Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models.

Background Large language models (LLMs) hold substantial promise for medical imaging interpretation. However, there is a lack of studies on their feasibility in handling reasoning questions associated with medical diagnosis. Purpose To investigate the viability of leveraging three publicly available LLMs to enhance consistency and diagnostic accuracy in medical imaging based on standardized reporting, with pathology as the reference standard. Materials and Methods US images of thyroid nodules with pathologic results were retrospectively collected from a tertiary referral hospital between July 2022 and December 2022 and used to evaluate malignancy diagnoses generated by three LLMs-OpenAI's ChatGPT 3.5, ChatGPT 4.0, and Google's Bard. Inter- and intra-LLM agreement of diagnosis were evaluated. Then, diagnostic performance, including accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), was evaluated and compared for the LLMs and three interactive approaches: human reader combined with LLMs, image-to-text model combined with LLMs, and an end-to-end convolutional neural network model. Results A total of 1161 US images of thyroid nodules (498 benign, 663 malignant) from 725 patients (mean age, 42.2 years ± 14.1 [SD]; 516 women) were evaluated. ChatGPT 4.0 and Bard displayed substantial to almost perfect intra-LLM agreement (κ range, 0.65-0.86 [95% CI: 0.64, 0.86]), while ChatGPT 3.5 showed fair to substantial agreement (κ range, 0.36-0.68 [95% CI: 0.36, 0.68]). ChatGPT 4.0 had an accuracy of 78%-86% (95% CI: 76%, 88%) and sensitivity of 86%-95% (95% CI: 83%, 96%), compared with 74%-86% (95% CI: 71%, 88%) and 74%-91% (95% CI: 71%, 93%), respectively, for Bard. Moreover, with ChatGPT 4.0, the image-to-text-LLM strategy exhibited an AUC (0.83 [95% CI: 0.80, 0.85]) and accuracy (84% [95% CI: 82%, 86%]) comparable to those of the human-LLM interaction strategy with two senior readers and one junior reader and exceeding those of the human-LLM interaction strategy with one junior reader. Conclusion LLMs, particularly integrated with image-to-text approaches, show potential in enhancing diagnostic medical imaging. ChatGPT 4.0 was optimal for consistency and diagnostic accuracy when compared with Bard and ChatGPT 3.5. © RSNA, 2024 Supplemental material is available for this article.

US-based Sequential Algorithm Integrating an AI Model for Advanced Liver Fibrosis Screening.

Background Noninvasive tests can be used to screen patients with chronic liver disease for advanced liver fibrosis; however, the use of single tests may not be adequate. Purpose To construct sequential clinical algorithms that include a US deep learning (DL) model and compare their ability to predict advanced liver fibrosis with that of other noninvasive tests. Materials and Methods This retrospective study included adult patients with a history of chronic liver disease or unexplained abnormal liver function test results who underwent B-mode US of the liver between January 2014 and September 2022 at three health care facilities. A US-based DL network (FIB-Net) was trained on US images to predict whether the shear-wave elastography (SWE) value was 8.7 kPa or higher, indicative of advanced fibrosis. In the internal and external test sets, a two-step algorithm (Two-step#1) using the Fibrosis-4 Index (FIB-4) followed by FIB-Net and a three-step algorithm (Three-step#1) using FIB-4 followed by FIB-Net and SWE were used to simulate screening scenarios where liver stiffness measurements were not or were available, respectively. Measures of diagnostic accuracy were calculated using liver biopsy as the reference standard and compared between FIB-4, SWE, FIB-Net, and European Association for the Study of the Liver guidelines (ie, FIB-4 followed by SWE), along with sequential algorithms. Results The training, validation, and test data sets included 3067 (median age, 42 years [IQR, 33-53 years]; 2083 male), 1599 (median age, 41 years [IQR, 33-51 years]; 1124 male), and 1228 (median age, 44 years [IQR, 33-55 years]; 741 male) patients, respectively. FIB-Net obtained a noninferior specificity with a margin of 5% (P < .001) compared with SWE (80% vs 82%). The Two-step#1 algorithm showed higher specificity and positive predictive value (PPV) than FIB-4 (specificity, 79% vs 57%; PPV, 44% vs 32%) while reducing unnecessary referrals by 42%. The Three-step#1 algorithm had higher specificity and PPV compared with European Association for the Study of the Liver guidelines (specificity, 94% vs 88%; PPV, 73% vs 64%) while reducing unnecessary referrals by 35%. Conclusion A sequential algorithm combining FIB-4 and a US DL model showed higher diagnostic accuracy and improved referral management for all-cause advanced liver fibrosis compared with FIB-4 or the DL model alone. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ghosh in this issue.

Surveillance for malignant progression of LI-RADS version 2017 category 3/4 nodules using contrast-enhanced ultrasound.

OBJECTIVES: To identify the risk factors for predicting the malignant progression of LR-3/4 observations on the baseline and contrast-enhanced ultrasound (CEUS). METHODS: In total, 245 liver nodules assigned to LR-3/4 in 192 patients from January 2010 to December 2016 were followed up by baseline US and CEUS. The differences in the rate and time of progression to hepatocellular carcinoma (HCC) among subcategories (defined as P1-P7) of LR-3/4 in CEUS Liver Imaging Reporting and Data System (LI-RADS) were analyzed. The risk factors to predict progression to HCC were analyzed by univariate and multivariate Cox proportional hazard model analysis. RESULTS: A total of 40.3% of LR-3 nodules and 78.9% of LR-4 nodules eventually progressed to HCC. The cumulative incidence of progression was significantly higher for LR-4 than LR-3 (p < 0.001). The rate of progression was 81.2% in nodules with arterial phase hyperenhancement (APHE), 64.7% in nodules with late and mild washout, and 100% in nodules with both characteristics. The overall progression rate and median progression time of subcategory P1 nodules (LR-3a) were lower (38.0% vs. 47.6-100.0%) and later (25.1 months vs. 2.0-16.3 months) than those of other subcategories. The cumulative incidence of progression of LR-3a (P1), LR-3b (P2/3/4), and LR-4 (P5/6/7) categories were 38.0%, 52.9%, and 78.9%. The risk factors of HCC progression were Visualization score B/C, CEUS characteristics (APHE, washout), LR-4 classification, echo changes, and definite growth. CONCLUSION: CEUS is a useful surveillance tool for nodules at risk of HCC. CEUS characteristics, LI-RADS classification, and changes in nodules provide useful information for the progress of LR-3/4 nodules. CLINICAL RELEVANCE STATEMENT: CEUS characteristics, LI-RADS classification, and nodule changes provide important predictions for LR-3/4 nodule progression to HCC, which may stratify the risk of malignant progression to provide a more optimized and refined, more cost-effective, and time-efficient management strategy for patients. KEY POINTS: • CEUS is a useful surveillance tool for nodules at risk of HCC, CEUS LI-RADS successfully stratified the risks that progress to HCC. • CEUS characteristics, LI-RADS classification, and changes in nodules can provide important information on the progression of LR-3/4 nodules, which may be helpful for a more optimized and refined management strategy.

US LI-RADS in surveillance for recurrent hepatocellular carcinoma after curative treatment.

OBJECTIVES: To investigate the performance of US LI-RADS in surveillance for recurrent hepatocellular carcinoma (RHCC) after curative treatment. MATERIALS AND METHODS: This study enrolled 644 patients between January 2018 and August 2018 as a derivation cohort, and 397 patients from September 2018 to December 2018 as a validation cohort. The US surveillance after HCC curative treatment was performed. The US LI-RADS observation categories and visualization scores were analyzed. Four criteria using US LI-RADS or Alpha-fetoprotein (AFP) as the surveillance algorithm were evaluated. The sensitivity, specificity, and negative predictive value (NPV) were calculated. RESULTS: A total of 212 (32.9%) patients in derivation cohort and 158 (39.8%) patients in validation cohort were detected to have RHCCs. The criterion of US-2/3 or AFP ≥ 20 µg/L had higher sensitivity (derivation, 96.7% vs 92.9% vs 81.1% vs 90.6%; validation, 96.2% vs 90.5% vs 80.4% vs 89.9%) and NPV (derivation, 95.7% vs 93.3% vs 88.0% vs 91.8%; validation, 94.6% vs 89.4% vs 83.6% vs 89.0%), but lower specificity (derivation, 35.9% vs 48.2% vs 67.6% vs 51.9%; validation, 43.5% vs 52.7% vs 66.1% vs 54.0%) than criterion of US-2/3, US-3, and US-3 or AFP ≥ 20 µg/L. Analysis of the visualization score subgroups confirmed that the sensitivity (89.2-97.6% vs 81.0-83.3%) and NPV(88.4-98.0% vs 80.0-83.3%) of score A and score B groups were higher than score C group in criterion of US-2/3 in both two cohorts. CONCLUSIONS: In the surveillance for RHCC, US LI-RADS with AFP had a high sensitivity and NPV when US-2/3 or AFP ≥ 20 µg/L was considered a criterion. CLINICAL RELEVANCE STATEMENT: The criterion of US-2/3 or AFP ≥ 20 µg/L improves sensitivity and NPV for RHCC surveillance, which provides a valuable reference for patients in RHCC surveillance after curative treatment. KEY POINTS: • US LI-RADS with AFP had high sensitivity and NPV in surveillance for RHCC when considering US-2/3 or AFP ≥ 20 µg/L as a criterion. • After US with AFP surveillance, patients with US-2/3 or AFP ≥ 20 µg/L should perform enhanced imaging for confirmative diagnosis. Patients with US-1 or AFP < 20 µg/L continue to repeat US with AFP surveillance. • Patients with risk factors for poor visualization scores limited the sensitivity of US surveillance in RHCC.

Strategy for Accurate Diagnosis by Contrast-Enhanced Ultrasound of Focal Liver Lesions in Patients Not at High Risk for Hepatocellular Carcinoma: A Preliminary Study.

OBJECTIVE: To develop an effective strategy for accurate diagnosis of focal liver lesions (FLLs) in patients with non-high risk for hepatocellular carcinoma (HCC). METHODS: From January 2012 to December 2015, consecutive patients with non-high risk for HCC who underwent contrast-enhanced ultrasound (CEUS) were included in this retrospective double-reader study. All patients were stratified into 2 different risks (intermediate, low-risk) groups according to criteria based on clinical characteristics, known as clinical risk stratification criteria. For the intermediate-risk group, the CEUS criteria for identifying benign lesions and HCCs were constructed based on selected CEUS features. The diagnostic performance of the clinical risk stratification criteria, and CEUS criteria for identifying benign lesions and HCCs was evaluated. RESULTS: This study included 348 FLLs in 348 patients. The sensitivity and specificity of the clinical risk stratification criteria for malignancy was 97.8 and 69.8%. Patients were classified as intermediate risk if they were male, or older than 40 years of age, or HBcAb positive, or having positive tumor markers. Otherwise, patients were classified as low risk. Among the 348 patients, 327 were in the intermediate-risk group and 21 were in the low-risk group. In the intermediate-risk group, the CEUS criteria for identifying benign lesions were any of the following features: 1) hyper/isoenhancement in the arterial phase without washout, 2) nonenhancement in all phases, 3) peripheral discontinuous globular enhancement in the arterial phase, 4) centrifugal enhancement or peripheral enhancement followed by no central enhancement, or 5) enhanced septa. The accuracy, sensitivity, and specificity of the CEUS criteria for identifying benign lesions were 94.5, 83.0, and 99.6%, respectively. Arterial phase hyperenhancement followed by mild and late washout (>60 seconds) was more common in HCC patients than in non-HCC patients (P < .001). Using arterial phase hyperenhancement followed by mild and late washout as the CEUS criteria for identifying HCCs, the sensitivity and specificity were 52.6 and 95.3%, but unfortunately, the positive predictive value was only 82.0%. For the low-risk group, no further analysis was performed due to the small sample size. CONCLUSIONS: Initial clinical risk stratification followed by assessment of certain CEUS features appears to be a promising strategy for the accurate diagnosis of FLLs in patients not at high risk for HCC.

Shear-wave elastography combined with contrast-enhanced ultrasound algorithm for noninvasive characterization of focal liver lesions.

PURPOSE: To establish shear-wave elastography (SWE) combined with contrast-enhanced ultrasound (CEUS) algorithm (SCCA) and improve the diagnostic performance in differentiating focal liver lesions (FLLs). MATERIAL AND METHODS: We retrospectively selected patients with FLLs between January 2018 and December 2019 at the First Affiliated Hospital of Sun Yat-sen University. Histopathology was used as a standard criterion except for hemangiomas and focal nodular hyperplasia. CEUS with SonoVue (Bracco Imaging) and SCCA combining CEUS and maximum value of elastography with < 20 kPa and > 90 kPa thresholds were used for the diagnosis of FLLs. The diagnostic performance of CEUS and SCCA was calculated and compared. RESULTS: A total of 171 FLLs were included, with 124 malignant FLLs and 47 benign FLLs. The area under curve (AUC), sensitivity, and specificity in detecting malignant FLLs were 0.83, 91.94%, and 74.47% for CEUS, respectively, and 0.89, 91.94%, and 85.11% for SCCA, respectively. The AUC of SCCA was significantly higher than that of CEUS (P = 0.019). Decision curves indicated that SCCA provided greater clinical benefits. The SCCA provided significantly improved prediction of clinical outcomes, with a net reclassification improvement index of 10.64% (P = 0.018) and integrated discrimination improvement of 0.106 (P = 0.019). For subgroup analysis, we divided the FLLs into a chronic-liver-disease group (n = 88 FLLs) and a normal-liver group (n = 83 FLLs) according to the liver background. In the chronic-liver-disease group, there were no differences between the CEUS-based and SCCA diagnoses. In the normal-liver group, the AUC of SCCA and CEUS in the characterization of FLLs were 0.89 and 0.83, respectively (P = 0.018). CONCLUSION: SCCA is a feasible tool for differentiating FLLs in patients with normal liver backgrounds. Further investigations are necessary to validate the universality of this algorithm.

Reproducibility of radiomics features from ultrasound images: influence of image acquisition and processing.

OBJECTIVES: To systematically assess the reproducibility of radiomics features from ultrasound (US) images during image acquisition and processing. MATERIALS AND METHODS: A standardized phantom was scanned to obtain US images. Reproducibility of radiomics features from US images, also known as ultrasomics features, was explored via (a) intra-US machine: changing the US acquisition parameters including gain, focus, and frequency; (b) inter-US machine: comparing three different scanners; (c) changing segmentation locations; and (d) inter-platform: comparing features extracted by the Ultrasomics and PyRadiomics algorithm platforms. Reproducible ultrasomics features were selected based on coefficients of variation. RESULTS: A total of 108 US images from three scanners were obtained; 5253 ultrasomics features including seven categories of features were extracted and evaluated for each US image. From intra-US machine analysis, 37.0-38.8% of features showed good reproducibility. From inter-US machine analysis, 42.8% (2248/5253) of features exhibited good reproducibility. From segmentation location analysis, 55.7-57.6% of features showed good reproducibility. No significant difference in the normalized feature ranges was found between the 100 features extracted by the Ultrasomics and PyRadiomics platforms with the same algorithm (p = 0.563). A total of 1452 (27.6%) ultrasomics features were reproducible whenever intra-/inter-US machine or segmentation location were changed, most of which were wavelet and shearlet features. CONCLUSIONS: Different acquisition parameters, US scanners, segmentation locations, and feature extraction platforms affected the reproducibility of ultrasomics features. Wavelet and shearlet features showed the best reproducibility across all procedures. KEY POINTS: • Different acquisition parameters, US scanners, segmentation locations, and feature extraction platforms affected the reproducibility of ultrasomics features. • A total of 1452 (27.6%) ultrasomics features were reproducible whenever intra-/inter-US machine or segmentation location were changed. • Wavelet and shearlet features showed the best reproducibility across all procedures.

LR-M Observations on Contrast-Enhanced Ultrasound: Detection of Hepatocellular Carcinoma Using Additional Features in Comparison With Current LI-RADS Criteria.

BACKGROUND. Contrast-enhanced ultrasound (CEUS) LI-RADS assigns category LR-M to observations that are definitely or probably malignant but that on imaging are not specific for hepatocellular carcinoma (HCC). A high percentage of LR-M observations represent HCC. OBJECTIVE. The purpose of this study was to retrospectively evaluate the utility of additional features, beyond conventional LI-RADS major features, for detecting HCC among LR-M observations on CEUS. METHODS. This retrospective study included 174 patients (145 men, 29 women; mean age, 53 years) at high risk of HCC who underwent CEUS from August 2014 to June 2016 that showed an LR-M observation according to CEUS LI-RADS version 2017. Two radiologists independently assessed CEUS images for major features and four additional features (chaotic vessels, peripheral circular artery, clear boundary of tumor enhancement, clear boundary of intratumoral unenhanced area). The diagnostic performance of four proposed criteria for the detection of HCC among LR-M observations was assessed. The impact of criteria based on the additional findings on detection of HCC was further explored. Histology or composite imaging and clinical follow-up were the reference standards. RESULTS. The 174 LR-M observations included 142 HCCs and 32 non-HCC lesions (20 intrahepatic cholangiocarcinomas, five combined hepatocellular-cholangiocarcinomas, seven benign lesions). Interreader agreement on the additional features ranged from κ = 0.65 to κ = 0.88. Two of the additional features had excellent PPV for HCC: chaotic vessels (94.8%) and peripheral circular arteries (98.1%). The presence of either of these two additional features had sensitivity of 50.7%, specificity of 90.6%, PPV of 96.0%, and NPV of 29.3% for HCC. Three other criteria incorporating variations of major LI-RADS features but not the additional features had sensitivities of 55.6-96.5%, specificities of 49.6-68.8%, PPVs of 87.8-90.6%, and NPVs of 25.0-75.0%. On the basis of criteria that included additional features, 75 of 174 LR-M observations were recategorized LR-5; 72 of the 75 were HCC. CONCLUSION. The presence of chaotic vessels and/or peripheral circular artery had high specificity and PPV for HCC among LR-M observations. Other explored criteria based on major features did not have higher specificity or PPV. CLINICAL IMPACT. Clinical adoption of the additional CEUS features could help establish the diagnosis of HCC noninvasively and avoid the need for biopsy of LR-M observations.

Preoperative prognostic value of alfa-fetoprotein density in patients with hepatocellular carcinoma undergoing radiofrequency ablation.

OBJECTIVES: To examine the prognostic value of preoperative alfa-fetoprotein (AFP) density and other clinical factors in patients undergoing percutaneous radiofrequency ablation (RFA) of hepatocellular carcinoma (HCC). METHODS: From January 2010 to December 2018, a total of 543 patients undergoing RFA for HCC meeting the Milan criteria were included at our institution. AFP density was calculated as absolute AFP pre-ablation divided by the total volume of all HCC lesions. The survival rates according to AFP density were estimated using the Kaplan-Meier method and compared using the log-rank test. Univariate and multivariate Cox proportional-hazards regression analyses were used to assess predictors of overall survival (OS) and progression-free survival (PFS). RESULTS: The Kaplan-Meier 1-, 3-, and 5-year OS rates were 98.8%, 88.5%, and 70.4%, respectively, for the low AFP density group, and 98.3%, 74.9%, and 49.4%, respectively, for the high AFP density group. The corresponding PFS rates were 78.9%, 56.7%, and 40.9% (low AFP density group), and 63.6%, 40.8%, and 27.5% (high AFP density group). High AFP density was associated with significantly reduced PFS and OS (both p < 0.001). Multivariate analysis suggested that AFP density was a predictor of OS and PFS. CONCLUSIONS: Serum AFP density may serve as a promising predictor of survival in patients with HCC undergoing RFA. High AFP density could identify patients who might be prone to recurrence or progression and need close surveillance.

Differentiation between combined hepatocellular carcinoma and hepatocellular carcinoma: comparison of diagnostic performance between ultrasomics-based model and CEUS LI-RADS v2017.

BACKGROUND: The imaging findings of combined hepatocellular cholangiocarcinoma (CHC) may be similar to those of hepatocellular carcinoma (HCC). CEUS LI-RADS may not perform well in distinguishing CHC from HCC. Studies have shown that radiomics has an excellent imaging analysis ability. This study aimed to establish and confirm an ultrasomics model for differentiating CHC from HCC. METHODS: Between 2004 and 2016, we retrospectively identified 53 eligible CHC patients and randomly included 106 eligible HCC patients with a ratio of HCC:CHC = 2:1, all of whom were categorized according to Contrast-Enhanced (CE) ultrasonography (US) Liver Imaging Reporting and Data System (LI-RADS) version 2017. The model based on ultrasomics features of CE US was developed in 74 HCC and 37 CHC and confirmed in 32 HCC and 16 CHC. The diagnostic performance of the LI-RADS or ultrasomics model was assessed by the area under the curve (AUC), accuracy, sensitivity and specificity. RESULTS: In the entire and validation cohorts, 67.0% and 81.3% of HCC cases were correctly assigned to LR-5 or LR-TIV contiguous with LR-5, and 73.6% and 87.5% of CHC cases were assigned to LR-M correctly. Up to 33.0% of HCC and 26.4% of CHC were misclassified by CE US LI-RADS. A total of 90.6% of HCC as well as 87.5% of CHC correctly diagnosed by the ultrasomics model in the validation cohort. The AUC, accuracy, sensitivity of the ultrasomics model were higher though without significant difference than those of CE US LI-RADS in the validation cohort. CONCLUSION: The proposed ultrasomics model showed higher ability though the difference was not significantly different for differentiating CHC from HCC, which may be helpful in clinical diagnosis.

Identification of the origin of tumor in vein: comparison between CEUS LI-RADS v2017 and v2016 for patients at high risk.

OBJECTIVES: To compare the diagnostic performance of the Contrast-Enhanced Ultrasound (CEUS) Liver Imaging Report and Data System (LI-RADS) v2016 and v2017 in identifying the origin of tumor in vein (TIV). METHODS: From April 2014 to December 2018, focal liver lesions (FLLs) accompanied by TIV formation in patients at high risk for hepatocellular carcinoma (HCC) were enrolled. Histologic evaluation or composite imaging reference standard were served as the reference standard. Each case was categorized according to the CEUS LI-RADS v2016 and v2017, respectively. Diagnostic performance of CEUS LI-RADS v2016 and v2017 in identifying the originated tumor of TIV was validated via sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value. RESULTS: A total of 273 FLLs with TIV were analyzed finally, including 266 HCCs and 7 non-HCCs. In v2016, when adopting all TIV as LR-5V, the accuracy and PPV in identifying the originated tumor were both 97.4%. In v2017, when assigning TIV according to contiguous FLLs CEUS LI-RADS category, the accuracy and PPV were 61.9% and 99.4% in subclass of LR-5 as the diagnostic criteria of HCC, and 64.1% and 99.4% in subclass of LR-4/5 as the criteria of HCC diagnosis. There were significant differences in diagnostic accuracy between CEUS LI-RADS v2016 and v2017 in identifying the originated tumor of TIV (p < 0.001). CONCLUSIONS: CEUS LI-RADS v2016 could be better than v2017 in identifying the originated tumor of TIV.

Preoperative Survival Prediction in Intrahepatic Cholangiocarcinoma Using an Ultrasound-Based Radiographic-Radiomics Signature.

OBJECTIVES: To construct a preoperative model for survival prediction in intrahepatic cholangiocarcinoma (ICC) patients using ultrasound (US) based radiographic-radiomics signatures. METHODS: Between April 2010 and September 2015, 170 patients with ICC who underwent curative resection were retrospectively recruited. Overall survival (OS)-related radiographic signatures and radiomics signatures based on preoperative US were built and assessed through a time-dependent receiver operating characteristic curve analysis. A nomogram was developed based on the selected predictors from the radiographic-radiomics signatures and clinical and laboratory results of the training cohort (n = 127), validated in an independent testing cohort (n = 43) by the concordance index (C-index), and compared with the Tumor Node Metastasis (TNM) cancer staging system as well as the radiographic and radiomics nomograms. RESULTS: The median areas under the curve of the radiomics signature and radiographic signature were higher than that of the TNM staging system in the testing cohort, although the values were not significantly different (0.76-0.82 versus 0.62, P = .485 and .264). The preoperative nomogram with CA 19-9, sex, ascites, radiomics signature, and radiographic signature had C-indexes of 0.72 and 0.75 in the training and testing cohorts, respectively, and it had significantly higher predictive performance than the 8th TNM staging system in the testing cohort (C-index: 0.75 versus 0.67, P = .004) and a higher C-index than the radiomics nomograms (0.75 versus 0.68, P = .044). CONCLUSIONS: The preoperative nomogram integrated with the radiographic-radiomics signature demonstrated good predictive performance for OS in ICC and was superior to the 8th TNM staging system.

Contrast-Enhanced Ultrasound for Differentiation Between Poorly Differentiated Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma.

PURPOSE: To evaluate the diagnostic performance of LR-5 for diagnosing poorly differentiated hepatocellular carcinoma (p-HCC). To build a contrast-enhanced ultrasound (CEUS) signature for improving the differential diagnostic performance between p-HCC and intrahepatic cholangiocarcinoma (ICC). METHODS: The B-mode ultrasound (BUS) and CEUS features of 60 p-HCCs and 56 ICCs were retrospectively analyzed. The CEUS LI-RADS category was assigned according to CEUS LI-RADS v2017. A diagnostic CEUS signature was built based on the independent significant features. An ultrasound (US) signature combining both BUS and CEUS features was also built. The diagnostic performances of the CEUS signature, US signature, and LR-5 were evaluated by receiver operating characteristic (ROC) analysis. RESULTS: One (1.7%) p-HCC and 26 (46.4%) ICC patients presented cholangiectasis or cholangiolithiasis (P < .001). Fifty-four (90.0%) p-HCCs and 8 (14.3%) ICCs showed clear boundaries in the artery phase (P < .001). The washout times of p-HCCs and ICCs were 81.0 ± 42.5 s and 34.7 ± 8.6 s, respectively (P < .001). The AUC, sensitivity, and specificity of the CEUS signature, US signature, and LR-5 were 0.955, 91.67%, and 90.57% versus 0.976, 96.67%, and 92.45% versus 0.758, 51.67%, and 100%, respectively. The AUC and sensitivity of CEUS LI-RADS were much lower than those of the CEUS and US signatures (P < .001). CONCLUSION: LR-5 had high specificity but low sensitivity in diagnosing p-HCC. When the washout time and tumor boundary were included in the CEUS signature, the sensitivity and AUC were remarkably increased in the differentiation between p-HCC and ICC.

Contrast-Enhanced Ultrasound-Based Nomogram: A Potential Predictor of Individually Postoperative Early Recurrence for Patients With Combined Hepatocellular-Cholangiocarcinoma.

PURPOSES: To evaluate the postsurgical prognostic implication of contrast-enhanced ultrasound (CEUS) for combined hepatocellular-cholangiocarcinoma (CHC). To build a CEUS-based early recurrence prediction classifier for CHC, in comparison with tumor-node-metastasis (TNM) staging. METHODS: The CEUS features and clinicopathological findings of each case were analyzed, and the Liver Imaging Reporting and Data System categories were assigned. The recurrence-free survival associated factors were evaluated by Cox proportional hazard model. Incorporating the independent factors, nomograms were built to estimate the possibilities of 3-month, 6-month, and 1-year recurrence and whose prognostic value was determined by time-dependent receiver operating characteristics, calibration curves, and hazard layering efficiency validation, comparing with TNM staging system. RESULTS: In the multivariable analysis, the levels of carbohydrate antigen 19-9, prothrombin time and total bilirubin, and tumor shape, the Liver Imaging Reporting and Data System category were independent factors for recurrence-free survival. The LR-M category showed longer recurrence-free survival than did the LR-4/5 category. The 3-month, 6-month, and 1-year area under the curves of the CEUS-clinical nomogram, clinical nomogram, and TNM staging system were 0.518, 0.552, and 0.843 versus 0.354, 0.240, and 0.624 (P = .048, .049, and .471) vs. 0.562, 0.545, and 0.843 (P = .630, .564, and .007), respectively. The calibration curves of the CEUS-clinical model at different prediction time pionts were all close to the ideal line. The CEUS-clinical model effectively stratified patients into groups of high and low risk of recurrence in both training and validation set, while the TNM staging system only works on the training set. CONCLUSIONS: Our CEUS-clinical nomogram is a reliable early recurrence prediction tool for hepatocellular-cholangiocarcinoma and helps postoperative risk stratification.

Using new criteria to improve the differentiation between HCC and non-HCC malignancies: clinical practice and discussion in CEUS LI-RADS 2017.

PURPOSE: Using contrast-enhanced ultrasound (CEUS) to evaluate the diagnostic performance of liver imaging reporting and data system (LI-RADS) version 2017 and to explore potential ways to improve the efficacy. METHODS: A total of 315 nodules were classified as LR-1 to LR-5, LR-M, and LR-TIV. New criteria were applied by adjusting the early washout onset (< 45 s) and the time of marked washout (within 3 min). Two subgroups of the LR-M nodules were recategorized as LR-5, respectively. The diagnostic performance was evaluated by calculating the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: By adjusting early washout onset to < 45 s, the LR-5 as a standard for diagnosing HCC had an improved sensitivity (74.1% vs. 56.1%, P < 0.001) without significant change in PPV (93.3% vs. 96.1%, P = 0.267), but the specificity was decreased (48.3% vs. 78.5%, P = 0.018). The LR-M as a standard for the diagnosis of non-HCC malignancies had an increase in specificity (89.2% vs. 66.2%, P < 0.001) but a decrease in sensitivity (31.5% vs. 68.4%, P = 0.023). After reclassification according to the time of marked washout, the sensitivity of the LR-5 increased (80% vs. 56.1%, P < 0.001) without a change in PPV (94.9% vs. 96.1%, P = 0.626) and specificity (80% vs. 78.5%, P = 0.879). For reclassified LR-M nodules, the specificity increased (87.5% versus 66.2%, P < 0.001) with a non-significant decrease in sensitivity (47.3% vs. 68.4%, P = 0.189). CONCLUSIONS: The CEUS LI-RADS showed good confidence in diagnosing HCC while tended to misdiagnose HCC as non-HCC malignancies. Adjusting the marked washout time within 3 min would reduce the possibility of this misdiagnosis.

Treatment effect of radiofrequency ablation versus liver transplantation and surgical resection for hepatocellular carcinoma within Milan criteria: a population-based study.

OBJECTIVES: Restricted mean survival time (RMST) has been increasingly used to assess the treatment effect. We aimed to evaluate a treatment effect of radiofrequency ablation (RFA) versus liver transplantation (LT) and surgical resection (SR) for hepatocellular carcinoma (HCC) within Milan criteria by using an adjusted RMST. METHODS: A total of 7,218 HCC patients (RFA, 3,327; LT, 2,332; SR 1,523) within Milan criteria were eligible for this retrospectively study. The RMST using inverse probability of treatment weighting (IPTW) adjustment were applied to estimate the treatment effect between RFA and LT, RFA, and SR groups. RESULTS: The 3-, 5-, and 10-year IPTW-adjusted difference in RMST of OS for LT over RFA were + 4.5, + 12.4, and + 36.3 months, respectively. For SR versus RFA group, the survival benefit was + 2.3, + 6.1, and + 15.8 months at 3, 5, and 10 years, respectively. But the incremental survival benefit of SR over RFA was only half than that of LT over RFA. In the subgroup of solitary tumor ≤ 2 cm, the adjusted RMST of RFA versus SR was comparable with no statistical differences. Beyond that, in comparison with RFA, a notably greater efficacy of LT and SR was consistently across all subgroups with solitary HCC > 2.0 cm, AFP positive or negative, and fibrosis score 0-4 or 5-6. CONCLUSIONS: RMST provides a measure of absolute survival benefit at a specific time point. Using IPTW-adjusted RMST, we showed that the incremental survival benefit of SR over RFA was about half than that of LT over RFA. KEY POINTS: • The restricted mean survival time offers an intuitive, clinically meaningful interpretation to quantify the treatment effect than the hazard ratio. • Liver transplantation and surgical resection provided better overall survival compared to radiofrequency ablation for HCC patients within Milan criteria, but RFA and SR provide equivalent long-term overall survival for solitary HCC ≤ 2 cm. • The incremental survival benefit of surgical resection over radiofrequency ablation was only half than that of liver transplantation over radiofrequency ablation.

Pathological considerations of CEUS LI-RADS: correlation with fibrosis stage and tumour histological grade.

OBJECTIVES: To evaluate the influence of pathological factors, such as fibrosis stage and histological grade, on the Liver Imaging Reporting and Data System (LI-RADS) v2017 category of contrast-enhanced ultrasonography (CEUS) in patients with high risk of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Between June 2015 and December 2016, 441 consecutive patients at high risk of HCC with 460 pathologically proven HCCs were enrolled in this retrospective study. All patients underwent a CEUS examination. The major features (arterial phase hyperenhancement, late and mild washout) were assessed, and LI-RADS categories were assigned according to CEUS LI-RADS v2017. CEUS LI-RADS categories and major features were compared in different histological grades and fibrosis stages. RESULTS: The CEUS LR-5 category was more frequently assigned in the low-grade group (151/280) than in the high-grade group (66/159) (p = 0.013), whereas the LR-TIV category was more frequently assigned in the high-grade group (36/159) than in the low-grade group (40/280) (p = 0.035). CEUS LI-RADS category was not significantly different among different fibrosis stages (p ≥ 0.05). Arterial phase hyperenhancement (APHE) and the hepatic fibrosis stage showed a significant correlation in HCCs ≥ 2 cm and the low-grade group (p = 0.027 and p = 0.003, respectively). No major features of CEUS LI-RADS showed statistically significant differences between the low- and high-grade groups (p ≥ 0.05). CONCLUSION: Hepatic fibrosis stage can influence APHE but showed no impact on the CEUS LI-RADS classification, whereas the histological grade of HCC influenced the LR-5 and LR-TIV categories. KEY POINTS: • Histological grade influenced CEUS LR-5 and LR-TIV category (p = 0.013 and p = 0.035 respectively). Low-grade HCCs occurred more frequently in LR-5 category whereas high-grade HCCs occurred more frequently in LR-TIV category. • Fibrosis stage shows significant influence on APHE on HCCs of the size ≥ 2 cm and low-grade group (p = 0.027 and p = 0.003, respectively). • Hepatic fibrosis stage and HCC histological grade exhibited limited impact on CEUS LI-RADS. CEUS LI-RADS may be feasible for diagnosing HCC in patients regardless of histological grade and fibrosis stage.

Inter-reader agreement of CEUS LI-RADS among radiologists with different levels of experience.

OBJECTIVES: To investigate the inter-reader agreement of contrast-enhanced ultrasound (CEUS) of Liver Imaging Reporting and Data System version 2017 (LI-RADS v2017) categories among radiologists with different levels of experience. MATERIALS AND METHODS: From January 2014 to December 2014, a total of 326 patients at high risk of hepatocellular carcinoma (HCC) who underwent CEUS were included in this retrospective study. All lesions were classified according to LI-RADS v2017 by six radiologists with different levels of experiences: two residents, two fellows, and two specialists. Kappa coefficient was used to assess consistency of LI-RADS categories and major features among radiologists with different levels of experience. The diagnostic performance of HCC was described by accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC). RESULTS: Inter-reader agreement among radiologists of different experience levels was substantial agreement for arterial phase hyperenhancement, washout appearance, and early or late washout. Inter-reader agreement for LI-RADS categories was moderate to substantial. When LR-5 was used as criteria to determinate HCC, the AUC of LI-RADS for HCC was 0.67 for residents, 0.72 for fellows, and 0.78 for specialist radiologists. When compared between residents and specialists, accuracy, sensitivity, and AUC were significantly different (all p < 0.05). However, there were no significant differences in specificity, PPV, and NPV between the two groups. CONCLUSION: CEUS LI-RADS showed good diagnostic consistency among radiologists with different levels of experience, and consistency increased with experience levels. KEY POINTS: • The inter-reader agreement for LI-RADS categories was moderate to substantial agreement (κ, 0.60-0.80). • When compared between residents and specialists, accuracy, sensitivity, and AUC showed significantly different (all p < 0.05). However, there were no significant differences for specificity, PPV, and NPV between these two groups. • Among the radiologists with more than 1 year of experience, there was no significant difference in the diagnostic performance of HCC, suggesting that CEUS LI-RADS is a good standardized categorization system for high-risk patients.

Artificial intelligence assists identifying malignant versus benign liver lesions using contrast-enhanced ultrasound.

BACKGROUND AND AIM: This study aims to construct a strategy that uses assistance from artificial intelligence (AI) to assist radiologists in the identification of malignant versus benign focal liver lesions (FLLs) using contrast-enhanced ultrasound (CEUS). METHODS: A training set (patients = 363) and a testing set (patients = 211) were collected from our institute. On four-phase CEUS images in the training set, a composite deep learning architecture was trained and tuned for differentiating malignant and benign FLLs. In the test dataset, AI performance was evaluated by comparison with radiologists with varied levels of experience. Based on the comparison, an AI assistance strategy was constructed, and its usefulness in reducing CEUS interobserver heterogeneity was further tested. RESULTS: In the test set, to identify malignant versus benign FLLs, AI achieved an area under the curve of 0.934 (95% CI 0.890-0.978) with an accuracy of 91.0%. Comparing with radiologists reviewing videos along with complementary patient information, AI outperformed residents (82.9-84.4%, P = 0.038) and matched the performance of experts (87.2-88.2%, P = 0.438). Due to the higher positive predictive value (PPV) (AI: 95.6% vs residents: 88.6-89.7%, P = 0.056), an AI strategy was defined to improve the malignant diagnosis. With the assistance of AI, radiologists exhibited a sensitivity improvement of 97.0-99.4% (P < 0.05) and an accuracy of 91.0-92.9% (P = 0.008-0.189), which was comparable with that of the experts (P = 0.904). CONCLUSIONS: The CEUS-based AI strategy improved the performance of residents and reduced CEUS's interobserver heterogeneity in the differentiation of benign and malignant FLLs.

Percutaneous thermal ablation of hepatic tumors: local control efficacy and risk factors for artificial ascites failure.

OBJECTIVE: To investigate the risk factors affecting the technical failure of artificial ascites (AA) formation and to evaluate the local control efficacy of percutaneous thermal ablation assisted by the AA for hepatic tumors. METHODS: A total of 341 patients with 362 hepatic tumors who underwent thermal ablation assisted by AA were reviewed retrospectively. The technical success of AA, the volume of liquid, and local efficacy after ablation were assessed. Predictive factors for the technical failure of AA formation and local tumor progression (LTP) were analyzed using univariate and multivariate analysis. RESULTS: The technical success rate of AA formation was 81.8% (296/362). The amount of fluid was higher when the tumor was located in the left lobe of the liver than when it was located in the right lobe (median 950 ml versus 700 ml, p < 0.001). Previous hepatic resection (OR: 12.63, 95% CI: 2.93-54.45, p < 0.001), ablation (OR: 6.48, 95% CI: 1.36-30.92, p = 0.019) and upper-abdomen surgery (OR: 11.34, 95% CI: 1.96-65.67, p = 0.007) were the independent risk factors of AA failure. In the AA success group, the complete ablation rate was higher and the LTP rate was lower than that in the AA failure group (98.7 versus 92.4%, p = 0.012; 8.8 versus 21.2%, p = 0.004). Multivariate analysis identified AA failure (p = 0.004), tumor size (>3.0 cm) (p = 0.002) and metastatic liver tumor (p = 0.008) as independent risk factors for LTP. CONCLUSION: History of hepatic resection, ablation and upper abdomen surgery were significant predictive factors affecting the technical failure of AA formation. Successful introduction of AA before thermal ablation can achieve better local tumor control efficacy.