Evidence map›Paper›PMID 42360478›Full record

ArticleEuropean radiology2026

LI-RADS v2018 versus KLCA-NCC v2022: comparison of probability-based HCC categories.

Jeong Hee Yoon, Eun Sun Lee, Young Kon Kim, Chang Hee Lee, Jeong Woo Kim, Won Chang, Joon-Il Choi, Beom Jin Park, Jin-Young Choi, Seung-Seob Kim and 6 more

Abstract read
PubMed Publisher
In one paragraph

Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Jeong Hee Yoon *Department of Radiology, Seoul National University Hospital, Seoul, 03080, Republic of Korea.
Eun Sun Lee *Department of Radiology, Chung-Ang University Hospital, Seoul, 06973, Republic of Korea.
Young Kon KimDepartment of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea.
Chang Hee LeeDepartment of Radiology, Korea University Guro Hospital & College of Medicine, Seoul, 08380, Republic of Korea.
Jeong Woo KimDepartment of Radiology, Korea University Guro Hospital & College of Medicine, Seoul, 08380, Republic of Korea.
Won ChangDepartment of Radiology, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
Joon-Il ChoiDepartment of Radiology, Seoul Saint Mary's Hospital, College of Medicine, The Catholic University of Korea, 06591, Seoul, Republic of Korea.
Beom Jin ParkDepartment of Radiology and Advanced Medical Imaging Institute, Korea University Anam Hospital, Korea University College of Medicine, Seoul, 02841, Republic of Korea.
Jin-Young ChoiDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea.
Seung-Seob KimDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea.
Jeong-Sik YuDepartment of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, 06273, Republic of Korea.
Seong Jin ParkDepartment of Radiology, Kyung Hee University College of Medicine, Kyung Hee University Hospital, Seoul, 02447, Republic of Korea.
Myung-Won YouDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea.
Myoung-Jin JangMedical Research Collaborating Center, Seoul National University Hospital & Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
Hee Sun ParkDepartment of Radiology, Konkuk University Medical Center, Konkuk University School of Medicine, 120-1 Neungdong-ro, Gwangjin-gu, Seoul, 05030, Republic of Korea. heesun.park@gmail.com.
Jeong Min LeeDepartment of Radiology, Seoul National University Hospital, Seoul, 03080, Republic of Korea. jmsh@snu.ac.kr.ORCID http://orcid.org/0000-0003-0561-8777

Funding

Bayer Korea SNUH-1809-030-969
6 · The paper itself

Abstract

objectivesTo compare the diagnostic performance of corresponding probability-based categories between LI-RADS v2018 and Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) v2022. MATERIALS AND

methodsThis retrospective multicenter study included treatment-naïve patients at risk of hepatocellular carcinoma (HCC) who underwent gadoxetic acid-enhanced MRI between January 2015 and June 2018. Four radiologists independently evaluated MRI and CT when available; observations were categorized according to both criteria. Reference standards were pathology or clinical diagnosis. Generalized estimating equations were used for lesion clustering.

resultsThe study included 2237 patients (1666 men; mean age, 59 ± 11 years) with 2445 lesions. On MRI, LR-5 showed a higher positive predictive value (PPV) than KLCA-NCC "definite HCC" (93.9% vs. 91.7%, p < 0.001). PPV was not different between LR-4 and KLCA-NCC "probable HCC" (68.2% vs. 64.1%, p = 0.141). HCC proportion was 13.2% in LR-3 and 40.8% in KLCA-NCC "indeterminate nodule" (p < 0.001). In 1455 patients with 1590 lesions on CT, LR-5 and KLCA-NCC had comparable PPV (92.9% in each). PPV of KLCA-NCC "probable HCC" was higher than LR-4 (83.8% vs. 73.9%, p = 0.012). HCC proportion was 52.0% in LR-3 and 46.2% in KLCA-NCC "indeterminate nodule" (p = 0.001).

conclusionBoth LI-RADS v2018 and KLCA-NCC v2022 demonstrated effective probability-based risk stratification, but corresponding probability categories were not interchangeable. On CT, category performance differed from MRI, highlighting the need for modality-specific refinement to improve diagnostic precision. KEY POINTS: Question Do conceptually corresponding diagnostic categories in LI-RADS v2018 and KLCA-NCC v2022 demonstrate equivalent diagnostic performance for HCC? Findings Both systems demonstrated effective probability-based stratification, but corresponding categories were not equivalent, and the performance was modality-specific. Clinical relevance Corresponding categories are not interchangeable between the two systems. The heterogeneity within "probable HCC" and modality-specific performance differences suggest potential benefits from subcategorization and refinement of CT-specific criteria.

Indexed as

CarcinomaGadolinium DTPAHepatocellularPredictive value of testsSensitivity and specificity

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.