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Background: Gadobenate and gadoxetate demonstrate different degrees of intracellular accumulation within hepatocytes, potentially impacting these agents' relative performance for hepatocellular carcinoma (HCC) diagnosis. Objective: To perform an intraindividual comparison of gadobenate-enhanced MRI and gadoxetate-enhanced MRI for detection of HCC, and to assess the impact of inclusion of hepatobiliary phase images on HCC detection for both agents. Methods: This prospective study enrolled 126 patients (112 men, 14 women; mean age 52.3 years) at high risk for HCC who consented to undergo two 3-T liver MRI examinations [one using gadobenate (0.05 mmol/kg), one using gadoxetate (0.025 mmol/kg)], separated by 7-14 days. The order of the two contrast agents was randomized. All examinations included post-contrast dynamic and hepatobiliary phase images (120 minutes for gadobenate; 20 minutes for gadoxetate). Three radiologists independently reviewed the gadobenate and gadoxetate examinations in separate sessions and recorded the location of detected observations. Observations were classified using LI-RADS version 2018 and using a LI-RADS modification whereby hepatobiliary phase hypointensity may upgrade observations from LR-4 to LR-5. Observations classified as LR-5 were considered positive interpretations for HCC. Diagnostic performance for histologically confirmed HCC (n=96) was assessed. Results: Across readers, sensitivity for HCC using dynamic images alone was 74.0%-80.2% for gadobenate versus 54.2%-67.7% for gadoexetate and using dynamic and hepatobiliary phase images was 82.1%-87.4% for gadobenate versus 66.3%-81.1% for gadoxetate. For HCCs measuring 1.0-2.0 cm, sensitivity using dynamic images alone was 61.9% (all readers) for gadobenate versus 38.1%-57.1% for gadoxetate and using dynamic and hepatobiliary phase images was 76.2%-85.7% for gadobenate versus 52.4%-61.9% for gadoxetate. PPV for HCC ranged from 88.6%-97.4% across readers, agents, and image sets. Conclusion: Sensitivity for HCC was higher for gadobenate than for gadoxetate, whether using dynamic images alone or dynamic and hepatobiliary phase images; the improved sensitivity using gadobenate was more pronounced for small HCCs. While hepatobiliary phase images improved sensitivity for both agents, sensitivity of gadobenate using dynamic images alone compared favorably with that of gadoxetate using dynamic and hepatobiliary phase images. Clinical Impact: The findings support gadobenate as a preferred agent over gadoxetate when performing liver MRI in patients at high risk for HCC.

Tumor-infiltrating CD8 cells and expression of programmed cell death ligand 1 (PD-L1) are immune checkpoint markers in patients with hepatocellular carcinoma (HCC). We aimed to determine the ability of preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI) findings to predict CD8 cell density and PD-L1 expression in HCC. A total of 120 patients with HCC who underwent 3.0-T gadoxetic acid-enhanced MRI before curative resection from January 2016 to June 2020 were enrolled and divided into a training set (n = 84) and a testing set (n = 36). Thirty-four patients with advanced stage HCC who received anti-PD-1 inhibitor between January 2017 and April 2020 and underwent pretreated gadoxetic acid-enhanced MRI scans were enrolled in an independent validation set. PD-L1 expression and CD8 cell infiltration were assessed with immunohistochemical staining, respectively. Two radiologists blinded to pathology results evaluated the pretreated MR features in consensus. Logistic regression and the receiver operating characteristic curve (ROC) analyses were used to determine the value of image features to predict high CD8 cell density, PD-L1 positivity and the combination of high CD8 cell density and PD-L1 positivity in HCC in the training set and validated the findings in the testing set. The associations of MRI predictors with the objective response to immunotherapy were assessed in the independent validation. In the training set, the independent MRI predictors were irregular tumor margin (ITM, P = 0.008) and peritumoral low signal intensity (PLSI) on hepatobiliary phase (HBP) images (P

To evaluate the value of gadobenate dimeglumine–enhanced MRI in predicting the pathologic grade of hepatocellular carcinoma (HCC). Patients with pathologically proven HCC who underwent preoperative gadobenate dimeglumine–enhanced dynamic MRI were included. Two radiologists blinded to pathology results evaluated images in consensus. Lesions were evaluated quantitatively in terms of ratio of enhancement (RE), and qualitatively based on image features related to tumor aggressiveness. Logistic regression and ROC analyses were used to determine the value of these parameters to predict pathologic grade. In total, 221 patients (194 males, 27 females, aged 52.9 ± 11.7 years) with 49 poorly differentiated HCCs and 172 well/moderately differentiated HCCs were evaluated. Features significantly related to poorer pathologic grade at univariate analysis included lower RE in the early arterial phase (EAP) (p = 0.001), nonsmooth margins (p = 0.001), absence of capsule (p < 0.001), arterial peritumoral hyperenhancement (p < 0.001), higher AFP (p = 0.004), multiple tumors (p = 0.026), and larger tumor size (p = 0.028). At multivariate analysis, lower RE (EAP) (OR = 0.144, p = 0.002), absence of capsule (OR = 0.281, p = 0.004), and arterial peritumoral hyperenhancement (OR = 4.117, p < 0.001) were independent predictive factors for poorer pathologic grade. ROC analysis showed lower RE (EAP) was predictive of poorer pathologic grade (AUC = 0.667). AUC increased to 0.797 when combined with absence of capsule and presence of peritumoral hyperenhancement. Lower RE (EAP), absence of capsule, and arterial peritumoral hyperenhancement were predictive biomarkers for poorer pathologic grade of HCC on gadobenate dimeglumine–enhanced dynamic MRI. • Gadobenate dimeglumine–enhanced dynamic MRI was a useful quantitative biomarker for preoperative prediction of pathologic grade in patients with HCC. • Lower RE in the early arterial phase, absence of capsule, and arterial peritumoral hyperenhancement were potential imaging indicators for preoperative prediction of poorer pathologic grade of HCC on gadobenate dimeglumine–enhanced MRI. • A lower RE in the early arterial phase was effective at predicting poorer pathologic grade of HCCs but prediction is improved when combined with absence of capsule and presence of peritumoral hyperenhancement.

Intrahepatic splenosis is quite rare and is often misdiagnosed as other lesions. We present two cases of intrahepatic splenosis examined with hepatobiliary contrast agents, intravoxel incoherent motion diffusion-weighted imaging and magnetic resonance elastography. We discuss various imaging modalities and the roles of various magnetic resonance imaging methods in diagnosis. We also discuss the differentiating features that allow the correct diagnosis to be made and provide a brief review of the literature.

To evaluate whether the LI-RADS v2018 LR-5 criteria can be modified to increase sensitivity without reducing specificity for diagnosing small (10–19 mm) HCC. 167 consecutive high-risk patients with 174 small observations reported clinically on extracellular contrast-enhanced MRI from 2014 to 2018 were retrospectively studied. The best available reference standard was applied for each observation. Blinded to the reference standard, two radiologists scored LI-RADS imaging features retrospectively and assigned each observation a LI-RADS category using LI-RADS v2018 and each of four modified LI-RADS versions (mLI-RADS I to IV) with successively more expansive LR-5 criteria. Per-observation sensitivity and specificity of LR-5 for small HCC using each version were assessed. Each modified version was compared to v2018 (McNemar test). The 174 observations included 135 HCC, 8 non-HCC malignancies, and 31 benign entities. Using LI-RADS v2018, LR-5 provided 70% (both readers) sensitivity and 95% (both readers) specificity for small HCC. Expanding the LR-5 criteria to include nonrim APHE plus at least one additional major feature (mLI-RADS I) or no APHE plus at least two additional major features (mLI-RADS II) significantly increased sensitivity (reader 1/reader 2: 75%/75% vs. 70%, p = 0.016/0.031; 78%/79% vs. 70%, p = 0.001/0.001) without significantly reducing specificity (reader 1/reader 2: 90%/92% vs. 95%, p = 0.500/1.000 for both). mLI-RADS III and IV further increased sensitivity (reader 1/reader 2: 80%/81% vs. 70%, p

To evaluate whether a three-phase dynamic contrast-enhanced CT protocol, when combined with a deep learning model, has similar accuracy in differentiating hepatocellular carcinoma (HCC) from other focal liver lesions (FLLs) compared with a four-phase protocol. Three hundred and forty-two patients (mean age 49.1 ± 10.5 years, range 19–86 years, 65.8% male) scanned with a four-phase CT protocol (precontrast, arterial, portal-venous and delayed phases) were retrospectively enrolled. A total of 449 FLLs were categorized into HCC and non-HCC groups based on the best available reference standard. Three convolutional dense networks (CDNs) with the input of four-phase CT images (model A), three-phase images without portal-venous phase (model B) and three-phase images without precontrast phase (model C) were trained on 80% of lesions and evaluated in the other 20% by receiver operating characteristics (ROC) and confusion matrix analysis. The DeLong test was performed to compare the areas under the ROC curves (AUCs) of A with B, B with C, and A with C. The diagnostic accuracy in differentiating HCC from other FLLs on test sets was 83.3% for model A, 81.1% for model B and 85.6% for model C, and the AUCs were 0.925, 0.862 and 0.920, respectively. The AUCs of models A and C did not differ significantly (p = 0.765), but the AUCs of models A and B (p = 0.038) and of models B and C (p = 0.028) did. When combined with a CDN, a three-phase CT protocol without precontrast showed similar diagnostic accuracy as a four-phase protocol in differentiating HCC from other FLLs, suggesting that the multiphase CT protocol for HCC diagnosis might be optimized by removing the precontrast phase to reduce radiation dose.

OBJECTIVE. We investigated in Liver Imaging Reporting and Data System category 5 (LR-5) observations whether imaging features, including LI-RADS imaging features, could predict microvascular invasion (MVI) and posthepatectomy recurrence in high-risk adult patients with hepatocellular carcinoma (HCC). MATERIALS AND METHODS. We retrospectively identified 149 high-risk patients who underwent 3-T MRI within 1 month before hepatectomy for HCC; 81 of 149 patients with no HCC recurrence were followed for more than 1 year. Tumors with clear surgical margins were confirmed in each hepatectomy specimen. MVI was evaluated histologically by a histopathologist. Tumor recurrence was determined by clinical and imaging follow-up. Two independent radiologists reviewed the prehepatectomy MR images and assessed LI-RADS v2018 imaging features as well as some non-LI-RADS features in all LR-5 observations in consensus. Alpha-fetoprotein level, tumor number, and imaging features were analyzed as potential predictors for MVI and posthepatectomy recurrence using multivariate logistic regression and Cox proportional hazards models. RESULTS. One hundred forty-nine patients with pathologically confirmed HCC were included; 64 of 149 (43.0%) patients had MVI, whereas 48 of 129 (37.2%) patients had tumor recurrence within 3 years after hepatectomy. Mosaic architecture (odds ratio, 3.420; p < 0.001) and nonsmooth tumor margin (odds ratio, 2.554; p = 0.011) were independent predictors of MVI. Multifocal tumors (hazard ratio, 2.101; p = 0.034), absence of fat in mass (hazard ratio, 2.109; p = 0.015), and nonsmooth tumor margin (hazard ratio, 2.415; p = 0.005) were independent predictors of posthepatectomy recurrence. CONCLUSION. In high-risk patients with LR-5 HCC, mosaic architecture and non-smooth tumor margin independently predicted MVI. Multifocal tumors, absence of fat in mass, and nonsmooth tumor margin independently predicted recurrence.

Hepatic metastases were reported in up to 70% of colorectal cancer patients, among which multifocal hepatic metastasis represents one of the complications that lead to poor prognosis. The majority of the patients carrying multifocal hepatic metastases required pharmaceutical treatments to reduce the tumor size prior to surgical resection. However, the clinical responses to pharmaceutical agents were difficult to predict due to the heterogeneous nature of the multifocal tumors. Here, we report a case with multifocal hepatic metastases from colorectal cancer that was resistant to the primary chemotherapy and Bevacizumab plus chemotherapy, but responded to the combined therapy of Cetuximab and FOLFOX. Genetic tests had revealed that the tumor was highly metastatic due to the mutations of the WNT signaling pathway, and the metastatic tumors might be sensitive to Cetuximab. Consistent with the molecular characterizations, the metastatic tumors continue to emerge after chemotherapy, and rapidly relapsed in great numbers after liver resection. However, the combined therapy of Cetuximab and FOLFOX guided by the genetic tests significantly reduced the size and number of metastatic tumors. To conclude, deciphering the mutation profiles of multifocal metastatic tumors may guide the determination of treatment tactics, which may benefit the patients with non-resectable advanced carcinoma.

This paper focuses on the impact of changes in planting industry structure on carbon emissions. Based on the statistical data of the planting industry in three provinces in Northeast China from 1999 to 2018, the study calculated the carbon emissions, carbon absorptions and net carbon sinks of the planting industry by using crop parameter estimation and carbon emissions inventory estimation methods. In addition, the multiple linear regression model and panel data model were used to analyze and test the carbon emissions and net carbon sinks of the planting industry. The results show that: (1). The increase of the planting area of rice, corn, and peanuts in the three northeastern provinces of China will promote carbon emissions, while the increase of the planting area of wheat, sorghum, soybeans, and vegetables will reduce carbon emissions, (2). Fertilizer application, technological progress, and planting structure factors have a significant positive effect on net carbon sinks, among which the changes in the planting industry structure have the greatest impact on net carbon sinks. Based on the comprehensive analysis, it is suggested that, under the guidance of the government, resource endowment and location advantages should be given full play to, and the internal planting structure of crops should be reasonably adjusted so as to promote the development of low-carbon agriculture and accelerate the development process of agricultural modernization.

Background: Preoperative evaluation of the T stage and prognosis of colorectal cancer (CRC) is vital for patients' management. Some of the known limitations of conventional computed tomography (CT) in the diagnosis of CRC needs to be resolved. Therefore, a deep learning system was developed by using patients' preoperative CT images to classify T stage and predict prognosis of CRC. Methods: Resnet50 (R), Inception-V3 (I), and Efficientnet-B5 (E) were adopted as the base model, and the three base model accepted CT images as multi-model image inputs and the output probabilities of the three networks were averaged to form an colorectal cancer ensemble model (CRCEM). This deep learning system was developed based on preoperative CT images of 654 patients (training cohort, n=393; validation cohort, n=131; test cohort, n=130). The performance of classifying T stage was assessed by our model, such as CRCEM (T1-2, T3, T4), CRCEM (T1-2, T3-4), and CRCEM (T1-3, T4). Then an observed study was conducted to evaluate our scheme performance in classifying T stage with two experienced radiologists. Furthermore, the output images of T stage were used as input and determined whether the tumor in the input CT images had a good or poor prognosis by using selected 284 patients (training cohort, n=228; test cohort, n=56), and this model was named as CRCEM (prognosis). Findings: Area under the curve (AUC) of classifying T stage in CRCEM (T1-2, T3, T4), CECEM (T1-2, T3-4), and CRCEM (T1-3, T4) was 0.859, 0.925, and 0.958, respectively. The AUC of classifying T1-2 vs. T3-4 was 0.749 and 0.763 in radiologist 1 and radiologist 2, respectively, and the AUC of classifying T1-3 vs. T4 was 0.774 and 0.765 in radiologist 1 and radiologist 2, respectively. Kappa value for inter-radiologist agreement was 0.792, (P

To determine the value of lesion hypointensity in the hepatobiliary phase (HBP) on gadobenate dimeglumine–enhanced MRI as an additional major imaging feature for diagnosis of hepatocellular carcinoma (HCC) using LI-RADS v2018 criteria. Between March 2016 and August 2018, 235 patients with 250 hepatic nodules at high risk of HCC underwent gadobenate dimeglumine–enhanced MRI. Two radiologists independently evaluated the imaging features and classified the nodules based on LI-RADS v2018 criteria, and their consensus data were used to calculate the diagnostic performance of LI-RADS categories. Two modified LI-RADS definitions were as follows: (1) LI-RADS-m1: HBP hypointensity as an additional major feature; (2) LI-RADS-m2: HBP hypointensity as an alternative to “enhancing capsule” as an additional major feature. The diagnostic performance of LR-5 categories was compared using McNemar’s test. The sensitivity and specificity for LR-5 classification using original LI-RADS v2018 criteria were 78.1% and 96.3%, respectively. Significantly improved sensitivity (82.7%; p = 0.004) with unchanged specificity (96.3%; p = 1.00) was seen for LR-5 classification using LI-RADS-m1. Similar sensitivity and specificity (82.7% and 96.3%, respectively) were also seen using LI-RADS-m2. Significantly improved sensitivity (79.5% vs. 64.0%; p = 0.031) with unchanged specificity (96.2% vs. 96.2%, p = 1.00) was seen using both LI-RADS-m1 and LI-RADS-m2 compared to the original LI-RADS v2018 for 39 HCC nodules measuring 10–19 mm. Lesion hypointensity on gadobenate dimeglumine–enhanced HBP MRI may improve sensitivity for LR-5 classification beyond that achievable using conventional LI-RADS v2018 criteria. Lesion hypointensity may prove a suitable alternative imaging feature to enhancing capsule for accurate LR-5 classification. • Including lesion hypointensity in the HBP as an additional major feature improved sensitivity for LR-5 classification on gadobenate dimeglumine–enhanced MRI. • Lesion hypointensity in the HBP can replace “enhancing capsule” as an additional major feature for LR-5 classification without impairing specificity.

Objectives: The chest CT findings that can distinguish patients with corona virus disease 2019 (COVID-19) from those with clinically suspected COVID-19 but subsequently found to be COVID-19 negative have not previously been described in detail. The purpose of this study was to determine the distinctions among patients with COVID-19 by comparing the imaging findings of patients with suspected confirmed COVID-19 and those of patients initially suspected to have COVID-19 who were ultimately negative for the disease. Methods: 28 isolated suspected in-patients with COVID-19 were enrolled in this retrospective study from January 22, 2020 to February 6, 2020. 12 patients were confirmed to have positive severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) RNA results, and 16 patients had negative results. The thin-section CT imaging findings and clinical and laboratory data of all the patients were evaluated. Results: There were no significant differences between the 12 confirmed COVID-19 (SARS-Cov-2-positive) patients and 16 SARS-CoV-2-negative patients in epidemiology and most of the clinical features or laboratory data. The CT images showed that the incidence of pure/mixed ground-glass opacities (GGOs) was not different between COVID-19 and SARS-CoV-2-negative patients [9/12 (75.0%) vs 10/16 (62.5%), p = 0.687], but pure/mixed GGOs in the peripheral were more common in patients with COVID-19 [11/12 (91.7%) vs 6/16 (37.5%), p = 0.006]. There were no significant differences in the number of lesions, bilateral lung involvement, large irregular/patchy opacities, rounded opacities, linear opacities, crazy-paving patterns, halo signs, interlobular septal thickening or air bronchograms. Conclusions: Although peripheral pure/mixed GGOs on CT may help distinguish patients with COVID-19 from clinically suspected but negative patients, CT cannot replace RT-PCR testing. Advances in knowledge: Peripheral pure/mixed GGOs on-chest CT findings can be helpful in distinguishing patients with COVID-19 from those with clinically suspected COVID-19 but subsequently found to be COVID-19 negative.

Background The accurate classification of focal liver lesions (FLLs) is essential to properly guide treatment options and predict prognosis. Dynamic contrast-enhanced computed tomography (DCE-CT) is still the cornerstone in the exact classification of FLLs due to its noninvasive nature, high scanning speed, and high-density resolution. Since their recent development, convolutional neural network-based deep learning techniques has been recognized to have high potential for image recognition tasks. Aim To develop and evaluate an automated multiphase convolutional dense network (MP-CDN) to classify FLLs on multiphase CT. Methods A total of 517 FLLs scanned on a 320-detector CT scanner using a four-phase DCE-CT imaging protocol (including precontrast phase, arterial phase, portal venous phase, and delayed phase) from 2012 to 2017 were retrospectively enrolled. FLLs were classified into four categories: Category A, hepatocellular carcinoma (HCC); category B, liver metastases; category C, benign non-inflammatory FLLs including hemangiomas, focal nodular hyperplasias and adenomas; and category D, hepatic abscesses. Each category was split into a training set and test set in an approximate 8:2 ratio. An MP-CDN classifier with a sequential input of the four-phase CT images was developed to automatically classify FLLs. The classification performance of the model was evaluated on the test set; the accuracy and specificity were calculated from the confusion matrix, and the area under the receiver operating characteristic curve (AUC) was calculated from the SoftMax probability outputted from the last layer of the MP-CDN. Results A total of 410 FLLs were used for training and 107 FLLs were used for testing. The mean classification accuracy of the test set was 81.3% (87/107). The accuracy/specificity of distinguishing each category from the others were 0.916/0.964, 0.925/0.905, 0.860/0.918, and 0.925/0.963 for HCC, metastases, benign non-inflammatory FLLs, and abscesses on the test set, respectively. The AUC (95% confidence interval) for differentiating each category from the others was 0.92 (0.837-0.992), 0.99 (0.967-1.00), 0.88 (0.795-0.955) and 0.96 (0.914-0.996) for HCC, metastases, benign non-inflammatory FLLs, and abscesses on the test set, respectively. Conclusion MP-CDN accurately classified FLLs detected on four-phase CT as HCC, metastases, benign non-inflammatory FLLs and hepatic abscesses and may assist radiologists in identifying the different types of FLLs.

Long non-coding RNAs (lncRNAs) are emerging as important regulators in the modulation of muscle development and muscle-related diseases. To explore potential regulators of muscle differentiation, we determined the expression profiles of lncRNAs and mRNAs in C2C12 mouse myoblast cell line using microarray analysis. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed to explore their function. We also constructed co-expression, cis/trans-regulation, and competing endogenous RNA (ceRNA) networks with bioinformatics methods. We found that 3067 lncRNAs and 3235 mRNAs were differentially regulated (fold change ≥2.0). Bioinformatics analysis indicated that the principal functions of the transcripts were related to muscle structure development and morphogenesis. Co-expression analysis showed 261 co-expression relationships between 233 lncRNAs and 10 mRNAs, and nine lncRNAs interacted with myog and MEF2C collectively. Cis/trans-regulation prediction revealed that lncRNA Myh6 could be a valuable gene via cis-regulation, and lncRNAs such as 2310043L19Ris, V00821, and AK139352 may participate in particular pathways regulated by transcription factors, including myog, myod1, and foxo1. The myog-specific ceRNA network covered 10 lncRNAs, 378 miRNAs, and 1960 edges. The upregulated lncRNAs Filip1, Myl1, and 2310043L19Rik may promote myog expression by acting as ceRNAs. Our results offer a new perspective on the modulation of lncRNAs in muscle differentiation.

The purposes of this study were to construct immortalized human bone marrow mesenchymal stem cells (UE7T-13) with overexpression of the hepatocyte nuclear factor4α (hHNF4α) and luciferase2-mKate2 dual-fusion reporter gene, further investigate their impact on treating acute liver injury (ALI) in rats, and track their biodistribution and survival by bioluminescence imaging (BLI). The hHNF4α and luciferase2-mKate2 genes were transduced by a lentiviral vector into UE7T-13 cells (named E7-hHNF4α-R cells), and expression was verified by immunofluorescence, RT-PCR, and flow cytometry. E7-hGFP-R cells expressing the luciferase2-mKate2/hGFP gene served as a negative group. A correlation between the bioluminescence signal and cell number was detected by BLI. The ALI rats were established and divided into three groups: PBS, E7-hGFP-R, and E7-hHNF4α-R. After transplantation of 2.0 × 106 cells, BLI was used to dynamically track their biodistribution and survival. The restoration of biological functions was assessed by serum biochemical and histological analyses. Stable high-level expression of hHNF4α and mKate2 protein was established in the E7-hHNF4α-R cells in vitro. The E7-hHNF4α-R cells strongly expressed hGFP, hHNF4α, and mKate2 proteins, and the hHNF4α gene. hGFP-mKate2 dual-positive cell expression reached approximately 93 %. BLI verified that a linear relationship existed between the cell number and bioluminescence signal (R2 = 0.9991). The cells improved liver function in vivo after transplantation into the ALI rat liver, as evidenced by the fact that AST and ALT temporarily returned to normal levels in the recipient ALI rats. The presence of the transplanted E7-hGFP-R and E7-hHNF4α-R cells in recipient rat livers was confirmed by BLI and immunohistochemistry. However, the cells were cleared by the immune system a short time after transplantation into ALI rats with a normal immune system. Our data revealed that the E7-hHNF4α-R cells can transiently improve damaged liver function and were rapidly cleared by the immune system. In addition, BLI is a useful tool to track transplanted cell biodistribution and survival.

Background There are few studies about the Liver Imaging Reporting and Data System (LI-RADS), which was developed with the purpose of standardizing the interpretation and reporting of liver imaging examinations in patients at risk for hepatocellular carcinoma (HCC). Purpose To evaluate the diagnostic accuracy of HCC diagnosis using LI-RADS. Material and Methods The computed tomography (CT), magnetic resonance imaging (MRI), and clinical data of 297 lesions in 249 patients between June 2012 and August 2013 were retrospectively analyzed. Using LI-RADS 2014, two radiologists evaluated the lesions and a LI-RADS category was retrospectively assigned to each nodule. Results The final diagnoses of 297 nodules in 249 patients consisted of 191 malignant and 106 benign lesions. Out of 44 LI-RADS category 1 lesions, none were HCCs. However, 2/25 category 2 lesions, 3/35 category 3 lesions, 16/25 category 4 lesions, 151/156 category 5 lesions, and 3/12 category LRM/OM (probable malignancy, not specific for HCC/other malignancy) lesions were HCCs. The Kappa value was 0.44 (95% confidence interval [CI] = 0.39–0.49) between two observers during LI-RADS grading. Conclusion The negative predictive value of LI-RADS category 1 was 100%. In addition, a relevant proportion of lesions categorized as category 2 or 3, or even as other malignancies, were HCCs. LI-RADS category 5 had a high specificity for HCC. LI-RADS was not able to give a differential diagnosis for the false-positive lesions of LI-RADS category 5.

OBJECTIVE: The microcirculatory hemodynamic changes of small-for-size syndrome (SFSS) are still unclear. In this study, they were investigated by four-dimensional CT perfusion (4D-CTP) technique. METHODS: The sham group, 50, 60, 70 and 80 % partial hepatectomy (PH) rat groups were established. At 1 hour (1 h), 1 day (1 d), 3 days (3 d) and 7 days (7 d) post-operation, serological examination, 4D-CTP scan and histopathological examination were performed. One-way analysis of variance and the Kruskal–Wallis test were used for the comparison. RESULTS: Based on the diagnostic criteria of SFSS, the 80 % group was considered to be a successful model. In all the PH groups, portal vein perfusion and total liver perfusion peaked at 1 h and declined at 1d and 3d. Both portal vein perfusion and total liver perfusion were significantly higher in the 80 % group than the sham group, 50 and 60% groups at 1 h (p < 0.05), and 80 % group at 3d and 7d (p < 0.05). In the 50 and 60 % groups, hepatic artery perfusion decreased at 1 h and maintained at a lower level until at 7 d; whereas, in the 70 and 80% groups, it increased at 1 h, then decreased and reached the lowest level at 7 d. No significant difference appeared in hepatic artery perfusion between any two groups at any time points. At all time points, hepatic perfusion index was lower in all the PH groups than the sham group. Significant differences in hepatic perfusion index appeared between the 80% group and the sham group at 1 h and 1 d (p < 0.05). CONCLUSIONS: The CTP parameters quantitatively revealed the microcirculatory hemodynamic changes in SFSS, which were further confirmed to be associated with histopathological injury. It is suggested that the hemodynamic changes in SFSS remnant liver can provide useful information for further revealing the mechanism of SFSS and may help for guiding the treatments. ADVANCES IN KNOWLEDGE: By using the 4D-CTP technique, the hepatic microcirculatory hemodynamic changes could be quantitatively measured in vivo for small animal research.

To evaluate the clinical application comparison of Surt-start imaging and dynamic volume scanning acquired from 320-detector row computed tomography (CT) for the diagnosis of hepatic artery complications after liver transplantation.Retrospective analysis was conducted for 20 patients undergoing 320-slice CT scanning. Aquilion One scanner after liver transplantation was performed from April 2009 to September 2011. Dynamic volume scanning group employed dynamic volume scanning pattern while Surt-start group used helical scanning pattern. The contrast medium (Ultravist, 370 mgI/ml iopromide) was infused at 6 ml/s with a total dose of 50 ml in dynamic volume scanning group versus 1.5 ml/kg in Surt-start group. Two groups were compared with regards to hepatic artery enhancing peak time, the best arterial phase time, maximum peak enhancement of artery, maximum absolute peak enhancement of artery and branches of hepatic artery.The hepatic artery enhancing peak time and the best arterial phase time was (21.5 ± 2.5) s and (22.4 ± 3.3) s in dynamic volume scanning group versus (19.5 ± 1.8) s in Surt-start group. And there was significant inter-group difference (P = 0.001, P = 0.000). The maximum peak enhancement of artery or the maximum absolute peak enhancement of artery and branches of hepatic artery had no inter-group difference. Two groups showed no difference in displaying hepatic artery anastomosis and variations. Dynamic volume scanning group was better than Surt-start group in displaying hepatic artery microscopic lesions.320-detector CT dynamic volume scanning has the advantage of low-dose contrast medium. Capable of acquiring overall accurate imaging process of hepatic artery, it is effective for follow-ups of hepatic artery complications after liver transplantation.