Estimation of Hepatic Extracellular Volume Fraction Using Multiphasic Liver Computed Tomography for Hepatic Fibrosis Grading:

Impact of pre-treatment extracellular volume fraction measured by computed tomography on response of primary lesion to preoperative chemotherapy in abdominal neuroblastoma

OBJECTIVES

To retrospectively investigate the impact of pre-treatment Extracellular Volume Fraction (ECV) measured by Computed Tomography (CT) on the response of primary lesions to preoperative chemotherapy in abdominal neuroblastoma.

METHODS

A total of seventy-five patients with abdominal neuroblastoma were retrospectively included in the study. The regions of interest for the primary lesion and aorta were determined on unenhanced and equilibrium phase CT images before treatment, and their average CT values were measured. Based on patient hematocrit and average CT values, the ECV was calculated. The correlation between ECV and the reduction in primary lesion volume was examined. A receiver operating characteristic curve was generated to assess the predictive performance of ECV for a very good partial response of the primary lesion.

RESULTS

There was a negative correlation between primary lesion volume reduction and ECV (r = -0.351, p = 0.002), and primary lesions with very good partial response had lower ECV (p < 0.001). The area under the curve for ECV in predicting the very good partial response of primary lesion was 0.742 (p < 0.001), with a 95 % Confidence Interval of 0.628 to 0.836. The optimal cut-off value was 0.28, and the sensitivity and specificity were 62.07 % and 84.78 %, respectively.

CONCLUSIONS

The measurement of pre-treatment ECV on CT images demonstrates a significant correlation with the response of the primary lesion to preoperative chemotherapy in abdominal neuroblastoma.

Computed Tomography-Derived Extracellular Volume Fraction and Splenic Size for Liver Fibrosis Staging

OBJECTIVE

Extracellular volume fraction (fECV) and liver and spleen size have been correlated with liver fibrosis stages and cirrhosis. The purpose of the current study was to determine the predictive value of fECV alone and in conjunction with measurement of liver and spleen size for severity of liver fibrosis.

METHODS

This was a retrospective study of 95 subjects (65 with liver biopsy and 30 controls). Spearman rank correlation coefficient was used to assess correlation between radiological markers and fibrosis stage. Receiver operating characteristic analysis was performed to assess the discriminative ability of radiological markers for significant (F2+) and advanced (F3+) fibrosis and cirrhosis (F4), by reporting the area under the curve (AUC).

RESULTS

The cohort had a mean age of 51.4 ± 14.4 years, and 52 were female (55%). There were 36, 5, 6, 9, and 39 in fibrosis stages F0, F1, F2, F3, and F4, respectively. Spleen volume alone showed the highest correlation (r = 0.552, P < 0.001) and AUCs of 0.823, 0.807, and 0.785 for identification of significant and advanced fibrosis and cirrhosis, respectively. Adding fECV to spleen length improved AUCs (0.764, 0.745, and 0.717 to 0.812, 0.781, and 0.738, respectively) compared with splenic length alone. However, adding fECV to spleen volume did not improve the AUCs for significant or advanced fibrosis or cirrhosis.

CONCLUSIONS

Spleen size (measured in length or volume) showed better correlation with liver fibrosis stages compared with fECV. The combination of fECV and spleen length had higher accuracy compared with fECV alone or spleen length alone.

Hepatic and pancreatic extracellular volume fraction analysis using contrast-enhanced CT in patients with diabetes mellitus and pre-diabetes

PURPOSE

Liver and pancreatic fibrosis is associated with diabetes mellitus (DM), and liver fibrosis is associated with pancreatic fibrosis. This study aimed to investigate the relationship between the hepatic and pancreatic extracellular volume fractions (fECVs), which correlate with tissue fibrosis, and their relationships with DM and pre-DM (pDM).

MATERIAL AND METHODS

We included 100 consecutive patients with known or suspected liver and/or pancreatic diseases who underwent contrast-enhanced CT. Patients were classified as nondiabetes, pDM, and DM with hemoglobin A1c (HbA1c) levels of < 5.7%, 5.7%-6.5%, and ≥ 6.5% or fasting plasma glucose (FPG) levels of < 100, 100-125 mg/dL, and ≥ 126 mg/dL, respectively. Subtraction images between unenhanced and equilibrium-phase images were prepared. The liver and the pancreas were automatically extracted using a high-speed, three-dimensional image analysis system, and their respective mean CT values were calculated. The enhancement degree of the aorta (Δaorta) was measured. fECV was calculated using the following equation: fECV = (100 - hematocrit) * Δliver or pancreas/Δaorta. Differences were investigated in hepatic and pancreatic fECVs among the three groups, and the correlation between each two in hepatic fECV, pancreatic fECV, and HbA1c was determined.

RESULTS

The pancreatic fECV, which was positively correlated with the hepatic fECV and HbA1c (r = 0.51, P < 0.001, and r = 0.51, P < 0.001, respectively), significantly differed among the three groups (P < 0.001) and was significantly greater in DM than in pDM or nondiabetes and in pDM with nondiabetes (P < 0.001). Hepatic fECV was significantly greater in DM than in nondiabetes (P < 0.05).

CONCLUSION

The pancreatic fECV and pDM/DM are closely related.

Nomogram based on dual-energy CT-derived extracellular volume fraction for the prediction of microsatellite instability status in gastric cancer

Purpose

To develop and validate a nomogram based on extracellular volume (ECV) fraction derived from dual-energy CT (DECT) for preoperatively predicting microsatellite instability (MSI) status in gastric cancer (GC).

Materials and methods

A total of 123 patients with GCs who underwent contrast-enhanced abdominal DECT scans were retrospectively enrolled. Patients were divided into MSI (n=41) and microsatellite stability (MSS, n=82) groups according to postoperative immunohistochemistry staining, then randomly assigned to the training (n=86) and validation cohorts (n=37). We extracted clinicopathological characteristics, CT imaging features, iodine concentrations (ICs), and normalized IC values against the aorta (nICs) in three enhanced phases. The ECV fraction derived from the iodine density map at the equilibrium phase was calculated. Univariate and multivariable logistic regression analyses were used to identify independent risk predictors for MSI status. Then, a nomogram was established, and its performance was evaluated by ROC analysis and Delong test. Its calibration performance and clinical utility were assessed by calibration curve and decision curve analysis, respectively.

Results

The ECV fraction, tumor location, and Borrmann type were independent predictors of MSI status (all P < 0.05) and were used to establish the nomogram. The nomogram yielded higher AUCs of 0.826 (0.729-0.899) and 0.833 (0.675-0.935) in training and validation cohorts than single variables (P<0.05), with good calibration and clinical utility.

Conclusions

The nomogram based on DECT-derived ECV fraction has the potential as a noninvasive biomarker to predict MSI status in GC patients.

Interpretable machine learning based on CT-derived extracellular volume fraction to predict pathological grading of hepatocellular carcinoma

PURPOSE

To develop a non-invasive auxiliary assessment method based on CT-derived extracellular volume (ECV) to predict the pathological grading (PG) of hepatocellular carcinoma (HCC).

METHODS

The study retrospectively analyzed 238 patients who underwent HCC resection surgery between January 2013 and April 2023. Six machine learning algorithms were employed to construct predictive models for HCC PG: logistic regression, extreme gradient boosting, Light Gradient Boosting Machine (LightGBM), random forest, adaptive boosting, and Gaussian naive Bayes. Model performance was evaluated using receiver operating characteristic curve analysis, including area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F1 score. Calibration plots were used for visual evaluation of model calibration. Clinical decision curve analysis was performed to assess potential clinical utility by calculating net benefit.

RESULTS

166 patients from Hospital A were allocated to the training set, while 72 patients from Hospital B (constituting 30.25% of the total sample) were assigned to the test set. The model achieved an AUC of 1.000 (95%CI: 1.000-1.000) in the training set and 0.927 (95%CI: 0.837-0.999) in the validation set, respectively. Ultimately, the model achieved an AUC of 0.909 (95%CI: 0.837-0.980) in the test set, with an accuracy of 0.778, sensitivity of 0.906, specificity of 0.789, negative predictive value of 0.556, and F1 score of 0.908.

CONCLUSION

This study successfully developed and validated a non-invasive auxiliary assessment method based on CT-derived ECV to predict the HCC PG, providing important supplementary information for clinical decision-making.

Automated classification of liver fibrosis stages using ultrasound imaging

BACKGROUND

Ultrasound imaging is the most frequently performed for the patients with chronic hepatitis or liver cirrhosis. However, ultrasound imaging is highly operator dependent and interpretation of ultrasound images is subjective, thus well-trained radiologist is required for evaluation. Automated classification of liver fibrosis could alleviate the shortage of skilled radiologist especially in low-to-middle income countries. The purposed of this study is to evaluate deep convolutional neural networks (DCNNs) for classifying the degree of liver fibrosis according to the METAVIR score using US images.

METHODS

We used ultrasound (US) images from two tertiary university hospitals. A total of 7920 US images from 933 patients were used for training/validation of DCNNs. All patient were underwent liver biopsy or hepatectomy, and liver fibrosis was categorized based on pathology results using the METAVIR score. Five well-established DCNNs (VGGNet, ResNet, DenseNet, EfficientNet and ViT) was implemented to predict the METAVIR score. The performance of DCNNs for five-level (F0/F1/F2/F3/F4) classification was evaluated through area under the receiver operating characteristic curve (AUC) with 95% confidential interval, accuracy, sensitivity, specificity, positive and negative likelihood ratio.

RESULTS

Similar mean AUC values were achieved for five models; VGGNet (0.96), ResNet (0.96), DenseNet (0.95), EfficientNet (0.96), and ViT (0.95). The same mean accuracy (0.94) and specificity values (0.96) were yielded for all models. In terms of sensitivity, EffcientNet achieved highest mean value (0.85) while the other models produced slightly lower values range from 0.82 to 0.84.

CONCLUSION

In this study, we demonstrated that DCNNs can classify the staging of liver fibrosis according to METAVIR score with high performance using conventional B-mode images. Among them, EfficientNET that have fewer parameters and computation cost produced highest performance. From the results, we believe that DCNNs based classification of liver fibrosis may allow fast and accurate diagnosis of liver fibrosis without needs of additional equipment for add-on test and may be powerful tool for supporting radiologists in clinical practice.

Prediction of pancreatic fibrosis by dual-energy CT-derived extracellular volume fraction: Comparison with MRI

OBJECTIVES

To investigate the correlation between dual-energy CT (DECT) and MRI measurements of the extracellular volume fraction (ECV) and to assess the accuracy of both methods in predicting pancreatic fibrosis (PF).

METHODS

We retrospectively analyzed 43 patients who underwent pancreatectomy and preoperative pancreatic DECT and MRI between November 2018 and May 2022. The ECV was calculated using the T1 relaxation time (for MR-ECV) or absolute enhancement (for DECT-ECV) at equilibrium phase (180 s after contrast injection in our study). Pearson coefficient and Bland-Altman analysis were used to compare the correlation between the two ECVs, Spearman correlations were used to investigate the association between imaging parameters and PF, Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the ECVs for advanced fibrosis (F2-F3), and multivariate logistic regression analysis was used to examine the relationship between PF and imaging parameters.

RESULTS

There was a strong correlation between DECT- and MR-derived ECVs (r = 0.948; p < 0.001). The two ECVs were positively correlated with PF (DECT: r = 0.647, p < 0.001; MR: r = 0.614, p < 0.001), and the mean values were 0.34 ± 0.08 (range: 0.22-0.62) and 0.35 ± 0.09 (range: 0.24-0.66), respectively. The area under the operating characteristic curve (AUC) for subjects with advanced fibrosis diagnosed by ECV was 0.86 for DECT-ECV and 0.87 for MR-ECV. Multivariate logistic regression analysis showed that the DECT-ECV was an independent predictor of PF.

CONCLUSIONS

The ECV could be an effective predictor of histological fibrosis, and DECT is equivalent to MRI for characterizing pancreatic ECV changes.

Extracellular volume by dual-energy CT, hepatic reserve capacity scoring, CT volumetry, and transient elastography for estimating liver fibrosis

Our purpose was to compare the efficacy of liver and splenic volumetry (LV and SV), extracellular volume (ECV) on dual-layer spectral-detector CT scoring systems for estimating liver fibrosis (LF) in 45 patients with pathologically staged LF. ECV measured on CT value (HU-ECV), iodine density (ID-ECV), atomic number (Zeff-ECV), and electron density (ED-ECV), LV or SV/body surface area (BSA), albumin bilirubin grade (ALBI), model for end-stage liver disease (MELD) score, aspartate aminotransferase platelet ratio index (APRI), and fibrosis index based on the four factors (FIB-4) were recorded. Transient elastography was measured in 22 patients, and compared to ECV. No correlation was found between transient elastography and all ECVs. Area under the curve (AUC) for estimating F4 on transient elastography was 0.885 (95% CI 0.745-1.000). ALBI was weakly associated with LF (p = 0.451), while MELD (p < 0.001), APRI (p = 0.010), and FIB-4 (p = 0.010) were significantly associated with LF. SV/BSA had a higher AUC than MELD, APRI, and FIB-4 for estimating F4 (AUC = 0.815, 95% CI 0.63-0.999), but MELD (AUC = 0.799, 95% CI 0.634-0.965), APRI (AUC = 0.722, 95% CI 0.561-0.883), and FIB-4 (AUC = 0.741, 95% CI 0.582-0.899) had higher AUCs than ALBI. SV/BSA significantly contributed to differentiation for estimating F4; odds ratio (OR) was 1.304-1.353 (Reader 1-2; R1-R2), whereas MELD significantly contributed to the differentiation between F0-2 and F3-4; OR was 1.528-1.509 (R1-R2). AUC for SV/BSA and MELD combined was 0.877 (95% CI 0.748-1.000). In conclusion, SV/BSA allows for a higher estimation of liver cirrhosis (F4). MELD is more suitable for assessing severe LF (≥ F3-4). The combination of SV/BSA and MELD had a higher AUC than SV/BSA alone for liver cirrhosis (F4).

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.

Correlations between contrast-enhanced CT-measured extracellular volume fraction, histopathological features, and MYCN amplification status in abdominal neuroblastoma: a retrospective study

PURPOSE

To retrospectively investigate the correlations between contrast-enhanced CT (CECT)-measured extracellular volume fraction (fECV) and histopathological features, as well as MYCN amplification status, in abdominal neuroblastoma.

MATERIALS AND METHODS

One hundred and forty-one patients with abdominal neuroblastoma who underwent CECT scanning were retrospectively enrolled. Calculation of fECV involved the measurement of CT values within regions of interest located within the neuroblastoma and aorta on both non-contrast-enhanced CT and equilibrium CECT. The correlations between fECV and various factors, including pathological subtype, mitosis karyorrhexis index (MKI), Shimada classification, MYCN amplification status, International Neuroblastoma Risk Group (INRG) stage, and risk group were analyzed using either the Mann-Whitney U test or Kruskal-Wallis test.

RESULTS

Neuroblastoma and ganglioneuroblastoma exhibited fECV values of 0.349 (0.252, 0.424) and 0.438 (0.327, 0.508), respectively, indicating a statistically significant difference (Z = 2.200, P = 0.028). Additionally, the fECV decreased significantly in neuroblastoma with high MKI (H = 8.314, P = 0.016) or unfavorable histology (Z = 3.880, P < 0.001), as well as in those with MYCN amplification (Z = 5.486, P < 0.001). Notably, a significant variation in fECV was observed among different INRG stages (H = 16.881, P <0.001) and risk groups (H = 29.014, P < 0.001).

CONCLUSION

CECT-derived fECV is associated with histopathological features, MYCN amplification status, INRG stage, and risk stratification of abdominal neuroblastoma, reflecting a potential correlation between the extracellular matrix and the biological behavior of neuroblastoma.

Extracellular volume fraction using contrast-enhanced CT is useful in differentiating intrahepatic cholangiocellular carcinoma from hepatocellular carcinoma

Objectives

To evaluate whether tumor extracellular volume fraction (fECV) on contrast-enhanced computed tomography (CT) aids in the differentiation between intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC).

Methods

In this retrospective study, 113 patients with pathologically confirmed ICC (n = 39) or HCC (n = 74) who had undergone preoperative contrast-enhanced CT were enrolled. Enhancement values of the tumor (Etumor) and aorta (Eaorta) were obtained in the precontrast and equilibrium phase CT images. fECV was calculated using the following equation: fECV [%] = Etumor/Eaorta × (100 - hematocrit [%]). fECV values were compared between the ICC and HCC groups using Welch's t-test. The diagnostic performance of fECV for differentiating ICC and HCC was assessed using receiver-operating characteristic (ROC) analysis. fECV and the CT imaging features of tumors were evaluated by two radiologists. Multivariate logistic regression analysis was performed to identify factors predicting a diagnosis of ICC.

Results

Mean fECV was significantly higher in ICCs (43.8% ± 13.2%) than that in HCCs (31.6% ± 9.0%, p < 0.001). The area under the curve for differentiating ICC from HCC was 0.763 when the cutoff value of fECV was 41.5%. The multivariate analysis identified fECV (unit OR: 1.10; 95% CI: 1.01-1.21; p < 0.05), peripheral rim enhancement during the arterial phase (OR: 17.0; 95% CI: 1.29-225; p < 0.05), and absence of washout pattern (OR: 235; 95% CI: 14.03-3933; p < 0.001) as independent CT features for differentiating between the two tumor types.

Conclusions

A high value of fECV, peripheral rim enhancement during the arterial phase, and absence of washout pattern were independent factors in the differentiation of ICC from HCC.

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.

Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation

BACKGROUND

Liver cirrhosis-acute decompensation (LC-AD) has rapid short-term disease progression and difficult early risk stratification. The purpose is to develop and validate a model based on dual-energy CT quantification of extracellular liver volume (ECV_IC-liver) for predicting the occurrence of acute-on-chronic liver failure (ACLF) within 90 days in patients with hepatitis B (HBV) LC-AD.

METHODS

The retrospective study included patients with HBV LC-AD who underwent dual-energy CT scans of the liver from January 2018 to March 2022 and were randomized to training group (215 patients) and validation group (92 patients). The primary outcome was the need for readmission within 90 days due to ACLF. Based on the training group data, independent risk factors for disease progression in clinical and dual-energy CT parameters were identified and modeled by logistic regression analysis. Based on the training and validation groups data, receiver operating characteristic (ROC) curves, calibration curves, and decision analysis curves (DCA) were used to verify the discrimination, calibration, and clinical validity of the nomogram.

RESULTS

Chronic liver failure consortium-acute decompensation score (CLIF-C ADs) (p = 0.008) and ECV_IC-liver (p < 0.001) were independent risk factors for ACLF within 90 days. The AUC of the model combined ECV_IC-liver and CLIF-C ADs were 0.893 and 0.838 in the training and validation groups, respectively. The calibration curves show good agreement between predicted and actual risks. The DCA indicates that the model has good clinical application.

CONCLUSION

The model combined ECV_IC-liver and CLIF-C ADs can early predict the occurrence of ACLF within 90 days in HBV LC-AD patients.

Extracellular Volume Fraction Calculated Using Contrast-Enhanced Computed Tomography as a Biomarker of Oxaliplatin-Induced Sinusoidal Obstruction Syndrome: A Preliminary Histopathological Analysis

Background

Oxaliplatin (OX)-based chemotherapy induces sinusoidal obstruction syndrome (SOS) in the nontumorous liver parenchyma, which can increase the risk of liver resection due to colorectal liver metastasis (CRLM). The extracellular volume (ECV) calculated from contrast-enhanced computed tomography (CT) has been reported to reflect the morphological change of hepatic fibrosis. The present retrospective study aimed to evaluate the ECV fraction as a predictive factor for OX-induced SOS.

Methods

Our study included 26 patients who underwent liver resection for CRLM after OX-based chemotherapy with a preoperative dynamic CT of appropriate quality. We investigated the relationship between the pathological SOS grade and the ECV fraction.

Results

Overall, 26 specimens from the patients were graded with the SOS classification of Rubbia-Brandt et al. as follows: grade 0, n = 17 (65.4%); grade 1, n = 4 (15.4%); and grade 2, n = 5 (19.2%). No specimens showed grade 3 SOS. In a univariate analysis, the ECV fraction in grade 0 SOS was significantly lower than that in grade 1 + 2 SOS (26.3 ± 3.4% vs. 30.6 ± 7.0%; P = 0.025). The cutoff value and AUC value of the ECV fraction to distinguish between grades 0 and 1 + 2 were 27.5% and 0.771, respectively.

Conclusions

Measurement of the ECV fraction was found to be a potential noninvasive diagnostic method for determining early-stage histopathological sinusoidal injury induced by OX-based chemotherapy.

A novel method for predicting hepatocellular carcinoma response to chemoembolization using an intraprocedural CT hepatic arteriography-based enhancement mapping: a proof-of-concept analysis

BACKGROUND

To evaluate the feasibility of a novel approach for predicting hepatocellular carcinoma (HCC) response to drug-eluting beads transarterial chemoembolization (DEB-TACE) using computed tomography hepatic arteriography enhancement mapping (CTHA-EM) method.

METHODS

This three-institution retrospective study included 29 patients with 46 HCCs treated with DEB-TACE between 2017 and 2020. Pre- and posttreatment CTHA-EM images were generated using a prototype deformable registration and subtraction software. Relative tumor enhancement (T_Post/pre-RE) defined as the ratio of tumor enhancement to normal liver tissue was calculated to categorize tumor response as residual (T_Post-RE > 1) versus non-residual (T_Post-RE ≤ 1) enhancement, which was blinded compared to the response assessment on first follow-up imaging using modified RECIST criteria. Additionally, for tumors with residual enhancement, CTHA-EM was evaluated to identify its potential feeding arteries.

RESULTS

CTHA-EM showed residual enhancement in 18/46 (39.1%) and non-residual enhancement in 28/46 (60.9%) HCCs, with significant differences on T_Post-RE (3.05 ± 2.4 versus 0.48 ± 0.23, respectively; p < 0.001). The first follow-up imaging showed non-complete response (partial response or stable disease) in 19/46 (41.3%) and complete response in 27/46 (58.7%) HCCs. CTHA-EM had a response prediction sensitivity of 94.7% (95% CI, 74.0-99.9) and specificity of 100% (95% CI, 87.2-100). Feeding arteries to the residual enhancement areas were demonstrated in all 18 HCCs (20 arteries where DEB-TACE was delivered, 2 newly developed collaterals following DEB-TACE).

CONCLUSION

CTHA-EM method was highly accurate in predicting initial HCC response to DEB-TACE and identifying feeding arteries to the areas of residual arterial enhancement.

A Preliminary Pathological Evaluation of Extracellular Volume Fraction with Contrast-enhanced Computed Tomography as a Novel Quantitative Parameter of Pancreatic Fibrosis

Objective The extracellular volume (ECV) calculated based on contrast-enhanced computed tomography (CT) has been reported as a novel imaging parameter reflecting the morphological change of fibrosis in several parenchymal organs. Our retrospective study assessed the validity of the ECV fraction for diagnosing pancreatic fibrosis and the appropriate imaging condition as the "equilibrium phase". Methods In 27 patients undergoing multiphasic CT and subsequent pancreaticoduodenectomy, we investigated pathological fibrotic changes related to the ECV fraction and conducted analyses using the value obtained by subtracting the equilibrium CT value of the portal vein from that of the abdominal aorta (Ao-PV_equilibrium) to estimate eligibility of the equilibrium phase. Results In all patients, the ECV fraction showed a weak positive correlation with the collagenous compartment ratio (r=0.388, p=0.045). All patients were divided into two groups - the high-Ao-PV_equilibrium group and low-Ao-PV_equilibrium group - based on the median value. No significant correlation was found in the high-Ao-PV_equilibrium group, whereas a significant correlation was observed in the low-Ao-PV_equilibrium group (r=0.566, p=0.035). Conclusion The ECV fraction is a possible predictive factor for histopathological pancreatic fibrosis. In its clinical application, the eligibility of the "equilibrium phase" may affect the diagnostic capability. It will be necessary to verify the imaging conditions in order to improve the accuracy of the diagnosis.

Extracellular volume fraction determined by equilibrium contrast-enhanced CT for the prediction of the pathological complete response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer

OBJECTIVES

To determine the extracellular volume (ECV) fraction derived from equilibrium contrast-enhanced CT for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal cancer (LARC).

METHODS

The ECV fraction before NCRT (ECV_pre) and/or ECV after NCRT (ECV_post) of rectal tumors was assessed, and ECV_Δ was calculated as ECV_post - ECV_pre. The histopathologic tumor regression grading (TRG) was assessed. pCR (TRG 0 grade) was defined as the absence of viable tumor cells in the primary tumor and lymph nodes. Demographic and clinicopathological characteristics and ECV fraction were compared between the pCR and non-pCR groups. A mixed model was constructed by logistic regression. The performance for predicting pCR was assessed with the area under the receiver-operator curve (AUC). The AUCs of the different methods were compared by the method proposed by DeLong et al. RESULTS: Seventy-five patients were included; 17 achieved pCR, and 58 achieved non-pCR. The ECV_post (17.05 ± 2.36% vs. 29.94 ± 1.20%; p < 0.001) and ECV_Δ (- 17.01 ± 3.01% vs. 0.44 ± 1.45%; p < 0.001) values in the pCR group were significantly lower than those in the non-pCR group. The mixed model that combined ECV_post with ECV_Δ achieved an AUC of 0.92 (95% confidence interval (CI) = 0.81-0.98), which was higher than that of ECV_post (AUC, 0.91 (95% CI = 0.80-0.97); p = 0.60) or ECV_Δ (AUC, 0.90 (95% CI = 0.79-0.97); p = 0.61).

CONCLUSIONS

ECV_post and ECV_Δ determined by using equilibrium contrast-enhanced CT were useful in distinguishing between pCR and non-pCR patients with LARC who received NCRT.

KEY POINTS

• ECV_post and ECV_Δ (ECV_post - ECV_pre) differed significantly between the non-pCR and pCR groups. • ECV_pre cannot be used to predict the efficacy of neoadjuvant chemoradiotherapy. • ECV_post combined with ECV_Δ had the best performance with an AUC of 0.92 for predicting pCR after NCRT in LARC.

Pancreatic fibrosis by extracellular volume fraction using Contrast-enhanced computed tomography and relationship with pancreatic cancer

PURPOSE

This study aimed to assess the relationship between pancreatic fibrosis measured by the extracellular volume fraction (ECV) using contrast-enhanced computed tomography (CT) and the histologic pancreatic fibrosis fraction and investigate the relationship between pancreatic fibrosis and pancreatic cancer.

METHOD

The study included 88 consecutive patients (48 males, 40 females; median age, 69 years; range, 17-89 years); 47 had pancreatic cancer, and 41 had other diseases. Fifty-two cases were evaluated pathologically for pancreatic fibrosis. The histologic pancreatic fibrosis fraction was quantified using image analysis software in nontumorous pancreatic tissue at the resection stump using 2-µm-thick Azan-stained slides. Two board-certified radiologists measured ECV in the pancreatic parenchyma at an estimated transection line. The correlation between histologic pancreatic fibrosis fraction and ECV was investigated, and whether the ECV value could be used as a biomarker for pancreatic cancer was investigated.

RESULTS

The histologic pancreatic fibrosis fraction was significantly correlated with the ECV (r = 0.64, P < 0.01). Pancreatic fibrosis evaluated by ECV was higher in pancreatic cancer patients than in other patients (P < 0.01). On receiver-operating characteristic curve analysis, the ECV had good diagnostic accuracy for the development of pancreatic cancer (cut-off value 32.8%; sensitivity 61.0%, specificity 85.1%). ECV was identified on multivariate analysis as an independent risk factor for pancreatic cancer (odds ratio 1.16; P < 0.01).

CONCLUSIONS

Extracellular volume fraction was strongly related to the histologic pancreatic fibrosis fraction, which was independently associated with pancreatic cancer. Thus, extracellular volume fraction is an imaging biomarker that reflects the progression of pancreatic fibrosis and may potentially help predict the development of pancreatic cancer, although further investigation will be needed.

Comparison between CT volumetry and extracellular volume fraction using liver dynamic CT for the predictive ability of liver fibrosis in patients with hepatocellular carcinoma

OBJECTIVES

To compare the predictive ability of liver fibrosis (LF) by CT-volumetry (CTV) for liver and spleen and extracellular volume fraction (ECV) for liver in patients undergoing liver resection.

METHODS

We retrospectively analysed 90 consecutive patients who underwent CTV and ECV. Manually placed region-of-interest ECV (manual-ECV), rigid-registration ECV (rigid-ECV), and nonrigid-registration ECV (nonrigid-ECV) were calculated as ECV(%) = (1-haematocrit) × (ΔHUliver/ΔHUaorta), where ΔHU = subtraction of unenhanced phase from equilibrium phase (240 s). Manual-ECV was compared with CTV for the estimation of LF. The total liver volume to body surface area (TLV/BSA), splenic volume to BSA (SV/BSA), ratio of TLV to SV (TLV/SV), ratio of right liver volume to SV (RV/SV), and liver segmental volume ratio (LSVR) were measured. ROC analyses were performed for ECV and CTV.

RESULTS

After excluding 10 patients, seventy-eight (97.5%) out of 80 patients had a Child-Pugh score of 5 points, and two (2.5%) patients had a Child-Pugh score of 6 points. AUC of ECV showed no significant difference among manual-ECV, rigid-ECV, and nonrigid-ECV. TLV/BSA, SV/BSA, TLV/SV, and RV/SV had a higher correlation with LF grades than manual-ECV. AUC of SV/BSA was significantly higher than that of manual-ECV in F0-1 vs F2-4 and F0-2 vs F3-4. AUC of SV/BSA (0.76-0.83) was higher than that of manual-ECV (0.61-0.75) for all LF grades, although manual-ECV could differentiate between F0-3 and F4 at high AUC (0.75).

CONCLUSIONS

In patients undergoing liver resection, SV/BSA is a better method for estimating severe LF grades, although manual-ECV has the ability to estimate cirrhosis (≥ F4).

KEY POINTS

The splenic volume is a better method for estimating liver fibrosis grades. The extracellular volume fraction is also a candidate for the estimation of severe liver fibrosis.

Noninvasive Liver Fibrosis Staging: Comparison of MR Elastography with Extracellular Volume Fraction Analysis Using Contrast-Enhanced CT

Purpose: To compare the accuracy of liver fibrosis staging with MR elastography and of staging with extracellular volume fraction (fECV) analysis using contrast-enhanced CT. Methods: This retrospective study included 60 patients who underwent both MR elastography and contrast-enhanced CT before liver surgery between October 2013 and July 2020. Two radiologists independently measured liver stiffness of MR elastography and fECV of CT images. Accuracy for liver fibrosis staging was assessed using receiver operating characteristic (ROC) analysis. Correlations between liver stiffness or fECV and liver fibrosis were also evaluated by means of the Spearman rank correlation coefficient. Results: The areas under the ROC curves for MR elastography for each stage differentiation of ≥F1 (0.85, 0.82 for the two radiologists), ≥F2 (0.88, 0.89), ≥F3 (0.87, 0.86), and F4 (0.84, 0.83) were greater than those for fECV analysis with CT (0.64, p = 0.06, 0.69, p = 0.2; 0.62, p < 0.005, 0.63, p < 0.005; 0.62, p < 0.005, 0.62, p < 0.01; and 0.70, p = 0.08, 0.71, p = 0.2, respectively). The correlation coefficients between liver stiffness and liver fibrosis in A0 (0.67, 0.69 for the two radiologists), A1 (0.64, 0.66) and A2 group (0.58, 0.51) were significantly higher than those between fECV and liver fibrosis (0.28, 0.30; 0.27, 0.31; and 0.23, 0.07; p < 0.05 for all comparisons). Conclusion: MR elastography allows for more accurate liver fibrosis staging compared with fECV analysis with CT. In addition, MR elastography may be less affected than fECV analysis by the inflammatory condition.

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.

What is the "washout" of hepatocellular carcinoma as observed on the equilibrium phase CT?: consideration based on the concept of extracellular volume fraction

PURPOSE

To verify the hypothesis that extracellular volume fraction (ECV) and precontrast CT density are the main determinants of washout of hepatocellular carcinoma (HCC) at the equilibrium phase CT.

MATERIALS AND METHODS

Between 2018 and 2020, patients with surgically resected HCC were recruited who had undergone preoperative 4-phase CT. Those larger than 6 cm were excluded to minimize the possibility of intratumoral hemorrhage or degeneration. Two radiologists reviewed the whole images in consensus and divided cases into washout positive and negative groups. Washout positive group at the equilibrium phase was defined as "HCC showing relatively low density as compared to the surrounding background liver (BGL), irrespective of the presence of early enhancement or fibrous capsule". Several clinico-pathological and radiological features, including ECV and precontrast CT density, were correlated to the presence of washout, using uni- and multi-variable analyses.

RESULTS

27 HCC in 24 patients met the inclusion criteria. 22 (82%) and five HCC belonged to washout positive and negative groups, respectively. Univariable analysis revealed ECV of HCC and BGL, ECV difference between HCC and BGL, and presence of fibrous capsule on the equilibrium phase CT were the significant factors. Multivariable analysis showed ECV of HCC and BGL, and precontrast CT density of BGL, were the independently significant factors related to washout, suggesting washout is more likely observed with lower HCC ECV, higher BGL ECV, and higher BGL precontrast CT density.

CONCLUSION

Major determinants of washout of HCC may be ECV of HCC and BGL, and precontrast CT density of BGL.

Assessment of liver cirrhosis severity with extracellular volume fraction MRI

We aimed to investigate the diagnostic utility of MRI extracellular volume fraction (ECV) for the assessment of liver cirrhosis severity as defined by Child–Pugh class. In this retrospective study, 90 patients (68 cirrhotic patients and 22 controls), who underwent multiparametric liver MRI, were identified. Hepatic T1 relaxation times and ECV were assessed. Clinical scores of liver disease severity were calculated. One-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test, Spearman’s correlation coefficient, and receiver operating characteristic (ROC) analysis were used for statistical analysis. In cirrhotic patients, hepatic native T1 increased depending on Child–Pugh class (620.5 ± 78.9 ms (Child A) vs. 666.6 ± 73.4 ms (Child B) vs. 828.4 ± 91.2 ms (Child C), P < 0.001). ECV was higher in cirrhotic patients compared to the controls (40.1 ± 11.9% vs. 25.9 ± 4.5%, P < 0.001) and increased depending of Child–Pugh class (33.3 ± 6.0% (Child A) vs. 39.6 ± 4.9% (Child B) vs. 52.8 ± 1.2% (Child C), P < 0.001). ECV correlated with Child–Pugh score (r = 0.64, P < 0.001). ECV allowed differentiating between Child–Pugh classes A and B, and B and C with an AUC of 0.785 and 0.944 (P < 0.001, respectively). The diagnostic performance of ECV for differentiating between Child–Pugh classes A and B, and B and C was higher compared to hepatic native T1 (AUC: 0.651 and 0.910) and MELD score (AUC: 0.740 and 0.795) (P < 0.05, respectively). MRI-derived ECV correlated with Child–Pugh score and had a high diagnostic performance for the discrimination of different Child–Pugh classes. ECV might become a valuable non-invasive biomarker for the assessment of liver cirrhosis severity.

Comparison of Liver Fibrosis and Function Indices with Extracellular Volume using Dual-Energy CT: A Retrospective Study

BACKGROUND

Dual-energy computed tomography (DECT) enables the direct measurement of iodine accumulation in the extracellular space.

OBJECTIVE

To compare measures of liver fibrosis and function with extracellular volume (ECV) from iodine/water images using DECT.

METHODS

Data was obtained from 119 consecutive patients who underwent abdominal DECT. A region of interest was set in the right lobe of the liver, pancreas, spleen, and aorta on iodine density images. ECV was calculated using the following formula: ECV = (1  hematocrit) × [iodine concentration in the liver (or pancreas, spleen) / iodine concentration in the aorta]. The severity of liver fibrosis was estimated using the aminotransferase/platelet ratio index (APRI) and the Fibrosis-4 (FIB-4) index. Liver function was assessed by the Child-Pugh classification and albumin-bilirubin (ALBI) grade. Data were analyzed by Spearman rank correlation coefficient, one-way analysis of variance, and post hoc analysis.

RESULTS

The correlation between ECV and fibrosis indices (APRI and FIB-4) was only significant and with a weak magnitude for the liver ECV quantification at the equilibrium phase (r=0.25 and r=0.20, respectively). The correlations between liver function index and ECV quantification were more robust than with fibrosis index. The highest correlations (r=0.50) were found between ALBI grade and liver ECV at the equilibrium phase. Liver ECV value at the equilibrium phase were significant difference between ALBI grade 1 vs. 2 and grade 1 vs. 3.

CONCLUSION

Liver ECV quantification by DECT is more suitable for evaluating liver function than liver fibrosis severity.

Myocardial Extracellular Volume Fraction Measured by Cardiac Magnetic Resonance Imaging Negatively Correlates With Cardiomyocyte Breadth in a Healthy Porcine Model

Background

The extracellular volume fraction (ECV) derived from cardiac magnetic resonance imaging (MRI) is extensively used to evaluate myocardial fibrosis. However, due to the limited histological verification in healthy individuals, it remains unclear whether the size of cardiomyocytes may play a potential role in the physiological changes of ECV. The aim of this study was to examine the association between cardiomyocyte size and myocardial ECV by using a healthy porcine model.

Methods

Sixteen domestic healthy pigs were anesthetized and underwent cardiac MRI with mechanical controlled breathing. Intravenous contrast medium was introduced at a dose of 0.2–0.25 mmol/kg. The interventricular septum ECV was calculated using an established MRI procedure, which was based on the pre- and post-contrast T1 values of the heart and individual blood hematocrit. The cardiomyocyte breadth (CmyB) in cross section was measured by hematoxylin and eosin staining to reflect the cardiomyocyte size.

Results

Data were successfully acquired from 14 pigs. The CmyB was obtained from the myocardial tissues corresponding to the region of interest on cardiac MRI. The mean ± SD of the ECV was 0.253 ± 0.043, and the mean ± SD of the CmyB was 10.02 ± 0.84 μm. The ECV exhibited a negative correlation with the CmyB (r = −0.729, p = 0.003).

Conclusion

The myocardial ECV detected by cardiac MRI is negatively correlated with the CmyB in healthy pigs, demonstrating that the size of cardiomyocytes is potentially associated with the ECV under physiological conditions.

Dual-Energy Computed Tomography in Diffuse Liver Diseases

Dual-energy computed tomography (DECT) is an advancement in the field of CT, where images are acquired at two energies. Materials are identified and quantified based on their attenuation pattern at two different energy beams using various material decomposition algorithms. With its ability to identify and quantify materials such as fat, calcium, iron, and iodine, DECT adds great value to conventional CT and has innumerable applications in body imaging. Continuous technological advances in CT scanner hardware, material decomposition algorithms, and image reconstruction software have led to considerable growth of these applications. Among all organs, the liver is the most widely investigated by DECT, and DECT has shown promising results in most liver applications. In this article, we aim to provide an overview of the role of DECT in the assessment of diffuse liver diseases, mainly the deposition of fat, fibrosis, and iron and review the most relevant literature.

Quantification of liver extracellular volume using dual-energy CT for ruling out high-risk varices in cirrhosis

PURPOSE

To determine the performance of quantification of liver extracellular volume fraction (fECV) using dual-energy CT (DECT) compared with CT imaging for ruling out high-riskesophageal varices(HRV) in cirrhotic patients.

METHODS

We retrospectively analyzed 229 cirrhotic patients (training [n = 159] and internal validation cohorts [n = 70]) who underwent dual-source DECT, serum marker assessment, and esophagogastroduodenoscopy (EGD) from 2017 to 2020. The fECV score was measured using iodine maps from 3-minute delayed, equilibrium-phase images at 100/140 Sn kVp. The association of CT parameters and serum markers with HRV was investigated. Criteria combining the fECV score (≤ 25.1%) or CT imaging with platelet count (> 150,000/mm³) were created and compared to rule out HRV.

RESULTS

In the training cohort, the fECV score (odds ratio (OR), 1.20; 95% confidence interval (CI), 1.09, 1.32) and CT imaging (OR, 28.21; 95% CI, 9.31, 85.93) were independent predictors of HRV, along with platelet count (OR, 0.85 and 0.78). Criteria combining the fECV score with platelet count showed significantly better performance than those combining CT imaging with platelet count in ruling out HRV (p < 0.001). Applying the criteria could have safely avoided an additional 10.7% and 8.6% of EGDs in the training and validation cohorts, respectively, achieving a final value of 36.5% and 35.7% spared EGDs (0 HRV missed) compared to CT imaging with platelet count.

CONCLUSIONS

The combined DECT-based fECV score with platelet count is useful for ruling out HRV and can safely avoid more EGDs than CT imaging with platelet count.

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

PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Assessing the progression of segmental fibrosis in chronic liver disease using extracellular volume fractions

PURPOSE

To assess the segmental difference of liver fibrosis during the progression of chronic liver disease (CLD) using hepatic extracellular volume fractions (fECVs) obtained by dual-energy CT.

METHODS

A total of 218 patients (92 men and 126 women; mean age, 67.8 ± 11.7 years) with CLD and 85 patients (44 men and 41 women; mean age, 62.8 ± 13.7 years) without CLD as a control underwent dual-energy computed tomography (CT) of the liver (5-min equilibrium phase images). The iodine densities of the lateral, medial, anterior, and posterior segments and the aorta were measured, and fECVs were calculated. Comparisons of the fECV of each segment and for each albumin-bilirubin (ALBI) grade were then statistically analyzed.

RESULTS

In the control group and ALBI grades 1 and 3, no significant difference in fECV was found between each segment, whereas in ALBI grade 2, the fECVs were significantly larger in the medial and anterior than in the other segments (p < 0.001). The fECVs of the lateral and posterior segments significantly increased with higher ALBI grade (p < 0.001). The fECVs of the medial and anterior segments were significantly increased with higher ALBI grade, up to grade 2 (p < 0.001), but no significant difference was found between ALBI grades 2 and 3.

CONCLUSION

During the progression of CLD, fibrosis antecedently progressed in the medial and anterior segments, followed by the other liver segments.

Evaluation of liver fibrosis using hepatic extracellular volume fraction by contrast-enhanced computed tomography before and after direct-acting antiviral therapy in patients with chronic hepatitis C infection: comparison with serological liver fibrosis markers

OBJECTIVE

To evaluate time-dependent changes in hepatic extracellular volume (ECV) fraction using contrast-enhanced CT (CECT) and serological liver fibrosis markers, the fibrosis-4 (FIB-4) index and aspartate aminotransferase to platelet ratio index (APRI), before and after direct-acting antiviral therapy (DAA) for hepatitis C virus (HCV) infection.

METHODS

41 HCV-infected patients who achieved sustained virological response (SVR) after DAA (SVR group) and 10 control patients (untreated or unresponsive to treatment) who underwent CECT and serum biochemical tests before or after the first examination/DAA (T1) and at intervals thereafter (T2:<6 months after T1, T3: at 6-12 months, T4: at 12-24 months, and T5:>24 months) were evaluated.

RESULTS

In the control group, ECV fractions remained relatively unchanged through the study, and significant differences in FIB-4 index comparisons and APRI comparisons were only seen between the T2 and T4 values (p = 0.046 and p = 0.028, respectively). In the SVR group, ECV fractions were significantly different between T1 and T4 and T1 and T5 (p = 0.046 and 0.022, respectively), and both FIB-4 index and APRI were significantly different between T1 and all other time points (p = 0.017 to p < 0.001 and p = 0.001 to p < 0.001, respectively).

CONCLUSION

After DAA, ECV fraction decreased slowly, suggesting an improvement in hepatic fibrosis, while serological liver fibrosis markers decreased immediately, probably due to improvement in hepatic inflammation.

ADVANCES IN KNOWLEDGE

ECV fraction has the potential to be a non-invasive biomarker for the assessment of liver fibrosis after direct-acting antiviral therapy.

Estimation of pancreatic fibrosis and prediction of postoperative pancreatic fistula using extracellular volume fraction in multiphasic contrast-enhanced CT

OBJECTIVE

To investigate the diagnostic performance of the extracellular volume (ECV) fraction in multiphasic contrast-enhanced computed tomography (CE-CT) for estimating histologic pancreatic fibrosis and predicting postoperative pancreatic fistula (POPF).

METHODS

Eighty-five patients (49 men; mean age, 69 years) who underwent multiphasic CE-CT followed by pancreaticoduodenectomy with pancreaticojejunal anastomosis between January 2012 and December 2018 were retrospectively included. The ECV fraction was calculated from absolute enhancements of the pancreas and aorta between the precontrast and equilibrium-phase images, followed by comparisons among histologic pancreatic fibrosis grades (F0‒F3). The diagnostic performance of the ECV fraction in advanced fibrosis (F2‒F3) was evaluated using receiver operating characteristic curve analysis. Multivariate logistic regression analysis was used to evaluate the associations of the risk of POPF development with patient characteristics, histologic findings, and CT imaging parameters.

RESULTS

The mean ECV fraction of the pancreas was 34.4% ± 9.5, with an excellent intrareader agreement of 0.811 and a moderate positive correlation with pancreatic fibrosis (r = 0.476; p < 0.001). The mean ECV fraction in advanced fibrosis was significantly higher than that in no/mild fibrosis (44.4% ± 10.8 vs. 31.7% ± 6.7; p < 0.001), and the area under the receiver operating characteristic curve for the diagnosis of advanced fibrosis was 0.837. Twenty-two patients (25.9%) developed clinically relevant POPF. Multivariate logistic regression analysis demonstrated that the ECV fraction was a significant predictor of POPF.

CONCLUSIONS

The ECV fraction can offer quantitative information for assessing pancreatic fibrosis and POPF after pancreaticojejunal anastomosis.

KEY POINTS

• There was a moderate positive correlation of the extracellular volume (ECV) fraction of the pancreas in contrast-enhanced CT with the histologic grade of pancreatic fibrosis (r = 0.476; p < 0.001). • The ECV fraction was higher in advanced fibrosis (F2‒F3) than in no/mild fibrosis (F0‒F1) (p < 0.001), with an AUC of 0.837 for detecting advanced fibrosis. • The ECV fraction was an independent risk factor for predicting subclinical (odds ratio, 0.81) and clinical (odds ratio, 0.80) postoperative pancreatic fistula.

Importance of extracellular volume fraction of the spleen as a predictive biomarker for high-risk esophago-gastric varices in patients with chronic liver diseases: A preliminary report

PURPOSE

To clarify clinico-radiological factors for high-risk esophago-gastric varices (EGV), including extracellular volume fraction (ECV) of the liver, pancreas, and the spleen.

METHODS

Between 2014 and 2018, 70 chronic liver disease patients who underwent 4-phase CT of the upper abdomen and either of upper gastrointestinal tract endoscopy, or actual treatment for bleeding EGV, within three months after CT, were retrospectively included. Patients were subdivided into high-risk EGV group (HRG), who had high-risk endoscopic findings or actual hemostatic treatments, and non-high-risk EGV group (NHRG). ECV of the liver, pancreas, and the spleen was measured on the ECV map generated from routine diagnostic CT data, and additional clinico-radiological factors including direct visualization of EGV on portal venous phase CT, were correlated to HRG, using both univariable and multivariable analyses.

RESULTS

There were 8 and 62 patients in HRG, and NHRG, respectively. None had symptoms related to EGV at the time of CT examinations. Univariable analysis revealed splenic volume, liver and splenic ECVs, and EGV visualization on portal venous phase CT, as significant factors. Multivariable analysis suggested that EGV visualization, splenic ECV, and splenic volume were independently significant factors. Using these three factors, sensitivity/specificity/positive predictive value/negative predictive value/accuracy = 100/85/40/100/87% were obtained with partition model analysis.

CONCLUSIONS

High-risk EGV can be predicted with acceptable accuracy using routine diagnostic CT data including splenic ECV.

CT-Based Prediction of Liver Function and Post-PVE Hypertrophy Using an Artificial Neural Network

Background: This study aimed to evaluate whether hypertrophy after portal vein embolization (PVE) and maximum liver function capacity (LiMAx) are predictable by an artificial neural network (ANN) model based on computed tomography (CT) texture features. Methods: We report a retrospective analysis on 118 patients undergoing preoperative assessment by CT before and after PVE for subsequent extended liver resection due to a malignant tumor at RWTH Aachen University Hospital. The LiMAx test was carried out in a subgroup of 55 patients prior to PVE. Associations between CT texture features and hypertrophy as well as liver function were assessed by a multilayer perceptron ANN model. Results: Liver volumetry showed a median hypertrophy degree of 33.9% (16.5–60.4%) after PVE. Non-response, defined as a hypertrophy grade lower than 25%, was found in 36.5% (43/118) of the cases. The ANN prediction of the hypertrophy response showed a sensitivity of 95.8%, specificity of 44.4% and overall prediction accuracy of 74.6% (p < 0.001). The observed median LiMAx was 327 (248–433) μg/kg/h and was strongly correlated with the predicted LiMAx (R² = 0.89). Conclusion: Our study shows that an ANN model based on CT texture features is able to predict the maximum liver function capacity and may be useful to assess potential hypertrophy after performing PVE.

Non-invasive assessment of cirrhosis using multiphasic dual-energy CT iodine maps: correlation with model for end-stage liver disease score

PURPOSE

To determine whether multiphasic dual-energy (DE) CT iodine quantitation correlates with the severity of chronic liver disease.

METHODS

We retrospectively included 40 cirrhotic and 28 non-cirrhotic patients who underwent a multiphasic liver protocol DECT. All three phases (arterial, portal venous (PVP), and equilibrium) were performed in DE mode. Iodine (I) values (mg I/ml) were obtained by placing regions of interest in the liver, aorta, common hepatic artery, and portal vein (PV). Iodine slopes (λ) were calculated as follows: (I_equilibrium-I_arterial)/time and (I_equilibrium-I_PVP)/time. Spearman correlations between λ and MELD scores were evaluated, and the area under the curve of the receiver operating characteristic (AUROC) was calculated to distinguish cirrhotic and non-cirrhotic patients.

RESULTS

Cirrhotic and non-cirrhotic patients had significantly different λ_{equilibrium-arterial} [IQR] for the caudate (λ = 2.08 [1.39-2.98] vs 1.46 [0.76-1.93], P = 0.007), left (λ = 2.05 [1.50-2.76] vs 1.51 [0.59-1.90], P = 0.002) and right lobes (λ = 1.72 [1.12-2.50] vs 1.13 [0.41-0.43], P = 0.003) and for the PV (λ = 3.15 [2.20-5.00] vs 2.29 [0.85-2.71], P = 0.001). λ_{equilibrium-PVP} were significantly different for the right (λ = 0.11 [- 0.45-1.03] vs - 0.44 [- 0.83-0.12], P = 0.045) and left lobe (λ = 0.30 [- 0.25-0.98] vs - 0.10 [- 0.35-0.24], P = 0.001). Significant positive correlations were found between MELD scores and λ_{equilibrium-arterial} for the caudate lobe (ρ = 0.34, P = 0.004) and λ_{equilibrium-PVP} for the caudate (ρ = 0.26, P = 0.028) and right lobe (ρ = 0.33, P = 0.007). AUROC in distinguishing cirrhotic and non-cirrhotic patients were 0.72 (P = 0.002), 0.71 (P = 0.003), and 0.75 (P = 0.001) using λ_{equilibrium-arterial} for the left lobe, right lobe, and PV, respectively. The λ_{equilibrium-PVP} AUROC of the right lobe was 0.73 (P = 0.001).

CONCLUSION

Multiphasic DECT iodine quantitation over time is significantly different between cirrhotic and non-cirrhotic patients, correlates with the MELD score, and it could potentially serve as a non-invasive measure of cirrhosis and disease severity with acceptable diagnostic accuracy.

Liver fibrosis assessment with multiphasic dual-energy CT: diagnostic performance of iodine uptake parameters

OBJECTIVES

To evaluate the ability of iodine uptake parameters from hepatic multiphasic CT to predict liver fibrosis, and compare absolute contrast enhancement (ΔHU) with dual-energy iodine density (ID) methods.

METHODS

One hundred seventeen patients with pathologically proven liver fibrosis who underwent dual-energy CT during portal-venous phase (PVP) and 3-min delayed phase (DP) between January 2017 and Octotber 2019 were retrospectively included. Two radiologists measured the hepatic and blood-pool iodine uptake using ΔHU and ID methods; extracellular volume fraction (ECV) and the iodine washout rate (IWR) calculated with both methods were compared between different fibrosis stages (F0-1 vs. F2-4, F0-2 vs. F3-4, or F0-3 vs. F4). The inter-observer reproducibility (intraclass correlation coefficients [ICCs]) for ECV and IWR was compared between the ΔHU and ID methods. The areas under the receiver operating characteristic curves (AUCs) to predict liver fibrosis severity were calculated for serum and imaging fibrosis markers. To identify independent predictors, multivariable logistic regression analysis was performed, and combined performance was assessed for the ΔHU and ID models.

RESULTS

Patients with F ≥ 2 (n = 70), F ≥ 3 (n = 51), and F4 (n = 29) had higher ECV and lower IWR than those with F ≤ 1, F ≤ 2, and F ≤ 3, respectively (all p < 0.001). ICCs were higher in the ID method than in the ΔHU method (ECV: p = 0.045; IWR: p < 0.001). The AUC ranges of ECV_ΔHU, ECV_ID, IWR_ΔHU, and IWR_ID for predicting liver fibrosis severity were 0.65-0.71, 0.67-0.73, 0.76-0.81, and 0.81-0.85, respectively. IWR and fibrosis-4 index were independent predictors, with combined AUCs of 0.82-0.87 for the ΔHU model and 0.86-0.89 for the ID model.

CONCLUSIONS

IWR more accurately predicted liver fibrosis than ECV in routine multiphasic CT. The dual-energy ID method yielded higher inter-observer reproducibility and predictive values than the single-energy ΔHU method.

KEY POINTS

• The IWR calculated from hepatic iodine uptake during PVP and 3-min DP predicted liver fibrosis (AUC, 0.76-0.85), while the ECV had a relatively limited predictive value (ACU, 0.65-0.73). • Compared with the conventional ΔHU method, the dual-energy ID method provided superior inter-observer reproducibility for measurement of ECV (p = 0.046) and IWR (p < 0.001). • The IWR and FIB-4 served as independent predictors of liver fibrosis; their combination yielded the high diagnostic performance particularly when using the ID method (combined AUCs of 0.86-0.89).

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.

Dual-energy CT quantification of fractional extracellular space in cirrhotic patients: comparison between early and delayed equilibrium phases and correlation with oesophageal varices

OBJECTIVE

Fractional extracellular space has been validated as a marker of hepatic fibrotic in cirrhotic patients at CT-scan as well as on dual-energy CT, which takes advantage from iodine uptake. Since no consensus still exists between equilibrium phases performed at 3 or 10 min, the first aim of this work is to evaluate performances at the two different time points. Moreover, correlation between fractional extracellular space and oesophageal varices, directly related to liver fibrosis, has been assessed.

MATERIALS AND METHODS

Dual-Energy equilibrium phases at 3 and 10 min were performed within a follow-up CT-protocol scan in cirrhotic patients. Oesophageal varices were endoscopically assessed according to their size. At the two different time points, correlation between iodine density of the right and left liver lobes and correlation between the fractional extracellular space values were assessed. Correlation between fractional extracellular space and endoscopic grade of oesophageal varices was calculated.

RESULTS

No statistical differences were found between the iodine density values from the two liver lobes at the two time points (p = 0.8 at 3'; p = 0.5 at 10'). No statistical difference about fractional extracellular space estimation was found between the two time points (p = 0.17). Correlation between fractional extracellular space values and oesophageal varices was moderate (ρ = 0.45, IC 0.08-0.71, p < 0.05).

CONCLUSION

Fractional extracellular space assessed on dual-energy CT at equilibrium phases with different timing was substantially similar. The moderate correlation found between fractional extracellular space and endoscopic grade of oesophageal varices confirms that CT-scan is not currently reliable as endoscopy.

Hepatic fibrosis grading with extracellular volume fraction from iodine mapping in spectral liver CT

PURPOSE

To determine whether hepatic extracellular volume fraction (ECV) obtained from iodine density map (ECV-iodine) can be used to estimate hepatic fibrosis grade and to compare performance with ECV measured using Hounsfield units (ECV-HU).

METHODS

From December 2016 to March 2019, patients who underwent liver resection or biopsy within four weeks after spectral liver CT were included. ECV-iodine and ECV-HU were calculated using the equilibrium phase. Within each of these, comparison of ECVs was made for different fibrosis grades (F0 - 1 vs. F2 - 3 vs. F4) and also for patients with compensated and decompensated cirrhosis. The diagnostic performance of ECVs in detecting clinically significant fibrosis (≥ F2) and cirrhosis (F4) was assessed using ROC analysis.

RESULTS

A total of 144 patients (men = 98, mean age 58.1 ± 11.5 years) were included. The ECV-iodine value was significantly higher in cirrhosis (33.6 ± 6.8 %) than those with F0 - 1 (25.0 ± 3.7 %) or F2 - 3 (28.3 ± 3.4 %, P < 0.001 for all). It was significantly higher in decompensated cirrhosis than those with compensated cirrhosis (36.5 ± 7.2 % vs. 30.7 ± 5.0 %, respectively; P < 0.001). The AUC of ECV-iodine was 0.82 for detecting F2 or above (cut-off value, > 26.9 %) and 0.81 for detecting cirrhosis (cut-off value, > 29 %). ECV-iodine had a significantly higher AUC than ECV-HU for detecting F2 or above (AUC: 0.69, P <  0.001) and cirrhosis (AUC: 0.74, P =  0.04).

CONCLUSIONS

ECV-iodine from spectral CT was able to detect clinically significant hepatic fibrosis and cirrhosis.

Added Value of CT Arterial Subtraction Images in Liver Imaging Reporting and Data System Treatment Response Categorization for Transcatheter Arterial Chemoembolization-Treated Hepatocellular Carcinoma

OBJECTIVES

The aim of this study was to assess the benefit of adding arterial subtraction images from computed tomography (CT) to the Liver Imaging Reporting and Data System (LI-RADS) v2018 treatment response (LR-TR) categorization in patients treated with transcatheter arterial chemoembolization (TACE) for hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

This retrospective study included 115 patients with 151 HCCs treated by TACE using an emulsion of doxorubicin and iodized oil who underwent multiphasic CT protocol that additionally generated arterial subtraction images based on nonrigid anatomic correction algorithm. Of 151 HCCs, 67 (44.4%) were viable and 84 (55.6%) were nonviable. Two independent readers assessed the per-lesion LR-TR categories in set 1 of multiphasic CT images alone and set 2 including both set 1 and CT arterial subtraction images, besides diagnostic confidence, and the quality of subtraction images. The sensitivity and specificity of LR-TR viable category between the sets were compared using the generalized estimating equation. Interobserver agreements of LR-TR categorization in each set and the quality of subtraction images were assessed by Cohen κ.

RESULTS

The quality of subtraction images was mostly good to perfect (98.7%) with good interobserver agreement (κ = 0.71), and none were nondiagnostic. For detecting viable HCC, LR-TR viable category showed sensitivity of 53.7% to 56.7% and specificity of 96.4% to 98.8% in set 1. In comparison, set 2 showed significantly higher sensitivity of 88.1% to 89.6% (P < 0.002) and equivalent specificity of 94% to 95.2% (P > 0.13) for the same category. In sets 1 and 2, 31.3% to 34.3% and 9% to 10.4% of viable HCC were miscategorized as LR-TR nonviable, respectively. LR-TR equivocal category was less assigned in set 2 (1.3%) than in set 1 (6.6%-7.9%). Set 2 showed slightly higher level of confidence for LR-TR categorization compared with set 1 (3.4 ± 0.8 vs 3.8 ± 0.5). Interobserver agreement was excellent in both sets (κ = 0.85 in set 1 and 0.97 in set 2).

CONCLUSIONS

The LR-TR viable category is highly specific but inadequately sensitive for detecting viable tumor in TACE-treated HCC on conventional multiphasic CT. Adding arterial subtraction images to the conventional CT images significantly increases sensitivity without compromising the specificity and improves the diagnostic confidence of LR-TR viable category.

A noninvasive index to predict liver cirrhosis in biliary atresia

BACKGROUND

Biliary atresia is a progressive obliterative cholangiopathy affecting both extrahepatic and intrahepatic biliary trees, resulting in fibrous obliteration of the biliary tract and subsequent development of cirrhosis.

OBJECTIVE

The aim of this study was to find noninvasive indices to predict the status of hepatic fibrosis in children with biliary atresia.

MATERIALS AND METHODS

We retrospectively measured the volume of the hepatic lobes and spleen from MR images, obtained biochemical data and analyzed the relationship between the imaging and biochemical indices, and the pathological status of hepatic fibrosis in 35 children with biliary atresia.

RESULTS

A combined index was obtained by logistic regression: logit (likelihood of cirrhosis) = 0.00043 x age at MR examination + 1.67 x aspartate aminotransferase and platelet ratio index (APRI) + 0.0029 x body-surface-area-adjusted left liver lobe volume (BSA adLLV) - 6.57 (log-likelihood chi-square P<0.05, pseudo-R²=0.59). The area under the receiver operator characteristic curve of age at MR examination, APRI, BSA adLLV and the combined index for prediction of cirrhosis were 0.91, 0.86, 0.83 and 0.94, respectively. The optimal cut-off value (sensitivity and specificity) of age at MR examination, APRI, BSA adLLV and combined index were 132 (86% and 92%), 1.3 (91% and 85%), 855.5 (96% and 62%) and 0.689 (91% and 92%). The accuracy of age at MR examination, APRI, BSA adLLV and combined index were 89%, 89%, 83% and 91%, respectively.

CONCLUSION

A combined noninvasive index of age, aspartate aminotransferase and platelet ratio index, and the body-surface-area-adjusted left liver lobe volume measured from MR images is a potential marker of liver cirrhosis in children with biliary atresia.

Noninvasive assessment of liver fibrosis by dual-layer spectral detector CT

PURPOSE

To elucidate the diagnostic ability of liver fibrosis using (1) liver parenchymal iodine density on equilibrium computed tomographic imaging and (2) extracellular volume (ECV) measured by dual-layer spectral detector CT.

METHODS

From April 2018 to June 2019, 68 patients [mean age, 62 years; 39 males, 29 females] underwent dynamic contrast-enhanced CT by a dual-layer spectral detector CT system before liver transplantation or liver resection. The iodine densities of liver parenchyma (I _liver) and aorta (I _aorta) were independently measured by two radiologists at the equilibrium phase. The iodine-density ratio (I-ratio) (I _liver/ I _aorta) and the CT-ECV were calculated. Spearman's rank correlation coefficient was used to analyze the relationship between the I-ratio or the CT-ECV and the fibrosis stage. A receiver operating characteristic (ROC) curve analysis was performed to determine the accuracy of the I-ratio and the CT-ECV for discriminating fibrosis stages.

RESULTS

For both readers, the I-ratio and the CT-ECV increased significantly as the fibrosis stage advanced (I-ratio: rho = 0.380 and 0.443, p < 0.01; CT-ECV: rho = 0.423 and 0.469, p < 0.01). The CT-ECV showed better diagnostic accuracy for staging fibrosis, and the area under the ROC curve values for discriminating F4 stage were 0.884 and 0.925. The two readers' cutoff values of the CT-ECV for diagnosing fibrosis as F4 were 26.2 % and 29.3 %, with 95.0 % and 90.0 % sensitivity and 72.9 % and 85.4 % specificity, respectively.

CONCLUSION

The liver parenchymal iodine density on the equilibrium phase and the CT-ECV can be useful for predicting a high stage of liver fibrosis.

Dual-Energy Computed Tomography of the Liver: Uses in Clinical Practices and Applications

Dual-energy computed tomography (DECT) is an imaging technique based on data acquisition at two different energy settings. Recent advances in CT have allowed data acquisitions and simultaneous analyses of X-rays at two energy levels, and have resulted in novel developments in the field of abdominal imaging. The use of low and high X-ray tube voltages in DECT provide fused images that improve the detection of liver tumors owing to the higher contrast-to-noise ratio (CNR) of the tumor compared with the liver. The use of contrast agents in CT scanning improves image quality by enhancing the CNR and signal-to-noise ratio while reducing beam-hardening artifacts. DECT can improve detection and characterization of hepatic abnormalities, including mass lesions. The technique can also be used for the diagnosis of steatosis and iron overload. This article reviews and illustrates the different applications of DECT in liver imaging.

Noninvasive Staging of Liver Fibrosis Using 5-Minute Delayed Dual-Energy CT: Comparison with US Elastography and Correlation with Histologic Findings

Background Normalized iodine concentration (NIC) (ratio of iodine concentration of liver to that of aorta) of liver at delayed dual-energy CT (DECT) may reflect the amount of fibrosis based on the extent of iodine uptake. Purpose To stage liver fibrosis by using 5-minute delayed DECT and compare findings with those of transient elastography (TE), shear-wave elastography (SWE), and histologic examination. Materials and Methods This prospective study included patients with chronic liver disease who were scheduled to undergo multiphase abdominal CT and liver biopsy from January 2017 to September 2018. Fifty individuals being screened as renal donors comprised the control group. Study participants underwent TE, SWE, multiphasic DECT (including 5-minute delayed dual-energy scanning), and liver biopsy. Multiphasic DECT and SWE were performed in the control group. The NIC of the right lobe of the liver (RNIC) was compared with liver stiffness (LS) as measured with TE and SWE and with the METAVIR fibrosis stage (ranging from F0 to F4). Diagnostic performance was assessed by using areas under the receiver operating characteristic curve (AUCs). Results A total of 107 participants (mean age, 35 years ± 12 [standard deviation]; 57 men) and 50 control subjects (mean age, 47 years ± 11; 29 women) were evaluated. The RNIC showed strong correlation with METAVIR stage (Spearman ρ = 0.81, P < .001). The AUC for RNIC with each METAVIR stage ranged between 0.86 (95% CI: 0.76, 0.97) and 0.96 (95% CI: 0.92, 0.99). The cut-off value of RNIC was 0.24 (sensitivity: 85% [86 of 101 participants; 95% CI: 77%, 91%]; specificity: 83% [84 of 101 participants; 95% CI: 42%, 98%]) for stage F1 fibrosis and 0.29 (sensitivity: 84% [67 of 80 participants; 95% CI: 74%, 90%]; specificity: 81% [65 of 80 participants; 95% CI: 63%, 92%]) for stage F2 fibrosis. RNIC correlated well with LS as measured with TE and SWE (Spearman ρ = 0.60 and 0.64, respectively; P < .001). Conclusion Normalized iodine concentration of liver at 5-minute delayed dual-energy CT showed strong correlation with the histologic stages of liver fibrosis and good diagnostic performance in estimating liver fibrosis. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Chandarana and Shanbhogue in this issue.

Dual-energy CT in diffuse liver disease: is there a role?

Dual-energy CT (DECT) can be defined as the use of two different energy levels to identify and quantify material composition. Since its inception, DECT has benefited from remarkable improvements in hardware and clinical applications. DECT enables accurate identification and quantification of multiple materials, including fat, iron, and iodine. As a consequence, multiple studies have investigated the potential role of DECT in the assessment of diffuse liver diseases. While this role is evolving, this article aims to review the most relevant literature on use of DECT for assessment of diffuse liver diseases. Moreover, the basic concepts on DECT techniques, types of image reconstruction, and DECT-dedicated software will be described, focusing on the areas that are most relevant for the evaluation of diffuse liver diseases. Also, we will review the evidence of added value of DECT in detection and assessment of hepatocellular carcinoma which is a known risk in patients with diffuse liver disease.

Liver function quantification of patients with portal vein embolization using dynamic contrast-enhanced MRI for assessment of hepatocyte uptake and elimination

PURPOSE

We evaluated pharmacokinetic models which quantify liver function including biliary elimination based on a dynamic Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) technique with sparse data collection feasible in clinical routine.

METHODS

Twelve patients with embolized liver segments following interventional treatment of primary liver cancer or hepatic metastasis underwent MRI. During Gd-EOB-DTPA bolus administration, a 3D dynamic gradient-echo (GRE) MRI examination was performed over approx. 28 min. Interrupted data sampling was started approx. 5 min after contrast agent administration. Different implementations of dual-inlet models were tested, namely the Euler method (DE) and convolution with residue functions (C). A simple uptake model (U) and an uptake- elimination model (UE) extended by incorporating the biliary contrast agent elimination rate (K_e) were evaluated.

RESULTS

The uptake-elimination model, calculated via the simple Euler method (UE- DE) and by convolution (UE-C), yielded similar overall estimates in terms of fitting quality and agreement with published values. The Euler method was approx. 50 times faster and yielded a mean elimination rate of K_e=1.8±1.2mL/(min·100 mL) in nonembolized liver tissue, which was significantly higher (p=8.8·10^-4) than in embolized tissue K_e=0.4±0.4 mL/(min·100 mL). Fractional hepatocyte volume v_h was not significantly higher in nonembolized tissue (52.4 ± 13.4 mL/100 mL) compared to embolized tissue (44.4 ± 26.1 mL/100 mL).

CONCLUSIONS

Interrupted late enhancement MRI data sampling in conjunction with the uptake-elimination model, deconvolved by integration of the differential rate equation and combined with the simple uptake model implemented with the Euler method (U-DE), turned out to be a stable and practical method for reliable noninvasive assessment of liver function.

Liver extracellular volume fraction values obtained with magnetic resonance imaging can quantitatively stage liver fibrosis: a validation study in monkeys with nonalcoholic steatohepatitis

OBJECTIVES

This study was to evaluate the diagnostic value of liver extracellular volume (LECV) for the staging of liver fibrosis in a cynomolgus monkey model of nonalcoholic steatohepatitis (NASH).

METHODS

Forty-eight cynomolgus monkeys were enrolled in this prospective study. There are 17 healthy monkeys and 31 monkeys with NASH. Ten of these monkeys were used for repeatability assessment. The remaining 38 monkeys were used to compare LECV with other indicators including pathology fibrosis score, native T1, and serum chemical indexes by Spearman, Pearson correlation test, and ROC curves. The inter-reader variability was assessed by interclass correlation. The repeatability measurement of LECV was analyzed using Bland-Altman plots and the coefficient of variation. Partial correlation analysis was performed to assess the effects of fat content and inflammation scores on the correlation between LECV/T1 and liver fibrosis score.

RESULTS

This study demonstrated a good intra-reader agreement (intraclass correlation = 0.79) of LECV in all monkeys and an excellent repeatability in 10 monkeys (coefficient of variation = 2.01%). The LECV has a strong correlation with the fibrosis score (r = 0.949; p < 0.0001), low-density lipoprotein (r = 0.72; p < 0.0001), and cholesterol (r = 0.70; p < 0.0001). LECV showed high diagnostic efficacy in the diagnosis of liver fibrosis (area under the curve of ROC, 0.945~1; p < 0.001).

CONCLUSIONS

LECV may serve as a noninvasive valuable biomarker for the quantification and differentiating of the non-severe liver fibrosis (stage ≤ F3). However, circulating serum markers low-density lipoprotein and cholesterol (CHO) may not serve for this purpose.

KEY POINTS

• This paper demonstrated the excellent repeatability (intraclass correlation coefficient = 0.79) of LECV in monkey animal model. • LECV-MRI has a strong correlation with histopathological fibrosis score stage (r = 0.949; p < 0.0001) and shows high diagnostic efficacy in the staging of non-severe liver fibrosis (the area under ROC curve ≥ 0.945). • The new fibrosis score maps appeared to provide a better imaging tool for the spatial assessment of liver fibrosis. It may eventually facilitate the diagnosis of liver fibrosis distribution.

Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach

Background

To evaluate whether machine learning algorithms allow the prediction of Child-Pugh classification on clinical multiphase computed tomography (CT).

Methods

A total of 259 patients who underwent diagnostic abdominal CT (unenhanced, contrast-enhanced arterial, and venous phases) were included in this retrospective study. Child-Pugh scores were determined based on laboratory and clinical parameters. Linear regression (LR), Random Forest (RF), and convolutional neural network (CNN) algorithms were used to predict the Child-Pugh class. Their performances were compared to the prediction of experienced radiologists (ERs). Spearman correlation coefficients and accuracy were assessed for all predictive models. Additionally, a binary classification in low disease severity (Child-Pugh class A) and advanced disease severity (Child-Pugh class ≥ B) was performed.

Results

Eleven imaging features exhibited a significant correlation when adjusted for multiple comparisons with Child-Pugh class. Significant correlations between predicted and measured Child-Pugh classes were observed (ρ_LA = 0.35, ρ_RF = 0.32, ρ_CNN = 0.51, ρ_ERs = 0.60; p < 0.001). Significantly better accuracies for the prediction of Child-Pugh classes versus no-information rate were found for CNN and ERs (p ≤ 0.034), not for LR and RF (p ≥ 0.384). For binary severity classification, the area under the curve at receiver operating characteristic analysis was significantly lower (p ≤ 0.042) for LR (0.71) and RF (0.69) than for CNN (0.80) and ERs (0.76), without significant differences between CNN and ERs (p = 0.144).

Conclusions

The performance of a CNN in assessing Child-Pugh class based on multiphase abdominal CT images is comparable to that of ERs.