Evaluation of synovial inflammation in juvenile idiopathic arthritis using superb microvascular imaging compared with power Doppler ultrasound.

OBJECTIVES: This study aimed to investigate the diagnostic and prognostic performance of superb microvascular imaging (SMI) in evaluation of synovial inflammation in patients with juvenile idiopathic arthritis (JIA) compared with power Doppler ultrasound (PDUS). METHODS: Fifty-nine patients with active disease and 62 patients with inactive disease were enrolled. The synovial inflammation was evaluated via vascularity index (VI) of SMI and PDUS. The correlations between VIs and the inflammatory biomarkers were analysed by Spearman's coefficient. Receiver operating characteristics curves were plotted to examine the prognostic value of SMI and PDUS. RESULTS: The VI of SMI was significantly higher than that of PDUS in JIA patients regardless of the disease activity. The SMI and PDUS VI were significantly correlated with levels of erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and serum amyloid A (SAA). The SMI VI was significantly higher in patients with relapse than in those with remission, and showed superior performance in predicting relapse in JIA patients with inactive disease. CONCLUSIONS: SMI may detect the synovial inflammation with greater sensitivity than PDUS in patients with JIA, and correlate well with the inflammatory biomarkers. SMI signal in the knees might play an important role in prediction of relapse in clinically inactive patients, thus allowing personalised treatment strategies for JIA patients.

Ultrasound-based radiomics analysis for preoperative prediction of central and lateral cervical lymph node metastasis in papillary thyroid carcinoma: a multi-institutional study.

BACKGROUND: An accurate preoperative assessment of cervical lymph node metastasis (LNM) is important for choosing an optimal therapeutic strategy for papillary thyroid carcinoma (PTC) patients. This study aimed to develop and validate two ultrasound (US) nomograms for the individual prediction of central and lateral compartment LNM in patients with PTC. METHODS: A total of 720 PTC patients from 3 institutions were enrolled in this study. They were categorized into a primary cohort, an internal validation, and two external validation cohorts. Radiomics features were extracted from conventional US images. LASSO regression was used to select optimized features to construct the radiomics signature. Two nomograms integrating independent clinical variables and radiomics signature were established with multivariate logistic regression. The performance of the nomograms was assessed with regard to discrimination, calibration, and clinical usefulness. RESULTS: The radiomics scores were significantly higher in patients with central/lateral LNM. A radiomics nomogram indicated good discrimination for central compartment LNM, with an area under the curve (AUC) of 0.875 in the training set, the corresponding value in the validation sets were 0.856, 0.870 and 0.870, respectively. Another nomogram for predicting lateral LNM also demonstrated good performance with an AUC of 0.938 and 0.905 in the training and internal validation cohorts, respectively. The AUC for the two external validation cohorts were 0.881 and 0.903, respectively. The clinical utility of the nomograms was confirmed by the decision curve analysis. CONCLUSION: The nomograms proposed here have favorable performance for preoperatively predicting cervical LNM, hold promise for optimizing the personalized treatment, and might greatly facilitate the decision-making in clinical practice.

Tumor Proliferation and Invasiveness Derived From Ultrasound Appearances of Invasive Breast Cancers: Moving Beyond the Routine Differential Diagnosis.

OBJECTIVES: To investigate the correlation between ultrasound (US) appearances of invasive breast cancers and tumor proliferation and invasiveness measured according to the histologic grade, Ki-67 expression, axillary lymph node metastasis (ALNM), and lymphovascular invasion (LVI). METHODS: This study evaluated 676 patients who underwent primary surgical treatment of invasive breast cancers. The preoperative US reports and postoperative pathologic and immunohistochemical results of the patients were retrospectively reviewed. Ultrasound characteristics were evaluated according to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) lexicon. Logistic regression analyses were used to identify independent predictive US features that were correlated with tumor proliferation and invasiveness of breast cancers. Odds ratios (ORs) were calculated. RESULTS: Posterior acoustic enhancement and calcifications on US images were independent predictive factors of a higher histologic grade and a higher Ki-67 level (OR, 1.69-6.54; P < .05). Meanwhile, a noncircumscribed margin (OR, 2.61; P < .05) and posterior acoustic shadow (OR, 1.62; P < .05) were independent predictors of ALNM. An irregular shape (OR, 2.13; P < .05) and calcifications (OR, 1.69; P < .05) were independent risk factors for LVI. Infiltrative breast cancers scored as BI-RADS category 5 had higher probability to be associated with ALNM (OR, 3.33; P < .0005) and LVI (OR, 2.87; P < .0005). CONCLUSIONS: Ultrasound features of invasieve breast cancers might have a predictive value for tumor proliferation and invasiveness. The US features correlated with a high cellular proliferation rate were different from those associated with ALNM. The tumor shape, margin, posterior acoustic pattern, and calcifications at US are suggested to be considered by clinicians when making clinical decisions.

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status.

OBJECTIVES: To investigate the value of ultrasound (US) feature-based models in predicting the proliferation and invasiveness of invasive breast cancer (IBC) and to compare the performance of models based solely on US features with models that combined US features, patient age, tumor size, and axilla status from US. METHODS: With ethical approval, 746 patients with a pathologic diagnosis of IBC were reviewed for preoperative clinical, US, and postoperative pathologic data. The proliferation and invasiveness properties of the IBC included the histologic grade and Ki-67 status and lymphovascular invasion (LVI) and axillary lymph node metastasis (ALNM), respectively. Logistic regression analyses were used to identify independent risk factors for tumor proliferation and invasiveness. RESULTS: Posterior echo enhancement, calcification, a tumor size larger than 2 cm, and suspicion of ALNM from axillary US were independent risk factors for a high histologic grade and high Ki-67 expression of IBC (P < .05). A posterior echo shadow, patient age younger than 45 years, and suspicious findings on axillary US imaging were independent variables for predicting the presence of LVI and ALNM in IBC (P < .05). Calcification was the independent factor for predicting LVI (P = .013). The predictive performance of the combined models was improved compared with the US feature-based models, with a higher accuracy rate and negative predictive value. The area under curve of the combined models was also significantly higher than that of the single models (P < .05). CONCLUSIONS: Compared with the US feature-based models, the combined models yielded better predictive performance. This may provide a more robust model to predict the tumor biological properties of IBC before surgery.

Clinicopathologic and Ultrasound Variables Associated With a Heavy Axillary Nodal Tumor Burden in Invasive Breast Carcinoma.

OBJECTIVES: To identify clinicopathologic and ultrasound (US) variables that were associated with a heavy nodal tumor burden, which was defined as 3 or more lymph nodes involved with metastasis to the axilla after invasive breast carcinoma. METHODS: With ethical approval, 621 patients with a pathologic diagnosis of invasive breast carcinoma were retrospectively analyzed for clinical, pathologic, and US data. Pathologic findings were ascertained by the final paraffin pathologic analysis. Ultrasound characteristics were evaluated on the basis of the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS). Univariate and multivariate logistic regression analyses were used to assess the clinicopathologic and US variables that were associated with a heavy nodal tumor burden at the axilla. RESULTS: There were 107 cases (17.2%) of invasive breast carcinoma with a heavy tumor burden at the axilla. The independent clinicopathologic variables for a heavy tumor burden at the axilla included a tumor size of 2 to 5 cm (odds ratio [OR], 1.86; P = .036), the presence of lymphovascular invasion (OR, 23.52; P < .001), the presence of papillary invasion (OR, 2.93; P = .043), and a non-triple-negative subtype (OR, 2.34; P = .04). The independent US features of breast tumors that were associated with a heavy tumor burden at the axilla included BI-RADS category 5 (OR, 5.50; P = .024) and a posterior acoustic shadow (OR, 1.94; P = .024). CONCLUSIONS: A large tumor size, lymphovascular invasion, papillary invasion, and a non-triple-negative subtype on the pathologic analysis as well as BI-RADS category 5 and a posterior acoustic shadow on a US assessment were associated with a heavy nodal tumor burden at the axilla. These US characteristics of the primary breast carcinoma might provide additional information to axillary US for the prediction of axillary nodal tumor loads.

Effect of a hypoxic microenvironment after radiofrequency ablation on residual hepatocellular cell migration and invasion.

Clinical observations have shown that the boundary of tumor ablation is often less than safe border and that the use of radiofrequency ablation (RFA) in the treatment of hepatocellular carcinoma (HCC) may probably accelerate its recurrence and metastasis. RFA can cause the formation of a transition zone between normal liver tissues and necrotic coagulation, where blood stagnation and thrombosis expose residual cancer cells to a hypoxic microenvironment. As the blocked vessels are slowly reperfused, the oxygen supply is gradually restored. Here, HCC cells underwent heat treatment and were cultured under hypoxic conditions to mimic the aforementioned situation, and morphological changes were observed in the surviving cells. Compared with their parental cells, hypoxic HCC cells showed changes that include enhanced invasive, metastatic, and chemoresistant abilities as well as mesenchymal characteristics. There was also a higher percentage of stem-like cells. However, either improving the hypoxic microenvironment or silencing hypoxia inducible factor (HIF)-1α signaling significantly reduced the invasive, metastatic, and chemoresistant potential and reversed the epithelial-mesenchymal transition to varying degrees. Together, these results indicated that a sustained hypoxic microenvironment after RFA may exert a negative impact on the prognosis of HCC patients, and minimizing exposure to a hypoxic microenvironment and targeting HIF-1α signaling might be effective strategies for patients who experience insufficient RFA therapy.

Ultrasound-Based Nomogram for Predicting the Aggressiveness of Papillary Thyroid Carcinoma in Adolescents and Young Adults.

RATIONALE AND OBJECTIVES: Assessing the aggressiveness of papillary thyroid carcinoma (PTC) preoperatively might play an important role in guiding therapeutic strategy. This study aimed to develop and validate a nomogram that integrated ultrasound (US) features with clinical characteristics to preoperatively predict aggressiveness in adolescents and young adults with PTC. MATERIALS AND METHODS: In this retrospective study, a total of 2373 patients were enrolled and randomly divided into two groups with 1000 bootstrap sampling. The multivariable logistic regression (LR) analysis or least absolute shrinkage and selection operator LASSO regression was applied to select predictive US and clinical characteristics in the training cohort. By incorporating most powerful predictors, two predictive models presented as nomograms were developed, and their performance was assessed with respect to discrimination, calibration, and clinical usefulness. RESULTS: The LR_model that incorporated gender, tumor size, multifocality, US-reported cervical lymph nodes (CLN) status, and calcification demonstrated good discrimination and calibration with an area under curve (AUC), sensitivity and specificity of 0.802 (0.781-0.821), 65.58% (62.61%-68.55%), and 82.31% (79.33%-85.46%), respectively, in the training cohort; and 0.768 (0.736-0.797), 60.04% (55.62%-64.46%), and 83.62% (78.84%-87.71%), respectively, in the validation cohort. Gender, tumor size, orientation, calcification, and US-reported CLN status were combined to build LASSO_model. Compared with LR_model, the LASSO_model yielded a comparable diagnostic performance in both cohorts, the AUC, sensitivity, and specificity were 0.800 (0.780-0.820), 65.29% (62.26%-68.21%), and 81.93% (78.77%-84.91%), respectively, in the training cohort; and 0.763 (0.731-0.792), 59.43% (55.12%-63.93%), and 84.98% (80.89%-89.08%), respectively, in the validation cohort. The decision curve analysis indicated that using the two nomograms to predict the aggressiveness of PTC provided a greater benefit than either the treat-all or treat-none strategy. CONCLUSION: Through these two easy-to-use nomograms, the possibility of the aggressiveness of PTC in adolescents and young adults can be objectively quantified preoperatively. The two nomograms may serve as a useful clinical tool to provide valuable information for clinical decision-making.

Ultrasound-based Nomogram for Predicting the Pathological Nodal Negativity of Unilateral Clinical N1a Papillary Thyroid Carcinoma in Adolescents and Young Adults.

RATIONALE AND OBJECTIVES: To develop and validate a nomogram incorporating clinical and ultrasound (US) characteristics for predicting the pathological nodal negativity of unilateral clinically N1a (cN1a) papillary thyroid carcinoma (PTC) among adolescents and young adults. MATERIALS AND METHODS: From December 2016 to August 2021, 278 patients aged ≤ 30 years from two medical centers were enrolled and randomly assigned to the training and validation cohorts at a ratio of 2:1. After performing univariate and multivariate analyses, a nomogram combining all independent predictive factors was constructed and applied to the validation cohort. The performance of the nomogram was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis . RESULTS: Multivariate logistic regression analysis showed that unilateral cN1a PTC in young patients with Hashimoto's thyroiditis, T1 stage, no intra-tumoral microcalcification, and tumors located in the upper third of the thyroid gland was more likely to be free of central lymph node metastases. The nomogram revealed good calibration and discrimination in both cohorts, with areas under the receiver operating characteristic curve of 0.764 (95% confidence interval [CI]: 0.684-0.843) and 0.728 (95% CI: 0.602-0.853) in the training and validation cohorts, respectively. The clinical application of the nomogram was further confirmed using decision curve analysis. CONCLUSION: This US-based nomogram may assist the assessment of central cervical lymph nodes in young patients with unilateral cN1a PTC, enabling improved risk stratification and optimal treatment management in clinical practice.

An Ultrasound-based Prediction Model for Occult Contralateral Papillary Thyroid Carcinoma in Adolescents and Young Adults.

RATIONALE AND OBJECTIVES: To investigate the occult contralateral papillary thyroid carcinoma (PTC)-associated ultrasound (US) and clinical characteristics and establish a US-based model for the prediction of occult contralateral carcinoma in adolescents and young adults (AYAs) who were diagnosed with unilateral thyroid carcinoma preoperatively. MATERIALS AND METHODS: From January 2015 to December 2020, patients who were diagnosed with unilateral thyroid carcinoma by preoperative US examination and underwent total thyroidectomy or thyroid lobectomy with more than 60 months of US follow-up at our hospital were retrospectively collected. Univariate and multivariate analyses were applied to identify the independent risk factors associated with occult contralateral PTC in AYAs, on which a prediction model was developed. The performance of the model was evaluated with accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve. RESULTS: Occult contralateral PTC was found in 91 of 365 (24.9%) PTC patients with a median age at diagnosis of 26 years (interquartile range, 24-29 years). The multivariate analysis indicated that the presence of contralateral benign nodule, intra-tumoral calcification, and intraglandular dissemination were significantly associated with occult contralateral PTC in AYAs. The prediction model, which incorporated all independent predictors, yielded an area under the receiver operating characteristic curve of .661 (95% CI: .602-.719). The accuracy, sensitivity and specificity were 67.9%, 54.9%, and 72.3%, respectively. CONCLUSION: The US-based prediction model proposed here exhibited a favorable performance for predicting occult contralateral PTC, which might be used to determine the appropriate extent of surgery for AYAs who had a preoperative diagnosis of unilateral thyroid carcinoma.

Impact of TP53 Mutations on EGFR-Tyrosine Kinase Inhibitor Efficacy and Potential Treatment Strategy.

BACKGROUND: We investigated the impact of factors that influence TP53 mutations on the efficacy of EGFR-tyrosine kinase inhibitors and potential treatment strategies. MATERIALS AND METHODS: Tumor samples were collected to screen gene mutations by next-generation sequencing, as well as the patients' baseline characteristics. The overall response to treatment with TKIs was evaluated based on interval computed tomography scans at each follow-up time point. A Fisher's exact test and log-rank test were used to determine the statistical differences in this study. RESULTS: A total of 1134 clinical samples were collected from NSCLC patients, and TP53mut was identified in 644 cases and EGFRmut in 622 cases. A low frequency of TP53mut or more than 50% EGFR co-mutation rate were related to the prognosis of TKI-treated patients. In addition, TP53mut in the region outside of the DB domain had the strongest correlation with TKI resistance, whereas various types of mutations in the DB domain only had an impact on PFS. A grouping study of EGFR-TKI-based treatment revealed that EGFR-TKIs with chemotherapy were associated with more significant survival benefits for patients with prognostic TP53mut, whereas EGFR-TKI therapy was favorable for TP53wt patients. Furthermore, TP53mut could shorten the time to the relapse of postoperative patients, who will also likely respond well to EGFR-TKIs with chemotherapy. CONCLUSION: Various characteristics of TP53mut affect the prognosis of TKI-treated patients to varying degrees. EGFR-TKIs with chemotherapy were benefit for patients' survival with prognostic TP53mut, which provides an important reference for treatment management of EGFRmut patients.

A special prognostic indicator: tumor mutation burden combined with immune infiltrates in lung adenocarcinoma with TP53 mutation.

BACKGROUND: TP53 mutation (TP53 mut) is significantly associated with immunotherapy response in lung adenocarcinoma (LUAD), but not an ideal independent prognostic predictor for it. Here, we investigated a novel potential biomarker and constructed a model for prognostic prediction in LUAD TP53 mut patients. METHODS: 469 LUAD samples retrieved from The Cancer Genome Atlas database were divided into TP53 wt (wild-type TP53) and TP53 mut groups. TMB values were calculated based on the number of variants/exon lengths, and high- and low-TMB groups were divided by the median value. Differentially expressed genes (DEGs) between the two TMB groups were identified using "limma" package, and functional analyses were performed by Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and Gene Set Enrichment Analysis. The infiltration ratio of 22 immune cells were calculated with the CIBERSORT algorithm. Survival analyses were estimated by Kaplan-Meier with the log-rank test. Finally a TMB prognostic index (TMBPI) with receiver operating characteristic (ROC) curve was constructed and calculated to evaluate the predictive value in TP53 mut LUAD. RESULTS: There were diverse mutation types in 100% of TP53 mutants, while mutations were present in 86.5% of cases with TP53 wt. TP53 mut patients had higher TMB levels than TP53 wt patients. Overall survival in TP53 mut patients with low-TMB levels was significantly shorter than that in high-TMB TP53 mut patients. High-TMB patients had higher levels of CD8 T cell and effector B cell, while lower levels of resting memory CD4 T cells, monocytes, activated dendritic cells, etc. than low-TMB patients. Poor survival outcome in TP53 mut patients was correlated with lower effector B cell infiltration and higher activated dendritic cell. Survival risk analyses of 121 DEGs showed that good survival outcomes correlated positively with FBXO36 and KLHL35 expression levels, but correlated negatively with that of LINC0054. TMBPI analysis of the TP53 mut patients showed that high-TMBPI patients had worse survival outcomes than low-TMBPI patients. CONCLUSIONS: Our findings suggest that the TMB value with immune infiltrates is a novel potential biomarker for prognostic prediction of TP53 mut patients. The TMBPI combined with detection of TP53 mutation can be used as a better predictor of prognosis in LUAD.

Ultrasound-Based Radiomic Nomogram for Predicting Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma.

RATIONALE AND OBJECTIVES: Accurate preoperative identification of lateral cervical lymph node metastasis (LNM) is important for decision-making and clinical management of patients with papillary thyroid carcinoma (PTC). The aim of this study was to develop an ultrasound (US)-based radiomic nomogram to preoperatively predict the lateral LNM in PTC patients. METHODS: In this retrospective study, a total of 886 patients were enrolled and randomly divided into 2 groups. Radiomic features were extracted from the preoperative US images. A radiomic signature was constructed using the least absolute shrinkage and selection operator algorithm in the training set. Multivariate logistic regression was performed to develop the radiomic nomogram, which incorporating the radiomic signature and the selected clinical characteristics. The performance of the nomogram was assessed by its discrimination, calibration, and clinical usefulness in both the training and validation sets. RESULTS: The radiomic signature was significantly associated with the lateral LNM in both cohorts (p< 0.001). The nomogram that consisted of radiomic signature, US-reported cervical lymph node (CLN) status, and CT-reported CLN status demonstrated good discrimination and calibration in the training and validation sets with an AUC of 0.946 and 0.914, respectively. The decision curve analysis indicated that the radiomic nomogram was worthy of clinical application. CONCLUSION: The radiomic nomogram proposed here has good performance for noninvasively predicting the lateral LNM and might be used to facilitate clinical decision-making and potentially improve the survival outcome in selected patients.

Radiogenomic Analysis of Papillary Thyroid Carcinoma for Prediction of Cervical Lymph Node Metastasis: A Preliminary Study.

BACKGROUND: Papillary thyroid carcinoma (PTC) is characterized by frequent metastases to cervical lymph nodes (CLNs), and the presence of lymph node metastasis at diagnosis has a significant impact on the surgical approach. Therefore, we established a radiomic signature to predict the CLN status of PTC patients using preoperative thyroid ultrasound, and investigated the association between the radiomic features and underlying molecular characteristics of PTC tumors. METHODS: In total, 270 patients were enrolled in this prospective study, and radiomic features were extracted according to multiple guidelines. A radiomic signature was built with selected features in the training cohort and validated in the validation cohort. The total protein extracted from tumor samples was analyzed with LC/MS and iTRAQ technology. Gene modules acquired by clustering were chosen for their diagnostic significance. A radiogenomic map linking radiomic features to gene modules was constructed with the Spearman correlation matrix. Genes in modules related to metastasis were extracted for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and a protein-protein interaction (PPI) network was built to identify the hub genes in the modules. Finally, the screened hub genes were validated by immunohistochemistry analysis. RESULTS: The radiomic signature showed good performance for predicting CLN status in training and validation cohorts, with area under curve of 0.873 and 0.831 respectively. A radiogenomic map was created with nine significant correlations between radiomic features and gene modules, and two of them had higher correlation coefficient. Among these, MEmeganta representing the upregulation of telomere maintenance via telomerase and cell-cell adhesion was correlated with 'Rectlike' and 'deviation ratio of tumor tissue and normal thyroid gland' which reflect the margin and the internal echogenicity of the tumor, respectively. MEblue capturing cell-cell adhesion and glycolysis was associated with feature 'minimum calcification area' which measures the punctate calcification. The hub genes of the two modules were identified by protein-protein interaction network. Immunohistochemistry validated that LAMC1 and THBS1 were differently expressed in metastatic and non-metastatic tissues (p=0.003; p=0.002). And LAMC1 was associated with feature 'Rectlike' and 'deviation ratio of tumor and normal thyroid gland' (p<0.001; p<0.001); THBS1 was correlated with 'minimum calcification area' (p<0.001). CONCLUSIONS: The radiomic signature proposed here has the potential to noninvasively predict the CLN status in PTC patients. Merging imaging phenotypes with genomic data could allow noninvasive identification of the molecular properties of PTC tumors, which might support clinical decision making and personalized management.

Normal values of shear wave velocity in liver tissue of healthy children measured using the latest acoustic radiation force impulse technology.

BACKGROUND: Several studies have demonstrated the feasibility and effectiveness of using ultrasound elastography to assess liver tissue stiffness. Virtual touch imaging quantification (VTIQ) based on acoustic radiation force impulse imaging has been developed as a latest and noninvasive method for assessing liver stiffness in children. AIM: To determine the standard value in healthy children, and to identify possible factors that might influence the VTIQ measurement. METHODS: With the ethical approval, 202 children between 1 month and 15 years old were included in this study. None of them had any liver or systematic diseases. All children had a normal ultrasound scan and normal body mass index (BMI) range. The subjects were divided into four age and BMI groups. The effects of gender, age, liver lobe, measurement depth, and BMI on liver elasticity were investigated. RESULTS: A significant correlation was found between age and shear wave velocity (SWV) value. At measurement depths of 1.5 cm and 2.0 cm in the left lobe, there were significant differences among the age groups. SWV values were significantly negatively correlated with the measurement depth. Gender, liver lobe, and BMI showed no significant effect on the SWV values. Age and BMI may influence the quality of the elastogram. CONCLUSION: VTIQ is a noninvasive technique that is feasible to measure liver stiffness in children. The afore-mentioned velocity value obtained utilizing VTIQ method could be used as reference value for normal liver stiffness in children.