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Image Processing Pipeline for Liver Fibrosis Classification Using Ultrasound Shear Wave Elastography.

ABSTRACT: The purpose of this study was to develop an automated method for classifying liver fibrosis stage ≥F2 based on ultrasound shear wave elastography (SWE) and to assess the system's performance in comparison with a reference manual approach. The reference approach consists of manually selecting a region of interest from each of eight or more SWE images, computing the mean tissue stiffness within each of the regions of interest and computing a resulting stiffness value as the median of the means. The 527-subject database consisted of 5526 SWE images and pathologist-scored biopsies, with data collected from a single system at a single site. The automated method integrates three modules that assess SWE image quality, select a region of interest from each SWE measurement and perform machine learning-based, multi-image SWE classification for fibrosis stage ≥F2. Several classification methods were developed and tested using fivefold cross-validation with training, validation and test sets partitioned by subject. Performance metrics were area under receiver operating characteristic curve (AUROC), specificity at 95% sensitivity and number of SWE images required. The final automated method yielded an AUROC of 0.93 (95% confidence interval: 0.90-0.94) versus 0.69 (95% confidence interval: 0.65-0.72) for the reference method, 71% specificity with 95% sensitivity versus 5% and four images per decision versus eight or more. In conclusion, the automated method reported in this study significantly improved the accuracy for ≥F2 classification of SWE measurements as well as reduced the number of measurements needed, which has the potential to reduce clinical workflow.

SUBMITTER: Brattain LJ

PROVIDER: S-EPMC7483774 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundComplications from liver cirrhosis are a leading cause of death in children with cystic fibrosis. Identifying children at risk for developing liver cirrhosis and halting its progression are critical to reducing liver-associated mortality.ObjectiveQuantitative US imaging, such as shear-wave elastography (SWE), might improve the detection of liver fibrosis in children with cystic fibrosis (CF) over gray-scale US alone. We incorporated SWE in our pediatric CF liver disease screening program and evaluated its performance using magnetic resonance (MR) elastography.Materials and methodsNinety-four children and adolescents with CF underwent 178 SWE exams, aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT) and platelet measurements. Of these, 27 children underwent 34 MR elastography exams. We evaluated SWE performance using 6-MHz and 9-MHZ point SWE, and 9-MHz two-dimensional (2-D) SWE.ResultsThe 6-MHz point SWE was the only method that correlated with MR elastography (r=0.52; 95% confidence interval [CI] 0.20-0.74; P=0.003). SWE of 1.45 m/s distinguished normal from abnormal MR elastography (79% sensitivity, 100% specificity, 100% positive predictive value [PPV], 55% negative predictive value [NPV], area under the receiver operating characteristic [AUROC] curve 0.94). SWE of 1.84 m/s separated mild-moderate (3.00-4.77 kPa) from severe (>4.77 kPa) MR elastography (88% sensitivity, 86% specificity, 78% PPV, 93% NPV, AUROC 0.79). Elevations of AST, ALT, GGT and thrombocytopenia were associated with higher SWE. AST-to-platelet ratio index of 0.42, fibrosis-4 of 0.29, and GGT-to-platelet ratio of 1.43 all had >95% NPV for SWE >1.84 m/s.ConclusionGiven its correlation with MR elastography, SWE might be a clinically useful predictor of liver fibrosis. We identified imaging criteria delineating the use of SWE to identify increased liver stiffness in children with CF. With multicenter validation, these data might be used to improve the detection and monitoring of liver fibrosis in children with CF.

Project description:BackgroundPediatric patients with liver disease require noninvasive monitoring to evaluate the risk of fibrosis progression. This study aimed to identify the significant factors affecting liver stiffness values using two-dimensional shear-wave elastography (2D-SWE), and determine whether liver stiffness can predict the fibrosis stage of various childhood liver diseases.MethodsThis study included 30 children (22 boys and 8 girls; mean age, 5.1 ± 6.1 years; range, 7 days-17.9 years) who had undergone biochemical evaluation, 2D-SWE examination, histopathologic analysis of fibrosis grade (F0 to F3), assessment of necroinflammatory activity, and steatosis grading between August 2016 and March 2020. The liver stiffness from 2D-SWE was compared between fibrosis stages using Kruskal-Wallis analysis. Factors that significantly affected liver stiffness were evaluated using univariate and multivariate linear regression analyses. The diagnostic performance was determined from the area under the receiver operating curve (AUC) values of 2D-SWE liver stiffness.ResultsLiver stiffness at the F0-1, F2, and F3 stages were 7.9, 13.2, and 21.7 kPa, respectively (P < 0.001). Both fibrosis stage and necroinflammatory grade were significantly associated with liver stiffness (P < 0.001 and P = 0.021, respectively). However, in patients with alanine aminotransferase (ALT) levels below 200 IU/L, the only factor affecting liver stiffness was fibrosis stage (P = 0.030). The liver stiffness value could distinguish significant fibrosis (≥ F2) with an AUC of 0.950 (cutoff value, 11.3 kPa) and severe fibrosis (F3 stage) with an AUC of 0.924 (cutoff value, 18.1 kPa). The 2D-SWE values for differentiating significant fibrosis were 10.5 kPa (≥ F2) and 18.1 kPa (F3) in patients with ALT levels below 200 IU/L.ConclusionThe liver stiffness values on 2D-SWE can be affected by both fibrosis and necroinflammatory grade and can provide excellent diagnostic performance in evaluating the fibrosis stage in various pediatric liver diseases. However, clinicians should be mindful of potential confounders, such as necroinflammatory activity or transaminase level, when performing 2D-SWE measurements for liver fibrosis staging.

Project description:Thromboembolism in a cerebral blood vessel is associated with high morbidity and mortality. Mechanical thrombectomy (MT) is one of the emergenc proceduresperformed to remove emboli. However, the interventional approaches such as aspiration catheters or stent retriever are empirically selected. An inappropriate selection of surgical devices can influence the success rate during embolectomy, which can lead to an increase in brain damage. There has been growing interest in the study of clot composition and using a priori knowledge of clot composition to provide guidance for an appropriate treatment strategy for interventional physicians. Developing imaging tools which can allow interventionalists to understand clot composition could affect management and device strategy. In this study, we investigated how clots of different compositions can be characterized by using acoustic radiation force optical coherence elastography (ARF-OCE) and compared with ultrasound shear wave elastography (SWE). Five different clots compositions using human blood were fabricated into cylindrical forms from fibrin-rich (21% red blood cells, RBCs) to RBC-rich (95% RBCs). Using the ARF-OCE and SWE, we characterized the wave velocities measured in the time-domain. In addition, the semi-analytical finite element model was used to explore the relationship between the phase velocities with various frequency ranges and diameters of the clots. The study demonstrated that the wave group velocities generally decrease as RBC content increases in ARF-OCE and SWE. The correlation of the group velocities from the OCE and SWE methods represented a good agreement as RBC composition is larger than 39%. Using the phase velocity dispersion analysis applied to ARF-OCE data, we estimated the shear wave velocities decoupling the effects of the geometry and material properties of the clots. The study demonstrated that the composition of the clots can be characterized by elastographic methods using ARF-OCE and SWE, and OCE demonstrated better ability to discriminate between clots of different RBC compositions, compared to the ultrasound-based approach, especially in clots with low RBC compositions.

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Image Processing Pipeline for Liver Fibrosis Classification Using Ultrasound Shear Wave Elastography.

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