Search

Objectives: To evaluate the preoperative diagnostic value of contrast-enhanced lymphatic ultrasound (CEUS) for the sentinel lymph node (SLN) status in early breast cancer. Materials and methods: We prospectively recruited 102 consecutive patients with clinically node-negative early breast cancer from July 2021 to October 2021. All patients underwent conventional US and percutaneous CEUS examinations. The CEUS of SLNs were classified into four enhancement patterns: homogeneous (I), featured inhomogeneous (II), focal defect (III), and no enhancement (IV). The diagnostic performance of conventional US and CEUS for SLN metastasis was assessed by receiver operating characteristic (ROC) curves and decision curves. Results: A total of 78 women were enrolled in this study, including 55, 18, and 5 patients with negative axilla, 1–2, and ≥ 3 metastastic SLNs pathologically, respectively. The identification rate of SLNs by CEUS was 100%. Patterns I and II can select 91.7% (44/48) of patients with disease-free axilla, while patterns III and IV had higher percentages of metastasis (65.2%, p < 0.001 and 57.1%, p < 0.002, respectively). For the SLN metastatic burden, 100% (48/48) of patients with pattern I/II had ≤ 2 metastatic SLNs. Compared with conventional US, the CEUS enhancement patterns showed significant improvement in diagnosing metastatic SLNs (0.813 vs 0.601, p < 0.001). CEUS had greater clinical benefits and correctly reclassified 48% of metastatic SLNs (p < 0.001) without sacrificing the classification accuracy of negative SLNs (p = 0.25), and could improve prediction accuracy by 0.42 (p < 0.001). Conclusions: CEUS demonstrated better diagnostic performance and greater clinical benefits than conventional US for the preoperative diagnosis of SLNs, showing its potential to select candidates for precluding axillary surgery in early breast cancer. Key Points: • The homogeneous and featured inhomogeneous enhancement of SLNs are highly suggestive of negative LNs, while focal defect (p < 0.001) and no enhancement (p < 0.002) patterns had higher percentages of metastasis. • The proportion of SLNs with highly suspicious signs on conventional US increases as the type of enhancement pattern increases (no suspicious signs in pattern I/II, 34.8% in pattern III, and 85.7% in pattern IV). • Compared with conventional US, CEUS improved the area under the receiver operating characteristic curve (0.813 vs. 0.601, p < 0.001) and had greater clinical benefits (IDI = 0.42, p < 0.001) for the diagnosis of axillary metastasis. [ABSTRACT FROM AUTHOR]

Objectives: To establish a prediction model for evaluating the axillary lymph node (ALN) status of patients with T1/T2 invasive breast cancer based on radiomics analysis of US images of primary breast lesions. Methods: Between August 2016 and November 2018, a total of 343 patients with histologically proven malignant breast tumors were included in this study and randomly assigned to the training and validation groups at a ratio of 7:3. ALN tumor burden was defined as low (< 3 metastatic ALNs) or high (≥ 3 metastatic ALNs). Radiomics features were obtained using the PyRadiomics package, and the radiomics score was established by least absolute shrinkage and selection operator regression. A nomogram combining the breast cancer US radiomics score with patient age and lesion size was generated based on the multivariate logistic regression results. Results: In the training and validation cohorts, 29.1% (69/237) and 32.08% (34/106) of patients were pathologically diagnosed with more than 2 metastatic ALNs, respectively. The radiomics score consisted of 16 US features, and patient age and lesion diameter identified by US were included to construct the model. The AUC of the model was 0.846 (95% CI, 0.790–0.902) for the training cohort and 0.733 (95% CI, 0.613–0.852) for the validation cohort. The calibration curves showed good agreement between the predictions and observations. Conclusions: Our novel nomogram demonstrates high accuracy in predicting ALN tumor burden in breast cancer patients. We also suggest further development of PyRadiomics to improve US radiomics. Key Points: • A nomogram based on US was developed to predict ALN tumor burden (low, < 3 metastatic ALNs; high, ≥ 3 metastatic ALNs). • The nomogram could assist clinicians in evaluating treatment strategies for T1/T2 invasive breast cancer. [ABSTRACT FROM AUTHOR]

Introduction and hypothesis: Pelvic organ prolapse (POP) is a common medical condition universally. In addition to physical examination, experts have increasingly turned their attention to ultrasound in diagnosing POP for its low cost and dynamic imaging. The aim of this paper is to provide an overview of the methods of pelvic floor ultrasound in diagnosing POP, which has been lacking up till now. Methods: We included original papers comparing the outcome of the Pelvic Organ Prolapse Quantification system and ultrasound, published from 2008 to present in English, using electronic databases (MEDLINE, EMBASE, CENTRAL, PUBMED). All stages of the review were conducted in parallel by two reviewers. Results: Fifteen papers were included. We found that current methods have advantages and limitations. The main methods are to measure levator hiatus-related parameters and distances between the lowest point of the pelvic organs and reference lines during Valsalva maneuver, contraction, and at rest. Conclusions: Pelvic floor ultrasound is valuable in diagnosing POP, yet suffers from a weakness in precision compared with physical examination. From the existing research, we found that the differences in baseline data such as weight, height, ethnicity, etc., may affect the cutoffs of the above-mentioned parameters. Further research is required to find one appropriate cutoff for each parameter, even if it is necessary to set group values for every parameter according to varying situations. [ABSTRACT FROM AUTHOR]

Objectives: To develop and validate a nomogram for predicting ≥ 3 metastatic axillary lymph nodes (ALNs) in early breast cancer with no palpable axillary adenopathy by clinicopathologic data, contrast-enhanced (CE) lymphatic ultrasound (US), and grayscale findings of sentinel lymph nodes (SLNs). Materials and methods: Women with T1-2N0 invasive breast cancer were consecutively recruited for the CE lymphatic US. Patients from Center 1 were grouped into development and internal validation cohorts at a ratio of 2:1. The external validation cohort was constructed from Center 2. The clinicopathologic data and US findings of SLNs were analyzed. A nomogram was developed to predict women with ≥ 3 metastatic ALNs. Nomogram performance was assessed with the area under the receiver operating characteristic curve (AUC) and calibration curve analysis. Results: One hundred seventy-nine from Center 1 were considered the development cohorts. The remaining 90 participants from Center 1 were internal cohorts and 197 participants from Center 2 were external validation cohorts. The US findings of no enhancement (odds ratio (OR), 15.3; p = 0.01), diffuse (OR, 19.1; p = 0.01) or focal eccentric (OR, 27.7; p = 0.003) cortical thickening, and absent hilum (OR, 169.7; p < 0.001) were independently associated with ≥ 3 metastatic ALNs. Compared to grayscale US or CE lymphatic US alone, the nomogram showed the highest AUC of 0.88 (0.85, 0.91). The nomogram showed a calibration slope of 1.0 (p = 0.80–0.81; Brier = 0.066–0.067) in validation cohorts in predicting ≥ 3 metastatic ALNs. Conclusion: Patients likely to have ≥ 3 metastatic ALNs were identified by combining the lymphatic and grayscale US findings of SLNs. Our nomogram could aid in multidisciplinary treatment decision-making. Trial registration: This trial is registered on www.chictr.org.cn: ChiCTR2000031231. Registered March 25, 2020. Critical relevance statement: A nomogram combining lymphatic CEUS and grayscale US findings of SLNs could identify early breast cancer patients with low or high axillary tumor burden preoperatively, which is more applicable to the Z0011 era. Our nomogram could be useful in aiding multidisciplinary treatment decision-making for patients with early breast cancer. Key points: • CEUS can help identify and diagnose SLN in early breast cancer preoperatively. • Combining lymphatic and grayscale US findings can predict axillary tumor burden. • The nomogram showed a high diagnostic value in validation cohorts. [ABSTRACT FROM AUTHOR]

Background: Acne treatment may fail or cause undesirable side effects due to inaccurate evaluation. High‐frequency ultrasound (HFUS) can monitor systemic treatment in patients with moderate‐to‐severe acne vulgaris. Materials and methods: In this prospective study, consecutive patients with moderate‐to‐severe acne vulgaris were recruited. Patients were graded by a comprehensive clinical assessment before and after therapy. Simultaneous HFUS grading was independently evaluated according to the sonographic scoring system for acne (SSSA). Clinical and HFUS grades were compared through kappa analysis. Results: A total of 70 patients were enrolled. At baseline, 36 (51.4%) and 34 (48.6%) patients were graded as moderate and severe, respectively, through clinical assessment. However, 27 patients (38.6%) scored SSSA‐Grade II and 43 (61.4%) scored SSSA‐Grade III in the HFUS grading. Sixty‐one patients (87.1%) were in the consistent category as per clinical assessment and HFUS grades, with Kappa1 = 0.745, whereas higher HFUS grades were observed in nine patients. By the end of the observation, 65 of all patients (92.9%) showed significant improvement and 5 (7.1%) showed no apparent improvement after the treatment. According to the clinical assessment, 14, 52, and 4 patients were graded as mild, moderate, and severe, respectively. On the other hand, 11, 51, and 8 patients had SSSA‐Grade I, II, and III, respectively. Of all patients, 63 (90.0%) had consistent evaluation results, with Kappa2 = 0.762, whereas the remaining seven patients had an HFUS grade higher than the clinical. Conclusion: HFUS is a useful tool for dermatologists to monitor the treatment of moderate and severe acne vulgaris. [ABSTRACT FROM AUTHOR]

To develop a deep-learning system for the automatic identification of triple-negative breast cancer (TNBC) solely from ultrasound images. A total of 145 patients and 831 images were retrospectively enrolled at Peking Union College Hospital from April 2018 to March 2019. Ultrasound images and clinical information were collected accordingly. Molecular subtypes were determined from immunohistochemical (IHC) results. A CNN with VGG-based architecture was then used to predict TNBC. The model's performance was evaluated using randomized k-fold stratified cross-validation. A t-SNE analysis and saliency maps were used for model visualization. TNBC was identified in 16 of 145 (11.03%) patients. One hundred fifteen (80%) patients, 15 (10%) patients, and 15 (10%) patients formed the train, validation, and test set respectively. The deep learning system exhibits good efficacy, with an AUC of 0.86 (95% CI: 0.64, 0.95), an accuracy of 85%, a sensitivity of 86%, a specificity of 86%, and an F1-score of 0.74. In addition, the internal representation features learned by the model showed clear differentiation across molecular subtype groups. Such a deep learning system can automatically predict triple-negative breast cancer preoperatively and accurately. It may help to get to more precise and comprehensive management. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive understanding of the amplitude- and frequency-dependent characteristics of rubber springs. The dynamic nonlinear inelasticity of rubber is a key academic problem for continuum mechanics and a bottleneck problem for the practical use of rubber structures. Despite intensive efforts witnessed in industrial applications, it still demands an unambiguous constitutive model for dynamic nonlinear inelasticity, which is known as the Payne effect. To this end, three types of rubber springs (shear-type (ST), compression-type (CT) and shear-compression-combination-type (SCCT)) were tested with amplitude and frequency sweeps in different conditions. We investigated and present changes in dynamic stiffness and loss factor with amplitude, frequency and the hysteresis loops of different rubber springs. We also propose a hypothesis and research strategy to study a constitutive model involving multiple factors of hyperelasticity, the Mullins effect, viscoelasticity and the Payne effect, which we hope will provide new ideas for the establishment of a constitutive equation. [ABSTRACT FROM AUTHOR]

Background: Basal cell carcinoma (BCC) is the most common cutaneous malignancy. Occasionally, it may have an appearance similar to that of some benign pigmented skin lesions. Therefore, additional information is needed to differentiate these lesions. Materials and Methods: A diagnostic accuracy study was performed from February 2018 to April 2019. All lesions underwent ultrasound examination with 50 and 20 MHz probes. The high‐frequency ultrasound (HFUS) images were evaluated independently by 2 experienced doctors for the presence of predefined features, including the depth, shape, margin, anechoic area, hyperechoic spots, epidermal interrupted echo, mushroom sign, flat‐bottom sign, and superficial hyperechoic focus (SHEF). Results: A total of 54 BCCs, 51 melanocytic nevi and 55 seborrheic keratoses (SK), were included. BCCs often involved the subcutaneous tissue (11/54, 20.4%; P <.001) and had an irregular shape (26/54, 48.1%; P <.001) and ill‐defined borders (26/54, 48.1%; P <.001), while most benign pigmented lesions had a regular shape (101/106, 95.3%; P <.001) and well‐defined borders (95/106, 89.6%; P <.001). BCCs occasionally showed anechoic areas (10/54, 18.5%; P <.001) and epidermal interrupted echo (18/54, 33.3%; P <.001). Moreover, hyperechoic spots could be found in BCCs (43/54, 79.6%), nevi (27/51, 52.9%), and SK (30, 54.5%) (P =.001), with mean number of 7.3, 5.5, and 8.0, respectively. The mushroom signs were all present in melanocytic nevi (18/51, 35.3%), while the flat‐bottom sign (43/55, 78.2%; P <.001) and SHEF (40/55, 72.7%; P <.001) presented mainly in SKs. Conclusions: Based on the typical features, HFUS could improve the accuracy of BCC identification and should be considered when dermatologists are unsure about the lesion type. [ABSTRACT FROM AUTHOR]