Ultrasound features as predictive markers of BRAFV600E mutation in thyroid cancer: a systematic review and meta-analysis.

Background: Conflicting evidence exists on the predictive value of ultrasound characteristics for BRAFV600E gene expression in thyroid cancer. This study aimed to determine the predictive value of ultrasound features for BRAFV600E gene expression status in thyroid cancer. Methods: A systematic review of studies published before December 31, 2023, was conducted in the PubMed, Web of Science, and Cochrane Library databases. Studies evaluating the ultrasonographic features for predicting BRAFV600E gene mutations in thyroid cancer were included. The relevant data were extracted, and the quality of eligible studies was independently assessed by two reviewers. Statistical analysis was performed using RevMan 5.4 and Stata 12.0 software. Results: The meta-analysis included 13 studies involving a total of 2,250 thyroid cancer patients. Ultrasound features significantly associated with BRAFV600E gene expression status in thyroid cancer (P<0.05) comprised hypoechogenicity, absence of halo, irregular borders, and vertical orientation. Contrastingly, no significant differences were observed in solid composition, irregular shape, and microcalcifications (P>0.05). Among the seven ultrasound features, the ones with superior combined sensitivity for nodules were hypoechogenicity, solid composition, absence of halo, and irregular borders, with sensitivities of 0.93 [95% confidence interval (CI): 0.87-0.96], 0.93 (95% CI: 0.86-0.97), 0.83 (95% CI: 0.72-0.91), and 0.74 (95% CI: 0.64-0.83), respectively. Finally, the areas under the summary receiver operating characteristic (SROC) curve with the highest diagnostic performance were the absence of halo and hypoechogenicity, with area under the curve (AUC) of 0.84 (95% CI: 0.80-0.87) and 0.81 (95% CI: 0.77-0.84), respectively. Conclusions: The expression status of the BRAFV600E gene in thyroid cancer correlates with nodules exhibiting hypoechogenicity, absence of halo, irregular borders, and taller-than-wide shape. Notably, the absence of a halo and hypoechogenicity were identified as the most predictive ultrasonic features. However, due to the limited sample size, there may be bias in the meta-analysis results, and more extensive research is necessary.

Insights into Ultrasound Features and Risk Stratification Systems in Pediatric Patients with Thyroid Nodules.

Thyroid nodules in pediatric patients are less common than in adults but show a higher malignancy rate. Accordingly, the management of thyroid nodules in pediatric patients is more complex the younger the patient is, needing careful evaluation by physicians. In adult patients, specific ultrasound (US) features have been associated with an increased risk of malignancy (ROM) in thyroid nodules. Moreover, several US risk stratification systems (RSSs) combining the US features of the nodule were built to define the ROM. RSSs are developed for the adult population and their use has not been fully validated in pediatric patients. This study aimed to evaluate the available data about US features of thyroid nodules in pediatric patients and to provide a summary of the evidence regarding the performance of RSS in predicting malignancy. Moreover, insights into the management of thyroid nodules in pediatric patients will be provided.

Multimodal Machine Learning-Based Ductal Carcinoma in situ Prediction from Breast Fibromatosis.

Objective: To develop a clinical-radiomics model using a multimodal machine learning method for distinguishing ductal carcinoma in situ (DCIS) from breast fibromatosis. Methods: The clinical factors, ultrasound features, and related ultrasound images of 306 patients (198 DCIS patients) were retrospectively collected. Patients in the development and validation cohort were 184 and 122, respectively. The independent clinical and ultrasound factors identified by the multivariable logistic regression analysis were used for the clinical-ultrasound model construction. Then, the region of interest of breast lesions was delineated and radiomics features were extracted. Six machine learning algorithms were trained to develop a radiomics model. The algorithm with higher and more stable prediction ability was chosen to convert the output of the results into the Radscore. Further, the independent clinical predictors and Radscore were enrolled into the logistic regression analysis to generate a combined clinical-radiomics model. The receiver operating characteristic curve analysis, DeLong test, and decision curve analysis were adopted to compare the prediction ability and clinical efficacy of three different models. Results: Among the six classifiers, logistic regression model was selected as the final radiomics model. Besides, the combined clinical-radiomics model exhibited a superior ability in distinguishing DCIS from breast fibromatosis to the clinical-ultrasound model and the radiomics model. Conclusion: The combined model by integrating clinical-ultrasound factors and radiomics features performed well in predicting DCIS, which might promote prompt interventions to improve the early diagnosis and prognosis of the patients.

Imprinted gene detection effectively improves the diagnostic accuracy for papillary thyroid carcinoma.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the most frequent histological type of thyroid carcinoma. Although an increasing number of diagnostic methods have recently been developed, the diagnosis of a few nodules is still unsatisfactory. Therefore, the present study aimed to develop and validate a comprehensive prediction model to optimize the diagnosis of PTC. METHODS: A total of 152 thyroid nodules that were evaluated by postoperative pathological examination were included in the development and validation cohorts recruited from two centres between August 2019 and February 2022. Patient data, including general information, cytopathology, imprinted gene detection, and ultrasound features, were obtained to establish a prediction model for PTC. Multivariate logistic regression analysis with a bidirectional elimination approach was performed to identify the predictors and develop the model. RESULTS: A comprehensive prediction model with predictors, such as component, microcalcification, imprinted gene detection, and cytopathology, was developed. The area under the curve (AUC), sensitivity, specificity, and accuracy of the developed model were 0.98, 97.0%, 89.5%, and 94.4%, respectively. The prediction model also showed satisfactory performance in both internal and external validations. Moreover, the novel method (imprinted gene detection) was demonstrated to play a role in improving the diagnosis of PTC. CONCLUSION: The present study developed and validated a comprehensive prediction model for PTC, and a visualized nomogram based on the prediction model was provided for clinical application. The prediction model with imprinted gene detection effectively improves the diagnosis of PTCs that are undetermined by the current means.

A multivariable model of ultrasound and clinicopathological features for predicting axillary nodal burden of breast cancer: potential to prevent unnecessary axillary lymph node dissection.

BACKGROUND: To develop a clinical model for predicting high axillary nodal burden in patients with early breast cancer by integrating ultrasound (US) and clinicopathological features. METHODS AND MATERIALS: Patients with breast cancer who underwent preoperative US examination and breast surgery at the Affiliated Hospital of Nantong University (centre 1, n = 250) and at the Affiliated Hospital of Jiangsu University (centre 2, n = 97) between January 2012 and December 2016 and between January 2020 and March 2022, respectively, were deemed eligible for this study (n = 347). According to the number of lymph node (LN) metastasis based on pathology, patients were divided into two groups: limited nodal burden (0-2 metastatic LNs) and heavy nodal burden (≥ 3 metastatic LNs). In addition, US features combined with clinicopathological variables were compared between these two groups. Univariate and multivariate logistic regression analysis were conducted to identify the most valuable variables for predicting ≥ 3 LNs in breast cancer. A nomogram was then developed based on these independent factors. RESULTS: Univariate logistic regression analysis revealed that the cortical thickness (p < 0.001), longitudinal to transverse ratio (p = 0.001), absence of hilum (p < 0.001), T stage (p = 0.002) and Ki-67 (p = 0.039) were significantly associated with heavy nodal burden. In the multivariate logistic regression analysis, cortical thickness (p = 0.001), absence of hilum (p = 0.042) and T stage (p = 0.012) were considered independent predictors of high-burden node. The area under curve (AUC) of the nomogram was 0.749. CONCLUSION: Our model based on US variables and clinicopathological characteristics demonstrates that can help select patients with ≥ 3 LNs, which can in turn be helpful to predict high axillary nodal burden in early breast cancer patients and prevent unnecessary axillary lymph node dissection.

The role of ultrasonographic findings for PIK3CA-mutated, hormone receptor-positive, human epidermal growth factor receptor-2-negative breast cancer.

To determine whether ultrasound (US) features of breast cancer are associated with Breast Imaging and Reporting Data System molecular subtype, histologic grade, and hormone receptor status as well as to assess the predictive value of these features. Retrospective analysis of the medical records of 220 consecutive patients with invasive breast cancer was reviewed according to the PIK3CA-mutated molecular tumor subtype. US findings of all patients were analyzed. Breast tumors harboring a PIK3CA-mutation were large and exhibited liquefied necrosis and posterior echo attenuation in the nodule. Moreover, such tumors were lobulated and calcified. The aspect ratio of the PIK3CA-mutant was more likely >1. The average nodule elasticity (7.479 ± 0.993 m/s) was measured using US shear wave elastography. Microcalcification was easier to detect inside the nodule using a fluorescence technique. Measurement of the nodule blood flow spectrum showed that the internal blood flow resistance index of nodules was lower than that of other types of breast cancer. The sonographic features of PIK3CA-mutated breast cancers were strongly associated with extensive and liquefied necrosis. The ability to predict molecular subtypes, particularly using US to detect the triple-negative subtype, may play an important role in early management and treatment.

Correlation of ultrasound features with Bcl-2 protein expression in basal cell carcinomas (BCCs).

BACKGROUND: The expression of the Bcl-2 protein is frequently observed in basal cell carcinomas (BCCs), making it a significant biological marker and potential therapeutic target. Skin ultrasonography offers a noninvasive means of obtaining anatomical information about cutaneous tumors. OBJECTIVES: The purpose of this study was to investigate the correlation between ultrasound features and Bcl-2 expression in BCCs, to provide a reference for developing pharmacological treatment plans. METHODS: According to the Bcl-2 protein expression, 74 BCCs confirmed by surgical pathology were divided into high Bcl-2 expression BCCs (HB-BCCs) and low Bcl-2 expression BCCs (LB-BCCs). Preoperative lesion ultrasound features were analyzed retrospectively based on Liang's criteria, which included the following features: shape, surface, keratinization, base, infiltration level, internal echogenicity, distribution of hyperechoic spots, posterior echogenic changes, internal Doppler signal, and lesion size (maximum diameter and infiltration depth). The differences of two groups were compared using a chi-square test or a paired t-test. RESULTS: Based on ultrasound features, cystic areas were more frequent in LB-BCCs (χ2 = 7.015, P = .008). Furthermore, LB-BCCs exhibited greater infiltration depth than HB-BCCs (4.86 ± 2.12 mm vs. 2.72 ± 1.40 mm, P = .000), had a higher propensity to infiltrate the subcutaneous tissue (χ2 = 12.422, P = .002), and displayed a more abundant internal Doppler signal within the lesions (χ2 = 24.696, P = .000). Conversely, maximum diameter of the lesions, shape, surface, keratinization, base, hyperechoic spots distribution, and posterior echogenic changes of the lesions did not differ significantly between the two groups. CONCLUSIONS: Ultrasound features are correlated with Bcl-2 protein expression level in BCCs. LB-BCCs show greater infiltration depth, subcutaneous infiltration, more cystic changes and more abundant internal Doppler signal than HB-BCCs, which may suggest a potential basis for drug selection in BCC chemotherapy.

Effect of caspase-1 (CASP1) combined with multimodal ultrasound features on the prognosis of breast cancer patients.

Background: Breast cancer (BRCA) is the malignant tumor with the highest incidence rate among women in the world, and its mortality rate ranks second. The purpose of our study is to explore the correlation between caspase-1 (CASP1) and the prognosis of BRCA patients and the potential mechanism of action, and to analyze the clinical value of CASP1 combined with multimodal ultrasound features in early screening and prognosis of BRCA. Methods: We analyzed The Cancer Genome Atlas (TCGA) database to confirm that CASP1 was expressed in BRCA patients and determine whether its expression was correlated with patient prognosis. The relationship between CASP1 expression and survival was measured by the clinicopathological parameters. Multivariate analysis was performed using Cox regression, and a nomogram was developed using these results for quality assurance purposes. The correlations between CASP1 and immune cells were investigated using the Tumor Immune Estimation Resource (TIMER) and TCGA databases. Next, we performed gene set enrichment analysis (GSEA) to determine the potential mechanism of action. Finally, to analyze the effect of CASP1 combined with multimodal ultrasonography characteristics on the prognosis of BRCA patients was studied by analyzing the clinical data of patients. Results: CASP1 expression was lower in BRCA tumor tissues than in the surrounding tissues. Patients with high CASP1 expression had better overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) than those with low CASP1 expression. GSEA suggested that CASP1 may affect the cell cycle, immune environment, inflammation, apoptosis, the HIPPOMERLIN pathway, Natural killer (NK) cell regulation of cytotoxicity, p53 expression, the Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway, the mitogen-activated protein kinase (MAPK) pathway, extracellular matrix, etc., thereby influencing the biological events in BRCA. Among conventional ultrasound features and contrast-enhanced ultrasound (CEUS) features, mass margin status and blood flow grade were associated with the expression of CASP1. Meanwhile, patients with poor ultrasound features tended to have low CASP1 expression. Conclusions: CASP1 may be a novel predictive marker for BRCA patients. CASP1 combined with multimodal ultrasound features has good clinical value in the early screening and prognostic prediction of BRCA.

Role of endoscopic ultrasound in the characterization of solid pseudopapillary neoplasm of the pancreas.

BACKGROUND: Solid pseudopapillary neoplasm (SPN) is an uncommon pathology of the pancreas with unpredictable malignant potential. Endoscopic ultrasound (EUS) assessment plays a vital role in lesion characterization and confirmation of the tissue diagnosis. However, there is a paucity of data regarding the imaging assessment of these lesions. AIM: To determine the characteristic EUS features of SPN and define its role in preoperative assessment. METHODS: This was an international, multicenter, retrospective, observational study of prospective cohorts from 7 large hepatopancreaticobiliary centers. All cases with postoperative histology of SPN were included in the study. Data collected included clinical, biochemical, histological and EUS characteristics. RESULTS: One hundred and six patients with the diagnosis of SPN were included. The mean age was 26 years (range 9 to 70 years), with female predominance (89.6%). The most frequent clinical presentation was abdominal pain (80/106; 75.5%). The mean diameter of the lesion was 53.7 mm (range 15 to 130 mm), with the slight predominant location in the head of the pancreas (44/106; 41.5%). The majority of lesions presented with solid imaging features (59/106; 55.7%) although 33.0% (35/106) had mixed solid/cystic characteristics and 11.3% (12/106) had cystic morphology. Calcification was observed in only 4 (3.8%) cases. Main pancreatic duct dilation was uncommon, evident in only 2 cases (1.9%), whilst common bile duct dilation was observed in 5 (11.3%) cases. One patient demonstrated a double duct sign at presentation. Elastography and Doppler evaluation demonstrated inconsistent appearances with no emergence of a predictable pattern. EUS guided biopsy was performed using three different types of needles: Fine needle aspiration (67/106; 63.2%), fine needle biopsy (37/106; 34.9%), and Sonar Trucut (2/106; 1.9%). The diagnosis was conclusive in 103 (97.2%) cases. Ninety-seven patients were treated surgically (91.5%) and the post-surgical SPN diagnosis was confirmed in all cases. During the 2-year follow-up period, no recurrence was observed. CONCLUSION: SPN presented primarily as a solid lesion on endosonographic assessment. The lesion tended to be located in the head or body of the pancreas. There was no consistent characteristic pattern apparent on either elastography or Doppler assessment. Similarly SPN did not frequently cause stricture of the pancreatic duct or common bile duct. Importantly, we confirmed that EUS-guided biopsy was an efficient and safe diagnostic tool. The needle type used does not appear to have a significant impact on the diagnostic yield. Overall SPN remains a challenging diagnosis based on EUS imaging with no pathognomonic features. EUS guided biopsy remains the gold standard in establishing the diagnosis.

Ultrasound-Based Risk Stratification System for the Assessment of Partially Cystic Thyroid Nodules.

OBJECTIVE: To develop and validate a risk stratification system for the prediction of malignancy in partially cystic thyroid nodules (PCTNs). METHODS: We retrospectively reviewed the sonography data of patients with PCTNs from 2 medical centers-Hangzhou Traditional Chinese Medicine Hospital and Hangzhou First People's Hospital-from January 2020 to December 2021. The independent risk factors for malignant PCTNs were evaluated using the univariate and multivariate logistic regression analyses. The nomogram prediction efficiency was assessed using the area under the curve and calibration curves. The decision curve analysis was used to determine the clinical value of the predictive model. RESULTS: A total of 285 patients were enrolled in this retrospective study, and of 301 PCTNs, 242 were benign and 59 were malignant. Younger age, hypoechoic, irregular margin, and microcalcifications were found to be the independent risk factors for malignant PCTNs. The area under the curve, sensitivity, and specificity were 0.860, 77.1%, and 84.7% in the training data set and 0.897, 91.7%, and 87.0% in the external validation data set, respectively. The total point of nomogram was >161, which showed the best to predict malignancy in PCTNs. CONCLUSION: Our findings demonstrated that the risk stratification system for the assessment of PCTNs showed good prediction capacities.

Ultrasound features affecting the sample adequacy after fine-needle aspiration of thyroid nodules with different risk stratification.

BACKGROUND: The inadequacy samples caused by the internal characteristic structure of thyroid nodules are difficult to be solved. OBJECTIVE: To evaluate the ultrasound features affecting the sample adequacy after fine-needle aspiration (FNA) of thyroid nodules with different risk stratification. METHODS: 592 thyroid nodules that underwent ultrasound-guided FNA were included in this retrospective study. The sample obtained by FNA were classified as inadequacy and adequacy according to the cytopathological results. Ultrasound features (ie., size, position, cystic predominance, composition, echo, shape, margin, and superficial annular calcification status) of the nodules were recorded and compared between the inadequacy sample group and adequacy sample group. RESULTS: Multiple logistic regression shows that preponderant cystic proportion (OR, 0.384; P = 0.041), extremely hypoechogenicity and hypoechogenicity (OR, 6.349; P = 0.006) were the independent influencing factors of inadequate samples after FNA in benign expected nodules. In addition, nodule size ≤10 mm (OR, 1.960; P = 0.010) and superficially annular calcification (OR, 4.600; P < 0.001) were independent influencing factors for inadequate samples after FNA in malignant expected nodules. CONCLUSION: The ultrasound features of hypoechogenicity or high cystic proportion in benign expected nodules and that of small size or annular calcification in malignant expected nodules were the risk factors for inadequacy samples by US-guided FNA.

Proportion of Malignancy and Evaluation of Sonographic Features of Thyroid Nodules Classified as Highly Suspicious Using ACR TI-RADS Criteria.

OBJECTIVES: The reported malignancy rate of highly suspicious thyroid nodules based on the ACR TI-RADS criteria (TI-RADS category 5 [TR5]) varies widely. The objective of our study was to determine the rate of malignancy of TR5 nodules at our institution. We also aimed to determine the predictive values of individual sonographic features, as well as the correlation of total points assigned to a nodule and rate of malignancy. METHODS: Our single-institution retrospective study evaluated 450 TR5 nodules that had cytology results available, in 399 patients over a 1-year period. Sonographic features and total TI-RADS points were determined by the interpreting radiologist. Statistical analyses included logistic regression models to find factors associated with increased odds of malignancy, and computing sensitivity, specificity, positive and negative predictive values of various individual sonographic features. RESULTS: Of the 450 nodules, 95 (21.1%, 95% exact confidence interval 17.4-25.2%) were malignant. Each additional TI-RADS point increased the odds of malignancy (adjusted odds ratio 1.35, 95% confidence interval 1.13-1.60, P < .001). "Very hypoechoic" was the sonographic feature with the highest specificity and positive predictive value for malignancy (95.5 and 44.8%, respectively), while "punctate echogenic foci" had the lowest positive predictive value (20.0%). CONCLUSIONS: The rate of malignancy of TR5 nodules at our institution was 21.1%, which is lower than other malignancy rates reported in the literature. The total number of points assigned on the basis of the TI-RADS criteria was positively associated with malignancy, which indicates that TR5 should be viewed as a spectrum of risk.

Nomogram to differentiate benign and malignant thyroid nodules in the American College of Radiology Thyroid Imaging Reporting and Data System level 5.

OBJECTIVES: To develop and validate a nomogram for differentiating benign and malignant thyroid nodules of American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) level 5 (TR5) and improving the performance of the guideline. METHODS: From May 2018 to December 2019, 640 patients with TR5 nodules were retrospectively included in the primary cohort. Univariate and multivariable analyses were performed to determine the risk factors for thyroid cancer. A nomogram was established on the basis of multivariable analyses; the performance of the nomogram was evaluated with respect to discrimination, calibration, and clinical usefulness. The nomogram model was also compared to the ACR score model. External validation was performed and the independent validation cohort contained 201 patients from April 2021 to January 2022. RESULTS: Multivariable analyses showed that age, tumour location, multifocality, concomitant Hashimoto's disease, neck lymph node status reported by ultrasound (US) and ACR score were the independent risk factors for thyroid cancer (all p < .05). The nomogram showed good discrimination, with an area under the curve (AUC) of 0.786 (95% confidence interval [CI]: 0.742-0.830) and 0.712 (95% CI: 0.615-0.809) in the primary cohort and external validation cohort, respectively. Decision curve analysis demonstrated the clinical usefulness of the model. Compared to the ACR score model, the nomogram showed higher AUC (0.786 vs. 0.626, p < .001) and specificity (0.783 vs. 0.391). CONCLUSIONS: The presented nomogram model, based on age, tumour features and ACR score, can differentiate benign and malignant thyroid nodules in TR5 and had a high specificity.

Elaboration and Validation of a Nomogram Based on Axillary Ultrasound and Tumor Clinicopathological Features to Predict Axillary Lymph Node Metastasis in Patients With Breast Cancer.

Background: This study aimed at constructing a nomogram to predict axillary lymph node metastasis (ALNM) based on axillary ultrasound and tumor clinicopathological features. Methods: A retrospective analysis of 281 patients with pathologically confirmed breast cancer was performed between January 2015 and March 2018. All patients were randomly divided into a training cohort (n = 197) and a validation cohort (n = 84). Univariate and multivariable logistic regression analyses were performed to identify the clinically important predictors of ALNM when developin1 g the nomogram. The area under the curve (AUC), calibration plots, and decision curve analysis (DCA) were used to assess the discrimination, calibration, and clinical utility of the nomogram. Results: In univariate and multivariate analyses, lymphovascular invasion (LVI), axillary lymph node (ALN) cortex thickness, and an obliterated ALN fatty hilum were identified as independent predictors and integrated to develop a nomogram for predicting ALNM. The nomogram showed favorable sensitivity for ALNM with AUCs of 0.87 (95% confidence interval (CI), 0.81-0.92) and 0.84 (95% CI, 0.73-0.92) in the training and validation cohorts, respectively. The calibration plots of the nomogram showed good agreement between the nomogram prediction and actual ALNM diagnosis (P > 0.05). Decision curve analysis (DCA) revealed the net benefit of the nomogram. Conclusions: This study developed a nomogram based on three daily available clinical parameters, with good accuracy and clinical utility, which may help the radiologist in decision-making for ultrasound-guided fine needle aspiration cytology/biopsy (US-FNAC/B) according to the nomogram score.

Evaluation of the pathological status of axillary lymph nodes after neoadjuvant chemotherapy based on multimodal ultrasound characteristics for breast cancer / 中华超声影像学杂志

Objective:To construct a diagnostic model based on the multimodal ultrasound imaging, and to predict the axillary lymph node (ALN) status of breast cancer patients after neoadjuvant chemotherapy (NAC).Methods:A total of 204 female breast cancer patients with ALN metastasis who had undergone puncture biopsy of aspiration in the Second Affiliated Hospital and Harbin Medical University Cancer Hospital between July 2017 to May 2021 were included. According to the pathological results of ALN surgery after NAC, the cases were divided into pathologically complete response (pCR) group and non-pCR group. The ultrasound images, immunohistochemistry and blood routine index were collected and compared between the two groups, the indexes whose P<0.02 were selected. In terms of logistic regression algorithm, a predictive model for the pathological state of axillary lymph nodes in breast cancer patients was established after NAC, and ROC curve was plotted to evaluate the performance of the model. Results:The P values for comparison between the two groups of the breast tumor size, blood flow resistance index (RI), elasticity score, lymph hilum structure, maximum cortical thickness, blood flow distribution, blood flow RI, and immunohistochemical detection indicators including estrogen receptor(ER), progesterone receptor(PR), human epidermal growth factor 2(HER-2), Ki67 molecular expressions were <0.20 by t test, Mann-Whitney U test, and χ 2 test analysis; in the multiple logistic regression analysis, tumor size, lymphatic hilum structure, maximum cortical thickness, lymph node blood flow distribution and blood flow resistance index, PR and HER-2 molecular expressions were the independent factors predicting the pathological status of axillary lymph nodes in breast cancer patients after NAC ( P<0.05). The performance of the predictive model was 0.870 (95% confidence interval: 0.819-0.922, P<0.05), with sensitivity of 86.82% and specificity of 70.67%. Conclusions:The model for predicting the pathological state of ALN in breast cancer patients after NAC using multi-modal ultrasound characteristic and immunohistochemical indexes achieves good diagnostic performance providing more objective evidence for the formulation of clinical treatment plans and prognostic evaluation.

Imaging diagnosis of a giant choledochal cyst in an infant.

The usual etiologies of giant abdominal cystic masses in infants are mesenteric cyst, enteric duplication cyst, ovarian cyst in females, cystic lymphangioma, however, the presentation of a choledochal cyst in a gigantic form, is unusual. The primary modality for diagnosis of this entity is ultrasound, followed by MRI. The characteristic ultrasound features of a choledochal cyst are a well-defined cystic lesion which may be found to replace any segment of the biliary tree and is distinctly separate from the gallbladder. The associated anomalies are biliary atresia, gallbladder atresia, hepatic fibrosis and those of the pancreatico-biliary ductal system. MRI with MRCP has a conclusive role in confirming the ultrasound diagnosis. Choledochal cysts are currently classified as proposed by Todani et al, into five types. Herein, we report the case study of a 4-month-old male infant afflicted with a gigantic, Type1 Choledochal cyst, complicated by perforation, which was diagnosed by us at the first instance itself, using ultrasound examination and confirmed by MRI. The diagnosis was further confirmed at surgery and histopathology. The recommended treatment of cyst resection accompanied by a hepatico-jejunostomy bypass procedure, was successfully performed in the reported infant.

Logistic Regression Analysis of Conventional Ultrasound, and Contrast-Enhanced Ultrasound Characteristics: Is It Helpful in Differentiating Benign and Malignant Superficial Lymph Nodes?

OBJECTIVES: This study aimed to screen the significant sonographic features for differentiation of benign and malignant superficial lymph nodes (LNs) by logistic regression analysis and fit a model to diagnose LNs. METHODS: A total of 204 pathological LNs were analyzed retrospectively. All the LNs underwent conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) examinations. A total of 16 suspicious sonographic features were used to assess LNs. All variables that were statistically related to the diagnosis of LNs were included in the logistic regression analysis in order to ascertain the significant features of diagnosing LNs, and to establish a logistic regression analysis model. RESULTS: The significant features in the logistic regression analysis model of diagnosing malignant LNs were absence of echogenic hilus, age, and absence of hilum after enhancement. According to the results of logistic regression analysis, the formula to predict whether LNs were malignant was established. The area under the receiver operating curve (ROC) was 0.908 and the accuracy, sensitivity, and specificity were 85.0%, 92.9%, and 85.3%, respectively. CONCLUSION: The logistic regression model for the significant sonographic features of conventional US and CEUS is an effective and accurate diagnostic tool for differentiating malignant and benign LNs.

Is There a Correlation between Multiparametric Assessment in Ultrasound and Intrinsic Subtype of Breast Cancer?

Molecular profile of breast cancer provides information about its biological activity, prognosis and treatment strategies. The purpose of our study was to investigate the correlation between ultrasound features and molecular subtypes of breast cancer. From June 2019 to December 2019, 86 patients (median age 57 years; range 32-88) with 102 breast cancer tumors were included in the study. The molecular subtypes were classified into five types: luminal A (LA), luminal B without HER2 overexpression (LB HER2-), luminal B with HER2 overexpression (LB HER2+), human epidermal growth factor receptor 2 positive (HER2+) and triple negative breast cancer (TNBC). Histopathological verification was obtained in core biopsy or/and post-surgery specimens in all cases. Univariate logistic regression analysis was performed to assess the association between the subtypes and ultrasound imaging features. Experienced radiologists assessed lesions according to the BIRADS-US lexicon. The ultrasound scans were performed with a Supersonic Aixplorer and Supersonix. Based on histopathological verification, the rates of LA, LB HER2-, LB HER2+, HER2+, and TNBC were 33, 17, 17, 16, 19, respectively. Both LB HER2+ and HER2+ subtypes presented higher incidence of calcification (OR = 3.125, p = 0.02, CI 0.0917-5.87) and HER2+ subtype presented a higher incidence of posterior enhancement (OR = 5.75, p = 0.03, CI 1.2257-32.8005), compared to other subtypes. The calcifications were less common in TNBC (OR = 0.176, p = 0.0041, CI 0.0469-0.5335) compared to other subtypes. There were no differences with regard to margin, shape, orientation, elasticity values and vascularity among five molecular subtypes. Our results suggest that there is a correlation between ultrasonographic features assessed according to BIRADS-US lexicon and BC subtypes with HER2 overexpression (both LB HER2+ and HER2+). It may be useful for identification of these aggressive subtypes of breast cancer.

A Scoring System for Assessing the Risk of Malignant Partially Cystic Thyroid Nodules Based on Ultrasound Features.

OBJECTIVE: To assess the ultrasound (US) features of partially cystic thyroid nodules (PCTNs) and to establish a scoring system to further improve the diagnostic accuracy. METHODS: A total of 262 consecutive nodules from September 2017 to March 2020 were included in a primary cohort to construct a scoring system. Moreover, 83 consecutive nodules were enrolled as an validation cohort from May 2018 to August 2020. All nodules were determined to be benign or malignant according to the pathological results after surgery or ultrasound-guided fine-needle aspiration (US-FNA). The US images and demographic characteristics of the patients were analyzed. The ultrasound features of PCTNs were extracted from primary cohort by two experienced radiologists. The features extracted were used to develop a scoring system using logistic regression analysis. Receiver operating characteristic (ROC) curves were applied to evaluate the diagnostic efficacy of the scoring system in both the primary cohort and validation cohort. In addition, the radiologists evaluated the benign and malignant PCTNs of the validation cohort according to the ACR TI-RADS guidelines and clinical experience, and the accuracy of their diagnosis were compared with that of the scoring system. RESULTS: Based on the eight features of PCTNs, the scoring system showed good differentiation and reproducibility in both cohorts. The scoring system was based on eight features of PCTNs and showed good performance. The area under the curve (AUC) was 0.876 (95% CI, 0.830 - 0.913) in the primary cohort and 0.829(95% CI, 0.730 - 0.903) in the validation cohort. The optimal cutoff value of the scoring system for the diagnosis of malignant PCTNs was 4 points, with a good sensitivity of 71.05% and specificity of 87.63%. The scoring system (AUC=0.829) was superior to radiologists (AUC= 0.736) in diagnosing PCTNs and is a promising method for clinical application. CONCLUSIONS: The scoring system described herein is a convenient and clinically valuable method that can diagnose PCTNs with relatively high accuracy. The use of this method to diagnose PCTNs, which have been previously underestimated, will allow PCTNs to receive reasonable attention, and assist radiologist to confidently diagnose the benignity or malignancy.

Analysis of differences of ultrasound features in different courses of thyroid carcinoma.

OBJECTIVE: To explore the changes of ultrasound features in patients with different courses of thyroid carcinoma, so as to provide a theoretical basis for the clinical treatment and diagnosis of thyroid carcinoma. METHODS: A total of 160 patients with thyroid carcinoma treated in our hospital were enrolled and divided into the early stage group (n=76) and the advanced stage group (n=84) according to the results of pathological examination, and further grouped into the lymph node metastasis group (n=78) and the non-metastasis group (n=82). Another 80 patients with benign thyroid disease were enrolled as the benign group. All the enrolled subjects were subjected to ultrasound examination, and the differences of ultrasound features were compared between the different groups. RESULTS: The average diameter of tumour and the proportion of nodular calcification and heterogeneous echo in the advanced stage group were significantly higher than those in the early stage group (P<0.05). The proportions of nodular calcification, heterogeneous echo, unsmooth margins, the aspect ratio of 1 or above, and irregular shapes in the malignant group were significantly higher than those in the benign group (P<0.05). The proportions of nodular calcification, heterogeneous echo, unsmooth margins, the aspect ratio of 1 or above, irregular shapes, multiple nodules, the largest diameter greater than 10 mm, rich blood flow, and absent halo in the lymph node metastasis group were significantly higher than those in the non-metastasis group (P<0.05). CONCLUSION: There were significant differences of ultrasound features in the different courses of thyroid carcinoma. Ultrasound examination can provide important reference for later clinical diagnosis and treatment.