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Objective: To validate the feasibility of ultrasound in assessing the curative effect of botulinum toxin type A (BTXA) in treating hypertrophic scar (HS). Methods: Eight healthy New Zealand long-eared rabbits were utilized in the study. Four wounds, each measuring 1.0 cm in diameter, were created on both ears of each rabbit. Immediately after surgery, each of these wounds received an injection containing a distinct concentration of BTXA. On postoperative week 6, scar thickness, vascularity, and hardness were assessed based on high frequency ultrasound (HFUS), superb microvascular imaging (SMI), shear wave elastography (SWE), Masson staining, and immunohistochemical staining for CD31. Results: All wounds healed well, and HSs formed after 6 weeks post-surgery. Scar thickness based on HFUS presented a significant decrease with increasing BTXA concentration (p < 0.05), aligning with the gross morphology. Simultaneously, scar stiffness, evaluated using SWE, showed a significant decrease in accordance with the variation of the collagen volume fraction, which refers to the ratio of the collagen positive area to the total area (p < 0.05). Although the vascularity index obtained by SMI did not exhibit a statistically significant change across different BTXA concentrations, this technique effectively illustrated the microvascular perfusion in HS. Immunohistochemical staining for CD31 revealed that BTXA inhibited angiogenesis. Conclusion: HFUS and SWE displayed excellent performance in evaluating HS thickness and stiffness. SMI showed a good performance in reflecting microvascular signals in HS. These ultrasound techniques have great potential in assessing the therapeutic effect of BTXA in HS.
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Objective: The present study aimed to evaluate the efficacy of a new two-dimensional shear wave elastography (2D-SWE) method using a Siemens ultrasound system and its combination with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) for the differential diagnosis of benign and malignant thyroid nodules. Methods: Conventional ultrasound images and 2D-SWE (E-whole-mean and E-stiffest-mean) were prospectively analyzed in 593 thyroid nodules from 543 patients. Nodules were divided into diameter (D) ≤10 mm and D > 10 mm groups and graded using ACR TI-RADS. The receiver operating characteristic curve was plotted using pathological findings as the gold standard. Diagnostic performance was compared among 2D-SWE, ACR TI-RADS, and their combination. Results: The area under the curve (AUC) for E-whole-mean was higher than that for E-stiffest-mean (0.858 vs. 0.790, P < 0.001), which indicated that it was the better 2D-SWE parameter for differentiating malignant nodules from benign nodules with an optimal cut-off point of 11.36 kPa. In the all-sizes group, the AUC for E-whole-mean was higher than that for ACR TI-RADS (0.858 vs. 0.808, P < 0.001). The combination of E-whole-mean and ACR TI-RADS resulted in a higher AUC (0.929 vs. 0.858 vs. 0.808, P < 0.001), sensitivity (87.0% vs. 80.3% vs. 85.2%), specificity (85.1% vs. 74.0% vs. 73.6%), accuracy (86.3% vs. 78.1% vs. 81.1%), positive predictive value (91.5% vs. 85.1% vs. 85.6%), and negative predictive value (78.0% vs. 67.0% vs. 72.9%) compared to E-whole-mean or ACR TI-RADS alone. The AUC for the combination of 2D-SWE and ACR TI-RADS was superior to that for E-whole-mean or ACR TI-RADS alone in both D ≤ 10 mm and D > 10 mm groups (P < 0.001). Conclusion: As the better 2D-SWE parameter, E-whole-mean had a higher diagnostic power than ACR TI-RADS and enhanced the diagnostic performance of ACR TI-RADS when identifying benign and malignant thyroid nodules. The combination of E-whole-mean and ACR TI-RADS improved the diagnostic performance compared to using ACR TI-RADS alone, providing a new and reliable method for the clinical diagnosis of thyroid nodules.
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Artificial intelligence (AI) is playing an increasingly important role in medicine, especially in the field of medical imaging. It can be used to diagnose diseases and predict certain statuses and possible events that may happen. Recently, more and more studies have confirmed the value of AI based on ultrasound in the evaluation of diffuse liver diseases and focal liver lesions. It can assess the severity of liver fibrosis and nonalcoholic fatty liver, differentially diagnose benign and malignant liver lesions, distinguish primary from secondary liver cancers, predict the curative effect of liver cancer treatment and recurrence after treatment, and predict microvascular invasion in hepatocellular carcinoma. The findings from these studies have great clinical application potential in the near future. The purpose of this review is to comprehensively introduce the current status and future perspectives of AI in liver ultrasound.
