The benefit of contrast-enhanced ultrasound in biopsies for focal liver lesions: a retrospective study of 820 cases.

OBJECTIVE: This study compared the performance between ultrasound (US)- and contrast-enhanced US (CEUS)-guided liver biopsies and evaluated the benefit of CEUS in percutaneous biopsy for focal liver lesions (FLLs). METHODS: We performed a retrospective study of 820 patients with FLLs, who underwent percutaneous liver biopsy in our center between 2017 and 2019. The patients were divided into two groups based on whether US (n = 362) or CEUS (n = 458) used before a biopsy. The two groups were compared based on specimen adequacy for pathological diagnosis and diagnostic accuracy of liver biopsy. Stratification analysis was performed based on lesion and protocol characteristics to provide detailed information for selecting the imaging guidance for biopsy. RESULTS: Compared with the US group, the CEUS group yielded more acceptable samples (97.6% vs. 99.4%, p < 0.05) and improved diagnostic accuracy (92.6% vs. 96.4%, p < 0.05), and achieved better sensitivity (92.5% vs. 96.2%, p < 0.05) for liver biopsies, especially in FLLs ≥ 5 cm, heterogeneous hypoechoic FLLs, or FLLs with an obscure boundary. The CEUS group showed significantly higher accuracy compared with the US group pertaining to single-puncture biopsies (100% vs. 92.7%, p < 0.05) or biopsies with punctures ≤ 2 (97.6% vs. 94.3%, p < 0.05). CONCLUSION: CEUS achieved an enhanced success rate for sampling and diagnostic accuracy of liver biopsies, especially in FLLs ≥ 5 cm, heterogeneous hypoechoic FLLs, or FLLs with an obscure boundary. CEUS can be used to decrease the number of punctures needed, which might increase the safety of liver biopsy. KEY POINTS: • CEUS can help confirm an adequate biopsy site, increasing the sampling success rate and diagnostic accuracy of the liver biopsy. • CEUS can be used to decrease the number of punctures needed to improve the safety of liver biopsy. • It is recommended to use CEUS guidance for liver biopsies, especially with FLLs ≥ 5 cm, heterogeneous hypoechoic FLLs, or FLLs with an obscure boundary.

Double contrast-enhanced ultrasonography improves diagnostic accuracy of T staging compared with multi-detector computed tomography in gastric cancer patients.

BACKGROUND: Gastric cancer (GC) is the most common malignant tumor and ranks third for cancer-related deaths among the worldwide. The disease poses a serious public health problem in China, ranking fifth for incidence and third for mortality. Knowledge of the invasive depth of the tumor is vital to treatment decisions. AIM: To evaluate the diagnostic performance of double contrast-enhanced ultrasonography (DCEUS) for preoperative T staging in patients with GC by comparing with multi-detector computed tomography (MDCT). METHODS: This single prospective study enrolled patients with GC confirmed by preoperative gastroscopy from July 2021 to March 2023. Patients underwent DCEUS, including ultrasonography (US) and intravenous contrast-enhanced ultrasonography (CEUS), and MDCT examinations for the assessment of preoperative T staging. Features of GC were identified on DCEUS and criteria developed to evaluate T staging according to the 8th edition of AJCC cancer staging manual. The diagnostic performance of DCEUS was evaluated by comparing it with that of MDCT and surgical-pathological findings were considered as the gold standard. RESULTS: A total of 229 patients with GC (80 T1, 33 T2, 59 T3 and 57 T4) were included. Overall accuracies were 86.9% for DCEUS and 61.1% for MDCT (P < 0.001). DCEUS was superior to MDCT for T1 (92.5% vs 70.0%, P < 0.001), T2 (72.7% vs 51.5%, P = 0.041), T3 (86.4% vs 45.8%, P < 0.001) and T4 (87.7% vs 70.2%, P = 0.022) staging of GC. CONCLUSION: DCEUS improved the diagnostic accuracy of preoperative T staging in patients with GC compared with MDCT, and constitutes a promising imaging modality for preoperative evaluation of GC to aid individualized treatment decision-making.

Delta Radiomics Based on Longitudinal Dual-modal Ultrasound Can Early Predict Response to Neoadjuvant Chemotherapy in Breast Cancer Patients.

RATIONALE AND OBJECTIVES: To develop a monitoring model using radiomics analysis based on longitudinal B-mode ultrasound (BUS) and shear wave elastography (SWE) to early predict pathological response to neoadjuvant chemotherapy (NAC) in breast cancer patients. MATERIALS AND METHODS: In this prospective study, 112 breast cancer patients who received NAC between September 2016 and March 2022 were included. The BUS and SWE data of breast cancer were obtained prior to treatment as well as after two and four cycles of NAC. Radiomics features were extracted followed by measuring the changes in radiomics features compared to baseline after the second and fourth cycles of NAC (△R [C2], △R [C4]), respectively. The delta radiomics signatures were established using a support vector machine classifier. RESULTS: The area under receiver operating characteristic curve (AUC) values of △RBUS (C2) and △RBUS (C4) for predicting the response to NAC were 0.83 and 0.84, while those of △RSWE (C2) and △RSWE (C4) were 0.88 and 0.90, respectively. △RSWE exhibited significantly superior performance to △RBUS for predicting NAC response (Delong test, p < 0.01). No significant differences were observed in the performances between △R (C2) and △R (C4) based on BUS or SWE data. The longitudinal dual-modal ultrasound radiomics (LDUR) model had an excellent discrimination, good calibration and clinical usefulness, with the AUC, sensitivity and specificity of 0.97, 95.52% and 91.11%, respectively. CONCLUSION: The LDUR model achieved excellent performance in predicting the pathological response to chemotherapy during the early stages of NAC for breast cancer.

Deep Learning Model Based on Dual-Modal Ultrasound and Molecular Data for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.

RATIONALE AND OBJECTIVES: To carry out radiomics analysis/deep convolutional neural network (CNN) based on B-mode ultrasound (BUS) and shear wave elastography (SWE) to predict response to neoadjuvant chemotherapy (NAC) in breast cancer patients. MATERIALS AND METHODS: In this prospective study, 255 breast cancer patients who received NAC between September 2016 and December 2021 were included. Radiomics models were designed using a support vector machine classifier based on US images obtained before treatment, including BUS and SWE. And CNN models also were developed using ResNet architecture. The final predictive model was developed by combining the dual-modal US and independently associated clinicopathologic characteristics. The predictive performances of the models were assessed with five-fold cross-validation. RESULTS: Pretreatment SWE performed better than BUS in predicting the response to NAC for breast cancer for both the CNN and radiomics models (P < 0.001). The predictive results of the CNN models were significantly better than the radiomics models, with AUCs of 0.72 versus 0.69 for BUS and 0.80 versus 0.77 for SWE, respectively (P = 0.003). The CNN model based on the dual-modal US and molecular data exhibited outstanding performance in predicting NAC response, with an accuracy of 83.60% ± 2.63%, a sensitivity of 87.76% ± 6.44%, and a specificity of 77.45% ± 4.38%. CONCLUSION: The pretreatment CNN model based on the dual-modal US and molecular data achieved excellent performance for predicting the response to chemotherapy in breast cancer. Therefore, this model has the potential to serve as a non-invasive objective biomarker to predict NAC response and aid clinicians with individual treatments.

Total Saponin from Root of Actinidia valvata Dunn Inhibits Hepatoma 22 Growth and Metastasis In Vivo by Suppression Angiogenesis.

The root of Actinidia valvata dunn has been widely used in the treatment of hepatocellular carcinoma (HCC), proved to be beneficial for a longer and better life in China. In present work, total saponin from root of Actinidia valvata Dunn (TSAVD) was extracted, and its effects on hepatoma H22-based mouse in vivo were observed. Primarily transplanted hypodermal hepatoma H22-based mice were used to observe TSAVD effect on tumor growth. The microvessel density (MVD), vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF) are characterized factors of angiogenesis, which were compared between TSAVD-treated and control groups. Antimetastasis effect on experimental pulmonary metastasis hepatoma mice was also observed in the study. The results demonstrated that TSAVD can effectively inhibit HCC growth and metastasis in vivo, inhibit the formation of microvessel, downregulate expressions of VEGF and bFGF, and retrain angiogenesis of hepatoma 22 which could be one of the reasons.