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Zhang ZX, Xv H, Du YN, Lv ZB, Yang ZH. Optimizing LI-RADS: ancillary features screened from LR-3/4 categories can improve the diagnosis of HCC on MRI. BMC Gastroenterol 2024; 24:117. [PMID: 38515017 PMCID: PMC10956370 DOI: 10.1186/s12876-024-03201-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 03/11/2024] [Indexed: 03/23/2024] Open
Abstract
OBJECTIVE To determine the high-efficiency ancillary features (AFs) screened from LR-3/4 lesions and the HCC/non-HCC group and the diagnostic performance of LR3/4 observations. MATERIALS AND METHODS We retrospectively analyzed a total of 460 patients (with 473 nodules) classified into LR-3-LR-5 categories, including 311 cases of hepatocellular carcinoma (HCC), 6 cases of non-HCC malignant tumors, and 156 cases of benign lesions. Two faculty abdominal radiologists with experience in hepatic imaging reviewed and recorded the major features (MFs) and AFs of the Liver Imaging Reporting and Data System (LI-RADS). The frequency of the features and diagnostic performance were calculated with a logistic regression model. After applying the above AFs to LR-3/LR-4 observations, the sensitivity and specificity for HCC were compared. RESULTS The average age of all patients was 54.24 ± 11.32 years, and the biochemical indicators ALT (P = 0.044), TBIL (P = 0.000), PLT (P = 0.004), AFP (P = 0.000) and Child‒Pugh class were significantly higher in the HCC group. MFs, mild-moderate T2 hyperintensity, restricted diffusion and AFs favoring HCC in addition to nodule-in-nodule appearance were common in the HCC group and LR-5 category. AFs screened from the HCC/non-HCC group (AF-HCC) were mild-moderate T2 hyperintensity, restricted diffusion, TP hypointensity, marked T2 hyperintensity and HBP isointensity (P = 0.005, < 0.001, = 0. 032, p < 0.001, = 0.013), and the AFs screened from LR-3/4 lesions (AF-LR) were restricted diffusion, mosaic architecture, fat in mass, marked T2 hyperintensity and HBP isointensity (P < 0.001, = 0.020, = 0.036, < 0.001, = 0.016), which were not exactly the same. After applying AF-HCC and AF-LR to LR-3 and LR-4 observations in HCC group and Non-HCC group, After the above grades changed, the diagnostic sensitivity for HCC were 84.96% using AF-HCC and 85.71% using AF-LR, the specificity were 89.26% using AF-HCC and 90.60% using AF-LR, which made a significant difference (P = 0.000). And the kappa value for the two methods of AF-HCC and AF-LR were 0.695, reaching a substantial agreement. CONCLUSION When adjusting for LR-3/LR-4 lesions, the screened AFs with high diagnostic ability can be used to optimize LI-RADS v2018; among them, AF-LR is recommended for better diagnostic capabilities.
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Affiliation(s)
- Zi-Xin Zhang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- Department of Radiology, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Hui Xv
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Yan-Ni Du
- Department of Radiology, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Zhi-Bin Lv
- Department of Radiology, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Zheng-Han Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
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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.
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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.)
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