1
|
Chernyak V. Editorial for "Diagnostic Model for Proliferative HCC Using LI-RADS: Assessing Therapeutic Outcomes in Hepatectomy and TKI-ICI Combination". J Magn Reson Imaging 2025; 61:148-149. [PMID: 38682725 DOI: 10.1002/jmri.29402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 04/04/2024] [Indexed: 05/01/2024] Open
Affiliation(s)
- Victoria Chernyak
- Department of Radiology, Memorial Sloan Kettering Cancer Center NYC, New York, New York, USA
| |
Collapse
|
2
|
Lee S, Kim YY, Shin J, Shin H, Sirlin CB, Chernyak V. Performance of LI-RADS category 5 vs combined categories 4 and 5: a systemic review and meta-analysis. Eur Radiol 2024; 34:7025-7040. [PMID: 38809263 DOI: 10.1007/s00330-024-10813-5] [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: 01/25/2024] [Revised: 04/10/2024] [Accepted: 04/16/2024] [Indexed: 05/30/2024]
Abstract
OBJECTIVE Computed tomography (CT)/magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS, LR) category 5 has high specificity and modest sensitivity for diagnosis of hepatocellular carcinoma (HCC). The purpose of this study was to compare the diagnostic performance of LR-5 vs combined LR-4 and LR-5 (LR-4/5) for HCC diagnosis. METHODS MEDLINE and EMBASE databases through January 03, 2023 were searched for studies reporting the performance of LR-5 and combined LR-4/5 for HCC diagnosis, using CT/MRI LI-RADS version 2014, 2017, or 2018. A bivariate random-effects model was used to calculate the pooled per-observation diagnostic performance. Subgroup analysis was performed based on imaging modalities and type of MRI contrast material. RESULTS Sixty-nine studies (15,108 observations, 9928 (65.7%) HCCs) were included. Compared to LR-5, combined LR-4/5 showed significantly higher pooled sensitivity (83.0% (95% CI [80.3-85.8%]) vs 65.7% (95% CI [62.4-69.1%]); p < 0.001), lower pooled specificity (75.0% (95% CI [70.5-79.6%]) vs 91.7% (95% CI [90.2-93.1%]); p < 0.001), lower pooled positive likelihood ratio (3.60 (95% CI [3.06-4.23]) vs 6.18 (95% CI [5.35-7.14]); p < 0.001), and lower pooled negative likelihood ratio (0.22 (95% CI [0.19-0.25]) vs 0.38 (95% CI [0.35-0.41]) vs; p < 0.001). Similar results were seen in all subgroups. CONCLUSIONS Our meta-analysis showed that combining LR-4 and LR-5 would increase sensitivity but decrease specificity, positive likelihood ratio, and negative likelihood ratio. These findings may inform management guidelines and individualized management. CLINICAL RELEVANCE STATEMENT This meta-analysis estimated the magnitude of changes in the sensitivity and specificity of imaging criteria when LI-RADS categories 4 and 5 were combined; these findings can inform management guidelines and individualized management. KEY POINTS There is no single worldwide reporting system for liver imaging, partly due to regional needs. Combining LI-RADS categories 4 and 5 increased sensitivity and decreased specificity and positive and negative likelihood ratios. Changes in the sensitivity and specificity of imaging criteria can inform management guidelines and individualized management.
Collapse
Affiliation(s)
- Sunyoung Lee
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yeun-Yoon Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School 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
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Victoria Chernyak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| |
Collapse
|
3
|
Kim DH, Choi SH. Inter-reader agreement for CT/MRI LI-RADS category M imaging features: a systematic review and meta-analysis. JOURNAL OF LIVER CANCER 2024; 24:192-205. [PMID: 38616543 PMCID: PMC11449575 DOI: 10.17998/jlc.2024.04.05] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/01/2024] [Accepted: 04/05/2024] [Indexed: 04/16/2024]
Abstract
BACKGROUNDS/AIMS To systematically evaluate inter-reader agreement in the assessment of individual liver imaging reporting and data system (LI-RADS) category M (LR-M) imaging features in computed tomography/magnetic resonance imaging (CT/MRI) LIRADS v2018, and to explore the causes of poor agreement in LR-M assignment. METHODS Original studies reporting inter-reader agreement for LR-M features on multiphasic CT or MRI were identified using the MEDLINE, EMBASE, and Cochrane databases. The pooled kappa coefficient (κ) was calculated using the DerSimonian-Laird random-effects model. Heterogeneity was assessed using Cochran's Q test and I2 statistics. Subgroup meta-regression analyses were conducted to explore the study heterogeneity. RESULTS In total, 24 eligible studies with 5,163 hepatic observations were included. The pooled κ values were 0.72 (95% confidence interval [CI], 0.65-0.78) for rim arterial phase hyperenhancement, 0.52 (95% CI, 0.39-0.65) for peripheral washout, 0.60 (95% CI, 0.50-0.70) for delayed central enhancement, 0.68 (95% CI, 0.57-0.78) for targetoid restriction, 0.74 (95% CI, 0.65-0.83) for targetoid transitional phase/hepatobiliary phase appearance, 0.64 (95% CI, 0.49-0.78) for infiltrative appearance, 0.49 (95% CI, 0.30-0.68) for marked diffusion restriction, and 0.61 (95% CI, 0.48-0.73) for necrosis or severe ischemia. Substantial study heterogeneity was observed for all LR-M features (Cochran's Q test, P<0.01; I2≥89.2%). Studies with a mean observation size of <3 cm, those performed using 1.5-T MRI, and those with multiple image readers, were significantly associated with poor agreement of LR-M features. CONCLUSIONS The agreement for peripheral washout and marked diffusion restriction was limited. The LI-RADS should focus on improving the agreement of LR-M features.
Collapse
Affiliation(s)
- Dong Hwan Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Sang Hyun Choi
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| |
Collapse
|
4
|
Wang L, Feng B, Liang M, Li D, Cong R, Chen Z, Wang S, Ma X, Zhao X. Prognostic performance of MRI LI-RADS version 2018 features and clinical-pathological factors in alpha-fetoprotein-negative hepatocellular carcinoma. Abdom Radiol (NY) 2024; 49:1918-1928. [PMID: 38642093 DOI: 10.1007/s00261-024-04278-9] [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: 12/31/2023] [Revised: 03/04/2024] [Accepted: 03/05/2024] [Indexed: 04/22/2024]
Abstract
PURPOSE To evaluate the role of the magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS) version 2018 features and clinical-pathological factors for predicting the prognosis of alpha-fetoprotein (AFP)-negative (≤ 20 ng/ml) hepatocellular carcinoma (HCC) patients, and to compare with other traditional staging systems. METHODS We retrospectively enrolled 169 patients with AFP-negative HCC who received preoperative MRI and hepatectomy between January 2015 and August 2020 (derivation dataset:validation dataset = 118:51). A prognostic model was constructed using the risk factors identified via Cox regression analysis. Predictive performance and discrimination capability were evaluated and compared with those of two traditional staging systems. RESULTS Six risk factors, namely the LI-RADS category, blood products in mass, microvascular invasion, tumor size, cirrhosis, and albumin-bilirubin grade, were associated with recurrence-free survival. The prognostic model constructed using these factors achieved C-index of 0.705 and 0.674 in the derivation and validation datasets, respectively. Furthermore, the model performed better in predicting patient prognosis than traditional staging systems. The model effectively stratified patients with AFP-negative HCC into high- and low-risk groups with significantly different outcomes (p < 0.05). CONCLUSION A prognostic model integrating the LI-RADS category, blood products in mass, microvascular invasion, tumor size, cirrhosis, and albumin-bilirubin grade may serve as a valuable tool for refining risk stratification in patients with AFP-negative HCC.
Collapse
Affiliation(s)
- Leyao Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bing Feng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Meng Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Dengfeng Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Rong Cong
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Zhaowei Chen
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Sicong Wang
- Magnetic Resonance Imaging Research, General Electric Healthcare (China), Beijing, 100176, China
| | - Xiaohong Ma
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| |
Collapse
|
5
|
Heo S, Kang HJ, Choi SH, Kim S, Yoo Y, Choi WM, Kim SY, Lee SS. Proliferative hepatocellular carcinomas in cirrhosis: patient outcomes of LI-RADS category 4/5 and category M. Eur Radiol 2024; 34:2974-2985. [PMID: 37848775 DOI: 10.1007/s00330-023-10305-y] [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: 02/06/2023] [Revised: 07/15/2023] [Accepted: 08/10/2023] [Indexed: 10/19/2023]
Abstract
OBJECTIVES We aimed to compare Liver Imaging Reporting and Data System (LI-RADS) category 4/5 and category M (LR-M) of proliferative hepatocellular carcinomas (HCCs) in cirrhotic patients and evaluate their impacts on prognosis. METHODS This retrospective multi-reader study included cirrhotic patients with single treatment-naïve HCC ≤ 5.0 cm who underwent contrast-enhanced CT, MRI, and subsequent hepatic resection within 2 months. The percentages of CT/MRI LR-4/5 and LR-M in proliferative and non-proliferative HCCs were compared. Univariable and multivariable Cox proportional hazards regression analyses were performed to assess the association of LI-RADS categories (LR-4/5 vs. LR-M) and pathologic classification (proliferative vs. non-proliferative) with overall survival (OS) and recurrence-free survival (RFS). Subgroups of patients with proliferative and non-proliferative HCCs were analyzed to compare OS and RFS between LR-4/5 and LR-M. RESULTS Of the 204 included patients, 38 were classified as having proliferative HCC. The percentages of LR-M were higher in proliferative than non-proliferative HCC on both CT (15.8% vs. 3.0%, p = 0.007) and MRI (26.3% vs. 9.6%, p = 0.016). Independent of pathologic classification, CT and MRI LR-M were significantly associated with poorer OS (hazard ratio (HR) = 4.58, p = 0.013, and HR = 6.45, p < 0.001) and RFS (HR = 3.66, p = 0.005, and HR = 6.44, p < 0.001) than LR-4/5. MRI LR-M was associated with significantly poorer OS (p ≤ 0.003) and RFS (p < 0.001) than MRI LR-4/5 in both proliferative and non-proliferative HCCs. CONCLUSIONS This multi-reader study showed that the percentages of LR-M were significantly higher in proliferative than non-proliferative HCCs. CT/MRI LR-M was significantly associated with poor OS and RFS, independent of the pathologic classification of proliferative versus non-proliferative HCCs. CLINICAL RELEVANCE STATEMENT CT and MRI LI-RADS category M can be clinically useful in predicting poor outcomes in patients with proliferative and non-proliferative hepatocellular carcinomas. KEY POINTS • The percentages of LR-M tumors on both CT and MRI were significantly higher in proliferative than non-proliferative hepatocellular carcinomas. • Independent of pathologic classification, CT/MRI LR-M categories were correlated with poor overall survival and recurrence-free survival. • Patients with both proliferative and non-proliferative hepatocellular carcinomas categorized as MRI LR-M had significantly poorer overall survival and recurrence-free survival than those categorized as MRI LR-4/5.
Collapse
Affiliation(s)
- Subin Heo
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Hyo Jeong Kang
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Sang Hyun Choi
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea.
| | - Sehee Kim
- Department of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Youngeun Yoo
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Won-Mook Choi
- Department of Gastroenterology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - So Yeon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Seung Soo Lee
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| |
Collapse
|
6
|
Lee S, Kim YY, Shin J, Roh YH, Choi JY, Chernyak V, Sirlin CB. Liver Imaging Reporting and Data System version 2018 category 5 for diagnosing hepatocellular carcinoma: an updated meta-analysis. Eur Radiol 2024; 34:1502-1514. [PMID: 37656177 DOI: 10.1007/s00330-023-10134-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 05/24/2023] [Accepted: 07/07/2023] [Indexed: 09/02/2023]
Abstract
OBJECTIVE We performed an updated meta-analysis to determine the diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS, LR) 5 category for hepatocellular carcinoma (HCC) using LI-RADS version 2018 (v2018), and to evaluate differences by imaging modalities and type of MRI contrast material. METHODS The MEDLINE and Embase databases were searched for studies reporting the performance of LR-5 using v2018 for diagnosing HCC. A bivariate random-effects model was used to calculate the pooled per-observation sensitivity and specificity. Subgroup analysis was performed based on imaging modalities and type of MRI contrast material. RESULTS Forty-eight studies qualified for the meta-analysis, comprising 9031 patients, 10,547 observations, and 7216 HCCs. The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC were 66% (95% CI, 61-70%) and 91% (95% CI, 89-93%), respectively. In the subgroup analysis, MRI with extracellular agent (ECA-MRI) showed significantly higher pooled sensitivity (77% [95% CI, 70-82%]) than CT (66% [95% CI, 58-73%]; p = 0.023) or MRI with gadoxetate (Gx-MRI) (65% [95% CI, 60-70%]; p = 0.001), but there was no significant difference between ECA-MRI and MRI with gadobenate (gadobenate-MRI) (73% [95% CI, 61-82%]; p = 0.495). Pooled specificities were 88% (95% CI, 80-93%) for CT, 92% (95% CI, 86-95%) for ECA-MRI, 93% (95% CI, 91-95%) for Gx-MRI, and 91% (95% CI, 84-95%) for gadobenate-MRI without significant differences (p = 0.084-0.803). CONCLUSIONS LI-RADS v2018 LR-5 provides high specificity for HCC diagnosis regardless of modality or contrast material, while ECA-MRI showed higher sensitivity than CT or Gx-MRI. CLINICAL RELEVANCE STATEMENT Refinement of the criteria for improving sensitivity while maintaining high specificity of LR-5 for HCC diagnosis may be an essential future direction. KEY POINTS • The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC using LI-RADSv2018 were 66% and 91%, respectively. • ECA-MRI showed higher sensitivity than CT (77% vs 66%, p = 0.023) or Gx-MRI (77% vs 65%, p = 0.001). • LI-RADS v2018 LR-5 provides high specificity (88-93%) for HCC diagnosis regardless of modality or contrast material type.
Collapse
Affiliation(s)
- Sunyoung Lee
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Yeun-Yoon Kim
- 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
| | - Yun Ho Roh
- Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jin-Young Choi
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Victoria Chernyak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA
| |
Collapse
|
7
|
Min JH, Lee MW, Rhim H, Han S, Song KD, Kang TW, Jeong WK, Cha DI, Kim JM, Choi GS, Kim K. LI-RADS category is associated with treatment outcomes of small single HCC: surgical resection vs. radiofrequency ablation. Eur Radiol 2024; 34:525-537. [PMID: 37526668 DOI: 10.1007/s00330-023-09998-y] [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: 02/21/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 08/02/2023]
Abstract
OBJECTIVES To assess whether the Liver Imaging Reporting and Data System (LI-RADS) category is associated with the treatment outcomes of small single hepatocellular carcinoma (HCC) after surgical resection (SR) and radiofrequency ablation (RFA). METHODS This retrospective study included 357 patients who underwent SR (n = 209) or RFA (n = 148) for a single HCC of ≤ 3 cm between 2014 and 2016. LI-RADS categories were assigned. Overall survival (OS), recurrence-free survival (RFS), and local tumor progression (LTP) rates after treatment were compared according to the LI-RADS category (LR-4/5 vs. LR-M) before and after propensity score matching (PSM). Prognostic factors for treatment outcomes were assessed. RESULTS In total, 357 patients (mean age, 59 years; men, 272) with 357 HCCs (294 LR-4/5 and 63 LR-M) were included. After PSM (n = 78 in each treatment group), there were 10 and 11 LR-M HCCs in the SR and RFA group, respectively. There were no significant differences in OS or RFS. However, SR provided a lower 5-year LTP rate than RFA (1.4% vs. 14.9%, p = 0.001). SR provided a lower 5-year LTP rate than RFA for LR-M HCCs (0% vs. 34.4%, p = 0.062) and LR-4/5 HCCs (1.5% vs. 12.0%, p = 0.008). The LI-RADS category was the sole risk factor associated with poor OS (hazard ratio [HR] 3.79, p = 0.004), RFS (HR 2.12; p = 0.001), and LTP (HR 2.89; p = 0.032). CONCLUSION LI-RADS classification is associated with the treatment outcome of HCC, supporting favorable outcomes of SR over RFA for LTP, especially for HCCs categorized as LR-M. CLINICAL RELEVANCE STATEMENT Liver Imaging Reporting and Data System category has a potential prognostic role, supporting favorable outcomes of surgical resection over radiofrequency ablation for local tumor progression, especially for hepatocellular carcinoma categorized as LR-M. KEY POINTS • SR provided a lower 5-year LTP rate than RFA for HCCs categorized as LR-M (0% vs. 34.4%, p = 0.062) and HCCs categorized as LR-4/5 (1.5% vs. 12.0%, p = 0.008). • There is a steeply increased risk of LTP within 1 year after RFA for LR-M HCCs, compared to SR. • The LI-RADS category was the sole risk factor associated with poor OS (HR 3.79, p = 0.004), RFS (HR 2.12; p = 0.001), and LTP (HR 2.89; p = 0.032) in patients with HCC of ≤ 3 cm treated with SR or RFA.
Collapse
Affiliation(s)
- Ji Hye Min
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Min Woo Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea.
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea.
| | - Hyunchul Rhim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Seungchul Han
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Kyoung Doo Song
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Tae Wook Kang
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Woo Kyoung Jeong
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Dong Ik Cha
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Jong Man Kim
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Gyu Seong Choi
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kyunga Kim
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| |
Collapse
|
8
|
Wang L, Liang M, Feng B, Li D, Cong R, Chen Z, Wang S, Ma X, Zhao X. Microvascular invasion-negative hepatocellular carcinoma: Prognostic value of qualitative and quantitative Gd-EOB-DTPA MRI analysis. Eur J Radiol 2023; 168:111146. [PMID: 37832198 DOI: 10.1016/j.ejrad.2023.111146] [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: 08/16/2023] [Revised: 09/27/2023] [Accepted: 10/06/2023] [Indexed: 10/15/2023]
Abstract
OBJECTIVES The purpose of this study was to establish a model for predicting the prognosis of patients with microvascular invasion (MVI)-negative hepatocellular carcinoma (HCC) based on qualitative and quantitative analyses of Gd-EOB-DTPA magnetic resonance imaging (MRI). MATERIALS AND METHODS Consecutive patients with MVI-negative HCC who underwent preoperative Gd-EOB-DTPA MRI between January 2015 and December 2019 were retrospectively enrolled.In total, 122 patients were randomly assigned to the training and validation groups at a ratio of 7:3. Univariate and multivariate logistic regression analyses were performed to identify significant clinical parameters and MRI features, including quantitative and qualitative parameters associated with prognosis, which were incorporated into a predictive nomogram. The end-point of this study was recurrence-free survival. Outcomes were compared between groups using the Kaplan-Meier method with the log-rank test. RESULTS During a median follow-up period of 58.86 months, 38 patients (31.15 %) experienced recurrence. Multivariate analysis revealed that lower relative enhancement ratio (RER), hepatobiliary phase hypointensity without arterial phase hyperenhancement, Liver Imaging Reporting and Data System category, mild-moderate T2 hyperintensity, and higher aspartate aminotransferase levels were risk factors associated with prognosis and then incorporated into the prognostic model. C-indices for training and validation groups were 0.732 and 0.692, respectively. The most appropriate cut-off value for RER was 1.197. Patients with RER ≤ 1.197 had significantly higher postoperative recurrence rates than those with RER > 1.197 (p = 0.004). CONCLUSION The model integrating qualitative and quantitative imaging parameters and clinical parameters satisfactorily predicted the prognosis of patients with MVI-negative HCC.
Collapse
Affiliation(s)
- Leyao Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Meng Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Bing Feng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Dengfeng Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Rong Cong
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Zhaowei Chen
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Sicong Wang
- Sicong Wang, Magnetic Resonance Imaging Research, General Electric Healthcare (China), Beijing 100176, China
| | - Xiaohong Ma
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
| |
Collapse
|
9
|
Pan YJ, Liu W, Qiu QX, Miao SL, Zeng MS, Shan Y, Lin J, Xu PJ. Prognostic value of LI-RADS category on MRI in patients with primary hepatic lymphoepithelioma-like carcinoma. Eur Radiol 2023; 33:5993-6000. [PMID: 37014407 DOI: 10.1007/s00330-023-09598-w] [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: 10/14/2022] [Revised: 01/18/2023] [Accepted: 02/10/2023] [Indexed: 04/05/2023]
Abstract
OBJECTIVES To compare the clinical and MRI features of primary hepatic lymphoepithelioma-like carcinoma (LELC) categorized as LR-M or LR-4/5 using the Liver Imaging Reporting and Data System (LI-RADS) version 2018 and to determine the prognostic factors for recurrence-free survival (RFS). METHODS In this retrospective study, 37 patients with surgically confirmed LELC were included. Two independent observers evaluated preoperative MRI features according to the LI-RADS version 2018. Clinical and imaging features were compared between two groups. RFS and the associated factors were evaluated using Cox proportional hazards regression analysis, Kaplan-Meier analysis, and log-rank test. RESULTS In total, 37 patients (mean age, 58.5 ± 10.3 years) were evaluated. Sixteen (43.2%) LELCs were categorized as LR-M and twenty-one (56.8%) LELCs were categorized as LR-4/5. In the multivariate analysis, the LR-M category was an independent factor for RFS (HR 7.908, 95% CI 1.170-53.437; p = 0.033). RFS rates were significantly lower in patients with LR-M LELCs than in patients with LR-4/5 LELCs (5-year RFS rate, 43.8% vs.85.7%; p = 0.002). CONCLUSION The LI-RADS category was significantly associated with postsurgical prognosis of LELC, with tumor categorized as LR-M having a worse RFS than those categorized as LR-4/5. KEY POINTS • Lymphoepithelioma-like carcinoma patients categorized as LR-M have worse recurrence-free survival than those categorized as LR-4/5. • MRI-based LI-RADS categorization was an independent factor for postoperative prognosis of primary hepatic lymphoepithelioma-like carcinoma.
Collapse
Affiliation(s)
- Yi-Jun Pan
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
| | - Wei Liu
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, No. 270 Dong'an Road, Xuhui District, Shanghai, 200032, China
| | - Qi-Xuan Qiu
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
| | - Shou-Liang Miao
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Nanbaixiang, Ouhai District, Wenzhou, 325015, Zhejiang, China
| | - Meng-Su Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
- Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
| | - Yan Shan
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
| | - Jiang Lin
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
| | - Peng-Ju Xu
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
| |
Collapse
|
10
|
Shen YT, Yue WW, Xu HX. Non-invasive imaging in the diagnosis of combined hepatocellular carcinoma and cholangiocarcinoma. Abdom Radiol (NY) 2023; 48:2019-2037. [PMID: 36961531 DOI: 10.1007/s00261-023-03879-0] [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: 11/27/2022] [Revised: 02/28/2023] [Accepted: 03/02/2023] [Indexed: 03/25/2023]
Abstract
Combined hepatocellular-cholangiocarcinoma (cHCC-CC) is a rare type of primary liver cancer. It is a complex "biphenotypic" tumor type consisting of bipotential hepatic progenitor cells that can differentiate into cholangiocytes subtype and hepatocytes subtype. The prognosis of patients with cHCC-CC is quite poor with its specific and more aggressive nature. Furthermore, there are no definite demographic or clinical features of cHCC-CC, thus a clear preoperative identification and accurate non-invasive imaging diagnostic analysis of cHCC-CC are of great value. In this review, we first summarized the epidemiological features, pathological findings, molecular biological information and serological indicators of cHCC-CC disease. Then we reviewed the important applications of non-invasive imaging modalities-particularly ultrasound (US)-in cHCC-CC, covering both diagnostic and prognostic assessment of patients with cHCC-CC. Finally, we presented the shortcomings and potential outlooks for imaging studies in cHCC-CC.
Collapse
Affiliation(s)
- Yu-Ting Shen
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China
| | - Wen-Wen Yue
- Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University, Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai, 200072, China.
| | - Hui-Xiong Xu
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China.
| |
Collapse
|
11
|
Chernyak V, Fowler KJ, Do RKG, Kamaya A, Kono Y, Tang A, Mitchell DG, Weinreb J, Santillan CS, Sirlin CB. LI-RADS: Looking Back, Looking Forward. Radiology 2023; 307:e222801. [PMID: 36853182 PMCID: PMC10068888 DOI: 10.1148/radiol.222801] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/09/2023] [Accepted: 01/23/2023] [Indexed: 03/01/2023]
Abstract
Since its initial release in 2011, the Liver Imaging Reporting and Data System (LI-RADS) has evolved and expanded in scope. It started as a single algorithm for hepatocellular carcinoma (HCC) diagnosis with CT or MRI with extracellular contrast agents and has grown into a multialgorithm network covering all major liver imaging modalities and contexts of use. Furthermore, it has developed its own lexicon, report templates, and supplementary materials. This article highlights the major achievements of LI-RADS in the past 11 years, including adoption in clinical care and research across the globe, and complete unification of HCC diagnostic systems in the United States. Additionally, the authors discuss current gaps in knowledge, which include challenges in surveillance, diagnostic population definition, perceived complexity, limited sensitivity of LR-5 (definite HCC) category, management implications of indeterminate observations, challenges in reporting, and treatment response assessment following radiation-based therapies and systemic treatments. Finally, the authors discuss future directions, which will focus on mitigating the current challenges and incorporating advanced technologies. Tha authors envision that LI-RADS will ultimately transform into a probability-based system for diagnosis and prognostication of liver cancers that will integrate patient characteristics and quantitative imaging features, while accounting for imaging modality and contrast agent.
Collapse
Affiliation(s)
- Victoria Chernyak
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| | - Kathryn J. Fowler
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| | - Richard K. G. Do
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| | - Aya Kamaya
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| | - Yuko Kono
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| | - An Tang
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| | - Donald G. Mitchell
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| | - Jeffrey Weinreb
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| | - Cynthia S. Santillan
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| | - Claude B. Sirlin
- From the Department of Radiology, Memorial Sloan-Kettering Cancer
Center, New York, NY (V.C., R.K.G.D.); Liver Imaging Group, Department of
Radiology, University of California, San Diego, San Diego, Calif (K.J.F.,
C.S.S., C.B.S.); Department of Radiology, Stanford University Medical Center,
Stanford, Calif (A.K.); Department of Medicine and Radiology, University of
California, San Diego, San Diego, Calif (Y.K.); Department of Radiology,
Radiation Oncology and Nuclear Medicine, Université de Montréal,
Montréal, Canada (A.T.); Department of Radiology, Thomas Jefferson
University Hospital, Philadelphia, Pa (D.G.M.); and Department of Radiology,
Yale Medical School, New Haven, Conn (J.W.)
| |
Collapse
|
12
|
Wang R, Xu H, Chen W, Jin L, Ma Z, Wen L, Wang H, Cao K, Du X, Li M. Gadoxetic acid-enhanced MRI with a focus on LI-RADS v2018 imaging features predicts the prognosis after radiofrequency ablation in small hepatocellular carcinoma. Front Oncol 2023; 13:975216. [PMID: 36816925 PMCID: PMC9932892 DOI: 10.3389/fonc.2023.975216] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 01/12/2023] [Indexed: 02/05/2023] Open
Abstract
Introduction Gadoxetic acid-enhanced magnetic resonance imaging (MRI) contributes to evaluating the prognosis of small hepatocellular carcinoma (sHCC) following treatment. We have investigated the potential role of gadoxetic acid-enhanced MRI based on LI-RADS (Liver Imaging Reporting and Data System) v2018 imaging features in the prognosis prediction of patients with sHCC treated with radiofrequency ablation (RFA) as the first-line treatment and formulated a predictive nomogram. Methods A total of 204 patients with sHCC who all received RFA as the first-line therapy were enrolled. All patients had undergone gadoxetic acid-enhanced MRI examinations before RFA. Uni- and multivariable analyses for RFS were assessing using a Cox proportional hazards model. A novel nomogram was further constructed for predicting RFS. The clinical capacity of the model was validated according to calibration curves, the concordance index (C-index), and decision curve analyses. Results Alpha fetoprotein (AFP) > 100 ng/ml (HR, 2.006; 95% CI, 1.111-3.621; P = 0.021), rim arterial phase hyperenhancement (APHE) (HR, 2.751; 95% CI, 1.511-5.011; P = 0.001), and targetoid restriction on diffusion-weighted imaging (DWI) (HR, 3.289; 95% CI, 1.832-5.906; P < 0.001) were considered as the independent risk features for recurrence in patients with sHCC treated with RFA. The calibration curves and C-indexes (C-index values of 0.758 and 0.807) showed the superior predictive performance of the integrated nomogram in both the training and validation groups. Discussion The gadoxetic acid-enhanced MRI features based on LI-RADS v2018, including rim APHE, targetoid restriction on DWI, and the AFP level, are the independent risk factors of recurrence in patients with sHCC treated with RFA as the first-line therapy. The predictive clinical-radiological nomogram model was constructed for clinicians to develop individualized treatment and surveillance strategies.
Collapse
Affiliation(s)
- Ruizhi Wang
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China
| | - Hengtian Xu
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Wufei Chen
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China
| | - Liang Jin
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China
| | - Zhuangxuan Ma
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China
| | - Lei Wen
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Hongwei Wang
- Department of General Surgery, Huadong Hospital, Fudan University, Shanghai, China
| | - Kun Cao
- Department of Hepatobiliary Surgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Xia Du
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China,*Correspondence: Xia Du, ; Ming Li,
| | - Ming Li
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China,*Correspondence: Xia Du, ; Ming Li,
| |
Collapse
|
13
|
Lee S, Kim YY, Shin J, Son WJ, Roh YH, Choi JY, Sirlin CB, Chernyak V. Percentages of Hepatocellular Carcinoma in LI-RADS Categories with CT and MRI: A Systematic Review and Meta-Analysis. Radiology 2023; 307:e220646. [PMID: 36625748 DOI: 10.1148/radiol.220646] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background The Liver Imaging Reporting and Data System (LI-RADS) CT and MRI algorithm applies equally to CT, MRI with extracellular contrast agents (ECA-MRI), and MRI with gadoxetate (Gx-MRI). Purpose To estimate pooled percentages of hepatocellular carcinoma (HCC) and overall malignancy for each LI-RADS category with CT and MRI. Materials and Methods MEDLINE and EMBASE databases were searched for research articles (January 2014-April 2021) reporting the percentages of observations in each LI-RADS category with use of versions 2014, 2017, or 2018. Study design, population characteristics, imaging modality, reference standard, and numbers of HCC and non-HCC malignancies in each category were recorded. A random-effects model evaluated the pooled percentage of HCC and overall malignancy for each category. Results There were 49 studies with 9620 patients and a total 11 562 observations, comprising 7921 HCCs, 1132 non-HCC malignancies, and 2509 benign entities. No HCC or non-HCC malignancies were reported with any modality in the LR-1 category. The pooled percentages of HCC for CT, ECA-MRI, and Gx-MRI, respectively, were 10%, 6%, and 1% for LR-2 (P = .16); 48%, 31%, and 38% for LR-3 (P = .42); 76%, 64%, and 77% for LR-4 (P = .62); 96%, 95%, and 96% for LR-5 (P = .76); 88%, 76%, and 78% for LR-5V or LR-TIV (tumor in vein) (P = .42); and 20%, 30%, and 35% for LR-M (P = .32). Most LR-M (93%-100%) and LR-5V or LR-TIV (99%-100%) observations were malignant, regardless of modality. Conclusion There was no difference in percentages of hepatocellular carcinoma and overall malignancy between CT, MRI with extracellular contrast agents, and MRI with gadoxetate for any Liver Imaging Reporting and Data System categories. © RSNA, 2023 Supplemental material is available for this article See also the editorial by Ronot in this issue.
Collapse
Affiliation(s)
- Sunyoung Lee
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.L., Y.Y.K., J.S., J.Y.C.); Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (W.J.S., Y.H.R.); Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S.); and Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (V.C.)
| | - Yeun-Yoon Kim
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.L., Y.Y.K., J.S., J.Y.C.); Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (W.J.S., Y.H.R.); Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S.); and Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (V.C.)
| | - Jaeseung Shin
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.L., Y.Y.K., J.S., J.Y.C.); Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (W.J.S., Y.H.R.); Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S.); and Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (V.C.)
| | - Won Jeong Son
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.L., Y.Y.K., J.S., J.Y.C.); Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (W.J.S., Y.H.R.); Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S.); and Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (V.C.)
| | - Yun Ho Roh
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.L., Y.Y.K., J.S., J.Y.C.); Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (W.J.S., Y.H.R.); Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S.); and Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (V.C.)
| | - Jin-Young Choi
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.L., Y.Y.K., J.S., J.Y.C.); Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (W.J.S., Y.H.R.); Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S.); and Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (V.C.)
| | - Claude B Sirlin
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.L., Y.Y.K., J.S., J.Y.C.); Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (W.J.S., Y.H.R.); Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S.); and Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (V.C.)
| | - Victoria Chernyak
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.L., Y.Y.K., J.S., J.Y.C.); Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (W.J.S., Y.H.R.); Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S.); and Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (V.C.)
| |
Collapse
|
14
|
Min JH, Lee MW, Park HS, Lee DH, Park HJ, Lee JE, Park SJ, Kim SS, Park SH, Ha SY, Hwang JA, Cha DI, Park B. LI-RADS Version 2018 Targetoid Appearances on Gadoxetic Acid-Enhanced MRI: Interobserver Agreement and Diagnostic Performance for the Differentiation of HCC and Non-HCC Malignancy. AJR Am J Roentgenol 2022; 219:421-432. [PMID: 35319906 DOI: 10.2214/ajr.22.27380] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
BACKGROUND. In LI-RADS version 2018, observations showing at least one of five targetoid appearances in different sequences or postcontrast phases are categorized LR-M, indicating likely non-hepatocellular carcinoma (HCC) malignancy. OBJECTIVE. The purpose of this study was to evaluate interobserver agreement for LI-RADS targetoid appearances among a large number of radiologists of varying experience and the diagnostic performance of targetoid appearances for differentiating HCC from non-HCC malignancy. METHODS. This retrospective study included 100 patients (76 men, 24 women; mean age, 58 ± 9 [SD] years) at high risk of HCC who underwent gadoxetic acid-enhanced MRI within 30 days before hepatic tumor resection (25 randomly included patients with non-HCC malignancy [13, intrahepatic cholangiocarcinoma; 12, combined HCC-cholangiocarcinoma]; 75 matched patients with HCC). Eight radiologists (four more experienced [8-15 years]; four less experienced [1-5 years]) from seven institutions independently assessed observations for the five targetoid appearances and LI-RADS categorization. Interobserver agreement and diagnostic performance for non-HCC malignancy were evaluated. RESULTS. Interobserver agreement was poor for peripheral washout (κ = 0.20); moderate for targetoid transitional phase or hepatobiliary phase appearance (κ = 0.33), delayed central enhancement (κ = 0.37), and targetoid restriction (κ = 0.43); and substantial for rim arterial phase hyperenhancement (κ = 0.61). Agreement was fair for at least one targetoid appearance (κ = 0.36) and moderate for at least two, three, or four targetoid appearances (κ = 0.43-0.51). Agreement for individual targetoid appearances was not significantly different between more experienced and less experienced readers other than for targetoid restriction (κ = 0.63 vs 0.43; p = .001). Agreement for at least one targetoid appearance was fair among more experienced (κ = 0.29) and less experienced (κ = 0.37) reviewers. Agreement for at least two, three, or four targetoid appearances was moderate to substantial among more experienced reviewers (κ = 0.45-0.63) and moderate among less experienced reviewers (κ = 0.42-0.56). Existing LR-M criteria of at least one targetoid appearance had median accuracy for non-HCC malignancy of 62%, sensitivity of 84%, and specificity of 54%. For all reviewers, accuracy was highest when at least three (median accuracy, 79%; sensitivity, 68%; specificity, 82%) or four (median accuracy, 80%; sensitivity, 54%; specificity, 88%) targetoid appearances were required. CONCLUSION. Targetoid appearances and LR-M categorization exhibited considerable interobserver variation among both more and less experienced reviewers. CLINICAL IMPACT. Requiring multiple targetoid appearances for LR-M categorization improved interobserver agreement and diagnostic accuracy for non-HCC malignancy.
Collapse
Affiliation(s)
- Ji Hye Min
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro Gangnam-gu, Seoul 06351, Republic of Korea
| | - Min Woo Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro Gangnam-gu, Seoul 06351, Republic of Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hee Sun Park
- Department of Radiology, Konkuk University School of Medicine, Seoul, Republic of Korea
| | - Dong Ho Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyun Jeong Park
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea
| | - Ji Eun Lee
- Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon, Republic of Korea
| | - Sae-Jin Park
- Department of Radiology, Seoul National University College of Medicine (Boramae Medical Center), Seoul, Republic of Korea
| | - Seung-Seob Kim
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seung Hyun Park
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro Gangnam-gu, Seoul 06351, Republic of Korea
| | - Sang Yun Ha
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jeong Ah Hwang
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro Gangnam-gu, Seoul 06351, Republic of Korea
| | - Dong Ik Cha
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro Gangnam-gu, Seoul 06351, Republic of Korea
| | - Boram Park
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| |
Collapse
|
15
|
Shin J, Lee S, Hwang JA, Lee JE, Chung YE, Choi JY, Park MS. MRI-diagnosis of category LR-M observations in the Liver Imaging Reporting and Data System v2018: a systematic review and meta-analysis. Eur Radiol 2022; 32:3319-3326. [PMID: 35031839 DOI: 10.1007/s00330-021-08382-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 09/17/2021] [Accepted: 10/04/2021] [Indexed: 11/29/2022]
Abstract
OBJECTIVES We performed a meta-analysis to determine the probability of hepatocellular carcinoma (HCC) and non-HCC malignancies in Liver Imaging Reporting and Data System (LI-RADS) category M (LR-M) observations and the frequency of defined LR-M imaging features on MRI using LI-RADS v2018. METHODS We searched the MEDLINE and EMBASE databases to identify studies published from 1 January 2018 to 16 March 2021 reporting the probability of category LR-M in HCC and non-HCC malignancies on MRI. The pooled percentages of HCC and non-HCC malignancies in the LR-M observations were evaluated. Meta-regression analysis was performed to identify factors for study heterogeneity. The frequencies of defined LR-M imaging features were also calculated. Risk of bias and concerns regarding applicability were evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. RESULTS We identified 18 studies reporting the diagnostic performance of the LR-M category (3,812 observations in 3,615 patients), with nine studies reporting the frequencies of LR-M imaging features. The pooled percentages of HCC and non-HCC malignancies in the LR-M observations were 29% (95% confidence interval [CI], 21-38%) and 67% (95%CI, 57-77%), respectively. The study type and inclusion of benign lesions were significant factors for study heterogeneity. Of the 10 LR-M imaging features, rim arterial phase hyperenhancement (APHE) showed the highest frequency in non-HCC malignancies (68%; 95%CI, 61-75%). CONCLUSIONS The LR-M category was commonly used to characterize non-HCC malignancies, but also included 29% of HCC. The frequencies of the different LR-M imaging features were variable, with rim APHE showing the highest frequency in non-HCC malignancies. KEY POINTS • In the LR-M category using LI-RADS v2018 for MRI, the pooled percentage of malignancies in general was 96%, with 29% HCC and 67% non-HCC malignancies, while the remaining 4% was benign entity. • The study type and inclusion of benign lesions were significant factors contributing to substantial heterogeneity among included studies. • The frequencies of the different LR-M imaging features were variable, with rim APHE showing the highest frequency in non-HCC malignancies.
Collapse
Affiliation(s)
- Jaeseung Shin
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Sunyoung Lee
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
| | - Jeong Ah Hwang
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Ji Eun Lee
- Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon, Republic of Korea
| | - Yong Eun Chung
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Jin-Young Choi
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Mi-Suk Park
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| |
Collapse
|
16
|
Moura Cunha G, Chernyak V, Fowler KJ, Sirlin CB. Up-to-Date Role of CT/MRI LI-RADS in Hepatocellular Carcinoma. J Hepatocell Carcinoma 2021; 8:513-527. [PMID: 34104640 PMCID: PMC8180267 DOI: 10.2147/jhc.s268288] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 04/01/2021] [Indexed: 12/16/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of mortality worldwide and a major healthcare burden in most societies. Computed tomography (CT) and magnetic resonance imaging (MRI) play a pivotal role in the medical care of patients with or at risk for hepatocellular carcinoma (HCC). When stringent imaging criteria are fulfilled, CT and MRI allow for diagnosis, staging, and assessment of response to treatment, without the need for invasive workup, and can inform clinical decision making. Owing to the central role of these imaging modalities in HCC management, standardization is essential to facilitate proper imaging technique, accurate interpretation, and clear communication among all stakeholders in both the clinical practice and research settings. The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system that provides standardization across the continuum of HCC imaging, including ordinal probabilistic approach for reporting that directs individualized management. This review discusses the up-to-date role of CT and MRI in HCC imaging from the LI-RADS perspective. It also provides a glimpse into the future by discussing how advances in knowledge and technology are likely to enrich the LI-RADS approach.
Collapse
Affiliation(s)
- Guilherme Moura Cunha
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Victoria Chernyak
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Kathryn J Fowler
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, CA, USA
| |
Collapse
|