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Simplified liver imaging reporting and data system for the diagnosis of hepatocellular carcinoma on gadoxetic acid-enhanced magnetic resonance imaging.
Lyu, Rong; Hu, Wei-Juan; Wang, Di; Wang, Jiao; Ye, Yu-Bing; Jia, Ke-Feng.
  • Lyu R; Department of Radiology, Tianjin Third Central Hospital, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin 300170, China.
  • Hu WJ; Department of Radiology, Tianjin Third Central Hospital, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin 300170, China.
  • Wang D; Department of Radiology, Tianjin Third Central Hospital, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin 300170, China.
  • Wang J; Department of Radiology, Tianjin Third Central Hospital, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin 300170, China.
  • Ye YB; Department of Radiology, Tianjin Third Central Hospital, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin 300170, China.
  • Jia KF; Department of Radiology, Tianjin Third Central Hospital, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin 300170, China. wangzhiwangzhi2000@126.com.
World J Gastrointest Oncol ; 16(6): 2439-2448, 2024 Jun 15.
Article en En | MEDLINE | ID: mdl-38994131
ABSTRACT

BACKGROUND:

The liver imaging reporting and data system (LI-RADS) diagnostic table has 15 cells and is too complex. The diagnostic performance of LI-RADS for hepatocellular carcinoma (HCC) is not satisfactory on gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI).

AIM:

To evaluate the ability of the simplified LI-RADS (sLI-RADS) to diagnose HCC on EOB-MRI.

METHODS:

A total of 331 patients with 356 hepatic observations were retrospectively analysed. The diagnostic performance of sLI-RADS A-D using a single threshold was evaluated and compared with LI-RADS v2018 to determine the optimal sLI-RADS. The algorithms of sLI-RADS A-D are as follows The single threshold for sLI-RADS A and B was 10 mm, that is, classified observations ≥ 10mm using an algorithm of 10-19 mm observations (sLI-RADS A) and ≥ 20 mm observations (sLI-RADS B) in the diagnosis table of LI-RADS v2018, respectively, while the classification algorithm remained unchanged for observations < 10 mm; the single threshold for sLI-RADS C and D was 20 mm, that is, for < 20 mm observations, the algorithms for < 10 mm observations (sLI-RADS C)and 10-19 mm observations (sLI-RADS D) were used, respectively, while the algorithm remained unchanged for observations ≥ 20 mm. With hepatobiliary phase (HBP) hypointensity as a major feature (MF), the final sLI-RADS (F-sLI-RADS) was formed according to the optimal sLI-RADS, and its diagnostic performance was evaluated. The times needed to classify the observations according to F-sLI-RADS and LI-RADS v2018 were compared.

RESULTS:

The optimal sLI-RADS was sLI-RADS D (with a single threshold of 20 mm), because its sensitivity was greater than that of LI-RADS v2018 (89.8% vs 87.0%, P = 0.031), and its specificity was not lower (89.4% vs 90.1%, P > 0.999). With HBP hypointensity as an MF, the sensitivity of F-sLI-RADS was greater than that of LI-RADS v2018 (93.0% vs 87.0%, P < 0.001) and sLI-RADS D (93.0% vs 89.8%, P = 0.016), without a lower specificity (86.5% vs 90.1%, P = 0.062; 86.5% vs 89.4%, P = 0.125). Compared with that of LI-RADS v2018, the time to classify lesions according to F-sLI-RADS was shorter (51 ± 21 s vs 73 ± 24 s, P < 0.001).

CONCLUSION:

The use of sLI-RADS with HBP hypointensity as an MF may improve the sensitivity of HCC diagnosis and reduce lesion classification time.
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