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Traditional markers, such as serum creatinine and blood urea nitrogen, frequently show delayed elevations following acute kidney injury (AKI), limiting their utility for prompt detection and timely intervention in AKI management. Shear wave elastography (SWE) exhibits potential for AKI diagnosis by measuring tissue stiffness. Our study aimed to evaluate the diagnostic performance of SWE in detecting AKI by measuring the stiffness of kidney tissue. Between July 2022 and December 2022, a total of 103 consecutive participants who met the eligibility criteria were prospectively enrolled, underwent SWE measurements, and were classified into AKI or non-AKI groups based on the 2012 Kidney Disease: Improving Global Outcomes (KDIGO) criteria. A receiver operating characteristic (ROC) curve was drawn to examine the feasibility of differentiating between AKI and non-AKI patients and assessing diagnostic performance. The effects of tissue anisotropy on SWE measurements were also examined. Our results revealed that patients in the AKI group exhibited significantly increased stiffness values in specific kidney regions compared with those in the non-AKI group. For the diagnosis of AKI, the optimal cut-off values were identified as 9.9 kPa, 2.9 kPa, and 4.4 kPa for the upper pole medulla, middle cortex, and middle medulla, respectively, in the longitudinal plane. Correspondingly, the areas under the ROC curves for these regions were 0.737 (95% confidence interval [CI]: 0.637, 0.822), 0.736 (95% CI: 0.637, 0.821), and 0.784 (95% CI: 0.688, 0.861). Additionally, we observed a significant variability in stiffness values due to tissue anisotropy, specifically in the segments of the upper pole cortex, and medulla across both longitudinal and transverse planes. SWE serves as a noninvasive approach for the quantification of tissue stiffness and shows promise as an adjunctive tool for the assessment of AKI., Competing Interests: The authors declare that there are no competing interests associated with this manuscript., (Copyright: © 2024 Qiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Abstract: This study aimed to evaluate the diagnostic value of automated breast volume scanner (ABVS) combined with virtual touch tissue quantification (VTQ) in the differential diagnosis of breast lesions.In this retrospective study, 183 patients (mean age, 49.8 ± 8.2 years) with 218 breast lesions underwent ABVS, VTQ, and mammography (MG). All lesions were confirmed by postoperative histopathology. A logistic regression model was constructed to generate a receiver operating characteristic (ROC) curve, calculate the area under the ROC curve (AUC), and compare and evaluate the diagnostic performance of ABVS, VTQ, MG, and ABVS combined with VTQ (ABVS-VTQ).The sensitivity, specificity, and accuracy of ABVS, VTQ, MG, and ABVS-VTQ in diagnosing breast lesions were 94.01% (110/117), 96.03% (97/101), and 94.95% (207/218); 80.34% (94/117), 94.05% (95/101), and 86.69% (189/218); 70.08% (82/117), 68.31% (69/101), and 69.26% (151/218); and 96.58% (113/117), 96.03% (97/101), and 96.33% (210/218), respectively. The AUC of ABVS-VTQ was higher than that of the other examinations alone. The detection rate of ABVS (100%, 218/218) was higher than that of MG (78.89%, 172/218), and the difference was statistically significant (χ2 = 51.426, P < .001).The combined application of ABVS and VTQ can improve the accuracy and specificity of the diagnosis and is a promising ultrasound method for the differential diagnosis of breast lesions., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.)