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Distinguishing malignant versus benign lymphadenopathies is a major diagnostic dilemma in clinical medicine. Metastatic deposits in normal-sized lymph nodes (LNs) can be smaller than a millimeter, thus presenting a diagnostic challenge. In most clinical settings, however, enlarged LNs detected on imaging need to be classified as malignant or benign. Ultrasound seems to be a very reliable method for LN characterization because of the high resolution, especially in the subcutaneous areas. However, B-mode and Doppler-ultrasound criteria for characterization of a lymphadenopathy as benign or malignant are lacking specificity. Newer methods such as elastography seem to be valuable for identifying metastatic deposits within LNs and may help discriminate malignant and benign LNs. This review summarizes the different elastographic methods available and provides an overview of the relevant publications. According to the literature, elastography can be used for identifying metastatic deposits, to guide fine needle aspiration and to non-invasively choose the most suspicious LN of a group of enlarged LNs for targeted biopsy. [ABSTRACT FROM AUTHOR]

The breast section of these Guidelines and Recommendations for Elastography produced under the auspices of the World Federation of Ultrasound in Medicine and Biology (WFUMB) assesses the clinically used applications of all forms of elastography used in breast imaging. The literature on various breast elastography techniques is reviewed, and recommendations are made on evidence-based results. Practical advice is given on how to perform and interpret breast elastography for optimal results, with emphasis placed on avoiding pitfalls. Artifacts are reviewed, and the clinical utility of some artifacts is discussed. Both strain and shear wave techniques have been shown to be highly accurate in characterizing breast lesions as benign or malignant. The relationship between the various techniques is discussed, and recommended interpretation based on a BI-RADS-like malignancy probability scale is provided. This document is intended to be used as a reference and to guide clinical users in a practical way. [ABSTRACT FROM AUTHOR]

Objectives: To define reference values for shear wave elastography (SWE) in unsuspicious axillary lymph nodes in patients undergoing breast ultrasound examination. Methods: In total, 177 clinically and sonographically unsuspicious axillary lymph nodes were prospectively evaluated with SWE using Virtual Touch Tissue Imaging Quantification (VTIQ) in 175 women. Mean values of tissue stiffness for axillary fatty tissue, lymph node cortex, and lymph node hilus were measured. Additionally, test‐retest reliability of SWE in the assessment of axillary lymph node stiffness was evaluated by repeating each measurement three times. Results: In 177 axillary lymph nodes, the mean stiffness of lymph node cortex, hilus, and surrounding fatty tissue as quantified by SWE was 1.90 m/s (SD: 0.34 m/s), 2.02 m/s (SD: 0.37 m/s), and 1.75 m/s (SD: 0.38 m/s), respectively. The mean stiffness of cortex and hilus was significantly higher compared to fatty tissue (p < 0.0001). SWE demonstrated good test–retest reliability in the assessment of stiffness of the lymph node hilus, cortex, and the surrounding fatty tissue with an intraclass correlation of 0.79 (95% CI: 0.75; 0.83), 0.75 (95% CI: 0.70; 0.79), and 0.78 (95% CI: 0.74; 0.82), respectively, (p < 0.0001). Conclusions: Reference values for SWE in unsuspicious axillary lymph nodes are determined. These results may help to better identify axillary lymph node metastasis for breast cancer patients when combined with other lymph node features. SWE is a reliable method for the objective quantification of tissue stiffness of axillary lymph nodes. Advances in knowledge: This study presents physiological reference values for tissue stiffness by examining the axillary lymph nodes with SWE in 175 women with sonomorphologically unsuspicious lymph nodes. [ABSTRACT FROM AUTHOR]

Ultrasound artifacts are encountered daily in clinical practice and may be a source of confusion on interpretation. Some artifacts arise secondary to improper scanning techniques and may be avoidable. Other artifacts are generated by the physical limitations of the technique. Recognition of artifacts is important, as they may be clues to tissue composition and aid in diagnosis. The ability to recognize and correct potential ultrasound artifacts is important for image-quality improvement and optimal patient care. In this article, we review common ultrasound artifacts that occur in B mode, spectral and color Doppler, and elastography. [ABSTRACT FROM AUTHOR]

The article discusses a substudy undertaken to assess the rate and stage of cancers detected with a single screening magnetic resonance imaging (MRI). Participants to the study included women who were asymptomatic and presented for routine annual mammography with heterogeneously dense or extremely dense breast tissue with at least one other risk factor for breast cancer. It suggests that the addition of screening MRI rather than ultrasound to mammography in a population of women at intermediate risk with dense breast may not be proper specially when the current high false-positive rates, cost and reduced tolerability of MRI are considered.

Breast ultrasound identifies additional carcinomas not detected in mammography but has a higher rate of false-positive findings. We evaluated whether use of intelligent multi-modal shear wave elastography (SWE) can reduce the number of unnecessary biopsies without impairing the breast cancer detection rate. We trained, tested, and validated machine learning algorithms using SWE, clinical, and patient information to classify breast masses. We used data from 857 women who underwent B-mode breast ultrasound, SWE, and subsequent histopathologic evaluation at 12 study sites in seven countries from 2016 to 2019. Algorithms were trained and tested on data from 11 of the 12 sites and externally validated using the additional site's data. We compared findings to the histopathologic evaluation and compared the diagnostic performance between B-mode breast ultrasound, traditional SWE, and intelligent multi-modal SWE. In the external validation set (n = 285), intelligent multi-modal SWE showed a sensitivity of 100% (95% CI, 97.1–100%, 126 of 126), a specificity of 50.3% (95% CI, 42.3–58.3%, 80 of 159), and an area under the curve of 0.93 (95% CI, 0.90–0.96). Diagnostic performance was significantly higher compared to traditional SWE and B-mode breast ultrasound (P < 0.001). Unlike traditional SWE, positive-predictive values of intelligent multi-modal SWE were significantly higher compared to B-mode breast ultrasound. Unnecessary biopsies were reduced by 50.3% (79 versus 159, P < 0.001) without missing cancer compared to B-mode ultrasound. The majority of unnecessary breast biopsies might be safely avoided by using intelligent multi-modal SWE. These results may be helpful to reduce diagnostic burden for patients, providers, and healthcare systems. • Breast ultrasound results in false-positive findings causing unnecessary biopsies. • We developed and tested an intelligent multi-modal shear wave elastography algorithm. • Performance was higher compared to breast ultrasound and traditional elastography. • Unnecessary biopsies were significantly reduced by 50.3% with 0% undetected malignancies. • Prospective validation of the algorithm in a diverse setting seems warranted. [ABSTRACT FROM AUTHOR]