Does Meal or Water Intake Affect Ultrasound Attenuation Coefficient Estimate?

OBJECTIVES: To assess whether meal or water intake may affect the measurement of the ultrasound (US) attenuation coefficient (AC) imaging, a parameter that is directly related to liver fat content. METHODS: The study was performed in two centers (Italy and USA). AC was obtained using the ATI algorithm implemented in the Aplio i-series US systems (Canon Medical Systems, Japan) by one operator at each center. Measurements were performed at baseline and 5, 15, 30, 45 minutes after drinking 500 mL of water (group 1), or 30, 45, 60, 90, 120 minutes after eating a meal of about 600 kcal (group 2). Multilevel generalized estimating equations for repeated measures were used for the statistical analysis to consider the clustered nature of the data. RESULTS: Twenty-six individuals were enrolled: 11 (10 females; age, 43.7 ± 12.5 years) in Italy and 15 (10 females; age, 60.7 ± 6.3 years) in USA. At B-mode US, 10 (38.5%) had liver steatosis. The baseline AC values, in decibel/centimeter/megahertz, were 0.64 (0.12) in group 1 and 0.66 (0.13) in group 2. There was not any significant difference in AC values at every time-point after water or meal intake either in group 1 or group 2. This result did not change including sex, age, and skin-to-liver capsule into the models. CONCLUSIONS: The measurement of the AC, which is a biomarker of liver steatosis, does not require a fasting state and drinking water does not affect the result.

Recent advances in noninvasive assessment of liver steatosis.

Due to the steatosis epidemic, noninvasive quantification of liver fat content is of great interest. Magnetic resonance (MR) techniques, including proton MR spectroscopy (MRS) and MR chemical shift imaging can quantify liver fat by measuring, directly or indirectly (the latter), the proton density fat fraction (PDFF). They have shown excellent diagnostic accuracy and are currently the reference standard for the noninvasive assessment of liver steatosis and are used in clinical trials for evaluating the change in liver fat over time. Using ultrasound (US), three different quantitative parameters can be obtained to estimate liver fat: attenuation coefficient, backscatter coefficient, and speed of sound. Controlled attenuation parameter (CAP), which estimates the attenuation of the US beam, was the first algorithm available and is performed with a non-imaging system. Currently, several other algorithms are available on B-mode imaging ultrasound systems, and they have shown an accuracy similar to or higher than the CAP. This article reports the current knowledge about their application in patients with metabolic dysfunction-associated steatotic liver disease.

Quantification of Hepatocellular Carcinoma Vascular Dynamics With Contrast-Enhanced Ultrasound for LI-RADS Implementation.

OBJECTIVE: The aim of this study is to describe a comprehensive contrast-enhanced ultrasound (CEUS) imaging protocol and analysis method to implement CEUS LI-RADS (Liver Imaging Reporting and Data System) in a quantifiable manner. The methods that are validated with a prospective single-center study aim to simplify CEUS LI-RADS evaluation, remove observer bias, and potentially improve the sensitivity of CEUS LI-RADS. MATERIALS AND METHODS: This prospective single-center study enrolled patients with hepatocellular carcinoma (April 2021-June 2022; N = 31; mean age ± SD, 67 ± 6 years; 24 men/7 women). For each patient, at least 2 CEUS loops spanning over 5 minutes were collected for different lesion scan planes using an articulated arm to hold the transducer. Automatic respiratory gating and motion compensation algorithms removed errors due to breathing motion. The long axis of the lesion was measured in the contrast and fundamental images to capture nodule size. Parametric processing of time-intensity curve analysis on linearized data provided quantifiable information of the wash-in and washout dynamics via rise time ( RT ) and degree of washout ( DW ) parameters extracted from the time-intensity curve, respectively. A Welch t test was performed between lesion and parenchyma RT for each lesion to confirm statistically significant differences. P values for bootstrapped 95% confidence intervals of the relative degree of washout ( rDW ), ratio of DW between the lesion and surrounding parenchyma, were computed to quantify lesion washout. Coefficient of variation (COV) of RT , DW , and rDW was calculated for each patient between injections for both the lesion and surrounding parenchyma to gauge reproducibility of these metrics. Spearman rank correlation tests were performed among size, RT , DW , and rDW values to evaluate statistical dependence between the variables. RESULTS: The mean ± SD lesion diameter was 23 ± 8 mm. The RT for all lesions, capturing arterial phase hyperenhancement, was shorter than that of surrounding liver parenchyma ( P < 0.05). All lesions also demonstrated significant ( P < 0.05) but variable levels of washout at both 2-minute and 5-minute time points, quantified in rDW . The COV of RT for the lesion and surrounding parenchyma were both 11%, and the COV of DW and rDW at 2 and 5 minutes ranged from 22% to 31%. Statistically significant relationships between lesion and parenchyma RT and between lesion RT and lesion DW at the 2- and 5-minute time points were found ( P < 0.05). CONCLUSIONS: The imaging protocol and analysis method presented provide robust, quantitative metrics that describe the dynamic vascular patterns of LI-RADS 5 lesions classified as hepatocellular carcinomas. The RT of the bolus transit quantifies the arterial phase hyperenhancement, and the DW and rDW parameters quantify the washout from linearized CEUS intensity data. This unique methodology is able to implement the CEUS-LIRADS scheme in a quantifiable manner for the first time and remove its existing issues of currently being qualitative and suffering from subjective evaluations.

Deep learning-based multimodal fusion network for segmentation and classification of breast cancers using B-mode and elastography ultrasound images.

Ultrasonography is one of the key medical imaging modalities for evaluating breast lesions. For differentiating benign from malignant lesions, computer-aided diagnosis (CAD) systems have greatly assisted radiologists by automatically segmenting and identifying features of lesions. Here, we present deep learning (DL)-based methods to segment the lesions and then classify benign from malignant, utilizing both B-mode and strain elastography (SE-mode) images. We propose a weighted multimodal U-Net (W-MM-U-Net) model for segmenting lesions where optimum weight is assigned on different imaging modalities using a weighted-skip connection method to emphasize its importance. We design a multimodal fusion framework (MFF) on cropped B-mode and SE-mode ultrasound (US) lesion images to classify benign and malignant lesions. The MFF consists of an integrated feature network (IFN) and a decision network (DN). Unlike other recent fusion methods, the proposed MFF method can simultaneously learn complementary information from convolutional neural networks (CNNs) trained using B-mode and SE-mode US images. The features from the CNNs are ensembled using the multimodal EmbraceNet model and DN classifies the images using those features. The experimental results (sensitivity of 100 ± 0.00% and specificity of 94.28 ± 7.00%) on the real-world clinical data showed that the proposed method outperforms the existing single- and multimodal methods. The proposed method predicts seven benign patients as benign three times out of five trials and six malignant patients as malignant five out of five trials. The proposed method would potentially enhance the classification accuracy of radiologists for breast cancer detection in US images.

Toward acquisition protocol standardization for estimating liver fat content using ultrasound attenuation coefficient imaging.

PURPOSE: This study's primary aim was to assess factors affecting ultrasound attenuation coefficient (AC) measurement repeatability using the Canon ultrasound (US) system. The secondary aim was to evaluate whether similar results were obtained with other vendors' AC algorithms. METHODS: This prospective study was performed at two centers from February to November 2022. AC was obtained using two US systems (Aplio i800 of Canon Medical Systems and Arietta 850 of Fujifilm). An algorithm combining AC and the backscatter coefficient was also used (Sequoia US System, Siemens Healthineers). To evaluate inter-observer concordance, AC was obtained by two expert operators using different transducer positions with regions of interest (ROIs) varying in terms of depth and size. Intra-observer concordance was evaluated on measurements performed intercostally, subcostally, and in the left liver lobe. Lin's concordance correlation coefficient was used. RESULTS: Thirty-four participants (mean age, 49.4±15.1 years; 18 females) were studied. AC values progressively decreased with depth. The measurements in intercostal spaces on bestquality US images using a 3-cm ROI with its upper edge 2 cm below the liver capsule during breath-hold showed the highest intra-observer and inter-observer concordance (0.92 [95% confidence interval, 0.88 to 0.95] and 0.89 [0.82 to 0.96], respectively). Measurements in the left lobe showed the lowest intra-observer and inter-observer concordance (0.67 [0.43 to 0.90] and 0.58 [0.12 to 1.00], respectively). Intercostal space measurements also had the highest repeatability for the other two ultrasound systems. CONCLUSION: AC values obtained in intercostal spaces on best-quality images using a 3-cm ROI placed with its top 2 cm below the liver capsule were highly repeatable.

Liver Fat Quantification With Ultrasound: Depth Dependence of Attenuation Coefficient.

OBJECTIVES: The primary aim was to estimate the influence of various depths on ultrasound attenuation coefficient (AC) of multiple vendors in the liver. The secondary aim was to evaluate the impact of region of interest (ROI) size on AC measurements in a subset of participants. METHODS: This Institutional Review Board (IRB)-approved Health Insurance Portability and Accountability Act (HIPAA)-compliant retrospective study was carried out in two centers using AC-Canon and AC-Philips algorithms and extracting AC-Siemens values from ultrasound-derived fat fraction algorithm. Measurements were performed positioning ROI upper edge (3 cm size) at 2, 3, 4, 5 cm from the liver capsule with AC-Canon and AC-Philips and at 1.5, 2, 3 cm with Siemens algorithm. In a subset of participants, measurements were obtained with 1 and 3 cm ROI size. Univariate and multivariate linear regression models and Lin's concordance correlation coefficient (CCC) were used for statistical analysis as appropriate. RESULTS: Three different cohorts were studied. Sixty-three participants (34 females; mean age: 51 ± 14 years) were studied with AC-Canon, 60 (46 females; mean age: 57 ± 11 years) with AC-Philips, and 50 (25 females; 61 ± 13 years) with AC-Siemens. There was a decrease in AC values per 1 cm increase in depth in all. In multivariable analysis, the coefficient was -0.049 (-0.060; -0.038 P < .001) with AC-Canon, -0.058 (-0.066; -0.049 P < .001) with AC-Philips and -0.081 (-0.112; -0.050 P < .001) with AC-Siemens. AC values with 1 cm ROI were significantly higher than those obtained with 3 cm ROI at all depths (P < .001) but the agreement between AC values obtained with different ROI size was excellent (CCC 0.82 [0.77-0.88]). CONCLUSIONS: There is depth dependence in AC measurement that affects results. A standardized protocol with fixed ROI's depth and size is needed.

New Technologies in the Assessment of Carotid Stenosis: Beyond the Color-Doppler Ultrasound-High Frame Rate Vector-Flow and 3D Arterial Analysis Ultrasound.

Atherosclerotic plaque in the carotid artery is the main cause of ischemic stroke, with a high incidence rate among people over 65 years. A timely and precise diagnosis can help to prevent the ischemic event and decide patient management, such as follow up, medical, or surgical treatment. Presently, diagnostic imaging techniques available include color-Doppler ultrasound, as a first evaluation technique, computed tomography angiography, which, however, uses ionizing radiation, magnetic resonance angiography, still not in widespread use, and cerebral angiography, which is an invasively procedure reserved for therapeutically purposes. Contrast-enhanced ultrasound is carving out an important and emerging role which can significantly improve the diagnostic accuracy of an ultrasound. Modern ultrasound technologies, still not universally utilized, are opening new horizons in the arterial pathologies research field. In this paper, the technical development of various carotid artery stenosis diagnostic imaging modalities and their impact on clinical efficacy is thoroughly reviewed.

Liver Fibrosis, Fat, and Iron Evaluation with MRI and Fibrosis and Fat Evaluation with US: A Practical Guide for Radiologists.

Quantitative imaging biomarkers of liver disease measured by using MRI and US are emerging as important clinical tools in the management of patients with chronic liver disease (CLD). Because of their high accuracy and noninvasive nature, in many cases, these techniques have replaced liver biopsy for the diagnosis, quantitative staging, and treatment monitoring of patients with CLD. The most commonly evaluated imaging biomarkers are surrogates for liver fibrosis, fat, and iron. MR elastography is now routinely performed to evaluate for liver fibrosis and typically combined with MRI-based liver fat and iron quantification to exclude or grade hepatic steatosis and iron overload, respectively. US elastography is also widely performed to evaluate for liver fibrosis and has the advantage of lower equipment cost and greater availability compared with those of MRI. Emerging US fat quantification methods can be performed along with US elastography. The author group, consisting of members of the Society of Abdominal Radiology (SAR) Liver Fibrosis Disease-Focused Panel (DFP), the SAR Hepatic Iron Overload DFP, and the European Society of Radiology, review the basics of liver fibrosis, fat, and iron quantification with MRI and liver fibrosis and fat quantification with US. The authors cover technical requirements, typical case display, quality control and proper measurement technique and case interpretation guidelines, pitfalls, and confounding factors. The authors aim to provide a practical guide for radiologists interpreting these examinations. © RSNA, 2023 See the invited commentary by Ronot in this issue. Quiz questions for this article are available in the supplemental material.

Improved Breast 2D SWE Algorithm to Eliminate False-Negative Cases.

OBJECTIVES: Two-dimensional shear wave elastography (SWE) has been limited in breast lesion characterization due to false-negative results from artifacts. The aim of this study was to evaluate an updated Food and Drug Administration-approved breast 2D-SWE algorithm and compare with the standard algorithm (SA). MATERIALS AND METHODS: This prospective, single-center study was approved by our local institutional review board and Health Insurance Portability and Accountability Act compliant. From April 25, 2019 to May 2, 2022, raw shear wave data were saved on patients having screening or diagnostic breast ultrasound on a Siemens Sequoia US. After removing duplicate images and those without biopsy diagnosis or stability over 2 years, there were 298 patients with 394 lesions with biopsy-proven pathology or >2-year follow-up. Raw data were processed using the SA and a new algorithm (NA). Five-millimeter regions of interest were placed in the highest stiffness in the lesion or adjacent 3 mm on the SA. Stiffness values (shear wave speed, max) in this location from both algorithms were recorded. Statistics were calculated for comparing the 2 algorithms. RESULTS: The mean patient age was 56.3 ± 16.1 years (range, 21-93 years). The mean benign lesion size was 10.7 ± 8.0 mm (range, 2-46 mm), whereas the mean malignant lesion size was 14.9 ± 7.8 mm (range, 4-36 mm). There were 201 benign (>2-year follow-up) and 193 biopsied lesions (65 benign; 128 malignant). The mean maximum stiffness for benign lesions was 2.37 m/s (SD 1.26 m/s) for SA and 3.51 m/s (SD 2.05 m/s) for NA. For malignant lesions, the mean maximum stiffness was 4.73 m/s (SD, 1.71 m/s) for SA and 8.45 m/s (SD, 1.42 m/s) for NA. The area under the receiver operating characteristic curve was 0.87 SA and 0.95 NA when using the optimal cutoff value. Using a threshold value of 5.0 m/s for NA and comparing to SA, the sensitivity increased from 0.45 to 1.00 and the specificity decreased from 0.94 to 0.81; the positive predictive value was 0.72, the negative predictive value was 1.00, and the negative likelihood ratio was 0.00. CONCLUSIONS: Using a new breast SWE algorithm significantly improves the sensitivity of the technique with a small decrease in specificity, virtually eliminating the "soft" cancer artifact. The new 2D-SWE algorithm significantly increases the sensitivity and negative predictive value in characterizing breast lesions as benign or malignant and allows for downgrading all BI-RADS 4 lesions.

Long-Term Follow-Up of Non-Enhancing Renal Masses on CEUS.

PURPOSE: To determine the natural history and necessity of long-term follow-up of renal masses that do not demonstrate enhancement on contrast-enhanced ultrasound (CEUS). METHODS: This retrospective single-center study was approved by our local IRB and is HIPAA compliant. Exactly 405 patients with 620 non-enhancing renal masses on CEUS from a previously reported study were followed for up to 10 years. Techniques and equipment are described in the original manuscript. Patient charts and imaging studies were reviewed for the change in features. There were 117 (18.6%) patients lost to follow-up leading to 341 patients with 512 lesions. The lesion size, patient age, number of lesions per patient, and Bosniak class assigned at the initial examination was recorded. RESULTS: Mean patient age was 66 ± 12.6 years (range 17-95 years). Average time of follow-up was 58.9 ± 41.7 months (range 1-207 months). There was a mean of 1.5 ± 1.0 lesions per patient (range 1-7 lesions). Lesion size was 24.9 ± 18.2 mm (range 3-161 mm). There were 276 (53.9%) patients with >5-year follow-up and 78 (15.2%) patients with >10-year follow-up. The probability of change within 5 years was 0% (95% CI: 0-0.37 per 100PY) and 10 years 0% (95% CI: 0.0-0.18 per 100PY). Two lesions (0.4%) resolved by 60 months. Five lesions (1.0%) decreased in size. Four lesions (0.8%) increased in size >20% during the follow-up period but remained benign on subsequent imaging. CONCLUSION: Any non-enhancing renal mass on CEUS can be classified as benign.