Effect of threshold growth as a major feature on LI-RADS categorization

Threshold growth has a limited role in differentiating hepatocellular carcinoma from other focal hepatic lesions

BACKGROUND AND OBJECTIVE: The role of threshold growth, as one of the major features (MFs) of hepatocellular carcinoma (HCC) in the Liver Imaging Reporting and Data System (LI-RADS) is inconsistent. This study evaluated the LI-RADS diagnostic performance for HCC when threshold growth was removed or replaced by independently significant ancillary features (AFs). MATERIALS AND METHODS: This retrospective institutional review board-approved study included patients with a high HCC risk who underwent gadoxetic acid-enhanced MRIs. The MRI findings were consistent with pathologically proven focal hepatic observations. The pathological results were used as the gold standard reference. The sizes of the lesions with and without threshold growth were compared. Univariate and multivariate logistic regression analyses were used to confirm the independently significant AFs of HCC. In addition to the classification criteria of LI-RADS version 2018 (LI-RADS v2018), the lesions were also reclassified according to the following two schemes: scheme A, using all MFs except threshold growth, with threshold growth feature treated as an AF favouring malignancy; and scheme B, replacing the threshold growth feature with independently significant AFs and treated them as new MFs. The diagnostic performance of the above two LI-RADS schemes for HCC was calculated and compared with that of LI-RADS v2018. RESULTS: A total of 379 patients and 426 observations were included. Threshold growth was not an independent significant MF for HCC diagnosis [odds ratio (OR), 1.0; 95% confidence interval (CI), 0.6-1.8; p = 0.927]. For all three groups of observations (HCCs, non-HCC malignancies, and benign lesions), the mean size with threshold growth was smaller than that without threshold growth (all p < 0.05). The nodule-in-nodule feature was an independent significant AF (OR, 9.8; 95% CI, 1.2-79.3; p = 0.032) and was used to replace threshold growth as a new MF in scheme B. The sensitivities of schemes A and B were 74.0% and 75.6%, respectively. The specificities of schemes A and B were the same (88.6%). None of the diagnostic performance metrics for HCC (sensitivity, specificity, accuracy) of either scheme A or B was significantly different from those of LI-RADS v2018 (all p > 0.05). CONCLUSION: Threshold growth is not an independently significant MF for HCC diagnosis. The diagnostic performance of LI-RADS for HCC is not affected regardless of whether threshold growth is removed from the list of MFs or replaced with an independently significant and more HCC-specific AF, which is the nodule-in-nodule feature.

Prevalence of different LI-RADS v2018 categories in high-risk patients undergoing CT- or MRI-based screening for hepatocellular carcinoma

PURPOSE

To estimate the prevalence of Liver Imaging Reporting and Data System (LI-RADS, LR) v2018 categories reported on CT or MRI performed for hepatocellular carcinoma (HCC) screening.

MATERIALS AND METHODS

This retrospective study included all reports for CT and MRI exams performed for HCC screening patients between 8/2018 and 4/2020. Patients with ultrasound, CT, or MRI of the abdomen within two years of the index exam were excluded. From each radiology report, we extracted number of reported liver observations, and LI-RADS v2018 category for each observation.

RESULTS

There were 329 patients (170 [52%] male, mean age 59 years [SD 12]), of whom 177 (54%) had MRI with gadoxetate, 72 (22%) had MRI with extracellular contrast, 7 (2%) had MRI with unspecified contrast, and 73 (22%) had CT. Of 329 patients, 199 (60%) had no reported observations; 130 patients had 166 reported observations: 114 (68.7%) LR-1, 8 (4.8%) LR-2, 21 (12.6%) LR-3, 6 (3.6%) LR-4, 13 (7.8%) LR-5, 3 (1.8%) LR-M, and 1 (0.6%) LR-TIV. Of 114 LR-1 observations, 78 (68%) were cysts, 17 (15%) were hemangiomas, 12 (11%) were vascular shunts, 3 (3%) were focal nodular hyperplasia, 2 (2%) were siderotic nodules, 1 (1%) was a lipoma, and 1 (1%) was biliary hamartoma. There were 23 observations with probably or definitely malignant categories (LR-4, LR-5, LR-M or LR- TIV), reported in 20/329 (6%) of patients.

CONCLUSION

In a cohort of at-risk patients undergoing contrast-enhanced CT/MRI for HCC screening, 60% of had no liver observations, and 6 % had probably or definitely malignant observations.

IMPLICATIONS FOR PATIENT CARE

The prevalence of LI-RADS v2018 categories on CT or MR exams used for HCC screening can help develop screening criteria and assess cost-effectiveness of surveillance strategies with CT and MRI.

Value of threshold growth as a major diagnostic feature of hepatocellular carcinoma in LI-RADS

BACKGROUND & AIMS

The Liver Reporting and Data System (LI-RADS) version 2018 simplified the definition of threshold growth to '≥50% size increase in a mass in ≤6 months'. However, the diagnostic value of threshold growth for hepatocellular carcinoma (HCC) remained unclear. We evaluated the value of threshold growth, as defined by LI-RADS v2018, in diagnosing HCCs.

METHODS

Patients who underwent preoperative gadoxetate disodium-enhanced MRI because of the presence of LI-RADS category 2, 3, or 4 rather than category 5 on prior CT/MRI between January 2017 and December 2020 were retrospectively evaluated. Pathologic or clinical diagnoses were used as reference standards. Imaging features were evaluated by three readers according to LI-RADS v2018. The frequency and diagnostic odds ratio of threshold growth were calculated. The diagnostic performance of LI-RADS category 5 was separately evaluated when threshold growth was and was not considered a major feature, and results were compared using generalized estimation equations. Subgroups of patients who underwent CT/MRI during the previous 3-6 months were analyzed.

RESULTS

Analysis of 340 observations in 243 patients found that the frequency of threshold growth was 18.8% and it gradually increased over time. Threshold growth was significantly associated with HCC (diagnostic odds ratio 5.2; 95% CI 2.1-12.7; p <0.001). Use of threshold growth as a major feature significantly increased sensitivity in both the overall (66.4% vs. 57.3%, p <0.001) and subgroup (73.4% vs. 58.2%, p <0.001) cohorts, but had no effect on specificity in either the overall (97.5% vs. 98.3%, p = 0.319) or subgroup (95.9% vs. 98.0%, p = 0.323) cohorts.

CONCLUSION

The revised threshold growth of LI-RADS v2018 was significantly associated with HCC. Use of threshold growth as a major diagnostic feature of HCC can improve the sensitivity of LI-RADS v2018.

IMPACT AND IMPLICATIONS

We found that the revised threshold growth in the Liver Imaging Reporting and Data System version 2018 (LI-RADS v2018) was a significant predictor of hepatocellular carcinoma (HCC). The use of threshold growth as a major imaging feature of HCC significantly increased the sensitivity of LI-RADS v2018, especially small HCCs (≤3.0 cm), compared with its non-use. Because these small HCCs are eligible for curative treatments, the additional detection of small HCCs is clinically meaningful.

What proportion of LI-RADS 5 observations reported in clinical practice do not meet LI-RADS 5 criteria?

OBJECTIVES

Liver Imaging Reporting and Data System (LI-RADS, LR) category 5 (definite hepatocellular carcinoma [HCC]) is assigned based on combinations of major imaging features (MFs): size, arterial-phase hyperenhancement (APHE), washout (WO), enhancing capsule, and threshold growth. The criteria were simplified in v2018 compared to v2017. The goal of this study is to assess the proportion of LR-5 observations reported in clinical practice with LI-RADS v2017 or v2018 that did not meet LR-5 criteria based on reported MFs.

METHODS

All MR and CT reports using a standardized LI-RADS template between April 2017 and September 2020 were identified retrospectively. For each reported LR-5 observation, size, MFs, and LI-RADS version (v2017 or v2018) were extracted. Reported MFs were used to determine whether LR-5 criteria were met using the applied version of LI-RADS. The data was summarized descriptively.

RESULTS

Three hundred eight observations in 234 patients (67.6% male, mean age 66.2 years) were reported as LR-5, including 136 (44.2%) with v2017 and 172 (55.8%) with v2018. 8/136 (6%) v2017 LR-5 observations and 6/172 (3%) v2018 LR-5 observations did not meet LR-5 criteria. Of 8 incorrectly categorized v2017 observations, 3 (43%) lacked APHE, 1 (14%) was a 16-mm new observation with APHE only, and 4 (43%) were 10-19 mm with APHE and WO. Of the 6 incorrectly categorized v2018 observations, 5 (83%) lacked APHE and 1 (17%) was < 10 mm.

CONCLUSIONS

Depending on the LI-RADS version, 3-6% of LR-5 observations reported in clinical practice do not meet LR-5 criteria based on reported MFs. Key Points • Depending on the LI-RADS version, 3-6% of LR-5 observations in clinical practice do not meet LR-5 criteria based on reported major imaging features. • Assigning LR-5 category to observations without nonrim arterial-phase hyperenhancement was the most common error.

Hepatocarcinogenesis: Radiology-Pathology Correlation

In the background of chronic liver disease, hepatocellular carcinoma develops via a complex, multistep process called hepatocarcinogenesis. This article reviews the causes contributing to the process. Emphasis is made on the imaging manifestations of the pathologic changes seen at many stages of hepatocarcinogenesis, from regenerative nodules to dysplastic nodules and then to hepatocellular carcinoma.

Should Threshold Growth Be Considered a Major Feature in the Diagnosis of Hepatocellular Carcinoma Using LI-RADS?

OBJECTIVE

Based on the Liver Imaging Reporting and Data System version 2018 (LI-RADS, v2018), this study aimed to analyze LR-5 diagnostic performance for hepatocellular carcinoma (HCC) when threshold growth as a major feature is replaced by a more HCC-specific ancillary feature, as well as the frequency of threshold growth in HCC and non-HCC malignancies and its association with tumor size.

MATERIALS AND METHODS

This retrospective study included treatment-naive patients who underwent gadoxetate disodium-enhanced MRIs for focal hepatic lesions and surgery between January 2009 and December 2016. The frequency of major and ancillary features was evaluated for HCC and non-HCC malignancies, and the LR-category was assessed. Ancillary features that were significantly more prevalent in HCC were then used to either replace threshold growth or were added as additional major features, and the diagnostic performance of the readjusted LR category was compared to the LI-RADS v2018.

RESULTS

A total of 1013 observations were analyzed. Unlike arterial phase hyperenhancement, washout, or enhancing capsule which were more prevalent in HCCs than in non-HCC malignancies (521/616 vs. 18/58, 489/616 vs. 19/58, and 181/616 vs. 5/58, respectively; p < 0.001), threshold growth was more prevalent in non-HCC malignancies than in HCCs (11/23 vs. 17/119; p < 0.001). The mean size of non-HCC malignancies showing threshold growth was significantly smaller than that of non-HCC malignancies without threshold growth (22.2 mm vs. 42.9 mm, p = 0.040). Similar results were found for HCCs; however, the difference was not significant (26.8 mm vs. 33.1 mm, p = 0.184). Additionally, Fat-in-nodule was more frequent in HCCs than in non-HCC malignancies (99/616 vs. 2/58, p = 0.010). When threshold growth and fat-in-nodule were considered as ancillary and major features, respectively, LR-5 sensitivity (73.2% vs. 73.9%, p = 0.289) and specificity (98.2% vs. 98.5%, p > 0.999) were comparable to the LI-RADS v2018.

CONCLUSION

Threshold growth is not a significant diagnostic indicator of HCC and is more common in non-HCC malignancies. The diagnostic performance of LR-5 was comparable when threshold growth was recategorized as an ancillary feature and replaced by a more HCC-specific ancillary feature.

CT/MRI LI-RADS v2018 vs. CEUS LI-RADS v2017-Can Things Be Put Together?

Simple Summary

The LI-RADS system is nowadays the mainstream system used in classifying liver nodules in cirrhotic liver according to their risk of malignancy. Two main LI-RADS documents have been released—the CEUS LI-RADS v2017 document, and the CT/MRI LI-RADS v2018 document. In some circumstances, a nodule can be differently classified when using CEUS versus when using CT or MRI. In this paper, we also focus on the existing similitudes between the two documents but, essentially, on the differences between the two main documents and the complementarities between imaging techniques in characterizing liver nodules in cirrhotic livers. Awareness of the complementarity of imaging techniques may lead to an improvement in the characterization and classification of liver nodules and will reduce the number of liver biopsies. This paper proposes practical solutions in order to better classify and manage observations or nodules detected in cirrhotic livers.

Abstract

Different LI-RADS core documents were released for CEUS and for CT/MRI. Both documents rely on major and ancillary diagnostic criteria. The present paper offers an exhaustive comparison of the two documents focusing on the similarities, but especially on the differences, complementarity, and added value of imaging techniques in classifying liver nodules in cirrhotic livers. The major diagnostic criteria are defined, and the sensitivity and specificity of each major diagnostic criteria are presented according to the literature. The existing differences between techniques in assessing the major diagnostic features can be then exploited in order to ensure a better classification and a better clinical management of liver nodules in cirrhotic livers. Ancillary features depend on the imaging technique used, and their presence can upgrade or downgrade the LI-RADS score of an observation, but only as far as LI-RADS 4. MRI is the imaging technique that provides the greatest number of ancillary features, whereas CEUS has fewer ancillary features than other imaging techniques. In the final part of the manuscript, some recommendations are made by the authors in order to guidephysicians as to when adding another imaging technique can be helpful in managing liver nodules in cirrhotic livers.

Increasing the sensitivity of LI-RADS v2018 for diagnosis of small (10-19 mm) HCC on extracellular contrast-enhanced MRI

PURPOSE

To evaluate whether the LI-RADS v2018 LR-5 criteria can be modified to increase sensitivity without reducing specificity for diagnosing small (10-19 mm) HCC.

METHODS

167 consecutive high-risk patients with 174 small observations reported clinically on extracellular contrast-enhanced MRI from 2014 to 2018 were retrospectively studied. The best available reference standard was applied for each observation. Blinded to the reference standard, two radiologists scored LI-RADS imaging features retrospectively and assigned each observation a LI-RADS category using LI-RADS v2018 and each of four modified LI-RADS versions (mLI-RADS I to IV) with successively more expansive LR-5 criteria. Per-observation sensitivity and specificity of LR-5 for small HCC using each version were assessed. Each modified version was compared to v2018 (McNemar test).

RESULTS

The 174 observations included 135 HCC, 8 non-HCC malignancies, and 31 benign entities. Using LI-RADS v2018, LR-5 provided 70% (both readers) sensitivity and 95% (both readers) specificity for small HCC. Expanding the LR-5 criteria to include nonrim APHE plus at least one additional major feature (mLI-RADS I) or no APHE plus at least two additional major features (mLI-RADS II) significantly increased sensitivity (reader 1/reader 2: 75%/75% vs. 70%, p = 0.016/0.031; 78%/79% vs. 70%, p = 0.001/0.001) without significantly reducing specificity (reader 1/reader 2: 90%/92% vs. 95%, p = 0.500/1.000 for both). mLI-RADS III and IV further increased sensitivity (reader 1/reader 2: 80%/81% vs. 70%, p < 0.001/< 0.001; 94%/92% vs. 70, p < 0.001/< 0.001) but with trend-level (reader 1/reader 2: 85%/80% vs. 95%, p = 0.125/0.063) or significant (reader 1/reader 2: 64%/62% vs. 95%, p < 0.001/< 0.001) specificity reductions.

CONCLUSIONS

Expanding the v2018 LR-5 criteria to include nonrim APHE plus at least one additional major feature or no APHE plus at least two additional major features significantly increases sensitivity without significantly reducing specificity for small HCC. Confirmation is warranted in multi-center prospective studies.

LI-RADS ancillary features on contrast-enhanced ultrasonography

The Liver Imaging Reporting and Data System (LI-RADS) was created to standardize liver imaging in patients at high risk for hepatocellular carcinoma (HCC), and it uses a diagnostic algorithm to assign categories that reflect the relative probability of HCC, non-HCC malignancies, or benign focal liver lesions. In addition to major imaging features, ancillary features (AFs) are used by radiologists to refine the categorization of liver nodules. In the present document, we discuss and explain the application of AFs currently defined within the LI-RADS guidelines. We also explore possible additional AFs visible on contrast-enhanced ultrasonography (CEUS). Finally, we summarize the management of CEUS LI-RADS features, including the role of current and potential future AFs.

Comparison of the diagnostic performance of the 2017 and 2018 versions of LI-RADS for hepatocellular carcinoma on gadoxetic acid enhanced MRI

AIM

To compare the diagnostic performance of the 2017 (v2017) and 2018 versions (v2018) of the Liver Imaging-Reporting and Data System (LI-RADS) for hepatocellular carcinoma (HCC) using gadoxetic acid-enhanced magnetic resonance imaging (Gd-EOB-MRI) and to evaluate the effect in v2018.

MATERIALS AND METHODS

Treatment-naive patients at high-risk for HCC who underwent Gd-EOB-MRI were included. The LI-RADS categories were assigned according to v2017 and v2018. The diagnostic performances were compared between v2017 and v2018 according to the size and combination of imaging features.

RESULTS

A total of 117 patients with 137 observations were identified, including 89 HCCs; 76.2% (64/84) of observations with threshold growth were re-classified as subthreshold growth when using v2018 instead of v2017. The final categories changed in nine (14%) cases. For the combination of LR-5/LR-5V, there were no significant differences in sensitivity and specificity between the two versions (sensitivity, 64% versus 58.4%; specificity, 87.5% versus 85.4%; all p>0.05). For the combination of LR-4 and LR-5/5V, the diagnostic performance of v2018 was inferior to that of v2017 when considering only major features (accuracy, 86.1% versus 80.3%, respectively; p=0.013), particularly in observations measuring 10-20 mm, but was comparable after adding the ancillary features (accuracy, 86.9% versus 86.1%, respectively; p=1.00).

CONCLUSION

In LI-RADS v2018, although a considerable number of observations re-classified subthreshold growth, changes in the assigned categories were insignificant; overall diagnostic performance was comparable to that of v2017, but v2018 might emphasise the value of ancillary features in combination with major features for determining the probability of HCC.

Liver Imaging Reporting and Data System Version 2018: Impact on Categorization and Hepatocellular Carcinoma Staging

The purpose of this study was to assess the concordance in categorization and radiologic T staging using Liver Imaging Reporting and Data System (LI-RADS, LR) version 2017 (v2017), version 2018 (v2018), and the Organ Procurement and Transplantation Network (OPTN) criteria. All magnetic resonance imaging and computed tomography reports using a standardized LI-RADS macro between April 2015 and March 2018 were identified retrospectively. The major features (size, arterial phase hyperenhancement, washout, enhancing capsule, or threshold growth) were extracted from the report for each LR-3, LR-4, and LR-5 observation. Each observation was assigned a new category based on LI-RADS v2017, v2018, and OPTN criteria. Radiologic T stage was calculated based on the size and number of LR-5 or OPTN class 5 observations. Categories and T stages assigned by each system were compared descriptively. There were 398 patients (66.6% male; mean age, 63.4 years) with 641 observations (median size, 14 mm) who were included. A total of 73/182 (40.1%) observations categorized LR-4 by LI-RADS v2017 were up-categorized to LR-5 by LI-RADS v2018 due to changes in the LR-5 criteria, and 4/196 (2.0%) observations categorized as LR-5 by LI-RADS v2017 were down-categorized to LR-4 by LI-RADS v2018 due to changes in the threshold growth definition. The T stage was higher by LI-RADS v2018 than LI-RADS v2017 in 49/398 (12.3%) patients. Compared with the OPTN stage, 12/398 (3.0%) patients were upstaged by LI-RADS v2017 and 60/398 (15.1%) by LI-RADS v2018. Of 101 patients, 5 (5.0%) patients with T2 stage based on LI-RADS v2017 and 10/102 (9.8%) patients with T2 stage based on LI-RADS v2018 did not meet the T2 criteria based on the OPTN criteria. Of the 98 patients with a T2 stage based on OPTN criteria, 2 (2.0%) had a T stage ≥3 based on LI-RADS v2017 and 6 (6.1%) had a T stage ≥3 based on LI-RADS v2018.

Uncommon imaging evolutions of focal liver lesions in cirrhosis

OBJECTIVE

The purpose of this article is to describe and illustrate uncommon imaging evolutions of benign (i.e., cyst, hemangioma, focal nodular hyperplasia-like nodules, and hepatic angiomyolipoma) and malignant (i.e., HCC and non HCC malignancies) lesions in a cirrhotic liver. The content highlights relevant pathogenesis and imaging clues for proper differential diagnosis. Revision of prior imaging and knowledge of these scenarios may help the abdominal radiologist to reach a noninvasive diagnosis and direct the patient to the most appropriate clinical management.

CONCLUSION

Uncommon imaging evolutions of focal liver lesions in cirrhosis may represent a challenge for the abdominal radiologist, with atypical changes in size, and internal vascularization changes that may lead to misdiagnoses.

Pitfalls and problems to be solved in the diagnostic CT/MRI Liver Imaging Reporting and Data System (LI-RADS)

The 2017 Core of the computed tomography (CT)/magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS) provides clear definitions and concise explanations of the CT/MRI diagnostic algorithm. Nevertheless, there remain some practical and controversial issues that radiologists should be aware of when using the system. This article discusses pitfalls and problems which may be encountered when the version 2017 diagnostic algorithm is used for CT and MRI. The pitfalls include challenges in applying major features and assigning the LR-M category, as well as categorisation discrepancy between CT and MRI. The problems include imprecision of category codes, application of ancillary features, and regional practice variations in hepatocellular carcinoma (HCC) diagnosis. Potential solutions are presented along with these pitfalls and problems. KEY POINTS: • Although the diagnostic algorithm provides clear and detailed explanations, major feature evaluation can be subject to pitfalls and differentiation of HCC and non-HCC malignancy remains challenging. • Ancillary features are optional and equally weighted. However, features such as hepatobiliary phase hypointensity and restricted diffusion have greater impact on HCC diagnosis than other ancillary features and may merit greater emphasis or weighting. • LI-RADS was initially developed from a Western paradigm, which may limit its applicability in the East due to regional practice variations. In Eastern Asia, high sensitivity is prioritised over near-perfect specificity for HCC diagnosis in order to detect tumours at early stages.