Multiparametric ultrasound as a new concept of assessment of liver tissue damage.

Liver disease accounts for approximately 2 million deaths per year worldwide. All chronic liver diseases (CLDs), whether of toxic, genetic, autoimmune, or infectious origin, undergo typical histological changes in the structure of the tissue. These changes may include the accumulation of extracellular matrix material, fats, triglycerides, or tissue scarring. Noninvasive methods for diagnosing CLD, such as conventional B-mode ultrasound (US), play a significant role in diagnosis. Doppler US, when coupled with B-mode US, can be helpful in evaluating the hemodynamics of hepatic vessels and detecting US findings associated with hepatic decompensation. US elastography can assess liver stiffness, serving as a surrogate marker for liver fibrosis. It is important to note that interpreting these values should not rely solely on a histological classification. Contrast-enhanced US (CEUS) provides valuable information on tissue perfusion and enables excellent differentiation between benign and malignant focal liver lesions. Clinical evaluation, the etiology of liver disease, and the patient current comorbidities all influence the interpretation of liver stiffness measurements. These measurements are most clinically relevant when interpreted as a probability of compensated advanced CLD. B-mode US offers a subjective estimation of fatty infiltration and has limited sensitivity for mild steatosis. The controlled attenuation parameter requires a dedicated device, and cutoff values are not clearly defined. Quan-titative US parameters for liver fat estimation include the attenuation coefficient, backscatter coefficient, and speed of sound. These parameters offer the advantage of providing fat quantification alongside B-mode evaluation and other US parameters. Multiparametric US (MPUS) of the liver introduces a new concept for complete noninvasive diagnosis. It encourages examiners to utilize the latest features of an US machine, including conventional B-mode, liver stiffness evaluation, fat quantification, dispersion imaging, Doppler US, and CEUS for focal liver lesion characterization. This comprehensive approach allows for diagnosis in a single examination, providing clinicians worldwide with a broader perspective and becoming a cornerstone in their diagnostic arsenal. MPUS, in the hands of skilled clinicians, becomes an invaluable predictive tool for diagnosing, staging, and monitoring CLD.

Comparison of Visual Transient Elastography, Vibration Controlled Transient Elastography, Shear Wave Elastography and Sound Touch Elastography in Chronic liver Disease assessment using liver biopsy as 'Gold Standard'.

PURPOSE: Chronic liver disease (CLD) is considered one of the main causes of death. Ultrasound Elastography (USE) is a CLD assessment imaging method. This study aims to evaluate a recently introduced commercial alternative of USE, Visual Transient Elastography (ViTE), and to compare it with three established USE methods, Vibration Controlled Transient Elastography (VCTE), Shear Wave Elastography (SWE) and Sound Touch Elastography (STE), using Liver Biopsy (LB) as 'Gold Standard'. METHOD: 152 consecutive subjects underwent a liver ViTE, VCTE, SWE and STE examination. A Receiver Operator Characteristic (ROC) analysis was performed on the measured stiffness values of each method. An inter- intra-observer analysis was also performed. RESULTS: The ViTE, VCTE, SWE and STE ROC analysis resulted in an AUC of 0.9481, 0.9900, 0.9621 and 0.9683 for F ≥ F1, 0.9698, 0.9767, 0.9931 and 0.9834 for F ≥ F2, 0.9846, 0.9651, 0.9835 and 0.9763 for F ≥ F3, and 0.9524, 0.9645, 0.9656, and 0.9509 for F = F4, respectively. ICC scores were 0.98 for Inter-observer and 0.97 for Intra-observer variability analysis. CONCLUSION: ViTE performance in CLD stage differentiation is comparable to the performance of VCTE, SWE and STE.

Non-invasive assessment of liver abnormalities in pediatric Fontan patients.

Liver abnormalities are well known among long-term survivors of Fontan palliation, which remains the definite surgery for complex congenital heart disease and single ventricle physiology. Pediatric data however are scarce. We assessed the prevalence and degree of liver abnormalities in pediatric Fontan patients through non-invasive investigations suitable for longitudinal follow-up. Thirty-five patients with a median age of 11.8 years (5.2-16.6) and median time since Fontan of 6 years (1.17-13.83) were studied. Each child underwent a blood test, liver Doppler ultrasound (US), and transient elastography (TE). Healthy children were used as controls for TE measurement. AST, ALT, γGT, and direct bilirubin were abnormal in respectively 12 (34%), 5 (14%), 24 (69%), and 7 (20%) patients, while platelet count was decreased in 7 (20%). Splenomegaly was present in 7 (20%) patients. Portal vein mean flow velocity was < 15 cm/s in 19 (54%) patients indicative of portal hypertension. Twenty-two patients (63%) showed inferior vena cava collapsibility index values below 17%, indicating venous congestion. Hepatic artery and superior mesenteric artery resistance index were inversely correlated with time post Fontan (p < 0.05). TE values in Fontan patients were significantly higher than controls, with a median of 12.6 versus 4.6 kPa (p < 0.001) and were already increased shortly after Fontan completion. Conclusion: Liver abnormalities are frequently observed in pediatric Fontan patients. The non-invasive investigations used were not able to confirm liver fibrosis or differentiate hepatic congestion from fibrosis. Based on our findings, we propose a prospective screening protocol with serial measurements of laboratory, (Doppler) US, and TE parameters. What is Known: • Hepatic dysfunction is a well-known consequence of the Fontan circulation. • The natural history of Fontan-associated liver disease in the pediatric age group remains unclear. What is New: • Liver abnormalities are frequently observed in pediatric Fontan patients; however, differentiating liver fibrosis and hepatic congestion with non-invasive investigations remains challenging. Sonographic Doppler measurements may improve our insight in both Fontan-associated liver disease development and the functioning of the Fontan circulation. • A prospective screening protocol is proposed to improve our ability to detect Fontan-associated liver disease early on and understand its natural history.

Noninvasive assessment of congestive hepatopathy in patients with constrictive pericardial physiology using MR relaxometry.

BACKGROUND: Constrictive pericarditis represents a treatable cause of mainly right heart failure (RHF), characterized by increased filling pressures and congestive hepatopathy. We hypothesized assessment of T1 and T2 liver relaxation times enables to depict liver congestion, and thus to diagnose RHF. METHODS: Cardiovascular magnetic resonance imaging (CMR) was performed in 45 pericarditis patients i.e., 25 with constrictive physiology (CP+), 20 with normal physiology (CP-), and 30 control subjects. CMR included morphologic and functional assessment of the heart and pericardium. Liver relaxation times were measured on T1 and T2 cardiac maps. RESULTS: CP+ and CP- patients were predominantly male, but CP+ patients were on average 13 years older than CP- patients (p = 0.003). T1 and T2 Liver values were significantly higher in CP+ than in CP- patients and controls, i.e. T1: 765 ± 102 ms vs 581 ± 56 ms and 537 ± 30 ms (both p < 0.001); T2: 63 ± 13 ms vs 50 ± 4 ms and 46 ± 4 ms (both p < 0.001). Extracellular volume (ECV) liver values were also increased, i.e. 42 ± 7% CP+ vs 31 ± 3% CP- and 30 ± 3% control (both p < 0.001). Using a cut-off right atrial pressure of >5 mmHg to discriminate between normal and increased pressure, native T1 liver yielded the highest AUC (0.926) at ROC analysis with a sensitivity of 79.3% and specificity of 95.6%. Gamma-glutamyl transpeptidase correlated well withT1 liver (r2 = 0.43) and ECV liver (r2 = 0.30). Excellent intra- and inter-reader agreement was found for T1, T2 and ECV measurement of the liver. CONCLUSIONS: Assessment of liver relaxation times in pericarditis patients provide valuable information on the presence of concomitant congestive hepatopathy, reflecting RHF.

Assessment of agreement between manual and automated processing of liver MR elastography for shear stiffness estimation in children and young adults with autoimmune liver disease.

PURPOSE: To compare automated versus standard of care manual processing of 2D gradient recalled echo (GRE) liver MR Elastography (MRE) in children and young adults. MATERIALS AND METHODS: 2D GRE liver MRE data from research liver MRI examinations performed as part of an autoimmune liver disease registry between March 2017 and March 2020 were analyzed retrospectively. All liver MRE data were acquired at 1.5 T with 60 Hz mechanical vibration frequency. For manual processing, two independent readers (R1, R2) traced regions of interest on scanner generated shear stiffness maps. Automated processing was performed using MREplus+ (Resoundant Inc.) using 90% (A90) and 95% (A95) confidence masks. Agreement was evaluated using intra-class correlation coefficients (ICC) and Bland-Altman analyses. Classification performance was evaluated using receiver operating characteristic curve (ROC) analyses. RESULTS: In 65 patients with mean age of 15.5 ± 3.8 years (range 8-23 years; 35 males) median liver shear stiffness was 2.99 kPa (mean 3.55 ± 1.69 kPa). Inter-reader agreement for manual processing was very strong (ICC = 0.99, mean bias = 0.01 kPa [95% limits of agreement (LoA): - 0.41 to 0.44 kPa]). Correlation between manual and A95 automated processing was very strong (R1: ICC = 0.988, mean bias = 0.13 kPa [95% LoA: - 0.40 to 0.68 kPa]; R2: ICC = 0.987, mean bias = 0.13 kPa [95% LoA: - 0.44 to 0.69 kPa]). Automated measurements were perfectly replicable (ICC = 1.0; mean bias = 0 kPa). CONCLUSION: Liver shear stiffness values obtained using automated processing showed excellent agreement with manual processing. Automated processing of liver MRE was perfectly replicable.

Efficacy of shear wave elastography for assessment of liver function in patients with heart failure.

AIMS: Liver dysfunction is important for prognosis in heart failure (HF). Shear wave elastography (SWE), which is a novel ultrasound technique for charactering tissues, has been used in liver diseases. However, clinical implication of SWE, including dispersion slope, remains unknown in heart diseases. This study aimed to evaluate the efficacy of SWE assessing liver function in the severity of HF. METHODS AND RESULTS: We enrolled 316 consecutive patients with or suspected heart diseases, who were classified according to the American College of Cardiology Foundation/American Heart Association stage of HF, including 37 with Stage A, 139 with Stage B, 114 with Stage C, and 26 with Stage D, and 45 normal subjects. Elasticity and dispersion slope of shear wave were assessed according to the HF stage. Elasticity and dispersion slope were not elevated in normal subjects and patients with Stage A. Elasticity was slightly increased from Stage A to Stage C and was remarkably elevated in Stage D (normal: 5.2 ± 1.1 kPa, Stage A: 5.4 ± 1.2 kPa, Stage B: 6.4 ± 1.8 kPa, Stage C: 7.8 ± 3.5 kPa, and Stage D: 17.7 ± 12.7 kPa), whereas dispersion slope was gradually increased from Stage A to Stage D (normal: 9.7 ± 1.7m/s/kHz, Stage A: 10.4 ± 1.6m/s/kHz, Stage B: 11.7 ± 2.4m/s/kHz, Stage C: 13.2 ± 3.4m/s/kHz, and Stage D: 17.6 ± 5.6 m/s/kHz). In the early HF stage, dispersion slope was elevated. In the advanced HF stage, both elasticity and dispersion slope were elevated. Liver function test abnormalities were observed only from Stage C or Stage D. CONCLUSIONS: Dispersion slope could detect early liver damage, and the combination of elasticity and dispersion slope could clarify the progression of liver dysfunction in HF. SWE may be valuable to manage therapeutic strategies in patients with HF.

Quantitative liver surface nodularity score based on imaging for assessment of early cirrhosis in patients with chronic liver disease: A protocol for systematic review and meta-analysis.

BACKGROUND: Early stage of cirrhosis is of great value in the diagnosis and management in patients with chronic liver disease (CLD). Recent studies have shown that quantitative liver surface nodularity (LSN) score based on imaging techniques can be used to predict the early cirrhosis stage noninvasively, with varied diagnostic accuracy and limited sample size. Hence, this study will evaluate the diagnostic accuracy of LSN in the prediction of early cirrhosis. METHODS: We will conduct a comprehensive search in PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases to identify eligible studies. The literature screening, data extraction, data analysis, and quality assessment will then be carried out. The summary receiver-operating-characteristic (ROC) and pooled sensitivity, specificity will be calculated to summarize the diagnostic performance of LSN using a random-effect model. A meta-regression analysis will be performed to investigate the underlying cause of the heterogeneity. RESULTS: This study will evaluate the diagnostic accuracy of LSN score in the identification of early cirrhosis, which may further determine whether this method can be used as an alternative in the assessment of CLD patients. CONCLUSIONS: This study will help to determine the diagnostic accuracy and summarize the recent evidence on this issue. STUDY REGISTRATION: INPLASY2020100096.

Quantitative magnetic resonance imaging for chronic liver disease.

Chronic liver disease (CLD) has rapidly increased in prevalence over the past two decades, resulting in significant morbidity and mortality worldwide. Historically, the clinical gold standard for diagnosis, assessment of severity, and longitudinal monitoring of CLD has been liver biopsy with histological analysis, but this approach has limitations that may make it suboptimal for clinical and research settings. Magnetic resonance (MR)-based biomarkers can overcome the limitations by allowing accurate, precise, and quantitative assessment of key components of CLD without the risk of invasive procedures. This review briefly describes the limitations associated with liver biopsy and the need for non-invasive biomarkers. It then discusses the current state-of-the-art for MRI-based biomarkers of liver iron, fat, and fibrosis, and inflammation.

Imaging Software-Based Sarcopenia Assessment in Gastroenterology: Evolution and Clinical Meaning.

Sarcopenia is gaining attention as a negative prognostic factor in different fields of medicine, including chronic liver failure. However, the assessment of sarcopenia in patients with liver diseases is often neglected due to unawareness of reliable tools and methods and thus is limited to research studies. Cross-sectional imaging is a diffuse diagnostic tool and is commonly performed in patients with chronic liver failure. The last advancements in radiology image analysis using dedicated software allow an easy and standardized method to assess skeletal muscle volume. Several measures can be obtained from cross-sectional imaging analysis to evaluate sarcopenia in patients affected by chronic liver disease. We aimed to review the recent advances in imaging-based sarcopenia assessment, in particular in patients with chronic liver diseases. As a result, we found that the skeletal muscle index (SMI) seems to be a reliable method to assess sarcopenia in cirrhotic patients. Even if further studies are needed to validate proper cut-offs for each clinical endpoint, physicians are invited to consider the assessment of sarcopenia in the work-up of patients with chronic liver disease.

Computed tomography with Hounsfield unit assessment is useful in the diagnosis of liver lobe torsion in pet rabbits (Oryctolagus cuniculus).

Clinical signs of liver lobe torsion in rabbits are often nonspecific and mimic those that are also generally detected with gastrointestinal stasis. Nonspecific clinical signs may result in pursuit of full-body imaging such as computed tomography (CT). The aim of this multicenter, retrospective, case series study was to describe CT findings of liver lobe torsion in a group of rabbits. Computed tomography studies of six rabbits with confirmed liver lobe torsion by surgery or necropsy were evaluated. The caudate liver lobe was affected in six out of six rabbits and was enlarged, rounded, hypoattenuating, heterogeneous, and minimally to noncontrast enhancing, with scant regional peritoneal effusion. Precontrast, mean Hounsfield units (HU) of the torsed liver lobe (39.3 HU [range, 24.4-48.1 HU]) were lower than mean HU of normal liver (55.1 HU [range, 49.6-60.8 HU]), with a mean torsed:normal HU ratio of 0.71 (range, 0.49-0.91). Postcontrast, mean HU of the torsed liver lobe (38.4 HU [range, 19.7-48.9 HU]) were also lower than mean HU of normal liver (108.4 HU [range, 84.5-142.0 HU]), with a lower postcontrast mean torsed:normal HU ratio of 0.35 (range, 0.14-0.48) compared to precontrast. Mean HU of torsed liver lobes had little difference pre- and postcontrast (postcontrast HU 1.0 times the average precontrast HU [range, 0.81-1.1]), and contrast enhancement of the torsed liver lobes was on average 50% lower than in normal liver. Liver lobe torsion should be considered in rabbits with an enlarged, hypoattenuating, heterogeneous, minimally to noncontrast enhancing liver lobe, particularly the caudate lobe, and scant regional peritoneal effusion.

Deep learning networks on chronic liver disease assessment with fine-tuning of shear wave elastography image sequences.

Chronic liver disease (CLD) is currently one of the major causes of death worldwide. If not treated, it may lead to cirrhosis, hepatic carcinoma and death. Ultrasound (US) shear wave elastography (SWE) is a relatively new, popular, non-invasive technique among radiologists. Although many studies have been published validating the SWE technique either in a clinical setting, or by applying machine learning on SWE elastograms, minimal work has been done on comparing the performance of popular pre-trained deep learning networks on CLD assessment. Currently available literature reports suggest technical advancements on specific deep learning structures, with specific inputs and usually on a limited CLD fibrosis stage class group, with limited comparison on competitive deep learning schemes fed with different input types. The aim of the present study is to compare some popular deep learning pre-trained networks using temporally stable and full elastograms, with or without augmentation as well as propose suitable deep learning schemes for CLD diagnosis and progress assessment. 200 liver biopsy validated patients with CLD, underwent US SWE examination. Four images from the same liver area were saved to extract elastograms and processed to exclude areas that were temporally unstable. Then, full and temporally stable masked elastograms for each patient were separately fed into GoogLeNet, AlexNet, VGG16, ResNet50 and DenseNet201 with and without augmentation. The networks were tested for differentiation of CLD stages in seven classification schemes over 30 repetitions using liver biopsy as the reference. All networks achieved maximum mean accuracies ranging from 87.2%-97.4% and area under the receiver operating characteristic curves (AUCs) ranging from 0.979-0.990 while the radiologists had AUCs ranging from 0.800-0.870. ResNet50 and DenseNet201 had better average performance than the other networks. The use of the temporal stability mask led to improved performance on about 50% of inputs and network combinations while augmentation led to lower performance for all networks. These findings can provide potential networks with higher accuracy and better setting in the CLD diagnosis and progress assessment. A larger data set would help identify the best network and settings for CLD assessment in clinical practice.

MRI-Based Radiomics Models Developed With Features of the Whole Liver and Right Liver Lobe: Assessment of Hepatic Inflammatory Activity in Chronic Hepatic Disease.

BACKGROUND: The noninvasive assessment of hepatic inflammatory activity (HIA) is crucial for making clinical decisions and monitoring therapeutic efficacy in chronic liver disease (CLD). PURPOSE: To develop MRI-based radiomics models by extracting features from the whole liver and localized regions of the right liver lobe, compare the efficiency of two radiomics models, and further develop a radiomics nomogram for the assessment of HIA in CLD. STUDY TYPE: Retrospective. POPULATION: In all, 137 consecutive patients. FIELD STRENGTH/SEQUENCE: 1.5T/T2 -weighted imaging. ASSESSMENT: All patients (nonsignificant HIA, n = 98; significant HIA, n = 39) were randomly divided into a training (n = 95) and a test cohort (n = 42). Radiomics features were extracted from the regions covering the whole liver (ROI-w) and localized regions of the right liver lobe (ROI-r). Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analyses were used to select features and develop radiomics models. A combined model fusing the valuable radiomics features with clinical-radiological predictors was developed. Finally, a radiomics nomogram derived from the combined model was developed. STATISTICAL TESTS: Synthetic minority oversampling technique algorithm, LASSO, receiver operator characteristic curve, and calibration curve analysis were performed. RESULTS: The area under the curve (AUC), sensitivity, and specificity of the ROI-w radiomics model in assessing HIA were 0.858, 0.800, and 0.733, respectively. The ROI-r model were 0.844, 0.733, and 0.867, respectively. No differences were detected between the two radiomics models (P = 0.8329). The combined model fusing valuable ROI-w radiomics features, albumin, and periportal edema exhibited a promising performance (AUC, 0.911). The calibration curves showed good agreement between the actual observations and nomogram predictions. DATA CONCLUSION: The MRI-based radiomics models had a powerful ability to evaluate HIA and the ROI-w radiomics model was comparable to the ROI-r model. Moreover, the radiomics nomogram could be a favorable method to individually estimate HIA in CLD. J. MAGN. RESON. IMAGING 2020;52:1668-1678.

Visual liver assessment using Gd-EOB-DTPA-enhanced magnetic resonance imaging of patients in the early post-Fontan period.

No imaging modality can be used to evaluate Fontan-associated liver disease (FALD). We retrospectively reviewed hepatic gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid-enhanced magnetic resonance imaging (EOB-MRI) characteristics of patients within 1 year post-Fontan procedure, and we evaluated the association between hepatic imaging abnormalities and clinical parameters, including follow-up cardiac catheterization and laboratory test findings. The EOB-MR images were graded, based on the extent of the decreased enhancement, as "normal" (Grade 1), "segmental" (Grade 2), "regional" (Grade 3), and "diffuse" (Grade 4). We enrolled 37 patients (mean age, 3.5 ± 1.0 years): 9 patients had Grade 1 or 2; 14 patients, Grade 3; and 14 patients, Grade 4. EOB-MRI revealed characteristic reticular or mosaic patterns of diminished enhancement (i.e. "frog spawn" appearance). Ultrasonography did not detect diminished enhancement or "frog spawn" appearance. A trend existed toward increased grade severity in imaging with increased central venous pressure, pulmonary vascular resistance, and gamma-glutamyltransferase levels. Noninvasive EOB-MRI revealed the characteristic pattern of diminished enhancement, which was correlated with certain clinical parameters indicative of Fontan physiology and liver dysfunction. Early-stage FALD may occur soon after the Fontan procedure and is associated with increased pressure in the inferior vena cava and hepatic veins.

Assessment of Lesion Detectability in Dynamic Whole-Body PET Imaging Using Compartmental and Patlak Parametric Mapping.

PURPOSE: Hybrid dynamic imaging allows not only the estimation of whole-body (WB) macroparametric maps but also the estimation of microparameters in the initial bed position targeting the blood pool region containing the pathology owing to the limited axial field of view of PET scanners. In this work, we assessed the capability of multipass WB F-FDG PET parametric imaging in terms of lesion detectability through qualitative and quantitative evaluation of simulation and clinical studies. METHODS: Simulation studies were conducted by generating data incorporating 3 liver and 3 lung lesions produced by 3 noise levels and 20 noise realizations for each noise level to estimate bias and lesion detection features. The total scan time for the clinical studies of 8 patients addressed for lung and liver lesions staging, including dynamic and static WB imaging, lasted 80 minutes. An in-house-developed MATLAB code was utilized to derive the microparametric and macroparametric maps. We compared lesion detectability and different image-derived PET metrics including the SUVs, Patlak-derived influx rate constant (Ki) and distribution volume (V) and K1, k2, k3, blood volume (bv) microparameters, and Ki estimated using the generalized linear least square approach. RESULTS: In total, 104 lesions were detected, among which 47 were located in the targeted blood pool bed position where all quantitative parameters were calculated, thus enabling comparative analysis across all parameters. The evaluation encompassed visual interpretation performed by an expert nuclear medicine specialist and quantitative analysis. High correlation coefficients were observed between SUVmax and Kimax derived from the generalized linear least square approach, as well as Ki generated by Patlak graphical analysis. Moreover, 3 contrast-enhanced CT-proven malignant lesions located in the liver and a biopsy-proven malignant liver lesion not visible on static SUV images and Patlak maps were clearly pinpointed on K1 and k2 maps. CONCLUSIONS: Our results demonstrate that full compartmental modeling for the region containing the pathology has the potential of providing complementary information and, in some cases, more accurate diagnosis than conventional static SUV imaging, favorably comparing to Patlak graphical analysis.

Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease.

OBJECTIVES: To evaluate whether the liver and spleen volumetric indices, measured on portal venous phase CT images, could be used to assess liver fibrosis severity in chronic liver disease. METHODS: From 2007 to 2017, 558 patients (mean age 48.7 ± 13.1 years; 284 men and 274 women) with chronic liver disease (n = 513) or healthy liver (n = 45) were retrospectively enrolled. The liver volume (sVolL) and spleen volume (sVolS), normalized to body surface area and liver-to-spleen volume ratio (VolL/VolS), were measured on CT images using a deep learning algorithm. The correlation between the volumetric indices and the pathologic liver fibrosis stages combined with the presence of decompensation (F0, F1, F2, F3, F4C [compensated cirrhosis], and F4D [decompensated cirrhosis]) were assessed using Spearman's correlation coefficient. The performance of the volumetric indices in the diagnosis of advanced fibrosis, cirrhosis, and decompensated cirrhosis were evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: The sVolS (ρ = 0.47-0.73; p < .001) and VolL/VolS (ρ = -0.77-- 0.48; p < .001) showed significant correlation with liver fibrosis stage in all etiological subgroups (i.e., viral hepatitis, alcoholic and non-alcoholic fatty liver, and autoimmune diseases), while the significant correlation of sVolL was noted only in the viral hepatitis subgroup (ρ = - 0.55; p < .001). To diagnose advanced fibrosis, cirrhosis, and decompensated cirrhosis, the VolL/VolS (AUC 0.82-0.88) and sVolS (AUC 0.82-0.87) significantly outperformed the sVolL (AUC 0.63-0.72; p < .001). CONCLUSION: The VolL/VolS and sVolS may be used for assessing liver fibrosis severity in chronic liver disease. KEY POINTS: • Volumetric indices of liver and spleen measured on computed tomography images may allow liver fibrosis severity to be assessed in patients with chronic liver disease.

A two-step automated quality assessment for liver MR images based on convolutional neural network.

PURPOSE: To propose an automatic approach based on a convolutional neural network (CNN) to evaluate the quality of T2-weighted liver magnetic resonance (MR) images as nondiagnostic (ND) or diagnostic (D). MATERIALS AND METHODS: We included 150 T2-weighted liver MR imaging examinations in this retrospective study. Each slice of liver image was annotated with a label D or ND by two radiologists with seven and six years of experience, respectively. Additionally, the radiologists segmented the liver region manually as the ground truth for liver segmentation. A CNN was trained to segment the liver region and another CNN was used to classify the qualities of patches extracted from the liver region. The quality of an image was obtained from the percentage of nondiagnostic patches in all liver patches in the image. Treating nondiagnostic as positive, the accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the receiver operating characteristic curve (AUC), and confusion matrix were used to evaluate our model. A Mann-Whitney U test was performed with the statistical significance set at 0.05. RESULTS: Our model achieved good performance with an accuracy of 88.3 %, sensitivity of 86.0 %, specificity of 89.4 %, PPV of 78.6 %, NPV of 93.4 %, and AUC of 0.911 (95 % confidence interval: 0.882-0.939, p < 0.05). The confusion matrix of our model indicated good concordance with that of the radiologists. CONCLUSIONS: The proposed two-step patch-based model achieved excellent performance when assessing the quality of liver MR images.

CT iterative reconstruction algorithms: a task-based image quality assessment.

PURPOSE: To assess the dose performance in terms of image quality of filtered back projection (FBP) and two generations of iterative reconstruction (IR) algorithms developed by the most common CT vendors. MATERIALS AND METHODS: We used four CT systems equipped with a hybrid/statistical IR (H/SIR) and a full/partial/advanced model-based IR (MBIR) algorithms. Acquisitions were performed on an ACR phantom at five dose levels. Raw data were reconstructed using a standard soft tissue kernel for FBP and one iterative level of the two IR algorithm generations. The noise power spectrum (NPS) and the task-based transfer function (TTF) were computed. A detectability index (d') was computed to model the detection task of a large mass in the liver (large feature; 120 HU and 25-mm diameter) and a small calcification (small feature; 500 HU and 1.5-mm diameter). RESULTS: With H/SIR, the highest values of d' for both features were found for Siemens, then for Canon and the lowest values for Philips and GE. For the large feature, potential dose reductions with MBIR compared with H/SIR were - 35% for GE, - 62% for Philips, and - 13% for Siemens; for the small feature, corresponding reductions were - 45%, - 78%, and - 14%, respectively. With the Canon system, a potential dose reduction of - 32% was observed only for the small feature with MBIR compared with the H/SIR algorithm. For the large feature, the dose increased by 100%. CONCLUSION: This multivendor comparison of several versions of IR algorithms allowed to compare the different evolution within each vendor. The use of d' is highly adapted and robust for an optimization process. KEY POINTS: • The performance of four CT systems was evaluated by using imQuest software to assess noise characteristic, spatial resolution, and lesion detection. • Two task functions were defined to model the detection task of a large mass in the liver and a small calcification. • The advantage of task-based image quality assessment for radiologists is that it does not include only complicated metrics, but also clinically meaningful image quality.

Liver Strain Using Feature Tracking of Cine Cardiac Magnetic Resonance Imaging: Assessment of Liver Dysfunction in Patients with Fontan Circulation and Tetralogy of Fallot.

We propose a novel method to quantify pulsatile liver deformation using the feature tracking method of cardiac cine magnetic resonance imaging (MRI) and investigate its association with liver dysfunction in long-term postoperative patients after Fontan and intracardiac repair for the tetralogy of Fallot (TOF). Standard cine MRI which was previously performed for cardiac evaluation of 85 patients who underwent Fontan operation (mean age, 22.9 years), 43 patients with TOF (mean age, 34.6 years), and 32 healthy controls (mean age, 42.3 years) were retrospectively analyzed. Pulsatile liver deformation in the craniocaudal direction was calculated using the feature tracking method of cardiac cine imaging derived from cine-balanced turbo field-echo sequences performed on a 1.5 Tesla MR scanner, and was defined as liver strain. The liver strain was compared across the three patient groups using one-way analysis of variance. Liver dysfunction by a liver strain were compared using the Mann-Whitney U test. Liver strain for patients who underwent Fontan operation and TOF patients was significantly lower than controls (Fontan, 13.3 ± 6.5%; TOF, 15.0 ± 11.2%; controls, 23.1 ± 10.2%, p < 0.0001). In Fontan and TOF patients, MELD score was significantly greater for patients with a liver strain < 15% than those with values > 15% (5.9 ± 5.8 vs. 2.9 ± 2.9, p < 0.001). Lower liver strain values were found in adolescent and adult patients after Fontan operation and TOF, and correlates with the severity of liver injury, expressed as MELD score. Our method can evaluate hepatic function in adult congenital heart disease, together with the assessment of cardiac function.