OBJECTIVE: Liver resection is currently considered the most effective treatment for patients with liver cancer. To the best of our knowledge, no study has investigated the association between gadoxetic acid-enhanced magnetic resonance imaging (MRI) findings and liver regeneration in patients who underwent hemihepatectomy. We aimed to clarify the relationship between the signal intensity (SI) of the liver parenchyma on gadoxetic acid-enhanced MRI and the degree of liver regeneration in patients who underwent hemihepatectomy.
METHODS: Forty-one patients who underwent gadoxetic acid-enhanced MRI before hemihepatectomy were enrolled. We calculated the liver-to-erector spinae muscle SI ratio (LMR) in the hepatobiliary phase and the precontrast images. ΔLMR was calculated using the following equation: ΔLMR = (LMR in the hepatobiliary phase-LMR in the precontrast image)/LMR in the precontrast image. The preoperative and postoperative remnant liver volumes (LVs) were calculated using CT volumetry. We calculated the resection rate (RR) and liver regeneration index (LRI) using the following formulas: RR = Resected LV/Total LV × 100 and LRI = (postoperative remnant LV-preoperative remnant LV)/preoperative remnant LV × 100. The relationships among LRI, imaging, and clinicopathological factors were analyzed.
RESULTS: Univariate analysis showed RR and ΔLMR showed a positive correlation with LRI (ρ = 0.4133, p = 0.0072 and ρ = 0.7773, p < 0.001, respectively). Spleen volume showed a negative correlation with LRI (ρ = -0.3138, p = 0.0486). Stepwise multiple regression analysis showed ΔLMR and RR were independently correlated with LRI (β coefficient = 44.8771, p = 0.0198 and β coefficient = 1.9653, p < 0.001, respectively).
CONCLUSIONS: ΔLMR may serve as a preoperative predictor of liver regeneration in patients undergoing hemihepatectomy.

BACKGROUND: In cases of coronavirus disease 2019 (COVID-19), favipiravir is commonly included to the therapy regimen. Drug interactions between favipiravir and other COVID-19 therapy drugs are frequently researched. However, no research on possible drug interactions between Favipiravir and radiocontrast agents, which have become almost crucial in diagnostic processes while not being part of the treatment, has been found.
OBJECTIVE: To determine potential medication interactions between Favipiravir and radiocontrast agents.
METHODS: The study comprised patients who were taking Favipiravir for COVID-19 therapy and underwent a contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI) test while taking the medicine. The computerized patient files of the cases included in the study, as well as the pharmacovigilance forms in the designated hospital, were evaluated for this purpose.
RESULTS: The study included the evaluation of data from 1046 patients. The study sample\'s mean age was 47.23 ± 9.48 years. The mean age of cases with drug interactions was statistically significant greater than that of cases with no drug interactions (P = 0.003). When evaluated with logistic regression analysis, a 1-year raises in age increases the risk of developing drug interactions by 1.63 times (P = 0.023). There was no statistically significant difference in the occurrence of medication interactions between the sexes (P = 0.090). Possible medication interactions were discovered in 42 cases (4%).
CONCLUSIONS: The findings of this study revealed that the most notable findings as a result of the combined use of contrast agents and favipiravir were increased creatinine and transaminase values, as well as an increase in the frequency of nausea and vomiting. The majority of drug interactions discovered were modest enough that they were not reflected in the clinic. Drug interactions become more common as people get older.

OBJECTIVE: To investigate the prognostic value of enhancement patterns of intrahepatic mass-forming cholangiocarcinomas (IMCCs) during the hepatobiliary phase (HBP) in gadoxetic acid (Gd-EOB)-enhanced MRI.
METHODS: We retrospectively identified 66 consecutive patients with histopathologically proven IMCCs (reference standard: resection) and preoperative Gd-EOB-enhanced MRI. Gd-EOB retention area was subjectively rated based on areas of intermediate signal intensity. Lesions were classified as either hypointense (0-25% retention area) or significantly-retaining (>25% retention area). Clinical, radiological, and prognostic features were compared between these groups. The primary endpoints were recurrence-free survival (RFS) and overall survival (OS) after primary surgical resection.
RESULTS: 73% (48/66) of lesions were rated as hypointense and 29% (19/66) as significantly-retaining. While the hypointense subgroup more frequently featured local and distant intrahepatic metastases (p = 0.039 and p = 0.022) and an infiltrative growth pattern (p = 0.005), RFS, OS, and clinical features did not differ significantly with estimated Gd-EOB retention area or quantitatively measured HBP enhancement ratios. Lymph node metastasis was an independent predictor of poor RFS (p = 0.001).
CONCLUSIONS: Gd-EOB-enhanced MRI revealed two subtypes of IMCC in the HBP: hypointense and signal-retaining. The hypointense subtype is associated with more frequent intrahepatic metastases and an infiltrative growth pattern, indicating potential tumor aggressiveness. However, this did not result in a significant difference in survival after the primary resection of IMCC.

OBJECTIVE: To evaluated the impact of a deep learning (DL)-based image reconstruction on multi-arterial-phase magnetic resonance imaging (MA-MRI) for small hypervascular hepatic masses in patients who underwent gadoxetic acid-enhanced liver MRI.
METHODS: We retrospectively enrolled 55 adult patients (aged ≥ 18 years) with small hepatic hypervascular mass (≤ 3 cm) between December 2022 and February 2023. All patients underwent MA-MRI, subsequently reconstructed with a DL-based application. Qualitative assessment with Linkert scale including motion artifact (MA), liver edge (LE), hepatic vessel clarity (HVC) and image quality (IQ) was performed. Quantitative image analysis including signal to noise ratio (SNR), contrast to noise ratio (CNR) and noise was performed.
RESULTS: On both arterial phases (APs), all qualitative parameters were significantly improved after DL-based image reconstruction. (LE on 1st AP, 1.22 vs 1.61; LE on 2nd AP, 1.21 vs 1.65; HVC on 1st AP, 1.24 vs 1.39; HVC on 2nd AP, 1.24 vs 1.44; IQ on 1st AP, 1.17 vs 1.45; IQ on 2nd AP, 1.17 vs 1.47, all p values < 0.05). The SNR, CNR and noise were significantly improved after DL-based image reconstruction. (SNR on AP1, 279.08 vs 176.14; SNR on AP2, 334.34 vs 199.24; CNR on AP1, 106.09 vs 64.14; CNR on AP2, 129.66 vs 73.73; noise on AP1, 1.51 vs 2.33; noise on AP2, 1.45 vs 2.28, all p values < 0.05).
CONCLUSIONS: Gadoxetic acid-enhanced MA-MRI with DL-based image reconstruction improved the qualitative and quantitative parameters. Despite the short acquisition time, high-quality MA-MRI is now achievable.

OBJECTIVE: Accurate prediction of recurrence risk after resction in patients with Hepatocellular Carcinoma (HCC) may help to individualize therapy strategies. This study aimed to develop machine learning models based on preoperative clinical factors and multiparameter Magnetic Resonance Imaging (MRI) characteristics to predict the 1-year recurrence after HCC resection.
METHODS: Eighty-two patients with single HCC who underwent surgery were retrospectively analyzed. All patients underwent preoperative gadoxetic acidenhanced MRI examination. Preoperative clinical factors and MRI characteristics were collected for feature selection. Least Absolute Shrinkage and Selection Operator (LASSO) was applied to select the optimal features for predicting postoperative 1-year recurrence of HCC. Four machine learning algorithms, Multilayer Perception (MLP), random forest, support vector machine, and k-nearest neighbor, were used to construct the predictive models based on the selected features. A Receiver Operating Characteristic (ROC) curve was used to assess the performance of each model.
RESULTS: Among the enrolled patients, 32 patients experienced recurrences within one year, while 50 did not. Tumor size, peritumoral hypointensity, decreasing ratio of liver parenchyma T1 value (ΔT1), and α-fetoprotein (AFP) levels were selected by using LASSO to develop the machine learning models. The area under the curve (AUC) of each model exceeded 0.72. Among the models, the MLP model showed the best performance with an AUC, accuracy, sensitivity, and specificity of 0.813, 0.742, 0.570, and 0.853, respectively.
CONCLUSIONS: Machine learning models can accurately predict postoperative 1-year recurrence in patients with HCC, which may help to provide individualized treatment.

To elucidate how precisely microvascular invasion (MVI) in hepatocellular carcinoma (HCC) can be predicted using multiparametric assessment of gadoxetic acid-enhanced MRI.
In this retrospective single-center study, patients who underwent liver resection or transplantation of HCC were evaluated. Data obtained in patients who underwent liver resection were used as the training set. Nine kinds of MR findings for predicting MVI were compared between HCCs with and without MVI by univariate analysis, followed by multiple logistic regression analysis. Using significant findings, a predictive formula for diagnosing MVI was obtained. The diagnostic performance of the formula was investigated in patients who underwent liver resection (validation set 1) and in patients who underwent liver transplantation (validation set 2) using a receiver operating characteristic curve analysis. The area under the curves (AUCs) of these three groups were compared.
A total of 345 patients with 356 HCCs were selected for analysis. Tumor diameter (D) (P = 0.021), tumor washout (TW) (P < 0.01), and peritumoral hypointensity in the hepatobiliary phase (PHH) (P < 0.01) were significantly associated with MVI after multivariate analysis. The AUCs for predicting MVI of the predictive formula were as follows: training set, 0.88 (95% confidence interval (CI) 0.82,0.93); validation set 1, 0.81 (95% CI 0.73,0.87); validation set 2, 0.67 (95% CI 0.51,0.80). The AUCs were not significantly different among three groups (training set vs validation set 1; P = 0.15, training set vs validation set 2; P = 0.09, validation set 1 vs validation set 2; P = 0.29, respectively).
Our multiparametric assessment of gadoxetic acid-enhanced MRI performed quite precisely and with good reproducibility for predicting MVI.

BACKGROUND: Chronic liver disease (CLD) will affect the enhancement of hepatic parenchyma and portal vein on abdominal-enhanced MRI.
OBJECTIVE: To investigate the difference in liver parenchyma and portal vein enhancement in patients with CLD of different liver function grades between Gd- EOB-DTPA and Gd-DPTA in the portal venous phase (PVP).
METHODS: This retrospective study included 218 patients with CLD who had undergone abdominal enhanced MRI from January 2019 to June 2020. Patients with various degrees of liver dysfunction were identified with Child-Turcotte-Pugh and albumin-bilirubin grade. Two readers measured the precontrast and PVP signal intensities of liver parenchyma, portal vein, spleen, and psoas muscle. Relative liver enhancement, liver-to-spleen contrast index, portal vein image contrast, and portal vein-to-liver contrast were calculated.
RESULTS: The relative enhancement of liver parenchyma was significantly lower for the Gd-EOB-DTPA group in any degree of liver function than the Gd- DTPA group in the PVP. The Gd-EOB-DTPA group showed significantly lower portal vein-to-liver contrast in the overall study population, CTP class B, and ALBI grade 2 patients compared to the group of Gd-DTPA at PVP. No significant difference was noted in the portal vein image contrast between the two contrast agents, regardless of CTP and ALBI grading.
CONCLUSIONS: In CLD patients, Gd-EOB-DTPA yielded lower liver parenchymal enhancement and similar portal vein image contrast compared to Gd-DTPA in the PVP. Portal vein-to-liver contrast in the Gd-EOB-DTPA group was lower in the CTP class B and ALBI grade 2 subgroups compared to the Gd- DTPA group.

This study aimed to compare the detection of neuroendocrine tumor liver metastases (NLMs) in hepatobiliary-specific contrast-enhanced MRI (pMR) versus 68Ga-DOTATATE PET/CT (DT-PET). This retrospective study cohort included 30 patients with well-differentiated neuroendocrine tumors who underwent both DT-PET and pMR. Two readers independently assessed NLMs count, SUVmax on DT-PET, and signal characteristics on pMR. A consensus review by two additional readers resolved discrepancies between the modalities. Results showed concordance between DT-PET and pMR NLM count in 14/30 patients (47%). pMR identified more NLMs in 12/30 patients (40%), of which 4 patients showed multiple deposits on pMR but only 0-1 lesions on DT-PET. DT-PET detected more in 4/30 patients (13%). Overall, pMR detected more metastases than DT-PET (p = 0.01). Excluding the four outliers, there was excellent agreement between the two methods (ICC: 0.945, 95%CI: 0.930, 0.958). Notably, pMR had a higher NLM detection rate than DT-PET, with correlations found between lesion size on pMR and DT-PET detectability, as well as diffusion restriction on pMR and SUVmax on DT-PET. In conclusion, in consecutive patients with well-differentiated NETs, the detection rate of NLM is higher with pMR than with DT-PET. However, when excluding patients whose tumors do not overexpress somatostatin receptors (13% of the cohort), high concordance in the detection of NLM is observed between DT PET and pMR.

OBJECTIVE: The study aims at assessing the quantitative features which distinguish focal liver lesions (FLLs) in gadoxetic acid (GA) enhanced liver MRI and at determining whether these features can accurately differentiate benign from malignant lesions.
METHODS: 107 patients with 180 unequivocal FLLs in previous examinations were included in a single-center retrospective study. All patients underwent a MRI test of the liver with GA. 99 benign and 74 malignant lesions were included. The group of benign lesions consisted of 60 focal nodular hyperplasias (FNH), 22 hemangiomas (HMG), 6 hepatic adenomas (HA), and 11 other benign lesions (1 angiomyolipioma, 6 lesions histopathology diagnoses as benign without further specification, or ones lacking features of malignancy, and 4 lesions radiologically diagnosed as benign which remained stable in the follow-up studies). The group of malignant lesions consisted of primary 51 hepatocellular carcinomas, 12 metastases, and 11 metastases from melanoma malignum (MM meta). 7 FLLs were excluded (4 cases of uncertain histopathological diagnosis, 2 cholangiocarcinomas, and 1 regenerative nodule). For the included lesions ROI (region of interest) measurements were taken by two observers in the T2-w, ADC (apparent diffusion coefficient) and in the T1-w sequence in the hepatobiliary phase (HBP). The interobserver agreement was evaluated with the Wilcoxon test. The Kruskal - Wallis, Mann - Whitney U and post hoc Dunn\'s tests were applied to assess if there were any significant differences in the ROI values between individual lesions. The variables with the p values of < 0.05 were considered statistically significant.
RESULTS: We found significant differences in the ROI values between lesions with p < 0.0001. Strikingly high ROI values in the T2-w sequence were found for HMG. The lowest ADC values were encountered for metastases and MM metastases. The highest ROI values in the HBP were found for FNH, and the lowest for metastases. We also found statistically significant differences in the ROI values between benign and malignant lesions with benign lesions presenting statistically higher ROI values compared to malignant lesions.
CONCLUSIONS: There were significant differences in the ROI values among different types of FLLs. The predominant quantitative feature in the T2-w sequence was a strikingly high ROI value for HMG. Benign lesions presented statistically higher ROI values in the T2-w, ADC, and HBP sequences compared to malignant lesions. This was true for all lesions except for HA.

Despite improvements in operative techniques and perioperative care, post-hepatectomy liver failure (PHLF) remains the most serious cause of morbidity and mortality after surgery, and several risk factors have been identified to predict PHLF. Although volumetric assessment using imaging contributes to surgical simulation by estimating the function of future liver remnants in predicting PHLF, liver function is assumed to be homogeneous throughout the liver. The combination of volumetric and functional analyses may be more useful for an accurate evaluation of liver function and prediction of PHLF than only volumetric analysis. Gadoxetic acid is a hepatocyte-specific magnetic resonance (MR) contrast agent that is taken up by hepatocytes via the OATP1 transporter after intravenous administration. Gadoxetic acid-enhanced MR imaging (MRI) offers information regarding both global and regional functions, leading to a more precise evaluation even in cases with heterogeneous liver function. Various indices, including signal intensity-based methods and MR relaxometry, have been proposed for the estimation of liver function and prediction of PHLF using gadoxetic acid-enhanced MRI. Recent developments in MR techniques, including high-resolution hepatobiliary phase images using deep learning image reconstruction and whole-liver T1 map acquisition, have enabled a more detailed and accurate estimation of liver function in gadoxetic acid-enhanced MRI.