“…The goal of the LI-RADS diagnostic algorithm is to provide 100% specificity for the diagnosis of HCC because the definitive diagnosis of HCC is typically based on imaging, while histologic confirmation is not needed prior to treatment, which is different from most other malignancies [ 9 ]. Therefore, the application rules of LI-RADS prevent the adjustment of the LR-4 lesion to the LR-5 category, and few LR-5 lesions could reach downgrade (from LR-5 to LR-4) [ 8 , 24 ], which causes the AFs of LR-5 lesions to be overlooked. Therefore, we tried to ignore the impact of LR-5 AFs on the results and only included AFs of LR-3 and LR-4 categories in different category groups for calculation and compared them with those screened based on all lesions.…”
Section: Discussionmentioning
confidence: 99%
“…TP hypointensity alone improved the classification of 2 lesions. In some previous studies, some larger lesions have a mosaic structure due to intralesional fatty components, necrosis, or hemorrhage at histopathology [ 8 , 24 , 29 ]. Similarly, the lesion contains lipids to change the degree and method of the arterial stage of the lesion, which also makes the lesion classify into the LR-3 or LR-4 categories due to the lack of nonrim APHE [ 9 , 24 ], which is similar to the results of Christian B. van der Pol’s study for filtering features by machine learning [ 15 ].…”
Section: Discussionmentioning
confidence: 99%
“…In some previous studies, some larger lesions have a mosaic structure due to intralesional fatty components, necrosis, or hemorrhage at histopathology [ 8 , 24 , 29 ]. Similarly, the lesion contains lipids to change the degree and method of the arterial stage of the lesion, which also makes the lesion classify into the LR-3 or LR-4 categories due to the lack of nonrim APHE [ 9 , 24 ], which is similar to the results of Christian B. van der Pol’s study for filtering features by machine learning [ 15 ]. In this study, when AF-HCC and AF-LR were used to adjust the categories of LR-3/LR-4 lesions, the consistency between the two methods was good, and both the sensitivity and specificity for AF-HCC is higher than that for AF-LR, which makes a significant difference.…”
Objective
To determine the high-efficiency ancillary features (AFs) screened from LR-3/4 lesions and the HCC/non-HCC group and the diagnostic performance of LR3/4 observations.
Materials and methods
We retrospectively analyzed a total of 460 patients (with 473 nodules) classified into LR-3-LR-5 categories, including 311 cases of hepatocellular carcinoma (HCC), 6 cases of non-HCC malignant tumors, and 156 cases of benign lesions. Two faculty abdominal radiologists with experience in hepatic imaging reviewed and recorded the major features (MFs) and AFs of the Liver Imaging Reporting and Data System (LI-RADS). The frequency of the features and diagnostic performance were calculated with a logistic regression model. After applying the above AFs to LR-3/LR-4 observations, the sensitivity and specificity for HCC were compared.
Results
The average age of all patients was 54.24 ± 11.32 years, and the biochemical indicators ALT (P = 0.044), TBIL (P = 0.000), PLT (P = 0.004), AFP (P = 0.000) and Child‒Pugh class were significantly higher in the HCC group. MFs, mild-moderate T2 hyperintensity, restricted diffusion and AFs favoring HCC in addition to nodule-in-nodule appearance were common in the HCC group and LR-5 category. AFs screened from the HCC/non-HCC group (AF-HCC) were mild–moderate T2 hyperintensity, restricted diffusion, TP hypointensity, marked T2 hyperintensity and HBP isointensity (P = 0.005, < 0.001, = 0. 032, p < 0.001, = 0.013), and the AFs screened from LR-3/4 lesions (AF-LR) were restricted diffusion, mosaic architecture, fat in mass, marked T2 hyperintensity and HBP isointensity (P < 0.001, = 0.020, = 0.036, < 0.001, = 0.016), which were not exactly the same. After applying AF-HCC and AF-LR to LR-3 and LR-4 observations in HCC group and Non-HCC group, After the above grades changed, the diagnostic sensitivity for HCC were 84.96% using AF-HCC and 85.71% using AF-LR, the specificity were 89.26% using AF-HCC and 90.60% using AF-LR, which made a significant difference (P = 0.000). And the kappa value for the two methods of AF-HCC and AF–LR were 0.695, reaching a substantial agreement.
Conclusion
When adjusting for LR-3/LR-4 lesions, the screened AFs with high diagnostic ability can be used to optimize LI-RADS v2018; among them, AF-LR is recommended for better diagnostic capabilities.
“…The goal of the LI-RADS diagnostic algorithm is to provide 100% specificity for the diagnosis of HCC because the definitive diagnosis of HCC is typically based on imaging, while histologic confirmation is not needed prior to treatment, which is different from most other malignancies [ 9 ]. Therefore, the application rules of LI-RADS prevent the adjustment of the LR-4 lesion to the LR-5 category, and few LR-5 lesions could reach downgrade (from LR-5 to LR-4) [ 8 , 24 ], which causes the AFs of LR-5 lesions to be overlooked. Therefore, we tried to ignore the impact of LR-5 AFs on the results and only included AFs of LR-3 and LR-4 categories in different category groups for calculation and compared them with those screened based on all lesions.…”
Section: Discussionmentioning
confidence: 99%
“…TP hypointensity alone improved the classification of 2 lesions. In some previous studies, some larger lesions have a mosaic structure due to intralesional fatty components, necrosis, or hemorrhage at histopathology [ 8 , 24 , 29 ]. Similarly, the lesion contains lipids to change the degree and method of the arterial stage of the lesion, which also makes the lesion classify into the LR-3 or LR-4 categories due to the lack of nonrim APHE [ 9 , 24 ], which is similar to the results of Christian B. van der Pol’s study for filtering features by machine learning [ 15 ].…”
Section: Discussionmentioning
confidence: 99%
“…In some previous studies, some larger lesions have a mosaic structure due to intralesional fatty components, necrosis, or hemorrhage at histopathology [ 8 , 24 , 29 ]. Similarly, the lesion contains lipids to change the degree and method of the arterial stage of the lesion, which also makes the lesion classify into the LR-3 or LR-4 categories due to the lack of nonrim APHE [ 9 , 24 ], which is similar to the results of Christian B. van der Pol’s study for filtering features by machine learning [ 15 ]. In this study, when AF-HCC and AF-LR were used to adjust the categories of LR-3/LR-4 lesions, the consistency between the two methods was good, and both the sensitivity and specificity for AF-HCC is higher than that for AF-LR, which makes a significant difference.…”
Objective
To determine the high-efficiency ancillary features (AFs) screened from LR-3/4 lesions and the HCC/non-HCC group and the diagnostic performance of LR3/4 observations.
Materials and methods
We retrospectively analyzed a total of 460 patients (with 473 nodules) classified into LR-3-LR-5 categories, including 311 cases of hepatocellular carcinoma (HCC), 6 cases of non-HCC malignant tumors, and 156 cases of benign lesions. Two faculty abdominal radiologists with experience in hepatic imaging reviewed and recorded the major features (MFs) and AFs of the Liver Imaging Reporting and Data System (LI-RADS). The frequency of the features and diagnostic performance were calculated with a logistic regression model. After applying the above AFs to LR-3/LR-4 observations, the sensitivity and specificity for HCC were compared.
Results
The average age of all patients was 54.24 ± 11.32 years, and the biochemical indicators ALT (P = 0.044), TBIL (P = 0.000), PLT (P = 0.004), AFP (P = 0.000) and Child‒Pugh class were significantly higher in the HCC group. MFs, mild-moderate T2 hyperintensity, restricted diffusion and AFs favoring HCC in addition to nodule-in-nodule appearance were common in the HCC group and LR-5 category. AFs screened from the HCC/non-HCC group (AF-HCC) were mild–moderate T2 hyperintensity, restricted diffusion, TP hypointensity, marked T2 hyperintensity and HBP isointensity (P = 0.005, < 0.001, = 0. 032, p < 0.001, = 0.013), and the AFs screened from LR-3/4 lesions (AF-LR) were restricted diffusion, mosaic architecture, fat in mass, marked T2 hyperintensity and HBP isointensity (P < 0.001, = 0.020, = 0.036, < 0.001, = 0.016), which were not exactly the same. After applying AF-HCC and AF-LR to LR-3 and LR-4 observations in HCC group and Non-HCC group, After the above grades changed, the diagnostic sensitivity for HCC were 84.96% using AF-HCC and 85.71% using AF-LR, the specificity were 89.26% using AF-HCC and 90.60% using AF-LR, which made a significant difference (P = 0.000). And the kappa value for the two methods of AF-HCC and AF–LR were 0.695, reaching a substantial agreement.
Conclusion
When adjusting for LR-3/LR-4 lesions, the screened AFs with high diagnostic ability can be used to optimize LI-RADS v2018; among them, AF-LR is recommended for better diagnostic capabilities.
“…8 ). The status of the patient (i.e., LI-RADS high risk of HCC or not) and the presence of other imaging ancillary features that favor the diagnosis of HCC, such as nonenhancing capsule, mosaic architecture, nodule-in-nodule architecture, intralesional fat, intralesional hemorrhage may guide the radiologists towards a diagnosis of HCC [ 2 , 45 , 51 ]. Fig.…”
Rim arterial phase hyperenhancement is an imaging feature commonly encountered on contrast-enhanced CT and MRI in focal liver lesions. Rim arterial phase hyperenhancement is a subtype of arterial phase hyperenhancement mainly present at the periphery of lesions on the arterial phase. It is caused by a relative arterialization of the periphery compared with the center of the lesion and needs to be differentiated from other patterns of peripheral enhancement, including the peripheral discontinuous nodular enhancement and the corona enhancement. Rim arterial phase hyperenhancement may be a typical or an atypical imaging presentation of many benign and malignant focal liver lesions, challenging the radiologists during imaging interpretation. Benign focal liver lesions that may show rim arterial phase hyperenhancement may have a vascular, infectious, or inflammatory origin. Malignant focal liver lesions displaying rim arterial phase hyperenhancement may have a vascular, hepatocellular, biliary, lymphoid, or secondary origin. The differences in imaging characteristics on contrast-enhanced CT may be subtle, and a multiparametric approach on MRI may be helpful to narrow the list of differentials. This article aims to review the broad spectrum of focal liver lesions that may show rim arterial phase hyperenhancement, using an approach based on the benign and malignant nature of lesions and their histologic origin.
Critical relevance statement
Rim arterial phase hyperenhancement may be an imaging feature encountered in benign and malignant focal liver lesions and the diagnostic algorithm approach provided in this educational review may guide toward the final diagnosis.
Key Points
Several focal liver lesions may demonstrate rim arterial phase hyperenhancement.
Rim arterial phase hyperenhancement may occur in vascular, inflammatory, and neoplastic lesions.
Rim arterial phase hyperenhancement may challenge radiologists during image interpretation.
Graphical Abstract
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