Nonrim Arterial Phase Hyperenhancement Research Articles

Using GPT-4 for LI-RADS feature extraction and categorization with multilingual free-text reports.

The Liver Imaging Reporting and Data System (LI-RADS) offers a standardized approach for imaging hepatocellular carcinoma. However, the diverse styles and structures of radiology reports complicate automatic data extraction. Large language models hold the potential for structured data extraction from free-text reports. Our objective was to evaluate the performance of Generative Pre-trained Transformer (GPT)-4 in extracting LI-RADS features and categories from free-text liver magnetic resonance imaging (MRI) reports. Three radiologists generated 160 fictitious free-text liver MRI reports written in Korean and English, simulating real-world practice. Of these, 20 were used for prompt engineering, and 140 formed the internal test cohort. Seventy-two genuine reports, authored by 17 radiologists were collected and de-identified for the external test cohort. LI-RADS features were extracted using GPT-4, with a Python script calculating categories. Accuracies in each test cohort were compared. On the external test, the accuracy for the extraction of major LI-RADS features, which encompass size, nonrim arterial phase hyperenhancement, nonperipheral 'washout', enhancing 'capsule' and threshold growth, ranged from .92 to .99. For the rest of the LI-RADS features, the accuracy ranged from .86 to .97. For the LI-RADS category, the model showed an accuracy of .85 (95% CI: .76, .93). GPT-4 shows promise in extracting LI-RADS features, yet further refinement of its prompting strategy and advancements in its neural network architecture are crucial for reliable use in processing complex real-world MRI reports.

Comparison contrast-enhanced CT with contrast-enhanced US in diagnosing combined hepatocellular-cholangiocarcinoma: a propensity score-matched study

ObjectivesTo develop and compare noninvasive models for differentiating between combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and HCC based on serum tumor markers, contrast-enhanced ultrasound (CEUS), and computed tomography (CECT).MethodsFrom January 2010 to December 2021, patients with pathologically confirmed cHCC-CCA or HCC who underwent both preoperative CEUS and CECT were retrospectively enrolled. Propensity scores were calculated to match cHCC-CCA and HCC patients with a near-neighbor ratio of 1:2. Two predicted models, a CEUS-predominant (CEUS features plus tumor markers) and a CECT-predominant model (CECT features plus tumor markers), were constructed using logistic regression analyses. Model performance was evaluated by the area under the curve (AUC), sensitivity, specificity, and accuracy.ResultsA total of 135 patients (mean age, 51.3 years ± 10.9; 122 men) with 135 tumors (45 cHCC-CCA and 90 HCC) were included. By logistic regression analysis, unclear boundary in the intratumoral nonenhanced area, partial washout on CEUS, CA 19-9 > 100 U/mL, lack of cirrhosis, incomplete tumor capsule, and nonrim arterial phase hyperenhancement (APHE) volume < 50% on CECT were independent factors for a diagnosis of cHCC-CCA. The CECT-predominant model showed almost perfect sensitivity for cHCC-CCA, unlike the CEUS-predominant model (93.3% vs. 55.6%, p < 0.001). The CEUS-predominant model showed higher diagnostic specificity than the CECT-predominant model (80.0% vs. 63.3%; p = 0.020), especially in the ≤ 5 cm subgroup (92.0% vs. 70.0%; p = 0.013).ConclusionsThe CECT-predominant model provides higher diagnostic sensitivity than the CEUS-predominant model for CHCC-CCA. Combining CECT features with serum CA 19-9 > 100 U/mL shows excellent sensitivity.Critical relevance statementCombining lack of cirrhosis, incomplete tumor capsule, and nonrim arterial phase hyperenhancement (APHE) volume < 50% on CECT with serum CA 19-9 > 100 U/mL shows excellent sensitivity in differentiating cHCC-CCA from HCC.Key points1. Accurate differentiation between cHCC-CCA and HCC is essential for treatment decisions.2. The CECT-predominant model provides higher accuracy than the CEUS-predominant model for CHCC-CCA.3. Combining CECT features and CA 19-9 levels shows a sensitivity of 93.3% in diagnosing cHCC-CCA.Graphical

Contrast-Enhanced Ultrasound With Perfluorobutane for Hepatocellular Carcinoma Diagnosis: Comparison of Imaging Phases and Diagnostic Criteria.

BACKGROUND. Contrast-enhanced ultrasound (CEUS) with perfluorobutane has used varying protocols and diagnostic criteria for hepatocellular carcinoma (HCC). OBJECTIVE. The purpose of this article was to assess diagnostic performance for HCC of CEUS with perfluorobutane in high-risk patients using various criteria. METHODS. This retrospective post hoc study evaluating individual patient data from three earlier prospective studies from one hospital included 204 patients (136 men, 68 women; mean age, 63 ± 11 [SD] years) at high risk of HCC with 213 liver observations. Patients underwent CEUS using perfluorobutane from March 2019 to June 2022. Three radiologists (the examination's operator and two subsequent reviewers) independently interpreted examinations, assessing arterial, portal venous (arterial phase completion through 2 minutes), transitional (2-5 minutes after injection), and Kupffer (≥ 10 minutes after injection) phase findings. Six criteria for HCC were tested: 1, any arterial phase hyperenhancement (APHE) with Kupffer phase hypoenhancement; 2, nonrim APHE with Kupffer phase hypoenhancement; 3, nonrim APHE with portal venous washout; 4, nonrim APHE with portal venous washout and/or Kupffer phase hypoenhancement; 5, nonrim APHE with portal venous and/or transitional washout; 6, nonrim APHE with any of portal venous washout, transitional washout, or Kupffer phase hypoenhancement. Depending on the criteria, observations were instead deemed to be a non-HCC malignancy if showing rim APHE, early washout (at < 1 minute), or marked washout (at 2 minutes). Reference was pathology for malignant observations and pathology or imaging follow-up for benign observations. Diagnostic performance was assessed, pooling readers' data. RESULTS. Criterion 1 (no recognized features of non-HCC malignancy) had highest sensitivity (86.9%) but lowest specificity (43.2%) for HCC. Compared with nonrim APHE and portal venous washout (criterion 3), the addition of Kupffer phase hypoenhancement (criterion 4), transitional washout (criterion 5), or either feature (criterion 6) significantly increased sensitivity (34.4% vs 62.6-64.2%) and accuracy (61.8% vs 75.1-76.5%), but significantly decreased specificity (98.5% vs 91.9-94.1%). Criteria 2, 4, 5, and 6 (all incorporating transitional washout and/or Kupffer phase hypoenhancement) showed no significant differences in sensitivity (62.6-64.2%), specificity (91.9-94.1%), or accuracy (75.1-76.5%). CONCLUSION. Recognition of features of non-HCC malignancy improved specificity for HCC. Incorporation of the findings of transitional washout and/or Kupffer phase hypoenhancement improved sensitivity and accuracy, albeit lowered specificity, versus arterial and portal venous findings alone, without further performance variation among criteria incorporating those two findings. CLINICAL IMPACT. Kupffer phase acquisition may be optional for observations classified as HCC or non-HCC malignancy by arterial, portal venous, and transitional phases.

Long-term evolution of LR-2, LR-3 and LR-4 observations in HBV-related cirrhosis based on LI-RADS v2018 using gadoxetic acid-enhanced MRI.

To investigate the long-term evolution of LR-2, LR-3 and LR-4 observations in patients with hepatitis B virus (HBV)-related cirrhosis based on LI-RADS v2018 and identify predictors of progression to a malignant category on serial gadoxetic acid-enhanced magnetic resonance imaging (Gd-EOB-MRI). This retrospective study included 179 cirrhosis patients with untreated indeterminate observations who underwent Gd-EOB-MRI exams at baseline and during the follow-up period between June 2016 and December 2021. Two radiologists independently assessed the major features, ancillary features, and LI-RADS category of each observation at baseline and follow-up. In cases of disagreement, a third radiologist was consulted for consensus. Cumulative incidences for progression to a malignant category (LR-5 or LR-M) and to LR-4 or higher were analyzed for each index category using Kaplan‒Meier methods and compared using log-rank tests. The risk factors for malignant progression were evaluated using a Cox proportional hazard model. A total of 213 observations, including 74 (34.7%) LR-2, 95 (44.6%) LR-3, and 44 (20.7%) LR-4, were evaluated. The overall cumulative incidence of progression to a malignant category was significantly higher for LR-4 observations than for LR-3 or LR-2 observations (each P < 0.001), and significantly higher for LR-3 observations than for LR-2 observations (P < 0.001); at 3-, 6-, and 12-month follow-ups, the cumulative incidence of progression to a malignant category was 11.4%, 29.5%, and 39.3% for LR-4 observations, 0.0%, 8.5%, and 19.6% for LR-3 observations, and 0.0%, 0.0%, and 0.0% for LR-2 observations, respectively. The cumulative incidence of progression to LR-4 or higher was higher for LR-3 observations than for LR-2 observations (P < 0.001); at 3-, 6-, and 12-month follow-ups, the cumulative incidence of progression to LR-4 or higher was 0.0%, 8.5%, and 24.6% for LR-3 observations, and 0.0%, 0.0%, and 0.0% for LR-2 observations, respectively. In multivariable analysis, nonrim arterial phase hyperenhancement (APHE) [hazard ratio (HR) = 2.13, 95% CI 1.04-4.36; P = 0.038], threshold growth (HR = 6.50, 95% CI 2.88-14.65; P <0.001), and HBP hypointensity (HR = 16.83, 95% CI 3.97-71.34; P <0.001) were significant independent predictors of malignant progression. The higher LI-RADS v2018 categories had an increasing risk of progression to a malignant category during long-term evolution. Nonrim APHE, threshold growth, and HBP hypointensity were the imaging features that were significantly predictive of malignant progression.

Added value of CE-CT radiomics to predict high Ki-67 expression in hepatocellular carcinoma

BackgroundThis study aimed to develop a computed tomography (CT) model to predict Ki-67 expression in hepatocellular carcinoma (HCC) and to examine the added value of radiomics to clinico-radiological features.MethodsA total of 208 patients (training set, n = 120; internal test set, n = 51; external validation set, n = 37) with pathologically confirmed HCC who underwent contrast-enhanced CT (CE-CT) within 1 month before surgery were retrospectively included from January 2014 to September 2021. Radiomics features were extracted and selected from three phases of CE-CT images, least absolute shrinkage and selection operator regression (LASSO) was used to select features, and the rad-score was calculated. CE-CT imaging and clinical features were selected using univariate and multivariate analyses, respectively. Three prediction models, including clinic-radiologic (CR) model, rad-score (R) model, and clinic-radiologic-radiomic (CRR) model, were developed and validated using logistic regression analysis. The performance of different models for predicting Ki-67 expression was evaluated using the area under the receiver operating characteristic curve (AUROC) and decision curve analysis (DCA).ResultsHCCs with high Ki-67 expression were more likely to have high serum α-fetoprotein levels (P = 0.041, odds ratio [OR] 2.54, 95% confidence interval [CI]: 1.04–6.21), non-rim arterial phase hyperenhancement (P = 0.001, OR 15.13, 95% CI 2.87–79.76), portal vein tumor thrombus (P = 0.035, OR 3.19, 95% CI: 1.08–9.37), and two-trait predictor of venous invasion (P = 0.026, OR 14.04, 95% CI: 1.39–144.32). The CR model achieved relatively good and stable performance compared with the R model (AUC, 0.805 [95% CI: 0.683–0.926] vs. 0.678 [95% CI: 0.536–0.839], P = 0.211; and 0.805 [95% CI: 0.657–0.953] vs. 0.667 [95% CI: 0.495–0.839], P = 0.135) in the internal and external validation sets. After combining the CR model with the R model, the AUC of the CRR model increased to 0.903 (95% CI: 0.849–0.956) in the training set, which was significantly higher than that of the CR model (P = 0.0148). However, no significant differences were found between the CRR and CR models in the internal and external validation sets (P = 0.264 and P = 0.084, respectively).ConclusionsPreoperative models based on clinical and CE-CT imaging features can be used to predict HCC with high Ki-67 expression accurately. However, radiomics cannot provide added value.

Performance of current versus modified CEUS LI-RADS in the diagnosis of non-hepatocellular carcinoma malignancies.

The high proportion of HCC in CEUS LR-M decreases the sensitivity of LR-5 for the diagnosis of HCC. However, when modifying LR-M criteria to further improve the sensitivity of LR-5, it is also important not to compromise the diagnostic performance (especially sensitivity) of LR-M for non-hepatocellular carcinoma malignancies (non-HCCMs). The purpose of this study was to evaluate the diagnostic performance of CEUS LI-RADS (2017 version) for non-HCCMs and to explore the impact of modified CEUS LI-RADS on the diagnostic performance of LR-M. In this retrospective study, patients with pathologically confirmed non-HCCMs were evaluated. Two radiologists independently interpreted the major CEUS features and categorized the liver lesions. New LR-M criteria were applied: early washout (< 45 s) or marked washout (< 5 min). The sensitivity values of the current and modified CEUS LR-M were assessed and then compared using a paired χ2 test. Cohen's κ was used to compare the inter-reader agreement of the LI-RADS categories. A total of 131 non-HCCMs were ultimately selected, including 71 intrahepatic cholangiocarcinomas, 26 combined hepatocellular cholangiocarcinomas, 29 metastases, and 5 other non-HCCMs. The numbers of LR-M, LR-5, LR-4, and LR-3 in liver lesions were 111, 18, 1, and 1, respectively. The inter-reader agreement of the LI-RADS categories for non-HCCMs was 0.59. The sensitivity of the current CEUS LR-M in diagnosing non-HCCMs was 84.7%. By adjusting the early washout time to < 45 s, the sensitivity of LR-M was 80.9%. By adjusting the marked washout time within 5 min, the sensitivity of LR-M was 72.5%. CEUS LR-M has high sensitivity in diagnosing non-HCCMs. For LR-M nodules with nonrim arterial phase hyperenhancement and early washout, advancing the time of early washout to < 45 s has a minimal impact on the sensitivity of LR-M in diagnosing non-HCCMs compared to the condition of increasing the marked washout within 5 min.

Diagnosis of hepatocellular carcinoma using Sonazoid: a comprehensive review.

Sonazoid contrast-enhanced ultrasonography (CEUS) is a promising technique for the detection and diagnosis of focal liver lesions, particularly hepatocellular carcinoma (HCC). Recently, a collaborative effort between the Korean Society of Radiology and Korean Society of Abdominal Radiology resulted in the publication of guidelines for diagnosing HCC using Sonazoid CEUS. These guidelines propose specific criteria for identifying HCC based on the imaging characteristics observed during Sonazoid CEUS. The suggested diagnostic criteria include nonrim arterial phase hyperenhancement, and the presence of late and mild washout, or Kupffer phase washout under the premise that the early or marked washout should not occur during the portal venous phase. These criteria aim to improve the accuracy of HCC diagnosis using Sonazoid CEUS. This review offers a comprehensive overview of Sonazoid CEUS in the context of HCC diagnosis. It covers the fundamental principles of Sonazoid CEUS and its clinical applications, and introduces the recently published guidelines. By providing a summary of this emerging technique, this review contributes to a better understanding of the potential role of Sonazoid CEUS for diagnosing HCC.

Automated CT LI-RADS v2018 scoring of liver observations using machine learning: A multivendor, multicentre retrospective study

Assessment of computed tomography (CT)/magnetic resonance imaging Liver Imaging Reporting and Data System (LI-RADS) v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. We assessed the performance and added-value of a machine learning (ML)-based algorithm in assessing CT LI-RADS major features and categorisation of liver observations compared with qualitative assessment performed by a panel of radiologists. High-risk patients as per LI-RADS v2018 with pathologically proven liver lesions who underwent multiphase contrast-enhanced CT at diagnosis between January 2015 and March 2019 in seven centres in five countries were retrospectively included and randomly divided into a training set (n= 84 lesions) and a test set (n= 345 lesions). An ML algorithm was trained to classify non-rim arterial phase hyperenhancement, washout, and enhancing capsule as present, absent, or of uncertain presence. LI-RADS major features and categories were compared with qualitative assessment of two independent readers. The performance of a sequential use of the ML algorithm and independent readers were also evaluated in a triage and an add-on scenario in LR-3/4 lesions. The combined evaluation of three other senior readers was used as reference standard. A total of 318 patients bearing 429 lesions were included. Sensitivity and specificity for LR-5 in the test set were 0.67 (95% CI, 0.62-0.72) and 0.91 (95% CI, 0.87-0.96) respectively, with 242 (70.1%) lesions accurately categorised. Using the ML algorithm in a triage scenario improved the overall performance for LR-5. (0.86 and 0.93 sensitivity, 0.82 and 0.76 specificity, 78% and 82.3% accuracy for the two independent readers). Quantitative assessment of CT LI-RADS v2018 major features is feasible and diagnoses LR-5 observations with high performance especially in combination with the radiologist's visual analysis in patients at high-risk for HCC. Assessment of CT/MRI LI-RADS v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. Rather than replacing radiologists, our results highlight the potential benefit from the radiologist-artificial intelligence interaction in improving focal liver lesions characterisation by using the developed algorithm as a triage tool to the radiologist's visual analysis. Such an AI-enriched diagnostic pathway may help standardise and improve the quality of analysis of liver lesions in patients at high risk for HCC, especially in non-expert centres in liver imaging. It may also impact the clinical decision-making and guide the clinician in identifying the lesions to be biopsied, for instance in patients with multiple liver focal lesions.

Development of a deep-learning model for classification of LI-RADS major features by using subtraction images of MRI: a preliminary study.

Liver Imaging Reporting and Data System (LI-RADS) is limited by interreader variability. Thus, our study aimed to develop a deep-learning model for classifying LI-RADS major features using subtraction images using magnetic resonance imaging (MRI). This single-center retrospective study included 222 consecutive patients who underwent resection for hepatocellular carcinoma (HCC) between January, 2015 and December, 2017. Subtraction arterial, portal venous, and transitional phase images of preoperative gadoxetic acid-enhanced MRI were used to train and test the deep-learning models. Initially, a three-dimensional (3D) nnU-Net-based deep-learning model was developed for HCC segmentation. Subsequently, a 3D U-Net-based deep-learning model was developed to assess three LI-RADS major features (nonrim arterial phase hyperenhancement [APHE], nonperipheral washout, and enhancing capsule [EC]), utilizing the results determined by board-certified radiologists as reference standards. The HCC segmentation performance was assessed using the Dice similarity coefficient (DSC), sensitivity, and precision. The sensitivity, specificity, and accuracy of the deep-learning model for classifying LI-RADS major features were calculated. The average DSC, sensitivity, and precision of our model for HCC segmentation were 0.884, 0.891, and 0.887, respectively, across all the phases. Our model demonstrated a sensitivity, specificity, and accuracy of 96.6% (28/29), 66.7% (4/6), and 91.4% (32/35), respectively, for nonrim APHE; 95.0% (19/20), 50.0% (4/8), and 82.1% (23/28), respectively, for nonperipheral washout; and 86.7% (26/30), 54.2% (13/24), and 72.2% (39/54) for EC, respectively. We developed an end-to-end deep-learning model that classifies the LI-RADS major features using subtraction MRI images. Our model exhibited satisfactory performance in classifying LI-RADS major features.

Gd-EOB MRI for HCC subtype differentiation in a western population according to the 5th edition of the World Health Organization classification.

To investigate the value of gadoxetic acid (Gd-EOB)-enhanced magnetic resonance imaging (MRI) for noninvasive subtype differentiation of HCCs according to the 5th edition of the WHO Classification of Digestive System Tumors in a western population. This retrospective study included 262 resected lesions in 240 patients with preoperative Gd-EOB-enhanced MRI. Subtypes were assigned by two pathologists. Gd-EOB-enhanced MRI datasets were assessed by two radiologists for qualitative and quantitative imaging features, including imaging features defined in LI-RADS v2018 and area of hepatobiliary phase (HBP) iso- to hyperintensity. The combination of non-rim arterial phase hyperenhancement with non-peripheral portal venous washout was more common in "not otherwise specified" (nos-ST) (88/168, 52%) than other subtypes, in particular macrotrabecular massive (mt-ST) (3/15, 20%), chromophobe (ch-ST) (1/8, 13%), and scirrhous subtypes (sc-ST) (2/9, 22%) (p = 0.035). Macrovascular invasion was associated with mt-ST (5/16, p = 0.033) and intralesional steatosis with steatohepatitic subtype (sh-ST) (28/32, p < 0.001). Predominant iso- to hyperintensity in the HBP was only present in nos-ST (16/174), sh-ST (3/33), and clear cell subtypes (cc-ST) (3/13) (p = 0.031). Associations were found for the following non-imaging parameters: age and sex, as patients with fibrolamellar subtype (fib-ST) were younger (median 44years (19-66), p < 0.001) and female (4/5, p = 0.023); logarithm of alpha-fetoprotein (AFP) was elevated in the mt-ST (median 397µg/l (74-5370), p < 0.001); type II diabetes mellitus was more frequent in the sh-ST (20/33, p = 0.027). Gd-EOB-MRI reproduces findings reported in the literature for extracellular contrast-enhanced MRI and CT and may be a valuable tool for noninvasive HCC subtype differentiation. Better characterization of the heterogeneous phenotypes of HCCaccording to the revised WHO classification potentially improves both diagnostic accuracy and the precision of therapeutic stratification for HCC. • Previously reported imaging features of common subtypes in CT and MRI enhanced with extracellular contrast agents are reproducible with Gd-EOB-enhanced MRI. • While uncommon, predominant iso- to hyperintensity in the HBP was observed only in NOS, clear cell, and steatohepatitic subtypes. • Gd-EOB-enhanced MRI offers imaging features that are of value for HCC subtype differentiation according to the 5th edition of the WHO Classification of Digestive System Tumors.

Distinct radiological features of lymphoepithelioma-likeintrahepatic cholangiocarcinoma: comparison with classical intrahepatic cholangiocarcinoma.

Lymphoepithelioma-like intrahepatic cholangiocarcinoma (LEICC) has been recently introduced as a genetically distinct of intrahepatic cholangiocarcinoma (ICC). We aimed to investigate whether LEICC has distinct radiological characteristics in comparison with classical ICC, and to determine MRI features that can be used to differentiate LEICC from classical ICC. Five hundred and sixty-seven consecutive patients who underwent surgical resection or liver transplantation for ICC between 2014 and 2021 were retrospectively identified. Among them, 30 patients with LEICC (LEICC-cohort) and 116 with stage-matched classical ICC (control-cohort) were finally included. Pre-operative MRI data were compared between the two cohorts. Multivariable logistic regression analysis was performed to determine relevant imaging features suggesting the diagnosis of LEICC over classical ICC. LEICCs showed significantly higher frequencies of a non-rim arterial phase hyperenhancement (APHE), washout on post-arterial images and a smooth margin, as well as less frequencies of perilesional enhancement and liver capsular retraction when compared with classical ICCs (P < 0.05 for all). The multivariate analysis revealed that non-rim APHE (odds ratio, 10.863; 95% CI [3.295-35.821]; P < 0.001) and the absence of perilesional enhancement (odds ratio, 3.350; 95% CI [1.167-9.619]; P = 0.025) are significant independent imaging features that suggest the diagnosis of LEICCs over classical ICCs. Compared with classical ICCs, LEICCs do have distinct radiological characteristics. A smooth margin, non-rim APHE, washout on post-arterial images, absent perilesional enhancement and absent liver capsular retraction are useful MRI features that could help to differentiate LEICCs from classical ICCs.

A new classification and regression tree algorithm: Improved diagnostic sensitivity for HCC ≤ 3.0 cm using gadoxetate disodium-enhanced MRI

PurposeTo develop and validate an effective algorithm, based on classification and regression tree (CART) analysis and LI-RADS features, for diagnosing HCC ≤ 3.0 cm with gadoxetate disodium‑enhanced MRI (Gd-EOB-MRI). MethodWe retrospectively included 299 and 90 high-risk patients with hepatic lesions ≤ 3.0 cm that underwent Gd-EOB-MRI from January 2018 to February 2021 in institution 1 (development cohort) and institution 2 (validation cohort), respectively. Through binary and multivariate regression analyses of LI-RADS features in the development cohort, we developed an algorithm using CART analysis, which comprised the targeted appearance and independently significant imaging features. On per-lesion basis, we compared the diagnostic performances of our algorithm, two previously reported CART algorithms, and LI-RADS LR-5 in development and validation cohorts. ResultsOur CART algorithm, presenting as a decision tree, included targetoid appearance, HBP hypointensity, nonrim arterial phase hyperenhancement (APHE), and transitional phase hypointensity plus mild-moderate T2 hyperintensity. For definite HCC diagnosis, the overall sensitivity of our algorithm (development cohort 93.2%, validation cohort 92.5%; P < 0.006) was significantly higher than those of Jiang’s algorithm modified LR-5 (defined as targetoid appearance, nonperipheral washout, restricted diffusion, and nonrim APHE) and LI-RADS LR-5, with the comparable specificity (development cohort: 84.3%, validation cohort: 86.7%; P ≥ 0.006). Our algorithm, providing the highest balanced accuracy (development cohort: 91.2%, validation cohort: 91.6%), outperformed other criteria for identifying HCCs from non-HCC lesions. ConclusionsIn high-risk patients, our CART algorithm developed with LI-RADS features showed promise for the early diagnosis of HCC ≤ 3.0 cm with Gd-EOB-MRI.

An improved diagnostic algorithm for subcentimeter hepatocellular carcinoma on gadoxetic acid-enhanced MRI.

Accurate diagnosis of subcentimeter hepatocellular carcinoma (HCC) is a challenge also with gadoxetic acid-enhanced MRI (EOB-MRI). This study aimed to assess the diagnostic accuracy of the Liver Imaging Reporting and Data System (LI-RADS) for subcentimeter HCC and to determine whether new diagnostic criteria (washout either on portal venous phase (PVP) or transitional phase (TP)) would improve the diagnostic performance. We evaluated 240 subcentimeter observations in 225 consecutive treatment-naïve patients at risk of HCC. Final diagnoses were 132 HCCs (all by pathology) and 108 non-HCC (41 by pathology and 67 by follow-up). Two radiologists assessed MR imaging features and assigned LI-RADS categories. A variety of diagnostic criteria were developed by combining significant MRI features based on washout on PVP or TP. Diagnostic performance was compared. Non-rim arterial phase hyperenhancement (non-rim APHE), washout on PVP or TP, and hepatobiliary-phase hypointensity were significant predictors for subcentimeter HCC diagnosis according to multivariable analysis. One criterion (non-rim APHE and washout on PVP or TP) yielded higher sensitivity (68.2% vs. 56.8%, p = 0.011) with comparable specificity (91.7% vs. 92.6%, p > 0.999) compared to the LR-4 category. This criterion had improved sensitivity (68.2% vs. 49.2%, p < 0.001) and slightly decreased specificity (91.7% vs. 94.4%, p = 0.250) compared to non-rim APHE with washout on PVP. LI-RADS exhibits modest diagnostic performance for subcentimeter HCC. Our new criterion (non-rim APHE and non-peripheral washout on PVP or TP) may increase the diagnostic sensitivity without compromised specificity compared to the LR-4 category. • The LR-4 category shows modest diagnostic performance for the diagnosis of subcentimeter HCC on EOB-MRI with a sensitivity and specificity of 56.8% and 92.6%, respectively. • Non-rim APHE, non-peripheral washout on PVP or TP, and HBP hypointensity were independent predictors for the diagnosis of subcentimeter HCC. • The combination of non-rim APHE and non-peripheral washout on PVP or TP improves the sensitivity from 56.8 to 68.2% (p = 0.011) with comparable specificity (91.7 vs. 92.6%, p > 0.999).

Multiple arterial-phase MRI with gadoxetic acid improves diagnosis of hepatocellular carcinoma ≤3.0 cm.

Multiple arterial-phase magnetic resonance imaging (MA-MRI) was introduced to overcome the limitations of gadoxetic acid-enhanced MRI, but its clinical impacts on hepatocellular carcinoma (HCC) diagnosis have not been well assessed. We investigated whether MA-MRI with gadoxetic acid could improve the diagnosis of HCC ≤3.0cm in comparison with single arterial-phase MRI (SA-MRI). This retrospective study included 397 patients from two tertiary institutions who underwent gadoxetic acid-enhanced MRI (243 patients with 271 lesions in cohort-1 underwent SA-MRI, and 154 patients with 166 lesions in cohort-2 underwent MA-MRI). The patients had 437 hepatic lesions ≤3.0cm with pathologic confirmation. The arterial-phase image quality and diagnostic performance of SA-MRI and MA-MRI were analysed and compared. To minimize the effects of selection bias because of potential confounding between the two groups, propensity score-matching was additionally performed. MA-MRI showed a significantly higher percentage of optimal arterial-phase timing (94.2% vs. 74.5%, p < .001) and lower incidence of inadequate examinations (1.3% vs. 5.8%, p=.034) than SA-MRI. MA-MRI had a significantly higher non-rim arterial-phase hyperenhancement (APHE) detection rate (94.9% vs. 85.5%, p=.005) and sensitivity for diagnosing HCC (87.4% vs. 70.0%, p < .001) than SA-MRI, but no significant difference in specificity (92.9% vs. 93.1%, p=.966). In 123 pairs of propensity score-matched patients, MA-MRI had significantly higher sensitivity (89.1% vs. 74.5%, p=.006) than SA-MRI with equal specificity (92.3% vs. 92.3%, p > .999). Compared with SA-MRI, MA-MRI with gadoxetic acid can detect more non-rim APHE and significantly improve sensitivity for diagnosing HCC ≤3.0cm, without a significant decrease in specificity.

Comparison of imaging findings of macrotrabecular-massive hepatocellular carcinoma using CT and gadoxetic acid-enhanced MRI.

To investigate the imaging findings of macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) on CT and MRI, and examine their diagnostic performance and prognostic significance. We retrospectively enrolled 220 consecutive patients who underwent hepatic resection between June 2009 and December 2013 for single treatment-naïve HCC, who have preoperative CT and gadoxetic acid-enhanced MRI. Independent reviews of histopathology and imaging were performed by two reviewers. Previously reported imaging findings, LI-RADS category, and CT attenuation of MTM-HCC were investigated. The diagnostic performance of the MTM-HCC diagnostic criteria was compared across imaging modalities. MTM-HCC was associated with ≥ 50% arterial phase hypovascular component, intratumoral artery, arterial phase peritumoral enhancement, and non-smooth tumor margin on CT and MRI (p < .05). Arterial phase hypovascular components were less commonly observed on MRI subtraction images than on CT or MRI, while non-rim arterial phase hyperenhancement and LR-5 were more commonly observed on MRI subtraction images than on MRI (p < .05). MTM-HCC showed lower tumor attenuation in the CT arterial phase (p = .01). Rhee's criteria, defined as ≥ 50% hypovascular component and ≥ 2 ancillary findings (intratumoral artery, arterial phase peritumoral enhancement, and non-smooth tumor margin), showed similar diagnostic performance for MRI (sensitivity, 41%; specificity, 97%) and CT (sensitivity, 31%; specificity, 94%). Rhee's criteria on CT were independent prognostic factors for overall survival. The MRI diagnostic criteria for MTM-HCC are applicable on CT, showing similar diagnostic performance and prognostic significance. For MTM-HCC, arterial phase subtraction images can aid in the HCC diagnosis by depicting subtle arterial hypervascularity. • MTM-HCC on CT demonstrated previously described MRI findings, including arterial phase hypovascular component, intratumoral artery, arterial phase peritumoral enhancement, and necrosis. • The MRI diagnostic criteria for MTM-HCC were also applicable to CT, showing comparable diagnostic performance and prognostic significance. • On arterial phase subtraction imaging, MTM-HCC more frequently demonstrated non-rim enhancement and LR-5 and less frequently LR-M than MRI arterial phase, which may aid in the diagnosis of HCC.

Fat in mass in primary liver lesions: are usual MRI diagnostic criteria of both malignant and benign liver lesions still applicable?

To evaluate the accuracy of the usual MRI diagnostic patterns of primary liver lesions applied to the diagnosis of pathologically proven fat-containing liver lesions. This monocentric IRB approved retrospective study included all patients with pathologically proven focal liver lesions and documented intra-tumoral fat on pathology and who underwent preoperative liver MRI for characterization. Both liver morphology and usual lesion MRI features were analyzed and their distribution correlated to the final pathological result (Khi-2 or Fisher exact tests, Student t-test or Mann-Whitney U test, as appropriate). The Sensitivity (Se) and Specificity (Sp) of MRI patterns known to be associated to both Hepatocellular Carcinoma (HCC), Focal Nodular Hyperplasia (FNH), and Hepatocellular Adenoma (HCA) subtypes were evaluated. Between March 2014 and November 2021, 66 lesions were included, corresponding to: 26 HCC, 32 HCA, 6 FNH and 2 hepatic angiomyolipoma (HAML). All lesions developed on a dysmorphic liver were HCC. A non-rim arterial phase hyperenhancement with a washout and an enhancing capsule had a 98% specificity for HCC diagnosis; A homogeneous dropout of signal on the opposed phase had a sensitivity of 92% and a specificity of 89% for the diagnosis of HNF1alpha inactivated subtype of HCA (HHCA). The FNH pattern was specific at 100% for the diagnosis of FNH with a 40% Se. Finally, the accuracy of inflammatory hepatocellular adenoma (IHCA) pattern had a low 60% Se but a high 89% Sp for IHCA diagnosis. Known MRI patterns remain reliable for the accurate diagnosis of primary liver tumors on MRI even in fat-containing lesions.

Noninvasive Diagnosis of Hepatocellular Carcinoma on Sonazoid-Enhanced US: Value of the Kupffer Phase.

The aim of this study was to compare the diagnostic performance of Contrast-Enhanced US Liver Imaging Reporting and Data System (CEUS LI-RADS) version 2017, which includes portal- and late-phase washout as a major imaging feature, with that of modified CEUS LI-RADS, which includes Kupffer-phase findings as a major imaging feature. Participants at risk of hepatocellular carcinoma (HCC) with treatment-naïve hepatic lesions (≥1 cm) were recruited and underwent Sonazoid-enhanced US. Arterial phase hyperenhancement (APHE), washout time, and echogenicity in the Kupffer phase were evaluated using both criteria. The diagnostic performance of both criteria was analyzed using the McNemar test. The evaluation was performed on 102 participants with 102 lesions (HCCs (n = 52), non-HCC malignancies (n = 36), and benign (n = 14)). Among 52 HCCs, non-rim APHE was observed in 92.3% (48 of 52). By 5 min, 73.1% (38 of 52) of HCCs showed mild washout, while by 10 min or in the Kupffer phase, 90.4% (47 of 52) of HCCs showed hypoenhancement. The sensitivity (67.3%; 35 of 52; 95% CI: 52.9%, 79.7%) of modified CEUS LI-RADS criteria was higher than that of CEUS LI-RADS criteria (51.9%; 27 of 52; 95% CI: 37.6%, 66.0%) (p = 0.0047). In conclusion, non-rim APHE with hypoenhancement in the Kupffer phase on Sonazoid-enhanced US is a feasible criterion for diagnosing HCC.

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

The 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. To modify LI-RADS (mLI-RADS) on EOB-MRI. Secondary analysis of a prospective observational study. Between 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. 3.0 TT2 -weighted fast spin-echo, diffusion-weighted spin-echo based echo-planar, and 3D T1 -weighted gradient echo sequences. Three 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. In 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. Five 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%). In 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. 2 TECHNICAL EFFICACY: Stage 2.

Diagnostic criteria of perfluorobutane-enhanced ultrasonography for diagnosing hepatocellular carcinoma in high-risk individuals: how is late washout determined?

PurposeThe aim of this study was to investigate the optimal washout criteria of perfluorobutane-enhanced ultrasonography (PFB-US) for the diagnosis of hepatocellular carcinoma (HCC) in high-risk individuals.MethodsParticipants at risk of HCC with treatment-naïve solid hepatic observations (≥1 cm) who underwent PFB-US from March 2019 to September 2020 were prospectively recruited. Arterial phase hyperenhancement (APHE), washout time, and washout degree were evaluated. The diagnosis of HCC was made by non-rim APHE with late and mild washout. The per-lesion diagnostic performance for diagnosing HCC using different cutoffs for late washout (50, 55, 60, 65, and 70 seconds postcontrast) and the different time windows for determining washout (until 2, 3, 4, 5, 6, 7, 8, 9, and 10 minutes postcontrast) were compared using the McNemar test.ResultsIn total, 101 participants with 113 observations (mean size, 33.5±2.8 mm; HCCs [n=82], non-HCC malignancies [n=16], benign [n=15]) were evaluated. Non-rim APHE was observed in 86.6% (71/82) of HCCs. As the cutoff time for late washout increased, the specificity increased to 100% (95% confidence interval [CI], 88.8% to 100%) at the 60-second cutoff with 62.2% sensitivity (95% CI, 50.8% to 72.7%). When the time window for determining washout became wider, the sensitivity and accuracy increased until 6 minutes, with 100% specificity at all times. ConclusionDetermining washout within 6 minutes after contrast injection with a 60-second cutoff for late washout showed the highest sensitivity without losing specificity for diagnosing HCC using PFB-US in individuals at high risk.

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

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. 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. Three hundred eight observations in 234 patients (67.6% male, mean age 66.2years) 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 10-19mm with APHE and WO. Of the 6 incorrectly categorized v2018 observations, 5 (83%) lacked APHE and 1 (17%) was < 10mm. 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.