Accuracy of liver surface nodularity quantification on MDCT for staging hepatic fibrosis in patients with hepatitis C virus

Acquisition Efficiency and Technical Repeatability of Dual-Frequency 3D Vector MR Elastography of the Liver

BACKGROUND

MR elastography (MRE) at 60 Hz is widely used for staging liver fibrosis. MRE with lower frequencies may provide inflammation biomarkers.

PURPOSE

To establish a practical simultaneous dual-frequency liver MRE protocol at both 30 Hz and 60 Hz during a single examination and validate the occurrence of second harmonic waves at 30 Hz.

STUDY TYPE

Retrospective.

SUBJECTS

One hundred six patients (48 females, age: 50.0 ± 13.4 years) were divided as follows: Cohort One (15 patients with chronic liver disease [CLD] and 25 healthy volunteers) with simultaneous dual-frequency MRE. Cohort Two (66 patients with CLD) with second harmonic MRE.

FIELD STRENGTH/SEQUENCE

3-T, single- or dual-frequency MRE at 30 Hz and 60 Hz.

ASSESSMENT

Liver stiffness (LS) in both cohorts was evaluated with manually placed volumetric ROIs by two independent analyzers. Image quality was assessed by three independent readers on a 4-point scale (0-3: none/failed, fair, moderate, excellent) based on the depth of wave propagation with 1/3 incremental penetration. The success rate was derived from the percentage of nonzero quality scores.

STATISTICAL TESTS

Measurement agreement, bias, and repeatability of LS were assessed using intraclass correlation coefficients (ICCs), Bland-Altman plots, and repeatability coefficient (RC). Mann-Whitney U tests were used to evaluate the differences in image quality between different methods. A P-value <0.05 was considered statistically significant.

RESULTS

Success rate was 97.5% in Cohort One and 91% success rate for the second harmonic MRE in Cohort Two. The second harmonic and conventional MRE showed excellent agreement in LS (all ICCs >0.90). The quality scores for the second harmonic wave images were lower than those from the conventional MRE (Z = -4.523).

DATA CONCLUSION

Compared with conventional and second harmonic methods, simultaneous dual-frequency had better image quality, high success rate and the advantage of intrinsic co-registration, while the second harmonic method can be an alternative if custom waveform is not available.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 1.

Noninvasive diagnosis of liver cirrhosis: qualitative and quantitative imaging biomarkers

A diagnosis of cirrhosis initiates a shift in the management of chronic liver disease and affects the diagnostic workflow and treatment decision of primary liver cancer. Liver biopsy remains the gold standard for cirrhosis diagnosis, but it is invasive and susceptible to sampling bias and observer variability. Various qualitative and quantitative imaging biomarkers based on ultrasound, CT and MRI have been proposed for noninvasive diagnosis of cirrhosis. Qualitative imaging features are easy to apply but have moderate diagnostic sensitivity. Elastography techniques allow quantitative assessment of liver stiffness and are highly accurate for cirrhosis diagnosis. Ultrasound elastography are widely used in clinical practice, while MR elastography has narrower availability. Although not applicable in clinical practice yet, other quantitative imaging features, including liver surface nodularity, linear and volumetric measurement, extracellular volume fraction, liver enhancement on hepatobiliary phase, and parameters derived from diffusion-weighted imaging, can provide additional information of liver morphology, perfusion, and function, thus may increase diagnosis performance. The introduction of radiomics and deep learning has further improved diagnostic accuracy while reducing subjectivity. Several imaging features may also help to assess liver function and outcomes in patients with cirrhosis. In this review, we summarize the qualitative and quantitative imaging biomarkers for noninvasive cirrhosis diagnosis, and the assessment of liver function and outcomes, and discuss the challenges and future directions in this field.

Conventional and artificial intelligence-based computed tomography and magnetic resonance imaging quantitative techniques for non-invasive liver fibrosis staging

Chronic liver disease (CLD) ultimately develops into liver fibrosis and cirrhosis and is a major public health problem globally. The assessment of liver fibrosis is important for patients with CLD for prognostication, treatment decisions, and surveillance. Liver biopsies are traditionally performed to determine the stage of liver fibrosis. However, the risks of complications and technical limitations restrict their application to screening and sequential monitoring in clinical practice. CT and MRI are essential for evaluating cirrhosis-associated complications in patients with CLD, and several non-invasive methods based on them have been proposed. Artificial intelligence (AI) techniques have also been applied to stage liver fibrosis. This review aimed to explore the values of conventional and AI-based CT and MRI quantitative techniques for non-invasive liver fibrosis staging and summarized their diagnostic performance, advantages, and limitations.

Reproducibility of MRI-derived liver surface nodularity score: analysis of patients with repeated MRI in various scanners

PURPOSE

To assess trans-regional differences, reproducibility across different MRI scanners, and interobserver agreement of liver surface nodularity (LSN) score from routine liver MRI and to evaluate the correlation between LSN score and liver stiffness (LS) value on MR elastography.

MATERIALS AND METHODS

Ninety patients who underwent gadoxetic acid-enhanced liver MRI twice using different MRI scanners within a year were evaluated. On axial hepatobiliary phase images, right anterior (LSN_{RT_ANT}), right posterior (LSN_{RT_POST}), and left anterior hepatic surface (LSN_LT) were chosen for the quantification of LSN score. Repeated-measures ANOVA, paired t test, Pearson's correlation coefficient analysis, and intraclass correlation coefficient (ICC) were used for statistical analysis.

RESULTS

LSN scores from high to low were LSN_{RT_POST}, LSN_{RT_ANT}, and LSN_LT, representing trans-regional differences (p < 0.001). Reproducibility of LSN measurement across different MRI scanners was high to excellent (ICC = 0.838-0.921). The mean difference between first and second examinations in LSN_{RT_ANT}, LSN_{RT_POST}, and LSN_LT were 0.032 (p = 0.013), 0.002 (p = 0.910), and 0.010 (p = 0.285) for reader 1 and 0.051 (p = 0.004), 0.061 (p = 0.002), and 0.023 (p = 0.005) for reader 2. The first and second examinations were highly correlated in all hepatic regions (r = 0.712-0.839, p < 0.001). There was a low to moderate correlation between LSN score and LS value (r = 0.364-0.592, p ≤ 0.001), which was higher in the chronic hepatitis B (CHB) group than in the non-CHB group in all hepatic regions.

CONCLUSIONS

In our study, LSN measurement on liver MRI showed trans-regional differences and excellent reproducibility across different MRI scanners. To use LSN score more widely, standardization of quantification software and selected hepatic regions is needed.

Noninvasive staging of liver fibrosis: review of current quantitative CT and MRI-based techniques

Liver fibrosis features excessive protein accumulation in the liver interstitial space resulting from repeated tissue injury due to chronic liver disease. Liver fibrosis eventually proceeds to cirrhosis and associated complications. So, early diagnosis and staging of liver fibrosis are of vital importance for clinical treatment. Liver biopsy remains the gold standard for the diagnosing and staging of fibrosis, but it is suboptimal due to various limitations. Recently, efforts have been made to migrate toward noninvasive techniques for assessing liver fibrosis. CT is relatively easy to perform, relatively standardized for different scanners, and does not require additional hardware in liver fibrosis staging. MRI is frequently performed to characterize indeterminate liver lesions. Because it does not use ionizing radiation and features high image contrast, its role has increased in the staging of liver fibrosis. More recently, several studies on liver fibrosis staging using deep learning algorithms in CT or MRI have been proposed and have shown meaningful results. In this review, we summarize the basic concept, diagnostic performance, and advantages and limitations of each technique to noninvasively stage liver fibrosis.

Rethinking Liver Fibrosis Staging in Patients with Hepatocellular Carcinoma: New Insights from a Large Two-Center Cohort Study

Background

Hepatocellular carcinoma (HCC) is a prevalent and aggressive malignancy closely related to background chronic liver disease. This study aimed to explore predictive factors associated with background liver fibrosis burden in patients with HCC and sought to construct a practical predictive model for clinical use.

Methods

This large two-center retrospective cohort study evaluated data from Chinese medical centers. Uni- and multivariate ordinal logistic regression analyses were performed to identify variables associated with liver fibrosis stages. Predictive models based on variables identified by multivariate analysis were established in the Derivation Cohort and subjected to internal and external validation. Model performance was evaluated for discriminative and calibration abilities.

Results

Multivariate ordinal logistic regression analysis identified liver fibrosis severity score (LFSS), portal hypertension (PH) severity, plateletcrit (PCT) and model for end-stage liver disease-sodium (MELD-Na) as independent predictors of liver fibrosis stage in HCC patients. Nomograms that integrated these factors disclosed that the area under receiver operating characteristic curves (AUROCs) to predict S1 in the Derivation and External Validation cohorts were 0.850 and 0.919, respectively. Internal validation disclosed C-indexes of 0.823 and 0.833 in the Derivation and External Validation cohorts, respectively, indicating that the nomogram had good and excellent performance for distinguishing between S1 and non-S1 patients. Nomogram performance in the Derivation and External Validation cohorts, respectively, was fair and good to predict stage S2 (AUROCs 0.726, 0.806; C-indexes 0.713, 0.791); poor for S3 (AUROCs 0.648, 0.698; C-indexes 0.616, 0.666); good for S4 (AUROCs 0.812, 0.824; C-indexes 0.804, 0.792); and good for S3+S4 (AUROCs 0.806, 0.840; C-indexes 0.795, 0.811).

Conclusion

We propose new predictive models for the staging of background liver fibrosis in patients with HCC that can be implemented into clinical practice as important complements to hepatic imaging to inform HCC management strategy.

Contrast-enhanced CT and liver surface nodularity for the diagnosis of porto-sinusoidal vascular disorder: A case-control study

BACKGROUND AND AIMS

Porto-sinusoidal vascular disorder (PSVD) is a rare and commonly overlooked cause of portal hypertension. The interest of CT analysis, including quantification of liver surface nodularity (LSN) for PSVD diagnosis has not been established. This study aimed at assessing the performance of LSN and CT features for a PSVD diagnosis in patients with signs of portal hypertension.

APPROACH AND RESULTS

This retrospective case-control study included a learning cohort consisting of 50 patients with histologically proven PSVD, according to VALDIG criteria, and 100 control patients with histologically proven cirrhosis, matched on ascites. All patients and controls had at least one sign of portal hypertension and CT available within 1 year of liver biopsy. Principal component analysis of CT features separated patients with PSVD from patients with cirrhosis. Patients with PSVD had lower median LSN than those with cirrhosis (2.4 vs. 3.1, p < 0.001). Multivariate analysis identified LSN < 2.5 and normal-sized or enlarged segment IV as independently associated with PSVD. Combination of these two features had a specificity of 90% for PSVD and a diagnostic accuracy of 84%. Even better results were obtained in an independent multicenter validation cohort including 53 patients with PSVD and 106 control patients with cirrhosis (specificity 94%, diagnostic accuracy 87%).

CONCLUSIONS

This study that included a total of 103 patients with PSVD and 206 patients with cirrhosis demonstrates that LSN < 2.5 combined with normal-sized or enlarged segment IV strongly suggests PSVD in patients with signs of portal hypertension.

Multiinstitutional Evaluation of the Liver Surface Nodularity Score on CT for Staging Liver Fibrosis and Predicting Liver-Related Events in Patients With Hepatitis C

BACKGROUND. In single-institution multireader studies, the liver surface nodularity (LSN) score accurately detects advanced liver fibrosis and cirrhosis and predicts liver decompensation in patients with chronic liver disease (CLD) from hepatitis C virus (HCV). OBJECTIVE. The purpose of this study was to assess the diagnostic performance of the LSN score alone and in combination with the (FIB-4; fibrosis index based on four factors) to detect advanced fibrosis and cirrhosis and to predict future liver-related events in a multiinstitutional cohort of patients with CLD from HCV. METHODS. This retrospective study included 40 consecutive patients, from each of five academic medical centers, with CLD from HCV who underwent nontargeted liver biopsy within 6 months before or after abdominal CT. Clinical data were recorded in a secure web-based database. A single central reader measured LSN scores using software. Diagnostic performance for detecting liver fibrosis stage was determined. Multivariable models were constructed to predict baseline liver decompensation and future liver-related events. RESULTS. After exclusions, the study included 191 patients (67 women, 124 men; mean age, 54 years) with fibrosis stages of F0-F1 (n = 37), F2 (n = 44), F3 (n = 46), and F4 (n = 64). Mean LSN score increased with higher stages (F0-F1, 2.26 ± 0.44; F2, 2.35 ± 0.37; F3, 2.42 ± 0.38; F4, 3.19 ± 0.89; p < .001). The AUC of LSN score alone was 0.87 for detecting advanced fibrosis (≥ F3) and 0.89 for detecting cirrhosis (F4), increasing to 0.92 and 0.94, respectively, when combined with FIB-4 scores (both p = .005). Combined scores at optimal cutoff points yielded sensitivity of 75% and specificity of 82% for advanced fibrosis, and sensitivity of 84% and specificity of 85% for cirrhosis. In multivariable models, LSN score was the strongest predictor of baseline liver decompensation (odds ratio, 14.28 per 1-unit increase; p < .001) and future liver-related events (hazard ratio, 2.87 per 1-unit increase; p = .03). CONCLUSION. In a multiinstitutional cohort of patients with CLD from HCV, LSN score alone and in combination with FIB-4 score exhibited strong diagnostic performance in detecting advanced fibrosis and cirrhosis. LSN score also predicted future liver-related events. CLINICAL IMPACT. The LSN score warrants a role in clinical practice as a quantitative marker for detecting advanced liver fibrosis, compensated cirrhosis, and decompensated cirrhosis and for predicting future liver-related events in patients with CLD from HCV.

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.

Intraindividual comparison of MRI-derived liver surface nodularity score at 1.5 T and 3 T

PURPOSE

To compare the MRI-derived liver surface nodularity (LSN) scores acquired on both 1.5 T and 3 T.

MATERIALS AND METHODS

Forty chronic liver disease patients who underwent gadoxetic acid-enhanced MRI at both 1.5 and 3 T were included. Axial hepatobiliary phase images with the same voxel size were used to calculate the LSN score in both liver lobes with a quantitative software. Rank correlation, Wilcoxon test, and Bland-Altman limits of agreement were used for statistical analysis.

RESULTS

There was a weak correlation between the right and left liver lobe on 1.5 T (r_s = 0.331, p = 0.037) and 3 T (r_s = 0.381, p = 0.015). The correlation between 1.5 T and 3 T on both liver lobes showed a very strong correlation (right, r_s = 0.927, p < 0.001; left, r_s = 0.845, p < 0.001). LSN scores differed significantly between both lobes on 1.5 T (median, 1.201 vs. 0.674, right vs. left) and 3 T (1.076 vs. 0.592) (all p < 0.001). LSN scores differed significantly between 1.5 T and 3 T on both lobes (all p < 0.001). The Bland-Altman plot comparing 1.5 T and 3 T on right and left liver lobes showed a systemic bias of 0.08 and 0.07, respectively.

CONCLUSIONS

LSN scores differed significantly on 1.5 T vs. 3 T and right vs. left liver lobe. Caution should be made when comparing LSN scores derived from different field strengths or the hepatic lobe. Interplatform, interlobar reproducibility should be resolved to use LSN scores, which is relatively easy to perform without additional hardware or images.

Non-invasive precise staging of liver fibrosis using deep residual network model based on plain CT images

PURPOSE

The aim of this study was to explore the application of five-class deep residual network models based on plain CT images and clinical features for the precise staging of liver fibrosis.

METHODS

This retrospective clinical study included 347 patients who underwent liver CT, with pathological staging of liver fibrosis as the gold standard. We established three ResNet models to stage liver fibrosis. The output diagnosis labels of models were 0, 1, 2, 3 and 4, which correspond to F0, F1, F2, F3, and F4 stages. Confusion matrices were used to evaluate the performances of models to precisely stage liver fibrosis. The performance for diagnosing cirrhosis (F4), advanced fibrosis (≥ F3) and significant fibrosis (≥ F2) of models was evaluated with receiver operating characteristic (ROC) analyses.

RESULTS

The kappa coefficients of the five-class ResNet model (based on plain CT images), the five-class ResNet clinical model (based on clinical features), and the five-class mixed ResNet model (based on plain CT images and clinical features) for precise staging liver fibrosis were 0.566, 0.306, and 0.63, respectively. The recall rates and precision rates for F0, F1, F2, and F3 of three models were lower than 60%. The ROC AUC values of the five-class ResNet model, the five-class ResNet clinical model, and the five-class mixed ResNet model for diagnosing cirrhosis, advanced fibrosis, and significant fibrosis were 0.95, 0.88, and 0.82, 0.80, 0.72, and 0.70, 0.95, 0.90, and 0.83, respectively.

CONCLUSIONS

The five-class ResNet models are of high value in the diagnosis of liver cirrhosis, advanced liver fibrosis, and significant liver fibrosis. However, for the precise staging of liver fibrosis, the models cannot accurately distinguish other liver fibrosis stages except F4. Plain CT images combined with clinical features have the potential to improve the performance of the ResNet models in diagnosing liver fibrosis.

Multicenter study on recent portal venous system thrombosis associated with cytomegalovirus disease

BACKGROUND & AIMS

Recent non-malignant non-cirrhotic portal venous system thrombosis (PVT) is a rare condition. Among risk factors for PVT, cytomegalovirus (CMV) disease is usually listed based on a small number of reported cases. The aim of this study was to determine the characteristics and outcomes of PVT associated with CMV disease.

METHODS

We conducted a French multicenter retrospective study comparing patients with recent PVT and CMV disease ("CMV positive"; n = 23) to patients with recent PVT for whom CMV testing was negative ("CMV negative"; n = 53) or unavailable ("CMV unknown"; n = 297).

RESULTS

Compared to patients from the "CMV negative" and "CMV unknown" groups, patients from the "CMV positive" group were younger, more frequently had fever, and had higher heart rate, lymphocyte count and serum ALT levels (p ≤0.01 for all). The prevalence of immunosuppression did not differ between the 3 groups (4%, 4% and 6%, respectively). Extension of PVT was similar between the 3 groups. Thirteen out of 23 "CMV positive" patients had another risk factor for thrombosis. Besides CMV disease, the number of risk factors for thrombosis was similar between the 3 groups. Heterozygosity for the prothrombin G20210A gene variant was more frequent in "CMV positive" patients (22%) than in the "CMV negative" (4%, p = 0.01) and "CMV unknown" (8%, p = 0.03) groups. Recanalization rate was not influenced by CMV status.

CONCLUSIONS

In patients with recent PVT, features of mononucleosis syndrome should raise suspicion of CMV disease. CMV disease does not influence thrombosis extension nor recanalization. More than half of "CMV positive" patients have another risk factor for thrombosis, with a particular link to the prothrombin G20210A gene variant.

LAY SUMMARY

Patients with cytomegalovirus (CMV)-associated portal venous system thrombosis have similar thrombosis extension and evolution as patients without CMV disease. However, patients with CMV-associated portal venous system thrombosis more frequently have the prothrombin G20210A gene variant, suggesting that these entities act synergistically to promote thrombosis.

Liver segmental volume and attenuation ratio (LSVAR) on portal venous CT scans improves the detection of clinically significant liver fibrosis compared to liver segmental volume ratio (LSVR)

Background

The aim of this proof-of-concept study was to show that the liver segmental volume and attenuation ratio (LSVAR) improves the detection of significant liver fibrosis on portal venous CT scans by adding the liver vein to cava attenuation (LVCA) to the liver segmental volume ratio (LSVR).

Material and methods

Patients who underwent portal venous phase abdominal CT scans and MR elastography (reference standard) within 3 months between 02/2016 and 05/2017 were included. The LSVAR was calculated on portal venous CT scans as LSVR*LVCA, while the LSVR represented the volume ratio between Couinaud segments I-III and IV-VIII, and the LVCA represented the density of the liver veins compared to the density in the vena cava. The LSVAR and LSVR were compared between patients with and without significantly elevated liver stiffness (based on a cutoff value of 3.5 kPa) using the Mann–Whitney U test and ROC curve analysis.

Results

The LSVR and LSVAR allowed significant differentiation between patients with (n = 19) and without (n = 122) significantly elevated liver stiffness (p < 0.001). However, the LSVAR showed a higher area under the curve (AUC = 0.96) than the LSVR (AUC = 0.74). The optimal cutoff value was 0.34 for the LSVR, which detected clinically increased liver stiffness with a sensitivity of 53% and a specificity of 88%. With a cutoff value of 0.67 for the LSVAR, the sensitivity increased to 95% while maintaining a specificity of 89%.

Conclusion

The LSVAR improves the detection of significant liver fibrosis on portal venous CT scans compared to the LSVR.

Liver Fibrosis Assessment

Early diagnosis of hepatic fibrosis (HF) is pivotal for management to cease progression to cirrhosis and hepatocellular carcinoma. HF is the telltale sign of chronic liver disease, and confirmed by liver biopsy, which is an invasive technique and inclined to sampling errors. The morphologic parameters of cirrhosis are assessed on conventional imaging such as on ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI). Newer imaging modalities such as magnetic resonance elastography and US elastography are reliable and accurate. More research studies on novel imaging modalities such as MRI with diffusion weighted imaging, enhancement by hepatobiliary contrast agents, and CT using perfusion are essential for earlier diagnosis, surveillance and accurate management. The purpose of this article is to discuss non-invasive CT, MRI, and US imaging modalities for diagnosis and stratify HF.

Imaging Biomarkers of Hepatic Fibrosis: Reliability and Accuracy of Hepatic Periportal Space Widening and Other Morphologic Features on MRI

OBJECTIVE. The purpose of this article was to assess the reliability and accuracy of hepatic periportal space widening and other qualitative imaging features for the prediction of hepatic fibrosis. MATERIALS AND METHODS. This single-center retrospective study identified consecutive patients who had undergone liver MR elastography. Two abdominal radiologists independently reviewed anatomic images, assessing multiple qualitative features of chronic liver disease (CLD) including periportal space widening. Each reader also measured the periportal space at the main portal vein (MPV) and right portal vein (RPV). Interrater reliability analysis was then performed. Sensitivity and specificity were determined for the detection of any hepatic fibrosis (stage I or higher) and of advanced fibrosis (stage III or higher) using stiffness on MR elastography as the reference standard. RESULTS. Of 229 subjects, 157 (69%) had fibrosis and 78 (34%) had advanced fibrosis. Agreement for periportal space widening was moderate (κ = 0.47), and agreement for remaining features was moderate to substantial (κ = 0.42-0.80). Agreement for the periportal space at the MPV was moderate (ICC, 0.55), and agreement for the periportal space at the RPV was near perfect (ICC, 0.83). Periportal space widening had the highest sensitivity (83.0%) for any fibrosis, with limited specificity (61.3%). Surface nodularity had the highest specificity (94.4%) for any fibrosis, with limited sensitivity (51.6%). Periportal space widening plus one or more additional imaging feature of CLD or the presence of surface nodularity alone had sensitivity of 72.6% and specificity of 76.1%. A periportal space at the MPV greater than 9.5 mm had substantial agreement with qualitative periportal space widening (κ = 0.74). CONCLUSION. Periportal space widening has a high sensitivity for hepatic fibrosis, with moderate specificity when combined with additional anatomic features of CLD.

Staging of Liver Fibrosis by Means of Semiautomatic Measurement of Liver Surface Nodularity in MRI

OBJECTIVE. The purposes of this study were to evaluate the accuracy of a semiautomatic method of measuring liver surface nodularity (LSN) on contrast-enhanced MR images and to compare the LSN score with pathologic fibrosis stage. MATERIALS AND METHODS. This retrospective study included patients who had undergone gadoxetate disodium-enhanced liver MRI 6 months before or after histopathologic investigation including percutaneous parenchymal biopsy and surgical biopsy for staging of chronic liver disease between January 2010 and December 2018. Semiautomated LSN quantification software was developed to measure LSN at MRI. Aspartate aminotransferase to platelet ratio index and fibrosis-4 index were derived from serum laboratory test results. The reference standard for staging of liver fibrosis was Metavir score. The accuracy of LSN score for staging of liver fibrosis was evaluated with AUC, and the optimal cutoff value was calculated by Youden index. Spearman correlation coefficient was used for correlation analysis. RESULTS. The study included 132 patients (93 men, 39 women). LSN score was evaluated without technical failure. There was high correlation between LSN score and Metavir score (Spearman ρ = 0.713, p < 0.001). The AUCs of LSN score for distinguishing Metavir score were 0.93 for F0-F1 versus F2-F4 (95% CI, 0.88-0.97; p < 0.001), 0.98 for F0-F2 vs F3-F4 (95% CI, 0.95-1.00; p < 0.001), and 0.83 for F0-F3 versus F4 (95% CI, 0.76-0.90; p < 0.001). The optimal cutoff value for differentiating F0-F2 from F3-F4 was 0.850 with 100% sensitivity and 85.4% specificity. CONCLUSION. LSN score calculated semiautomatically from MR images of the liver has high accuracy and correlates directly with the pathologic fibrosis stage.

CT-based liver surface nodularity for the detection of clinically significant portal hypertension: defining measurement quality criteria

PURPOSE

To establish measurement quality criteria for the noninvasive assessment of clinically significant portal hypertension (CSPH) in patients with cirrhosis using CT-based liver surface nodularity (LSN) measurements.

METHODS

Seventy-four consecutive patients with cirrhosis (mean 62 ± 13 years), including 30 with CSPH (41%), underwent CT and hepatic venous pressure gradient measurements. Three independent readers performed 15 LSN measurements/patient using dedicated software. LSN was computed based on the median and means of one to 15 measurements. Accuracy for diagnosing CSPH was assessed using receiver operating characteristic (ROC) curve analysis. Variability was assessed by the intra-class correlation coefficient (ICC) and the Bland-Altman plot (BA). Quality criteria were identified to maximize the accuracy of LSN and minimize variability.

RESULTS

The area under the (AU) ROCs of mean and median LSN measurements based on one to 15 measurements ranged from 0.79 ± 0.05 to 0.91 ± 0.04 and 0.86 ± 0.04 to 0.91 ± 0.03, respectively, with no difference on pair-wise comparisons (all p > 0.05). AUROCs of LSN increased from one to eight and leveled off between eight and 15 measurements. Inter- and intra-reader variability decreased from one to 15 measurements, with only slight improvement after more than eight measurements. Intra- and inter-observer agreements were excellent with eight measurements (ICC = 0.90 [95%CI 0.84-0.94], and ICC = 0.93 [95%CI 0.89-0.95], respectively), and variability for intra-observer and inter-observer agreement was low (BA bias 4.2% (95% limits of agreement [LoA] [- 15.3; + 23.7%]) and 4.8% LoA [ - 17.5; + 27.1%], respectively).

CONCLUSIONS

CT-based LSN measurement is highly reproducible and accurate. We suggest using at least 8 valid measurements to determine the mean LSN value for the detection of CSPH.

Usefulness of Different Imaging Modalities in Evaluation of Patients with Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are becoming some of the major health problems in well-developed countries, together with the increasing prevalence of obesity, metabolic syndrome, and all of their systemic complications. As the future prognoses are even more disturbing and point toward further increase in population affected with NAFLD/NASH, there is an urgent need for widely available and reliable diagnostic methods. Consensus on a non-invasive, accurate diagnostic modality for the use in ongoing clinical trials is also required, particularly considering a current lack of any registered drug for the treatment of NAFLD/NASH. The aim of this narrative review was to present current information on methods used to assess liver steatosis and fibrosis. There are several imaging modalities for the assessment of hepatic steatosis ranging from simple density analysis by computed tomography or conventional B-mode ultrasound to magnetic resonance spectroscopy (MRS), magnetic resonance imaging proton density fat fraction (MRI-PDFF) or controlled attenuation parameter (CAP). Fibrosis stage can be assessed by magnetic resonance elastography (MRE) or different ultrasound-based techniques: transient elastography (TE), shear-wave elastography (SWE) and acoustic radiation force impulse (ARFI). Although all of these methods have been validated against liver biopsy as the reference standard and provided good accuracy, the MRS and MRI-PDFF currently outperform other methods in terms of diagnosis of steatosis, and MRE in terms of evaluation of fibrosis.

Diagnostic value of MRI-derived liver surface nodularity score for the non-invasive quantification of hepatic fibrosis in non-alcoholic fatty liver disease

OBJECTIVES

To assess the accuracy of MRI-derived liver surface nodularity (LSN) score for staging of hepatic fibrosis in patients with non-alcoholic fatty liver disease (NAFLD).

METHODS

Forty-seven patients with clinicopathological diagnosis of NAFLD who underwent 1.5-T liver MRI within 12 months of liver biopsy were included. Axial non-contrast T1-weighted 3D GRE was used for image analysis. LSN of the left lobe was measured using a custom semiautomated software. Histopathologic analysis (F0-F4) served as the reference standard for staging of fibrosis. Mann-Whitney test and Spearman's correlation coefficient were used to compare LSN scores between different stages of fibrosis and to assess the correlation. Diagnostic performance of LSN score for detection of significant (F2-F4) and advanced (F3-F4) fibrosis was assessed by receiver operating characteristics (ROC) curve. p value of less than 0.05 was considered statistically significant different.

RESULTS

Twenty-one subjects had advanced fibrosis. The LSN scores among different stages of fibrosis were significantly different (p < 0.001). The correlation between LSN score and stage of fibrosis was also strong (ρ = 0.71; p < 0.001). The areas under ROC curves for detection of significant and advanced fibrosis were 0.80 (95% CI 0.66-0.95) and 0.86 (95% CI 0.75-0.97), using a threshold of 2.23 and 2.44, respectively. This method showed 81% sensitivity and 88% specificity for detection of advanced fibrosis.

CONCLUSION

MR-based LSN score is a promising non-invasive objective tool for detection of advanced fibrosis in patients with NAFLD.

KEY POINTS

• Liver surface nodularity (LSN) score is a fast retrospective method for precise quantification of nodularity of liver surface. • MR-based LSN score is a promising non-invasive objective tool to accurately detect different stages of fibrosis in patients with non-alcoholic fatty liver disease (NAFLD).

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.

Multiparametric CT for Noninvasive Staging of Hepatitis C Virus-Related Liver Fibrosis: Correlation With the Histopathologic Fibrosis Score

OBJECTIVE

The objective was to develop a multiparametric CT algorithm to stage liver fibrosis in patients with chronic hepatitis C virus (HCV) infection.

MATERIALS AND METHODS

Abdominal CT and laboratory measures in 469 patients with HCV (340 men and 129 women; mean age, 50.1 years) were compared against the histopathologic Metavir fibrosis reference standard (F0, n = 49 patients; F1, n = 69 patients; F2, n = 102 patients; F3, n = 76 patients; F4, n = 173 patients). From the initial candidate pool, nine CT and two laboratory measures were included in the final assessment (CT-based features: hepatosplenic volumetrics, texture features, liver surface nodularity [LSN] score, and linear CT measurements; laboratory-based measures: Fibrosis-4 [FIB-4] score and aspartate transaminase-to-platelets ratio index [APRI]). Univariate logistic regression and multivariate logistic regression were performed with ROC analysis, proportional odds modeling, and probabilities.

RESULTS

ROC AUC values for the model combining all 11 parameters for discriminating significant fibrosis (≥ F2), advanced fibrosis (≥ F3), and cirrhosis (F4) were 0.928, 0.956, and 0.972, respectively. For all nine CT-based parameters, these values were 0.905, 0.936, and 0.972, respectively. Using more simplified panels of two, three, or four parameters yielded good diagnostic performance; for example, a two-parameter model combining only LSN score with FIB-4 score had ROC AUC values of 0.886, 0.915, and 0.932, for significant fibrosis, advanced fibrosis, and cirrhosis. The LSN score performed best in the univariate analysis.

CONCLUSION

Multiparametric CT assessment of HCV-related liver fibrosis further improves performance over the performance of individual parameters. An abbreviated panel of LSN score and FIB-4 score approached the diagnostic performance of more exhaustive panels. Results of the abbreviated panel compare favorably with elastography, but this approach has the advantage of retrospective assessment using preexisting data without planning.

CT texture analysis of the liver for assessing hepatic fibrosis in patients with hepatitis C virus

OBJECTIVE

To evaluate CT texture analysis (CTTA) for non-invasively staging of hepatic fibrosis (stages F0-F4) in a cohort of patients with hepatitis C virus (HCV).

METHODS

Quantitative texture analysis of the liver was performed on abdominal multidimensional CT scans. Single slice region of interest measurements of the total liver, Couinaud segments IV-VIII and segments I-III were made. CT texture parameters were tested against stage of hepatic fibrosis in segments IV-VIII on the portal venous phase. Texture parameters were correlated with biopsy performed within 1 year for all cases with intermediate fibrosis (F0-F3).

RESULTS

CT scans of 556 adults (360 males, 196 females; mean age, 49.8 years), including a healthy control group (F0, n = 77) and patients with hepatitis C virus and Stage 0 disease (n = 49), and patients with increasing stages of fibrosis (F1, n = 80; F2 n = 99; F3 n = 87; F4 n = 164) were evaluated. Mean gray level intensity increased with increasing fibrosis. For significant fibrosis (≥F2), mean showed receiver operatingcharacteristic area under the curve (AUC) of 0.80 with sensitivity and specificity of 74 and 75% using a threshold of 0.44, with similar receiver operatingcharacteristic AUC and sensitivity/specificity for advanced fibrosis (≥F3). Skewness and kurtosis were inversely associated with hepatic fibrosis, most prominently in cirrhotic patients. A multivariate model combining these four texture features (mean, mpp, skewness and kurtosis) showed slightly improved performance with AUC of 0.82, 0.82 and 0.86 for any fibrosis (F0 vs F1-F4), significant fibrosis (F0-1 vs F2-4) and advanced fibrosis (F0-2 vs F3-4) respectively.

CONCLUSION

CT texture features may be associated with hepatic fibrosis and have utility in staging fibrosis, particularly at advanced levels.

ADVANCES IN KNOWLEDGE

CTTA may be helpful in detecting and staging hepatic fibrosis, particularly at advanced levels. CT measures like CTTA can be retrospectively evaluated without special equipment.

Imaging of Hepatic Fibrosis

PURPOSE OF REVIEW

The purpose of this review is to discuss the current imaging techniques for non-invasive assessment of liver fibrosis (LF).

RECENT FINDINGS

Elastography-based techniques are the most widely used imaging methods for the evaluation of LF. Currently, MR elastography (MRE) is the most accurate non-invasive method for detection and staging of LF. Ultrasound-based vibration-controlled transient elastography (VCTE) is the most widely used as it can be easily performed at the point of care but has technical limitations especially in the obese. Innovations and technical improvements continue to evolve in elastography for improving accuracy and avoiding misinterpretation from confounding factors. Other imaging methods including diffusion-weighted imaging (DWI), hepatocellular contrast-enhanced (HCE) MRI, T1 relaxometry, T1ρ imaging, textural analysis, liver surface nodularity, susceptibility-weighted imaging, and perfusion imaging are promising but need further evaluation and clinical validation. MRE is the most accurate imaging technique for assessment of LF.