New strategy for Liver Imaging Reporting and Data System category M to improve diagnostic performance of MRI for hepatocellular carcinoma ≤ 3.0 cm
- Abstract
- Purpose: We aimed to determine a new strategy for Liver Imaging Reporting and Data System category M (LR-M) criteria to improve the diagnosis of HCC ≤ 3.0 cm on magnetic resonance imaging (MRI).
Methods: A total of 463 pathologically confirmed hepatic observations ≤ 3.0 cm (375 HCCs, 32 other malignancies, 56 benignities) in 384 patients at risk of HCC who underwent gadoxetate-enhanced MRI were retrospectively analyzed. Two radiologists evaluated the presence of major, ancillary, and LR-M features according to LI-RADS v2018. Of the ten LR-M features, those significantly associated with non-HCC malignancy were identified using multivariable logistic regression analysis, and new LR-M criteria for improving the diagnosis of HCC were investigated. Generalized estimating equations were used to compare sensitivity and specificity of LR-5 for diagnosing HCC using the new LR-M criteria with values calculated using the original LR-M criteria. p < 0.05 was considered to indicate a significant difference.
Results: Of ten LR-M features, rim arterial-phase hyperenhancement, delayed central enhancement, targetoid restriction, and targetoid transitional-phase/hepatobiliary-phase appearance were independently significantly associated with non-HCC malignancy (adjusted odds ratio ≥ 6.2; p ≤ 0.02). Using the new LR-M criteria (two or more of these significant features), the sensitivity of LR-5 for diagnosing HCC was higher than that with the original LR-M criteria (69% [95% confidence interval 64-73%] vs. 65% [61-70%], p = 0.002), whereas the specificity was similar (90% [82-95%] vs. 92% [83-96%], p = 0.28).
Conclusion: The new LR-M criteria (two or more significant features) can improve the sensitivity of LR-5 for diagnosing HCC ≤ 3.0 cm, without compromising specificity.
- Author(s)
- Jong Keon Jang; Sang Hyun Choi; Jae Ho Byun; Seo Young Park; So Jung Lee; So Yeon Kim; Hyung Jin Won; Yong Moon Shin; Pyo-Nyun Kim
- Issued Date
- 2022
- Type
- Article
- Keyword
- Accuracy; Diagnosis; Hepatocellular carcinoma; Liver Imaging Reporting and Data System; Magnetic resonance imaging
- DOI
- 10.1007/s00261-022-03538-w
- URI
- https://oak.ulsan.ac.kr/handle/2021.oak/15637
- Publisher
- ABDOMINAL RADIOLOGY
- Language
- 영어
- ISSN
- 2366-004X
- Citation Volume
- 47
- Citation Number
- 7
- Citation Start Page
- 2289
- Citation End Page
- 2298
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Appears in Collections:
- Medicine > Nursing
- 공개 및 라이선스
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