US visibility and ensure a safe puncture route in patients undergoing local ablation therapies.
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Affiliation(s)
- Hitomi Takada
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Yasuyuki Komiyama
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Leona Osawa
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Masaru Muraoka
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Yuichiro Suzuki
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Mitsuaki Sato
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Shoji Kobayashi
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Takashi Yoshida
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Shinichi Takano
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Shinya Maekawa
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
| | - Nobuyuki Enomoto
- Gastroenterology and Hepatology Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan
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19
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Koh JH, Wang M, Suzuki H, Muthiah M, Ng CH, Huang DQ. NAFLD and NAFLD-related HCC in Asia: Burden and Surveillance. J Clin Exp Hepatol 2024; 14:101213. [PMID: 38076360 PMCID: PMC10701133 DOI: 10.1016/j.jceh.2023.06.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 06/30/2023] [Indexed: 06/21/2024] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is rapidly emerging as a leading etiology of chronic liver disease (CLD) in Asia. The increasing incidence of NAFLD is projected to drive a surge in NAFLD-related hepatocellular carcinoma (HCC). A notable characteristic of NAFLD-HCC is its capacity for development in individuals without cirrhosis in more than a third of patients. Most practice guidelines recommend biannual ultrasound screening for patients with cirrhosis. In cases of severe limitations to ultrasound visualisation, cross-sectional abdominal imaging may be warranted. Improved strategies for HCC risk stratification are required for people with NAFLD but without cirrhosis. In this Review, we discuss the evolving trends of NAFLD and HCC in Asia, and implications for surveillance.
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Affiliation(s)
- Jia H. Koh
- Department of Medicine, National University Hospital, Singapore, Singapore
| | - Meng Wang
- Department of Medicine, National University Hospital, Singapore, Singapore
| | - Hiroyuki Suzuki
- Division of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Kurume, Japan
| | - Mark Muthiah
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, Singapore, Singapore
| | - Cheng H. Ng
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, Singapore, Singapore
| | - Daniel Q. Huang
- NAFLD Research Center, University of California at San Diego, USA
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20
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Huang H, Cheng MQ, He DN, Xian MF, Zeng D, Wu SH, Li CQ, Ruan SM, Li MD, Lin MX, Lu MD, Kuang M, Wang W, Chen LD. US LI-RADS in surveillance for recurrent hepatocellular carcinoma after curative treatment. Eur Radiol 2023; 33:9357-9367. [PMID: 37460801 DOI: 10.1007/s00330-023-09903-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 03/24/2023] [Accepted: 04/19/2023] [Indexed: 11/26/2023]
Abstract
OBJECTIVES To investigate the performance of US LI-RADS in surveillance for recurrent hepatocellular carcinoma (RHCC) after curative treatment. MATERIALS AND METHODS This study enrolled 644 patients between January 2018 and August 2018 as a derivation cohort, and 397 patients from September 2018 to December 2018 as a validation cohort. The US surveillance after HCC curative treatment was performed. The US LI-RADS observation categories and visualization scores were analyzed. Four criteria using US LI-RADS or Alpha-fetoprotein (AFP) as the surveillance algorithm were evaluated. The sensitivity, specificity, and negative predictive value (NPV) were calculated. RESULTS A total of 212 (32.9%) patients in derivation cohort and 158 (39.8%) patients in validation cohort were detected to have RHCCs. The criterion of US-2/3 or AFP ≥ 20 µg/L had higher sensitivity (derivation, 96.7% vs 92.9% vs 81.1% vs 90.6%; validation, 96.2% vs 90.5% vs 80.4% vs 89.9%) and NPV (derivation, 95.7% vs 93.3% vs 88.0% vs 91.8%; validation, 94.6% vs 89.4% vs 83.6% vs 89.0%), but lower specificity (derivation, 35.9% vs 48.2% vs 67.6% vs 51.9%; validation, 43.5% vs 52.7% vs 66.1% vs 54.0%) than criterion of US-2/3, US-3, and US-3 or AFP ≥ 20 µg/L. Analysis of the visualization score subgroups confirmed that the sensitivity (89.2-97.6% vs 81.0-83.3%) and NPV(88.4-98.0% vs 80.0-83.3%) of score A and score B groups were higher than score C group in criterion of US-2/3 in both two cohorts. CONCLUSIONS In the surveillance for RHCC, US LI-RADS with AFP had a high sensitivity and NPV when US-2/3 or AFP ≥ 20 µg/L was considered a criterion. CLINICAL RELEVANCE STATEMENT The criterion of US-2/3 or AFP ≥ 20 µg/L improves sensitivity and NPV for RHCC surveillance, which provides a valuable reference for patients in RHCC surveillance after curative treatment. KEY POINTS • US LI-RADS with AFP had high sensitivity and NPV in surveillance for RHCC when considering US-2/3 or AFP ≥ 20 µg/L as a criterion. • After US with AFP surveillance, patients with US-2/3 or AFP ≥ 20 µg/L should perform enhanced imaging for confirmative diagnosis. Patients with US-1 or AFP < 20 µg/L continue to repeat US with AFP surveillance. • Patients with risk factors for poor visualization scores limited the sensitivity of US surveillance in RHCC.
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Affiliation(s)
- Hui Huang
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
| | - Mei-Qing Cheng
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
| | - Dan-Ni He
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
- Department of Medical Ultrasonics, the Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
| | - Meng-Fei Xian
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
| | - Dan Zeng
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
| | - Shao-Hong Wu
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
| | - Chao-Qun Li
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
- Department of Ultrasound Medicine, West China Xiamen Hospital of Sichuan University, Xiamen, China
| | - Si-Min Ruan
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
| | - Ming-De Li
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
| | - Man-Xia Lin
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
| | - Ming-De Lu
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
- Department of Hepatobiliary Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Ming Kuang
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
- Department of Hepatobiliary Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Wei Wang
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China
| | - Li-Da Chen
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China.
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21
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Kim YY, Cho SB, Lee JS, Lee HW, Choi JY, Kim SU. Utility of fusion imaging for the evaluation of ultrasound quality in hepatocellular carcinoma surveillance. Ultrasonography 2023; 42:580-588. [PMID: 37722723 PMCID: PMC10555691 DOI: 10.14366/usg.23106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/11/2023] [Accepted: 08/15/2023] [Indexed: 09/20/2023] Open
Abstract
PURPOSE This study evaluated the quality of surveillance ultrasound (US) for hepatocellular carcinoma (HCC) utilizing fusion imaging. METHODS This research involved a secondary analysis of a prospectively recruited cohort. Under institutional review board approval, participants referred for surveillance US who had undergone liver computed tomography (CT) or magnetic resonance imaging (MRI) within the past year were screened between August 2022 and January 2023. After patient consent was obtained, the US visualization score in the Liver Imaging Reporting and Data System was assessed with fusion imaging at the time of examination. This score was compared to that of conventional US using the extended McNemar test. Multivariable logistic regression analysis was used to identify factors independently associated with a US visualization score of B or C. Factors limiting visualization of focal lesions were recorded during fusion imaging. RESULTS Among the 105 participants (mean age, 59±11 years; 66 men), US visualization scores of B and C were assigned to 57 (54.3%) and 17 (16.2%) participants, respectively, by conventional US and 54 (51.4%) and 32 (30.5%) participants, respectively, by fusion imaging. The score distribution differed significantly between methods (P=0.010). Male sex was independently associated with US visualization scores of B or C (adjusted odds ratio, 3.73 [95% confidence interval, 1.30 to 10.76]; P=0.015). The most common reason (64.5%) for lesion nondetection was a limited sonic window. CONCLUSION Conventional US may underestimate the limitations of the sonic window relative to real-time fusion imaging with pre-acquired CT or MRI in the surveillance of HCC.
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Affiliation(s)
- Yeun-Yoon Kim
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Seo-Bum Cho
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Jae Seung Lee
- Department of Internal Medicine and Institute of Gastroenterology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Hye Won Lee
- Department of Internal Medicine and Institute of Gastroenterology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Jin-Young Choi
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Seung Up Kim
- Department of Internal Medicine and Institute of Gastroenterology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
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22
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Vianna P, Calce SI, Boustros P, Larocque-Rigney C, Patry-Beaudoin L, Luo YH, Aslan E, Marinos J, Alamri TM, Vu KN, Murphy-Lavallée J, Billiard JS, Montagnon E, Li H, Kadoury S, Nguyen BN, Gauthier S, Therien B, Rish I, Belilovsky E, Wolf G, Chassé M, Cloutier G, Tang A. Comparison of Radiologists and Deep Learning for US Grading of Hepatic Steatosis. Radiology 2023; 309:e230659. [PMID: 37787678 DOI: 10.1148/radiol.230659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
Background Screening for nonalcoholic fatty liver disease (NAFLD) is suboptimal due to the subjective interpretation of US images. Purpose To evaluate the agreement and diagnostic performance of radiologists and a deep learning model in grading hepatic steatosis in NAFLD at US, with biopsy as the reference standard. Materials and Methods This retrospective study included patients with NAFLD and control patients without hepatic steatosis who underwent abdominal US and contemporaneous liver biopsy from September 2010 to October 2019. Six readers visually graded steatosis on US images twice, 2 weeks apart. Reader agreement was assessed with use of κ statistics. Three deep learning techniques applied to B-mode US images were used to classify dichotomized steatosis grades. Classification performance of human radiologists and the deep learning model for dichotomized steatosis grades (S0, S1, S2, and S3) was assessed with area under the receiver operating characteristic curve (AUC) on a separate test set. Results The study included 199 patients (mean age, 53 years ± 13 [SD]; 101 men). On the test set (n = 52), radiologists had fair interreader agreement (0.34 [95% CI: 0.31, 0.37]) for classifying steatosis grades S0 versus S1 or higher, while AUCs were between 0.49 and 0.84 for radiologists and 0.85 (95% CI: 0.83, 0.87) for the deep learning model. For S0 or S1 versus S2 or S3, radiologists had fair interreader agreement (0.30 [95% CI: 0.27, 0.33]), while AUCs were between 0.57 and 0.76 for radiologists and 0.73 (95% CI: 0.71, 0.75) for the deep learning model. For S2 or lower versus S3, radiologists had fair interreader agreement (0.37 [95% CI: 0.33, 0.40]), while AUCs were between 0.52 and 0.81 for radiologists and 0.67 (95% CI: 0.64, 0.69) for the deep learning model. Conclusion Deep learning approaches applied to B-mode US images provided comparable performance with human readers for detection and grading of hepatic steatosis. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Tuthill in this issue.
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Affiliation(s)
- Pedro Vianna
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Sara-Ivana Calce
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Pamela Boustros
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Cassandra Larocque-Rigney
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Laurent Patry-Beaudoin
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Yi Hui Luo
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Emre Aslan
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - John Marinos
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Talal M Alamri
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Kim-Nhien Vu
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Jessica Murphy-Lavallée
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Jean-Sébastien Billiard
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Emmanuel Montagnon
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Hongliang Li
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Samuel Kadoury
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Bich N Nguyen
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Shanel Gauthier
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Benjamin Therien
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Irina Rish
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Eugene Belilovsky
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Guy Wolf
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Michaël Chassé
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - Guy Cloutier
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
| | - An Tang
- From the Department of Imaging and Engineering (P.V., S.I.C., C.L.R., L.P.B., E.M., H.L., S.K., M.C., G.C., A.T.), Laboratory of Biorheology and Medical Ultrasonics (P.V., G.C.), and Clinical Laboratory of Image Processing (E.M., A.T.), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada; Institute of Biomedical Engineering (P.V., G.C.) and Department of Computer Science and Operations Research (S.G., I.R., G.W.), Université de Montréal, Montréal, Canada; Departments of Radiology (S.I.C., P.B., C.L.R., L.P.B., Y.H.L., E.A., J.M., T.M.A., K.N.V., J.M.L., J.S.B., A.T.) and Pathology (B.N.N.), Centre Hospitalier de l'Université de Montréal (CHUM), 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Canada (S.K.); Mila-Quebec Artificial Intelligence Institute, Montréal, Canada (S.G., B.T., I.R., E.B., G.W.); and Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada (B.T., E.B.)
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Girardet R, Dubois M, Manasseh G, Jreige M, Du Pasquier C, Canniff E, Gulizia M, Bonvin M, Aleman Y, Taouli B, Fraga M, Dromain C, Vietti Violi N. The combination of non-contrast abbreviated MRI and alpha foetoprotein has high performance for hepatocellular carcinoma screening. Eur Radiol 2023; 33:6929-6938. [PMID: 37464111 PMCID: PMC10511584 DOI: 10.1007/s00330-023-09906-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 06/09/2023] [Indexed: 07/20/2023]
Abstract
OBJECTIVES This study aimed to compare two abbreviated MRI (AMRI) protocols to complete MRI for HCC detection: non-contrast (NC)-AMRI without/with alpha foetoprotein (AFP) and dynamic contrast-enhanced (Dyn)-AMRI. METHODS This retrospective single-center study included 351 patients (M/F: 264/87, mean age: 57y) with chronic liver disease, who underwent MRI for HCC surveillance between 2014 and 2020. Two reconstructed AMRI sets were obtained based on complete MRI: NC-AMRI (T2-weighted imaging (WI) + diffusion-WI) and Dyn-AMRI (T2-WI + dynamic T1-WI) and were assessed by 2 radiologists who reported all suspicious lesions, using LI-RADS/adapted LI-RADS classification. The reference standard was based on all available patient data. Inter-reader agreement was assessed and MRI diagnostic performance was compared to the reference standard. RESULTS The reference standard demonstrated 83/351 HCC-positive patients (prevalence: 23.6%, median size: 22 mm, and positive MRIs: 83/631). Inter-reader agreement was substantial for all sets. Sensitivities of Dyn-AMRI and complete MRI (both 92.8%) were similar, higher than NC-AMRI (72.3%, p < 0.001). Specificities were not different between sets. NC-AMRI + AFP (92.8%) had similar sensitivity to Dyn-AMRI and complete MRI. In patients with small size HCCs (≤ 2 cm), sensitivities of Dyn-AMRI (85.3%) and complete MRI (88.2%) remained similar (p = 0.564), also outperforming NC-AMRI (52.9%, p < 0.05). NC-AMRI + AFP had similar sensitivity (88.2%) to Dyn-AMRI and complete MRI (p = 0.706 and p = 1, respectively). CONCLUSIONS Dyn-AMRI has similar diagnostic performance to complete MRI for HCC detection, while both outperform NC-AMRI, especially for small size HCCs. NC-AMRI + AFP demonstrates similar sensitivity to Dyn-AMRI and complete MRI. CLINICAL RELEVANCE STATEMENT Due to the low sensitivity of ultrasound for hepatocellular screening, new screening methods are needed. Abbreviated MRI (AMRI) is a candidate, especially non-contrast AMRI with serum alpha foetoprotein as the acquisition time is low, without the need for contrast medium injection. KEY POINTS • Dynamic contrast-enhanced abbreviated MRI using extracellular gadolinium-based contrast agent and complete MRI have similar diagnostic performance for hepatocellular carcinoma detection in an at-risk population. • Non-contrast abbreviated MRI with alpha foetoprotein has similar diagnostic performance to dynamic contrast-enhanced abbreviated MRI and complete MRI, including when considering small size hepatocellular carcinoma ≤ 2 cm. • Non-contrast abbreviated MRI and dynamic contrast-enhanced abbreviated MRI can be performed in 7 and 10 min, excluding patient setup time.
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Affiliation(s)
- Raphaël Girardet
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Margaux Dubois
- Department of Gastro-enterology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Gibran Manasseh
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Mario Jreige
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Céline Du Pasquier
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Emma Canniff
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Marianna Gulizia
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Melissa Bonvin
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Yasser Aleman
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Bachir Taouli
- Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Montserrat Fraga
- Department of Gastro-enterology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Clarisse Dromain
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
| | - Naik Vietti Violi
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.
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Taru MG, Lupsor-Platon M. Exploring Opportunities to Enhance the Screening and Surveillance of Hepatocellular Carcinoma in Non-Alcoholic Fatty Liver Disease (NAFLD) through Risk Stratification Algorithms Incorporating Ultrasound Elastography. Cancers (Basel) 2023; 15:4097. [PMID: 37627125 PMCID: PMC10452922 DOI: 10.3390/cancers15164097] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 08/08/2023] [Accepted: 08/11/2023] [Indexed: 08/27/2023] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD), with its progressive form, non-alcoholic steatohepatitis (NASH), has emerged as a significant public health concern, affecting over 30% of the global population. Hepatocellular carcinoma (HCC), a complication associated with both cirrhotic and non-cirrhotic NAFLD, has shown a significant increase in incidence. A substantial proportion of NAFLD-related HCC occurs in non-cirrhotic livers, highlighting the need for improved risk stratification and surveillance strategies. This comprehensive review explores the potential role of liver ultrasound elastography as a risk assessment tool for HCC development in NAFLD and highlights the importance of effective screening tools for early, cost-effective detection and improved management of NAFLD-related HCC. The integration of non-invasive tools and algorithms into risk stratification strategies could have the capacity to enhance NAFLD-related HCC screening and surveillance effectiveness. Alongside exploring the potential advancement of non-invasive tools and algorithms for effectively stratifying HCC risk in NAFLD, we offer essential perspectives that could enable readers to improve the personalized assessment of NAFLD-related HCC risk through a more methodical screening approach.
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Affiliation(s)
- Madalina-Gabriela Taru
- Hepatology Department, Regional Institute of Gastroenterology and Hepatology “Octavian Fodor”, 400162 Cluj-Napoca, Romania;
- “Iuliu Hatieganu” University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
| | - Monica Lupsor-Platon
- “Iuliu Hatieganu” University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
- Medical Imaging Department, Regional Institute of Gastroenterology and Hepatology “Octavian Fodor”, 400162 Cluj-Napoca, Romania
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Becker AS, Giganti F, Purysko AS, Fainberg J, Vargas HA, Woo S. Taking PI-QUAL beyond the prostate: Towards a standardized radiological image quality score (RI-QUAL). Eur J Radiol 2023; 165:110955. [PMID: 37421773 PMCID: PMC10404469 DOI: 10.1016/j.ejrad.2023.110955] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 06/25/2023] [Accepted: 06/29/2023] [Indexed: 07/10/2023]
Abstract
PURPOSE To compare the interreader agreement of a novel quality score, called the Radiological Image Quality Score (RI-QUAL), to a slighly modified version of the existing Prostate Imaging Quality (mPI-QUAL) score for magnetic resonance imaging (MRI) of the prostate. METHODS A total of 43 consecutive scans were evaluated by two subspecialized radiologists who assigned scores using both the RI-QUAL and mPI-QUAL methods. The interreader agreement was analyzed using three statistical methods: concordance correlation coefficient (CCC), intraclass correlation coefficient (ICC), and Cohen's kappa. Time needed to arrive at a quality judgment was measured and compared using the Wilcoxon signed rank test. RESULTS The interreader agreement for RI-QUAL and mPI-QUAL scores was comparable, as evidenced by the high CCC (0.76 vs. 0.77, p = 0.93), ICC (0.86 vs. 0.87, p = 0.93), and moderate Cohen's kappa (0.61 vs. 0.64, p = 0.85) values. Moreover, RI-QUAL assessment was faster than mPI-QUAL (19 vs. 40 s, p = 0.001). CONCLUSION RI-QUAL is a new quality score that has comparable interreader agreement to the mPI-QUAL score, but with the potential to be applied to different MRI protocols and even different modalities. Like PI-QUAL, RI-QUAL may also facilitate communication about quality to referring physicians, as it provides a standardized and easily interpretable score. Further studies are warranted to validate the usefulness of RI-QUAL in larger patient cohorts and for other imaging modalities.
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Affiliation(s)
- Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States; Department of Radiology, NYU Langone, New York, NY, United States.
| | - Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK; Division of Surgery & Interventional Science, University College London, London, UK
| | - Andrei S Purysko
- Department of Radiology, Abdominal Imaging Section, Cleveland Clinic, Cleveland, OH, United States
| | - Jonathan Fainberg
- Department of Urology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Hebert Alberto Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States; Department of Radiology, NYU Langone, New York, NY, United States
| | - Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
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Oh S, Kwon H, Lim K, Cho J, Kang E, Kim S, Baek Y. The feasibility of early response evaluation using superb microvascular imaging one day after transcatheter arterial chemoembolization for hepatocellular carcinoma. JOURNAL OF CLINICAL ULTRASOUND : JCU 2023; 51:866-875. [PMID: 36897661 DOI: 10.1002/jcu.23449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 02/20/2023] [Accepted: 02/21/2023] [Indexed: 06/02/2023]
Abstract
PURPOSE The purpose of this study was to determine the feasibility of early Superb microvascular imaging (SMI) for prediction of the effect of HCC treatment after transcatheter arterial chemoembolization (TACE). MATERIALS AND METHODS A total of 96 HCCs (70 patients) treated with TACE between September 2021 and May 2022 were included in this study. SMI, Color Doppler imaging (CDI), and Power Doppler imaging (PDI) were performed the day after TACE for evaluation of intratumoral vascularity of the lesion using an Aplio500 ultrasound scanner (Toshiba Medical Systems, Corporation, Tochigi, Japan). Grading of the vascular presence was performed using a five-point scale. A dynamic CT image taken after 29-42 days was used for comparison of sensitivity, specificity, and accuracy for detection of tumor vascularity between SMI, CDI, and PDI. Univariate and multivariate analysis were performed for assessment of factors affecting intratumoral vascularity. RESULTS Fifty-eight lesions (60%) showed complete remission (CR) and 38 lesions (40%) showed partial response (PR) or no response at 29-42 days on Multi-detector Computed Tomography (MDCT) after TACE. SMI showed sensitivity of 86.84% for detection of intratumoral flow, which was significantly higher compared with that of CDI (10.53%, p < 0.001) and PDI (36.84%, p < 0.001). The results of multivariate analysis indicated that tumor size was a significant factor in detection of blood flow using the SMI technique. CONCLUSION Early SMI may be utilized as an adjunctive diagnostic test for evaluation of treated lesions after TACE, particularly when the location of the tumor is in an area of the liver where a suitable sonic window can be identified.
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Affiliation(s)
- Soeui Oh
- Department of Radiology, Dong-A University Hospital, Busan, Republic of Korea
| | - Heejin Kwon
- Department of Radiology, Dong-A University Hospital, Busan, Republic of Korea
| | - Kyungjae Lim
- Department of Radiology, Dong-A University Hospital, Busan, Republic of Korea
| | - Jinhan Cho
- Department of Radiology, Dong-A University Hospital, Busan, Republic of Korea
| | - Eunju Kang
- Department of Radiology, Dong-A University Hospital, Busan, Republic of Korea
| | - Sanghyun Kim
- Department of Radiology, Dong-A University Hospital, Busan, Republic of Korea
| | - Yanghyun Baek
- Department of Internal Medicine, Dong-A University Hospital, Busan, Republic of Korea
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Giustini AB, Ioannou GN, Sirlin C, Loomba R. Review article: Available modalities for screening and imaging diagnosis of hepatocellular carcinoma-Current gaps and challenges. Aliment Pharmacol Ther 2023; 57:1056-1065. [PMID: 37038283 PMCID: PMC10792522 DOI: 10.1111/apt.17506] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/17/2022] [Accepted: 03/24/2023] [Indexed: 04/12/2023]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) incidence and mortality continue to rise worldwide. Society guidelines recommend HCC screening for patients with chronic hepatitis B (CHB) or cirrhosis. Unfortunately, HCC screening rates remain relatively low, and the performance characteristics of current screening modalities are suboptimal. AIM The aim of the study was to discuss the current state of HCC screening and imaging diagnosis utilising standard and emerging imaging modalities in addition to outlining areas of need and ongoing study. METHODS A review of the field was performed combining literature searches and expert opinion. RESULTS The development of the Liver Imaging Reporting and Data System (LI-RADS version 2018) algorithms have advanced and standardised the imaging diagnosis of HCC. While guidelines recommend US for HCC screening, the sensitivity of ultrasound is highly variable for the detection of early-stage HCC with sensitivity reports ranging from 40% to 80%. Biomarker-based scores such as GALAD and alternative imaging modalities such as abbreviated MRI are promising tools to improve HCC early detection. Patients with non-alcoholic fatty liver disease (NAFLD) and patients hepatitis C (HCV) who have achieved sustained virologic response (SVR) can present a clinical dilemma regarding the need for HCC screening. Biomarkers and elastography can aid in identification of individuals at high risk for HCC in these populations. CONCLUSIONS The LI-RADS system has standardised the imaging interpretation and diagnosis of HCC. Work remains regarding screening in special populations and optimization of screening modalities.
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Affiliation(s)
- Abbey Barnard Giustini
- Division of Gastroenterology, Veterans Affairs Puget Sound Healthcare System and University of Washington, Seattle, Washington, USA
| | - George N. Ioannou
- Division of Gastroenterology, Veterans Affairs Puget Sound Healthcare System and University of Washington, Seattle, Washington, USA
| | - Claude Sirlin
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, California, USA
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California at San Diego, La Jolla, California, USA
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Criss C, Nagar AM, Makary MS. Hepatocellular carcinoma: State of the art diagnostic imaging. World J Radiol 2023; 15:56-68. [PMID: 37035828 PMCID: PMC10080581 DOI: 10.4329/wjr.v15.i3.56] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Revised: 02/12/2023] [Accepted: 03/22/2023] [Indexed: 03/27/2023] Open
Abstract
Primary liver cancer is the fourth most common malignancy worldwide, with hepatocellular carcinoma (HCC) comprising up to 90% of cases. Imaging is a staple for surveillance and diagnostic criteria for HCC in current guidelines. Because early diagnosis can impact treatment approaches, utilizing new imaging methods and protocols to aid in differentiation and tumor grading provides a unique opportunity to drastically impact patient prognosis. Within this review manuscript, we provide an overview of imaging modalities used to screen and evaluate HCC. We also briefly discuss emerging uses of new imaging techniques that offer the potential for improving current paradigms for HCC characterization, management, and treatment monitoring.
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Affiliation(s)
- Cody Criss
- Heritage College of Osteopathic Medicine, Ohio University, Athens, OH 45701, United States
| | - Arpit M Nagar
- Department of Radiology, The Ohio State University Medical Center, Columbus, OH 43210, United States
| | - Mina S Makary
- Department of Radiology, The Ohio State University Medical Center, Columbus, OH 43210, United States
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Grazzini G, Chiti G, Zantonelli G, Matteuzzi B, Pradella S, Miele V. Imaging in Hepatocellular Carcinoma: what's new? Semin Ultrasound CT MR 2023; 44:145-161. [PMID: 37245881 DOI: 10.1053/j.sult.2023.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2023]
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30
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Granata V, Fusco R, De Muzio F, Cutolo C, Grassi F, Brunese MC, Simonetti I, Catalano O, Gabelloni M, Pradella S, Danti G, Flammia F, Borgheresi A, Agostini A, Bruno F, Palumbo P, Ottaiano A, Izzo F, Giovagnoni A, Barile A, Gandolfo N, Miele V. Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence. BIOLOGY 2023; 12:213. [PMID: 36829492 PMCID: PMC9952965 DOI: 10.3390/biology12020213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 01/21/2023] [Accepted: 01/25/2023] [Indexed: 01/31/2023]
Abstract
Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver tumor, with a median survival of only 13 months. Surgical resection remains the only curative therapy; however, at first detection, only one-third of patients are at an early enough stage for this approach to be effective, thus rendering early diagnosis as an efficient approach to improving survival. Therefore, the identification of higher-risk patients, whose risk is correlated with genetic and pre-cancerous conditions, and the employment of non-invasive-screening modalities would be appropriate. For several at-risk patients, such as those suffering from primary sclerosing cholangitis or fibropolycystic liver disease, the use of periodic (6-12 months) imaging of the liver by ultrasound (US), magnetic Resonance Imaging (MRI)/cholangiopancreatography (MRCP), or computed tomography (CT) in association with serum CA19-9 measurement has been proposed. For liver cirrhosis patients, it has been proposed that at-risk iCCA patients are monitored in a similar fashion to at-risk HCC patients. The possibility of using Artificial Intelligence models to evaluate higher-risk patients could favor the diagnosis of these entities, although more data are needed to support the practical utility of these applications in the field of screening. For these reasons, it would be appropriate to develop screening programs in the research protocols setting. In fact, the success of these programs reauires patient compliance and multidisciplinary cooperation.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
| | - Federica De Muzio
- Diagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, University of Molise, 86100 Campobasso, Italy
| | - Carmen Cutolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, 84081 Salerno, Italy
| | - Francesca Grassi
- Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80138 Naples, Italy
| | - Maria Chiara Brunese
- Diagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, University of Molise, 86100 Campobasso, Italy
| | - Igino Simonetti
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Orlando Catalano
- Radiology Unit, Istituto Diagnostico Varelli, Via Cornelia dei Gracchi 65, 80126 Naples, Italy
| | - Michela Gabelloni
- Nuclear Medicine Unit, Department of Translational Research, University of Pisa, 56216 Pisa, Italy
| | - Silvia Pradella
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
| | - Ginevra Danti
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
| | - Federica Flammia
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
| | - Alessandra Borgheresi
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Conca 71, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
| | - Andrea Agostini
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Conca 71, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
| | - Federico Bruno
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy
| | - Pierpaolo Palumbo
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy
| | - Alessandro Ottaiano
- SSD Innovative Therapies for Abdominal Metastases, Istituto Nazionale Tumori IRCCS-Fondazione G. Pascale, 80130 Naples, Italy
| | - Francesco Izzo
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Andrea Giovagnoni
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Conca 71, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
| | - Antonio Barile
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy
| | - Nicoletta Gandolfo
- Diagnostic Imaging Department, Villa Scassi Hospital-ASL 3, Corso Scassi 1, 16149 Genoa, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
| | - Vittorio Miele
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
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Positive predictive value of LI-RADS US-3 observations: multivariable analysis of clinical and imaging features. ABDOMINAL RADIOLOGY (NEW YORK) 2023; 48:271-281. [PMID: 36253490 DOI: 10.1007/s00261-022-03681-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 01/21/2023]
Abstract
PURPOSE To determine how clinical and imaging features affect the positive predictive values (PPV) of US-3 observations. METHODS In this retrospective study, 10,546 adult patients who were high risk for hepatocellular carcinoma (HCC) from 2017 to 2021 underwent ultrasound screening/surveillance. Of these, 225 adult patients (100 women, 125 men) with an US-3 observation underwent diagnostic characterization with multiphasic CT (93; 41%), MRI (130; 58%), or contrast-enhanced ultrasound (2; 1%). US-3 observations included focal observations ≥ 10 mm in 216 patients and new venous thrombi in 9 patients. PPV with 95% confidence intervals were calculated using diagnostic characterization as the reference standard. Multivariable analysis of clinical and imaging features was performed to determine the strongest associations with cancer. RESULTS Overall PPV for an US-3 observation was 33% (27-39%) for at least intermediate probability of cancer (≥ LR-3) and 15% (10-20%) for at least probable cancer (≥ LR-4). At multivariable analysis, cirrhosis had the strongest effect size for at least probable cancer (p < 0.001; odds ratio OR 20.4), followed by observation size (p < 0.001; OR 2.65) and age (p = 0.004; OR 1.05). Alpha-fetoprotein, visualization score, and observation echogenicity were not statistically significant associations. Modality (MRI versus CT) did not affect PPV. Due to the large effect of cirrhosis, PPV was then stratified by the presence (n = 116; 52%) or absence (n = 109; 48%) of cirrhosis. For at least probable cancer (≥ LR-4), PPV increased from 4% (0-7%; non-cirrhotic) to 26% (18-34%; p < 0.001; cirrhosis). CONCLUSION Cirrhosis most strongly affects PPV of US-3 observations for at least probable cancer at diagnostic characterization among high-risk patients, increasing to 1 in 4 among cirrhotic patients from 1 in 25 among non-cirrhotic patients.
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Osama MBS, Ajay MBS, Corinne EWMSMBARDMS, Ji-Bin LMD, John REP, Andrej LMDP. Contrast-Enhanced Ultrasound LI-RADS: A Pictorial Review. ADVANCED ULTRASOUND IN DIAGNOSIS AND THERAPY 2023; 7:321. [DOI: 10.37015/audt.2023.230041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2025] Open
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Forrest A, Afshari S, Franssen N, Ali N. Prevalence of extra-hepatic incidental findings on ultrasound screening for hepatocellular carcinoma. ABDOMINAL RADIOLOGY (NEW YORK) 2023; 48:257-262. [PMID: 36136159 DOI: 10.1007/s00261-022-03678-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/02/2022] [Accepted: 09/03/2022] [Indexed: 01/21/2023]
Abstract
PURPOSE Abdominal ultrasound is a cost-effective method for screening for hepatocellular carcinoma (HCC) in high-risk individuals. Currently, at many institutions the protocol for obtaining HCC screening ultrasounds includes a traditional examination of the right upper quadrant, including the pancreas and right kidney. There is no consensus on the role of imaging of extra-hepatic structures and there are limited data describing the frequency and clinical significance of incidental findings discovered during HCC screening. The purpose of this retrospective study is to assess the prevalence and significance of extra-hepatic incidental findings during HCC screening ultrasounds. METHODS A single-center retrospective review of all right upper quadrant HCC screening ultrasounds identified 432 HCC screening ultrasounds performed on 294 adults over a 2.5-year period. Findings in all organs evaluated were recorded. Any incidental finding was classified as minor, moderate, or major clinical significance. RESULTS At least one extra-hepatic finding was documented in 57.4% of examinations. The most common extra-hepatic findings occurred in the gallbladder (40.3%), most commonly gallstones (25.4%). Four moderate clinically significant incidental findings were recorded (0.9%). Only one of these incidental findings required specific imaging follow up (0.2%). No major clinical significance incidental findings were identified. CONCLUSIONS Potentially clinically significant incidental findings during ultrasound HCC screenings are rare. Incidental findings identified on HCC screening did not result in significant additional follow-up imaging or interventions.
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Affiliation(s)
- Allison Forrest
- University of Vermont Medical Center, Burlington, VT, USA. .,Department of Radiology, University of Vermont Medical Center, 111 Colchester Ave, Burlington, VT, 05401, USA.
| | - Sam Afshari
- University of Vermont Medical Center, Burlington, VT, USA
| | | | - Naiim Ali
- University of Vermont Medical Center, Burlington, VT, USA
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Sabeti S, Ternifi R, Larson NB, Olson MC, Atwell TD, Fatemi M, Alizad A. Morphometric analysis of tumor microvessels for detection of hepatocellular carcinoma using contrast-free ultrasound imaging: A feasibility study. Front Oncol 2023; 13:1121664. [PMID: 37124492 PMCID: PMC10134399 DOI: 10.3389/fonc.2023.1121664] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 03/21/2023] [Indexed: 05/02/2023] Open
Abstract
Introduction A contrast-free ultrasound microvasculature imaging technique was evaluated in this study to determine whether extracting morphological features of the vascular networks in hepatic lesions can be beneficial in differentiating benign and malignant tumors (hepatocellular carcinoma (HCC) in particular). Methods A total of 29 lesions from 22 patients were included in this work. A post-processing algorithm consisting of clutter filtering, denoising, and vessel enhancement steps was implemented on ultrasound data to visualize microvessel structures. These structures were then further characterized and quantified through additional image processing. A total of nine morphological metrics were examined to compare different groups of lesions. A two-sided Wilcoxon rank sum test was used for statistical analysis. Results In the malignant versus benign comparison, six of the metrics manifested statistical significance. Comparing only HCC cases with the benign, only three of the metrics were significantly different. No statistically significant distinction was observed between different malignancies (HCC versus cholangiocarcinoma and metastatic adenocarcinoma) for any of the metrics. Discussion Obtained results suggest that designing predictive models based on such morphological characteristics on a larger sample size may prove helpful in differentiating benign from malignant liver masses.
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Affiliation(s)
- Soroosh Sabeti
- Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
| | - Redouane Ternifi
- Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
| | - Nicholas B. Larson
- Department of Quantitative Health Sciences, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
| | - Michael C. Olson
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
| | - Thomas D. Atwell
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
| | - Mostafa Fatemi
- Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
| | - Azra Alizad
- Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
- *Correspondence: Azra Alizad,
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Outcomes of LI-RADS US-2 Subthreshold Observations Detected on Surveillance Ultrasound. AJR Am J Roentgenol 2022; 219:774-783. [PMID: 35703411 DOI: 10.2214/ajr.22.27812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND. Ultrasound LI-RADS version 2017 recommends that patients with US-2 subthreshold observations undergo repeat surveillance ultrasound in 3-6 months and return to routine surveillance if the observation shows no growth for 2 years. However, outcomes of US-2 observations are unknown. OBJECTIVE. The purpose of this article was to determine imaging outcomes of US-2 observations detected on surveillance ultrasound examinations. METHODS. This retrospective study included 175 patients (median age, 59 years; 70 women, 105 men) at high risk for hepatocellular carcinoma (HCC) with US-2 observations (i.e., subcentimeter observations) on surveillance ultrasound. Observations were classified on follow-up ultrasound performed 2 or more years later as showing no correlate, stable (if remaining subcentimeter), or progressed (if measuring ≥ 10 mm, meeting US-3 criteria). Observations were classified on follow-up multiphasic CT or MRI (stratified as < 2-year vs ≥ 2-year follow-up) as showing no correlate or, if showing a correlate, using CT/MRI LI-RADS version 2018. RESULTS. A total of 111 patients had follow-up ultrasound after 2 or more years and 106 had follow-up CT or MRI (79 before 2 years, 27 after 2 years). On the basis of final follow-up examinations, 173 of 175 observations were stable on follow-up ultrasound 2 or more years later (n = 68); showed no correlate on follow-up ultrasound, CT, or MRI (n = 88); or were classified as LR-1 or LR-2 on CT or MRI (n = 17). The remaining 2 of 175 observations were LR-3 on CT or MRI. No observations progressed to US-3 on follow-up ultrasound or were classified as LR-4 or greater on CT or MRI. A correlate was observed in 25 of the 106 follow-up CT or MRI examinations (LR-1 or LR-2 in 23; LR-3 in two). Eight patients developed HCC at a median of 2.0 years after initial US-2 observation detection; all HCCs were in separate locations from the baseline observations and were preceded by a surveillance ultrasound that could not reidentify the baseline observation. In three patients who underwent liver transplant, the explant showed no dysplastic nodule or HCC. CONCLUSION. US-2 subthreshold observations are unlikely to progress or become HCC and commonly have no correlate on follow-up imaging. CLINICAL IMPACT. Because of the low progression rate of US-2 subthreshold observations, it is unclear if an extended period of intensive surveillance, as recommended by multiple professional societies, is warranted.
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De Muzio F, Grassi F, Dell’Aversana F, Fusco R, Danti G, Flammia F, Chiti G, Valeri T, Agostini A, Palumbo P, Bruno F, Cutolo C, Grassi R, Simonetti I, Giovagnoni A, Miele V, Barile A, Granata V. A Narrative Review on LI-RADS Algorithm in Liver Tumors: Prospects and Pitfalls. Diagnostics (Basel) 2022; 12:1655. [PMID: 35885561 PMCID: PMC9319674 DOI: 10.3390/diagnostics12071655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 06/27/2022] [Accepted: 07/05/2022] [Indexed: 11/16/2022] Open
Abstract
Liver cancer is the sixth most detected tumor and the third leading cause of tumor death worldwide. Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with specific risk factors and a targeted population. Imaging plays a major role in the management of HCC from screening to post-therapy follow-up. In order to optimize the diagnostic-therapeutic management and using a universal report, which allows more effective communication among the multidisciplinary team, several classification systems have been proposed over time, and LI-RADS is the most utilized. Currently, LI-RADS comprises four algorithms addressing screening and surveillance, diagnosis on computed tomography (CT)/magnetic resonance imaging (MRI), diagnosis on contrast-enhanced ultrasound (CEUS) and treatment response on CT/MRI. The algorithm allows guiding the radiologist through a stepwise process of assigning a category to a liver observation, recognizing both major and ancillary features. This process allows for characterizing liver lesions and assessing treatment. In this review, we highlighted both major and ancillary features that could define HCC. The distinctive dynamic vascular pattern of arterial hyperenhancement followed by washout in the portal-venous phase is the key hallmark of HCC, with a specificity value close to 100%. However, the sensitivity value of these combined criteria is inadequate. Recent evidence has proven that liver-specific contrast could be an important tool not only in increasing sensitivity but also in diagnosis as a major criterion. Although LI-RADS emerges as an essential instrument to support the management of liver tumors, still many improvements are needed to overcome the current limitations. In particular, features that may clearly distinguish HCC from cholangiocarcinoma (CCA) and combined HCC-CCA lesions and the assessment after locoregional radiation-based therapy are still fields of research.
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Affiliation(s)
- Federica De Muzio
- Department of Medicine and Health Sciences V. Tiberio, University of Molise, 86100 Campobasso, Italy;
| | - Francesca Grassi
- Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 81100 Naples, Italy; (F.G.); (F.D.); (R.G.)
| | - Federica Dell’Aversana
- Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 81100 Naples, Italy; (F.G.); (F.D.); (R.G.)
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
| | - Ginevra Danti
- Division of Radiology, Azienda Ospedaliera Universitaria Careggi, 50134 Florence, Italy; (G.D.); (F.F.); (G.C.); (V.M.)
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy; (P.P.); (F.B.)
| | - Federica Flammia
- Division of Radiology, Azienda Ospedaliera Universitaria Careggi, 50134 Florence, Italy; (G.D.); (F.F.); (G.C.); (V.M.)
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy; (P.P.); (F.B.)
| | - Giuditta Chiti
- Division of Radiology, Azienda Ospedaliera Universitaria Careggi, 50134 Florence, Italy; (G.D.); (F.F.); (G.C.); (V.M.)
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy; (P.P.); (F.B.)
| | - Tommaso Valeri
- Department of Clinical Special and Dental Sciences, University Politecnica delle Marche, 60126 Ancona, Italy; (T.V.); (A.A.); (A.G.)
- Department of Radiological Sciences, University Hospital Ospedali Riuniti, Via Tronto 10/a, 60126 Torrette, Italy
| | - Andrea Agostini
- Department of Clinical Special and Dental Sciences, University Politecnica delle Marche, 60126 Ancona, Italy; (T.V.); (A.A.); (A.G.)
- Department of Radiological Sciences, University Hospital Ospedali Riuniti, Via Tronto 10/a, 60126 Torrette, Italy
| | - Pierpaolo Palumbo
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy; (P.P.); (F.B.)
- Area of Cardiovascular and Interventional Imaging, Department of Diagnostic Imaging, Abruzzo Health Unit 1, 67100 L’Aquila, Italy
| | - Federico Bruno
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy; (P.P.); (F.B.)
- Emergency Radiology, San Salvatore Hospital, Via Lorenzo Natali 1, 67100 L’Aquila, Italy;
| | - Carmen Cutolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, 84084 Fisciano, Italy;
| | - Roberta Grassi
- Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 81100 Naples, Italy; (F.G.); (F.D.); (R.G.)
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy; (P.P.); (F.B.)
| | - Igino Simonetti
- Radiology Division, Istituto Nazionale Tumori-IRCCS-Fondazione G. Pascale, Via Mariano Semmola, 80131 Naples, Italy; (I.S.); (V.G.)
| | - Andrea Giovagnoni
- Department of Clinical Special and Dental Sciences, University Politecnica delle Marche, 60126 Ancona, Italy; (T.V.); (A.A.); (A.G.)
- Department of Radiological Sciences, University Hospital Ospedali Riuniti, Via Tronto 10/a, 60126 Torrette, Italy
| | - Vittorio Miele
- Division of Radiology, Azienda Ospedaliera Universitaria Careggi, 50134 Florence, Italy; (G.D.); (F.F.); (G.C.); (V.M.)
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy; (P.P.); (F.B.)
| | - Antonio Barile
- Emergency Radiology, San Salvatore Hospital, Via Lorenzo Natali 1, 67100 L’Aquila, Italy;
| | - Vincenza Granata
- Radiology Division, Istituto Nazionale Tumori-IRCCS-Fondazione G. Pascale, Via Mariano Semmola, 80131 Naples, Italy; (I.S.); (V.G.)
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Kutaiba N, Ardalan ZS. Limitations Associated With Assessing Liver Ultrasound Quality Using US LI-RADS Visualization Score When Utilizing Acquired Images. Clin Gastroenterol Hepatol 2022; 20:1617-1618. [PMID: 34358717 DOI: 10.1016/j.cgh.2021.07.049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 07/27/2021] [Indexed: 02/07/2023]
Affiliation(s)
- Numan Kutaiba
- Department of Radiology, Austin Health, Melbourne, Victoria, Australia
| | - Zaid S Ardalan
- Department of Gastroenterology, Alfred Health and Monash University, Melbourne, Victoria, Australia
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Singal AG, Schoenberger H, Fetzer D. Reply. Clin Gastroenterol Hepatol 2022; 20:1618-1619. [PMID: 34411711 DOI: 10.1016/j.cgh.2021.08.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 08/12/2021] [Indexed: 02/07/2023]
Affiliation(s)
- Amit G Singal
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | | | - David Fetzer
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
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Dawkins A, Nelson LW, Gulati V, Stepp A, Chapelin F, Khurana A. Interobserver Agreement Between Primary Sonographers and Secondary Overreaders for Screening and Surveillance Liver Ultrasounds Using Ultrasound Liver Imaging Reporting and Data System. Ultrasound Q 2022; 38:116-123. [PMID: 35678479 DOI: 10.1097/ruq.0000000000000566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
ABSTRACT The authors aim to identify if primary sonographers and secondary reviewers, both radiologists and sonographers, are likely to assign the same Ultrasound Liver Imaging Reporting and Data System (US LI-RADS) scores for liver surveillance ultrasounds. Institutional review board approval was obtained. Sonographers were familiarized with US LI-RADS via radiologist-led lectures. Three sonographers prospectively scored 170 screening examinations using US LI-RADS recommendations. Scans were retrospectively rescored by a fourth sonographer and a radiologist, both of whom were blinded to the original scores. Results were analyzed with weighted and nonweighted Cohen kappa statistical analysis methods. There was near-perfect agreement between primary and secondary sonographers and primary sonographer and radiologist (kappa of 0.87 and 0.92, respectively) for US LI-RADS category (cat) scores. However, only substantial and moderate agreements were noted for visualization (vis) scores between primary and secondary sonographers and primary sonographer and radiologist (weighted kappa of 0.73 and 0.48, respectively). There was vis score disagreement between the primary sonographer and radiologist in 60 (35.3%) cases. In 35 (20%) cases, the radiologist assigned a lower/more conservative vis score. There was vis score disagreement between the primary and secondary reviewing sonographers in 30 (17.6%) cases. In 12 (7%) cases, the secondary sonographer assigned a more conservative vis score. Although a good degree of concordance was noted between the groups, radiologists will need to generate their own US LI-RADS scoring to accurately reflect their impression and appropriately steer management.
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Affiliation(s)
- Adrian Dawkins
- Department of Radiology, University of Kentucky Lexington, KY
| | - Leslie W Nelson
- Department of Radiology, University of Kentucky Lexington, KY
| | - Vaibhav Gulati
- Imaging Associates at National Heart Institute, New Delhi, India
| | - Angela Stepp
- Department of Radiology, University of Kentucky Lexington, KY
| | - Fanny Chapelin
- Department of Biomedical Engineering, University of Kentucky, Lexington, KY
| | - Aman Khurana
- Department of Radiology, University of Kentucky Lexington, KY
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Fetzer DT, Browning T, Xi Y, Yokoo T, Singal AG. Associations of Ultrasound LI-RADS Visualization Score With Examination, Sonographer, and Radiologist Factors: Retrospective Assessment in Over 10,000 Examinations. AJR Am J Roentgenol 2022; 218:1010-1020. [PMID: 34910539 PMCID: PMC9270853 DOI: 10.2214/ajr.21.26735] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND. When performing ultrasound (US) for hepatocellular carcinoma (HCC) screening, numerous factors may impair hepatic visualization, potentially lowering sensitivity. US LI-RADS includes a visualization score as a technical adequacy measure. OBJECTIVE. The purpose of this article is to identify associations between examination, sonographer, and radiologist factors and the visualization score in liver US HCC screening. METHODS. This retrospective study included 6598 patients (3979 men, 2619 women; mean age, 58 years) at risk for HCC who underwent a total of 10,589 liver US examinations performed by 91 sonographers and interpreted by 50 radiologists. Visualization scores (A, no or minimal limitations; B, moderate limitations; C, severe limitations) were extracted from clinical reports. Patient location (emergency department [ED], in-patient, outpatient), sonographer and radiologist liver US volumes during the study period (< 50, 50-500, > 500 examinations), and radiologist practice pattern (US, abdominal, community, interventional) were recorded. Associations with visualization scores were explored. RESULTS. Frequencies of visualization scores were 71.5%, 24.2%, and 4.2% for A, B, and C, respectively. Scores varied significantly (p < .001) between examinations performed in ED patients (49.8%, 40.1%, and 10.2%), inpatients (58.8%, 33.9%, and 7.3%), and outpatients (76.7%, 20.3%, and 2.9%). Scores also varied significantly (p < .001) by sonographer volume (< 50 examinations: 58.4%, 33.7%, and 7.9%; > 500 examinations: 72.9%, 22.5%, and 4.6%); reader volume (< 50 examinations: 62.9%, 29.9%, and 7.1%; > 500 examinations: 67.3%, 28.0%, and 4.7%); and reader practice pattern (US: 74.5%, 21.3%, and 4.3%; abdominal: 67.0%, 28.1%, and 4.8%; community: 75.2%, 21.9%, and 2.9%; interventional: 68.5%, 24.1%, and 7.4%). In multivariable analysis, independent predictors of score C were patient location (ED/inpatient: odds ratio [OR], 2.62; p < .001) and sonographer volume (< 50: OR, 1.55; p = .01). Among sonographers performing 50 or more examinations, the percentage of outpatient examinations with score C ranged from 0.8% to 5.4%; 9/33 were above the upper 95% CI of 3.2%. CONCLUSION. The US LI-RADS visualization score may identify factors affecting quality of HCC screening examinations and identify outlier sonographers in terms of poor examination quality. The approach also highlights potential systematic biases among radiologists in their quality assessment process. CLINICAL IMPACT. These findings may be applied to guide targeted quality improvement efforts and establish best practices and performance standards for screening programs.
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Affiliation(s)
- David T Fetzer
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-8896
| | - Travis Browning
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-8896
- Clinical Informatics, Parkland Health and Hospital System, Dallas, TX
| | - Yin Xi
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-8896
| | - Takeshi Yokoo
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-8896
| | - Amit G Singal
- Department of Internal Medicine, Division of Digestive and Liver Diseases, University of Texas Southwestern Medical Center, Dallas, TX
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Bastawrous S. Editorial Comment: Factors Impacting Ultrasound LI-RADS Visualization Scores-Optimizing Future Quality Assurance and Standards. AJR Am J Roentgenol 2022; 218:1020. [PMID: 35018797 DOI: 10.2214/ajr.21.27314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Affiliation(s)
- Sarah Bastawrous
- University of Washington School of Medicine, VA Puget Sound Health Care System, Seattle, WA
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Multicenter Study of ACR Ultrasound LI-RADS Visualization Scores on Serial Examinations: Implications for Changes in Surveillance Strategies. AJR Am J Roentgenol 2022; 219:445-452. [PMID: 35383486 DOI: 10.2214/ajr.22.27405] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Background: American College of Radiology Ultrasound LI-RADS includes the visualization score as a subjective measure of examination quality and expected level of sensitivity. Whether a single suboptimal visualization score warrants change in surveillance strategy is unknown. Objective: To determine the relative stability of visualization scores on serial surveillance ultrasound examinations in patients at risk for HCC. Methods: This retrospective study included patients at risk for HCC who underwent at least two HCC surveillance ultrasound examinations at one of three institutions between January 2017 and November 2020. Frequencies of score remaining unchanged after variable numbers of preceding examinations with the given score were determined. A mixed-effects logistic model was fitted to identify factors associated with a repeat score C (severe limitations) versus change to score A (no or minimal limitations) or score B (moderate limitations). Results: A total of 3169 patients underwent at least 2 ultrasound examinations, yielding a total of 9602 examinations. A total of 8030 (83.6%) examinations had score A, 1378 (14.4%) score B, and 194 (2.0%) score C. Frequency of score A was 88%, 91%, and 93% after 1, 2 and 3 consecutive prior examinations with score A. Frequency of score B was 45%, 48%, and 55% after 1, 2, and 3 consecutive prior examinations with score B. Frequency of score C was 42%, 67%, and 80% after 1, 2, and 3 consecutive prior examinations with score C. Among 109 examinations with score C in 91 patients with an available follow-up examination, no factor (including age, sex, severe steatosis, advanced cirrhosis, ascites, body mass index, and change in ultrasound machine, sonographer, or radiologist) was significantly associated with repeat score C (all p>.05). Although not statistically significant, presence of severe steatosis and advanced cirrhosis had the highest odds ratios (2.88 and 2.38, respectively) for repeat score C in multivariable analysis. Conclusion: Only 42% of patients with visualization score C on surveillances examination have score C on follow-up examination. Clinical Impact: The findings may inform decisions for alternative surveillance strategies in patients with visualization score C on ultrasound. This decision should consider the number of previous examinations with score C.
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Chong N, Schoenberger H, Yekkaluri S, Fetzer DT, Rich NE, Yokoo T, Gopal P, Manwaring C, Quirk L, Singal AG. Association between ultrasound quality and test performance for HCC surveillance in patients with cirrhosis: a retrospective cohort study. Aliment Pharmacol Ther 2022; 55:683-690. [PMID: 35170052 DOI: 10.1111/apt.16779] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Revised: 12/18/2021] [Accepted: 01/10/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND Ultrasound visualisation is limited in approximately 20% of patients with cirrhosis undergoing hepatocellular carcinoma (HCC) surveillance; however, it is unknown if impaired visualisation directly impacts test performance. We aimed to evaluate the association between ultrasound visualisation and surveillance test performance. METHODS We performed a retrospective cohort study among patients with cirrhosis, with or without HCC, who underwent ultrasound-based surveillance at two large health systems between July 2016 and July 2019. Ultrasound visualisation assessment was recorded by interpreting radiologists using the ultrasound LI-RADS Visualisation score. We performed logistic regression analyses to evaluate the association between ultrasound visualisation and diagnostic test performance. We assessed sensitivity for HCC detection among ultrasounds performed in the year prior to HCC diagnoses and specificity using ultrasounds in those without HCC. RESULTS Among 186 patients with HCC, severely limited visualisation (Vis Score C) on ultrasound prior to HCC diagnosis was associated with increased odds of false-negative results, that is lower sensitivity (OR 7.94, 95% CI 1.23-51.16) in multivariable analysis. Ultrasound sensitivity with visualisation scores A or B exceeded 75%, compared to only 27.3% with visualisation score C. Among 2052 cirrhosis patients without HCC, moderate visualisation limitations (Vis score B) were associated with increased odds of false-positive results (OR 1.60, 1.13-2.27), although specificity exceeded 95% across all visualisation scores. CONCLUSIONS Impaired ultrasound visualisation is associated with worse surveillance test performance. Alternative blood-based biomarkers and imaging strategies are needed for patients at risk for ultrasound-based surveillance failure.
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Affiliation(s)
- Nicolas Chong
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA.,Parkland Health & Hospital System, Dallas, TX, USA
| | - Haley Schoenberger
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA.,Parkland Health & Hospital System, Dallas, TX, USA
| | - Sruthi Yekkaluri
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - David T Fetzer
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Nicole E Rich
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA.,Parkland Health & Hospital System, Dallas, TX, USA
| | - Takeshi Yokoo
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Purva Gopal
- Department of Pathology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Carrie Manwaring
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Lisa Quirk
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Amit G Singal
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA.,Parkland Health & Hospital System, Dallas, TX, USA
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Giorgio A, De Luca M, Gatti P, Giorgio V. Non-enhanced Magnetic Resonance Imaging Compared to Ultrasound as a Surveillance Tool for Hepatocellular Carcinoma. Not all that glitters is gold: the ultrasound hepatologist's point of view. J Ultrasound 2022; 25:129-131. [PMID: 33389594 PMCID: PMC8964864 DOI: 10.1007/s40477-020-00543-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 11/15/2020] [Indexed: 11/25/2022] Open
Affiliation(s)
- Antonio Giorgio
- Liver Unit and Interventional Ultrasound Unit, Athena Clinical Institute, Piedimonte Matese (CE), viale Colli Aminei, 491, 80131, Naples, Italy.
| | | | - Pietro Gatti
- Internal Medicine Unit, Brindisi General Hospital, Brindisi, Italy
| | - Valentina Giorgio
- Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
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Singal AG, El-Serag HB. Rational HCC screening approaches for patients with NAFLD. J Hepatol 2022; 76:195-201. [PMID: 34508791 PMCID: PMC8688224 DOI: 10.1016/j.jhep.2021.08.028] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 08/24/2021] [Accepted: 08/30/2021] [Indexed: 02/07/2023]
Abstract
Non-alcoholic fatty liver disease (NAFLD) is associated with an increased risk of developing hepatocellular carcinoma (HCC), especially among those who have cirrhosis or advanced fibrosis, but 20-30% of cases of NAFLD-related HCC occur in the absence of advanced fibrosis. The prevalence of NAFLD-related HCC is increasing in most countries worldwide. There are few direct data to support or refute the efficacy or effectiveness of HCC surveillance in NAFLD or to guide its application. We use evidence on surveillance in other conditions and studies on the clinical course of patients with NAFLD to arrive at recommendations for rational approaches to HCC surveillance in this growing cohort of patients. We also outline gaps in research and practice, including opportunities to advance the field.
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Affiliation(s)
- Amit G Singal
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Hashem B El-Serag
- Department of Internal Medicine, Baylor College of Medicine, Houston, TX, USA.
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46
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Zhou J, Pan F, Li W, Hu H, Wang W, Huang Q. Feature Fusion for Diagnosis of Atypical Hepatocellular Carcinoma in Contrast- Enhanced Ultrasound. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2022; 69:114-123. [PMID: 34487493 DOI: 10.1109/tuffc.2021.3110590] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Contrast-enhanced ultrasound (CEUS) is generally employed for focal liver lesions (FLLs) diagnosis. Among the FLLs, atypical hepatocellular carcinoma (HCC) is difficult to distinguish from focal nodular hyperplasia (FNH) in CEUS video. For this reason, we propose and evaluate a feature fusion method to resolve this problem. The proposed algorithm extracts a set of hand-crafted features and the deep features from the CEUS cine clip data. The hand-crafted features include the spatial-temporal feature based on a novel descriptor called Velocity-Similarity and Dissimilarity Matching Local Binary Pattern (V-SDMLBP), and the deep features from a 3-D convolution neural network (3D-CNN). Then the two types of features are fused. Finally, a classifier is employed to diagnose HCC or FNH. Several classifiers have achieved excellent performance, which demonstrates the superiority of the fused features. In addition, compared with general CNNs, the proposed fused features have better interpretability.
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Tiyarattanachai T, Bird KN, Lo EC, Mariano AT, Ho AA, Ferguson CW, Chima RS, Desser TS, Morimoto LN, Kamaya A. Ultrasound Liver Imaging Reporting and Data System (US LI-RADS) Visualization Score: a reliability analysis on inter-reader agreement. Abdom Radiol (NY) 2021; 46:5134-5141. [PMID: 34228197 DOI: 10.1007/s00261-021-03067-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 03/12/2021] [Accepted: 03/18/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIM The American College of Radiology Ultrasound Liver Imaging Reporting and Data System (ACR US LI-RADS) Visualization Score conveys the expected level of sensitivity of screening and surveillance ultrasound exams in patients at risk for hepatocellular carcinoma (HCC). We sought to determine inter-reader agreement of the Visualization Score which is currently unknown. METHODS Consecutive 6998 ultrasound HCC screening and surveillance studies in 3115 patients from 2017 to 2020 were retrospectively retrieved. Of these, 6154 (87.9%) studies were Visualization A (No or minimal limitations), 709 (10.1%) were Visualization B (Moderate limitations), and 135 (1.9%) were Visualization C (Severe limitations). Randomly sampled 90 studies, with 30 studies in each Visualization category, were included for analysis. Nine radiologists (3 senior attendings, 3 junior attendings and 3 body imaging fellows) blinded to the original categorization independently reviewed each study and assigned a Visualization Score. Intraclass correlation coefficient (ICC) was used to quantify inter-reader agreement. RESULTS ICC among all 9 radiologists was 0.70 (95% CI 0.63-0.77). ICCs among senior attendings, junior attendings and body imaging fellows were 0.68 (CI 0.58-0.76), 0.72 (CI 0.62-0.80) and 0.76 (CI 0.68-0.83), respectively. Subgroup analysis by liver parenchyma was further performed. ICC was highest in the patient group with normal liver parenchyma (0.69, CI 0.56-0.81), followed by steatosis (0.66, CI 0.54-0.79) and cirrhosis (0.58, CI 0.43-0.73), respectively. CONCLUSIONS US LI-RADS Visualization Score is a reliable tool with good inter-reader agreement that can be used to indicate the expected level of sensitivity of a screening and surveillance ultrasound examination for detecting focal liver observations.
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da Silva PH, Gomes MM, de Matos CAL, de Souza E Silva IS, Gonzalez AM, Torres US, Salazar GMM, D'Ippolito G. HCC Detection on Surveillance US: Comparing Focused Liver Protocol Using US LI-RADS Technical Guidelines to a General Complete Abdominal US Protocol. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2021; 40:2487-2495. [PMID: 33463734 DOI: 10.1002/jum.15637] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 12/08/2020] [Accepted: 01/06/2021] [Indexed: 06/12/2023]
Abstract
OBJECTIVE Focused US examinations of the liver in the routine hepatocellular carcinoma (HCC) screening reduce the time spent on evaluating other structures deemed irrelevant to the clinical setting. It is still unknown, however, if such a strategy may additionally improve the frequency of nodules detection. We aimed to assess the impact of an HCC surveillance program in high-risk patients by means of targeted liver US following LI-RADS technical guidelines in comparison to a complete upper abdominal scan. METHODS In this IRB-approved, single-center, prospective study, patients at high-risk for HCC enrolled from 06/2016 to 09/2019 were randomly assigned to 1 of the 2 institutional protocols: Group A (targeted liver US) or Group B (complete upper abdominal scan). Twenty examiners with similar experience in abdominal US were randomly assigned to perform the examinations exclusively in 1 of the groups (10 in each group). Frequency of hepatic nodules between groups was compared by using Fisher's exact test. RESULTS Four hundred and sixty-five patients were enrolled, with no significant differences in both groups regarding sex, age, etiology of liver disease, MELD scores, and alpha-fetoprotein levels. A significantly higher frequency of nodules detection was found in Group A (230 patients; 23 nodules detected; 10% of the sample) in comparison to Group B (235 patients; 3 nodules; 1.3% of the sample) (p <.001). Five patients in Group A and 1 in Group B were positive for HCC after full diagnostic work-up. CONCLUSION Adopting an HCC screening program based on targeted liver US improved the detection of hepatic nodules among high-risk individuals.
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Affiliation(s)
- Priscila Henriques da Silva
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo-UNIFESP, São Paulo, Brazil
| | - Matheus Menezes Gomes
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo-UNIFESP, São Paulo, Brazil
| | - Carla Adriana Loureiro de Matos
- Department of Gastroenterology, Liver Transplantation Unit, Escola Paulista de Medicina, Universidade Federal de São Paulo-UNIFESP, São Paulo, Brazil
| | | | - Adriano Miziara Gonzalez
- Department of Surgery, Liver Transplantation Unit, Escola Paulista de Medicina, Universidade Federal de São Paulo-UNIFESP, São Paulo, Brazil
| | - Ulysses S Torres
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo-UNIFESP, São Paulo, Brazil
- Fleury Group, São Paulo, Brazil
| | | | - Giuseppe D'Ippolito
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo-UNIFESP, São Paulo, Brazil
- Fleury Group, São Paulo, Brazil
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Choi HH, Rodgers SK, Fetzer DT, Wasnik AP, Millet JD, Morgan TA, Dawkins A, Gabriel H, Kamaya A. Ultrasound Liver Imaging Reporting and Data System (US LI-RADS): An Overview with Technical and Practical Applications. Acad Radiol 2021; 28:1464-1476. [PMID: 32718745 DOI: 10.1016/j.acra.2020.06.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 06/01/2020] [Accepted: 06/01/2020] [Indexed: 12/12/2022]
Abstract
The Ultrasound Liver Imaging Reporting and Data System (US LI-RADS), introduced in 2017 by the American College of Radiology, standardizes the technique, interpretation, and reporting of screening and surveillance ultrasounds intended to detect hepatocellular carcinoma in high-risk patients. These include patients with cirrhosis of any cause as well as subsets of patients with chronic hepatitis B viral infection. The US LI-RADS scheme is composed of an ultrasound category and a visualization score: ultrasound categories define the exam as negative, subthreshold, or positive and direct next steps in management; visualization scores denote the expected sensitivity of the exam, based on adequacy of liver visualization with ultrasound. Since its introduction, multiple institutions across the United States have implemented US LI-RADS. This review includes a background of hepatocellular carcinoma and US LI-RADS, definition of screening/surveillance population, recommendations and tips for technique, interpretation, and reporting, and preliminary outcomes analysis.
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Affiliation(s)
- Hailey H Choi
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1001 Potrero Ave. Building 5, 1st floor, San Francisco, CA 94110.
| | - Shuchi K Rodgers
- Department of Radiology, Einstein Medical Center, Philadelphia, Pennsylvania
| | - David T Fetzer
- Department of Radiology, UT Southwestern Medical Center, Dallas Texas
| | - Ashish P Wasnik
- Department of Radiology, Michigan Medicine, University of Michigan, Arbor, Michigan
| | - John D Millet
- Department of Radiology, Michigan Medicine, University of Michigan, Arbor, Michigan
| | - Tara A Morgan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1001 Potrero Ave. Building 5, 1st floor, San Francisco, CA 94110
| | - Adrian Dawkins
- Department of Radiology, University of Kentucky, Lexington, Kentucky
| | - Helena Gabriel
- Department of Radiology, Northwestern University, Chicago, Illinois
| | - Aya Kamaya
- Department of Radiology, Stanford University Medical Center, Stanford, California
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Adeniji N, Dhanasekaran R. Current and Emerging Tools for Hepatocellular Carcinoma Surveillance. Hepatol Commun 2021; 5:1972-1986. [PMID: 34533885 PMCID: PMC8631096 DOI: 10.1002/hep4.1823] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 08/04/2021] [Accepted: 08/30/2021] [Indexed: 12/13/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer‐related mortality worldwide. Early detection of HCC enables patients to avail curative therapies that can improve patient survival. Current international guidelines advocate for the enrollment of patients at high risk for HCC, like those with cirrhosis, in surveillance programs that perform ultrasound every 6 months. In recent years, many studies have further characterized the utility of established screening strategies and have introduced new promising tools for HCC surveillance. In this review, we provide an overview of the most promising new imaging modalities and biomarkers for the detection of HCC. We discuss the role of imaging tools like ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) in the early detection of HCC, and describe recent innovations which can potentially enhance their applicability, including contrast enhanced ultrasound, low‐dose CT scans, and abbreviated MRI. Next, we outline the data supporting the use of three circulating biomarkers (i.e., alpha‐fetoprotein [AFP], AFP lens culinaris agglutinin‐reactive fraction, and des‐gamma‐carboxy prothrombin) in HCC surveillance, and expand on multiple emerging liquid biopsy biomarkers, including methylated cell‐free DNA (cfDNA), cfDNA mutations, extracellular vesicles, and circulating tumor cells. These promising new imaging modalities and biomarkers have the potential to improve early detection, and thus improve survival, in patients with HCC.
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Affiliation(s)
- Nia Adeniji
- Stanford School of Medicine, Stanford, CA, USA
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