Application of Liver Imaging Reporting and Data System version 2018 ancillary features to upgrade from LR-4 to LR-5 on gadoxetic acid–enhanced MRI

Lee, Sunyoung; Kim, Seung-Seob; Bae, Heejin; Shin, Jaeseung; Yoon, Ja Kyung; Kim, Do Young

doi:10.1007/s00330-020-07146-4

Cited by 21 publications

(21 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…21,24 In this context, an increasing number of studies have attempted to elevate the sensitivity of LI- RADS. 9,11,13,14,[25][26][27] In these studies, improved diagnostic performances were achieved by regrouping the current major feature system 13 or utilizing certain ancillary features as additional major features. 9,11,14,[25][26][27] However, despite relatively strong evidence supporting the use of the existing major features individually, 5,15,16 the selection of which feature combinations to examine has typically been experience-based.…”

Section: Discussionmentioning

confidence: 99%

“…9,11,13,14,[25][26][27] In these studies, improved diagnostic performances were achieved by regrouping the current major feature system 13 or utilizing certain ancillary features as additional major features. 9,11,14,[25][26][27] However, despite relatively strong evidence supporting the use of the existing major features individually, 5,15,16 the selection of which feature combinations to examine has typically been experience-based. Our study allowed the data to entirely dictate the most appropriate feature combinations.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, the applications of these ancillary features are optional in LI-RADS and highly variable in clinical practices. 16,20 However, considering their promising diagnostic values, 9,11,14,[25][26][27] future researches are encouraged to further refine the roles of ancillary features in LI-RADS.…”

Section: Discussionmentioning

confidence: 99%

“…[7][8][9] As a result, investigators have explored possible solutions to improve the simplicity and diagnostic sensitivity of LI-RADS using various MR techniques and contrast agents. [9][10][11][12][13][14] However, many of these proposed modifications were based on investigator experiences, and limited data have been reported concerning the performances of the many available combinations of imaging features. Notably, there are strong data supporting the LI-RADS major features as the main determinants of HCC diagnosis, as reflected in the LI-RADS diagnostic table.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Data‐Driven Modification of the LI‐RADS Major Feature System on Gadoxetate Disodium‐Enhanced MRI: Toward Better Sensitivity and Simplicity

Jiang

Song

Qin

et al. 2021

Magnetic Resonance Imaging

View full text Add to dashboard Cite

Background: The Liver Imaging Reporting and Data System (LI-RADS) is widely accepted as a reliable diagnostic scheme for hepatocellular carcinoma (HCC) in at-risk patients. However, its application is hampered by substantial complexity and suboptimal diagnostic sensitivity. Purpose: To propose data-driven modifications to the LI-RADS version 2018 (v2018) major feature system (rLI-RADS) on gadoxetate disodium (EOB)-enhanced magnetic resonance imaging (MRI) to improve sensitivity and simplicity while maintaining high positive predictive value (PPV) for detecting HCC. Study Type: Retrospective. Population: Two hundred and twenty-four consecutive at-risk patients (training dataset: 169, independent testing dataset: 55) with 742 LR-3 to LR-5 liver observations (HCC: N = 498 [67%]) were analyzed from a prospective observational registry collected between July 2015 and September 2018. Field Strength/Sequence: 3.0 T/T2-weighted fast spin-echo, diffusion-weighted spin-echo based echo-planar and threedimensional (3D) T1-weighted gradient echo sequences. Assessment: All images were evaluated by three independent abdominal radiologists who were blinded to all clinical, pathological, and follow-up information. Composite reference standards of either histopathology or imaging follow-up were used. Statistical Tests: In the training dataset, LI-RADS v2018 major features were used to develop rLI-RADS based on their associated PPV for HCC. In an independent testing set, diagnostic performances of LI-RADS v2018 and rLI-RADS were computed using a generalized estimating equation model and compared with McNemar's test. A P value <0.05 was considered statistically significant. Results: The median (interquartile range) size of liver observations was 13 mm (7-27 mm). The diagnostic table for rLI-RADS encompassed 9 cells, as opposed to 16 cells for LI-RADS v2018. In the testing set, compared to LI-RADS v2018, rLI-RADS category 5 demonstrated a significantly superior sensitivity (76% vs. 61%) while maintaining comparably high PPV (92.5% vs. 94.1%, P = 0.126). Data Conclusion: Compared with LI-RADS v2018, rLI-RADS demonstrated improved simplicity and significantly superior diagnostic sensitivity for HCC in at-risk patients. Level of Evidence: 3 Technical Efficacy Stage: 2

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Data‐Driven Modification of the LI‐RADS Major Feature System on Gadoxetate Disodium‐Enhanced MRI: Toward Better Sensitivity and Simplicity

Jiang

Song

Qin

et al. 2021

Magnetic Resonance Imaging

View full text Add to dashboard Cite

show abstract

“…Previous reports showed that auxiliary features could contribute to HCC diagnosis for an uncertain situation in HRP [10,11]. Alpha fetal protein (AFP) as a well-known clinical factor is closely associated with the development of HCC with high speci city.…”

Section: Introductionmentioning

confidence: 99%

Non-invasive diagnosis strategy of hepatocellular carcinoma in low-risk population

Xie

Peng

Zou

et al. 2022

Preprint

View full text Add to dashboard Cite

Aims With the increase prevalence of hepatocellular carcinoma (HCC) in the low-risk population (LRP), establishing a non-invasive diagnostic strategy becomes more and more urgent to spare unnecessary biopsies in this population. The purposes of this study were to find the imaging features of HCC and establish a proper non-invasive method to diagnosis HCC in LRP. Methods A total of 681 patients in LRP (defined by the population without cirrhosis, chronic HBV infection or HCC history) were collected from 2 institutions. The images of computed tomography (CT) and magnetic resonance imaging (MRI) were analyzed. We divided the patients into training cohort (n = 324) and internal validating cohort (n = 139) by admission time in the first institution. The second institution were viewed as the external validation (n = 218). A multivariate logistic regression model incorporating imaging features and previously confirmed independent risk predictors was further developed. C-statistics was used to evaluate the diagnostic performance. Results Except for the typical hallmark features of HCC (non-rim enhancement, washout and capsule enhancement), tumor necrosis or severe ischemia (TNSI) and two clinical characteristics (gender and alpha fetoprotein) were also independently associated with HCC diagnosis (all P < 0.01). A clinical-imaging model (using 3 typical hallmark features, TNSI, gender and AFP) were built to diagnose HCC and achieved good diagnostic performance (area under curve values were 0.954 in training cohort, 0.931 in internal validation cohort and 0.902 in external cohort). Conclusions The clinical-imaging model that this study developed achieved a satisfied non-invasive diagnostic performance for HCC in LRP.

show abstract

Modifying LI‐RADS on Gadoxetate Disodium‐Enhanced MRI: A Secondary Analysis of a Prospective Observational Study

Jiang

Song

Qin

et al. 2022

Magnetic Resonance Imaging

View full text Add to dashboard Cite

BackgroundThe Liver Imaging Reporting and Data System (LI‐RADS) is widely used for diagnosing hepatocellular carcinoma (HCC), however, with unsatisfactory sensitivity, complex ancillary features, and inadequate integration with gadoxetate disodium (EOB)‐enhanced MRI.PurposeTo modify LI‐RADS (mLI‐RADS) on EOB‐MRI.Study TypeSecondary analysis of a prospective observational study.PopulationBetween July 2015 and September 2018, 224 consecutive high‐risk patients (median age, 51 years; range, 26–83; 180 men; training/testing sets: 169/55 patients) with 742 (median size, 13 mm; interquartile range, 7–27; 498 HCCs) LR‐3/4/5 observations.Field Strength/Sequence3.0 T T2‐weighted fast spin‐echo, diffusion‐weighted spin‐echo based echo‐planar, and 3D T1‐weighted gradient echo sequences.AssessmentThree radiologists (with 5, 5, and 10 years of experience in liver MR imaging, respectively) blinded to the reference standard (histopathology or imaging follow‐up) reviewed all MR images independently. In the training set, the optimal LI‐RADS version 2018 (v2018) features selected by Random Forest analysis were used to develop mLI‐RADS via decision tree analysis.Statistical TestsIn an independent testing set, diagnostic performances of mLI‐RADS, LI‐RADS v2018, and the Korean Liver Cancer Association (KLCA) guidelines were computed using a generalized estimating equation model and compared with McNemar's test. A two‐tailed P < 0.05 was statistically significant.ResultsFive features (nonperipheral “washout,” restricted diffusion, nonrim arterial phase hyperenhancement [APHE], mild–moderate T2 hyperintensity, and transitional phase hypointensity) constituted mLI‐RADS, and mLR‐5 was nonperipheral washout coupled with either nonrim APHE or restricted diffusion. In the testing set, mLI‐RADS was significantly more sensitive (72%) and accurate (80%) than LI‐RADS v2018 (sensitivity, 61%; accuracy 74%; both P < 0.001) and the KLCA guidelines (sensitivity, 64%; accuracy 74%; both P < 0.001), without sacrificing positive predictive value (mLI‐RADS, 94%; LI‐RADS v2018, 94%; KLCA guidelines, 92%).Data ConclusionIn high‐risk patients, the EOB‐MRI‐based mLI‐RADS was simpler and more sensitive for HCC than LI‐RADS v2018 while maintaining high positive predictive value.Level of Evidence2Technical EfficacyStage 2

show abstract

Application of Liver Imaging Reporting and Data System version 2018 ancillary features to upgrade from LR-4 to LR-5 on gadoxetic acid–enhanced MRI

Cited by 21 publications

References 20 publications

Data‐Driven Modification of the LI‐RADS Major Feature System on Gadoxetate Disodium‐Enhanced MRI: Toward Better Sensitivity and Simplicity

Data‐Driven Modification of the LI‐RADS Major Feature System on Gadoxetate Disodium‐Enhanced MRI: Toward Better Sensitivity and Simplicity

Non-invasive diagnosis strategy of hepatocellular carcinoma in low-risk population

Modifying LI‐RADS on Gadoxetate Disodium‐Enhanced MRI: A Secondary Analysis of a Prospective Observational Study

Contact Info

Product

Resources

About