Liver-specific DICER1 syndrome model mice develop cystic liver tumors with defective primary cilia

DICER1 syndrome is a tumor predisposition syndrome caused by familial genetic mutations in DICER1. Pathogenic variants of DICER1 have been discovered in many rare cancers, including cystic liver tumors. However, the molecular mechanisms underlying liver lesions induced by these variants remain unclear. In the present study, we sought to gain a better understanding of the pathogenesis of these variants by generating a mouse model of liver-specific DICER1 syndrome. The mouse model developed bile duct hyperplasia with fibrosis, similar to congenital hepatic fibrosis, as well as cystic liver tumors resembling those in Caroli's syndrome, intrahepatic cholangiocarcinoma, and hepatocellular carcinoma. Interestingly, the mouse model of DICER1 syndrome showed abnormal formation of primary cilia in the bile duct epithelium, which is a known cause of bile duct hyperplasia and cyst formation. These results indicated that DICER1 mutations contribute to cystic liver tumors by inducing defective primary cilia. The mouse model generated in this study will be useful for elucidating the potential mechanisms of tumorigenesis induced by DICER1 variants and for obtaining a comprehensive understanding of DICER1 syndrome. © 2024 The Pathological Society of Great Britain and Ireland.

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.

Quantitative edge analysis of pancreatic margins in patients with head pancreatic tumors: correlations between pancreatic margins and the onset of postoperative pancreatic fistula

OBJECTIVE

To assess the correlation between pancreatic quantitative edge analysis as a surrogate of parenchymal stiffness and the incidence of postoperative pancreatic fistula (POPF), in patients undergoing pancreaticoduodenectomy (PD).

METHODS

All consecutive patients who underwent PD at our Institution between March 2018 and November 2019 with an available preoperative CT were included. Pancreatic margin score (PMS) was calculated through computer-assisted quantitative edge analysis on the margins of the pancreatic body and tail (the expected pancreatic remnant) on non-contrast scans with in-house software. Intraoperative assessment of pancreatic stiffness by manual palpation was also performed, classifying pancreatic texture into soft and non-soft. PMS values were compared between groups using an unpaired T-test and correlated with the intraoperative evaluation of stiffness and with the grading of postoperative pancreatic fistula according to the International Study Group on Pancreatic Surgery (ISGPS).

RESULTS

Patient population included 200 patients (mean age 64.6 years), 146 without onset of POPF (73%, non-POPF group), and 54 with POPF (27%, POPF group). A significant difference in PMS values was observed between POPF and non-POPF (respectively 1.88 ± 0.05 vs 0.69 ± 0.01; p < 0.0001). PMS values of pancreatic parenchymas intraoperatively considered "soft" were significantly higher than those evaluated as "non-soft" (1.21 ± 0.04 vs 0.73 ± 0.02; p < 0.0001). A significant correlation between PMS values and POPF grade was observed (r = 0.8316), even in subgroups of patients with soft (r = 0.8016) and non-soft (r = 0.7602) pancreas (all p < 0.0001).

CONCLUSIONS

Quantitative edge analysis with dedicated software may stratify patients with different pancreatic stiffness, thus potentially improving preoperative risk assessment and strategies for POPF mitigation.

CLINICAL RELEVANCE STATEMENT

This study proposes quantitative pancreas edge analysis as a predictor for postoperative pancreatic fistula. The test has high accuracy and correlation with fistula grade according to the International Study Group on Pancreatic Surgery.

KEY POINTS

• Prediction of postoperative pancreatic fistula (POPF) onset risk after pancreaticoduodenectomy is based only on intraoperative evaluation. • Quantitative edge analysis may preoperatively identify patients with higher risk of POPF. • Quantification of pancreatic stiffness through the analysis of pancreatic margins could be done on preoperative CT.

Liver surface nodularity and ascites are associated with mortality risk in acute alcohol-associated hepatitis

BACKGROUND

Acute alcohol-associated hepatitis (AH) is associated with high mortality. CT-derived liver surface nodularity (LSN) is a robust prognostic biomarker in other chronic liver diseases. The aim of this study was to determine relationships between LSN, disease severity, and mortality in AH.

METHODS

Adults hospitalized with AH from January 2016 to March 2020 were included if an abdominal CT was performed between 8 weeks prior to 72 h after hospitalization. LSN was measured using quantitative methods (Liver Surface Nodularity Software version 0.88, Birmingham, AL, USA). Cox proportional hazards models, logistic regression and AUROC analysis were used to examine relationships between LSN and 180-day transplant-free survival.

RESULTS

Of 386 patients hospitalized with AH during the study period, 230 had CT scans performed, and 205 met inclusion criteria. Mean transplant-free survival was 127 days (95% CI 118-137). Within each cohort, patients were grouped into low [LSN-LOW, N = 109 (53.2%)] and high [LSN-HIGH, N = 96 (46.8%)] LSN strata based on an optimal cutoff of 2.86 derived from unadjusted ROC curves. Patients with high LSN had features of portal hypertension, which included encephalopathy [53 (55.2%) vs. 43 (39.4%), p = 0.017], ascites on CT [81 (84.4%) vs. 69 (63.3%), p = 0.001] and portosystemic shunts [78 (81.2%) vs. 69 (63.3%), p = 0.003]. High LSN, ascites and MELD were independently associated with lower likelihood of 180-day transplant-free survival, and inclusion of a score assigning 1 point each for high LSN or ascites on CT (AHRADS score) to MELD enhanced diagnostic accuracy of AUROC for 180-day survival compared to MELD alone [AUROC 0.782 (95% CI 0.719-0.845) vs. 0.735 (0.667-0.802), p = 0.023].

CONCLUSIONS

CT-derived factors that include LSN and ascites are radiographic biomarkers associated with 180-day transplant-free survival in alcohol-associated hepatitis.

CT-based methods for assessment of metabolic dysfunction associated with fatty liver disease

Metabolic dysfunction-associated fatty liver disease (MAFLD), previously called metabolic nonalcoholic fatty liver disease, is the most prevalent chronic liver disease worldwide. The multi-factorial nature of MAFLD severity is delineated through an intricate composite analysis of the grade of activity in concert with the stage of fibrosis. Despite the preeminence of liver biopsy as the diagnostic and staging reference standard, its invasive nature, pronounced interobserver variability, and potential for deleterious effects (encompassing pain, infection, and even fatality) underscore the need for viable alternatives. We reviewed computed tomography (CT)-based methods for hepatic steatosis quantification (liver-to-spleen ratio; single-energy "quantitative" CT; dual-energy CT; deep learning-based methods; photon-counting CT) and hepatic fibrosis staging (morphology-based CT methods; contrast-enhanced CT biomarkers; dedicated postprocessing methods including liver surface nodularity, liver segmental volume ratio, texture analysis, deep learning methods, and radiomics). For dual-energy and photon-counting CT, the role of virtual non-contrast images and material decomposition is illustrated. For contrast-enhanced CT, normalized iodine concentration and extracellular volume fraction are explained. The applicability and salience of these approaches for clinical diagnosis and quantification of MAFLD are discussed.Relevance statementCT offers a variety of methods for the assessment of metabolic dysfunction-associated fatty liver disease by quantifying steatosis and staging fibrosis.Key points• MAFLD is the most prevalent chronic liver disease worldwide and is rapidly increasing.• Both hardware and software CT advances with high potential for MAFLD assessment have been observed in the last two decades.• Effective estimate of liver steatosis and staging of liver fibrosis can be possible through CT.

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.

Assessing Liver Fibrosis Using 2D-SWE Liver Ultrasound Elastography and Dynamic Liver Scintigraphy with 99mTc-mebrofenin: A Comparative Prospective Single-Center Study

Background and Objectives: Many quantitative imaging modalities are available that quantify chronic liver disease, although only a few of them are included in clinical guidelines. Many more imaging options are still competing to find their place in the area of diagnosing chronic liver disease. We report our first prospective single-center study evaluating different imaging modalities that stratify viral hepatitis-associated liver fibrosis in a treatment-naïve patient group. Materials and Methods: The aim of our study is to compare and to combine already employed 2D shear wave elastography (2D-SWE) with dynamic liver scintigraphy with 99mTc-mebrofenin in chronic viral hepatitis patients for the staging of liver fibrosis. Results: Seventy-two patients were enrolled in the study. We found that both 2D-SWE ultrasound imaging, with dynamic liver scintigraphy with 99mTc-mebrofenin are able to stratify CLD patients into different liver fibrosis categories based on histological examination findings. We did not find any statistically significant difference between these imaging options, which means that dynamic liver scintigraphy with 99mTc-mebrofenin is not an inferior imaging technique. A combination of these imaging modalities showed increased accuracy in the non-invasive staging of liver cirrhosis. Conclusions: Our study presents that 2D-SWE and dynamic liver scintigraphy with 99mTc-mebrofenin could be used for staging liver fibrosis, both in singular application and in a combined way, adding a potential supplementary value that represents different aspects of liver fibrosis in CLD.

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.

Regional Analysis of Liver Surface Nodularity in a Single Axial MR Image for Staging Liver Fibrosis

BACKGROUND

The assessment of liver surface nodularity (LSN) for staging hepatic fibrosis is restricted in clinical practice because it requires customized software and time-consuming procedures. A simplified method to estimate LSN score may be useful in the clinic.

PURPOSE

To evaluate the regional analysis of LSN and processing time in a single axial liver MR image for staging liver fibrosis.

STUDY TYPE

Retrospective.

POPULATION

A total of 210 subjects, a multicenter study.

FIELD STRENGTH/SEQUENCE

A 3 T/noncontrast gradient echo T1WI.

ASSESSMENT

Subjects were divided into five fibrosis groups (F₀  = 29; F₁  = 20; F₂  = 32; F₃  = 50; F₄  = 79) based on the METAVIR fibrosis scoring system. The mean LSN (on three slices) and regional LSN (on one slice) measurements, and the processing times, are compared. The regional LSN scores in five regions-of-interests (ROI_1-5 ) were analyzed in a single axial MRI at the level of the hilum by two independent observers.

STATISTICAL TESTS

Regional variations in LSN scores were compared using ANOVA with Tukey test. Agreement between the mean and regional LSN measurements was evaluated using Pearson correlation coefficients (r) and Bland-Altman plots. The diagnostic performance of mean and regional LSN scores according to fibrosis stage was evaluated with the AUROC. A P value < 0.05 was considered statistically significant.

RESULTS

Total processing time for a regional LSN measurement (3.6 min) was 75.5% less than that for mean LSN measurement (14.7 min). Mean LSN scores and all five regional LSN scores showed significant differences between fibrosis groups. Among regional LSN scores, ROI₅ showed the highest AUROC (0.871 at cut-off 1.12) for discriminating F_0-2 vs. F_3-4 and the best correlation with mean LSN score (r = 0.800, -0.07 limit of agreement).

CONCLUSION

Quantitative regional LSN measurement in a single axial MR image reduces processing time. Regional ROI₅ LSN score might be useful for clinical decision-making and for distinguishing the difference between early fibrosis (F_0-2 ) and advanced fibrosis (F_3-4 ) in the liver.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Quantitative Assessment of Liver Impairment in Chronic Viral Hepatitis with [99mTc]Tc-Mebrofenin: A Noninvasive Attempt to Stage Viral Hepatitis-Associated Liver Fibrosis

Background and objectives—Chronic viral hepatitis B and C infections are one of the leading causes of chronic liver impairment, resulting in liver fibrosis and liver cirrhosis. An early diagnosis with accurate liver fibrosis staging leads to a proper diagnosis, thus tailoring correct treatment. Both invasive and noninvasive techniques are used in the diagnosis and staging of chronic liver impairment. Those techniques include liver biopsy, multiple serological markers (as either single tests or combined panels), and imaging examinations, such as ultrasound or magnetic resonance elastography. Nuclear medicine probes may also be employed in staging liver fibrosis, although the literature scarcely reports this. The purpose of our study was to investigate whether a dynamic liver scintigraphy with [^99mTc]Tc-mebrofenin has any value in staging or grading chronic liver damage. Materials and Methods—We prospectively enrolled patients with chronic viral hepatitis B and C infection referred for liver biopsy. All patient underwent dynamic liver scintigraphy with 99mTc-mebrofenin prior to liver biopsy. Dynamic liver scintigraphy was performed immediately after intravenous tracer injection for 30 min scanning time. Multiple scintigraphy parameters were calculated (whole liver lobe and focal area time to peak (TTP), 30 min to peak ratio (30/peak), whole lobe and focal area slope index in 350 s (slope_350). Liver biopsy took place shortly after imaging. Results—We found that many dynamic scintigraphic parameters are positively or negatively associated with different stages of liver fibrosis. The main parameters that showed most value are the ratio between 30 min and the peak of the dynamic curve (30/peak_dex (ratio)), and liver clearance corrected for body surface area and liver area (LCL_m²_dm² (%/min/m²/dm²)). Conclusions—Our present study proves that conducting dynamic liver scintigraphies with [^99mTc]Tc-mebrofenin has potential value in staging liver fibrosis. The benefits of this method, including whole liver imaging and direct imaging of the liver function, provide an advantage over presently used quantitative imaging modalities.

Fully Automated and Explainable Liver Segmental Volume Ratio and Spleen Segmentation at CT for Diagnosing Cirrhosis

PURPOSE

To evaluate the performance of a deep learning (DL) model that measures the liver segmental volume ratio (LSVR) (ie, the volumes of Couinaud segments I-III/IV-VIII) and spleen volumes from CT scans to predict cirrhosis and advanced fibrosis.

MATERIALS AND METHODS

For this Health Insurance Portability and Accountability Act-compliant, retrospective study, two datasets were used. Dataset 1 consisted of patients with hepatitis C who underwent liver biopsy (METAVIR F0-F4, 2000-2016). Dataset 2 consisted of patients who had cirrhosis from other causes who underwent liver biopsy (Ishak 0-6, 2001-2021). Whole liver, LSVR, and spleen volumes were measured with contrast-enhanced CT by radiologists and the DL model. Areas under the receiver operating characteristic curve (AUCs) for diagnosing advanced fibrosis (≥METAVIR F2 or Ishak 3) and cirrhosis (≥METAVIR F4 or Ishak 5) were calculated. Multivariable models were built on dataset 1 and tested on datasets 1 (hold out) and 2.

RESULTS

Datasets 1 and 2 consisted of 406 patients (median age, 50 years [IQR, 44-56 years]; 297 men) and 207 patients (median age, 50 years [IQR, 41-57 years]; 147 men), respectively. In dataset 1, the prediction of cirrhosis was similar between the manual versus automated measurements for spleen volume (AUC, 0.86 [95% CI: 0.82, 0.9] vs 0.85 [95% CI: 0.81, 0.89]; significantly noninferior, P < .001) and LSVR (AUC, 0.83 [95% CI: 0.78, 0.87] vs 0.79 [95% CI: 0.74, 0.84]; P < .001). The best performing multivariable model achieved AUCs of 0.94 (95% CI: 0.89, 0.99) and 0.79 (95% CI: 0.71, 0.87) for cirrhosis and 0.8 (95% CI: 0.69, 0.91) and 0.71 (95% CI: 0.64, 0.78) for advanced fibrosis in datasets 1 and 2, respectively.

CONCLUSION

The CT-based DL model performed similarly to radiologists. LSVR and splenic volume were predictive of advanced fibrosis and cirrhosis.Keywords: CT, Liver, Cirrhosis, Computer Applications-Detection/Diagnosis Supplemental material is available for this article. © RSNA, 2022.

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.

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.

Value-added Opportunistic CT Screening: State of the Art

Opportunistic CT screening leverages robust imaging data embedded within abdominal and thoracic scans that are generally unrelated to the specific clinical indication and have heretofore gone largely unused. This incidental imaging information may prove beneficial to patients in terms of wellness, prevention, risk profiling, and presymptomatic detection of relevant disease. The growing interest in CT-based opportunistic screening relates to a confluence of factors: the objective and generalizable nature of CT-based body composition measures, the emergence of fully automated explainable AI solutions, the sheer volume of body CT scans performed, and the increasing emphasis on precision medicine and value-added initiatives. With a systematic approach to body composition and other useful CT markers, initial evidence suggests that their ability to help radiologists assess biologic age and predict future adverse cardiometabolic events rivals even the best available clinical reference standards. Emerging data suggest that standalone "intended" CT screening over an unorganized opportunistic approach may be justified, especially when combined with established cancer screening. This review will discuss the current status of opportunistic CT screening, including specific body composition markers and the various disease processes that may be impacted. The remaining hurdles to widespread clinical adoption include generalization to more diverse patient populations, disparate technical settings, and reimbursement.

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.

Development and validation of a management system and dataset quality assessment tool for the Radiology Common Data Model (R_CDM): A case study in liver disease

BACKGROUND

The Observational Medical Outcomes Partnership-Common Data Model (OMOP-CDM), a distributed research network, has low clinical data coverage. Radiological data are valuable, but imaging metadata are often incomplete, and a standardized recording format in the OMOP-CDM is lacking. We developed a web-based management system and data quality assessment (RQA) tool for a radiology_CDM (R_CDM) and evaluated the feasibility of clinically applying this dataset.

METHODS

We designed an R_CDM with Radiology_Occurrence and Radiology_Image tables. This was seamlessly linked to the OMOP-CDM clinical data. We adopted the standardized terminology using the RadLex playbook and mapped 5,753 radiology protocol terms to the OMOP vocabulary. An extract, transform, and load (ETL) process was developed to extract detailed information that was difficult to extract from metadata and to compensate for missing values. Image-based quantification was performed to measure liver surface nodularity (LSN), using customized Wonkwang abdomen and liver total solution (WALTS) software.

RESULTS

On a PACS, 368,333,676 DICOM files (1,001,797 cases) were converted to R_CDM chronic liver disease (CLD) data (316,596 MR images, 228 cases; 926,753 CT images, 782 cases) and uploaded to a web-based management system. Acquisition date and resolution were extracted accurately, but other information, such as "contrast administration status" and "photography direction", could not be extracted from the metadata. Using WALTS, 9,609 pre-contrast axial-plane abdominal MR images (197 CLD cases) were assigned LSN scores by METAVIR fibrosis grades, which differed significantly by ANOVA (p < 0.001). The mean RQA score (83.5) indicated good quality.

CONCLUSION

This study developed a web-based system for management of the R_CDM dataset, RQA tool, and constructed a CLD R_CDM dataset, with good quality for clinical application. Our management system and R_CDM CLD dataset would be useful for multicentric and image-based quantification researches.

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.

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.

Noncontrast-enhanced MRI-based Noninvasive Score for Portal Hypertension (CHESS1802): An International Multicenter Study

BACKGROUND AND AIMS

This study aimed to determine the performance of the non-invasive score using noncontrast-enhanced MRI (CHESS-DIS score) for detecting portal hypertension in cirrhosis.

METHODS

In this international multicenter, diagnostic study (ClinicalTrials.gov, NCT03766880), patients with cirrhosis who had hepatic venous pressure gradient (HVPG) measurement and noncontrast-enhanced MRI were prospectively recruited from four university hospitals in China (n=4) and Turkey (n=1) between December 2018 and April 2019. A cohort of patients was retrospectively recruited from a university hospital in Italy between March 2015 and November 2017. After segmentation of the liver on fat-suppressed T1-weighted MRI maps, CHESS-DIS score was calculated automatically by an in-house developed code based on the quantification of liver surface nodularity.

RESULTS

A total of 149 patients were included, of which 124 were from four Chinese hospitals (training cohort) and 25 were from two international hospitals (validation cohort). A positive correlation between CHESS-DIS score and HVPG was found with the correlation coefficients of 0.36 (p<0.0001) and 0.55 (p<0.01) for the training and validation cohorts, respectively. The area under the receiver operating characteristic curve of CHESS-DIS score in detection of clinically significant portal hypertension (CSPH) was 0.81 and 0.9 in the training and validation cohorts, respectively. The intraclass correlation coefficients for assessing the inter- and intra-observer agreement were 0.846 and 0.841, respectively.

CONCLUSIONS

A non-invasive score using noncontrast-enhanced MRI was developed and proved to be significantly correlated with invasive HVPG. Besides, this score could be used to detect CSPH in patients with cirrhosis.

Combining hepatic surface nodularity and serum tests better predicts hepatic fibrosis stages in chronic liver disease

PURPOSE

Hepatic surface nodularity quantified on CT images has shown promising results in staging hepatic fibrosis in chronic hepatitis C. The aim of this study was to evaluate hepatic surface nodularity, serum fibrosis indices, and a linear combination of them for staging fibrosis in chronic liver disease, mainly chronic hepatitis B.

METHODS

We developed a semiautomated software quantifying hepatic surface nodularity on CT images. Hepatic surface nodularity and serum fibrosis indices were assessed in the development group of 125 patients to generate 3 linear models combining hepatic surface nodularity with the aspartate aminotransferase to platelet ratio index, fibrosis-4 index, or platelet count in reference to the METAVIR scoring system. The models were validated in 183 patients.

RESULTS

Hepatic surface nodularity and serum fibrosis indices all significantly correlated with fibrosis stages. For binary classifications into cirrhosis (F4), advanced fibrosis (≥ F3), and significant fibrosis (≥ F2), hepatic surface nodularity was significantly different across categories. The areas under the curve (AUCs) of the best model were 0.901, 0.872, and 0.794 for cirrhosis, advanced fibrosis, and significant fibrosis, respectively, higher than serum fibrosis indices alone (0.797-0.802, 0.799-0.818, and 0.761-0.773). In the validation group, the same model likewise showed higher AUCs (0.872, 0.831, and 0.850) compared to serum fibrosis indices (0.722-0.776, 0.692-0.768, and 0.695-0.769; p < 0.001 for F4).

CONCLUSION

Hepatic surface nodularity combined with serum blood test could be a practical method to predict cirrhosis, advanced fibrosis, and significant fibrosis in chronic liver disease patients, providing higher accuracy than using serum fibrosis indices alone.

1-year outcomes for lung transplantation recipients with non-alcoholic fatty liver disease

Advanced hepatic fibrosis and cirrhosis are absolute contraindications to lung transplantation. [ 1] However, whether fatty liver disease with mild–moderate fibrosis contributes to increased adverse outcomes post-lung transplantation remains unknown.

 We present a retrospective analysis of patients transplanted at Brigham and Women's Hospital between 2015 and 2017 to identify whether patients with mild–moderate non-alcoholic fatty liver disease (NAFLD) experience increased short-term complications compared to patients with normal liver architecture. Patients with advanced (F3–F4) fibrosis and/or cirrhosis were considered non-suitable transplant candidates, a priori. This study was powered for a difference in index hospital-free days within the first 30 days of 25% (α=0.05, β=0.8). Secondary outcomes included index intensive care unit (ICU)-free days within the first 10 days post-transplant, perioperative blood product transfusion, incidence of index hospitalisation arrhythmias and delirium, need for insulin on discharge post-transplant, tacrolimus dose required to maintain a trough of 8–12 ng·mL⁻¹ at index hospital discharge, and 1-year post-transplant incidence of insulin-dependent diabetes, acute kidney injury, acute cellular rejection, unplanned hospital readmissions and infection.

 150 patients underwent lung transplantation between 2015 and 2017 and were included in the analysis; of these patients 40 (27%) had evidence of NAFLD. Median index hospital-free days for patients with NAFLD were non-inferior to those without (16 days, IQR 10.5–19.5 versus 12 days, IQR 0–18.0, p=0.03). Regarding secondary outcomes, both index hospitalisation and 1-year outcomes were non-inferior between patients with NAFLD and those with normal liver architecture.

 This study demonstrates that mild–moderate severity NAFLD may not be a contraindication to lung transplantation.

In this single-centre, retrospective analysis of lung transplant recipients, we identified that mild–moderate non-alcoholic fatty liver disease is associated with acceptable perioperative and 1-year outcomeshttps://bit.ly/36WNzhi

Liver stiffness measured with two-dimensional shear wave elastography comparable to histopathology falls dominantly on the severe liver fibrosis

BACKGROUND

Two-dimensional shear-wave elastography (2D-SWE) has been used for years for liver assessment of patients with chronic hepatitis B (CHB), but its effectiveness remains unclear in different populations and using different ultrasound systems.

OBJECTIVE

This study investigated the effectiveness of 2D-SWE in evaluating liver fibrosis in patients with CHB.

METHODS

A prospective investigation was conducted after approval by the institutional ethics committee, with 116 out of 133 patients with CHB referred for liver biopsy included and 50 patients with healthy livers selected as controls. Assessment with 2D-SWE of liver stiffness measurement (LSM) was compared with histopathological results. Cutoff values for LSM were set to determine the degree of fibrosis, and area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity were calculated.

RESULTS

The optimal LSM cutoff for differentiating healthy livers from livers with CHB and any liver fibrosis was 6.485 kPa, with an AUROC of 0.927, sensitivity of 94%, and specificity of 19.8%. The optimal LSM cutoff values for F1, F2, F3, and F4 were 6.19 kPa, 6.485 kPa, 7.46 kPa, and 9.62 kPa, respectively, with corresponding AUROCs of 0.516, 0.625, 0.779, and 0.881, respectively. Comparisons of AUROCs between F1 and F3, F1 and F4, F2 and F3, and F2 and F4 were all significantly different (P = 0.0001, P <  0.0001, P = 0.0139, and P = 0.0003, respectively); comparisons of AUROCs between F1 and F2 and between F3 and F4 were not significantly different (P = 0.1232 and P = 0.2462, respectively). Comparisons of LSMs between healthy livers and F0 and between healthy livers and a combination of F0 and F1 were significantly different (P = 0.002 and P = 0.001, respectively). Comparisons of LSMs between F1 and F2 and between F3 and F4 were not significantly different (P = 0.233 and P = 0.072, respectively). Other comparisons between fibrosis score groups were significantly different (F1 and F3, P = 0.003; F1 and F4, P = 0.007; F2 and F3, P = 0.013; F2 and F4, P = 0.015).

CONCLUSION

2D-SWE using a specific diagnostic ultrasound system is effective for the assessment of severe liver fibrosis and cirrhosis, but is limited in diagnosing mild liver fibrosis.

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.

Assessment of Liver Fibrosis Stage Using Integrative Analysis of Hepatic Heterogeneity and Nodularity in Routine MRI with FIB-4 Index as Reference Standard

Image-based quantitative methods for liver heterogeneity (L_Het) and nodularity (L_Nod) provide helpful information for evaluating liver fibrosis; however, their combinations are not fully understood in liver diseases. We developed an integrated software for assessing L_Het and L_Nod and compared L_Het and L_Nod according to fibrosis stages in chronic liver disease (CLD). Overall, 111 CLD patients and 16 subjects with suspected liver disease who underwent liver biopsy were enrolled. The procedures for quantifying L_Het and L_Nod were bias correction, contour detection, liver segmentation, and L_Het and L_Nod measurements. L_Het and L_Nod scores among fibrosis stages (F0–F3) were compared using ANOVA with Tukey’s test. Diagnostic accuracy was determined by calculating the area under the receiver operating characteristics (AUROC) curve. The mean L_Het scores of F0, F1, F2, and F3 were 3.49 ± 0.34, 5.52 ± 0.88, 6.80 ± 0.97, and 7.56 ± 1.79, respectively (p < 0.001). The mean L_Nod scores of F0, F1, F2, and F3 were 0.84 ± 0.06, 0.91 ± 0.04, 1.09 ± 0.08, and 1.15 ± 0.14, respectively (p < 0.001). The combined L_Het × L_Nod scores of F0, F1, F2, and F3 were 2.96 ± 0.46, 5.01 ± 0.91, 7.30 ± 0.89, and 8.48 ± 1.34, respectively (p < 0.001). The AUROCs of L_Het, L_Nod, and L_Het × L_Nod for differentiating F1 vs. F2 and F2 vs. F3 were 0.845, 0.958, and 0.954; and 0.619, 0.689, and 0.761, respectively. The combination of L_Het and L_Nod scores derived from routine MR images allows better differential diagnosis of fibrosis subgroups in CLD.

Hepatic Elastometry and Glissonian Line in the Assessment of Liver Fibrosis

The aim of this study was to identify a method for staging hepatic fibrosis using a non-invasive, rapid and inexpensive technique based on ultrasound morphologic hepatic features. A total of 215 patients with different liver diseases underwent B-mode (2-D brightness mode) ultrasonography, vibration-controlled transient elastography, 2-D shear wave elastography and measurement of the controlled attenuation parameter with transient elastography. B-Mode images of the anterior margin of the left lobe were obtained and processed with automatic Genoa Line Quantification (GLQ) software based on a neural network for staging liver fibrosis. The accuracy of GLQ was 90.6% during model training and 78.9% in 38 different patients with concordant elastometric measures. Receiver operating characteristic curve analysis of GLQ performance using vibration-controlled transient elastography as a reference yielded areas under the curves of 0.851 for F ≥ F1, 0.793 for F ≥ F2, 0.784 for F ≥ F3 and 0.789 for F ≥ F4. GLQ has the potential to be a rapid, easy-to-perform and tolerable method in the staging of liver fibrosis.

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.

Opportunistic Screening at Abdominal CT: Use of Automated Body Composition Biomarkers for Added Cardiometabolic Value

Abdominal CT is a frequently performed imaging examination for a wide variety of clinical indications. In addition to the immediate reason for scanning, each CT examination contains robust additional data on body composition that generally go unused in routine clinical practice. There is now growing interest in harnessing this additional information. Prime examples of cardiometabolic information include measurement of bone mineral density for osteoporosis screening, quantification of aortic calcium for assessment of cardiovascular risk, quantification of visceral fat for evaluation of metabolic syndrome, assessment of muscle bulk and density for diagnosis of sarcopenia, and quantification of liver fat for assessment of hepatic steatosis. All of these relevant biometric measures can now be fully automated through the use of artificial intelligence algorithms, which provide rapid and objective assessment and allow large-scale population-based screening. Initial investigations into these measures of body composition have demonstrated promising performance for prediction of future adverse events that matches or exceeds the best available clinical prediction models, particularly when these CT-based measures are used in combination. In this review, the concept of CT-based opportunistic screening is discussed, and an overview of the various automated biomarkers that can be derived from essentially all abdominal CT examinations is provided, drawing heavily on the authors' experience. As radiology transitions from a volume-based to a value-based practice, opportunistic screening represents a promising example of adding value to services that are already provided. If the potentially high added value of these objective CT-based automated measures is ultimately confirmed in subsequent investigations, this opportunistic screening approach could be considered for intentional CT-based screening. ^©RSNA, 2021.

Quantitative liver surface nodularity score based on imaging for assessment of early cirrhosis in patients with chronic liver disease: A protocol for systematic review and meta-analysis

BACKGROUND

Early stage of cirrhosis is of great value in the diagnosis and management in patients with chronic liver disease (CLD). Recent studies have shown that quantitative liver surface nodularity (LSN) score based on imaging techniques can be used to predict the early cirrhosis stage noninvasively, with varied diagnostic accuracy and limited sample size. Hence, this study will evaluate the diagnostic accuracy of LSN in the prediction of early cirrhosis.

METHODS

We will conduct a comprehensive search in PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases to identify eligible studies. The literature screening, data extraction, data analysis, and quality assessment will then be carried out. The summary receiver-operating-characteristic (ROC) and pooled sensitivity, specificity will be calculated to summarize the diagnostic performance of LSN using a random-effect model. A meta-regression analysis will be performed to investigate the underlying cause of the heterogeneity.

RESULTS

This study will evaluate the diagnostic accuracy of LSN score in the identification of early cirrhosis, which may further determine whether this method can be used as an alternative in the assessment of CLD patients.

CONCLUSIONS

This study will help to determine the diagnostic accuracy and summarize the recent evidence on this issue.

STUDY REGISTRATION

INPLASY2020100096.

Utility of Multiparametric CT for Identification of High-Risk NAFLD

OBJECTIVE. The purpose of this study was to evaluate the utility of laboratory and CT metrics in identifying patients with high-risk nonalcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS. Patients with biopsy-proven NAFLD who underwent CT within 1 year of biopsy were included. Histopathologic review was performed by an experienced gastrointestinal pathologist to determine steatosis, inflammation, and fibrosis. The presence of any lobular inflammation and hepatocyte ballooning was categorized as nonalcoholic steatohepatitis (NASH). Patients with NAFLD and advanced fibrosis (stage F3 or higher) were categorized as having high-risk NAFLD. Aspartate transaminase to platelet ratio index and Fibrosis-4 (FIB-4) laboratory scores were calculated. CT metrics included hepatic attenuation, liver segmental volume ratio (LSVR), splenic volume, liver surface nodularity score, and selected texture features. In addition, two readers subjectively assessed the presence of NASH (present or not present) and fibrosis (stages F0-F4). RESULTS. A total of 186 patients with NAFLD (mean age, 49 years; 74 men and 112 women) were included. Of these, 87 (47%) had NASH and 112 (60%) had moderate to severe steatosis. A total of 51 patients were classified as fibrosis stage F0, 42 as F1, 23 as F2, 37 as F3, and 33 as F4. Additionally, 70 (38%) had advanced fibrosis (stage F3 or F4) and were considered to have high-risk NAFLD. FIB-4 score correlated with fibrosis (ROC AUC of 0.75 for identifying high-risk NAFLD). Of the individual CT parameters, LSVR and splenic volume performed best (AUC of 0.69 for both for detecting high-risk NAFLD). Subjective reader assessment performed best among all parameters (AUCs of 0.78 for reader 1 and 0.79 for reader 2 for detecting high-risk NAFLD). FIB-4 and subjective scores were complementary (combined AUC of 0.82 for detecting high-risk NAFLD). For NASH assessment, FIB-4 performed best (AUC of 0.68), whereas the AUCs were less than 0.60 for all individual CT features and subjective assessments. CONCLUSION. FIB-4 and multiple CT findings can identify patients with high-risk NAFLD (advanced fibrosis or cirrhosis). However, the presence of NASH is elusive on CT.

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.

Similar performance of liver stiffness measurement and liver surface nodularity for the detection of portal hypertension in patients with hepatocellular carcinoma

BACKGROUND & AIMS

We compare the performance of liver surface nodularity (LSN) and liver stiffness measurements (LSM) using transient elastography (TE) for the detection of clinically significant portal hypertension (CSPH) in patients with cirrhosis and hepatocellular carcinoma (HCC).

METHODS

All patients with cirrhosis and HCC who underwent computed tomography, LSM and hepatic venous pressure gradient (HVPG) measurements within 30 days between 2015 and 2018 were included. The estimation of CSPH by LSN and LSM, and the LSM-spleen-size-to-platelet ratio score (LSPS) were evaluated and compared.

RESULTS

In total, 140 patients were included (109 men [78%], mean age 63 ± 9 years old), including 39 (28%) with CSPH. LSN measurements were valid in 130 patients (93%) and significantly correlated with HVPG (r = 0.68; p <0.001). Patients with CSPH had higher LSN measurements compared with those without [3.1 ± 0.4 vs. 2.5 ± 0.3, p <0.001; area under the receiver operating characteristic (AUROC): 0.87 ± 0.31]. LSM and LSPS were valid in 132 patients (94%) and significantly correlated with HVPG (r = 0.75, p <0.001; AUROC 0.87 ± 0.04 and r = 0.68, p <0.001; AUROC 0.851 ± 0.04, respectively). There was no significant difference in the diagnostic performance between LSN and LSM-LSPS (DeLong, p = 0.28, 0.37, and 0.65, respectively) in patients with both valid tests (n = 122). LSN <2.50 had a 100% negative predictive value for CSPH. A 2-step algorithm combining LSN and LSPS for the diagnosis of CSPH classified 108/140 patients (77%) with an 8% error.

CONCLUSIONS

The diagnostic performance and feasibility of LSN measurements were similar to those of LSM for the detection of CSPH in patients with compensated cirrhosis and HCC. Combining LSN and LSPS accurately detected CSPH in >75% of patients. Such a combination could be useful in centres where the HVPG measurement is unavailable.

LAY SUMMARY

The diagnostic performance and feasibility of liver surface nodularity was similar to that of liver stiffness measurement (LSM) for the detection of clinically significant portal hypertension in patients with compensated cirrhosis. Thus, liver surface nodularity could be an option for the preoperative detection of clinically significant portal hypertension in patients with hepatocellular carcinoma. Combining liver surface nodularity with LSM-spleen-size-to-platelet ratio score resulted in the accurate detection of clinically significant portal hypertension in >75% of patients, thus limiting the need for HVPG measurements.

Liver Steatosis Categorization on Contrast-Enhanced CT Using a Fully Automated Deep Learning Volumetric Segmentation Tool: Evaluation in 1204 Healthy Adults Using Unenhanced CT as a Reference Standard

BACKGROUND. Hepatic attenuation at unenhanced CT is linearly correlated with the MRI proton density fat fraction (PDFF). Liver fat quantification at contrast-enhanced CT is more challenging. OBJECTIVE. The purpose of this article is to evaluate liver steatosis categorization on contrast-enhanced CT using a fully automated deep learning volumetric hepatosplenic segmentation algorithm and unenhanced CT as the reference standard. METHODS. A fully automated volumetric hepatosplenic segmentation algorithm using 3D convolutional neural networks was applied to unenhanced and contrast-enhanced series from a sample of 1204 healthy adults (mean age, 45.2 years; 726 women, 478 men) undergoing CT evaluation for renal donation. The mean volumetric attenuation was computed from all designated liver and spleen voxels. PDFF was estimated from unenhanced CT attenuation and served as the reference standard. Contrast-enhanced attenuations were evaluated for detecting PDFF thresholds of 5% (mild steatosis, 10% and 15% (moderate steatosis); PDFF less than 5% was considered normal. RESULTS. Using unenhanced CT as reference, estimated PDFF was ≥ 5% (mild steatosis), ≥ 10%, and ≥ 15% (moderate steatosis) in 50.1% (n = 603), 12.5% (n = 151) and 4.8% (n = 58) of patients, respectively. ROC AUC values for predicting PDFF thresholds of 5%, 10%, and 15% using contrast-enhanced liver attenuation were 0.669, 0.854, and 0.962, respectively, and using contrast-enhanced liver-spleen attenuation difference were 0.662, 0.866, and 0.986, respectively. A total of 96.8% (90/93) of patients with contrast-enhanced liver attenuation less than 90 HU had steatosis (PDFF ≥ 5%); this threshold of less than 90 HU achieved sensitivity of 75.9% and specificity of 95.7% for moderate steatosis (PDFF ≥ 15%). Liver attenuation less than 100 HU achieved sensitivity of 34.0% and specificity of 94.2% for any steatosis (PDFF ≥ 5%). A total of 93.8% (30/32) of patients with contrast-enhanced liver-spleen attenuation difference 10 HU or less had moderate steatosis (PDFF ≥ 15%); a liver-spleen difference less than 5 HU achieved sensitivity of 91.4% and specificity of 95.0% for moderate steatosis. Liver-spleen difference less than 10 HU achieved sensitivity of 29.5% and specificity of 95.5% for any steatosis (PDFF ≥ 5%). CONCLUSION. Contrast-enhanced volumetric hepatosplenic attenuation derived using a fully automated deep learning CT tool may allow objective categoric assessment of hepatic steatosis. Accuracy was better for moderate than mild steatosis. Further confirmation using different scanning protocols and vendors is warranted. CLINICAL IMPACT. If these results are confirmed in independent patient samples, this automated approach could prove useful for both individualized and population-based steatosis assessment.

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.

Relevance of liver surface nodularity for preoperative risk assessment in patients with resectable hepatocellular carcinoma

BACKGROUND

Quantification of liver surface nodularity (LSN) on routine preoperative CT images allows detection of cirrhosis and clinically significant portal hypertension. This study aimed to assess the relevance of LSN in preoperative assessment of operative risks for patients with resectable hepatocellular carcinoma (HCC).

METHODS

All patients undergoing hepatectomy for HCC between 2012 and 2017 were analysed retrospectively. LSN was assessed at the liver-fat interface on the left liver lobe on preoperative CT images. The feasibility of LSN quantification was assessed. The association between LSN and outcomes (severe complications and posthepatectomy liver failure (PHLF)) was evaluated by multivariable analysis and after propensity score matching.

RESULTS

Among 210 patients, LSN measurement was successful in 187 (89·0 per cent). Among these, the median LSN score was 2·42 (i.q.r. 2·21-2·66) and 52·9 per cent had severe fibrosis, including 33·7 per cent with cirrhosis. LSN score increased with hepatic venous pressure gradient (P = 0·048), severity of steatosis (P = 0·011) and fibrosis grade (P = 0·001). LSN score was independently associated with severe complications (odds ratio (OR) 5·25; P = 0·006) and PHLF (OR 6·78; P = 0·003). After matching with respect to model for end-stage liver disease, aspartate aminotransferase-to-platelet ratio index and fibrosis-4 score, patients with a LSN score of 2·63 or higher retained an increased risk of PHLF (OR 5·81; P = 0·018). In the subgroup of patients without severe fibrosis, LSN was accurate in predicting severe complications (P = 0·005). Patients with (P = 0·039) or without (P = 0·018) severe fibrosis with increased LSN score had a higher comprehensive complication index score. Among patients with cirrhosis who had clinically significant portal hypertension, a LSN value below 2·63 ruled out the risk of PHLF.

CONCLUSION

LSN measurement represents a practical tool that may allow improvement in the preoperative evaluation and management of patients with HCC.

ACR Appropriateness Criteria® Chronic Liver Disease

The liver fibrosis stage is the most important clinical determinate of morbidity and mortality in patients with chronic liver diseases. With newer therapies, liver fibrosis can be stabilized and possibly reversed, thus accurate diagnosis and staging of liver fibrosis are clinically important. Ultrasound, CT, and conventional MRI can be used to establish the diagnosis of advanced fibrosis/cirrhosis but have limited utility for assessing earlier stages of fibrosis. Elastography-based ultrasound and MRI techniques are more useful for assessment of precirrhotic hepatic fibrosis. In patients with advanced fibrosis at risk for hepatocellular carcinoma (HCC), ultrasound is the surveillance modality recommended by international guidelines in nearly all circumstances. However, in patients in whom ultrasound does not assess the liver well, including those with severe steatosis or obesity, multiphase CT or MRI may have a role in surveillance for HCC. Both multiphase CT and MRI can be used for continued surveillance in patients with a history of HCC, and contrast-enhanced ultrasound may have an emerging role in this setting. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Performance of liver surface nodularity quantification for the diagnosis of portal hypertension in patients with cirrhosis: comparison between MRI with hepatobiliary phase sequences and CT

PURPOSE

To assess and compare the performance of liver surface nodularity (LSN) quantification using Gd-BOPTA-enhanced MRI and contrast-enhanced CT for the diagnosis of clinically significant portal hypertension (CSPH) in patients with cirrhosis.

METHODS

This retrospective study included 30 patients with compensated histologically proven cirrhosis who underwent hepatic venous pressure gradient (HVPG), abdominal CT and Gd-BOPTA-MRI within a 60-day interval during pre-surgery workup for hepatocellular carcinoma (HCC) between January 2016 and August 2018. LSN score was derived from CT portal venous phase (PVP), axial T2- and T1-weighted PVP and hepatobiliary phase (HBP). Accuracy for the detection of CSPH was evaluated for each set of images by ROC curve analysis. Intra-observer, inter-observer and inter-method reproducibilities were assessed by the intraclass correlation coefficient (ICC) and coefficient of variation (CV).

RESULTS

Thirty patients were analysed (23 men [77%], mean age 60 ± 11 years old), including 15 (50%) with CSPH. All CT- and MRI-derived LSN quantifications were correlated to HVPG (CT-PVP: r = 0.63, p = 0.001, AUROC = 0.908 ± 0.06; T1-w-PVP: r = 0.43, p = 0.028, AUROC = 0.876 ± 0.07; T1-w-HBP: r = 0.50, p = 0.012, AUROC = 0.823 ± 0.08; T2-w: r = 0.51, p = 0.007, AUROC = 0.801 ± 0.09). There was no significant difference in AUROC pairwise comparisons (p = 0.12-0.88). Patients with CSPH had higher LSN than those without (CT-PVP: 3.2 ± 0.6 vs 2.4 ± 0.5, p < 0.001; T1-w-PVP: 2.7 ± 0.4 vs 2.2 ± 0.4, p = 0.002; T1-w-HBP: 3.0 ± 0.6 vs 2.3 ± 0.3, p < 0.001; T2-w: 3.0 ± 0.6 vs 2.2 ± 0.3, p = 0.001) and 86%, 82%, 85% and 82% of patients were correctly classified, respectively. Reproducibility of inter-image set comparisons was excellent (ICC = 0.84-0.96 and CV = 8.3-14.2%).

CONCLUSION

The diagnostic performance of MRI-based LSN for detecting CSPH is strong and similar to that of CT-based LSN.

Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment

Background Nonalcoholic fatty liver disease and its consequences are a growing public health concern requiring cross-sectional imaging for noninvasive diagnosis and quantification of liver fat. Purpose To investigate a deep learning-based automated liver fat quantification tool at nonenhanced CT for establishing the prevalence of steatosis in a large screening cohort. Materials and Methods In this retrospective study, a fully automated liver segmentation algorithm was applied to noncontrast abdominal CT examinations from consecutive asymptomatic adults by using three-dimensional convolutional neural networks, including a subcohort with follow-up scans. Automated volume-based liver attenuation was analyzed, including conversion to CT fat fraction, and compared with manual measurement in a large subset of scans. Results A total of 11 669 CT scans in 9552 adults (mean age ± standard deviation, 57.2 years ± 7.9; 5314 women and 4238 men; median body mass index [BMI], 27.8 kg/m²) were evaluated, including 2117 follow-up scans in 1862 adults (mean age, 59.2 years; 971 women and 891 men; mean interval, 5.5 years). Algorithm failure occurred in seven scans. Mean CT liver attenuation was 55 HU ± 10, corresponding to CT fat fraction of 6.4% (slightly fattier in men than in women [7.4% ± 6.0 vs 5.8% ± 5.7%; P < .001]). Mean liver Hounsfield unit varied little by age (<4 HU difference among all age groups) and only weak correlation was seen with BMI (r² = 0.14). By category, 47.9% (5584 of 11 669) had negligible or no liver fat (CT fat fraction <5%), 42.4% (4948 of 11 669) had mild steatosis (CT fat fraction of 5%-14%), 8.8% (1025 of 11 669) had moderate steatosis (CT fat fraction of 14%-28%), and 1% (112 of 11 669) had severe steatosis (CT fat fraction >28%). Excellent agreement was seen between automated and manual measurements, with a mean difference of 2.7 HU (median, 3 HU) and r² of 0.92. Among the subcohort with longitudinal follow-up, mean change was only -3 HU ± 9, but 43.3% (806 of 1861) of patients changed steatosis category between first and last scans. Conclusion This fully automated CT-based liver fat quantification tool allows for population-based assessment of hepatic steatosis and nonalcoholic fatty liver disease, with objective data that match well with manual measurement. The prevalence of at least mild steatosis was greater than 50% in this asymptomatic screening cohort. © RSNA, 2019.

Development of liver surface nodularity quantification program and its clinical application in nonalcoholic fatty liver disease

The liver morphological changes in relation to fibrosis stage in nonalcoholic fatty liver disease (NAFLD) have not yet been clearly understood. This study was to develop a liver surface nodularity (LSN) quantification program and to compare the fibrosis grades in simple steatosis (SS) and nonalcoholic steatohepatitis (NASH). Thirty subjects (7 normal controls [NC], 12 SS and 11 NASH) were studied. LSN quantification procedure was bias correction, boundary detection, segmentation and LSN measurement. LSN scores among three groups and fibrosis grades compared using Kruskal–Wallis H test. Diagnostic accuracy was determined by calculating the area under the receiver operating characteristics (ROC) curve. Mean LSN scores were NC 1.30 ± 0.09, SS 1.54 ± 0.21 and NASH 1.59 ± 0.23 (p = 0.008). Mean LSN scores according to fibrosis grade (F) were F0 1.30 ± 0.09, F1 1.45 ± 0.17 and F2&F3 1.67 ± 0.20 (p = 0.001). The mean LSN score in F2&F3 is significantly higher than that in F1 (p = 0.019). The AUROC curve to distinguish F1 and F2&F3 was 0.788 (95% CI 0.595–0.981, p = 0.019) at a cut-off LSN score greater than 1.48, and its diagnostic accuracy had 0.833 sensitivity and 0.727 specificity. This study developed LSN program and its clinical application demonstrated that the quantitative LSN scores can help to differentially diagnose fibrosis stage in 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.

Precision analysis of a quantitative CT liver surface nodularity score

PURPOSE

To evaluate precision of a software-based liver surface nodularity (LSN) score derived from CT images.

METHODS

An anthropomorphic CT phantom was constructed with simulated liver containing smooth and nodular segments at the surface and simulated visceral and subcutaneous fat components. The phantom was scanned multiple times on a single CT scanner with adjustment of image acquisition and reconstruction parameters (N = 34) and on 22 different CT scanners from 4 manufacturers at 12 imaging centers. LSN scores were obtained using a software-based method. Repeatability and reproducibility were evaluated by intraclass correlation (ICC) and coefficient of variation. Using abdominal CT images from 68 patients with various stages of chronic liver disease, inter-observer agreement and test-retest repeatability among 12 readers assessing LSN by software- vs. visual-based scoring methods were evaluated by ICC.

RESULTS

There was excellent repeatability of LSN scores (ICC:0.79-0.99) using the CT phantom and routine image acquisition and reconstruction parameters (kVp 100-140, mA 200-400, and auto-mA, section thickness 1.25-5.0 mm, field of view 35-50 cm, and smooth or standard kernels). There was excellent reproducibility (smooth ICC: 0.97; 95% CI 0.95, 0.99; CV: 7%; nodular ICC: 0.94; 95% CI 0.89, 0.97; CV: 8%) for LSN scores derived from CT images from 22 different scanners. Inter-observer agreement for the software-based LSN scoring method was excellent (ICC: 0.84; 95% CI 0.79, 0.88; CV: 28%) vs. good for the visual-based method (ICC: 0.61; 95% CI 0.51, 0.69; CV: 43%). Test-retest repeatability for the software-based LSN scoring method was excellent (ICC: 0.82; 95% CI 0.79, 0.84; CV: 12%).

CONCLUSION

The software-based LSN score is a quantitative CT imaging biomarker with excellent repeatability, reproducibility, inter-observer agreement, and test-retest repeatability.

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

PURPOSE

To evaluate semi-automated measurement of liver surface nodularity (LSN) on MDCT in a cause-specific cohort of patients with chronic hepatitis C virus infection (HCV) for identification of hepatic fibrosis (stages F0-4).

METHODS

MDCT scans in patients with known HCV were evaluated with an independently validated, semi-automated LSN measurement tool. Consecutive LSN measurements along the anterior liver surface were performed to derive mean LSN scores. Scores were compared with METAVIR fibrosis stage (F0-4). Fibrosis stages F0-3 were based on biopsy results within 1 year of CT. Most patients with cirrhosis (F4) also had biopsy within 1 year; the remaining cases had unequivocal clinical/imaging evidence of cirrhosis and biopsy was not indicated.

RESULTS

288 patients (79F/209M; mean age, 49.7 years) with known HCV were stratified based on METAVIR fibrosis stage: F0 (n = 43), F1 (n = 29), F2 (n = 53), F3 (n = 37), and F4 (n = 126). LSN scores increased with increasing fibrosis (mean: F0 = 2.3 ± 0.2, F1 = 2.4 ± 0.3, F2 = 2.6 ± 0.5, F3 = 2.9 ± 0.6, F4 = 3.8 ± 1.0; p < 0.001). For identification of significant fibrosis (≥ F2), advanced fibrosis (≥ F3), and cirrhosis (≥ F4), the ROC AUCs were 0.88, 0.89, and 0.90, respectively. The sensitivity and specificity for significant fibrosis (≥ F2) using LSN threshold of 2.80 were 0.68 and 0.97; for advanced fibrosis (≥ F3; threshold = 2.77) were 0.83 and 0.85; and for cirrhosis (≥ F4, LSN threshold = 2.9) were 0.90 and 0.80.

CONCLUSION

Liver surface nodularity assessment at MDCT allows for accurate discrimination of intermediate stages of hepatic fibrosis in a cause-specific cohort of patients with HCV, particularly at more advanced levels.