Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: This study assessed the benefits of quality threshold (QT) implementation for liver shear wave elastography (SWE) in children during free breathing. Methods: The QT, which adjusts the SWE map display based on shear wave quality, was set at 55%. Phantom measurements (PMs) were taken with a fixed probe using QT (termed PM-1); a moving probe without QT (PM-2); and a moving probe with QT (PM-3). Each measurement was subjected to random samplings of various sizes. Clinical measurements (CMs) were obtained from children with biliary atresia using following protocols: CM-1, manually defined regions of interest (ROIs); CM-2, default ROIs without QT; and CM-3, default ROIs with QT. Elasticity measurements were compared across fibrosis grades, and color patterns on the SWE maps were analyzed. Results: In the phantom experiments, the moving probe produced lower elasticity measurements; this difference decreased upon QT application. With the moving probe, random sampling indicated fewer interquartile range-to-median ratios exceeding 30% upon QT application (4% vs. 14% when five values were sampled, P=0.004). In clinical experiments, QT improved the differentiation of fibrosis grade in patients over 5 years old, with a significant difference between moderate and severe fibrosis (P=0.004). Elasticity variability was positively correlated with fibrosis grade (τ=0.376, P<0.001). Certain apparent errors, termed artificial stripe patterns, were not eliminated by QT. Conclusion Applying QT to exclude low-quality pixels can minimize measurement error and improve differentiation of liver fibrosis grades. The presence of an artificial stripe pattern on the SWE map may indicate images requiring exclusion.

Purpose: The study aimed to compare the diagnostic performance of washout-parametric imaging (WOPI) with that of conventional contrast-enhanced ultrasound (cCEUS) in differentiating focal liver lesions (FLLs). Methods: A total of 181 FLLs were imaged with contrast-enhanced ultrasound using Sonazoid, and the recordings were captured for 10 minutes in a prospective setting. WOPI was constructed from three images, depicting the arterial phase (peak enhancement), the early portal venous phase (1-minute post-injection), and the vasculo-Kupffer phase (5 or 10 minutes post-injection). The intensity variations in these images were color-coded and superimposed to produce a single image representing the washout timing across the lesions. From the 181 FLLs, 30 hepatocellular carcinomas (HCCs), 30 non-HCC malignancies, and 30 benign lesions were randomly selected for an observer study. Both techniques (cCEUS and WOPI) were evaluated by four off-site readers. They classified each lesion as benign or malignant using a continuous rating scale, with the endpoints representing "definitely benign" and "definitely malignant." The diagnostic performance of cCEUS and WOPI was compared using the area under the receiver operating characteristic curve (AUC) with the DeLong test. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC). Results: The difference in average AUC values between WOPI and cCEUS was 0.0062 (95% confidence interval, -0.0161 to 0.0285), indicating no significant difference between techniques. The interobserver agreement was higher for WOPI (ICC, 0.77) than cCEUS (ICC, 0.67). Conclusion The diagnostic performance of WOPI is comparable to that of cCEUS in differentiating FLLs, with superior interobserver agreement.

Purpose: The study aimed to compare the diagnostic performance of washout-parametric imaging (WOPI) with that of conventional contrast-enhanced ultrasound (cCEUS) in differentiating focal liver lesions (FLLs). Methods: A total of 181 FLLs were imaged with contrast-enhanced ultrasound using Sonazoid, and the recordings were captured for 10 minutes in a prospective setting. WOPI was constructed from three images, depicting the arterial phase (peak enhancement), the early portal venous phase (1-minute post-injection), and the vasculo-Kupffer phase (5 or 10 minutes post-injection). The intensity variations in these images were color-coded and superimposed to produce a single image representing the washout timing across the lesions. From the 181 FLLs, 30 hepatocellular carcinomas (HCCs), 30 non-HCC malignancies, and 30 benign lesions were randomly selected for an observer study. Both techniques (cCEUS and WOPI) were evaluated by four off-site readers. They classified each lesion as benign or malignant using a continuous rating scale, with the endpoints representing "definitely benign" and "definitely malignant." The diagnostic performance of cCEUS and WOPI was compared using the area under the receiver operating characteristic curve (AUC) with the DeLong test. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC). Results: The difference in average AUC values between WOPI and cCEUS was 0.0062 (95% confidence interval, -0.0161 to 0.0285), indicating no significant difference between techniques. The interobserver agreement was higher for WOPI (ICC, 0.77) than cCEUS (ICC, 0.67). Conclusion The diagnostic performance of WOPI is comparable to that of cCEUS in differentiating FLLs, with superior interobserver agreement.

Purpose: The study aimed to compare the diagnostic performance of washout-parametric imaging (WOPI) with that of conventional contrast-enhanced ultrasound (cCEUS) in differentiating focal liver lesions (FLLs). Methods: A total of 181 FLLs were imaged with contrast-enhanced ultrasound using Sonazoid, and the recordings were captured for 10 minutes in a prospective setting. WOPI was constructed from three images, depicting the arterial phase (peak enhancement), the early portal venous phase (1-minute post-injection), and the vasculo-Kupffer phase (5 or 10 minutes post-injection). The intensity variations in these images were color-coded and superimposed to produce a single image representing the washout timing across the lesions. From the 181 FLLs, 30 hepatocellular carcinomas (HCCs), 30 non-HCC malignancies, and 30 benign lesions were randomly selected for an observer study. Both techniques (cCEUS and WOPI) were evaluated by four off-site readers. They classified each lesion as benign or malignant using a continuous rating scale, with the endpoints representing "definitely benign" and "definitely malignant." The diagnostic performance of cCEUS and WOPI was compared using the area under the receiver operating characteristic curve (AUC) with the DeLong test. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC). Results: The difference in average AUC values between WOPI and cCEUS was 0.0062 (95% confidence interval, -0.0161 to 0.0285), indicating no significant difference between techniques. The interobserver agreement was higher for WOPI (ICC, 0.77) than cCEUS (ICC, 0.67). Conclusion The diagnostic performance of WOPI is comparable to that of cCEUS in differentiating FLLs, with superior interobserver agreement.

Purpose: The study aimed to compare the diagnostic performance of washout-parametric imaging (WOPI) with that of conventional contrast-enhanced ultrasound (cCEUS) in differentiating focal liver lesions (FLLs). Methods: A total of 181 FLLs were imaged with contrast-enhanced ultrasound using Sonazoid, and the recordings were captured for 10 minutes in a prospective setting. WOPI was constructed from three images, depicting the arterial phase (peak enhancement), the early portal venous phase (1-minute post-injection), and the vasculo-Kupffer phase (5 or 10 minutes post-injection). The intensity variations in these images were color-coded and superimposed to produce a single image representing the washout timing across the lesions. From the 181 FLLs, 30 hepatocellular carcinomas (HCCs), 30 non-HCC malignancies, and 30 benign lesions were randomly selected for an observer study. Both techniques (cCEUS and WOPI) were evaluated by four off-site readers. They classified each lesion as benign or malignant using a continuous rating scale, with the endpoints representing "definitely benign" and "definitely malignant." The diagnostic performance of cCEUS and WOPI was compared using the area under the receiver operating characteristic curve (AUC) with the DeLong test. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC). Results: The difference in average AUC values between WOPI and cCEUS was 0.0062 (95% confidence interval, -0.0161 to 0.0285), indicating no significant difference between techniques. The interobserver agreement was higher for WOPI (ICC, 0.77) than cCEUS (ICC, 0.67). Conclusion The diagnostic performance of WOPI is comparable to that of cCEUS in differentiating FLLs, with superior interobserver agreement.

Purpose: The study aimed to compare the diagnostic performance of washout-parametric imaging (WOPI) with that of conventional contrast-enhanced ultrasound (cCEUS) in differentiating focal liver lesions (FLLs). Methods: A total of 181 FLLs were imaged with contrast-enhanced ultrasound using Sonazoid, and the recordings were captured for 10 minutes in a prospective setting. WOPI was constructed from three images, depicting the arterial phase (peak enhancement), the early portal venous phase (1-minute post-injection), and the vasculo-Kupffer phase (5 or 10 minutes post-injection). The intensity variations in these images were color-coded and superimposed to produce a single image representing the washout timing across the lesions. From the 181 FLLs, 30 hepatocellular carcinomas (HCCs), 30 non-HCC malignancies, and 30 benign lesions were randomly selected for an observer study. Both techniques (cCEUS and WOPI) were evaluated by four off-site readers. They classified each lesion as benign or malignant using a continuous rating scale, with the endpoints representing "definitely benign" and "definitely malignant." The diagnostic performance of cCEUS and WOPI was compared using the area under the receiver operating characteristic curve (AUC) with the DeLong test. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC). Results: The difference in average AUC values between WOPI and cCEUS was 0.0062 (95% confidence interval, -0.0161 to 0.0285), indicating no significant difference between techniques. The interobserver agreement was higher for WOPI (ICC, 0.77) than cCEUS (ICC, 0.67). Conclusion The diagnostic performance of WOPI is comparable to that of cCEUS in differentiating FLLs, with superior interobserver agreement.