Radiating blood flow signal: A new ultrasound feature of thyroid carcinoma.

OBJECTIVE: To summary radiating blood flow signals and evaluate their diagnostic value in differentiating benign and malignant thyroid nodules. MATERIALS AND METHODS: We retrospectively recruited consecutive patients undergoing US at 4 hospitals from 2018 to 2022. In a training dataset, the correlations of US features with malignant thyroid nodules were assessed by multivariate logistic analysis. Multivariate logistic regression models involving the ACR TI-RADS score, radiating blood flow signals and their combination were built and validated internally and externally. The AUC with 95% asymptotic normal confidence interval as well as sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) with 95% exact binomial confidence intervals were calculated. RESULTS: Among 2475 patients (1818 women, age: 42.47 ± 11.57; 657 men, age: 42.16 ± 11.69), there were 3187 nodules (2342 malignant nodules and 845 benign nodules). Radiating blood flow signals were an independent risk factor for diagnosing thyroid carcinoma. In the training set, the AUC of the model using the combination of radiating blood flow signals and the ACR TI-RADS score (0.95 95 % CI: [0.94, 0.97]; P < 0.001) was significantly higher than that of the ACR TI-RADS model (0.91 [0.89, 0.93]). In the two internal validation sets and the external validation set, the AUCs of the combination model were 0.97 [0.96, 0.98], 0.92 [0.88, 0.96], and 0.91 [0.86, 0.95], respectively, and were all significantly higher than that of the ACR TI-RADS score (0.92 [0.90, 0.95], 0.86 [0.81, 0.91], 0.84 [0.79, 0.89]; P < 0.001). CONCLUSION: Radiating blood flow is a new US feature of thyroid carcinomas that can significantly improve the diagnostic performance vs. the ACR TI-RADS score.

Itaconate inhibits corticosterone-induced necroptosis and neuroinflammation via up-regulating menin in HT22 cells.

Corticosterone (CORT) damages hippocampal neurons as well as induces neuroinflammation. The tricarboxylic acid cycle metabolite itaconate has an anti-inflammatory role. Necroptosis is a form of programmed cell death, also known as inflammatory cell death. Menin is a multifunctional scaffold protein, which deficiency aggravates neuroinflammation. In this study, we explored whether itaconate inhibits CORT-induced neuroinflammation as well as necroptosis and further investigated the mediatory role of Menin in this protective effect of itaconate by using an exposure of CORT to HT22 cells (a hippocampal neuronal cell line). The viability of HT22 cells was examined by the cell counting kit 8 (CCK-8). The morphology of HT22 cells was observed by transmission electron microscope (TEM). The expressions of necroptosis-related proteins (p-RIP1/RIP1, p-RIP3/RIP3, and p-MLKL/MLKL) were evaluated by western blotting. The contents of inflammatory factors were detected by an enzyme-linked immunosorbent assay (ELISA) kit. Our results showed that CORT increases the contents of pro-inflammatory factors (IL-1ß, TNF-α) as well as decreases the contents of anti-inflammatory factors (IL-4, IL-10) in HT22 cells. We also found that CORT increases the expressions of necroptosis-related proteins (p-RIP1/RIP1, p-RIP3/RIP3, and p-MLKL/MLKL) and decreases the cell viability in HT22 cells, indicating that CORT induces necroptosis in HT22 cells. Itaconate improves CORT-induced neuroinflammation and necroptosis. Furthermore, itaconate upregulates the expression of Menin in CORT-exposed HT22 cells. Importantly, silencing Menin abolishes the antagonistic effect of itaconate on CORT-induced necroptosis and neuroinflammation. In brief, these results indicated that itaconate protects HT22 cells against CORT-induced neuroinflammation and necroptosis via upregulating Menin.

Isthmin: A multifunctional secretion protein.

Isthmin is a polypeptide secreted by adipocytes that was first detected in Xenopus gastrula embryos. Recent studies have focused on the biological functions of isthmin in growth and development, angiogenesis, and metabolism. Distinct spatiotemporal expression of isthmin-1 (ISM-1) was observed during growth and development. ISM-1 plays an important role in the occurrence and development of cancer by regulating cell proliferation, migration, angiogenesis, and immune microenvironments. Moreover, ISM-1, as a newly identified insulin-like adipokine, increases adipocyte glucose uptake and inhibits hepatic lipid synthesis. However, the biological function of ISM-1 remains largely unknown. In this review, we highlight the structure and physiological functions of isthmin and explore its application potential, contributing to a better understanding of its function and providing prevention and treatment strategies for various diseases.

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.

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.

Diagnostic Performance of Quantitative and Qualitative Elastography for Axillary Lymph Node Metastasis in Breast Cancer: A Systematic Review and Meta-Analysis.

Background: Studies have shown inconsistent results regarding the diagnostic performance of ultrasound elastography for axillary lymph node metastasis (ALNM) in breast cancer. This meta-analysis aimed to estimate the diagnostic performance of ultrasound elastography (divided into quantitative and qualitative elastography) for ALNM in patients with breast cancer. Methods: The PubMed and Embase databases were searched for eligible studies exploring the diagnostic performance of ultrasound elastography for ALNM in patients with breast cancer. The included studies were divided into quantitative and qualitative elastography groups to perform separate meta-analyses. The diagnostic performance was investigated with pooled sensitivity and specificity and diagnostic odds ratio (DOR) using a bivariate mixed-effects regression model. A summary receiver operating characteristic curve was constructed, and the area under the curve (AUC) was calculated. Results: Seven and 11 studies were included in the quantitative and qualitative elastography meta-analyses, respectively. The pooled sensitivity and specificity, DOR, and AUC with their corresponding 95% confidence intervals were 0.82 (0.75, 0.87), 0.88 (0.78, 0.93), 33 (13, 83), and 0.89 (0.86, 0.91), respectively, for quantitative elastography and 0.81 (0.69, 0.89), 0.92 (0.79, 0.97), 46 (12, 181), and 0.92 (0.89, 0.94), respectively, for qualitative elastography. No significant publication bias existed. Fagan plots demonstrated good clinical utility. However, substantial heterogeneity existed among studies. Study design, measurement, and reference standard served as potential sources of heterogeneity for quantitative studies, which were measurement and reference standard for qualitative studies. Conclusions: Both quantitative and qualitative elastography seem to be feasible, non-invasive diagnostic tools for ALNM in breast cancer. Nevertheless, the results must be interpreted carefully, paying attention to heterogeneity issues, especially for quantitative elastography studies.

Malignancy risk stratification and FNA recommendations for thyroid nodules: A comparison of ACR TI-RADS, AACE/ACE/AME and ATA guidelines.

OBJECTIVE: To compare diagnostic performance and malignancy risk stratification among guidelines set forth by the American Thyroid Association (ATA) in 2015, the American Association of Clinical Endocrinologists (AACE), the American College of Endocrinology (ACE) and the Association Medici Endocrinologi (AME) in 2016, and the American College of Radiology (ACR) in 2017. METHODS: The retrospective study was approved by the hospital ethics committee, and the informed consent requirement was waived. From October 2015 to March 2016, a total of 230 patients with 230 consecutive thyroid nodules were enrolled in this study. Each nodule was classified by one junior and one senior radiologist separately according to ACR TI-RADS, AACE/ACE/AME and ATA guidelines. The malignancy diagnostic performance and the number of FNA recommendations were pairwise compared among three guidelines using chi-square tests. RESULTS: Of the 230 thyroid nodules, 137 were malignant, and 93 were benign. However, 19.6% of the nodules (45 of 230) did not match any pattern using the ATA guidelines but with a high risk of malignancy (68.9%). The ACR TI-RADS derived the highest diagnostic performance, from both junior radiologist (AUC 0.815) and senior radiologist (AUC 0.864). The ACR guidelines also showed the greatest level of sensitivity (junior: 86.1%, senior: 94.9%), compared with AACE/ACE/AME and ATA guidelines. The number of thyroid nodules recommended to fine-needle aspiration (FNA) was the lowest (37.8%, 40.4%) by ACR TI-RADS, and meanwhile, the malignant detection rate within these nodules was highest (64.4%, 68.8%). CONCLUSIONS: The ACR guidelines present a higher level of diagnostic indicators and may offer a meaningful reduction in FNA recommendations with a higher malignancy detection rate.

Gene-Focused Networks Underlying Phenotypic Convergence in a Systematically Phenotyped Cohort With Heterogeneous Intellectual Disability.

The broad spectrum of intellectual disability (ID) patients' clinical manifestations, the heterogeneity of ID genetic variation, and the diversity of the phenotypic variation represent major challenges for ID diagnosis. By exploiting a manually curated systematic phenotyping cohort of 3803 patients harboring ID, we identified 704 pathogenic genes, 3848 pathogenic sites, and 2075 standard phenotypes for underlying molecular perturbations and their phenotypic impact. We found the positive correlation between the number of phenotypes and that of patients that revealed their extreme heterogeneities, and the relative contribution of multiple determinants to the heterogeneity of ID phenotypes. Nevertheless, despite the extreme heterogeneity in phenotypes, the ID genes had a specific bias of mutation types, and the top 44 genes that ranked by the number of patients accounted for 39.9% of total patients. More interesting, enriched co-occurrent phenotypes and co-occurrent phenotype networks for each gene had the potential for prioritizing ID genes, further exhibited the convergences of ID phenotypes. Then we established a predictor called IDpred using machine learning methods for ID pathogenic genes prediction. Using10-fold cross-validation, our evaluation shows remarkable AUC values for IDpred (auc = 0.978), demonstrating the robustness and reliability of our tool. Besides, we built the most comprehensive database of ID phenotyped cohort to date: IDminer http://218.4.234.74:3100/IDminer/, which included the curated ID data and integrated IDpred tool for both clinical and experimental researchers. The IDminer serves as an important resource and user-friendly interface to help researchers investigate ID data, and provide important implications for the diagnosis and pathogenesis of developmental disorders of cognition.

Ultrasomics for Early Evaluation of the Tumor Response to MicroRNA-122 in a Nude Mouse Hepatocellular Carcinoma Model.

OBJECTIVES: To explore the value of ultrasomics in temporal monitoring of tumor changes in response to gene therapy in hepatocellular carcinoma compared with methods according to the Response Evaluation Criteria in Solid Tumors (RECIST) and modified RECIST (mRECIST). METHODS: Hepatocellular carcinoma-bearing mice were injected intratumorally with microRNA-122 (miR-122) mimics and an miR-122 negative control in the treatment and control groups, respectively. The injections were performed every 3 days for 5 times (on days 0, 3, 6, 9, and 12). Before each injection and at the experiment ending, 2-dimensional ultrasound imaging was performed for tumor size measurement with RECIST and computing a quantitative imaging analysis with ultrasomics. To analyze the tumor perfusion by mRECIST, perfusion parameters were analyzed offline based on dynamic contrast-enhanced ultrasound image videos using SonoLiver software (TomTec, Unterschleissheim, Germany) on day 13. Tumor miR-122 expression was then analyzed by real-time reverse transcription-polymerase chain reaction experiments. RESULTS: Tumors in mice treated with miR-122 mimics demonstrated a mean ± SD 763- ± 60-fold increase in miR-122 levels compared with tumors in the control group. With RECIST, a significant therapeutic response evaluated by tumor size changes was detected after day 9 (days 9, 12, and 13; P < .001). With mRECIST, no parameters showed significant differences (P > .05). Significant different features of the 2-dimensional ultrasound images between the groups were detected by the ultrasomics analysis, and the model could be successfully built. The ultrasomics score values between the groups were statistically significant after day 6 (days 6, 9, 12, and 13; P < .05). CONCLUSIONS: Ultrasomics revealed significant changes after the second injection of miR-122, showing the potential as an important imaging biomarker for gene therapy.

Relationship between carotid intima-media thickness and carotid artery stiffness assessed by ultrafast ultrasound imaging in patients with type 2 diabetes.

OBJECTIVES: To evaluate the relationship between carotid stiffness and carotid intima-media thickness (CIMT) in patients with type 2 diabetes (T2DM). MATERIALS AND METHODS: Carotid properties were evaluated in 317 consecutive subjects (98 volunteers for controls, 105 patients with normal CIMT for T2DM group 1, and 114 patients with thickened CIMT for T2DM group 2). The CIMT and carotid pulse wave velocity at the beginning (PWV-BS) and at the end of systole (PWV-ES) were measured. RESULTS: Apart from PWV-BS in T2DM group 1, CIMT and PWV-ES were significant higher in patients groups than those of in controls. In multiple regression analysis, diabetes was independently associated with PWV-ES and not with PWV-BS. Moreover, when adjusting for baseline covariates, only PWV-ES (odds ratio = 4.27, P < 0.001) distinguished carotid in T2DM group 1 from that of controls. Concerning the relationship between log(CIMT) and PWV-ES, when adjusting for baseline covariates, the association were still significant in controls and T2DM group 1, whereas it was no longer present in T2DM group 2 (P = 0.091). Additionally, the slope (ß) after adjustment for the PWV-ES to log(CIMT) was significantly steeper in T2DM group 1 than that of in controls (ß= 8.35 vs. 3.31, P < 0.01). CONCLUSIONS: The PWV-ES seem to be a better biomarker candidate than PWV-BS to assess the carotid stiffness in diabetic patients. Compared with controls, diabetic patients showed more advanced functional changes than morphological changes despite normal CIMT, whereas the relationship trend was not present when thickened CIMT emerged.

Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis.

OBJECTIVE: To assess significant liver fibrosis by multiparametric ultrasomics data using machine learning. MATERIALS AND METHODS: This prospective study consisted of 144 patients with chronic hepatitis B. Ultrasomics-high-throughput quantitative data from ultrasound imaging of liver fibrosis-were generated using conventional radiomics, original radiofrequency (ORF) and contrast-enhanced micro-flow (CEMF) features. Three categories of features were explored using pairwise correlation and hierarchical clustering. Features were selected using diagnostic tests for fibrosis, activity and steatosis stage, with the histopathological results as the reference. The fibrosis staging performance of ultrasomics models with combinations of the selected features was evaluated with machine-learning algorithms by calculating the area under the receiver-operator characteristic curve (AUC). RESULTS: ORF and CEMF features had better predictive power than conventional radiomics for liver fibrosis stage (both p < 0.01). CEMF features exhibited the highest diagnostic value for activity stage (both p < 0.05), and ORF had the best diagnostic value for steatosis stage (both p < 0.01). The machine-learning classifiers of adaptive boosting, random forest and support vector machine were found to be optimal algorithms with better (all mean AUCs = 0.85) and more stable performance (coefficient of variation = 0.01-0.02) for fibrosis staging than decision tree, logistic regression and neural network (mean AUC = 0.61-0.72, CV = 0.07-0.08). The multiparametric ultrasomics model achieved much better performance (mean AUC values of 0.78-0.85) than the features from a single modality in discriminating significant fibrosis (≥ F2). CONCLUSION: Machine-learning-based analysis of multiparametric ultrasomics can help improve the discrimination of significant fibrosis compared with mono or dual modalities. KEY POINTS: • Multiparametric ultrasomics has achieved much better performance in the discrimination of significant fibrosis (≥ F2) than the single modality of conventional radiomics, original radiofrequency and contrast-enhanced micro-flow. • Adaptive boosting, random forest and support vector machine are the optimal algorithms for machine learning.

Comparison between M-score and LR-M in the reporting system of contrast-enhanced ultrasound LI-RADS.

OBJECTIVE: To develop a contrast-enhanced ultrasound (CEUS) M-score and compare it with LR-M in CEUS Liver Imaging Reporting and Data System (LI-RADS). METHODS: We retrospectively enrolled 105 consecutive high-risk patients with hepatocellular carcinoma (HCC) and 105 with intrahepatic cholangiocarcinoma (ICC). The subjects were selected by propensity score matching between November 2003 and December 2017. A CEUS M-score for predicting ICC was constructed based on specific CEUS features by the least absolute shrinkage and selection operator regularised regression. M-score was used to develop a modified CEUS LI-RADS. The diagnostic performance of the modified CEUS LI-RADS using M-score for diagnosing HCC and ICC was compared with American College of Radiology (ACR) CEUS LI-RADS using LR-M. RESULTS: The most useful features for ICC were as follows: poorly circumscribed (69.52%), rim enhancement (63.81%), early washout (92.38%), intratumoural vein (56.19%), obscure boundary of intratumoural non-enhanced area (57.14%), and marked washout (59.05%, all p < 0.001). For predicting ICC, the M-score had a higher specificity (88.57% vs. 63.81%) with lower sensitivity (89.52% vs. 95.24%) compared with LR-M. For diagnosing HCC, the sensitivity of modified LI-RADS (80.95%) was much higher than that of ACR LI-RADS (57.14%), but the specificity was lower (90.48% vs. 96.19%). The area under the curve (AUC) of modified LI-RADS (0.857) was much higher than that of ACR LI-RADS (0.767, p = 0.0001). The modified positive predictive value (PPV) of ACR LI-RADS and modified LI-RADS were 99.42% and 98.99%, respectively. CONCLUSIONS: The modified LI-RADS with M-score had higher sensitivity for diagnosing HCC and higher specificity for diagnosing ICC than ACR LI-RADS. KEY POINTS: • For predicting ICC, the M-score had a higher specificity (88.57% vs. 63.81%) with lower sensitivity (89.52% vs. 95.24%) compared with LR-M. • A CEUS M-score for predicting ICC consisted of more detailed CEUS features (poorly circumscribed, rim enhancement, early washout, intratumoural vein, obscure boundary of intratumoural non-enhanced area, and marked washout) was constructed. • For diagnosing HCC, the sensitivity of modified LI-RADS (80.95%) was much higher than that of ACR LI-RADS (57.14%), but the specificity was lower (90.48% vs. 96.19%). The modified positive predictive value (PPV) of ACR LI-RADS and modified LI-RADS were 99.42% and 98.99%, respectively.

Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound.

AIM: To develop a contrast-enhanced ultrasound (CEUS) predictive model for distinguishing intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) in high-risk patients. METHODS: This retrospective study consisted of 88 consecutive high-risk patients with ICC and 88 high-risk patients with HCC selected by propensity score matching between May 2004 and July 2016. Patients were assigned to two groups, namely, a training set and validation set, at a 1:1 ratio. A CEUS score for diagnosing ICC was generated based on significant CEUS features. Then, a nomogram based on the CEUS score was developed, integrating the clinical data. The performance of the nomogram was then validated and compared with that of the LR-M of the CEUS Liver Imaging Reporting and Data System (LI-RADS). RESULTS: The most useful CEUS features for ICC were as follows: rim enhancement (64.5%), early washout (91.9%), intratumoral vein (58.1%), obscure boundary of intratumoral non-enhanced area (64.5%), and marked washout (61.3%, all P < 0.05). In the validation set, the area under the curve (AUC) of the CEUS score (AUC = 0.953) for differentiation between ICC and HCC was improved compared to the LI-RADS (AUC = 0.742) (P < 0.001). When clinical data were added, the CEUS score nomogram was superior to the LI-RADS nomogram (AUC: 0.973 vs 0.916, P = 0.036, Net Reclassification Improvement: 0.077, Integrated Discrimination Index: 0.152). Subgroup analysis demonstrated that the CEUS score model was notably improved compared to the LI-RADS in tumors smaller than 5.0 cm (P < 0.05) but not improved in tumors smaller than 3.0 cm (P > 0.05). CONCLUSION: The CEUS predictive model for differentiation between ICC and HCC in high-risk patients had improved discrimination and clinical usefulness compared to the CEUS LI-RADS.

Multiparametric radiomics improve prediction of lymph node metastasis of rectal cancer compared with conventional radiomics.

AIMS: To establish multiparametric radiomics of rectal tumor for the preoperative prediction of lymph node (LN) metastasis. MATERIALS AND METHODS: This prospective study consisted of 115 consecutive patients with rectal carcinoma between April 2015 and April 2017. The multiparametric radiomics scores were extracted from the endorectal ultrasound (ERUS), computed tomography (CT) and shear-wave elastography (SWE) features of the rectal tumor, LN, and peripheral tissues. The three radiomics scores were generated. Further validation as an independent predictor was performed using multivariate logistic regression together with clinical data, and a nomogram was subsequently developed. The predictive performance of the multiparametric radiomics nomogram was compared with that of conventional radiomics. KEY FINDINGS: All three scores (ERUS, CT, and SWE) were significantly higher in patients with LN metastasis than in patients with negative LN metastasis (all P < 0.05) in both training and validation set. Multivariate analysis indicated that CT and SWE scores were independent risk variables (odds ratio, OR = 6.764 and 5.482, respectively). In validation cohort, the multiparametric radiomics nomogram showed the highest predictive accuracy for LN metastasis, with a concordance index (C-index) of 0.857 compared with the conventional radiomics nomogram (C-index, 0.703, P = 0.100), resulting in a significantly improved net reclassification index (NRI) (P < 0.05) and integrated discriminatory improvement (IDI) (P = 0.002). Decision curve analysis showed that the multiparametric radiomics nomogram had a higher overall net benefit. SIGNIFICANCE: Multiparametric radiomics of rectal cancer, which captures blood supply and stiffness phenotypes, is a useful tool for predicting LN metastasis preoperatively and has marked discrimination accuracy compared to conventional radiomics.

Do hepatocellular carcinomas located in subcapsular space or in proximity to vessels increase the rate of local tumor progression? A meta-analysis.

AIMS: To determine if tumors located in the subcapsular space or in proximity to vessels would be a risk factor of local tumor progression (LTP2) in hepatocellular carcinomas (HCC) after radiofrequency ablation. MATERIALS AND METHODS: A search of the MEDLINE, EMBASE and Cochrane Library databases from 1998 to 2017 was performed to identify studies examining the risk factors of LTP after radiofrequency ablation (RFA3) in HCC. No language or other restrictions were imposed. Summary estimates of risk factors of LTP were obtained by using a random-effects model with further exploration with meta-regression and sub-group analyses. KEY FINDINGS: There were 16 studies included, of which 7 were focused on the association of LTP with tumors abutting vessels, and 15 focused on tumors of subcapsular location. In total, 2870 patients were included. Tumors that were located in the subcapsular area had a higher occurrence of LTP (P = 0.04) with a high heterogeneity (I2 = 65%), which could not be explained by the results of the meta-regression. However, tumor that were in close to vessels had contrary results (P = 0.54) with a high heterogeneity (I2 = 77%). SIGNIFICANCE: The findings of the present meta-analysis indicate that the subscapsular location is a possible risk factor of LTP. Nevertheless, a clear definition or classification of the subcapsular location should be highlighted in future studies. Whether tumor location adjacent to a vessel has an influence on the incidence of LTP remains controversial, and more relevant research should be performed.

Carotid Artery Stiffness Assessment by Ultrafast Ultrasound Imaging: Feasibility and Potential Influencing Factors.

OBJECTIVES: To evaluate the feasibility of the ultrafast ultrasound pulsed wave velocity (PWV) for carotid stiffness assessment and potential influencing factors. METHODS: Ultrafast PWV measurements of 442 carotid arteries in 162 consecutive patients (patient group) and 66 healthy volunteers (control group) were performed. High- and very high-frequency transducers were used in 110 carotid segments. The ultrafast PWVs at the beginning and end of systole were automatically measured. The correlations between the intima-media thickness (IMT) and ultrafast PWV and the equipment and carotid factors influencing the utility of ultrafast PWV were analyzed. RESULTS: Each ultrafast PWV acquisition was completed within 1 minute. The intraobserver variability showed mean differences ± SD of 0.12 ± 1.28 m/s for the PWV before systole and 0.06 ± 1.30 m/s for the PWV at the end of systole. Ultrafast PWV measurements were more likely obtained with the very high- frequency transducer when the IMT was less than 1.5 mm (P < .05). A generalized linear mixed-effects model analysis showed that the very high-frequency transducer had a greater ability to obtain a valid carotid ultrafast PWV measurement with an IMT of less than 1.5 mm (P < .05). The IMT was positively correlated with the PWV before systole and at the end of systole (r = 0.207-0.771; all P < .05) in the control group, patient group, and carotid subgroup with an IMT of less than 1.5 mm. A multiple regression analysis showed that the IMT and plaque were important independent factors in predicting failure of the ultrafast PWV (P < .001). CONCLUSIONS: The ultrafast PWV is an effective and user-friendly method for evaluating carotid stiffness. The IMT and transducer type are factors influencing the ability to obtain an ultrafast PWV measurement.

Non-Invasive Diagnostic Criteria for Hepatocellular Carcinoma in Hepatitis B Virus-Endemic Areas: Is Cirrhosis Indispensable?

AIM: To confirm whether cirrhosis is indispensable for the non-invasive diagnostic criteria for hepatocellular carcinoma (HCC) in hepatitis B virus (HBV)-endemic areas. METHODS: Between January 2014 and December 2014, a total of 409 patients with pathologically proven focal liver lesions who underwent contrast-enhanced ultrasound (CEUS) were recruited from our institution. Clinical liver cirrhosis, HBV/HCV infection and HCC-typical vascular pattern of the targeted lesion on CEUS were evaluated. The following 3 criteria were applied to these patients to diagnose HCC: criterion 1, clinical liver cirrhosis and HCC-typical vascular pattern; criterion 2, HBV/HCV infection and HCC-typical vascular pattern; criterion 3, HBV/HCV infection or clinical liver cirrhosis and HCC-typical vascular pattern. Pathological reports were considered the gold standard. RESULTS: A total of 311 patients had confirmed HCC by pathology. The sensitivity, specificity, accuracy, positive predictive value, negative predictive value and area under the ROC curve for criterion 1 were 29.6, 90.8, 44.3, 91.1, 28.9, and 0.60% respectively. For criterion 2, they were 83.3, 74.5, 81.2, 91.2, 58.4, and 0.79%, respectively, and for criterion 3, they were 86.2, 72.5, 82.9, 90.9, 62.3, and 0.79% respectively. CONCLUSIONS: In HBV-endemic areas, when using the HBV/HCV infection instead of cirrhosis as the precondition of the non-invasive diagnostic criteria for HCC, we should be aware of the potential false positive. Cirrhosis still plays an important role in the non-invasive diagnostic criteria for HCC because of the high specificity.

Transplant renal artery stenosis: Evaluation with contrast-enhanced ultrasound.

OBJECTIVE: To assess the efficacy of contrast-enhanced ultrasound (CEUS) in depicting transplant renal artery stenosis (TRAS). MATERIALS AND METHODS: Seventy-eight patients (56 men and 22 women; aged 36±12.2years) who were suspected of TRAS due to either Doppler ultrasound (DUS) abnormalities or difficult control of blood pressure and/or persistent deterioration of renal function were enrolled to perform CEUS. The reference standard for the TRAS diagnoses was computed tomography angiography (CTA). The diagnostic performance of DUS and CEUS parameters was assessed by the area under the receiver operating characteristic curve (AUC). RESULTS: TRAS was diagnosed in 32 out of 78 cases by CTA. The AUC, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of CEUS in predicting TRAS were 0.92, 92.3%, 87.5%, 95.7%, 93.3%, and 91.7%, respectively. CEUS rectified 13 (28.3%) false-positive cases on DUS, which were confirmed by CTA. Compared to DUS parameters, CEUS showed the highest AUC, statistically significant differences of AUC were found (P=0.006-0.039), except for that of the PSV ratio in the main transplant renal artery to that in interlobar artery (PSV-ratio) (AUC: 0.92 versus 0.86, P=0.422). However, CEUS showed a significantly higher specificity (95.7% versus 76.1%, P=0.008) and the same sensitivity compared to PSV-ratio. CONCLUSIONS: CEUS is superior to DUS in depicting TRAS. Moreover, our results suggest that CEUS might potentially be used as a noninvasive tool to spare many patients from unnecessary CTA.

FOXK2, regulted by miR-1271-5p, promotes cell growth and indicates unfavorable prognosis in hepatocellular carcinoma.

The forkhead transcription factor FOXK2 has been implicated in the progression of human cancers, but its role and clinical significance in hepatocellular carcinoma (HCC) have not been explored. Here we showed that FOXK2 expression was increased and associated with tumor size, TNM stage and vascular invasion. High FOXK2 expression was correlated with poor overall and disease-free survival in two independent cohorts consisting of 864 patients with HCC. The prognostic value of FOXK2 was validated by stratified survival analyses in subgroups difined by factors contributing to worse survival. Multivariate Cox regression model revealed that FOXK2 served as an independent factor for overall survival. The FOXK2 expression was reversely connected with miR-1271-5p in clinical samples. Re-introduction of miR-1271 decreased FOXK2 at both mRNA and protein levels. Luciferase assay confirmed that FOXK2 was a direct target of miR-1271 in HCC cells. Overexpression of FOXK2 enhanced the cell growth and migration, whereas FOXK2 silence resulted in the opposite phenotypes. Further studies demonstrated that FOXK2 exerted oncogenic activity via activation of PI3K/AKT signaling pathway. Collectively, our data suggest FOXK2 as an oncogene and a promising prognostic biomarker in HCC. Targeting the newly identified miR-1271/FOXK2/AKT axis may represent a potential strategy for HCC intervention.

Added value of two-dimensional shear wave elastography to ultrasonography for staging common femoral vein thrombi.

prove the performance for staging common femoral vein thrombi (CFVT). MATERIAL AND METHODS: A total of 194 consecutive patients with CFVT who underwent US and 2D-SWE were enrolled. These patients were categorized into three groups according to CFVT duration: Stage A (≤14 days), Stage B (14 days to 6 months), and Stage C (≥6 months). The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC). RESULTS: Among all US features, CFV diameter ratio of thrombosed leg to contralateral leg (CFVD_ratio) showed the highest AUC in predicting Stage A and Stage C (0.87 and 0.84, respectively). The diagnostic performance of 2D-SWE value of CFVT (CFVT_E) is comparable with that of CFVD_ratio for Stage A (AUC: 0.85, p=0.630), whereas inferior to that of CFVD_ratio for Stage C (AUC: 0.73, p=0.026). Combining CFVD_ratio with CFVT_E showed lower performance in predicting Stage A (AUC: 0.81, p=0.021) and Stage C (AUC: 0.67, p<0.0001) relative to CFVD_ratio alone. However, this combination increased the specificity from 80.3% to 92.7% (p<0.0001) without a significant reduction of sensitivity (from 77.2% to 70.2%, p=0.371) for predicting Stage A. CONCLUSIONS: Adding 2D-SWE to US did not improve the diagnostic performance for staging CFVT compared with US alone. However, the combination improved the specificity in predicting CFVT less than 14 days without loss of sensitivity.