Whole-Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis

Advanced Magnetic Resonance Imaging for Detection of Liver Fibrosis and Inflammation in Autoimmune Hepatitis: A State-of-the-Art Review

Autoimmune hepatitis is a rare chronic liver disease, associated with a high level of morbidity and high mortality; approximately 40% of patients with severe untreated disease die within 6 months of diagnosis. It should be treated to achieve complete biochemical and histologic resolution of the disease using corticosteroids and immunosuppression to prevent further progression to cirrhosis. The use of invasive liver biopsy is recommended for the staging and assessment of inflammation and fibrosis for treatment decision-making in the face of an unsatisfactory response or clinical remission, including being a determinant for withdrawal of immunosuppression. On the other hand, liver biopsy is invasive, costly, and not free of complications. It also has potential sampling error and poor interobserver agreement. The limitations of liver biopsy highlight the importance of developing new imaging biomarkers that allow accurate and non-invasive assessment of autoimmune hepatitis in terms of liver inflammation and fibrosis, developing the virtual biopsy concept. Therefore, we review the state-of-the-art of Magnetic Resonance Imaging sequences for the noninvasive evaluation of autoimmune hepatitis, including historical advances and future directions.

The volumetric ADC histogram analysis in differentiating stage IA endometrial carcinoma from endometrial polyp

OBJECTIVE

This study aimed to explore the value of apparent diffusion coefficient (ADC) histogram based on whole lesion volume in distinguishing stage IA endometrial carcinoma from the endometrial polyp.

METHODS

MRI of 108 patients with endometrial lesions confirmed by pathology were retrospectively analysed, including 65 cases of stage IA endometrial carcinoma and 43 cases of endometrial polyp. The volumetric ADC histogram metrics and general imaging features were evaluated and measured simultaneously. All the features were compared between the 2 groups. The receiver operating characteristic curve was utilized to evaluate the diagnostic performance.

RESULTS

The mean, max, min, and percentiles (10th, 25th, 50th, 75th, 95th) ADC values of endometrial carcinoma were significantly lower than that of polyp (all P < .05). The skewness and kurtosis of ADC values in the endometrial carcinoma group were significantly higher than those in the endometrial polyp group, and the variance of ADC values in the endometrial carcinoma group was lower than those in the endometrial polyp group (all P < .05). Endometrial carcinoma demonstrated more obvious myometrial invasion combined with intralesion haemorrhage than polyp (all P < .05). The 25th percentile of ADC values achieved the largest areas under the curve (0.861) among all the ADC histogram metrics and general imaging features, and the sensitivity and specificity were 83.08% and 76.74%, with the cut-off value of 1.01 × 10-3 mm2/s.

CONCLUSION

The volumetric ADC histogram analysis was an effective method in differentiating endometrial carcinoma from an endometrial polyp. The 25th percentile of ADC values has satisfactory performance for detecting malignancy in the endometrium.

ADVANCES IN KNOWLEDGE

The ADC histogram metric based on whole lesion is a promising imaging-maker in differentiating endometrial benign and malignant lesions.

Magnetic susceptibility and R2*-based texture analysis for evaluating liver fibrosis in chronic liver disease

PURPOSE

To explore potential feasibility of texture features in magnetic susceptibility and R2* maps for evaluating liver fibrosis.

METHODS

Thirty-one patients (median age 46 years; 22 male) with chronic liver disease were prospectively recruited and underwent magnetic resonance imaging (MRI), blood tests, and liver biopsy. Susceptibility and R2* maps were obtained using a 3-dimensional volumetric interpolated breath-hold examination sequence with a 3T MRI scanner. Texture features, including histogram, gray-level co-occurrence matrix (GLCM), gray-level dependence matrix (GLDM), gray-level run length matrix (GLRLM), gray-level size zone matrix (GLSZM), and neighboring gray tone difference matrix (NGTDM) features, were extracted. Texture features and blood test results of non-significant (Ishak-F < 3) and significant fibrosis patients (Ishak-F ≥ 3) were compared, and correlations with Ishak-F stages were analyzed. Areas under the curve (AUCs) were calculated to determine the efficacy for evaluating liver fibrosis.

RESULTS

Nine texture features of susceptibility maps and 19 features of R2* maps were significantly different between non-significant and significant fibrosis groups (all P < 0.05). Large dependence high gray-level emphasis (LDHGLE) of GLDM and long run high gray-level emphasis (LRHGLE) of GLRLM in R2* maps showed significantly negative and good correlations with Ishak-F stages (r = -0.616, P < 0.001; r = -0.637, P < 0.001). Busyness (NGTDM) in susceptibility maps, LDHGLE of GLDM and LRHGLE of GLRLM in R2* maps yield the highest AUCs (AUC = 0.786, P = 0.007; AUC = 0.807, P = 0.004; AUC = 0.819, P = 0.003).

CONCLUSION

Texture characteristics of susceptibility and R2* maps revealed possible staging values for liver fibrosis. Susceptibility and R2*-based texture analysis may be a useful and noninvasive method for staging liver fibrosis.

Prospective Evaluation of Virtual MR Elastography With Diffusion-Weighted Imaging in Subjects With Nonalcoholic Fatty Liver Disease

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is increasingly common worldwide and can lead to the development of cirrhosis, liver failure and cancer. Virtual magnetic resonance elastography (VMRE), which is based on a shifted apparent diffusion coefficient (sADC), is a potential noninvasive method to assess liver fibrosis without the specialized hardware and expertise required to implement traditional MR elastography (MRE). Although hepatic steatosis is known to confound ADC measurements, previous studies using VMRE have not corrected for hepatic fat fraction.

PURPOSE

To compare VMRE, corrected for the confounding effects of unsuppressed fat signal, to MRE and biopsy in subjects with suspected NAFLD.

STUDY TYPE

Prospective, cross-sectional.

POPULATION

A total of 49 adult subjects with suspected NAFLD (18 male; median age 55 years, range 33-74 years) who underwent liver biopsy.

FIELD STRENGTH/SEQUENCE

3T, diffusion-weighted spin echo planar, chemical-shift encoded (IDEAL IQ) and MRE sequences.

ASSESSMENT

Two observers drew regions of interest on sADC, proton density fat fraction and MRE-derived stiffness maps. Fat-corrected sADC values were used to calculate the diffusion-based shear modulus according to the VMRE method. Predicted fibrosis stage for MRE and VMRE was determined using previously published cut-off values.

STATISTICAL TESTS

The relationship between VMRE and MRE was assessed with least-squares linear regression (coefficient of determination, R² ). Agreement between MRE and VMRE-predicted fibrosis stage was evaluated with a kappa coefficient and accuracy compared using McNemar's test. A one-way ANOVA determined if the fat-corrected sADC (VMRE) and MRE differed by fibrosis stage. A P value < 0.05 was considered statistically significant.

RESULTS

Least squares regression of VMRE vs. MRE revealed R²  = 0.046 and a slope that was not significantly different from zero (P = 0.14). There was no agreement between MRE and VMRE-predicted fibrosis stage (kappa = -0.01). The proportion of correctly predicted fibrosis stage was significantly higher for MRE compared to VMRE. MRE was significantly associated with fibrosis stage, but fat-corrected sADC was not (P = 0.24).

DATA CONCLUSION

Fat-corrected VMRE was not associated with fibrosis stage in NAFLD. Further investigation is required if VMRE is to be considered in subjects with NAFLD.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Diagnostic accuracy of apparent diffusion coefficient values combined with γ-glutamyl transpeptidase-to-platelet ratio parameters for predicting hepatitis B-related fibrosis

OBJECTIVES

The accuracy of non-invasive liver fibrosis diagnosis based on the apparent diffusion coefficient (ADC) value combined with the γ-glutamyl transpeptidase-to-platelet ratio (GPR) model to predict the stage of hepatitis B-related fibrosis has not been reported. This study aimed to evaluate the diagnostic efficacy of ADC value combined with GPR for liver fibrosis grading.

METHODS

The data of 180 patients with chronic hepatitis B (CHB) diagnosed by liver biopsy were analyzed. The ADC value, GPR, and their combination were assessed in different cirrhosis stages using receiver operating characteristic curve analysis to evaluate their value in diagnosing liver fibrosis.

RESULTS

We observed that liver fibrosis stages were inversely associated with ADC values (r=-0.691, P<0.001), and positively associated with GPR (r=0.502, P<0.001). The area under the curve for diagnostic efficacy of ADC values, GPR, and their combination for F≥2 liver fibrosis was 0.831, 0.749, and 0.858, respectively, and for F≥3 was 0.872, 0.771, and 0.903, respectively. The diagnostic cutoffs of the combination for each stage were -7.07, -12.21 and -37.75, respectively.

CONCLUSIONS

The combined diagnostic tool of ADC and GPR may improve the accuracy of hepatitis B-related liver fibrosis diagnosis, especially for F≥3.

Alterations to cognitive abilities and functional networks in rats post broad-band intense noise exposure

This study aimed to investigate the alterations of cognition and functional connectivity post noise, and find the progress and neural substrates of noise induced hearing loss (NIHL)-associated cognitive impairment. We exposed rats to 122 dB broad-band noise for 2 h to induce hearing loss and the auditory function was assessed by measuring auditory brainstem response thresholds. Morris water maze test and resting state MRI were computed at 0 day, 1, 3, 6 months post noise to reveal cognitive ability and neural substrate. The interregional connections in the auditory network and default mode network, as well as the connections using the auditory cortex and cingulate cortex as seeds were also examined addtionally. The deficit in spatial learning/memory was only observed at 6 months after noise exposure. The internal connections in the auditory network and default mode network were enhanced at 0 day and decreased at 6 months post noise. The connectivity using the auditory cortex and cingulate cortex as seeds generally followed the rule of "enhancement-normal-decrease-widely decrease". A new model accounting for arousal, dementia, motor control of NIHL in is proposed. Our study highlights the fundamental flexibility of neural systems, and may also point toward novel therapeutic strategies for treating sensory disorders.

A novel radiomics signature based on T2-weighted imaging accurately predicts hepatic inflammation in individuals with biopsy-proven nonalcoholic fatty liver disease: a derivation and independent validation study

Background

Currently, there are no effective methods for assessing hepatic inflammation without resorting to histological examination of liver tissue obtained by biopsy. T2-weighted images (T2WI) are routinely obtained from liver magnetic resonance imaging (MRI) scan sequences. We aimed to establish a radiomics signature based on T2WI (T2-RS) for assessment of hepatic inflammation in people with nonalcoholic fatty liver disease (NAFLD).

Methods

A total of 203 individuals with biopsy-confirmed NAFLD from two independent Chinese cohorts with liver MRI examination were enrolled in this study. The hepatic inflammatory activity score (IAS) was calculated by the unweighted sum of the histologic scores for lobular inflammation and ballooning. One thousand and thirty-two radiomics features were extracted from the localized region of interest (ROI) in the right liver lobe of T2WI and, subsequently, selected by minimum redundancy maximum relevance and least absolute shrinkage and selection operator (LASSO) methods. The T2-RS was calculated by adding the selected features weighted by their coefficients.

Results

Eighteen radiomics features from Laplacian of Gaussian, wavelet, and original images were selected for establishing T2-RS. The T2-RS value differed significantly between groups with increasing grades of hepatic inflammation (P<0.01). The T2-RS yielded an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.80 [95% confidence interval (CI): 0.71-0.89] for predicting hepatic inflammation in the training cohort with excellent calibration. The AUROCs of T2-RS in the internal cohort and external validation cohorts were 0.77 (0.61-0.93) and 0.75 (0.63-0.84), respectively.

Conclusions

The T2-RS derived from radiomics analysis of T2WI shows promising utility for predicting hepatic inflammation in individuals with NAFLD.

Assessment of renal function using magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses

Background

The incidence of chronic kidney disease (CKD) is high, and is easy to develop into end-stage renal disease (ESRD), which requires kidney dialysis or kidney transplantation. Therefore, we want to explore the clinical value of magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses (SLEEK) in assessing renal function in the early stage.

Methods

One hundred and twenty-nine patients underwent abdominal MRI examination, including a coronal SLEEK sequence. The patients were divided into the control group [CG, 47 cases, estimated glomerular filtration rate (eGFR) >90], the mild renal function impairment (mRI) group (48 cases, eGFR =60–90), and the moderate to severe renal function impairment (m-sRI) group (34 cases, eGFR <60). Two experienced radiologists delineated cortex and medulla regions of interest (ROIs) on SLEEK images to obtain cortex and medulla quantitative histogram parameters [Mean, Median, Percentiles (5^th, 10^th, 25^th, 75^th, and 90^th), Skewness, Kurtosis, and Entropy] using FireVoxel. These histogram parameters were compared by proper statistical methods such as one-way analysis of variance, the χ² test, and receiver operating characteristic (ROC) curve analysis.

Results

Four histogram parameters (Inhomogeneity_cortex, Skewness_cortex, Kurtosis_medulla, and Entropy_medulla) differed significantly between the CG and the mRI group. One medulla (Entropy_medulla) and nine cortex (Mean_cortex, Median_cortex, Kurtosis_cortex, Entropy_cortex, and 5^th, 10^th, 25^th, 75^th, and 90^th Percentile_cortex) histogram parameters were significantly different between the m-RI and m-sRI groups. The most relevant parameter to eGFR was Inhomogenity_cortex (r=−0.450, P<0.001). Inhomogeneity_cortex had the largest area under the curve (AUC) for differentiating the mRI group from the CG (AUC =0.718; 95% CI: 0.616–0.806), while 25^th Percentile_cortex generated the largest AUC (AUC =0.786; 95% CI: 0.681–0.869) for differentiating the mRI and m-sRI groups.

Conclusions

Quantitative histogram parameters based on a SLEEK sequence can be used to supplement renal dysfunction assessment. Cortex histogram parameters are more valuable for evaluating renal function than medulla histogram parameters.

Whole-lesion ADC histogram analysis versus single-slice ADC measurement for the differentiation of benign and malignant soft tissue tumors

PURPOSE

To evaluate and compare the diagnostic performances of whole-lesion apparent diffusion coefficient (ADC) histogram analysis and single-slice ADC measurement in the differentiation of benign and malignant soft tissue tumors.

METHODS

Fifty-three patients (mean age: 48.5 ± 21.4) with soft tissue tumors (27 benign and 26 malignant) were evaluated with diffusion-weighted MRI. Whole-lesion ADC histogram parameters (mean, median, 10^th percentile, 90^th percentile, minimum, maximum, range, mean absolute deviation, interquartile range, kurtosis, skewness, root mean squared, variance and inhomogeneity) of the lesions were measured using the whole solid tumor volume region of interest (ROI). In other sessions, five ROIs were manually drawn on the tumor slices, and mean ADC and minimum ADC of the measurements were calculated. Diagnostic accuracies of the two methods were assessed and compared.

RESULTS

Mean, median, minimum, 10^th percentile, 90^th percentile, range, root mean squared and inhomogeneity of ADC histogram analysis, and mean ADC and minimum ADC of single-slice ADC measurement were significantly different between malignant and benign lesions (p < 0.001 - p = 0.002). Among the ADC histogram parameters, 10^th percentile had the highest diagnostic performance (AUC = 0.825) followed by mean (AUC = 0.792) and median (AUC = 0.789). For the single-slice ADC measurement, the AUC of mean ADC and minimum ADC were 0.842 and 0.786, respectively. Mean ADC of single-slice measurement had a similar diagnostic performance with the 10^th percentile, mean, and median of ADC histogram analysis (p = 0.070-1.000).

CONCLUSIONS

Both whole-lesion ADC histogram analysis and single-slice ADC measurement can differentiate benign and malignant soft tissue tumors with similar diagnostic performances.

Therapeutic and diagnostic targeting of fibrosis in metabolic, proliferative and viral disorders

Fibrosis is a common denominator in many pathologies and crucially affects disease progression, drug delivery efficiency and therapy outcome. We here summarize therapeutic and diagnostic strategies for fibrosis targeting in atherosclerosis and cardiac disease, cancer, diabetes, liver diseases and viral infections. We address various anti-fibrotic targets, ranging from cells and genes to metabolites and proteins, primarily focusing on fibrosis-promoting features that are conserved among the different diseases. We discuss how anti-fibrotic therapies have progressed over the years, and how nanomedicine formulations can potentiate anti-fibrotic treatment efficacy. From a diagnostic point of view, we discuss how medical imaging can be employed to facilitate the diagnosis, staging and treatment monitoring of fibrotic disorders. Altogether, this comprehensive overview serves as a basis for developing individualized and improved treatment strategies for patients suffering from fibrosis-associated pathologies.

Autoimmune hepatitis in practice, from diagnosis to complications: What is the role of imaging? A clinicoradiological review

Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease of unknown origin that can lead to liver cirrhosis, hepatocellular carcinoma (HCC), liver transplantation or death. The diagnosis is performed upon a multifactorial score. Treatment is based on the combination of immunosuppressants and aims at clinical, laboratory and histological remission, the latter being the most difficult to be achieved and proven. The absence of liver inflammation, defined by biopsy, is the main determinant in remission or therapeutic modification. Imaging exams have a limited role in this clinical management and the main findings are those related to chronic liver disease. Imaging's relevance, therefore, lies mainly in helping to exclude overlapping syndromes and in assessing complications related to cirrhosis, such as in screening for HCC. In recent years, however, the radiological literature has been witnessing increasing advances with regard to imaging biomarkers in liver disease, leading some authors to consider a future of virtual liver biopsy performed by magnetic resonance imaging. The present study aims to review the role of imaging in the management of AIH in the light of recent advances in the current literature and to provide an illustrated guide with the main findings described in the disease.

Feasibility of T1 mapping with histogram analysis for the diagnosis and staging of liver fibrosis: Preclinical results

PURPOSE

To compare the diagnostic accuracy of parameters derived from the histogram analysis of precontrast, 10-min hepatobiliary phase (HBP) and 20-min HBP T1 maps for staging liver fibrosis (LF).

METHODS

LF was induced in New Zealand white rabbits by subcutaneous injections of carbon tetrachloride for 4-16 weeks (n = 120), and 20 rabbits injected with saline served as controls. Precontrast, 10-min and 20-min HBP modified Look-Locker inversion recovery (MOLLI) T1 mapping was performed. Histogram analysis of T1 maps was performed, and the mean, median, skewness, kurtosis, entropy, inhomogeneity and 10th/25th/75th/90th percentiles of T1_native, T1_10min and T1_20min were derived. Quantitative histogram parameters were compared. For significant parameters, further receiver operating characteristic (ROC) analyses were performed to evaluate the potential diagnostic performance in differentiating LF stages.

RESULTS

Finally, 17, 20, 21, 21 and 20 rabbits were included for the F0, F1, F2, F3, and F4 pathological grades of fibrosis, respectively. The mean/75th of T1_native, entropy of T1_10min and entropy/mean/median/10th of T1_20min demonstrated a significant good correlation with the LF stage (|r| = 0.543-0.866, all P < 0.05). The 75th of T1_native, entropy_10min, and entropy_20min were the three most reliable imaging markers in reflecting the stage of LF. The area under the ROC curve of entropy_20min was larger than that of entropy_10min (P < 0.05 for LF ≥ F2, ≥F3, and ≥ F4) and the 75th of T1_native (P < 0.05 for LF ≥ F2 and ≥ F3) for staging LF.

CONCLUSION

Magnetic resonance histogram analysis of T1 maps, particularly the entropy derived from 20-min HBP T1 mapping, is promising for predicting the LF stage.

Multiparametric MR mapping in clinical decision-making for diffuse liver disease

Accurate diagnosis, monitoring and treatment decisions in patients with chronic liver disease currently rely on biopsy as the diagnostic gold standard, and this has constrained early detection and management of diseases that are both varied and can be concurrent. Recent developments in multiparametric magnetic resonance imaging (mpMRI) suggest real potential to bridge the diagnostic gap between non-specific blood-based biomarkers and invasive and variable histological diagnosis. This has implications for the clinical care and treatment pathway in a number of chronic liver diseases, such as haemochromatosis, steatohepatitis and autoimmune or viral hepatitis. Here we review the relevant MRI techniques in clinical use and their limitations and describe recent potential applications in various liver diseases. We exemplify case studies that highlight how these techniques can improve clinical practice. These techniques could allow clinicians to increase their arsenals available to utilise on patients and direct appropriate treatments.

The value of multiparametric histogram features based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for the differential diagnosis of liver lesions

Background

The present study analyzed whole-lesion histogram parameters from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) to explore the clinical value of IVIM histogram features in the differentiation of liver lesions.

Methods

In this retrospective study, 33 cases of hepatic hemangioma (HH), 22 cases of hepatic cysts (HC), and 34 cases of hepatocellular carcinoma (HCC) were underwent IVIM-DWI (b =0–600 s/mm²), which were confirmed pathologically and clinically. The data were processed by IVIM model to obtain the following quantitative indicators: perfusion fraction (f), slow diffusion coefficient (D), and pseudo-diffusion coefficient (or fast diffusion coefficient, D*). The region of interest in the largest solid part of the lesion was delineated for histogram analysis of the correlation between tissue image and lesion type. The relevant histogram parameters were obtained and statistically analyzed. The characteristic histogram parameters for HH, HC, and HCC were compared to find significantly different parameters. The diagnostic efficacies of these parameters for HH, liver cysts, and HCC were assessed using the receiver operating characteristic (ROC) curves.

Results

There were significant differences in the maximum diameter, maximum value, minimum value, mean, median, standard deviation, uniformity, skewness, kurtosis, volume, 10th percentile (P10) of D, and 90th percentile (P90) of D between the three groups (P<0.05). The maximum diameter, minimum value, entropy, and volume of D* differed significantly between the three groups (P<0.05). The maximum diameter, minimum value, mean, median, skewness, kurtosis, volume, P10, and P90 of f differed significantly between the three groups (P<0.05). The largest area under the ROC curve (AUC) for both D* and f was that of volume (AUC =0.883 for both). When 1438.802 was used as the volume cut-off, the sensitivity and specificity of volume in differentiating between HH and HC were 87.88 and 77.27, respectively, and the sensitivity and specificity of volume in differentiating between HC and HCC were 77.27 and 85.29.

Conclusions

A multiparametric histogram from IVIM-DWI magnetic resonance imaging (MRI) is an effective means of identifying HH, HC, and HCC that provides valuable reference information for clinical diagnosis.