Comparison between CT volumetry, technetium99m galactosyl-serum-albumin scintigraphy, and gadoxetic-acid-enhanced MRI to estimate the liver fibrosis stage in preoperative patients.

OBJECTIVES: To compare the efficacy of computed tomography volumetry (CTV), technetium99m galactosyl-serum-albumin (99mTc-GSA) scintigraphy, and gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic-acid-enhanced MRI (EOB-MRI) in estimating the liver fibrosis (LF) stage in patients undergoing liver resection. METHODS: This retrospective study included 91 consecutive patients who had undergone preoperative dynamic CT and 99mTc-GSA scintigraphy. EOB-MRI was performed in 76 patients. CTV was used to measure the total liver volume (TLV), spleen volume (SV), normalised to the body surface area (BSA), and liver-to-spleen volume ratio (TLV/SV). 99mTc-GSA scintigraphy provided LHL15, HH15, and GSA indices. The liver-to-spleen ratio (LSR) was calculated in the hepatobiliary phase of EOB-MRI. Hyaluronic acid and type 4 collagen levels were measured in 65 patients. Logistic regression and receiver operating characteristic (ROC) analyses were performed to identify useful parameters for estimating the LF stage and laboratory data. RESULTS: According to the multivariable logistic regression analysis, SV/BSA (odds ratio [OR], 1.01; 95% confidence interval [CI], 1.003-1.02; p = 0.011), LSR (OR, 0.06; 95%CI, 0.004-0.70; p = 0.026), and hyaluronic acid (OR, 1.01; 95%CI, 1.001-1.02; p = 0.024) were independent variables for severe LF (F3-4). Combined SV/BSA, LSR, and hyaluronic acid correctly estimated severe LF, with an AUC of 0.91, which was significantly larger than the AUCs of the GSA index (AUC = 0.84), SV/BSA (AUC = 0.83), or LSR (AUC = 0.75) alone. CONCLUSIONS: Combined CTV, EOB-MRI, and hyaluronic acid analyses improved the estimation accuracy of severe LF compared to CTV, EOB-MRI, or 99mTc-GSA scintigraphy individually. CLINICAL RELEVANCE STATEMENT: The combined analysis of spleen volume on CT volumetry, liver-to-spleen ratio on gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic-acid-enhanced MRI, and hyaluronic acid can identify severe liver fibrosis associated with a high risk of liver failure after hepatectomy and recurrence in patients with hepatocellular carcinoma. KEY POINTS: • Spleen volume of CT volumetry normalised to the body surface area, liver-to-spleen ratio of EOB-MRI, and hyaluronic acid were independent variables for liver fibrosis. • CT volumetry and EOB-MRI enable the detection of severe liver fibrosis, which may correlate with post-hepatectomy liver failure and complications. • Combined CT volumetry, gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic-acid-enhanced MRI (EOB-MRI), and hyaluronic acid analyses improved the estimation of severe liver fibrosis compared to technetium99m galactosyl-serum-albumin scintigraphy.

Tumor stiffness measurement using magnetic resonance elastography can predict recurrence and survival after curative resection of hepatocellular carcinoma.

BACKGROUND: Tumor stiffness measurement using magnetic resonance elastography can assess tumor mechanical properties and predict hepatocellular carcinoma recurrence. This study aimed to investigate preoperative tumor stiffness on magnetic resonance elastography as a predictor of overall survival and recurrence-free survival in patients with solitary nodular hepatocellular carcinoma who underwent curative resection. METHODS: Seventy-eight patients with solitary nodular hepatocellular carcinoma who underwent preoperative magnetic resonance elastography and curative resection were retrospectively analyzed. Potential associations of tumor stiffness and other clinicopathological variables with overall survival and recurrence-free survival were analyzed in both univariate and multivariate Cox proportional hazards analyses. The optimal tumor stiffness cutoff value was determined using the minimal P value approach. RESULTS: In multivariate analysis, tumor stiffness (hazard ratio 1.31; 95% confidence interval, 1.07-1.59; P = .008) and vascular invasion (hazard ratio 2.62; 95% confidence interval, 1.27-5.17; P = .010) were independent predictors of recurrence-free survival. For overall survival, tumor stiffness (hazard ratio, 1.33; 95% confidence interval, 1.02-1.76; P = .037) was the only independent predictor. The optimal tumor stiffness cutoff value was 5.81 kPa for both overall survival and recurrence-free survival. Patients with tumor stiffness ≥5.81 kPa had a significantly greater risk of death (hazard ratio 6.10; 95% confidence interval, 2.11-21.90; P < .001) than those with tumor stiffness <5.81 kPa. CONCLUSION: Preoperative tumor stiffness as measured by magnetic resonance elastography was a predictor of overall survival and recurrence-free survival in hepatocellular carcinoma patients who underwent curative resection. Higher tumor stiffness was associated with higher risk of recurrence and death.

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.

A proposed model on MR elastography for predicting postoperative major complications in patients with hepatocellular carcinoma.

OBJECTIVE: To develop a model for predicting post-operative major complications in patients with hepatocellular carcinoma (HCC). METHODS: In all, 186 consecutive patients with pre-operative MR elastography were included. Complications were categorised using Clavien‒Dindo classification, with major complications defined as ≥Grade 3. Liver-stiffness measurement (LSM) values were measured on elastogram. The indocyanine green clearance rate of liver remnant (ICG-Krem) was based on the results of CT volumetry, intraoperative data, and ICG-K value. For an easy application to the prediction model, the continuous variables were converted to categories. Moreover, logistic regression analysis and fivefold cross-validation were performed. The prediction model's discriminative performance was evaluated using the area under the receiver operating characteristic curve (AUC), and the calibration of the model was assessed by the Hosmer‒Lemeshow test. RESULTS: 43 of 186 patients (23.1%) had major complications. The multivariate analysis demonstrated that LSM, albumin-bilirubin (ALBI) score, intraoperative blood loss, and ICG-Krem were significantly associated with major complications. The median AUC of the five validation subsets was 0.878. The Hosmer-Lemeshow test confirmed no evidence of inadequate fit (p = 0.13, 0.19, 0.59, 0.59, and 0.73) on the fivefold cross-validation. The prediction model for major complications was as follows: -2.876 + 2.912 [LSM (>5.3 kPa)]+1.538 [ALBI score (>-2.28)]+0.531 [Intraoperative blood loss (>860 ml)]+0.257 [ICG-Krem (<0.10)]. CONCLUSION: The proposed prediction model can be used to predict post-operative major complications in patients with HCC. ADVANCES IN KNOWLEDGE: The proposed prediction model can be used in routine clinical practice to identify post-operative major complications in patients with HCC and to strategise appropriate treatments of HCC.

Predictive value of combined computed tomography volumetry and magnetic resonance elastography for major complications after liver resection.

PURPOSE: To retrospectively compare the predictive value of computed tomography volumetry (CTV), magnetic resonance elastography (MRE) of the liver, and their combination for major complications after liver resection. METHODS: We enrolled 108 consecutive patients who underwent anatomical liver resection for liver tumors and preoperative contrast-enhanced CT and MRE. The future liver remnant (FLR) ratio was calculated by CTV, while the liver stiffness measurement (LSM) was obtained by MRE. FLR ratio alone, LSM alone, and combined FLR ratio and LSM were evaluated to predict major complications (Clavien-Dindo grade ≥ IIIa). Univariate and multivariate analyses of hepatic biochemical parameters and imaging data were performed to identify predictors of major complications. Receiver operating characteristic analyses of FLR ratio, LSM, and their combination were performed, and the sensitivity and specificity were calculated. RESULTS: Twenty-two (20.4%) of the 108 patients experienced major complications. According to multiple regression analysis, the FLR ratio (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.91-0.99, p = 0.040) and LSM (OR 1.72, 95% CI 1.01-2.94, p = 0.047) were independent predictors of major complications. The combined FLR ratio and LSM were predictive of major complications, with an area under the curve (AUC) of 0.818, sensitivity of 68.2%, and specificity of 84.9%. The AUC and specificity for combined FLR ratio and LSM were larger than those for FLR ratio (AUC: 0.711, specificity: 80.2%) and LSM (AUC: 0.793, specificity: 80.2%). CONCLUSION: Combined CTV and MRE analysis can improve the AUC and specificity for predicting major complications after anatomical liver resection.

Prediction of esophageal varices by liver and spleen MR elastography.

OBJECTIVES: We aimed to assess the diagnostic performance of MR elastography (MRE) in predicting esophageal varices (EVs) in patients with chronic liver disease. METHODS: We prospectively performed liver (LSM) and spleen stiffness measurements (SSM) using MRE and endoscopic screening for EVs to determine if patients with hepatocellular carcinoma were eligible for resection. We investigated whether LSM, SSM, and other non-invasive preoperative parameters were associated with the presence of EVs. In order to predict EVs, 211 patients were divided into training (n = 140) and test (n = 71) groups. A nomogram was built using independent factors based on logistic regression analysis in the training group and its accuracy was validated using an independent cohort. RESULTS: Forty-six patients (21.8%) were diagnosed as having EVs (mild, n = 36; severe, n = 10). According to multiple regression analysis, LSM (odds ratio, 2.362; 95% confidence interval [CI], 1.341-4.923; p = 0.001) and SSM (1.489; 1.095-2.235; p = 0.010) were independent predictors of EVs in the training group. The nomogram showed good discrimination, with a C-index of 0.942 (95% CI, 0.892-0.974) through internal validation, and good calibration. Application of the nomogram in the test group still gave good discrimination (C-index, 0.948; 95% CI, 0.868-0.995). CONCLUSIONS: The combination of LSM and SSM using MRE is an accurate tool to identify patients at risk for EVs. KEY POINTS: • Performance of MR elastography can estimate the presence of esophageal varices non-invasively. • Liver and spleen stiffness measurements are independent predictors for esophageal varices. • The nomogram using a combination of liver and spleen stiffness measurements allows for the risk of esophageal varices.