Reference values of carotid intima-media thickness and arterial stiffness in Chinese adults based on ultrasound radio frequency signal: A nationwide, multicenter study.

BACKGROUND: Carotid intima-media thickness (IMT) and diameter, stiffness, and wave reflections, are independent and important clinical biomarkers and risk predictors for cardiovascular diseases. The purpose of the present study was to establish nationwide reference values of carotid properties for healthy Chinese adults and to explore potential clinical determinants. METHODS: A total of 3053 healthy Han Chinese adults (1922 women) aged 18-79 years were enrolled at 28 collaborating tertiary centers throughout China between April 2021 and July 2022. The real-time tracking of common carotid artery walls was achieved by the radio frequency (RF) ultrasound system. The IMT, diameter, compliance coefficient, ß stiffness, local pulse wave velocity (PWV), local systolic blood pressure, augmented pressure (AP), and augmentation index (AIx) were then automatically measured and reported. Data were stratified by age groups and sex. The relationships between age and carotid property parameters were analyzed by Jonckheere-Terpstra test and simple linear regressions. The major clinical determinants of carotid properties were identified by Pearson's correlation, multiple linear regression, and analyses of covariance. RESULTS: All the parameters of carotid properties demonstrated significantly age-related trajectories. Women showed thinner IMT, smaller carotid diameter, larger AP, and AIx than men. The ß stiffness and PWV were significantly higher in men than women before forties, but the differences reversed after that. The increase rate of carotid IMT (5.5 µm/year in women and 5.8 µm/year in men) and diameter (0.03 mm/year in both men and women) were similar between men and women. For the stiffness and wave reflections, women showed significantly larger age-related variations than men as demonstrated by steeper regression slopes (all P for age by sex interaction <0.05). The blood pressures, body mass index (BMI), and triglyceride levels were identified as major clinical determinants of carotid properties with adjustment of age and sex. CONCLUSIONS: The age- and sex-specific reference values of carotid properties measured by RF ultrasound for healthy Chinese adults were established. The blood pressures, BMI, and triglyceride levels should be considered for clinical application of corresponding reference values.

Research on the RZB-Type Three-Dimensional Drilling Strain Measurement System.

Borehole strain gauges play a crucial role in geophysical, seismological, and crustal dynamics studies. While existing borehole strain gauges are proficient in measuring horizontal strains within vertical boreholes, their effectiveness in capturing vertical and oblique strains is limited due to technical constraints arising from the cylindrical probe's characteristics. However, the accurate measurement of three-dimensional strain is essential for a comprehensive understanding of crustal tectonics, dynamics, and geophysics, particularly considering the diverse geological structures and force sources within the crustal medium. In this study, we present a novel approach to address this challenge by enhancing an existing horizontal-component borehole strain gauge with a bellows structure and line strain measurement technology to enable vertical and borehole oblique strain measurements. Integrating these enhancements with horizontal strain measurement capabilities enables comprehensive three-dimensional borehole strain measurements within the same hole section. The system was deployed and tested at the Gongxian seismic station in Sichuan Province. Clear observations of solid tides were recorded across horizontal, oblique, and vertical measurement units, with the tidal morphology and amplitude being consistent with the theoretical calculations. The achieved measurement sensitivity of 10-10 meets the requirements for borehole strain measurement, enabling the characterization of three-dimensional strain states within boreholes through association methods.

Infertility risk assessment with ultrasound in congenital adrenal hyperplasia male patients.

Testicular adrenal rest tumor (TART) is a prevalent complication associated with congenital adrenal hyperplasia (CAH), culminating in gonadal dysfunction and infertility. Early hormonal intervention is preventive, but excessive glucocorticoid poses risks. Developing reliable methods for early TART diagnosis and monitoring is crucial. The present study aims to formulate a scoring system to identify high-risk infertility through analysis of TART ultrasound features. Grayscale and power Doppler ultrasound were employed in this retrospective study to evaluate testicular lesions in male CAH patients. Lesion assessment encompassed parameters such as range, echogenicity, and blood flow, and these were subsequently correlated with semen parameters. Results of 49 semen analyzes from 35 patients demonstrated a notable inverse correlation between lesion scores and both sperm concentration (rs = - 0.83, P < 0.001) and progressive motility (rs = - 0.56, P < 0.001). The ROC curve areas for evaluating oligospermia and asthenozoospermia were calculated as 0.94 and 0.72, respectively. Establishing a lesion score threshold of 6 revealed a sensitivity of 75.00% and specificity of 93.94% for oligospermia and a sensitivity of 53.85% and specificity of 100.00% for asthenozoospermia. These findings underscore the potential utility of incorporating ultrasound into routine CAH patient management, facilitating timely interventions to preserve male fertility.

Ultrasound Viscosity Imaging in Breast Lesions: A Multicenter Prospective Study.

RATIONALE AND OBJECTIVES: To explore and validate the clinical value of ultrasound (US) viscosity imaging in differentiating breast lesions by combining with BI-RADS, and then comparing the diagnostic performances with BI-RADS alone. MATERIALS AND METHODS: This multicenter, prospective study enrolled participants with breast lesions from June 2021 to November 2022. A development cohort (DC) and validation cohort (VC) were established. Using histological results as reference standard, the viscosity-related parameter with the highest area under the receiver operating curve (AUC) was selected as the optimal one. Then the original BI-RADS would upgrade or not based on the value of this parameter. Finally, the results were validated in the VC and total cohorts. In the DC, VC and total cohorts, all breast lesions were divided into the large lesion, small lesion and overall groups respectively. RESULTS: A total of 639 participants (mean age, 46 years ± 14) with 639 breast lesions (372 benign and 267 malignant lesions) were finally enrolled in this study including 392 participants in the DC and 247 in the VC. In the DC, the optimal viscosity-related parameter in differentiating breast lesions was calculated to be A'-S2-Vmax, with the AUC of 0.88 (95% CI: 0.84, 0.91). Using > 9.97 Pa.s as the cutoff value, the BI-RADS was then modified. The AUC of modified BI-RADS significantly increased from 0.85 (95% CI: 0.81, 0.88) to 0.91 (95% CI: 0.87, 0.93), 0.85 (95% CI: 0.80, 0.89) to 0.90 (95% CI: 0.85, 0.93) and 0.85 (95% CI: 0.82, 0.87) to 0.90 (95% CI: 0.88, 0.92) in the DC, VC and total cohorts respectively (P < .05 for all). CONCLUSION: The quantitative viscous parameters evaluated by US viscosity imaging contribute to breast cancer diagnosis when combined with BI-RADS.

Clinical features combined with ultrasound characteristics to predict TERT promoter mutations in papillary thyroid carcinoma: a single-center study over the past 5 years.

Purpose: Telomerase reverse transcriptase (TERT) has been reported in papillary thyroid carcinoma (PTC). This study aimed to investigate the correlation of TERT promoter mutations with clinical and ultrasound (US) features in PTC and to develop a model to predict TERT promoter mutations. Methods: Preoperative US images, postoperative pathological features, and TERT promoter mutation information were evaluated in 365 PTC patients confirmed by surgery. Univariate and multivariate factor analyses were performed to identify risk factors for TERT promoter mutations. A predictive model was established to assess the clinical predictive value. Results: Of the 365 patients with PTC (498 nodules), the number of those with TERT promoter mutations was 67 cases (75 nodules), and the number of those without mutations was 298 cases (423 nodules). The median age was 40 years in the wild-type group and 60 years in the mutant group. Male patients made up 35.82% of the mutant group and 22.82% of the wild-type group. Multivariate analysis revealed that the independent risk factors associated with the occurrence of TERT promoter mutation in PTC were as follows: older age (odds ratio (OR) = 1.07; p = 0.002), maximum diameter of ≥ 10 mm (OR = 3.94; p < 0.0001), unilateral (OR = 4.15; p < 0.0001), multifocal (OR = 7.69; p < 0.0001), adjacent to the thyroid capsule (OR = 1.94; p = 0.044), and accompanied by other benign nodules (OR = 1.94, p = 0.039). A predictive model was established, and the area under the curve (AUC) of the receiver operating characteristic was 0.839. TERT promoter mutations were associated with high-risk US and clinical features compared with the wild-type group. Conclusion: TERT promoter mutations were associated with older ages. They were also found to be multifocal, with a maximum diameter of ≥ 10 mm, unilateral, adjacent to the thyroid capsule, and accompanied by other benign nodules. The predictive model was of high diagnostic value.

Active landslide detection using integrated remote sensing technologies for a wide region and multiple stages: A case study in southwestern China.

While significant progress has been achieved in utilizing remote sensing technologies for landslide investigation in China, there remains a notable gap in consolidating information on applicable conditions, application stages, and workflows across various remote sensing methodologies. This paper proposes a comprehensive framework for active landslide detection, incorporating multiple stages and data sources, successfully implemented in a vast region of southwestern China. Furthermore, detailed discussions are provided on the effects of the geometric distortion, land cover type, and various InSAR methods on the accuracy of active landslide identification results. Additionally, the paper delves into the advantages of integrated remote sensing technology in active landslide investigation, encompassing the assessment of current landslide activity status, precise delineation of boundaries, identification of different deformation stages, and determination of damage patterns. Through comprehensive analysis of multisource data, it enhances understanding of the active landslide process, ultimately contributing to the mitigation of casualties and property damage.

Risk factors and nomogram to predict skip metastasis in papillary thyroid carcinoma.

Background: Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy. Skip metastases of PTCs are easily misdiagnosed before surgery, and it could lead to re-operation and affect the prognosis. Although there are a few studies about nomograms for predicting central lymph node metastases (CLNM) or lateral lymph node metastases (LLNM) of PTCs, there are few studies about nomograms for skip metastases. Based on the clinical and ultrasonographic characteristics of patients with PTCs, the aim of our study was to investigate the risk factors and establish a nomogram for predicting the risk of skip metastases in PTCs. Methods: This study enrolled 218 PTCs patients with lateral cervical lymph node metastases and their data were analyzed retrospectively. According to the postoperative pathological results, the patients were divided into skip-positive group and skip-negative group. In order to establish the nomogram, univariate and multivariate analyses were used to estimate risk factors of skip metastases. The receiver operating characteristic (ROC) curve, internal calibration plot and decision curve analysis (DCA) were used to evaluate the nomogram model's efficacy. Results: There were statistical differences between skip-positive group and skip-negative group in tumor location, the maximum diameter (D) and capsule invasion (P<0.05). No statistical differences were observed in sex, age, Hashimoto's thyroiditis, multifocality, anteroposterior diameter/transverse diameter (A/T) ratio, shape, margin, microcalcification, intra-nodular vascularity and preoperative serum thyroglobulin (Tg) (P≥0.05). The risk factors of skip metastases in PTCs were D ≤10 mm, location in the upper portion and capsule invasion. The area under the curve (AUC) of nomogram was 0.877, the accuracy was 85.32%, the sensitivity was 60.98%, and the specificity was 90.96%. The calibration curve and the Hosmer-Lemeshow goodness of fit test showed that the consistency between the nomogram and the actual observation was good. The DCA showed that most PTC patients might benefit from the predictive nomogram model. Conclusions: A nomogram for predicting skip metastases in PTCs may be useful in clinical diagnosis and treatment.

Diffusion-Weighted MRI-Based Virtual Elastography and Shear-Wave Elastography for the Assessment of Breast Lesions.

BACKGROUND: Diffusion-weighted imaging (DWI)-based virtual MR elastography (DWI-vMRE) in the assessment of breast lesions is still in the research stage. PURPOSE: To investigate the usefulness of elasticity values on DWI-vMRE in the evaluation of breast lesions, and the correlation with the values calculated from shear-wave elastography (SWE). STUDY TYPE: Prospective. POPULATION/SUBJECTS: 153 patients (mean age ± standard deviation: 55 ± 12 years) with 153 pathological confirmed breast lesions (24 benign and 129 malignant lesions). FIELD STRENGTH/SEQUENCE: 1.5-T MRI, multi-b readout segmented echo planar imaging (b-values of 0, 200, 800, and 1000 sec/mm2 ). ASSESSMENT: For DWI-vMRE assessment, lesions were manually segmented using apparent diffusion coefficient (ADC0-1000 ) map, then the region of interests were copied to the map of shifted-ADC (sADC200-800 , sADC 200-1500 ). For SWE assessment, the shear modulus of the lesions was measured by US elastic modulus (µUSE ). Intraclass/interclass kappa coefficients were calculated to measure the consistency. STATISTICAL TESTS: Pearson's correlation was used to assess the relationship between sADC and µUSE . A receiver operating characteristic analysis with the area under the curve (AUC) was performed to compare the diagnostic accuracy between benign and malignant breast lesions of sADC and µUSE . A P value <0.05 was considered statistically significant. RESULTS: There were significant differences between benign and malignant breast lesions of µUSE (24.17 ± 10.64 vs. 37.20 ± 12.61), sADC200-800 (1.38 ± 0.31 vs. 0.97 ± 0.18 × 10-3 mm2 /sec), and sADC200-1500 (1.14 ± 0.30 vs. 0.78 ± 0.13 × 10-3 mm2 /sec). In all breast lesions, a moderate but significant correlation was observed between µUSE and sADC200-800 /sADC200-1500 (r = -0.49/-0.44). AUC values to differentiate benign from malignant lesions were as follows: µUSE , 0.78; sADC200-800 , 0.89; sADC200-1500 , 0.89. DATA CONCLUSIONS: Both SWE and DWI-vMRE could be used for the differentiation of benign versus malignant breast lesions. Furthermore, DWI-vMRE with the use of sADC show relatively higher AUC values than SWE. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Predictive nomogram using multimodal ultrasonographic features for axillary lymph node metastasis in early­stage invasive breast cancer.

Axillary lymph node (ALN) status is a key prognostic factor in patients with early-stage invasive breast cancer (IBC). The present study aimed to develop and validate a nomogram based on multimodal ultrasonographic (MMUS) features for early prediction of axillary lymph node metastasis (ALNM). A total of 342 patients with early-stage IBC (240 in the training cohort and 102 in the validation cohort) who underwent preoperative conventional ultrasound (US), strain elastography, shear wave elastography and contrast-enhanced US examination were included between August 2021 and March 2022. Pathological ALN status was used as the reference standard. The clinicopathological factors and MMUS features were analyzed with uni- and multivariate logistic regression to construct a clinicopathological and conventional US model and a MMUS-based nomogram. The MMUS nomogram was validated with respect to discrimination, calibration, reclassification and clinical usefulness. US features of tumor size, echogenicity, stiff rim sign, perfusion defect, radial vessel and US Breast Imaging Reporting and Data System category 5 were independent risk predictors for ALNM. MMUS nomogram based on these factors demonstrated an improved calibration and favorable performance [area under the receiver operator characteristic curve (AUC), 0.927 and 0.922 in the training and validation cohorts, respectively] compared with the clinicopathological model (AUC, 0.681 and 0.670, respectively), US-depicted ALN status (AUC, 0.710 and 0.716, respectively) and the conventional US model (AUC, 0.867 and 0.894, respectively). MMUS nomogram improved the reclassification ability of the conventional US model for ALNM prediction (net reclassification improvement, 0.296 and 0.288 in the training and validation cohorts, respectively; both P<0.001). Taken together, the findings of the present study suggested that the MMUS nomogram may be a promising, non-invasive and reliable approach for predicting ALNM.

Volume reduction rate of radiofrequency ablation in ≤ 2 cm Bethesda IV thyroid nodules.

OBJECTIVE: This prospective observational study aimed to evaluate the efficacy of radiofrequency ablation (RFA) in treating ≤ 2 cm thyroid nodules with Bethesda IV cytology and C-TIRADS 4A categorization. Additionally, the factors influencing the completed absorption of ablation (CAA) were examined. METHODS: A total of 62 cases with 62 nodules underwent ultrasound-guided RFA and were included in the study. The volume reduction rate (VRR), CAA, and incomplete absorption of ablation (IAA) were assessed at the 1st, 3rd, 6th, and subsequent 6-month follow-ups. Clinical and ultrasound features were compared between the CAA and IAA groups at the 12th month follow-up. RESULTS: The average VRR at the 1st, 3rd, 6th, 12th month, and last follow-up were -88.6%, 16.0%, 59.7%, 82.0%, and 98.2%, respectively. More than half of the nodules achieved a 90% VRR after 1 year of RFA, with 88.7% demonstrating CAA at the end of the study (follow-up duration of 14 to 63 months). Nodules with grade 3 vascularity and those associated with chronic thyroiditis showed delayed CAA at the 12th month follow-up (p = 0.036 and 0.003, respectively). CONCLUSION: RFA is an effective technique for treating ≤ 2 cm thyroid nodules with Bethesda IV cytology and C-TIRADS 4A categorization. Nodules with grade 3 blood supply and patients with chronic thyroiditis exhibited an impact on the completed absorption following RFA. CLINICAL RELEVANCE STATEMENT: Our study has shown that radiofrequency ablation is an effective treatment for ≤ 2 cm thyroid nodules classified as Bethesda IV cytology. However, we identified that high vascularity of the nodule and chronic thyroiditis are adverse factors affecting the completed absorption of the ablation. KEY POINTS: •Radiofrequency ablation (RFA) is an effective technique for treatment of ≤ 2 cm Bethesda IV category thyroid nodules. •Higher blood supply and chronic thyroiditis influence the completed absorption after RFA.

Machine Learning-Based Breast Tumor Ultrasound Radiomics for Pre-operative Prediction of Axillary Sentinel Lymph Node Metastasis Burden in Early-Stage Invasive Breast Cancer.

OBJECTIVE: The aim of the work described here was to assess the application of ultrasound (US) radiomics with machine learning (ML) classifiers to the prediction of axillary sentinel lymph node metastasis (SLNM) burden in early-stage invasive breast cancer (IBC). METHODS: In this study, 278 early-stage IBC patients with at least one SLNM (195 in the training set and 83 in the test set) were studied at our institution. Pathologic SLNM burden was used as the reference standard. The US radiomics features of breast tumors were extracted by using 3D-Slicer and PyRadiomics software. Four ML classifiers-linear discriminant analysis (LDA), support vector machine (SVM), random forest (RF) and decision tree (DT)-were used to construct radiomics models for the prediction of SLNM burden. The combined clinicopathologic-radiomics models were also assessed with respect to sensitivity, specificity, accuracy and areas under the curve (AUCs). RESULTS: Among the US radiomics models, the SVM classifier achieved better predictive performance with an AUC of 0.920 compared with RF (AUC = 0.874), LDA (AUC = 0.835) and DT (AUC = 0.800) in the test set. The clinicopathologic model had low efficacy, with AUCs of 0.678 and 0.710 in the training and test sets, respectively. The combined clinicopathologic (C) factors and SVM classifier (C + SVM) model improved the predictive ability with an AUC of 0.934, sensitivity of 86.7%, specificity of 89.9% and accuracy of 91.0% in the test set. CONCLUSION: ML-based US radiomics analysis, as a novel and promising predictive tool, is conducive to a precise clinical treatment strategy.

Musculoskeletal Biomaterials: Stimulated and Synergized with Low Intensity Pulsed Ultrasound.

Clinical biophysical stimulating strategies, which have significant effects on improving the function of organs or treating diseases by causing the salutary response of body, have shown many advantages, such as non-invasiveness, few side effects, and controllable treatment process. As a critical technique for stimulation, the low intensity pulsed ultrasound (LIPUS) has been explored in regulating osteogenesis, which has presented great promise in bone repair by delivering a combined effect with biomaterials. This review summarizes the musculoskeletal biomaterials that can be synergized with LIPUS for enhanced biomedical application, including bone regeneration, spinal fusion, osteonecrosis/osteolysis, cartilage repair, and nerve regeneration. Different types of biomaterials are categorized for summary and evaluation. In each subtype, the verified biological mechanisms are listed in a table or graphs to prove how LIPUS was effective in improving musculoskeletal tissue regeneration. Meanwhile, the acoustic excitation parameters of LIPUS that were promising to be effective for further musculoskeletal tissue engineering are discussed, as well as their limitations and some perspectives for future research. Overall, coupled with biomimetic scaffolds and platforms, LIPUS may be a powerful therapeutic approach to accelerate musculoskeletal tissue repair and even in other regenerative medicine applications.

Design of A High-Precision Component-Type Vertical Pendulum Tiltmeter Based on FPGA.

This paper presents a high-precision component-type vertical pendulum tiltmeter based on an FPGA (Field Programmable Gate Array) that improves the utility and reliability of geophysical field tilt observation instruments. The system is designed for rapid deployment and offers flexible and efficient adaptability. It comprises a pendulum body, a triangular platform, a locking motor and sealing cover, a ratiometric measurement bridge, a high-speed ADC, and an FPGA embedded system. The pendulum body is a plumb-bob-type single-suspension wire vertical pendulum capable of measuring ground tilt in two orthogonal directions simultaneously. It is installed on a triangular platform, sealed as a whole, and equipped with a locking motor to withstand a free-fall impact of 2 m. The system utilizes a differential capacitance ratio bridge in the measurement circuit, replacing analog circuits with high-speed AD sampling and FPGA digital signal processing technology. This approach reduces hardware expenses and interferences from active devices. The system also features online compilation functionality for flexible measurement parameter settings, high reliability, ease of use, and rapid deployment without the need for professional technical personnel. The proposed tiltmeter holds significant importance for further research in geophysics.

A Multi-Channel Borehole Strain Measurement and Acquisition System Based on FPGA.

In this study, an FPGA(Field Programmable Gate Array)-based borehole strain measurement system was designed that makes extensive use of digital signal processing operations to replace analog circuits. Through the formidable operational capability of FPGA, the sampled data were filtered and denoised to improve the signal-to-noise ratios. Then, with the goal of not reducing observational accuracy, the signal amplification circuit was removed, the excitation voltage was reduced, and the dynamic range of the primary adjustments was expanded to 130 dB. The system's online compilation function made it more flexible to changes in measurement parameters, allowing it to adapt to various needs. In addition, the efficiency of the equipment use was enhanced. The actual observational results showed that this study's FPGA-based borehole strain measurement system had a voltage resolution higher than 1 µV. Clear solid tides were successfully recorded in low-frequency bands, and seismic wave strain was accurately recorded in high-frequency bands. The arrival times and seismic phases of the seismic waves S and P were clearly recorded, which met the requirements for geophysical field deformation observations. Therefore, the system proposed in this study is of major significance for future analyses of geophysical and crust deformation observations.

Generalizability and Diagnostic Performance of AI Models for Thyroid US.

Background Artificial intelligence (AI) models have improved US assessment of thyroid nodules; however, the lack of generalizability limits the application of these models. Purpose To develop AI models for segmentation and classification of thyroid nodules in US using diverse data sets from nationwide hospitals and multiple vendors, and to measure the impact of the AI models on diagnostic performance. Materials and Methods This retrospective study included consecutive patients with pathologically confirmed thyroid nodules who underwent US using equipment from 12 vendors at 208 hospitals across China from November 2017 to January 2019. The detection, segmentation, and classification models were developed based on the subset or complete set of images. Model performance was evaluated by precision and recall, Dice coefficient, and area under the receiver operating characteristic curve (AUC) analyses. Three scenarios (diagnosis without AI assistance, with freestyle AI assistance, and with rule-based AI assistance) were compared with three senior and three junior radiologists to optimize incorporation of AI into clinical practice. Results A total of 10 023 patients (median age, 46 years [IQR 37-55 years]; 7669 female) were included. The detection, segmentation, and classification models had an average precision, Dice coefficient, and AUC of 0.98 (95% CI: 0.96, 0.99), 0.86 (95% CI: 0.86, 0.87), and 0.90 (95% CI: 0.88, 0.92), respectively. The segmentation model trained on the nationwide data and classification model trained on the mixed vendor data exhibited the best performance, with a Dice coefficient of 0.91 (95% CI: 0.90, 0.91) and AUC of 0.98 (95% CI: 0.97, 1.00), respectively. The AI model outperformed all senior and junior radiologists (P < .05 for all comparisons), and the diagnostic accuracies of all radiologists were improved (P < .05 for all comparisons) with rule-based AI assistance. Conclusion Thyroid US AI models developed from diverse data sets had high diagnostic performance among the Chinese population. Rule-based AI assistance improved the performance of radiologists in thyroid cancer diagnosis. © RSNA, 2023 Supplemental material is available for this article.

Reliable neck sonography of nodal thyroglobulin to diagnose recurrent/persistent disease from papillary thyroid carcinoma.

OBJECTIVE: This study evaluates the correlation between the sonographic features and the nodal fine-needle aspiration thyroglobulin (FNA-Tg) in papillary thyroid carcinoma (PTC) patients with the recurrent/persistent lymph node for the purpose of the reasonable selection of lymph nodes. METHODS: This study prospectively contained PTC patients with the suspicious cervical lymph nodes in one medical center from April 2018 to January 2019. Each suspected lymph node was aspirated with a 22-gauge needle and the value of FNA-Tg was measured as well. RESULTS: There were 136 lymph nodes related to the disease involved. The FNA-Tg levels of 89 (65.44%) metastatic lymph nodes were significantly higher than those of the benign. The median value of the former was 631.550 ng/mL while the latter was 0.056 ng/mL (p = 0.000). The cut-off value of the metastatic lymph nodes diagnosed by FNA-Tg was 2.71 ng/mL, and 6.5 by FNA-Tg/sTg. The suspicious ultrasonographic features including cystic, hyperechoic content, and lack of hilum were closely related to the high level of FNA-Tg value (p < 0.05). However, the round shape (Solbiati index <2) and calcification were not significantly correlated with the positive FNA-Tg (p > 0.05). CONCLUSION: FNA-Tg is an effective supplement to fine-needle aspiration (FNA) cytology in the nodal metastasis diagnosis. The FNA-Tg level was much higher in the metastatic lymph nodes. The reliable sonographic features of lymph nodes suggested the positive FNA-Tg were cystic content, hyperechoic content and lack hilum. Solbiati index <2 and calcification did not show an exact correlation with the result of FNA-Tg.

Virtual elastography ultrasound via generative adversarial network for breast cancer diagnosis.

Elastography ultrasound (EUS) imaging is a vital ultrasound imaging modality. The current use of EUS faces many challenges, such as vulnerability to subjective manipulation, echo signal attenuation, and unknown risks of elastic pressure in certain delicate tissues. The hardware requirement of EUS also hinders the trend of miniaturization of ultrasound equipment. Here we show a cost-efficient solution by designing a deep neural network to synthesize virtual EUS (V-EUS) from conventional B-mode images. A total of 4580 breast tumor cases were collected from 15 medical centers, including a main cohort with 2501 cases for model establishment, an external dataset with 1730 cases and a portable dataset with 349 cases for testing. In the task of differentiating benign and malignant breast tumors, there is no significant difference between V-EUS and real EUS on high-end ultrasound, while the diagnostic performance of pocket-sized ultrasound can be improved by about 5% after V-EUS is equipped.

Clinical and Sonographic Features of Noninvasive Follicular Thyroid Neoplasm With Papillary-Like Nuclear Features: A Retrospective Study.

ABSTRACT: This study was designed to investigate the clinical and sonographic features of noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTPs) as compared with classical papillary thyroid carcinoma (cPTC), follicular adenoma (FA), and follicular thyroid carcinoma (FTC). A total of 178 patients were enrolled in this study. The clinical characteristics and sonographic features of thyroid nodules were compared between NIFTP and cPTC or FA/FTC. All nodules were reclassified according to the Thyroid Ultrasound Imaging Reporting and Data System and American Thyroid Association guidelines classification. The mean size of NIFTP was 29.91 ± 14.71 mm, which was larger than that of cPTC ( P = 0.000). Significant difference was found in lymph node metastases between NIFTP and cPTC ( P = 0.000). Most NIFTPs showed solid composition, hypoechoic echogenicity, smooth margin, wider than tall shape, none echogenic foci, absence of halo, and perinodular vascularity, which were similar with FA and FTC. Compared with NIFTP, hypoechoic and very hypoechoic, taller than wide, irregular margin, punctate echogenic foci, absence of halo, and low vascularity were more commonly observed in cPTC. There were statistical differences both in American College of Radiology Thyroid Ultrasound Imaging Reporting and Data System and in American Thyroid Association classification between NIFTP and cPTC ( P < 0.05), but there were no significant differences between NIFTP and FTC/FA ( P > 0.05). The ultrasonographic characteristics of NIFTP were obviously different from cPTC but overlapped with FTC and FA. Ultrasound could help increase preoperative attention of NIFTP in an appropriate clinical setting, which may lead to a more conservative treatment approach.

Clinical and Ultrasonographic Features of Papillary Thyroid Carcinoma Located in the Isthmus.

ABSTRACT: The aim of this research was to investigate the clinical and ultrasonographic features of papillary thyroid carcinoma (PTC) in the isthmus. A total of 823 patients with 823 PTCs including 133 in the isthmus and 690 in the lateral lobe were included in our study. All patients were confirmed by postoperative pathology. The clinical and ultrasonographic characteristics were retrospectively analyzed and compared. Univariate analysis and multivariate logistic regression analysis were performed. Multifactor analyses showed that PTC in the isthmus was significantly different from PTC originating from the lateral lobe in aspect ratio, microcalcification, extrathyroid extension, lymph node metastases, and lymph node density ( P < 0.05, for all). There were no significant differences in age, sex, tumor size, margin, halo, echogenicity, and homogeneity ( P > 0.05, for all). The results indicated that the sonographic appearances of PTC in the isthmus were relatively atypical; however, it had a higher incidence of extrathyroidal extension, central lymph node metastasis, and a tendency of higher lymph node density. Therefore, more careful ultrasound evaluation should be performed for these nodules.

Ultrasound-based deep learning in the establishment of a breast lesion risk stratification system: a multicenter study.

OBJECTIVES: To establish a breast lesion risk stratification system using ultrasound images to predict breast malignancy and assess Breast Imaging Reporting and Data System (BI-RADS) categories simultaneously. METHODS: This multicenter study prospectively collected a dataset of ultrasound images for 5012 patients at thirty-two hospitals from December 2018 to December 2020. A deep learning (DL) model was developed to conduct binary categorization (benign and malignant) and BI-RADS categories (2, 3, 4a, 4b, 4c, and 5) simultaneously. The training set of 4212 patients and the internal test set of 416 patients were from thirty hospitals. The remaining two hospitals with 384 patients were used as an external test set. Three experienced radiologists performed a reader study on 324 patients randomly selected from the test sets. We compared the performance of the DL model with that of three radiologists and the consensus of the three radiologists. RESULTS: In the external test set, the DL model achieved areas under the receiver operating characteristic curve (AUCs) of 0.980 and 0.945 for the binary categorization and six-way categorizations, respectively. In the reader study set, the DL BI-RADS categories achieved a similar AUC (0.901 vs. 0.933, p = 0.0632), sensitivity (90.98% vs. 95.90%, p = 0.1094), and accuracy (83.33% vs. 79.01%, p = 0.0541), but higher specificity (78.71% vs. 68.81%, p = 0.0012) than those of the consensus of the three radiologists. CONCLUSIONS: The DL model performed well in distinguishing benign from malignant breast lesions and yielded outcomes similar to experienced radiologists. This indicates the potential applicability of the DL model in clinical diagnosis. KEY POINTS: • The DL model can achieve binary categorization for benign and malignant breast lesions and six-way BI-RADS categorizations for categories 2, 3, 4a, 4b, 4c, and 5, simultaneously. • The DL model showed acceptable agreement with radiologists for the classification of breast lesions. • The DL model performed well in distinguishing benign from malignant breast lesions and had promise in helping reduce unnecessary biopsies of BI-RADS 4a lesions.