Elhamy Heba

Magnetic resonance elastography is superior to acoustic radiation force impulse for the Diagnosis of fibrosis in patients with biopsy‐proven nonalcoholic fatty liver disease: A prospective study

Magnetic resonance elastography (MRE), an advanced magnetic resonance–based imaging technique, and acoustic radiation force impulse (ARFI), an ultrasound‐based imaging technique, are accurate for diagnosing nonalcoholic fatty liver disease (NAFLD) fibrosis. However, no head‐to‐head comparisons between MRE and ARFI for diagnosing NAFLD fibrosis have been performed. We compared MRE versus ARFI head‐to‐head for diagnosing fibrosis in well‐characterized patients with biopsy‐proven NAFLD. This cross‐sectional analysis of a prospective cohort involved 125 patients (54.4% female) who underwent MRE, ARFI, and contemporaneous liver biopsies scored using the Nonalcoholic Steatohepatitis Clinical Research Network histological scoring system. The performances of MRE versus ARFI for diagnosing fibrosis were evaluated using area under the receiver operating characteristic curves (AUROCs). The mean (± standard deviation) age and body mass index were 48.9 (±15.4) years and 31.8 (±7.0) kg/m2, respectively. For diagnosing any fibrosis (≥ stage 1), the MRE AUROC was 0.799 (95% confidence interval [CI] 0.723‐0.875), significantly (P = 0.012) higher than the ARFI AUROC of 0.664 (95% CI 0.568‐0.760). In stratified analysis by presence or absence of obesity, MRE was superior to ARFI for diagnosing any fibrosis in obese patients (P < 0.001) but not in nonobese patients (P = 0.722). The MRE AUROCs for diagnosing ≥stages 2, 3, and 4 fibrosis were 0.885 (95% CI 0.816‐0.953), 0.934 (95% CI 0.863‐1.000), and 0.882 (95% CI 0.729‐1.000); and the ARFI AUROCs were 0.848 (95% CI 0.776‐0.921), 0.896 (95% CI 0.824‐0.968), and 0.862 (95% CI 0.721‐1.000). MRE had higher AUROCs than ARFI for discriminating dichotomized fibrosis stages at all dichotomization cutoff points, but the AUROC differences decreased as the cutoff points (fibrosis stages) increased. Conclusion: MRE is more accurate than ARFI for diagnosing any fibrosis in NAFLD patients, especially those who are obese. (Hepatology 2016;63:453–461)

Noninvasive Diagnosis of Nonalcoholic Fatty Liver Disease and Quantification of Liver Fat Using a New Quantitative Ultrasound Technique

BACKGROUND & AIMS Liver biopsy analysis is the standard method used to diagnose nonalcoholic fatty liver disease (NAFLD). Advanced magnetic resonance imaging is a noninvasive procedure that can accurately diagnose and quantify steatosis, but is expensive. Conventional ultrasound is more accessible but identifies steatosis with low levels of sensitivity, specificity, and quantitative accuracy, and results vary among technicians. A new quantitative ultrasound (QUS) technique can identify steatosis in animal models. We assessed the accuracy of QUS in the diagnosis and quantification of hepatic steatosis, comparing findings with those from magnetic resonance imaging proton density fat fraction (MRI-PDFF) analysis as a reference. METHODS We performed a prospective, cross-sectional analysis of a cohort of adults (N = 204) with NAFLD (MRI-PDFF, ≥5%) and without NAFLD (controls). Subjects underwent MRI-PDFF and QUS analyses of the liver on the same day at the University of California, San Diego, from February 2012 through March 2014. QUS parameters and backscatter coefficient (BSC) values were calculated. Patients were assigned randomly to training (n = 102; mean age, 51 ± 17 y; mean body mass index, 31 ± 7 kg/m(2)) and validation (n = 102; mean age, 49 ± 17 y; body mass index, 30 ± 6 kg/m(2)) groups; 69% of patients in each group had NAFLD. RESULTS BSC (range, 0.00005-0.25 1/cm-sr) correlated with MRI-PDFF (Spearman ρ = 0.80; P < .0001). In the training group, the BSC analysis identified patients with NAFLD with an area under the curve value of 0.98 (95% confidence interval, 0.95-1.00; P < .0001). The optimal BSC cut-off value identified patients with NAFLD in the training and validation groups with 93% and 87% sensitivity, 97% and 91% specificity, 86% and 76% negative predictive values, and 99% and 95% positive predictive values, respectively. CONCLUSIONS QUS measurements of BSC can accurately diagnose and quantify hepatic steatosis, based on a cross-sectional analysis that used MRI-PDFF as the reference. With further validation, QUS could be an inexpensive, widely available method to screen the general or at-risk population for NAFLD.

MRE is superior to ARFI for the diagnosis of fibrosis in patients with biopsy‐proven NAFLD: A prospective study

Magnetic resonance elastography (MRE), an advanced magnetic resonance–based imaging technique, and acoustic radiation force impulse (ARFI), an ultrasound‐based imaging technique, are accurate for diagnosing nonalcoholic fatty liver disease (NAFLD) fibrosis. However, no head‐to‐head comparisons between MRE and ARFI for diagnosing NAFLD fibrosis have been performed. We compared MRE versus ARFI head‐to‐head for diagnosing fibrosis in well‐characterized patients with biopsy‐proven NAFLD. This cross‐sectional analysis of a prospective cohort involved 125 patients (54.4% female) who underwent MRE, ARFI, and contemporaneous liver biopsies scored using the Nonalcoholic Steatohepatitis Clinical Research Network histological scoring system. The performances of MRE versus ARFI for diagnosing fibrosis were evaluated using area under the receiver operating characteristic curves (AUROCs). The mean (± standard deviation) age and body mass index were 48.9 (±15.4) years and 31.8 (±7.0) kg/m2, respectively. For diagnosing any fibrosis (≥ stage 1), the MRE AUROC was 0.799 (95% confidence interval [CI] 0.723‐0.875), significantly (P = 0.012) higher than the ARFI AUROC of 0.664 (95% CI 0.568‐0.760). In stratified analysis by presence or absence of obesity, MRE was superior to ARFI for diagnosing any fibrosis in obese patients (P < 0.001) but not in nonobese patients (P = 0.722). The MRE AUROCs for diagnosing ≥stages 2, 3, and 4 fibrosis were 0.885 (95% CI 0.816‐0.953), 0.934 (95% CI 0.863‐1.000), and 0.882 (95% CI 0.729‐1.000); and the ARFI AUROCs were 0.848 (95% CI 0.776‐0.921), 0.896 (95% CI 0.824‐0.968), and 0.862 (95% CI 0.721‐1.000). MRE had higher AUROCs than ARFI for discriminating dichotomized fibrosis stages at all dichotomization cutoff points, but the AUROC differences decreased as the cutoff points (fibrosis stages) increased. Conclusion: MRE is more accurate than ARFI for diagnosing any fibrosis in NAFLD patients, especially those who are obese. (Hepatology 2016;63:453–461)

Association between novel MRI‐estimated pancreatic fat and liver histology‐determined steatosis and fibrosis in non‐alcoholic fatty liver disease

Ectopic fat deposition in the pancreas and its association with hepatic steatosis have not previously been examined in patients with biopsy‐proven non‐alcoholic fatty liver disease (NAFLD).

Accuracy and the effect of possible subject-based confounders of magnitude-based MRI for estimating hepatic proton density fat fraction in adults, using MR spectroscopy as reference.

To determine the accuracy and the effect of possible subject‐based confounders of magnitude‐based magnetic resonance imaging (MRI) for estimating hepatic proton density fat fraction (PDFF) for different numbers of echoes in adults with known or suspected nonalcoholic fatty liver disease, using MR spectroscopy (MRS) as a reference.

A Pilot Comparative Study of Quantitative Ultrasound, Conventional Ultrasound, and MRI for Predicting Histology-Determined Steatosis Grade in Adult Nonalcoholic Fatty Liver Disease

OBJECTIVE The purpose of this study is to explore the diagnostic performance of two investigational quantitative ultrasound (QUS) parameters, attenuation coefficient and backscatter coefficient, in comparison with conventional ultrasound (CUS) and MRI-estimated proton density fat fraction (PDFF) for predicting histology-confirmed steatosis grade in adults with nonalcoholic fatty liver disease (NAFLD). SUBJECTS AND METHODS In this prospectively designed pilot study, 61 adults with histology-confirmed NAFLD were enrolled from September 2012 to February 2014. Subjects underwent QUS, CUS, and MRI examinations within 100 days of clinical-care liver biopsy. QUS parameters (attenuation coefficient and backscatter coefficient) were estimated using a reference phantom technique by two analysts independently. Three-point ordinal CUS scores intended to predict steatosis grade (1, 2, or 3) were generated independently by two radiologists on the basis of QUS features. PDFF was estimated using an advanced chemical shift-based MRI technique. Using histologic examination as the reference standard, ROC analysis was performed. Optimal attenuation coefficient, backscatter coefficient, and PDFF cutoff thresholds were identified, and the accuracy of attenuation coefficient, backscatter coefficient, PDFF, and CUS to predict steatosis grade was determined. Interobserver agreement for attenuation coefficient, backscatter coefficient, and CUS was analyzed. RESULTS CUS had 51.7% grading accuracy. The raw and cross-validated steatosis grading accuracies were 61.7% and 55.0%, respectively, for attenuation coefficient, 68.3% and 68.3% for backscatter coefficient, and 76.7% and 71.3% for MRI-estimated PDFF. Interobserver agreements were 53.3% for CUS (κ = 0.61), 90.0% for attenuation coefficient (κ = 0.87), and 71.7% for backscatter coefficient (κ = 0.82) (p < 0.0001 for all). CONCLUSION Preliminary observations suggest that QUS parameters may be more accurate and provide higher interobserver agreement than CUS for predicting hepatic steatosis grade in patients with NAFLD.

Adaptive local window for level set segmentation of CT and MRI liver lesions

HighlightsWe improve the local level set segmentation by proposing a novel method to estimate the adaptive local window size surrounding each contour point.The local window size is re‐estimated at each point by an iterative process that considers the object scale, local and global texture statistics, and minimization of the cost function, thus generating an adaptive local window.The proposed method estimates the size of the local window directly from the image, not by testing a specific scale from a range of scales and thus requires no pyramid of pre‐defined scales as input, removing any potential sensitivity to user input regarding scale sizes.The results indicate that our proposed method outperforms the state of the art methods in terms of agreement with the manual marking and segmentation robustness to contour initialization or the energy model used. In case of complex lesions, such as low contrast lesions, heterogeneous lesions, or lesions with a noisy background, our method shows significantly better segmentation with an improvement of 0.25 ± 0.13 in Dice similarity coefficient, compared with state of the art fixed‐size local windows (Wilcoxon, p < 0.001). Abstract We propose a novel method, the adaptive local window, for improving level set segmentation technique. The window is estimated separately for each contour point, over iterations of the segmentation process, and for each individual object. Our method considers the object scale, the spatial texture, and the changes of the energy functional over iterations. Global and local statistics are considered by calculating several gray level co‐occurrence matrices. We demonstrate the capabilities of the method in the domain of medical imaging for segmenting 233 images with liver lesions. To illustrate the strength of our method, those lesions were screened by either Computed Tomography or Magnetic Resonance Imaging. Moreover, we analyzed images using three different energy models. We compared our method to a global level set segmentation, to a local framework that uses predefined fixed‐size square windows and to a local region‐scalable fitting model. The results indicate that our proposed method outperforms the other methods in terms of agreement with the manual marking and dependence on contour initialization or the energy model used. In case of complex lesions, such as low contrast lesions, heterogeneous lesions, or lesions with a noisy background, our method shows significantly better segmentation with an improvement of 0.25 ± 0.13 in Dice similarity coefficient, compared with state of the art fixed‐size local windows (Wilcoxon, p < 0.001). Graphical abstract Figure. No Caption available.

Accuracy of multiecho magnitude-based MRI (M-MRI) for estimation of hepatic proton density fat fraction (PDFF) in children

To assess accuracy of magnitude‐based magnetic resonance imaging (M‐MRI) in children to estimate hepatic proton density fat fraction (PDFF) using two to six echoes, with magnetic resonance spectroscopy (MRS) ‐measured PDFF as a reference standard.

Accurate diagnosis of nonalcoholic fatty liver disease in human participants via quantitative ultrasound

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in the United States, affects 30% of adult Americans, may progress to nonalcoholic steatohepatitis (NASH) and end-stage liver disease, and is a risk factor for diabetes and cardiovascular disease. The diagnosis, grading, and staging of NAFLD currently is based on liver biopsy examination with histologic assessment. Noninvasive image-based methods to evaluate the liver in adults with NAFLD are urgently needed. We developed a quantitative ultrasound (QUS) method that in animal studies shows promise for detection and quantification of liver fat content. The current studys contribution is to extend the work to human participants by assessing the accuracy of backscatter coefficient and attenuation coefficient for detection of hepatic steatosis in a cohort of adult participants with NAFLD and non-NAFLD controls. QUS parameters measured using routine clinical US scanners show promise for detecting and perhaps grading NAFLD.

Assessment of treatment response in non‐alcoholic steatohepatitis using advanced magnetic resonance imaging

Magnetic resonance imaging‐derived measures of liver fat and volume are emerging as accurate, non‐invasive imaging biomarkers in non‐alcoholic steatohepatitis (NASH). Little is known about these measures in relation to histology longitudinally.