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.

Feasibility and Measurement Value of Pancreatic 2-D Shear Wave Elastography in Healthy Adults: Evaluation, Influencing Factors, Reference Range, Measurement Stability and Reproducibility.

OBJECTIVE: The present study was aimed at assessing the success rate and measurement value, determining the influencing factors and reference range and examining the intra-operator stability and inter-operator reproducibility of pancreatic 2-D shear wave elastography (SWE) measurement in healthy adults. METHODS: In 2022, 387 healthy adults were prospectively recruited. Logistic regression and linear regression analyses were used to explore the factors influencing the success rate and the measurement value of pancreatic 2-D SWE measurement, respectively. A two-sided 95% reference range was estimated accordingly. The intraclass correlation coefficient was calculated to evaluate the intra-operator stability and inter-operator reproducibility of the pancreatic 2-D SWE measurement. RESULTS: The pancreatic body (89.6%) bore the highest while the tail (72.8%) bore the lowest success rate of pancreatic 2-D SWE measurement. Sex and body mass index (BMI) were the independent factors influencing measurement success rate in all three parts of the pancreas. Mean measurement values (Emean) were not the same in the three parts of the pancreas of the same participant. BMI and image depth were the independent factors influencing Emean in the pancreatic body, while region of interest depth and BMI were the only independent factors influencing Emean in the pancreatic head and tail, respectively. The intra-operator stability of pancreatic 2-D SWE measurement was found to be excellent, whereas its inter-operator reproducibility was poor to good. CONCLUSION: Pancreatic 2-D SWE is a reliable technique for evaluating pancreatic stiffness in healthy adults, but its success rate and measurement value are influenced by multiple factors.

A Two-stage Diagnostic Framework for Post-ablation Treatment Response Assessment in Patients with Hepatocellular Carcinoma.

Contrast-enhanced ultrasound (CEUS) video plays an important role in post-ablation treatment response assessment in patients with hepatocellular carcinoma (HCC). However, the assessment of treatment response using CEUS video is challenging due to issues such as high inter-frame data repeatability, small ablation area and poor imaging quality of CEUS video. To address these issues, we propose a two-stage diagnostic framework for post-ablation treatment response assessment in patients with HCC using CEUS video. The first stage is a location stage, which is used to locate the ablation area. At this stage, we propose a Yolov5-SFT to improve the location results of the ablation area and a similarity comparison module (SCM) to reduce data repeatability. The second stage is an assessment stage, which is used for the evaluation of postoperative efficacy. At this stage, we design an EfficientNet-SK to improve assessment accuracy. The Experimental results on the self-collected data show that the proposed framework outperforms other selected algorithms, and can effectively assist doctors in the assessment of post-ablation treatment response.

Complementary Role of CEUS and CT/MR LI-RADS for Diagnosis of Recurrent HCC.

PURPOSE: We retrospectively compared the diagnostic performance of contrast-enhanced ultrasonography (CEUS) and contrast-enhanced computer tomography-magnetic resonance imaging (CT/MRI) for recurrent hepatocellular carcinoma (HCC) after curative treatment. MATERIALS AND METHODS: After curative treatment with 421 ultrasound (US) detected lesions, 303 HCC patients underwent both CEUS and CT/MRI. Each lesion was assigned a Liver Imaging Reporting and Data System (LI-RADS) category according to CEUS and CT/MRI LI-RADS. Receiver-operating characteristic (ROC) curves were computed to determine the optimal diagnosis algorithms for CEUS, CT and MRI. The diagnostic accuracy, sensitivity, specificity, and area under the curve (AUC) were compared between CEUS and CT/MRI. RESULTS: Among the 421 lesions, 218 were diagnosed as recurrent HCC, whereas 203 lesions were diagnosed as benign. In recurrent HCC, CEUS detected more arterial hyperenhancement (APHE) and washout than CT and more APHE than MRI. CEUS yielded better diagnostic performance than CT (AUC: 0.981 vs. 0.958) (p = 0.024) comparable diagnostic performance to MRI (AUC: 0.952 vs. 0.933) (p > 0.05) when using their optimal diagnostic criteria. CEUS missed 12 recurrent HCCs, CT missed one, and MRI missed none. The detection rate of recurrent HCC on CEUS (94.8%, 218/230) was lower than that on CT/MRI (99.6%, 259/260) (p = 0.001). Lesions located on the US blind spots and visualization score C would hinder the ability of CEUS to detect recurrent HCC. CONCLUSION: CEUS demonstrated excellent diagnostic performance but an inferior detection rate for recurrent HCC. CEUS and CT/MRI played a complementary role in the detection and characterization of recurrent HCC.

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.

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.

Integration of Artificial Intelligence Decision Aids to Reduce Workload and Enhance Efficiency in Thyroid Nodule Management.

Importance: To optimize the integration of artificial intelligence (AI) decision aids and reduce workload in thyroid nodule management, it is critical to incorporate personalized AI into the decision-making processes of radiologists with varying levels of expertise. Objective: To develop an optimized integration of AI decision aids for reducing radiologists' workload while maintaining diagnostic performance compared with traditional AI-assisted strategy. Design, Setting, and Participants: In this diagnostic study, a retrospective set of 1754 ultrasonographic images of 1048 patients with 1754 thyroid nodules from July 1, 2018, to July 31, 2019, was used to build an optimized strategy based on how 16 junior and senior radiologists incorporated AI-assisted diagnosis results with different image features. In the prospective set of this diagnostic study, 300 ultrasonographic images of 268 patients with 300 thyroid nodules from May 1 to December 31, 2021, were used to compare the optimized strategy with the traditional all-AI strategy in terms of diagnostic performance and workload reduction. Data analyses were completed in September 2022. Main Outcomes and Measures: The retrospective set of images was used to develop an optimized integration of AI decision aids for junior and senior radiologists based on the selection of AI-assisted significant or nonsignificant features. In the prospective set of images, the diagnostic performance, time-based cost, and assisted diagnosis were compared between the optimized strategy and the traditional all-AI strategy. Results: The retrospective set included 1754 ultrasonographic images from 1048 patients (mean [SD] age, 42.1 [13.2] years; 749 women [71.5%]) with 1754 thyroid nodules (mean [SD] size, 16.4 [10.6] mm); 748 nodules (42.6%) were benign, and 1006 (57.4%) were malignant. The prospective set included 300 ultrasonographic images from 268 patients (mean [SD] age, 41.7 [14.1] years; 194 women [72.4%]) with 300 thyroid nodules (mean [SD] size, 17.2 [6.8] mm); 125 nodules (41.7%) were benign, and 175 (58.3%) were malignant. For junior radiologists, the ultrasonographic features that were not improved by AI assistance included cystic or almost completely cystic nodules, anechoic nodules, spongiform nodules, and nodules smaller than 5 mm, whereas for senior radiologists the features that were not improved by AI assistance were cystic or almost completely cystic nodules, anechoic nodules, spongiform nodules, very hypoechoic nodules, nodules taller than wide, lobulated or irregular nodules, and extrathyroidal extension. Compared with the traditional all-AI strategy, the optimized strategy was associated with increased mean task completion times for junior radiologists (reader 11, from 15.2 seconds [95% CI, 13.2-17.2 seconds] to 19.4 seconds [95% CI, 15.6-23.3 seconds]; reader 12, from 12.7 seconds [95% CI, 11.4-13.9 seconds] to 15.6 seconds [95% CI, 13.6-17.7 seconds]), but shorter times for senior radiologists (reader 14, from 19.4 seconds [95% CI, 18.1-20.7 seconds] to 16.8 seconds [95% CI, 15.3-18.3 seconds]; reader 16, from 12.5 seconds [95% CI, 12.1-12.9 seconds] to 10.0 seconds [95% CI, 9.5-10.5 seconds]). There was no significant difference in sensitivity (range, 91%-100%) or specificity (range, 94%-98%) between the 2 strategies for readers 11 to 16. Conclusions and Relevance: This diagnostic study suggests that an optimized AI strategy in thyroid nodule management may reduce diagnostic time-based costs without sacrificing diagnostic accuracy for senior radiologists, while the traditional all-AI strategy may still be more beneficial for junior radiologists.

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.

Prevalence of breast fibroadenoma in healthy physical examination population in Guangdong province of China: a cross-sectional study.

OBJECTIVE: To provide an accurate assessment of the prevalence of breast fibroadenoma in a large population and to confirm the diagnostic accuracy of ultrasound for fibroadenoma. DESIGN: This was a cross-sectional survey. SETTING: This research was conducted at Nanfang Hospital, Guangzhou, Guangdong, China. PARTICIPANTS: A total of 11 898 women aged 18-40 years who underwent breast screening between 1 January 2019 and 31 December 2019 were included in the fibroadenoma prevalence study. From 1 June 2019 to 31 December 2019, 342 breast lesions with pathology reports and preoperative ultrasound images were collected for diagnostic fibroadenoma testing (vs histological diagnostic testing). PRIMARY OUTCOME MEASURES: Pearson's χ2 test was performed to compare the prevalence of different lesions between age groups, and descriptive statistics were used to report the clinical characteristics of fibroadenoma. For ultrasound diagnosis, fibroadenoma was defined as a well-circumscribed lesion with round or oval shape, consisting of a homogeneously hypoechoic or isoechoic solid mass, located parallel to the chest wall with a smooth margin and no posterior shadowing. Diagnostic test results for breast fibroadenoma were stratified by diagnostic type (histological vs ultrasound). RESULTS: Of the women aged 18-40 years, 27.6% (3285/11 898) had an ultrasound diagnosis offibroadenoma. Of these, the prevalence of fibroadenoma was stable across age groups (p=0.14) and did not differ between the left and right sides of the breast. Almost two-thirds of women presented with a single fibroadenoma, and most fibroadenomas did not exceed 1 cm in size. The sensitivity and specificity for fibroadenoma were 97.0% (95% CI for sensitivity: 93.7% to 98.8%) and 91.4% (95% CI for specificity: 85.4% to 95.5%) for ultrasonography, respectively. CONCLUSIONS: The prevalence of fibroadenoma in South China is as high as 27.6%, and ultrasound could be used as a tool to diagnose fibroadenoma.

Application of the CT/MRI LI-RADS Treatment Response Algorithm to Contrast-Enhanced Ultrasound: A Feasibility Study.

Purpose: The contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) treatment response algorithm (TRA) is still in development. The aim of this study was to explore whether the CT/MRI LI-RADS TRA features were applicable to CEUS in evaluating the liver locoregional therapy (LRT) response. Patients and Methods: This study was a retrospective review of a prospectively maintained database of patients with hepatocellular carcinoma undergoing ablation between July 2017 and December 2018. The standard criteria for a viable lesion were a histopathologically confirmed or typical viable appearance in the follow-up CT/MRI. Performance of the LI-RADS TRA assessing tumor viability was then compared between CEUS and CT/MRI. Inter-reader association was calculated. Results: A total of 244 patients with 389 treated observations (118 viable) were evaluated. The sensitivity and specificity of the CEUS TRA and CT/MRI LI-RADS TRA viable categories for predicting viable lesions were 55.0% (65/118) versus 56.8% (67/118) (P = 0.480) and 99.3% (269/271) versus 96.3% (261/271) (P = 0.013), respectively. The PPV of CEUS was higher than that of CT/MRI (97.0% vs 87.0%). Subgroup analysis showed that the sensitivity was low in the 1-month assessment for both CEUS (38.1%, 16/42) and CT/MR (47.6%, 20/42) and higher in the 2-6-month assessment for both CEUS (65.7%, 23/35) and CT/MR (62.9%, 22/35). Interobserver agreements were substantial for both CEUS TRA and CT/MRI LI-RADS TRA (κ, 0.74 for both). Conclusion: The CT/MRI LI-RADS TRA features were applicable to CEUS TRA for liver locoregional therapy. The CEUS TRA for liver locoregional therapy has sufficiently high specificity and PPV to diagnose the viability of lesions after ablation.

Cardiovascular risk factors and breast cancer incidence in a large middle-aged cohort study.

BACKGROUND: Several studies have demonstrated that cardiovascular risk factors play a role in the etiology of breast cancer. However, the combined effect of cardiovascular risk factors on the risk of breast cancer is still uncertain. METHODS: Data from the Atherosclerosis Risk in Communities (ARIC) study, a prospective cohort of middle-aged women, were used to investigate the association of individual and combined cardiovascular risk factors with breast cancer. Cox proportional hazards models were applied to calculate the hazard ratio (HR) and 95% confidence intervals (CI). RESULTS: A total of 7501 women were included. During a mean follow-up of 19.7 years, 576 women were diagnosed with breast cancer. White women and premenopausal status were independently associated with increased risk of breast cancer. Of the individual cardiovascular risk factors, only obesity was independently associated with an increased risk of breast cancer (HR 1.29, 95% CI 1.04-1.61). Compared with women without cardiovascular risk factors, women having three or greater, but not those with fewer than three cardiovascular risk factors, had a significantly higher risk of developing breast cancer (HR 1.27, 95% CI 1.06-1.53). Subgroup analyses indicated that women with three or greater cardiovascular risk factors had higher risk of breast cancer among postmenopausal Black women, but not among premenopausal Black and White women. CONCLUSIONS: Combinations of cardiovascular risk factors are associated with increased risk of breast cancer in middle-aged women, especially in postmenopausal Black women. Joint interventions to modify cardiovascular risk factors could be used to prevent breast cancer in these higher-risk individuals.

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.

An assessment of liver lesions using a combination of CEUS LI-RADS and AFP.

PURPOSE: To improve noninvasive diagnosis of HCC using a combination of CE US LI-RADS and alpha-fetoprotein (AFP). METHODS: 757 solitary liver nodules from 757 patients at risk of HCC with CE US and serum AFP test were categorized as LR-1 to LR-5 through LR-M according to CE US LI-RADS version 2017. In LR-3, LR-4, and LR-M nodules, those with AFP > 200 ng/ml were reclassified as mLR-5. Nodules with LR-5 and mLR-5 were reclassified as definitely HCC to modify CE US LI-RADS. Diagnostic performance was assessed with specificity, sensitivity, and PPV. RESULTS: The sensitivity, specificity, and PPV of LR-5 as a predictor of HCC were 64.7%, 97.8%, and 98.9%, respectively. 32.1% patients with solitary liver nodule had AFP greater than 200 ng/ml, of which 98.8% were HCC (25.8%, 7.5%, 2.5% assigned to LR-M, LR-4, LR-3, respectively) and 1.2% were Combined Hepatocellular Cholangiocarcinoma. After modification, the sensitivity increased to 79.6% (P < 0.001), while specificity and PPV remained high (96.6% and 98.7%, P > 0.050). CONCLUSION: The combination of CE US LI-RADS and AFP for diagnosing HCC improved diagnostic sensitivity significantly, while maintaining high PPV and specificity in patients with the solitary liver nodule.

Can monodisperse microbubble-based three-dimensional contrast-enhanced ultrasound reduce quantitative heterogeneity? An in vitro study.

BACKGROUND: Heterogeneity within the tumor may cause large heterogeneity in quantitative perfusion parameters. Three-dimensional contrast-enhanced ultrasound (3D-CEUS) can show the spatial relationship of vascular structure after post-acquisition reconstruction and monodisperse bubbles can resonate the ultrasound pulse, resulting in the increase in sensitivity of CEUS imaging. OBJECTIVES: To evaluate whether the combination of 3D-CEUS and monodisperse microbubbles could reduce the heterogeneity of quantitative CEUS. MATERIAL AND METHODS: Three in vitro perfusion models with perfusion volume ratio of 1:2:4 were set up. Both quantitative 2D-CEUS and 3D-CEUS were used to acquire peak intensity (PI) with 2 kinds of ultrasound agents. One was a new kind of monodisperse bubbles produced in this study, named Octafluoropropane-loaded cerasomal microbubbles (OC-MBs), the other was SonoVue®. The coefficient of variation (CV) was calculated to evaluate the cross-sectional variability. Pearson's correlation analysis was used to assess the correlation between weighted PIs (average of PIs of 3 different planes) and perfusion ratios. RESULTS: The average CVs of quantitative 3D-CEUS was slightly lower than that of 2D-CEUS (0.41 ±0.17 compared to 0.55 ±0.26, p = 0.3592). As for quantitative 3D-CEUS, the PI of the OC-MBs has shown better stability than that of SonoVue®, but without a significant difference (average CVs: 0.32 ±0.19 compared to 0.50 ±0.10, p = 0.0711). In the 2D-CEUS condition, the average CVs of OC-MBs group and SonoVue® group were 0.68 ±0.15 and 0.41 ±0.17 (p = 0.2747). As for 3D-CEUS condition, using OC-MBs group and SonoVue®, the r-values of the weighted PI and perfusion ratio were 0.8685 and 0.5643, respectively, while that of 2D-CEUS condition were 0.7760 and 0.3513, respectively. CONCLUSIONS: Our in vitro experiments showed that OC-MBs have the potential in acquiring more stable quantitative CEUS value, as compared to the SonoVue® in 3D-CEUS condition. The combination of 3D-CEUS and OC-MBs can reflect perfusion volume more precisely and may be a potential way to reduce quantitative heterogeneity.

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.

Contrast-enhanced ultrasound-based ultrasomics score: a potential biomarker for predicting early recurrence of hepatocellular carcinoma after resection or ablation.

OBJECTIVES: This study aimed to construct a prediction model based on contrast-enhanced ultrasound (CEUS) ultrasomics features and investigate its efficacy in predicting early recurrence (ER) of primary hepatocellular carcinoma (HCC) after resection or ablation. METHODS: This study retrospectively included 215 patients with primary HCC, who were divided into a developmental cohort (n = 139) and a test cohort (n = 76). Four representative images-grayscale ultrasound, arterial phase, portal venous phase and delayed phase-were extracted from each CEUS video. Ultrasomics features were extracted from tumoral and peritumoral area inside the region of interest. Logistic regression was used to establish models, including a tumoral model, a peritumoral model and a combined model with additional clinical risk factors. The performance of the three models in predicting recurrence within 2 years was verified. RESULTS: The combined model performed best in predicting recurrence within 2 years, with an area under the curve (AUC) of 0.845, while the tumoral model had an AUC of 0.810 and the peritumoral model one of 0.808. For prediction of recurrence-free survival, the 2-year cumulative recurrence rate was significant higher in the high-risk group (76.5%) than in the low-risk group (9.5%; p < 0.0001). CONCLUSION: These CEUS ultrasomics models, especially the combined model, had good efficacy in predicting early recurrence of HCC. The combined model has potential for individual survival assessment for HCC patients undergoing resection or ablation. ADVANCES IN KNOWLEDGE: CEUS ultrasomics had high sensitivity, specificity and PPV in diagnosing early recurrence of HCC, and high efficacy in predicting early recurrence of HCC (AUC > 0.8). The combined model performed better than the tumoral ultrasomics model and peritumoral ultrasomics model in predicting recurrence within 2 years. Recurrence was more likely to occur in the high-risk group than in the low-risk group, with 2-year cumulative recurrence rates, respectively, 76.5% and 9.5% (p < 0.0001).

Contrast-enhanced US diagnostic algorithm of hepatocellular carcinoma in patients with occult hepatitis B.

PURPOSE: To assess the diagnostic performance of contrast-enhanced (CE) US Liver Imaging Reporting and Data System (LI-RADS) version 2017 and propose a diagnostic algorithm in diagnosing hepatocellular carcinoma (HCC) in patients with occult HBV infection (OBI). METHODS: 251 OBI patients with 251 newly diagnosed focal liver lesions were retrospectively enrolled. Each nodule was evaluated according to CEUS LI-RADS. The subgroup analyses were also performed in patients with alpha-fetoprotein (AFP) more than 20ug/L or not. Diagnostic performance of CEUS LI-RADS for diagnosing HCC was validated via sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV), respectively. RESULTS: There were 90 HCCs (90 of 251, 35.9%), of which 2 (2.0%), 53 (53.5%), and 35 (35.4%) were classified as LR-4, LR-5, and LR-M, respectively. The sensitivity, specificity, accuracy, PPV, and NPV of CEUS LR-5 for HCC diagnosis were 58.9%, 88.8%, 78.1%, 74.6%, and 79.4%, respectively. AFP increased in 50.6% (45/89) HCCs. Using a proposed diagnostic algorithm (for OBI patients with AFP more than 20 ug/L, LR-5 nodules were diagnosed as definitely HCC), the sensitivity, specificity, accuracy, PPV, and NPV were 62.2%, 71.4%, 63.5%, 93.3%, and 22.7%, respectively. Therefore, 12.2% (30 of 246) nodules could be confirmed as HCC by CEUS without biopsy. CONCLUSION: HCC diagnosis in patients with OBI is challenging. However, using LR-5 as a noninvasively diagnostic standard in OBI patients with AFP more than 20ug/L, HCC could be confirmed by CEUS without biopsy.

RGB Three-Channel SWE-Based Ultrasomics Model: Improving the Efficiency in Differentiating Focal Liver Lesions.

OBJECTIVE: To explore a new method for color image analysis of ultrasomics and investigate the efficiency in differentiating focal liver lesions (FLLs) by Red, Green, and Blue (RGB) three-channel SWE-based ultrasomics model. METHODS: One hundred thirty FLLs were randomly divided into training set (n = 65) and validation set (n = 65). The RGB three-channel and direct conversion methods were applied to the same color SWE images. Ultrasomics features were extracted from the preprocessing images establishing two feature data sets. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. Two models, named RGB model (based on RGB three-channel conversion) and direct model (based on direct conversion), were used to differentiate FLLs. The diagnosis performance of the two models was evaluated by area under the curve (AUC), calibration curves, decision curves, and net reclassification index (NRI). RESULTS: In the validation cohort, the AUC of the direct model and RGB model in characterization on FLLs were 0.813 and 0.926, respectively (p = 0.038). Calibration curves and decision curves indicated that the RGB model had better calibration efficiency and provided greater clinical benefits. NRI revealed that the RGB model correctly reclassified 7% of malignant cases and 25% of benign cases compared to the direct model (p = 0.01). CONCLUSION: The RGB model generated by RGB three-channel method yielded better diagnostic efficiency than the direct model established by direct conversion method. The RGB three-channel method may be promising on ultrasomics analysis of color images in clinical application.

MAPK4 silencing together with a PARP1 inhibitor as a combination therapy in triple­negative breast cancer cells.

Triple­negative breast cancer (TNBC) is the most common type of cancer among females worldwide and is associated with poor prognosis. Poly ADP­ribose polymerase­1 (PARP1) inhibitors are effective against TNBC with mutations in the breast cancer type 1 susceptibility protein (BRCA1) and/or BRCA2 genes; however, the development of resistance to PARP1 inhibitors limits their use. Thus, identifying strategies to overcome this resistance is urgently required. The aim of the present study was to investigate the potential function and mechanism of small interfering (si)RNA­MAPK4 (siMAPK4) in enhancing the efficacy of a PARP1 inhibitor and reducing the resistance. In the present study, data on the mRNA expression level of MAPK4 in normal breast tissues and TNBC tissues were obtained from The Cancer Genome Atlas database. The mRNA and protein expression levels of MAPK4 in normal breast cells and TNBC cells were analyzed using reverse transcription­quantitative PCR and western blotting, respectively. The phosphorylated (p) histone H2AX (γH2AX) protein expression was assessed via immunofluorescence. Cell Counting Kit­8, wound healing and TUNEL assays were used to determine the proliferative, migratory and apoptotic abilities of HCC1937 cells. MAPK4 was highly expressed in TNBC patient tissues and cell lines. Moreover, overexpression of MAPK4 could promote HCC1937 cell proliferation. Treatment of HCC1937 cells with the combination of siMAPK4 and a PARP1 inhibitor olaparib decreased their proliferation and migration and increased their apoptosis. The protein expression levels of the DNA repair­related proteins p­DNA­dependent protein kinase catalytic subunit (DNA­PK) and RAD51 recombinase (RAD51) were inhibited in the siMAPK4 and siMAPK4 + olaparib groups. However, the marker of a double­stranded break γH2AX showed increased protein expression in the siMAPK4 + olaparib group. As MAPK4 could phosphorylate AKT at threonine 308 (AKTT308), the current study restored p­AKTT308 using a constitutively active AKT plasmid (AKT­CA). p­DNA­PK and RAD51 showed high expression and γH2AX exhibited lower protein expression in the AKT­CA group. The present findings suggested that siMAPK4 can enhance the sensitivity of TNBC cells to PARP1 inhibitors.

Can repeat IVF/ICSI cycles compensate for the natural decline in fertility with age? an estimate of cumulative live birth rates over multiple IVF/ICSI cycles in Chinese advanced-aged population.

In order to find out to what extent ovarian aging could be compensated by the in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) treatments, a total of 4102 women above the age of 35 undergoing 6489 complete cycles from 2009 to 2015 with follow-up visits until 2017 were retrospectively analyzed. Cumulative live birth rates (CLBRs) across multiple IVF/ICSI cycles were compared in the study population stratified by age and ovarian reserve (classified by the POSEIDON criteria). Younger patients (aged between 35 and 40) could well benefit from repeat IVF treatments, with the optimal CLBRs ranging from 62%-72% for up to four complete cycles. However, the CLBRs sharply declined to 7.7%-40% in older patients (>40yrs). In light of ovarian reserve, the optimal-estimated-four-cycle CLBR of younger patients (35-40yrs) in POSEIDON group 2 could approached to those with normal ovarian response (non-POSEIDON), with 57.3%-70% versus 74.5%-81% respectively. However, the CLBR of older patients (>40yrs) in POSEIDON group 2 only reached 50% of their counterparts. Extending the number of IVF cycles beyond three or four is effective for advanced-aged women, especially in younger normal responders (non-POSEIDON) and unexpected poor/suboptimal responders (POSEIDON group 2). The real turning point at which female fecundity dropped after multiple IVF cycles is at the age of 40.