Liver Fibrosis Quantification by Magnetic Resonance Imaging

Diagnostic accuracy of texture analysis applied to T1- and T2-Relaxation maps for liver fibrosis classification via machine-learning algorithms with liver histology as reference standard

OBJECTIVES

To explore texture analysis' ability on T1 and T2 relaxation maps to classify liver fibrosis into no-to-mild liver fibrosis (nmF) versus severe fibrosis (sF) group using machine learning algorithms and histology as reference standard.

MATERIALS AND METHODS

In this single-center study, patients undergoing 3 T MRI who also had histology examination were retrospectively enrolled. SNAPSHOT-FLASH sequence for T1 mapping, radial turbo-spin-echo sequence for T2 mapping and spin-echo echo-planar-imaging magnetic resonance elastography (MRE) sequences were analyzed. Grey-level co-occurrence matrix texture analysis features were extracted from T1 (TA-T1) and T2 (TA-T2) maps from single-slice whole-liver region-of-interest. The extracted features were evaluated as predictors for nmF and sF group classification separately using support-vector-machine algorithm combined with principal component analysis in case of texture features. Recursive Feature Elimination with Cross-Validation (RFECV) was used to identify the most significant features and the importance of selected features was assessed with permutation importance algorithm. A combined model was identified and evaluated. Area under the receiver operating characteristic curve (AUC) was used for scoring and model comparison.

RESULTS

46 patients (mean age 52.8 ± 16.1 years, 23 males) were evaluated. TA-T1 performed comparably to MRE (0.748 vs 0.759, p = 0.905) and T1 performed slightly worse compared to MRE which was not statistically significant (0.692 vs 0.759, p = 0.396). MRE outperformed T2 (0.759 vs 0.552) and TA-T2 (0.759 vs 0.515). RFECV algorithm identified four features: MRE, T1 and 1st two TA-T1 principal components, constituting the first combined model. The permutation importance identified T1 as feature of very low importance, therefore a second combined model was constructed, omitting T1 from the first combined model. Even though both combined models performed higher than MRE (0.759 vs 0.797, p = 0.597 for MRE vs MRE + T1 + TA-T1, and 0.759 vs 0.817, p = 0.373 for MRE vs MRE + TA-T1), it was not statistically significant.

CONCLUSIONS

TA-T1 performed comparably to MRE in liver fibrosis classification to nmF and sF groups, and even though not statistically significant, combining those with MRE increased the performance, suggesting their complementary nature. Given the broad availability, robustness and short scanning times of T1 mapping, we would advocate for the inclusion of T1 mapping in every clinical and research liver examination.

The application of B1 inhomogeneity-corrected variable flip angle T1 mapping for assessing liver fibrosis

PURPOSE

The aim of this study was to evaluate the diagnostic accuracy of the B1 inhomogeneity-corrected variable flip angle (VFA) method using native T1 values in the staging of liver fibrosis.

METHODS

Eighty-three patients who presented for liver biopsy due to varying degrees of liver damage, underwent MR examinations and had T1-mapping images of the liver acquired using the B1 inhomogeneity-corrected VFA VIBE method. Among them, 65 patients underwent Fibroscan, and their results were used to evaluate the elasticity of liver tissue. Additionally, T1-mapping images were collected from 19 normal control patients. Independent sample t-tests were used to analyze the correlation between T1 mapping and Fibroscan. The diagnostic efficacy of T1 mapping in patients with different stages of liver fibrosis was evaluated using receiver operating characteristic (ROC) curves.

RESULTS

The consistency between different observer groups was intraclass correlation coefficient (ICC) =0.802. T1 mapping demonstrated significant differences between mid-stage liver fibrosis (S = 2) and late-stage liver fibrosis (S = 3), as well as moderate inflammation (G = 2) and severe inflammation (G = 3), P < 0.05. The Area Under Curve(AUC) values of T1 mapping for early liver fibrosis (S ≥ 1), significant liver fibrosis (S ≥ 2), advanced liver fibrosis (S ≥ 3), and end-stage liver fibrosis (S = 4) were 0.760, 0.709, 0.790, and 0.768, respectively. T1 mapping combined with Fibroscan had an AUC value of 0.860.

CONCLUSIONS

The B1 inhomogeneity-corrected VFA T1 mapping may be useful for the staging of liver fibrosis. It has a superior diagnostic efficiency for diagnosing advanced fibrosis (≥S3), while native T1 values combined with Fibroscan have potential value for the staging of liver fibrosis.

Diagnostic performance of shear wave measurement in the detection of hepatic fibrosis: A multicenter prospective study

AIM

This study aimed to establish the shear wave measurement (SWM) cut-off value for each fibrosis stage using magnetic resonance (MR) elastography values as a reference standard.

METHODS

We prospectively analyzed 594 patients with chronic liver disease who underwent SWM and MR elastography. Correlation coefficients (were analyzed, and the diagnostic value was evaluated by the area under the receiver operating characteristic curve. Liver stiffness was categorized by MR elastography as F0 (<2.61 kPa), F1 (≥2.61 kPa, <2.97 kPa, any fibrosis), F2 (≥2.97 kPa, <3.62 kPa, significant fibrosis), F3 (≥3.62 kPa, <4.62 kPa, advanced fibrosis), or F4 (≥4.62 kPa, cirrhosis).

RESULTS

The median SWM values increased significantly with increasing fibrosis stage (p < 0.001). The correlation coefficient between SWM and MR elastography values was 0.793 (95% confidence interval 0.761-0.821). The correlation coefficients between SWM and MR elastography values significantly decreased with increasing body mass index and skin-capsular distance; skin-capsular distance values were associated with significant differences in sensitivity, specificity, accuracy, or positive predictive value, whereas body mass index values were not. The best cut-off values for any fibrosis, significant fibrosis, advanced fibrosis, and cirrhosis were 6.18, 7.09, 8.05, and 10.89 kPa, respectively.

CONCLUSIONS

This multicenter study in a large number of patients established SWM cut-off values for different degrees of fibrosis in chronic liver diseases using MR elastography as a reference standard. It is expected that these cut-off values will be applied to liver diseases in the future.

Advancements of non‐invasive imaging technologies for the diagnosis and staging of liver fibrosis: Present and future

Liver fibrosis is a reparative response triggered by liver injury. Non‐invasive assessment and staging of liver fibrosis in patients with chronic liver disease are of paramount importance, as treatment strategies and prognoses depend significantly on the degree of fibrosis. Although liver fibrosis has traditionally been staged through invasive liver biopsy, this method is prone to sampling errors, particularly when biopsy sizes are inadequate. Consequently, there is an urgent clinical need for an alternative to biopsy, one that ensures precise, sensitive, and non‐invasive diagnosis and staging of liver fibrosis. Non‐invasive imaging assessments have assumed a pivotal role in clinical practice, enjoying growing popularity and acceptance due to their potential for diagnosing, staging, and monitoring liver fibrosis. In this comprehensive review, we first delved into the current landscape of non‐invasive imaging technologies, assessing their accuracy and the transformative impact they have had on the diagnosis and management of liver fibrosis in both clinical practice and animal models. Additionally, we provided an in‐depth exploration of recent advancements in ultrasound imaging, computed tomography imaging, magnetic resonance imaging, nuclear medicine imaging, radiomics, and artificial intelligence within the field of liver fibrosis research. We summarized the key concepts, advantages, limitations, and diagnostic performance of each technique. Finally, we discussed the challenges associated with clinical implementation and offer our perspective on advancing the field, hoping to provide alternative directions for the future research.

Native and Gd-EOB-DTPA-Enhanced T1 mapping for Assessment of Liver Fibrosis in NAFLD: Comparative Analysis of Modified Look-Locker Inversion Recovery and Water-specific T1 mapping

RATIONALE AND OBJECTIVES

To investigate the diagnostic performance of water-specific T1 mapping for staging liver fibrosis in a non-alcoholic fatty liver disease (NAFLD) rabbit model, in comparison to Modified Look-Locker Inversion recovery (MOLLI) T1 mapping.

MATERIALS AND METHODS

60 rabbits were randomly divided into the control group (12 rabbits) and NAFLD model groups (eight rabbits per subgroup) corresponding to different durations of high-fat high cholesterol diet feeding. All rabbits underwent MRI examination including MOLLI T1 mapping and 3D multi-echo variable flip angle (VFAME- GRE) sequences were acquired before and 20 min after the administration of Gd- EOB-DTPA. Histological assessments were performed to evaluate steatosis, inflammation, ballooning, and fibrosis. Statistical analysis included the intraclass correlation coefficient, analysis of variance, spearman correlation, multiple linear regression, and receiver operating characteristic curve.

RESULTS

A moderate correlation was observed between conventional native T1 and MRI-PDFF (r = -0.513, P < 0.001), as well as between conventional native T1 and liver steatosis grades (r = -0.319, P = 0.016). However, no significant correlation was found between the native wT1 and PDFF (r = 0.137, P = 0.314), or between the native wT1 and steatosis grades (r = 0.106, P = 0.435). In the multiple regression analysis, liver fibrosis, and hepatocellular ballooning were identified as independent factors influencing native wT1 in this study (R2 =0.545, P < 0.05), while steatosis was independently associated with conventional native T1 (R2 =0.321, P < 0.05). The AUC values for native T1, native wT1, HBP T1, and HBP wT1 were 0.549(0.410-0.682), 0.811(0.684-0.903), 0.775(0.644-0.876), and 0.752(0.619-0.858) for F1 or higher, 0.581(0.441-0.711), 0.828(0.704-0.916), 0.832(0.708-0.919), and 0.854(0.734-0.934) for F2 or higher, respectively.

CONCLUSION

The native wT1 may provide a more reliable assessment of early liver fibrosis in the context of NAFLD compared to conventional native T1.

Staging liver fibrosis with various diffusion-weighted magnetic resonance imaging models

BACKGROUND

Diffusion-weighted imaging (DWI) has been developed to stage liver fibrosis. However, its diagnostic performance is inconsistent among studies. Therefore, it is worth studying the diagnostic value of various diffusion models for liver fibrosis in one cohort.

AIM

To evaluate the clinical potential of six diffusion-weighted models in liver fibrosis staging and compare their diagnostic performances.

METHODS

This prospective study enrolled 59 patients suspected of liver disease and scheduled for liver biopsy and 17 healthy participants. All participants underwent multi-b value DWI. The main DWI-derived parameters included Mono-apparent diffusion coefficient (ADC) from mono-exponential DWI, intravoxel incoherent motion model-derived true diffusion coefficient (IVIM-D), diffusion kurtosis imaging-derived apparent diffusivity (DKI-MD), stretched exponential model-derived distributed diffusion coefficient (SEM-DDC), fractional order calculus (FROC) model-derived diffusion coefficient (FROC-D) and FROC model-derived microstructural quantity (FROC-μ), and continuous-time random-walk (CTRW) model-derived anomalous diffusion coefficient (CTRW-D) and CTRW model-derived temporal diffusion heterogeneity index (CTRW-α). The correlations between DWI-derived parameters and fibrosis stages and the parameters' diagnostic efficacy in detecting significant fibrosis (SF) were assessed and compared.

RESULTS

CTRW-D (r = -0.356), CTRW-α (r = -0.297), DKI-MD (r = -0.297), FROC-D (r = -0.350), FROC-μ (r = -0.321), IVIM-D (r = -0.251), Mono-ADC (r = -0.362), and SEM-DDC (r = -0.263) were significantly correlated with fibrosis stages. The areas under the ROC curves (AUCs) of the combined index of the six models for distinguishing SF (0.697-0.747) were higher than each of the parameters alone (0.524-0.719). The DWI models' ability to detect SF was similar. The combined index of CTRW model parameters had the highest AUC (0.747).

CONCLUSION

The DWI models were similarly valuable in distinguishing SF in patients with liver disease. The combined index of CTRW parameters had the highest AUC.

Establishment of Noninvasive Prediction Models for the Diagnosis of Uterine Leiomyoma Subtypes

OBJECTIVE

To establish prediction models for the diagnosis of the subtypes of uterine leiomyomas by machine learning using magnetic resonance imaging (MRI) data.

METHODS

This is a prospective observational study. Ninety uterine leiomyoma samples were obtained from 51 patients who underwent surgery for uterine leiomyomas. Seventy-one samples (49 mediator complex subunit 12 [ MED12 ] mutation-positive and 22 MED12 mutation-negative leiomyomas) were assigned to the primary data set to establish prediction models. Nineteen samples (13 MED12 mutation-positive and 6 MED12 mutation-negative leiomyomas) were assigned to the unknown testing data set to validate the prediction model utility. The tumor signal intensity was quantified by seven MRI sequences (T2-weighted imaging, apparent diffusion coefficient, magnetic resonance elastography, T1 mapping, magnetization transfer contrast, T2* blood oxygenation level dependent, and arterial spin labeling) that can estimate the collagen and water contents of uterine leiomyomas. After surgery, the MED12 mutations were genotyped. These results were used to establish prediction models based on machine learning by applying support vector classification and logistic regression for the diagnosis of uterine leiomyoma subtypes. The performance of the prediction models was evaluated by cross-validation within the primary data set and then finally evaluated by external validation using the unknown testing data set.

RESULTS

The signal intensities of five MRI sequences (T2-weighted imaging, apparent diffusion coefficient, T1 mapping, magnetization transfer contrast, and T2* blood oxygenation level dependent) differed significantly between the subtypes. In cross-validation within the primary data set, both machine learning models (support vector classification and logistic regression) based on the five MRI sequences were highly predictive of the subtypes (area under the curve [AUC] 0.974 and 0.988, respectively). External validation with the unknown testing data set confirmed that both models were able to predict the subtypes for all samples (AUC 1.000, 100.0% accuracy). Our prediction models with T2-weighted imaging alone also showed high accuracy to discriminate the uterine leiomyoma subtypes.

CONCLUSION

We established noninvasive prediction models for the diagnosis of the subtypes of uterine leiomyomas by machine learning using MRI data.

Radiotracers for Imaging of Fibrosis: Advances during the Last Two Decades and Future Directions

Fibrosis accompanies various pathologies, and there is thus an unmet medical need for non-invasive, sensitive, and quantitative methods for the assessment of fibrotic processes. Currently, needle biopsy with subsequent histological analysis is routinely used for the diagnosis along with morphological imaging techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US). However, none of these imaging techniques are sufficiently sensitive and accurate to detect minor changes in fibrosis. More importantly, they do not provide information on fibrotic activity on the molecular level, which is critical for fundamental understanding of the underlying biology and disease course. Molecular imaging technology using positron emission tomography (PET) offers the possibility of imaging not only physiological real-time activity, but also high-sensitivity and accurate quantification. This diagnostic tool is well established in oncology and has exhibited exponential development during the last two decades. However, PET diagnostics has only recently been widely applied in the area of fibrosis. This review presents the progress of development of radiopharmaceuticals for non-invasive detection of fibrotic processes, including the fibrotic scar itself, the deposition of new fibrotic components (fibrogenesis), or the degradation of existing fibrosis (fibrolysis).

Raman microspectroscopy identifies fibrotic tissues in collagen-related disorders via deconvoluted collagen type I spectra

Fibrosis is a consequence of the pathological remodeling of extracellular matrix (ECM) structures in the connective tissue of an organ. It is often caused by chronic inflammation, which over time, progressively leads to an excess deposition of collagen type I (COL I) that replaces healthy tissue structures, in many cases leaving a stiff scar. Increasing fibrosis can lead to organ failure and death; therefore, developing methods that potentially allow real-time monitoring of early onset or progression of fibrosis are highly valuable. In this study, the ECM structures of diseased and healthy human tissue from multiple organs were investigated for the presence of fibrosis using routine histology and marker-independent Raman microspectroscopy and Raman imaging. Spectral deconvolution of COL I Raman spectra allowed the discrimination of fibrotic and non-fibrotic COL I fibers. Statistically significant differences were identified in the amide I region of the spectral subpeak at 1608 cm^-1, which was deemed to be representative for structural changes in COL I fibers in all examined fibrotic tissues. Raman spectroscopy-based methods in combination with this newly discovered spectroscopic biomarker potentially offer a diagnostic approach to non-invasively track and monitor the progression of fibrosis. STATEMENT OF SIGNIFICANCE: Current diagnosis of fibrosis still relies on histopathological examination with invasive biopsy procedures. Although, several non-invasive imaging techniques such as positron emission tomography, single-photon emission computed tomography and second harmonic generation are gradually employed in preclinical or clinical studies, these techniques are limited in spatial resolution and the morphological interpretation highly relies on individual experience and knowledge. In this study, we propose a non-destructive technique, Raman microspectroscopy, to discriminate fibrotic changes of collagen type I based on a molecular biomarker. The changes of the secondary structure of collagen type I can be identified by spectral deconvolution, which potentially can provide an automatic diagnosis for fibrotic tissues in the clinical applicaion.

Correlation Between Computed Tomography Findings and the Laboratory Test-Derived Severity Score in Patients With Severe Acute Alcoholic Hepatitis

OBJECTIVE

This study aimed to compare computed tomography (CT) findings between patients with severe and nonsevere acute alcoholic hepatitis (AAH).

METHODS

We included 96 patients diagnosed with AAH between January 2011 and October 2021 who underwent 4-phase liver CT and laboratory blood tests. Two radiologists reviewed the initial CT images with respect to distribution and grade of hepatic steatosis; transient parenchymal arterial enhancement (TPAE); and presence of cirrhosis, ascites, and hepatosplenomegaly. A Maddrey discriminant function score (4.6 × [patient's prothrombin time - control] + total bilirubin [mg/mL]) was used as cutoff indicator for severity, with a score of 32 or higher indicating severe disease. The image findings were compared between the severe (n = 24) and nonsevere (n = 72) groups using the χ2 test or Fisher exact test. After univariate analysis, the most significant factor was identified using a logistic regression analysis.

RESULTS

In the univariate analysis, there were significant between-group differences in the TPAE, liver cirrhosis, splenomegaly, and ascites (P < 0.0001, P < 0.0001, P = 0.0002, and P = 0.0163, respectively). Among them, TPAE was the only significant factor for severe AAH (P < 0.0001; odds ratio, 48.1; 95% confidence interval, 8.3-280.6). Using this single indicator, the estimated accuracy, positive predictive, and negative predictive values were 86%, 67%, and 97%, respectively.

CONCLUSIONS

Transient parenchymal arterial enhancement was the only significant CT finding in severe AAH.

Preclinical Long-term Magnetic Resonance Imaging Study of Silymarin Liver-protective Effects

BACKGROUND AND AIMS

Efficacy evaluations with preclinical magnetic resonance imaging (MRI) are uncommon, but MRI in the preclinical phase of drug development provides information that is useful for longitudinal monitoring. The study aim was to monitor the protective effectiveness of silymarin with multiparameter MRI and biomarkers in a thioacetamide (TAA)-induced model of liver injury in rats. Correlation analysis was conducted to assess compare the monitoring of liver function by MRI and biomarkers.

METHODS

TAA was injected three times a week for 8 weeks to generate a disease model (TAA group). In the TAA and silymarin-treated (TAA-SY) groups, silymarin was administered three times weekly from week 4. MR images were acquired at 0, 2, 4, 6, and 8 weeks in the control, TAA, and TAA-SY groups.

RESULTS

The area under the curve to maximum time (AUC_tmax) and T₂* values of the TAA group decreased over the study period, but the serological markers of liver abnormality increased significantly more than those in the control group. In the TAA-SY group, MRI and serological biomarkers indicated attenuation of liver function as in the TAA group. However, pattern changes were observed from week 6 to comparable levels in the control group with silymarin treatment. Negative correlations between either AUC_tmax or T₂* values and the serological biomarkers were observed.

CONCLUSIONS

Silymarin had hepatoprotective effects on TAA-induced liver injury and demonstrated the usefulness of multiparametric MRI to evaluate efficacy in preclinical studies of liver drug development.

Biodistribution Profile of Magnetic Nanoparticles in Cirrhosis-Associated Hepatocarcinogenesis in Rats by AC Biosusceptometry

Since magnetic nanoparticles (MNPs) have been used as multifunctional probes to diagnose and treat liver diseases in recent years, this study aimed to assess how the condition of cirrhosis-associated hepatocarcinogenesis alters the biodistribution of hepatic MNPs. Using a real-time image acquisition approach, the distribution profile of MNPs after intravenous administration was monitored using an AC biosusceptometry (ACB) assay. We assessed the biodistribution profile based on the ACB images obtained through selected regions of interest (ROIs) in the heart and liver position according to the anatomical references previously selected. The signals obtained allowed for the quantification of pharmacokinetic parameters, indicating that the uptake of hepatic MNPs is compromised during liver cirrhosis, since scar tissue reduces blood flow through the liver and slows its processing function. Since liver monocytes/macrophages remained constant during the cirrhotic stage, the increased intrahepatic vascular resistance associated with impaired hepatic sinusoidal circulation was considered the potential reason for the change in the distribution of MNPs.

MR elastography in nonalcoholic fatty liver disease: inter-center and inter-analysis-method measurement reproducibility and accuracy at 3T

OBJECTIVES

To assess reproducibility and fibrosis classification accuracy of magnetic resonance elastography (MRE)-determined liver stiffness measured manually at two different centers, and by automated analysis software in adults with nonalcoholic fatty liver disease (NAFLD), using histopathology as a reference standard.

METHODS

This retrospective, cross-sectional study included 91 adults with NAFLD who underwent liver MRE and biopsy. MRE-determined liver stiffness was measured independently for this analysis by an image analyst at each of two centers using standardized manual analysis methodology, and separately by an automated analysis. Reproducibility was assessed pairwise by intraclass correlation coefficient (ICC) and Bland-Altman analysis. Diagnostic accuracy was assessed by receiver operating characteristic (ROC) analyses.

RESULTS

ICC of liver stiffness measurements was 0.95 (95% CI: 0.93, 0.97) between center 1 and center 2 analysts, 0.96 (95% CI: 0.94, 0.97) between the center 1 analyst and automated analysis, and 0.94 (95% CI: 0.91, 0.96) between the center 2 analyst and automated analysis. Mean bias and 95% limits of agreement were 0.06 ± 0.38 kPa between center 1 and center 2 analysts, 0.05 ± 0.32 kPa between the center 1 analyst and automated analysis, and 0.11 ± 0.41 kPa between the center 2 analyst and automated analysis. The area under the ROC curves for the center 1 analyst, center 2 analyst, and automated analysis were 0.834, 0.833, and 0.847 for distinguishing fibrosis stage 0 vs. ≥ 1, and 0.939, 0.947, and 0.940 for distinguishing fibrosis stage ≤ 2 vs. ≥ 3.

CONCLUSION

MRE-determined liver stiffness can be measured with high reproducibility and fibrosis classification accuracy at different centers and by an automated analysis.

KEY POINTS

• Reproducibility of MRE liver stiffness measurements in adults with nonalcoholic fatty liver disease is high between two experienced centers and between manual and automated analysis methods. • Analysts at two centers had similar high diagnostic accuracy for distinguishing dichotomized fibrosis stages. • Automated analysis provides similar diagnostic accuracy as manual analysis for advanced fibrosis.

Liver fibrosis quantification

Liver fibrosis (LF) is the wound healing response to chronic liver injury. LF is the endpoint of chronic liver disease (CLD) regardless of etiology and the single most important determinant of long-term liver-related clinical outcomes. Quantification of LF is important for staging, to evaluate response to treatment and to predict outcomes. LF is traditionally staged by liver biopsy. However, liver biopsy is invasive and suffers from sampling errors when biopsy size is inadequate; therefore, non-invasive tests (NITs) have found important roles in clinical care. NITs include simple laboratory-based serum tests, panels of serum tests, and imaging biomarkers. NITs are validated against the liver biopsy and will be used in the future for evaluation of nearly all CLDs with invasive liver biopsy reserved for some cases. Both serum tests and some imaging biomarkers such as elastography are currently used clinically as surrogate markers for LF. Several other imaging biomarkers are still considered research and awaiting clinical application in the future. As the evaluation of imaging biomarkers will likely become the norm in the future, understanding pathogenesis of LF is important. Knowledge of properties measured by imaging biomarkers and its correlation with LF is important to understand the application of NITs by abdominal radiologists. In this review, we present a brief overview of pathogenesis of LF, spatiotemporal evolution of LF in different CLD, and severity assessment with liver biopsy. This will be followed by a brief discussion on properties measured by imaging biomarkers and their relationship to the LF.

Diagnostic potential of T1ρ and T2 relaxations in assessing the severity of liver fibrosis and necro-inflammation

PURPOSE

To investigate the utility of T1ρ and T2 relaxations for assessing the severity of liver fibrosis (F stage) and necro-inflammation (A stage) in patients with chronic liver disease (CLD).

MATERIALS AND METHODS

We calculated T1ρ and T2 relaxations of the liver parenchyma in 82 patients who underwent liver surgery. F and A stages of enrolled patients were assessed by referring to surgically resected specimens. The relationships between T1ρ or T2 relaxation and F or A stage were assessed using one-way analysis of variance followed by Tukey's multiple comparison test, Spearman's rank correlation test and a receiver operating characteristic analysis.

RESULTS

The T1ρ and T2 values of the liver parenchyma were significantly increased as the F and A stages progressed. The T1ρ and T2 values showed significant differences between F0 and F4, between F1 and F4, and between F2 and F4. In addition, T1ρ values showed a significant difference between F0 and F3 as well. The highest diagnostic ability for fibrosis was obtained when differentiating ≥F3 from ≤F2 using T1ρ: the sensitivity was 82.8%, the specificity 79.2% and the area under the curve (AUC) 0.87. The sensitivity and AUC of T1ρ relaxation (46.9% and 0.67) were significantly higher than those of T2 relaxation (29.7% and 0.60) for differentiating ≥A1 from A0.

CONCLUSION

T1ρ and T2 relaxations have potential as a biochemical marker for assessing the severity of liver fibrosis and necro-inflammation. T1ρ relaxation may be slightly superior to T2 relaxation in terms of diagnostic ability for liver fibrosis and necro-inflammation.

Magnetic Resonance Elastography of the Liver: A Single-Institution Review of Cases Performed in a 5-Year Interval

OBJECTIVE

This study aimed to assess the diagnostic accuracy of magnetic resonance elastography (MRE) in detecting hepatic fibrosis and determining clinically relevant stiffness cutoff values per stage of fibrosis.

METHODS

This retrospective study assessed 1488 hepatic MRE evaluations performed at a single institution for 5 years. Mean liver stiffness measurements were collected from 282 patients who had an MRE study within 1 year of histopathologic analysis. Areas under receiver operating characteristic curves were calculated for each stage of fibrosis with nonparametric ordinal measures of accuracy, and Youden Index was determined.

RESULTS

Mean liver stiffness measurement values were as follows: F0, 2.5± 0.55 kPa; F1, 3.1± 0.80 kPa; F2, 3.4±0.95 kPa; F3, 4.7±1.44 kPa; and F4, 7.9± 2.64 kPa. Nonparametric ordinal measures of accuracy per fibrosis stage were as follows: F0: 0.934, P < 0.001; F0-F1: 0.917, P < 0.001; F0-F2: 0.944, P < 0.001; and F0-F3: 0.941, P < 0.001. Youden Index values for fibrosis stages F2, F3, and F4 were 3.9, 4.0, and 4.5 kPa, respectively.

CONCLUSIONS

Magnetic resonance elastography is an accurate diagnostic tool in assessing liver fibrosis.

Quantitative magnetic resonance imaging of chronic kidney disease: an experimental in vivo study using rat chronic kidney disease models

BACKGROUND

Recent advances in magnetic resonance imaging (MRI) may allow it to be an alternative emerging tool for the non-invasive evaluation of renal parenchymal disease.

PURPOSE

To validate the usefulness of quantitative multiparametric MRI protocols and suggest the suitable quantitative MR sequence protocol to evaluate parenchymal fibrosis using an animal model of chronic kidney disease (CKD) by long-term adenine intake.

MATERIAL AND METHODS

In this prospective animal study, 16 male Wistar rats were analyzed and categorized into three groups. Rats in the CKD groups underwent 0.25% adenine administration for three or six weeks. Quantitative MRI protocols, including diffusion-weighted imaging (DWI), T1ρ (T1 rho), and T2* mapping were performed using a 9.4-T animal MR scanner. A semi-quantitative histopathologic analysis for renal fibrosis was conducted. Quantitative MR values measured from anatomic regions of kidneys underwent intergroup comparative analyses.

RESULTS

The apparent diffusion coefficient (ADC) and T1 (T1 rho) values were significantly increased in all CKD groups. Values measured from the cortex and outer medulla showed significant intergroup differences. Total ADC values tended to increase according to periods, and T1ρ values increased in three weeks and decreased in six weeks.

CONCLUSION

Quantitative MRI protocols could be a non-invasive assessment modality in the diagnosis and evaluation of CKD. Particularly, T1ρ may be a suitable MR sequence to quantitatively assess renal parenchymal fibrosis.

Systemic Mastocytosis: Radiological Point of View

Radiological diagnosis of systemic mastocytosis (SM) can be hard to establish. This difficulty is mainly due to the variable radiological features involving many organ systems (e.g., respiratory, cardiovascular, lympho-reticular, digestive systems, and most commonly skin), and above all, to the broad spectrum of skeletal findings. Skeletal involvement is the most common and prominent imaging feature in patients with SM and represents a prognostic factor as it may entail an aggressive course of the disease. Diagnosis, largely established by histological evaluation of a bone marrow trephine biopsy, supplemented by imaging modalities such as radiography, CT, and magnetic resonance imaging, requires a team approach between the hematologist, radiologist, and pathologist. The general radiologist needs to be familiar with the imaging findings because they may be the first to suggest the correct diagnosis. The primary purpose of this review article was to equip clinicians with pertinent radiological semiotics by presenting relevant radiological features that assist early diagnosis and selection of an effective treatment.

Evaluation of liver fibrosis and cirrhosis on the basis of quantitative T1 mapping: Are acute inflammation, age and liver volume confounding factors?

PURPOSE

To evaluate potential confounding factors in the quantitative assessment of liver fibrosis and cirrhosis using T1 relaxation times.

METHODS

The study population is based on a radiology-information-system database search for abdominal MRI performed from July 2018 to April 2019 at our institution. After applying exclusion criteria 200 (59 ± 16 yrs) remaining patients were retrospectively included. 93 patients were defined as liver-healthy, 40 patients without known fibrosis or cirrhosis, and 67 subjects had a clinically or biopsy-proven liver fibrosis or cirrhosis. T1 mapping was performed using a slice based look-locker approach. A ROI based analysis of the left and the right liver was performed. Fat fraction, R2*, liver volume, laboratory parameters, sex, and age were evaluated as potential confounding factors.

RESULTS

T1 values were significantly lower in healthy subjects without known fibrotic changes (1.5 T MRI: 575 ± 56 ms; 3 T MRI: 857 ± 128 ms) compared to patients with acute liver disease (1.5 T MRI: 657 ± 73 ms, p < 0.0001; 3 T MRI: 952 ± 37 ms, p = 0.028) or known fibrosis or cirrhosis (1.5 T MRI: 644 ± 83 ms, p < 0.0001; 3 T MRI: 995 ± 150 ms, p = 0.018). T1 values correlated moderately with the Child-Pugh stage at 1.5 T (p = 0.01, ρ = 0.35).

CONCLUSION

T1 mapping is a capable predictor for detection of liver fibrosis and cirrhosis. Especially age is not a confounding factor and, hence, age-independent thresholds can be defined. Acute liver diseases are confounding factors and should be ruled out before employing T1-relaxometry based thresholds to screen for patients with liver fibrosis or cirrhosis.

Paediatric gastrointestinal and hepatobiliary radiology: why do we need subspecialists, and what is new?

We present the case for subspecialisation in paediatric gastrointestinal and hepato-pancreatico-biliary radiology. We frame the discussion around a number of questions: What is different about the paediatric patient and paediatric gastrointestinal system? What does the radiologist need to do differently? And finally, what can be translated from these subspecialty areas into everyday practice? We cover conditions that the sub-specialist might encounter, focusing on entities such as inflammatory bowel disease and hepatic vascular anomalies. We also highlight novel imaging techniques that are a focus of research in the subspecialties, including contrast-enhanced ultrasound, MRI motility, magnetisation transfer factor, and magnetic resonance elastography.

Diagnostic value of spleen stiffness by magnetic resonance elastography for prediction of esophageal varices in cirrhotic patients

PURPOSE

To evaluate the diagnostic value of spleen stiffness (SS) via magnetic resonance elastography (MRE) in predicting esophageal varices.

METHODS

From January 2016 to September 2018, we retrospectively reviewed 263 patients with esophagogastroduodenoscopy (EGD) records and available spleen and liver stiffness (LS) values from MRE. Clinical information including the underlying diseases, endoscopic grade of esophageal varices (EV) and laboratory data were collected from electronic medical records.

RESULTS

In cirrhotic patients, MRE-SS was higher in those with EV than in those without. MRE-SS also showed significant association with EV in the multivariate analysis, whereas MRE-LS did not. The diagnostic performance of MRE-SS for EV in cirrhotic patients was demonstrated by the area under curve of 0.853 (cut-off value: 9.53 kPa, P < 0.001), 84.4% sensitivity and 73.7% specificity.

CONCLUSION

For prediction of EV in cirrhotic patients, MRE-SS is a useful non-invasive tool and it demonstrates better diagnostic performance than MRE-LS does.

Radiolabelling and positron emission tomography imaging of a high-affinity peptide binder to collagen type 1

INTRODUCTION

Pathological formation of fibrosis, is an important feature in many diseases. Fibrosis in liver and pancreas has been associated to metabolic disease including type 1 and 2 diabetes. The current methods for detecting and diagnosing fibrosis are either invasive, or their sensitivity to detect fibrosis in early stage is limited. Therefore, it is crucial to develop non-invasive methods to detect, stage and study the molecular processes that drive the pathology of liver fibrosis. The peptide LRELHLNNN was previously identified as a selective binder to collagen type I with an affinity of 170 nM. Radiolabelled LRELHLNNN thus constitute a potential PET tracer for fibrosis.

METHOD

LRELHLNNN was conjugated to a DOTA/NOTA moiety via a PEG2-linker. DOTA-PEG2-LRELHLNNN was labelled with Gallium-68 and NOTA- PEG2-LRELHLNNN with aluminium fluoride-18. Biodistribution of [68Ga]Ga-DOTA-PEG2-LRELHLNNN and [18F]AlF-NOTA-PEG2-LRELHLNNN was performed in healthy rats ex vivo and in vivo. The 68Ga-labelled analogue was evaluated in a mouse model of liver fibrosis by PET/MRI-imaging. The human predicted dosimetry of the tracers was extrapolated from rat ex vivo biodistribution studies at 10, 20, 40, 60, 120, 180 min (only fluoride-18) post-injection.

RESULTS

The peptides were successfully radiolabelled with gallium-68 and aluminium fluoride-18, respectively. The biodistribution of [68Ga]Ga-DOTA-PEG2-LRELHLNNN and [18F]AlF-NOTA-PEG2-LRELHLNNN was favorable showing rapid clearance and low background binding in organs where fibrosis may develop. Binding of [68Ga]Ga-DOTA-PEG2-LRELHLNNN to fibrotic liver was higher than surrounding tissues in mice with induced hepatic fibrosis. However, the binding was in the range of SUV 0.3, indicating limited targeting of the tracer to liver. The extrapolated human predicted dosimetric profiles of [68Ga]Ga-DOTA-PEG2-LRELHLNNN and [18F]AlF-NOTA-PEG2-LRELHLNNN were beneficial, potentially allowing at least three PET examinations annually.

CONCLUSIONS

We describe the modification, radiolabelling and evaluation of the collagen type I binding peptide LRELHLNNN. The resulting radiotracer analogues demonstrated suitable biodistribution and dosimetry. [68Ga]Ga-DOTA-PEG2-LRELHLNNN exhibited binding to hepatic fibrotic lesions and is a promising tool for PET imaging of fibrosis.

ADVANCES IN KNOWLEDGE

Validation of a new collagen targeting PET tracer.

IMPLICATIONS FOR PATIENT CARE

Early, non-invasive diagnosis and stratification of fibrosis in order to improve the diagnosis, staging and treatment of patients with diseases involving fibrosis.

Using qualitative descriptors of chronic liver disease on MRI: A practice prone to error

PURPOSE

Assess accuracy of qualitative descriptors for chronic liver disease (CLD) in radiology reports compared to histopathological staging.

METHODS

Database search for patients with hepatitis B/C (HBV/HCV) CLD, abdominal MRI during 2009-2016, and liver biopsy within 6 months of MRI or prior biopsy showing cirrhosis. Reports reviewed for mention of CLD and associated descriptors. Findings stratified into categories: normal/no mention of CLD; changes of CLD without qualitative descriptor; mild/early; moderate; severe/advanced and cirrhosis. Descriptive ranges categorized to the lesser degree. Percent concordance/discordance of descriptors and Scheuer stage (F0-F4), false positive (FP), false negative (FN) and sensitivity/specificity calculated.

RESULTS

309 patients, median age 54 (24-74). 91% had HCV (282/309), 7% HBV and 2% both HBV/HCV. Biopsy showed 19% without CLD/F0; 8% F1, 15% F2, 15% F3 and 43% F4. 188 MRI reports (61%) stated CLD was present; however, 16 had no fibrosis on histopathology (9% FP). 39% (121/309) did not mention or stated no CLD; however, 78 had CLD on histopathology (64% FN). 59% of FN were early fibrosis (F1 or F2), 27% F3 and 11% F4. Overall sensitivity and specificity was 69% and 73%, respectively. 77% (145/188) of MRI reports used a descriptive qualifier when describing CLD. 10% were concordant with exact histopathology staging. Of discordant reports, 90% identified CLD but under-called severity.

CONCLUSION

Abdominal radiologists can detect CLD on MRI but degree of CLD is often under-called compared to histopathology suggesting radiologists should refrain from qualitative descriptors in assessing CLD on MRI and reaffirms the need for quantitative imaging.

Development and validation of radiomics model built by incorporating machine learning for identifying liver fibrosis and early-stage cirrhosis

BACKGROUND

Liver fibrosis (LF) continues to develop and eventually progresses to cirrhosis. However, LF and early-stage cirrhosis (ESC) can be reversed in some cases, while advanced cirrhosis is almost impossible to cure. Advances in quantitative imaging techniques have made it possible to replace the gold standard biopsy method with non-invasive imaging, such as radiomics. Therefore, the purpose of this study is to develop a radiomics model to identify LF and ESC.

METHODS

Patients with LF (n = 108) and ESC (n = 116) were enrolled in this study. As a control, patients with healthy livers were involved in the study (n = 145). Diffusion-weighted imaging (DWI) data sets with three b-values (0, 400, and 800 s/mm) of enrolled cases were collected in this study. Then, radiomics features were extracted from manually delineated volumes of interest. Two modeling strategies were performed after univariate analysis and feature selection. Finally, an optimal model was determined by the receiver operating characteristic area under the curve (AUC).

RESULTS

The optimal models were built in plan 1. For model 1 in plan 1, the AUCs of the training and validation cohorts were 0.973 (95% confidence interval [CI] 0.946-1.000) and 0.948 (95% CI 0.903-0.993), respectively. For model 2 in plan 1, the AUCs of the training and validation cohorts were 0.944, 95% CI 0.905 to 0.983, and 0.968, 95% CI 0.940 to 0.996, respectively.

CONCLUSIONS

Radiomics analysis of DWI images allows for accurate identification of LF and ESC, and the non-invasive biomarkers extracted from the functional DWI images can serve as a better alternative to biopsy.

Novel imaging-based approaches for predicting the hepatic venous pressure gradient in a porcine model of liver cirrhosis and portal hypertension

AIMS

Hepatic venous pressure gradient (HVPG) is critical for staging and prognosis prediction of portal hypertension (PH). However, HVPG measurement has limitations (e.g., invasiveness). This study examined the value of non-invasive, imaging-based approaches including magnetic resonance elastography (MRE) and intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for the prediction of HVPG in a porcine model of liver cirrhosis and PH.

MAIN METHODS

Male Bama miniature pigs were used to establish a porcine model of liver cirrhosis and PH induced by embolization. They were randomly assigned to an experimental group (n = 12) and control group (n = 3). HVPG was examined before and after transjugular intrahepatic portosystemic shunt (TIPS). MRE and IVIM-DWI were performed to obtain quantitative parameters including liver stiffness (LS) in MRE, tissue diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) in IVIM-DWI. The correlation between HVPG and the parameters was assessed.

KEY FINDINGS

LS values were significantly greater in the experimental group, while f values were significantly decreased at 4, 8, and 12 weeks after embolization compared to the control group. Furthermore, HVPG was significantly lower immediately after versus before TIPS. In parallel, LS and f values showed significant alterations after TIPS, and these changes were consistent with a reduction in HVPG. Spearman analysis revealed a significant correlation between the parameters (LS and f) and HVPG. The equation was eventually generated for prediction of HVPG.

SIGNIFICANCE

The findings show a good correlation between HVPG and the quantitative parameters; thus, imaging-based techniques have potential as non-invasive methods for predicting HVPG.

Diffusion-weighted imaging and texture analysis: current role for diffuse liver disease

Multiparametric MRI represents the primary imaging modality to assess diffuse liver disease, both in a qualitative and in a quantitative manner. Diffusion-weighted imaging (DWI) is among the imaging techniques that can be used to assess fibrosis due to its unique capability to assess microstructural changes at the tissue level. DWI is based on water mobility patterns and has the potential to become a non-invasive and non-destructive virtual biopsy to assess diffuse liver disease, overcoming sampling bias errors due to its three-dimensional imaging capabilities. Parallel to DWI, another quantitative method called texture analysis may be used to assess early and advanced diffused liver disease through quantifying spatial relationships in a global and local level, applying to any type of digital imaging technique like MRI or CT. Initial results using texture analysis hold great promise. In the current paper, we will review the role of DWI and texture analysis using MR images in assessing diffuse liver disease.

7-T MRI of explanted liver and ex-vivo pancreatic specimens: prospective study protocol of radiological-pathological correlation feasibility (the EXLIPSE project)

The study focuses on radiological-pathological correlation between imaging of ex vivo samples obtained by a 7-T scanner and histological examination. The specimens will be derived from native explanted cirrhotic livers, liver grafts excluded from donation because of severe steatosis, and primary pancreatic tumours. Magnetic resonance imaging (MRI) examinations will be performed within 24 h from liver or pancreatic lesion surgical removal. The MRI protocol will include morphological sequences, quantitative T1, T2, and fat-, water-fraction maps with Cartesian k-space acquisition, and multiparametric methods based on a transient-state “MRI fingerprinting”. Finally, the specimen will be fixed by formalin. Qualitative imaging analysis will be performed by two independent blinded radiologists to assess image consistency score. Quantitative analysis will be performed by drawing regions of interest on different tissue zones to measure T1 and T2 relaxation times as well as fat- and water-fraction. The same tissue areas will be analysed by the pathologists. This study will provide the possibility to improve our knowledge about qualitative and quantitative abdominal imaging assessment at 7 T, by correlating imaging characteristics and the corresponding histological composition of ex vivo specimens, in order to identify imaging biomarkers. Trial registration: ClinicalTrials.gov: 13646. Registered 9 July 2019—retrospectively registered

Resveratrol contributes to the inhibition of liver fibrosis by inducing autophagy via the microRNA‑20a‑mediated activation of the PTEN/PI3K/AKT signaling pathway

Liver fibrosis (LF) is a healing response to wounds resulting in liver injury that can cause liver failure or even cancer without functional prevention. Resveratrol (RSV) has been suggested to exert biological effects against various human diseases. MicroRNA-20a (miRNA/miR-20a) has been shown to promote disease progression. The present study aimed to assess the mechanisms through which RSV induces autophagy and activates the miR-20a-mediated phosphatase and tensin homolog (PTEN)/PI3K/AKT signaling pathway in LF. First, a rat model of carbon tetrachlo-ride (CCL₄)-induced LF and a cell model of platelet-derived growth factor (PDGF)-BB-stimulated HSC-T6 cells were established for use in subsequent experiments. Subsequently, RSV at a range of concentrations was injected into the model rats with LF. Indicators related to liver injury, oxidative stress and fibrosis were determined in the rats with LF. The RSV-treated HSC-T6 cells were subjected to transfection with miR-20a mimic and PTEN overexpression plasmid to assess the levels of liver injury and LF. A dual-luciferase reporter gene assay was performed to verify the binding sites between PTEN and miR-20a. RSV was found to alleviate LF in rats, and autophagy was enhanced in the rats with LF following RSV treatment. Furthermore, the activation of the PTEN/PI3K/AKT axis attenuated LF, which was reversed by transfection with miR-20a mimic. RSV reversed the inhibitory effects of miR-20a on PTEN expression, reducing miR-20a expression and promoting PTEN, PI3K and p-AKT protein expression, thus attenuating LF. On the whole, the present study demonstrates that RSV induces autophagy and activates the miR-20a-mediated PTEN/PI3K/AKT signaling pathway to attenuate LF. These findings may lead to the development of potential therapeutic strategies for LF.

Advances in the clinical use of collagen as biomarker of liver fibrosis

INTRODUCTION

Hepatic fibrosis is the excessive synthesis and deposition of extracellular matrix including collagen in the tissue. Chronic liver insult leads to progressive parenchymal damage, portal hypertension, and cirrhosis. Determination of hepatic collagen by invasive liver biopsy is the gold standard to estimate severity and stage of fibrosis. However, this procedure is associated with pain, carries the risk of infection and bleeding, and is afflicted with a high degree of sampling error. Therefore, there is urgent need for serological collagen-derived markers to assess collagen synthesis/turnover.

AREAS COVERED

Biochemical properties of collagens, cellular sources of hepatic collagen synthesis, and regulatory aspects in collagen expression. Markers are discussed suitable to estimate hepatic collagen synthesis and/or turnover. Discussed studies were identified through a PubMed search done in May 2020 and the authors' topic knowledge.

EXPERT OPINION

Hepatic fibrosis is mainly characterized by accumulation of collagen-rich scar tissue. Although traditionally performed liver biopsy is still standard in estimating hepatic fibrosis, there is evidence that noninvasive diagnostic scores and collagen-derived neo-epitopes provide clinical useful information. These noninvasive tests are less expensive than liver biopsy, better tolerated, safer, and more acceptable to patients. Therefore, these tests will lead to dramatic changes in diagnosis.

Efficacy of ZOOMit coronal diffusion-weighted imaging and MR texture analysis for differentiating between benign and malignant distal bile duct strictures

PURPOSE

To investigate the diagnostic efficacy of ZOOMit coronal diffusion-weighted imaging (Z-DWI) and MR texture analysis (MRTA) for differentiating benign from malignant distal bile duct strictures.

METHODS

We retrospectively enrolled a total of 71 patients with distal bile duct stricture who underwent magnetic resonance cholangiopancreatography (MRCP). For quantitative analysis, the average apparent diffusion coefficient (ADC) value at suspected stricture sites was assessed on both Z-DWI and conventional DWI (C-DWI). For qualitative analysis, two reviewers independently reviewed two image sets containing different diffusion-weighted images, and receiver operating characteristic (ROC) curve analysis was performed. Several MRTA parameters were extracted from the area of the stricture on the ADC map of the ZOOMit coronal diffusion-weighted images using commercially available software.

RESULTS

Among 71 patients, 26 patients were diagnosed with malignant stricture. On quantitative analysis, the average ADC value of the malignant and benign strictures, using Z-DWI, was 1.124 × 10^-3 mm²/s and 1.522 × 10^-3 mm²/s, respectively (P < 0.001). The average ADC value of the malignant and benign strictures, using C-DWI, was 1.107 × 10^-3 mm²/s and 1.519 × 10^-3 mm²/s, respectively (P < 0.001). On qualitative analysis, for each reviewer, the area under the ROC curve (AUC) values for differentiating benign from malignant stricture was 0.928 and 0.939, respectively, for the ZOOMit diffusion set and 0.851 and 0.824, respectively, for the conventional diffusion set. Multiple MRTA parameters showed a significantly different distribution for the benign and malignant strictures, including mean, entropy, mean of positive pixels, and kurtosis at spatial filtration values of 0, 5, and 6 mm.

CONCLUSION

The addition of Z-DWI to conventional MRCP is helpful in differentiating benign from malignant bile duct strictures, and some MRTA parameters also can be helpful in differentiating benign from malignant distal bile duct strictures.

Intravoxel incoherent motion parameters in the evaluation of chronic hepatitis B virus-induced hepatic injury: fibrosis and capillarity changes

OBJECTIVE

To evaluate the diagnostic efficacy of intravoxel incoherent motion (IVIM) parameters in hepatitis B virus (HBV)-induced hepatic fibrosis using different calculation methods and to investigate histopathologic origins.

MATERIALS AND METHODS

Liver biopsies from 37 prospectively recruited chronic hepatitis B patients were obtained. Twelve b-value (0-1000 s/mm²) diffusion-weighted imaging (DWI) was performed with a 1.5 T scanner and was followed by blinded percutaneous liver biopsy. All biopsy specimens were evaluated with Ishak staging, and the microvascular density (MVD) was calculated. Patients were classified as having no/mild (F0-1), moderate (F2-3), or marked (F4-5) fibrosis. Pseudodiffusion (D*), the perfusion fraction (f), and the apparent diffusion coefficient (ADC) were calculated using all b-values, while true diffusion (D) was calculated using all b-values [D_0-1000] and b-values greater than 200 s/mm² [D_200-1000]. Three concentric regions of interest (ROIs) (5, 10, and 20 mm) centered on the biopsy site were used.

RESULTS

D* was correlated with the MVD (p = 0.015, Pearson's r = 0.415), but f was not (p = 0.119). D_0-1000 was inversely correlated with Ishak stage (p = 0.000, Spearman's r_s =  - 0.685) and was significantly decreased in all the fibrosis groups; however, only the no/mild and marked fibrosis groups had significantly different D_200-1000 values. A pairwise comparison of receiver operating characteristic (ROC) curves of D_0-1000 and D_200-1000 showed significant differences (p = 0.039). D* was the best at discriminating early fibrosis (AUC = 0.861), while the ADC best discriminated advanced fibrosis (AUC = 0.964).

CONCLUSION

D* was correlated with the MVD and is a powerful parameter to discriminate early hepatic fibrosis. D significantly decreased with advanced fibrosis stage when using b-values less than 200 s/mm² in calculations.

MR Imaging Texture Analysis in the Abdomen and Pelvis

Add "which is a" before "distribution"? Texture analysis (TA) is a form of radiomics that refers to quantitative measurements of the histogram, distribution and/or relationship of pixel intensities or gray scales within a region of interest on an image. TA can be applied to MR images of the abdomen and pelvis, with the main strength quantitative analysis of pixel intensities and heterogeneity rather than subjective/qualitative analysis. There are multiple limitations of MRTA. Despite these limitations, there is a growing body of literature supporting MRTA. This review discusses application of MRTA to the abdomen and pelvis.

The Value of TTPVI in Prediction of Microvascular Invasion in Hepatocellular Carcinoma

Purpose

The objective of our study was to evaluate the value of two-trait predictor of venous invasion (TTPVI) in the prediction of pathological microvascular invasion (pMVI) in patients with hepatocellular carcinoma (HCC) from preoperative computed tomography (CT) and magnetic resonance (MR).

Methods

A total of 128 preoperative patients with findings of HCC were enrolled. Tumor size, tumor margins, tumor capsule, peritumoral enhancement, and TTPVI was assessed on preoperative CT and MRI images. Histopathological features were reviewed: pathological tumor size, tumor differentiation, pMVI along with alpha-fetoprotein level (AFP). Significant imaging findings and histopathological features were determined with univariate and multivariate logistic regression analysis.

Results

Univariate analysis revealed that tumor size (p<0.01), AFP level (p=0.043), tumor differentiation (p<0.01), peritumoral enhancement (p=0.003), pathological tumor size (p<0.01), tumor margins (p<0.01) on CT and MRI, and TTPVI (p<0.01) showed statistically significant associations with pMVI. In multivariate logistic regression analysis, tumor size (odds ratio [OR] = 1.294; 95% confidence interval [CI]: 1.155, 1.451; p < 0.001), tumor differentiation (odds ratio [OR] =1.384; 95% confidence interval [CI]: 1.224, 1.564; p < 0.001), and TTPVI (odds ratio [OR] = 4.802; 95% confidence interval [CI]: 1.037, 22.233; p=0.045) were significant independent predictors of pMVI. Using 5.8 as the threshold for size, one could obtain an area-under-curve (AUC) of 0.793, 95% confidence interval [CI]: 0.715 to 0.857.

Conclusion

Tumor size, tumor differentiation, and TTPVI depicted in preoperative CT and MRI had a statistically significant correlation with pMVI. Hence, TTPVI detected on CT and MRI may be predictive of pMVI in HCC cases.

Indications for abdominal imaging: When and what to choose?

Imaging has a very important role in evaluating abdominal pathology. A good knowledge of indications is of crucial importance in the management of the patient with abdominal pathology. Ultrasound, which on its own can lead to an accurate diagnosis, plays a pivotal role in the management of abdominal pathology. The use of ultrasound contrast agents has significantly improved ultrasound diagnostic capacities in both hepatic and non-hepatic pathology. The use of computed tomography should be limited due to the potential harmful side effects of ionizing radiation, but it has established roles in evaluating severe abdominal traumatic and non-traumatic emergencies as well as in staging oncologic patients. Magnetic resonance imaging has very limited utility in abdominal emergencies due to difficulty of accessing the scanner and the long duration of the examination compared to computed tomography or ultrasound. However, magnetic resonance imaging has well-established clinical roles particularly for evaluating diffuse or focal hepatic pathology, benign and malignant bile duct pathology, pancreatic tumors, inflammatory bowel disease and rectal tumors. The aims of the following paper are to familiarize the clinician with the indications for imaging in abdominal pathology, to guide the clinician and radiologist in choosing the correct technique for a particular clinical situation, to prevent the overuse of imaging techniques and to prevent misdiagnosis of disease and incorrect therapy resulting from inappropriate imaging.

Imaging has a very important role in evaluating abdominal pathology. A good knowledge of indications is of crucial importance in the management of the patient with abdominal pathology. Ultrasound, which on its own can lead to an accurate diagnosis, plays a pivotal role in the management of abdominal pathology. The use of ultrasound contrast agents has significantly improved ultrasound diagnostic capacities in both hepatic and non-hepatic pathology. The use of computed tomography should be limited due to the potential harmful side effects of ionizing radiation, but it has established roles in evaluating severe abdominal traumatic and non-traumatic emergencies as well as in staging oncologic patients. Magnetic resonance imaging has very limited utility in abdominal emergencies due to difficulty of accessing the scanner and the long duration of the examination compared to computed tomography or ultrasound. However, magnetic resonance imaging has well-established clinical roles particularly for evaluating diffuse or focal hepatic pathology, benign and malignant bile duct pathology, pancreatic tumors, inflammatory bowel disease and rectal tumors. The aims of the following paper are to familiarize the clinician with the indications for imaging in abdominal pathology, to guide the clinician and radiologist in choosing the correct technique for a particular clinical situation, to prevent the overuse of imaging techniques and to prevent misdiagnosis of disease and incorrect therapy resulting from inappropriate imaging.

Current Imaging Techniques for Noninvasive Staging of Hepatic Fibrosis

OBJECTIVE. The purpose of this article is to discuss quantitative methods of CT, MRI, and ultrasound (US) for noninvasive staging of hepatic fibrosis. Hepatic fibrosis is the hallmark of chronic liver disease (CLD), and staging by random liver biopsy is invasive and prone to sampling errors and subjectivity. Several noninvasive quantitative imaging methods are under development or in clinical use. The accuracy, precision, technical aspects, advantages, and disadvantages of each method are discussed. CONCLUSION. The most promising methods are the liver surface nodularity score using CT and measurement of liver stiffness using MR elastography or US elastography.

Diagnostic value of MR-based texture analysis for the assessment of hepatic fibrosis in patients with nonalcoholic fatty liver disease (NAFLD)

PURPOSE

To investigate the performance of MR-based texture analysis (TA) for the assessment of hepatic fibrosis in patients with nonalcoholic fatty liver disease (NAFLD).

METHODS

Fifty-four adult patients (33 females, 21 males, mean age 49.8 ± 13.5 years) with biopsy-proven NAFLD were enrolled and underwent MR imaging on a 1.5 T system. TA parameters were extracted on axial noncontrast 3D-GRE T1W images (slice thickness = 4.6 mm) using a commercially available research software (TexRAD). Receiver operating curves (ROC), areas under the ROC (AUROC) and 95% confidence intervals (CI) were calculated to assess the accuracy of each TA parameter for the diagnosis of significant (F ≥ 2) and advanced fibrosis (F ≥ 3). The correlation between TA and histopathological features of nonalcoholic steatohepatitis (NASH) was tested calculating the Spearman's rank correlation coefficient (ρ).

RESULTS

Thirty-seven (68%) subjects had significant fibrosis and 20 (37%) had advanced fibrosis. The TA parameters with the best performance were standard deviation (SD) and entropy, respectively, with AUROC 0.755 (95% CI 0.619-0.862, p ≤ 0.0002) and 0.769 (95% CI 0.634-0.873, p < 0.0001) for significant fibrosis and AUROC 0.746 (95% CI 0.609-0.854, p ≤ 0.0004) and 0.754 (95% CI 0.618-0.861, p ≤ 0.0002) for advanced fibrosis. SD and entropy demonstrated a moderate correlation with the degree of fibrosis (ρ = 0.457 and 0.480; p < 0.01). No significant correlation was found between TA parameters and other histopathological features of NASH.

CONCLUSIONS

Entropy and SD extracted on T1-weighted MR images have fair accuracy for the diagnosis of significant and advanced hepatic fibrosis in patients with NAFLD.

Liver Fibrosis Conventional and Molecular Imaging Diagnosis Update

Liver fibrosis is a serious, life-threatening disease with high morbidity and mortality that result from diverse causes. Liver biopsy, considered the "gold standard" to diagnose, grade, and stage liver fibrosis, has limitations in terms of invasiveness, cost, sampling variability, inter-observer variability, and the dynamic process of fibrosis. Compelling evidence has demonstrated that all stages of fibrosis are reversible if the injury is removed. There is a clear need for safe, effective, and reliable non-invasive assessment modalities to determine liver fibrosis in order to manage it precisely in personalized medicine. However, conventional imaging methods used to assess morphological and structural changes related to liver fibrosis, including ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), are only useful in assessing advanced liver disease, including cirrhosis. Functional imaging techniques, including MR elastography (MRE), US elastography, and CT perfusion are useful for assessing moderate to advanced liver fibrosis. MRE is considered the most accurate noninvasive imaging technique, and US elastography is currently the most widely used noninvasive means. However, these modalities are less accurate in early-stage liver fibrosis and some factors affect the accuracy of these techniques. Molecular imaging is a target-specific imaging mechanism that has the potential to accurately diagnose early-stage liver fibrosis. We provide an overview of recent advances in molecular imaging for the diagnosis and staging of liver fibrosis which will enable clinicians to monitor the progression of disease and potentially reverse liver fibrosis. We compare the promising technologies with conventional and functional imaging and assess the utility of molecular imaging in precision and personalized clinical medicine in the early stages of liver fibrosis.

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.