Effect of disease progression on liver apparent diffusion coefficient and T2 values in a murine model of hepatic fibrosis at 11.7 Tesla MRI

Biejiajian pill inhibits progression of hepatocellular carcinoma by downregulating PDGFRβ signaling in cancer-associated fibroblasts

ETHNOPHARMACOLOGICAL RELEVANCE

Biejiajian pill (BJJP) is a canonical formula that is clinically used to treat chronic liver disease, especially to decrease the incidence of hepatocellular carcinoma (HCC). However, the mechanisms underlying the prevention of HCC progression by BJJP remain unclear.

AIM OF THE STUDY

This study aimed to determine whether BJJP inhibits HCC progression by downregulating platelet-derived growth factor receptor beta (PDGFRβ) signaling in cancer-associated fibroblasts (CAFs) in a mouse model of diethylnitrosamine (DEN)/carbon tetrachloride (CCl₄)-induced HCC.

MATERIALS AND METHODS

C57BL/6 male mice were intraperitoneally injected with DEN 2 weeks after birth, followed by repeated injections of CCl₄ weekly from 6 weeks of age onwards, to recapitulate features of HCC. At week 14, BJJP was orally administered to mice. The effects of BJJP on HCC progression were evaluated using histology, immunohistochemistry, and serum biochemical marker levels. Transcriptome analysis, molecular docking, quantitative real-time PCR, and Western blot were used to study the genes targeted by BJJP and the associated signaling pathway. The effects of BJJP on PDGFRβ signaling in CAFs and the underlying mechanism were demonstrated.

RESULTS

BJJP treatment significantly suppressed carcinogenesis and cancer progression, and it ameliorated liver inflammation in mice with HCC. A total of 176 genes, including PDGFRβ, were significantly downregulated after BJJP treatment and five components of BJJP with high binding affinity to PDGFRβ were identified. BJJP inhibited the phosphorylation of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT), and glycogen synthase kinase 3 beta (GSK3β) by suppressing PDGFRβ expression in CAFs, and it also downregulated the expression of the downstream proteins hepatocyte growth factor (HGF) and vascular endothelial growth factor A (VEGF-A). Furthermore, BJJP-containing serum consistently reduced PDGFRβ, HGF, and VEGF-A expression levels in HSC-derived CAFs in vitro. Importantly, PDGF-BB induced PDGFRβ activation in CAFs and both BJJP and sunitinib (a kinase inhibitor) inhibited PDGF-BB/PDGFRβ signaling.

CONCLUSION

BJJP inhibits the progression of HCC through suppressing VEGF-A and HGF expression in CAFs by downregulating PDGFRβ signaling.

Texture Analysis Based on Vascular Ultrasound to Identify the Vulnerable Carotid Plaques

Vulnerable carotid plaques are closely related to the occurrence of ischemic stroke. Therefore, accurate and rapid identification of the nature of carotid plaques is essential. This study aimed to determine whether texture analysis based on a vascular ultrasound can be applied to identify vulnerable plaques. Data from a total of 150 patients diagnosed with atherosclerotic plaque (AP) by carotid ultrasound (CDU) and high-resolution magnetic resonance imaging (HRMRI) were collected. HRMRI is the in vivo reference to assess the nature of AP. MaZda software was used to delineate the region of interest and extract 303 texture features from ultrasonic images of plaques. Following regression analysis using the least absolute shrinkage and selection operator (LASSO) algorithm, the overall cohort was randomized 7:3 into the training (n = 105) and testing (n = 45) sets. In the training set, the conventional ultrasound model, the texture feature model, and the conventional ultrasound-texture feature combined model were constructed. The testing set was used to validate the model’s effectiveness by calculating the area under the curve (AUC), accuracy, sensitivity, and specificity. Based on the combined model, a nomogram risk prediction model was established, and the consistency index (C-index) and the calibration curve were obtained. In the training and testing sets, the AUC of the prediction performance of the conventional ultrasonic-texture feature combined model was higher than that of the conventional ultrasonic model and the texture feature model. In the training set, the AUC of the combined model was 0.88, while in the testing set, AUC was 0.87. In addition, the C-index results were also favorable (0.89 in the training set and 0.84 in the testing set). Furthermore, the calibration curve was close to the ideal curve, indicating the accuracy of the nomogram. This study proves the performance of vascular ultrasound-based texture analysis in identifying the vulnerable carotid plaques. Texture feature extraction combined with CDU sonogram features can accurately predict the vulnerability of AP.

A Comprehensive Computer-Assisted Diagnosis System for Early Assessment of Renal Cancer Tumors

Renal cell carcinoma (RCC) is the most common and a highly aggressive type of malignant renal tumor. In this manuscript, we aim to identify and integrate the optimal discriminating morphological, textural, and functional features that best describe the malignancy status of a given renal tumor. The integrated discriminating features may lead to the development of a novel comprehensive renal cancer computer-assisted diagnosis (RC-CAD) system with the ability to discriminate between benign and malignant renal tumors and specify the malignancy subtypes for optimal medical management. Informed consent was obtained from a total of 140 biopsy-proven patients to participate in the study (male = 72 and female = 68, age range = 15 to 87 years). There were 70 patients who had RCC (40 clear cell RCC (ccRCC), 30 nonclear cell RCC (nccRCC)), while the other 70 had benign angiomyolipoma tumors. Contrast-enhanced computed tomography (CE-CT) images were acquired, and renal tumors were segmented for all patients to allow the extraction of discriminating imaging features. The RC-CAD system incorporates the following major steps: (i) applying a new parametric spherical harmonic technique to estimate the morphological features, (ii) modeling a novel angular invariant gray-level co-occurrence matrix to estimate the textural features, and (iii) constructing wash-in/wash-out slopes to estimate the functional features by quantifying enhancement variations across different CE-CT phases. These features were subsequently combined and processed using a two-stage multilayer perceptron artificial neural network (MLP-ANN) classifier to classify the renal tumor as benign or malignant and identify the malignancy subtype as well. Using the combined features and a leave-one-subject-out cross-validation approach, the developed RC-CAD system achieved a sensitivity of 95.3%±2.0%, a specificity of 99.9%±0.4%, and Dice similarity coefficient of 0.98±0.01 in differentiating malignant from benign tumors, as well as an overall accuracy of 89.6%±5.0% in discriminating ccRCC from nccRCC. The diagnostic abilities of the developed RC-CAD system were further validated using a randomly stratified 10-fold cross-validation approach. The obtained results using the proposed MLP-ANN classification model outperformed other machine learning classifiers (e.g., support vector machine, random forests, relational functional gradient boosting, etc.). Hence, integrating morphological, textural, and functional features enhances the diagnostic performance, making the proposal a reliable noninvasive diagnostic tool for renal tumors.

A novel computer-aided diagnostic system for accurate detection and grading of liver tumors

Liver cancer is a major cause of morbidity and mortality in the world. The primary goals of this manuscript are the identification of novel imaging markers (morphological, functional, and anatomical/textural), and development of a computer-aided diagnostic (CAD) system to accurately detect and grade liver tumors non-invasively. A total of 95 patients with liver tumors (M = 65, F = 30, age range = 34–82 years) were enrolled in the study after consents were obtained. 38 patients had benign tumors (LR1 = 19 and LR2 = 19), 19 patients had intermediate tumors (LR3), and 38 patients had hepatocellular carcinoma (HCC) malignant tumors (LR4 = 19 and LR5 = 19). A multi-phase contrast-enhanced magnetic resonance imaging (CE-MRI) was collected to extract the imaging markers. A comprehensive CAD system was developed, which includes the following main steps: i) estimation of morphological markers using a new parametric spherical harmonic model, ii) estimation of textural markers using a novel rotation invariant gray-level co-occurrence matrix (GLCM) and gray-level run-length matrix (GLRLM) models, and iii) calculation of the functional markers by estimating the wash-in/wash-out slopes, which enable quantification of the enhancement characteristics across different CE-MR phases. These markers were subsequently processed using a two-stages random forest-based classifier to classify the liver tumor as benign, intermediate, or malignant and determine the corresponding grade (LR1, LR2, LR3, LR4, or LR5). The overall CAD system using all the identified imaging markers achieved a sensitivity of 91.8%±0.9%, specificity of 91.2%±1.9%, and F\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{1}$$\end{document}1 score of 0.91±0.01, using the leave-one-subject-out (LOSO) cross-validation approach. Importantly, the CAD system achieved overall accuracies of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$88\%\pm 5\%$$\end{document}88%±5%, 85%±2%, 78%±3%, 83%±4%, and 79%±3% in grading liver tumors into LR1, LR2, LR3, LR4, and LR5, respectively. In addition to LOSO, the developed CAD system was tested using randomly stratified 10-fold and 5-fold cross-validation approaches. Alternative classification algorithms, including support vector machine, naive Bayes classifier, k-nearest neighbors, and linear discriminant analysis all produced inferior results compared to the proposed two stage random forest classification model. These experiments demonstrate the feasibility of the proposed CAD system as a novel tool to objectively assess liver tumors based on the new comprehensive imaging markers. The identified imaging markers and CAD system can be used as a non-invasive diagnostic tool for early and accurate detection and grading of liver cancer.

T2 Values for Diagnosing Acute-on-Chronic Liver Failure in Hepatitis B Patients

OBJECTIVES

The aim of this study was to investigate the value of hepatic T2 imaging for the evaluation of chronic hepatitis-B-related acute-on-chronic liver failure (HBV-ACLF).

METHODS

Three groups of patients underwent liver MRI utilising m-GRASE sequence (multi-echo gradient and spin echo): HBV-ACLF patients (n = 28), chronic hepatitis B patients (n = 11), and healthy control patients (n = 14). A T₂ image was produced using post-processing software, and the mean T₂ (relaxation time) value was calculated. Blood biochemical indices for the HBV-ACLF and Chronic Hepatitis B were obtained within 2 days pre- or post-MR scanning. The patients' T₂ values, and the correlation between their biochemical indices and T₂ values were analysed. A receiver operating characteristic curve was employed to evaluate the efficiency of utilising T₂ values in the diagnosis of HBV-ACLF.

RESULTS

There were significant variations in the T₂ values (χ² = 19.074, P < 0.001) among the 3 groups. The AUC of T₂ values for diagnosing HBV-ACLF was 0.86 (P < 0.001), with a cut-off value of 57.73 ms. A moderately positive correlation was observed between the T2 value and the international normalised ratio, prothrombin time, and hyaluronic acid values (r_s = 0.65, P < 0.001; r_s = 0.67, P < 0.001; r_s = 0.39, P = 0.025). A moderately negative correlation was observed between the T₂ value and the prothrombin activity, albumin, and prealbumin values (r_s = -0.67, P < 0.001; r_s = -0.48, P = 0.004; r_s = -0.37, P = 0.030).

CONCLUSION

T₂ values could accurately reflect liver function state, as they correlated well with certain biochemical indices, illustrating good diagnostic efficiency for diagnosing HBV-ACLF.

Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation

PURPOSE

To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B.

METHODS

Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades.

RESULTS

The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen's d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047.

CONCLUSION

D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis.

Short-term changes observed in multiparametric liver MRI following therapy with direct-acting antivirals in chronic hepatitis C virus patients

Methods

We applied multiparametric MRI to assess changes in liver composition, perfusion and blood flow in 17 patients before direct-acting antiviral (DAA) therapy and after treatment completion (within 12 weeks of last DAA tablet swallowed).

Results

We observed changes in hepatic composition indicated by a reduction in both liver longitudinal relaxation time (T1, 35 ± 4 ms), transverse relaxation time (T2, 2.5 ± 0.8 ms; T2* 3.0 ± 0.7 ms), and liver perfusion (28.1 ± 19.7 ml/100 g/min) which we suggest are linked to reduced pro-inflammatory milieu, including interstitial oedema, within the liver. No changes were observed in liver or spleen blood flow, splenic perfusion, or superior mesenteric artery blood flow.

Conclusion

For the first time, our study has shown that treatment of HCV with DAAs in patients with cirrhosis leads to an acute reduction in liver T1, T2 and T2* and an increase in liver perfusion measured using MR parameters. The ability of MRI to characterise changes in the angio-architecture of patients with cirrhosis after intervention in the short term will enhance our understanding of the natural history of regression of liver disease and potentially influence clinical decision algorithms.

Key Points

• DAAs have revolutionised the treatment of hepatitis C and achieve sustained virological response in over 95% of patients, even with liver cirrhosis.

• Currently available non-invasive measures of liver fibrosis are not accurate after HCV treatment with DAAs, this prospective single-centre study has shown that MRI can sensitively measure changes within the liver, which could reflect the reduction in inflammation with viral clearance.

• The ability of MRI to characterise changes in structural and haemodynamic MRI measures in the liver after intervention will enhance our understanding of the progression/regression of liver disease and could potentially influence clinical decision algorithms.

Progress in non-invasive detection of liver fibrosis

Liver fibrosis is an important pathological precondition for hepatocellular carcinoma. The degree of hepatic fibrosis is positively correlated with liver cancer. Liver fibrosis is a series of pathological and physiological process related to liver cell necrosis and degeneration after chronic liver injury, which finally leads to extracellular matrix and collagen deposition. The early detection and precise staging of fibrosis and cirrhosis are very important for early diagnosis and timely initiation of appropriate therapeutic regimens. The risk of severe liver fibrosis finally progressing to liver carcinoma is >50%. It is known that biopsy is the gold standard for the diagnosis and staging of liver fibrosis. However, this method has some limitations, such as the potential for pain, sampling variability, and low patient acceptance. Furthermore, the necessity of obtaining a tissue diagnosis of liver fibrosis still remains controversial. An increasing number of reliable non-invasive approaches are now available that are widely applied in clinical practice, mostly in cases of viral hepatitis, resulting in a significantly decreased need for liver biopsy. In fact, the non-invasive detection and evaluation of liver cirrhosis now has good accuracy due to current serum markers, ultrasound imaging, and magnetic resonance imaging quantification techniques. A prominent advantage of the non-invasive detection and assessment of liver fibrosis is that liver fibrosis can be monitored repeatedly and easily in the same patient. Serum biomarkers have the advantages of high applicability (>95%) and good reproducibility. However, their results can be influenced by different patient conditions because none of these markers are liver-specific. The most promising techniques appear to be transient elastography and magnetic resonance elastography because they provide reliable results for the detection of fibrosis in the advanced stages, and future developments promise to increase the reliability and accuracy of the staging of hepatic fibrosis. This article aims to describe the recent progress in the development of non-invasive assessment methods for the staging of liver fibrosis, with a special emphasize on computer-aided quantitative and deep learning methods.

Texture analysis as a radiomic marker for differentiating renal tumors

PURPOSE

To evaluate the utility of texture analysis for the differentiation of renal tumors, including the various renal cell carcinoma subtypes and oncocytoma.

MATERIALS AND METHODS

Following IRB approval, a retrospective analysis was performed, including all patients with pathology-proven renal tumors and an abdominal computed tomography (CT) examination. CT images of the tumors were manually segmented, and texture analysis of the segmented tumors was performed. A support vector machine (SVM) method was also applied to classify tumor types. Texture analysis results were compared to the various tumors and areas under the curve (AUC) were calculated. Similar calculations were performed with the SVM data.

RESULTS

One hundred nineteen patients were included. Excellent discriminators of tumors were identified among the histogram-based features noting features skewness and kurtosis, which demonstrated AUCs of 0.91 and 0.93 (p < 0.0001), respectively, for differentiating clear cell subtype from oncocytoma. Histogram feature median demonstrated an AUC of 0.99 (p < 0.0001) for differentiating papillary subtype from oncocytoma and an AUC of 0.92 for differentiating oncocytoma from other tumors. Machine learning further improved the results achieving very good to excellent discrimination of tumor subtypes. The ability of machine learning to distinguish clear cell subtype from other tumors and papillary subtype from other tumors was excellent with AUCs of 0.91 and 0.92, respectively.

CONCLUSION

Texture analysis is a promising non-invasive tool for distinguishing renal tumors on CT images. These results were further improved upon application of machine learning, and support the further development of texture analysis as a quantitative biomarker for distinguishing various renal tumors.

Enhanced Laws textures: A potential MRI surrogate marker of hepatic fibrosis in a murine model

PURPOSE

To compare enhanced Laws textures derived from parametric proton density (PD) maps to other MRI surrogate markers (T₂, PD, apparent diffusion coefficient (ADC)) in assessing degrees of liver fibrosis in an ex vivo murine model of hepatic fibrosis imaged using 11.7T MRI.

METHODS

This animal study was IACUC approved. Fourteen male, C57BL/6 mice were divided into control and experimental groups. The latter were fed a 3,5-dicarbethoxy-1,4-dihydrocollidine (DDC) supplemented diet to induce hepatic fibrosis. Ex vivo liver specimens were imaged using an 11.7T scanner, from which the parametric PD, T₂, and ADC maps were generated from spin-echo pulsed field gradient and multi-echo spin-echo acquisitions. A sequential enhanced Laws texture analysis was applied to the PD maps: automated dual-clustering algorithm, optimal thresholding algorithm, global grayscale correction, and Laws texture features extraction. Degrees of fibrosis were independently assessed by digital image analysis (a.k.a. %Area Fibrosis). Scatterplot graphs comparing enhanced Laws texture features, T₂, PD, and ADC values to degrees of fibrosis were generated and correlation coefficients were calculated.

RESULTS

Hepatic fibrosis and the enhanced Laws texture features were strongly correlated with higher %Area Fibrosis associated with higher Laws textures (r=0.89). Without the proposed enhancements, only a moderate correlation was detected between %Area Fibrosis and unenhanced Laws texture features (r=0.70). Correlation also existed between %Area Fibrosis and ADC (r=0.86), PD (r=0.65), and T₂ (r=0.66).

CONCLUSIONS

Higher degrees of hepatic fibrosis are associated with increased Laws textures. The proposed enhancements could improve the accuracy of Laws texture features significantly.

Using texture analyses of contrast enhanced CT to assess hepatic fibrosis

PURPOSE

To determine the ability of texture analyses of contrast-enhanced CT images for distinguishing between varying degrees of hepatic fibrosis in patients with chronic liver disease using histopathology as the reference standard.

MATERIALS AND METHODS

Following IRB approval, 83 patients who underwent contrast enhanced 64-MDCT of the abdomen and pelvis in the portal venous phase between 12/2005 and 01/2013 and who had a liver biopsy within 6 months of the CT were included. An in-house developed, MATLAB-based texture analysis program was employed to extract 41 texture features from each of 5 axial segmented volumes of liver. Using the Ishak fibrosis staging scale, histopathologic grades of hepatic fibrosis were correlated with texture parameters after stratifying patients into three analysis groups, comparing Ishak scales 0-2 with 3-6, 0-3 with 4-6, and 0-4 with 5-6. To assess the utility of texture features, receiver operating characteristic (ROC) curves were constructed and the area under the curve (AUC) was used to determine the performance of each feature in distinguishing between normal/low and higher grades of hepatic fibrosis.

RESULTS

A total of 19 different texture features with 7 histogram features, one grey level co-occurrence matrix, 6 gray level run length, 1 Laws feature, and 4 gray level gradient matrix demonstrated statistically significant differences for discriminating between fibrosis groupings. The highest AUC values fell in the range of fair performance for distinguishing between different fibrosis groupings.

CONCLUSION

These findings suggest that texture-based analyses of contrast-enhanced CT images offer a potential avenue toward the non-invasive assessment of liver fibrosis.

In Vivo MRI Assessment of Hepatic and Splenic Disease in a Murine Model of Schistosomiasis [corrected]

BACKGROUND

Schistosomiasis (or bilharzia), a major parasitic disease, affects more than 260 million people worldwide. In chronic cases of intestinal schistosomiasis caused by trematodes of the Schistosoma genus, hepatic fibrosis develops as a host immune response to the helminth eggs, followed by potentially lethal portal hypertension. In this study, we characterized hepatic and splenic features of a murine model of intestinal schistosomiasis using in vivo magnetic resonance imaging (MRI) and evaluated the transverse relaxation time T2 as a non-invasive imaging biomarker for monitoring hepatic fibrogenesis.

METHODOLOGY/PRINCIPAL FINDINGS

CBA/J mice were imaged at 11.75 T two, six and ten weeks after percutaneous infection with Schistosoma mansoni. In vivo imaging studies were completed with histology at the last two time points. Anatomical MRI allowed detection of typical manifestations of the intestinal disease such as significant hepato- and splenomegaly, and dilation of the portal vein as early as six weeks, with further aggravation at 10 weeks after infection. Liver multifocal lesions observed by MRI in infected animals at 10 weeks post infection corresponded to granulomatous inflammation and intergranulomatous fibrosis with METAVIR scores up to A2F2. While most healthy hepatic tissue showed T2 values below 14 ms, these lesions were characterized by a T2 greater than 16 ms. The area fraction of increased T2 correlated (rS = 0.83) with the area fraction of Sirius Red stained collagen in histological sections. A continuous liver T2* decrease was also measured while brown pigments in macrophages were detected at histology. These findings suggest accumulation of hematin in infected livers.

CONCLUSIONS/SIGNIFICANCE

Our multiparametric MRI approach confirms that this murine model replicates hepatic and splenic manifestations of human intestinal schistosomiasis. Quantitative T2 mapping proved sensitive to assess liver fibrogenesis non-invasively and may therefore constitute an objective imaging biomarker for treatment monitoring in diseases involving hepatic fibrosis.

Age-related T2 changes in hindlimb muscles of mdx mice

INTRODUCTION

Magnetic resonance imaging (MRI) was used to monitor changes in the transverse relaxation time constant (T2) in lower hindlimb muscles of mdx mice at different ages.

METHODS

Young (5 weeks), adult (44 weeks), and old mdx (96 weeks), and age-matched control mice were studied. Young mdx mice were imaged longitudinally, whereas adult and old mdx mice were imaged at a single time-point.

RESULTS

Mean muscle T2 and percent of pixels with elevated T2 were significantly different between mdx and control mice at all ages. In young mdx mice, mean muscle T2 peaked at 7-8 weeks and declined at 9-11 weeks. In old mdx mice, mean muscle T2 was decreased compared with young and adult mice, which could be attributed to fibrosis.

CONCLUSIONS

MRI captured longitudinal changes in skeletal muscle integrity of mdx mice. This information will be valuable for pre-clinical testing of potential therapeutic interventions for muscular dystrophy.

Using Texture Analysis to Determine Human Papillomavirus Status of Oropharyngeal Squamous Cell Carcinomas on CT

BACKGROUND AND PURPOSE

Human papillomavirus-associated oropharyngeal squamous cell carcinoma is increasing in prevalence and typically occurs in younger patients than human papillomavirus-negative squamous cell carcinoma. While imaging features of human papillomavirus-positive versus human papillomavirus-negative squamous cell carcinoma nodal metastases have been described, characteristics distinguishing human papillomavirus-positive from human papillomavirus-negative primary squamous cell carcinomas have not been well established. The purpose of this project was to evaluate the use of texture features to distinguish human papillomavirus-positive and human papillomavirus-negative primary oropharyngeal squamous cell carcinoma.

MATERIALS AND METHODS

Following institutional review board approval, 40 patients with primary oropharyngeal squamous cell carcinoma and known human papillomavirus status who underwent contrast-enhanced CT between December 2009 and October 2013 were included in this study. Segmentation of the primary lesion was manually performed with a semiautomated graphical-user interface. Following segmentation, an in-house-developed texture analysis program extracted 42 texture features from each segmented volume. A t test was used to evaluate differences in texture parameters between human papillomavirus-positive and human papillomavirus-negative squamous cell carcinomas.

RESULTS

Of the 40 included patients, 29 had human papillomavirus-positive oropharyngeal squamous cell carcinoma and 11 had human papillomavirus-negative oropharyngeal squamous cell carcinoma. Significant differences were seen in the histogram parameters median (P = .006) and entropy (P = .016) and squamous cell carcinoma entropy (P = .043).

CONCLUSIONS

There are statistically significant differences in some texture features between human papillomavirus-positive and human papillomavirus-negative oropharyngeal tumors. Texture analysis may be considered an adjunct to the evaluation of human papillomavirus status and characterization of squamous cell carcinoma.

IVIM Diffusion-weighted Imaging of the Liver at 3.0T: Comparison with 1.5T

Purpose

To compare intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) of the liver between 1.5 T and 3.0 T in terms of parameter quantification and inter-platform reproducibility.

Materials and methods

In this IRB approved prospective study, 19 subjects (17 patients with chronic liver disease and 2 healthy volunteers) underwent two repeat scans at 1.5 T and 3.0 T. Each scan included IVIM DWI using 16 b values from 0 to 800 s/mm². A single observer measured IVIM parameters for each platform and estimated signal to noise ratio (eSNR) at b0, 200, 400 and 800 s/mm². Wilcoxon paired tests were used to compare liver eSNR and IVIM parameters. Inter-platform reproducibility was assessed by calculating within-subject coefficient of variation (CV) and Bland–Altman limits of agreement. An ice water phantom was used to test ADC variability between the two MRI systems.

Results

The mean invitro difference in ADC between the two platforms was 6.8%. eSNR was significantly higher at 3.0T for all selected b values (p = 0.006–0.020), except for b0 (p = 0.239). Liver IVIM parameters were significantly different between 1.5 T and 3.0 T (p = 0.005–0.044), except for ADC (p = 0.748). The inter-platform reproducibility of true diffusion coefficient (D) and ADC were good, with mean CV of 10.9% and 11.1%, respectively. Perfusion fraction (PF) and pseudodiffusion coefficient (D*) showed more limited inter-platform reproducibility (mean CV of 22.6% for PF and 46.9% for D*).

Conclusion

Liver D and ADC values showed good reproducibility between 1.5 T and 3.0 T platforms; while there was more variability in PF, and large variability in D* parameters between the two platforms. These findings may have implications for drug trials assessing the role of IVIM DWI in tumor response and liver fibrosis.

Assessment of diffusion tensor MR imaging (DTI) in liver fibrosis with minimal confounding effect of hepatic steatosis

PURPOSE

Given the potential confounding effect of fat on apparent diffusion coefficient (ADC) in the liver, we have assessed diffusion tensor imaging in liver fibrosis with minimal effect of fat on ADC and fractional anisotropy (FA).

METHODS

Thirty-six mice were used, among which 20 mice were CCl4 treated for fibrosis induction. Diffusion tensor imaging was performed at 9.4T using a spin-echo diffusion tensor imaging sequence with six gradient directions. Hepatic fat fraction obtained by MR spectroscopy was used as hepatic fat content. Fibrosis scores were obtained from histopathology.

RESULTS

The hepatic fat fractions of the two animal groups were below 5.5% and not different (5.3 ± 1.5 vs. 4.6 ± 1.1%; P = 0.115). Fibrosis scores were higher in CCl4 -treated mice (0.0 ± 0.0 vs. 2.1 ± 0.7; P < 0.001). Nonetheless, there was no difference in ADC between the two groups (0.711 ± 0.068 × 10(-3) vs. 0.718 ± 0.095 × 10(-3) mm(2) s(-1) ; P = 0.911). The treated group had a lower FA than control (0.552 ± 0.050 vs. 0.586 ± 0.013; P = 0.023). ADC was not correlated with hepatic fat fraction and fibrosis. FA was correlated with hepatic fat fraction (r = 0.418, P = 0.011) and fibrosis (r = -0.411, P = 0.012).

CONCLUSION

FA may be more sensitive to mild-to-moderate liver fibrosis than ADC. In addition to ADC, FA may also be sensitive to hepatic fat content, and therefore need careful interpretation in liver fibrosis with concomitant fatty liver.

Characterizing non-gaussian, high b-value diffusion in liver fibrosis: Stretched exponential and diffusional kurtosis modeling

PURPOSE

To employ the stretched exponential and diffusional kurtosis models to study the non-Gaussian behavior of diffusion-related signal decay of the liver in an animal model of hepatic fibrosis.

MATERIALS AND METHODS

High b-value diffusion imaging data (up to 3500 s/mm(2) ) of ex vivo murine liver specimens was acquired using a 9.4 T MRI scanner. A simple monoexponential model as well as the stretched exponential and diffusional kurtosis models were employed to analyze the diffusion data, the results of which were correlated with liver histopathology.

RESULTS

Strong correlations between histopathological assessments of hepatic fibrosis and parameters derived from the stretched exponential and diffusional kurtosis models were found. Using Akaike's Information Criterion (AIC) analyses, the kurtosis model was found to result in an improved fit of the high b-value diffusion data when compared to both the monoexponential and stretched exponential models.

CONCLUSION

The use of diffusional kurtosis or stretched exponential models, applied to the characterization of the non-Gaussian behavior of the molecular diffusion of liver exhibited over an extended b-factor range, affords the potential for an increased capability of magnetic resonance imaging (MRI) in the characterization of chronic liver disease.

Multiexponential T(2) analyses in a murine model of hepatic fibrosis at 11.7 T MRI

This study evaluated the effects of hepatic fibrosis on the multiexponential T(2) (MET(2) ) relaxation of ex vivo murine liver specimens using an 11.7 T MRI. This animal study was approved by the Institutional Animal Care and Use Committee. Eighteen male C57BL/6 mice were divided into control (n = 3) and experimental (n = 15) groups; the latter group was fed a 3,5-dicarbethoxy-1,4-dihydrocollidine-supplemented diet to induce hepatic fibrosis. Ex vivo liver specimens were imaged using an 11.7 T MRI scanner. A multi-echo spin-echo sequence was utilized for subsequent MET(2) analysis. Degrees of fibrosis were determined by a pathologist, as well as by digital image analysis. Scatterplot graphs comparing various features of the MET(2) signal decay with the degrees of fibrosis were generated, and correlation coefficients were calculated. Two distinct peaks of the MET(2) signal decay were identified in all liver specimens: a short T(2) component with a geometric mean T(2) (GMT(2) ) approximating 30 ms; and a long T(2) component with GMT(2) approximating 400 ms. Strong correlation was found between the degree of hepatic fibrosis and the amplitude of the short T(2) component, with a higher degrees of fibrosis associated with a lower amplitude. Moderate correlation was also found between hepatic fibrosis and the GMT(2) values of the long T(2) component, with higher degrees of fibrosis associated with lower GMT(2) values. The study of hepatic microenvironments using MET(2) analyses offers potential utility in the ongoing development of the noninvasive assessment of hepatic fibrosis using MRI.

Diagnostic performance of conventional diffusion weighted imaging and diffusion tensor imaging for the liver fibrosis and inflammation

OBJECTIVE

To evaluate the diagnostic accuracy of liver apparent diffusion coefficient (ADC) measured with conventional diffusion-weighted imaging (CDI) and diffusion tensor imaging (DTI) for the diagnosis of liver fibrosis and inflammation.

MATERIALS AND METHODS

Thirty-seven patients with histologic diagnosis of chronic viral hepatitis and 34 healthy volunteers were included in this prospective study. All patients and healthy volunteers were examined by 3T MRI. CDI and DTI were performed using a breath-hold single-shot echo-planar spin echo sequence with b factors of 0 and 1000 s/mm(2). ADCs were obtained with CDI and DTI. Histopathologically, fibrosis of the liver parenchyma was classified with the use of a 5-point scale (0-4) and inflammation was classified with use of a 4-point scale (0-3) in accordance with the METAVIR score. Quantitatively, signal intensity and the ADCs of the liver parenchyma were compared between patients stratified by fibrosis stage and inflammation grade.

RESULTS

With a b factor of 1000 s/mm(2), the signal intensity of the cirrhotic livers was significantly higher than those of the normal volunteers. In addition, ADCs reconstructed from CDI and DTI of the patients were significantly lower than those of the normal volunteers. Liver ADC values inversely correlated with fibrosis and inflammation but there was only statistically significant for inflammatory grading. CDI performed better than DTI for the diagnosis of fibrosis and inflammation.

CONCLUSION

ADC values measured with CDI and DTI may help in the detection of liver fibrosis. They may also give contributory to the inflammatory grading, particularly in distinguishing high from low grade.

Quantifying hepatic fibrosis using a biexponential model of diffusion weighted imaging in ex vivo liver specimens

The purpose of this study was to evaluate the non-Gaussian behavior of diffusion related signal decay of the ex vivo murine liver tissues from a dietary model of hepatic fibrosis. To this end, a biexponential formalism was used to model high b-value diffusion imaging (up to 3500 s/mm(2)), the findings of which were correlated with liver histopathology and compared to a simple monoexponential model. The presence of a major, fast diffusing component and a minor, slow diffusing component was demonstrated. With increasing hepatic fibrosis, the fractional contribution of the fast diffusing component decreased, as did the diffusion coefficient of the fast diffusing component. Strong correlation between the degrees of liver fibrosis and a two-predictor regression model incorporating parameters of the biexponential model was found. Using Akaike's Information Criterion analyses, the biexponential model resulted in an improved fit of the high b-value diffusion data when compared to the monoexponential model.

Intravoxel incoherent motion diffusion-weighted imaging in nonalcoholic fatty liver disease: a 3.0-T MR study

PURPOSE

To compare pure molecular diffusion, D, perfusion-related diffusion, D*, and perfusion fraction, f, determined from diffusion-weighted (DW) magnetic resonance (MR) imaging on the basis of the intravoxel incoherent motion (IVIM) theory in patients with type 2 diabetes with and without liver steatosis.

MATERIALS AND METHODS

This prospective study was approved by the appropriate ethics committee, and written informed consent was obtained from all patients. Between December 2009 and September 2011, 108 patients with type 2 diabetes (51 men, 57 women; mean age, 50 years) underwent 3.0-T single-voxel point-resolved proton MR spectroscopy of the liver (segment VII) to calculate the liver fat fraction from water (4.76 ppm) and methylene (1.33 ppm) peaks, corrected for T1 and T2 decay. Steatosis was defined as a liver fat fraction of at least 5.56%. DW imaging was performed by using a single-shot echo-planar sequence with 11 b values (0, 5, 15, 25, 35, 50, 100, 200, 400, 600, 800 sec/mm2). Liver D, D*, and f were measured and compared in patients with and patients without steatosis (Mann-Whitney test).

RESULTS

The mean liver fat fraction was 7.8% (standard deviation, 9%; range, 0.99%-45%). Forty patients had liver steatosis. D was significantly lower in steatotic compared with nonsteatotic livers (mean, 1.03×10(-3) mm2/sec±0.23 [standard deviation] vs 1.24×10(-3) mm2/sec±0.15, respectively; P<.0001), as was D* (mean, 72.2×10(-3) mm2/sec±61.4 vs 110.6×10(-3) mm2/sec±79; P=.0025). However, f was significantly higher in steatotic compared with nonsteatotic livers (mean, 33.8%±9.4 vs 26.9%±8.8; P=.0003).

CONCLUSION

D is significantly decreased in steatosis. The reduction in D* reflects decreased liver parenchymal perfusion in steatosis. Therefore, steatosis can affect diffusion parameters obtained with IVIM.