The Association Between Tumor Radiomic Analysis and Peritumor Habitat-Derived Radiomic Analysis on Gadoxetate Disodium-Enhanced MRI With Microvascular Invasion in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) has a poor prognosis, often characterized by microvascular invasion (MVI). Radiomics and habitat imaging offer potential for preoperative MVI assessment. PURPOSE: To identify MVI in HCC by habitat imaging, tumor radiomic analysis, and peritumor habitat-derived radiomic analysis. STUDY TYPE: Retrospective. SUBJECTS: Three hundred eighteen patients (53 ± 11.42 years old; male = 276) with pathologically confirmed HCC (training:testing = 224:94). FIELD STRENGTH/SEQUENCE: 1.5 T, T2WI (spin echo), and precontrast and dynamic T1WI using three-dimensional gradient echo sequence. ASSESSMENT: Clinical model, habitat model, single sequence radiomic models, the peritumor habitat-derived radiomic model, and the combined models were constructed for evaluating MVI. Follow-up clinical data were obtained by a review of medical records or telephone interviews. STATISTICAL TESTS: Univariable and multivariable logistic regression, receiver operating characteristic (ROC) curve, calibration, decision curve, Delong test, K-M curves, log rank test. A P-value less than 0.05 (two sides) was considered to indicate statistical significance. RESULTS: Habitat imaging revealed a positive correlation between the number of subregions and MVI probability. The Radiomic-Pre model demonstrated AUCs of 0.815 (95% CI: 0.752-0.878) and 0.708 (95% CI: 0.599-0.817) for detecting MVI in the training and testing cohorts, respectively. Similarly, the AUCs for MVI detection using Radiomic-HBP were 0.790 (95% CI: 0.724-0.855) for the training cohort and 0.712 (95% CI: 0.604-0.820) for the test cohort. Combination models exhibited improved performance, with the Radiomics + Habitat + Dilation + Habitat 2 + Clinical Model (Model 7) achieving the higher AUC than Model 1-4 and 6 (0.825 vs. 0.688, 0.726, 0.785, 0.757, 0.804, P = 0.013, 0.048, 0.035, 0.041, 0.039, respectively) in the testing cohort. High-risk patients (cutoff value >0.11) identified by this model showed shorter recurrence-free survival. DATA CONCLUSION: The combined model including tumor size, habitat imaging, radiomic analysis exhibited the best performance in predicting MVI, while also assessing prognostic risk. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Deep Learning-Based Approach for Identifying and Measuring Focal Liver Lesions on Contrast-Enhanced MRI.

BACKGROUND: The number of focal liver lesions (FLLs) detected by imaging has increased worldwide, highlighting the need to develop a robust, objective system for automatically detecting FLLs. PURPOSE: To assess the performance of the deep learning-based artificial intelligence (AI) software in identifying and measuring lesions on contrast-enhanced magnetic resonance imaging (MRI) images in patients with FLLs. STUDY TYPE: Retrospective. SUBJECTS: 395 patients with 1149 FLLs. FIELD STRENGTH/SEQUENCE: The 1.5 T and 3 T scanners, including T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging. ASSESSMENT: The diagnostic performance of AI, radiologist, and their combination was compared. Using 20 mm as the cut-off value, the lesions were divided into two groups, and then divided into four subgroups: <10, 10-20, 20-40, and ≥40 mm, to evaluate the sensitivity of radiologists and AI in the detection of lesions of different sizes. We compared the pathologic sizes of 122 surgically resected lesions with measurements obtained using AI and those made by radiologists. STATISTICAL TESTS: McNemar test, Bland-Altman analyses, Friedman test, Pearson's chi-squared test, Fisher's exact test, Dice coefficient, and intraclass correlation coefficients. A P-value <0.05 was considered statistically significant. RESULTS: The average Dice coefficient of AI in segmentation of liver lesions was 0.62. The combination of AI and radiologist outperformed the radiologist alone, with a significantly higher detection rate (0.894 vs. 0.825) and sensitivity (0.883 vs. 0.806). The AI showed significantly sensitivity than radiologists in detecting all lesions <20 mm (0.848 vs. 0.788). Both AI and radiologists achieved excellent detection performance for lesions ≥20 mm (0.867 vs. 0.881, P = 0.671). A remarkable agreement existed in the average tumor sizes among the three measurements (P = 0.174). DATA CONCLUSION: AI software based on deep learning exhibited practical value in automatically identifying and measuring liver lesions. TECHNICAL EFFICACY: Stage 2.

Diagnostic algorithm for subcentimeter hepatocellular carcinoma using alpha-fetoprotein and imaging features on gadoxetic acid-enhanced MRI.

OBJECTIVE: To investigate the role of serum alpha-fetoprotein (AFP) in diagnosing subcentimeter hepatocellular carcinoma (HCC) on gadoxetic acid-enhanced MRI (EOB-MRI). METHODS: This study retrospectively enrolled treatment-naïve patients with chronic hepatitis B who had a solitary subcentimeter observation on EOB-MRI from January 2017 to March 2023. Final diagnosis was confirmed by pathology for HCC and pathology or follow-up for benign controls. The AFP cutoff value for HCC was determined using Youden's index. Diagnostic criteria were developed according to significant findings in logistic regression analyses based on AFP and imaging features. The diagnostic performance of possible criteria was compared to the diagnostic hallmarks of HCC (arterial-phase hyperintensity and portal-phase hypointensity). RESULTS: A total of 305 patients (mean age, 51.5 ± 10.7 years; 153 men) were divided into derivation and temporal validation cohorts. Four findings, namely AFP >13.7 ng/mL, arterial-phase hyperintensity, portal-phase hypointensity, and transitional-phase hypointensity, were predictors of HCC. A new criterion (at least three of the four findings) showed higher sensitivity than the diagnostic hallmarks (derivation cohort, 71.6% vs. 52.3%, p < 0.001; validation cohort, 75.0% vs. 47.5%, p = 0.003) without decreasing specificity (derivation cohort, 92.5% vs. 92.5%, p > 0.999; validation cohort, 92.0% vs. 92.0%, p > 0.999). Another criterion (all four findings) achieved a slightly higher specificity than the diagnostic hallmark (derivation cohort, 99.1% vs. 92.5%, p = 0.023; validation cohort, 100.0% vs. 92.0%, p = 0.134). Subgroup analysis for hepatobiliary hypointense observations yielded similar results. CONCLUSION: Including AFP in the diagnostic algorithm may improve the diagnostic performance for subcentimeter HCC. CLINICAL RELEVANCE STATEMENT: Combining imaging features on gadoxetic acid-enhanced MRI with alpha-fetoprotein may enhance the diagnostic performance for subcentimeter HCC in treatment-naïve patients with chronic hepatitis B. KEY POINTS: • The traditional diagnostic hallmark of HCC (arterial-phase hyperintensity and portal-phase hypointensity) shows modest diagnostic performance for subcentimeter HCC on EOB-MRI. • Serum alpha-fetoprotein > 13.7 ng/mL, arterial-phase hyperintensity, portal-phase hypointensity, and transitional-phase hypointensity were independent predictors for subcentimeter HCC. • A criterion of at least three of the four above findings achieved a higher sensitivity without decreasing specificity.

An MRI-Based Prognostic Stratification System for Medical Decision-Making of Multinodular Hepatocellular Carcinoma Patients Beyond the Milan Criteria.

BACKGROUND: The suitability of hepatectomy among patients with multinodular hepatocellular carcinoma (MHCC) beyond the Milan criteria remains controversial. There is a need for a reliable risk stratification tool among these patients for the selection of ideal candidates of curative resection. PURPOSE: To determine the clinicoradiological prognostic factors for patients with MHCC beyond the Milan criteria to further develop a stratification system. STUDY TYPE: Retrospective. SUBJECTS: 176 patients with pathologically confirmed MHCC beyond the Milan criteria. FIELD STRENGTH/SEQUENCE: The 1.5 T scanner, including T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging. ASSESSMENT: Conventional MRI features and preoperative laboratory data including aspartate aminotransferase (AST) and α-fetoprotein (AFP) were collected and analyzed. Two nomograms incorporating clinicoradiological variables were independently constructed to predict recurrence-free survival (RFS) and overall survival (OS) with Cox regression analyses and verified with 5-fold cross validation. Based on the nomograms, two prognostic stratification systems for RFS and OS were further developed. STATISTICAL TESTS: The Cohen's kappa/intraclass correlation coefficient, C-index, calibration curve, Kaplan-Meier curve, log-rank test. A P value <0.05 was considered statistically significant. RESULTS: AST > 40 U/L, increased tumor burden score, radiological liver cirrhosis and nonsmooth tumor margin were independent predictors for poor RFS, while AST > 40 U/L, AFP > 400 ng/mL and radiological liver cirrhosis were independent predictors for poor OS. The two nomograms demonstrated good discrimination performance with C-index of 0.653 (95% confidence interval [CI], 0.602-0.794) and 0.685 (95% CI, 0.623-0.747) for RFS and OS, respectively. The 5-fold cross validation further validated the discrimination capability of the nomograms. Based on the nomogram models, MHCC patients beyond the Milan criteria were stratified into low-/medium-/high-risk groups with significantly different RFS and OS. DATA CONCLUSION: The proposed MRI-based prognostic stratification system facilitates the refinement and further subclassification of patients with MHCC beyond the Milan criteria. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: 2.

An improved diagnostic algorithm for subcentimeter hepatocellular carcinoma on gadoxetic acid-enhanced MRI.

OBJECTIVES: Accurate diagnosis of subcentimeter hepatocellular carcinoma (HCC) is a challenge also with gadoxetic acid-enhanced MRI (EOB-MRI). This study aimed to assess the diagnostic accuracy of the Liver Imaging Reporting and Data System (LI-RADS) for subcentimeter HCC and to determine whether new diagnostic criteria (washout either on portal venous phase (PVP) or transitional phase (TP)) would improve the diagnostic performance. METHODS: We evaluated 240 subcentimeter observations in 225 consecutive treatment-naïve patients at risk of HCC. Final diagnoses were 132 HCCs (all by pathology) and 108 non-HCC (41 by pathology and 67 by follow-up). Two radiologists assessed MR imaging features and assigned LI-RADS categories. A variety of diagnostic criteria were developed by combining significant MRI features based on washout on PVP or TP. Diagnostic performance was compared. RESULTS: Non-rim arterial phase hyperenhancement (non-rim APHE), washout on PVP or TP, and hepatobiliary-phase hypointensity were significant predictors for subcentimeter HCC diagnosis according to multivariable analysis. One criterion (non-rim APHE and washout on PVP or TP) yielded higher sensitivity (68.2% vs. 56.8%, p = 0.011) with comparable specificity (91.7% vs. 92.6%, p > 0.999) compared to the LR-4 category. This criterion had improved sensitivity (68.2% vs. 49.2%, p < 0.001) and slightly decreased specificity (91.7% vs. 94.4%, p = 0.250) compared to non-rim APHE with washout on PVP. CONCLUSIONS: LI-RADS exhibits modest diagnostic performance for subcentimeter HCC. Our new criterion (non-rim APHE and non-peripheral washout on PVP or TP) may increase the diagnostic sensitivity without compromised specificity compared to the LR-4 category. KEY POINTS: • The LR-4 category shows modest diagnostic performance for the diagnosis of subcentimeter HCC on EOB-MRI with a sensitivity and specificity of 56.8% and 92.6%, respectively. • Non-rim APHE, non-peripheral washout on PVP or TP, and HBP hypointensity were independent predictors for the diagnosis of subcentimeter HCC. • The combination of non-rim APHE and non-peripheral washout on PVP or TP improves the sensitivity from 56.8 to 68.2% (p = 0.011) with comparable specificity (91.7 vs. 92.6%, p > 0.999).

Combined hepatocellular carcinoma-cholangiocarcinoma with a predominant HCC component: better survival and MRI-based prediction.

OBJECTIVES: To determine the optimal cutoff value of HCC% for predicting the outcome of patients with combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) and to investigate how preoperative MR features based on the Liver Imaging Reporting and Data System (LI-RADS ver. 2018) are related to the HCC% in cHCC-CCA. METHODS: The study enrolled 107 patients pathologically confirmed to have single cHCC-CCA according to the 2019 WHO classification. A receiver operating characteristic (ROC) curve was used to find the optimal cutoff value of HCC% based on overall survival (OS). The preoperative MR imaging features and clinicopathological findings were retrospectively evaluated and compared between the high HCC% and low HCC% groups. RESULTS: In total, 107 patients (mean age, males vs. females: 56.6 ± 10.7 years vs. 54.2 ± 12.8 years) were evaluated. Analysis of the relationship between HCC% and OS by ROC curve suggested that the optimal cutoff value was 65%, by which 51 (47.7%) patients were assigned to the high HCC% group. LI-RADS categorization (OR = 3.657, p = 0.006 vs. OR = 4.075, p = 0.004) and serum carcinoembryonic antigen (CEA) >5 ng/mL (OR = 0.348, p = 0.089 vs. OR = 0.298, p = 0.040) were significant predictors for HCC% in cHCC-CCA in both univariate and multivariate analysis. CONCLUSIONS: cHCC-CCA patients with HCC components higher than 65% tend to exhibit better overall survival, and MRI-based LI-RADS categorization and serum CEA level are valuable for identifying HCC% in cHCC-CCA preoperatively. KEY POINTS: • cHCC-CCA patients with HCC components higher than 65% tend to exhibit better overall survival. • MRI-based LI-RADS categorization and serum CEA level were significant predictors for HCC% in cHCC-CCA in both univariate and multivariate analyses and valuable for identifying HCC% in cHCC-CCA preoperatively.

Prognostic factors for long-term outcome in bifocal hepatocellular carcinoma after resection.

OBJECTIVES: This study aimed to evaluate whether the radiological similarity and clinicopathological factors determine the prognosis in bifocal hepatocellular carcinoma (bHCC) stratified by the Milan criteria. METHODS: Consecutive patients with pathologically confirmed bHCC examined between January 2016 and December 2018 were retrospectively enrolled and grouped based on the Milan criteria. Two radiologists independently evaluated whether the imaging features of both tumors were consistent or not, which was defined as the radiological similarity. The clinicopathological data were also collected. The multivariable Cox regression was applied to separately identify the independent factors for recurrence-free survival (RFS) and overall survival (OS) in bHCC within and beyond the Milan criteria. RESULTS: A total of 193 patients were evaluated and divided into the within the Milan criteria group (n = 72) and the beyond the Milan criteria group (n = 121). bHCC within the Milan criteria showed a significantly better prognosis than those beyond the criteria. In the within the Milan criteria group, HBV-DNA load >104 IU/mL, microvascular invasion (MVI), and different enhancement patterns were independently associated with poor RFS. MVI was an independent prognostic factor for poor OS. In the beyond the Milan criteria group, HBV infection, MVI, increased ratio of the larger to the smaller tumor diameter (RLSD) value, and low comprehensive similarity were associated with shorter RFS, whereas MVI and increased RLSD value were independent predictors for poor OS. CONCLUSIONS: Our study revealed that in addition to MVI- and HBV-related factors, similarity in imaging features between lesions of bHCC is associated with the long-term prognosis. KEY POINTS: • The prognosis of bifocal HCC patients within the Milan criteria is significantly better than those beyond the criteria. • The similarity in imaging features between lesions of bHCC was an independent prognostic factor. • The more similar the bifocal lesions are in imaging features, the better the prognosis is.

How to differentiate between combined hepatocellular carcinoma-cholangiocarcinoma and intrahepatic cholangiocarcinoma with rim arterial phase hyperenhancement?

PURPOSE: To analyze and compare the differences in MRI features between combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) and intrahepatic cholangiocarcinoma (iCCA) with arterial phase peripheral enhancement, so as to provide valuable references for preoperative differential diagnosis. METHODS: Seventy cHCC-CCA patients and 74 iCCA patients confirmed by pathology were included in this study. Their contrast-enhanced MRI showed rim arterial phase hyperenhancement (Rim APHE). The differences of clinicopathological data and MRI features between cHCC-CCA and iCCA were compared. Then, the sensitivity, specificity, and area under curve (AUC) were also analyzed and compared. RESULTS: Seventy cHCC-CCA patients (mean age, 55.7 ± 10.6 years) and 74 iCCA patients (mean age, 61.1 ± 10.5 years) were evaluated. In this study, univariable and multivariable regression analysis showed that AFP > 20 ng/ml (OR = 5.824, p = 0.006), enhancing capsule (OR = 7.252, p = 0.001), and mosaic architecture (OR = 32.732, p < 0.001) were independent risk factors of cHCC-CCA with Rim APHE. However, only hepatic capsule retraction (OR = 0.091, p < 0.001) was an independent predictor of iCCA. In addition, combining AFP > 20 ng/ml with enhancing capsule (96.7% vs. 79.2%, p < 0.001) and/or mosaic architecture (96.4% vs. 94.7%, p < 0.001) can improve the sensitivity of differentiating cHCC-CCA (vs. iCCA) with Rim APHE. CONCLUSION: The combination of elevated AFP and MRI features, such as enhancing capsule and mosaic architecture, will help in preoperative differential diagnosis of cHCC-CCA and iCCA with Rim APHE.

MR radiomics to predict microvascular invasion status and biological process in combined hepatocellular carcinoma-cholangiocarcinoma.

OBJECTIVES: To establish an MRI-based radiomics model for predicting the microvascular invasion (MVI) status of cHCC-CCA and to investigate biological processes underlying the radiomics model. METHODS: The study consisted of a retrospective dataset (82 in the training set, 36 in the validation set) and a prospective dataset (25 patients in the test set) from two hospitals. Based on the training set, logistic regression analyses were employed to develop the clinical-imaging model, while radiomic features were extracted to construct a radiomics model. The diagnosis performance was further validated in the validation and test sets. Prognostic aspects of the radiomics model were investigated using the Kaplan-Meier method and log-rank test. Differential gene expression analysis and gene ontology (GO) analysis were conducted to explore biological processes underlying the radiomics model based on RNA sequencing data. RESULTS: One hundred forty-three patients (mean age, 56.4 ± 10.5; 114 men) were enrolled, in which 73 (51.0%) were confirmed as MVI-positive. The radiomics model exhibited good performance in predicting MVI status, with the area under the curve of 0.935, 0.873, and 0.779 in training, validation, and test sets, respectively. Overall survival (OS) was significantly different between the predicted MVI-negative and MVI-positive groups (median OS: 25 vs 18 months, p = 0.008). Radiogenomic analysis revealed associations between the radiomics model and biological processes involved in regulating the immune response. CONCLUSION: A robust MRI-based radiomics model was established for predicting MVI status in cHCC-CCA, in which potential prognostic value and underlying biological processes that regulate immune response were demonstrated. CRITICAL RELEVANCE STATEMENT: MVI is a significant manifestation of tumor invasiveness, and the MR-based radiomics model established in our study will facilitate risk stratification. Furthermore, underlying biological processes demonstrated in the radiomics model will offer valuable insights for guiding immunotherapy strategies. KEY POINTS: MVI is of prognostic significance in cHCC-CCA, but lacks reliable preoperative assessment. The MRI-based radiomics model predicts MVI status effectively in cHCC-CCA. The MRI-based radiomics model demonstrated prognostic value and underlying biological processes. The radiomics model could guide immunotherapy and risk stratification in cHCC-CCA.

Component prediction in combined hepatocellular carcinoma-cholangiocarcinoma: habitat imaging and its biologic underpinnings.

PURPOSE: To construct an MRI-based habitat imaging model to help predict component percentage in combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) preoperatively, and investigate the biologic underpinnings of habitat imaging in cHCC-CCA. METHODS: The study consisted of one retrospective model-building dataset and one prospective validation dataset from two hospitals. All voxels were assigned into different clusters according to the similarity of enhancement pattern by using K-means clustering method, and each habitat's volume fraction in each lesion was calculated. Least absolute shrinkage and selection operator (LASSO) regression analysis was performed to select optimal predictors, and then to establish an MRI-based habitat imaging model. R-squared was calculated to evaluate performance of the prediction models. Model performance was also verified in the prospective dataset with RNA sequencing data, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was then applied to investigate the biologic underpinnings of habitat imaging. RESULTS: A total of 129 patients were enrolled (mean age, 56.1 ± 10.4, 102 man), among which 104 patients were in the retrospective model-building set, while 25 patients in the prospective validation set. Three habitats, habitat1 (HCC-alike habitat), habitat2 (iCCA-alike habitat), and habitat3 (in-between habitat), were identified. Habitat 1's volume fraction, habitat 3's volume fraction, nonrim APHE, nonperipheral washout, and LI-RADS categorization were selected to develop an HCC percentage prediction model with R-squared of 0.611 in the model-building set and 0.541 in the validation set. Habitat 1's volume fraction was correlated with genes involved in regulation of actin cytoskeleton and Rap1 signaling pathway, which regulate cell migration and tumor metastasis. CONCLUSION: Preoperative prediction of HCC percentage in patients with cHCC-CCA was achieved using an MRI-based habitat imaging model, which may correlate with signaling pathways regulating cell migration and tumor metastasis.

Value of magnetic resonance imaging for diagnosis of LR­3 and LR-4 lesions coexisting with hepatocellular carcinoma.

PURPOSE: To explore which preoperative clinical data and conventional magnetic resonance imaging (MRI) features may indicate the presence of hepatocellular carcinoma (HCC) in HCC patients coexisting with LR-3 and LR-4 lesions. METHODS: HCC Patients coexisting with LR-3 and LR-4 lesions who participated in a prospective clinical trial (XX) were included in this study. Two radiologists independently assessed the preoperative MRI features and each lesion was assigned according to the liver imaging reporting and data system (LI-RADS). The preoperative clinical data were also evaluated. The relative values of these parameters were assessed as potential predictors of HCC for coexisting LR-3 and LR-4 lesions. RESULTS: We enrolled 102 HCC patients (58.1 ± 11.5 years; 84.3% males) coexisting with 110 LR-3 and LR-4 lesions (HCCs group [n = 66]; non-HCCs group [n = 44]). The presence of restricted diffusion (OR: 18.590, p < 0.001), delayed enhancement (OR: 0.113, p < 0.001), and mild-moderate T2 hyperintensity (OR: 3.084, p = 0.048) were found to be independent predictors of HCC diagnosis. The sensitivity and specificity of the above independent variables for the diagnosis of HCC ranged from 66.7 to 80.3% and 56.8 to 88.6%, respectively. ROC analysis showed that, in discriminating HCC, the AUCs of the above factors were 0.777, 0.686, and 0.670, respectively. Combining these three findings for the prediction of HCC resulted in a specificity greater than 97%, and the AUC further increased to 0.874. CONCLUSION: The presence of restricted diffusion, delayed enhancement, and mild-moderate T2 hyperintensity can be useful features for risk stratification of coexisting LR-3 and LR-4 lesions in HCC patients. Trial registration a prospective clinical trial (ChiCTR2000036201).

Subcentimeter Nodules with Diagnostic Hallmarks of Hepatocellular Carcinoma: Comparison of Pathological Features and Survival Outcomes with Nodules Measuring 1-2 cm.

Objective: To compare the pathologic diagnosis and survival of patients with subcentimeter and 1-2 cm nodules that present with diagnostic hallmarks of hepatocellular carcinoma (HCC). Methods: Diagnostic hallmarks of HCC were defined as hyperintensity on T2 weighted imaging, restricted diffusion, arterial phase hyperenhancement, washout on portal venous phase, and hypointensity on hepatobiliary phase. We retrospectively included 139 patients undergoing curative resection with single nodules ≤2 cm that present imaging features described above on gadoxetic acid-enhanced MRI. The final diagnosis was confirmed by histopathological assessment. Recurrence-free survival (RFS) was compared using Kaplan-Meier analysis with the Log-rank test. Factors associated with overall and early recurrence were identified using Cox regression analysis. Results: Among 139 nodules (49 nodules <1 cm), there was no significant difference in the percentage of HCC between subcentimeter and 1-2 cm nodules (94.0% vs 94.4%, P > 0.999). Microvascular invasion (MVI) was less common in subcentimeter HCC (4.3% vs 17.6%, P = 0.032). There were 27 recurrences during a median follow-up time of 46.7 months. Patients with subcentimeter HCC achieved less recurrence, with a 5-year RFS rate of 87.3%. The MVI-positive patients had more early and overall recurrence. A tumor size <1 cm was associated with lower overall recurrence (HR, 0.336; P = 0.047). No factors were independently associated with early recurrence. Conclusion: Subcentimeter nodules with diagnostic hallmarks of HCC are highly associated with HCC diagnosis and achieve less tumor recurrence after resection. Early diagnosis and treatment of subcentimeter HCC may be more appropriate.

Preoperative subcategorization based on magnetic resonance imaging in intrahepatic cholangiocarcinoma.

BACKGROUND: Appropriate preoperative identification of iCCA subtype is essential for personalized management, so the aim of this study is to investigate the role of MR imaging features in preoperatively differentiating the iCCA subtype. METHODS: Ninety-three patients with mass-forming intrahepatic cholangiocarcinoma (iCCA, 63 small duct type and 30 large duct type) were retrospectively enrolled according to the latest 5th WHO classification (mean age, males vs. females: 60.66 ± 10.53 vs. 61.88 ± 12.82, 50 men). Significant imaging features for differentiating large duct iCCA and small duct iCCA were identified using univariate and multivariate logistic regression analyses, and a regression-based predictive model was then generated. Furthermore, diagnostic performance parameters of single significant imaging features and the predictive model were obtained, and corresponding receiver operating characteristic (ROC) curves were subsequently presented. RESULTS: The univariate analysis showed that tumor in vein, arterial phase hypoenhancement, intrahepatic duct dilatation, lack of targetoid restriction and lack of targetoid appearance in T2 were predictors of large duct type iCCA. Arterial phase hypoenhancement, intrahepatic duct dilatation and lack of targetoid restriction were independent predictors for large duct type iCCA in multivariate analysis. The regression-based predictive model has achieved the best preoperative prediction performance in iCCA subcategorization so far. The area under the ROC curve of the regression-based predictive model was up to 0.91 (95% CI: 0.85, 0.98), and it was significantly higher than every single significant imaging feature. CONCLUSIONS: Arterial phase hypoenhancement, intrahepatic duct dilatation and lack of targetoid restriction could be considered reliable MR imaging indicators of large duct type iCCA. MR imaging features can facilitate noninvasive prediction of iCCA subtype with satisfactory predictive performance.

Estimating Microvascular Invasion in Patients with Resectable Multinodular Hepatocellular Carcinoma by Using Preoperative Contrast-Enhanced MRI: Establishment and Validation of a Risk Score.

Objective: To determine the preoperative clinicoradiological factors to predict microvascular invasion (MVI) in patients with resectable multinodular hepatocellular carcinoma (mHCC), and further to establish and validate a stratified risk scoring system. Methods: Two hundred and seventy-three patients with pathologically confirmed mHCC (≥2 lesions) without major vascular invasion and biliary tract tumor thrombosis, who underwent preoperative contrast-enhanced MRI and hepatectomy, were consecutively enrolled (training/validation cohort=193/80). Preoperative clinicoradiological variables were collected and analyzed. The multivariable logistic regression was performed to determine the independent predictors of MVI and create a risk score system. The C-index, calibration curve and decision curve were used to evaluate the performance of the risk score. A risk score-based prognostic stratification system was performed in mHCC patients. The risk score system was further verified in the validation cohort. Results: AFP > 400 ng/mL, presence of satellite nodule, mosaic architecture and increased total tumor diameter were independent predictors of MVI while fat in mass was an independent protective factor of MVI. The risk score yielded satisfactory C-index values (training/validation cohort: 0.777/0.758) and fitted well in calibration curves. Decision curve analysis further confirmed its clinical utility. Based on the risk score, mHCC patients were stratified into high-/low-MVI-risk subgroups with significantly different recurrence-free survival (both P < 0.001). Conclusion: The presented risk score incorporating clinicoradiological parameters could stratify mHCC patients into high-risk and low-risk subgroups and predict prognosis in patients with resectable mHCC.

Classification and identification of mosquitoes in China based on rDNA 28S D5 region.

Accurate classification and identification of mosquitoes are essential for the prevention and control of mosquito-borne diseases. In this study, adult mosquitoes were collected from 15 cities across 14 provinces in China. They were identified morphologically with the dominant species determined. Furthermore, representative samples were identified at the molecular level based on rDNA 28S D5. In total, 880 adult mosquitoes were collected belonging to Culex (266), Aedes (473), Armigeres (13), and Anopheles (5). Aedes albopictus and "C. pipiens subgroup" were the dominant species. A total of 140 sequences of 28S D5 region (68 for "C. pipiens subgroup", 51 for Ae. albopictus, 18 for Ar. subalbatus, and three for An. sinensis) ranging from 148 to 161 bp were obtained, with 100 % success of amplification and sequencing. Molecular identification were consistent with morphological classification. Sequence analysis showed that "C. pipiens subgroup" was identified into three clades: the traditional C. pipiens subgroup (Clade I), the newly discovered C. cf. perexiguus (Clade II), and C. new sp. (Clade III). Clade I contained the most abundant haplotypes (16) widely distributed without geographical differences. Clade II included six haplotypes that were aggregately distributed south of the Yangtze River. Only three sequences in Clade III showed two haplotypes with no geographical differences. Further morphological comparisons demonstrated differences in body color, beaks, and abdomens among the three clades. In conclusion, the rDNA 28S D5 region could effectively distinguish Culex, Aedes, Armigeres, and Anopheles species at the lower category level, demonstrating its potential as a mini-DNA barcode for mosquito identification.

Subcentimeter hepatocellular carcinoma (HCC) on gadoxetic-acid-enhanced MRI: less frequent typical imaging features compared to 1-2 cm HCC but better prognosis after surgical resection.

PURPOSE: To compare the imaging features, pathologic characteristics, and survival outcomes between subcentimeter and 1-2 cm hepatocellular carcinoma (HCC). METHODS: This retrospective observational study evaluated the imaging features and medical records of patients with HCC smaller than 2 cm who underwent surgical resection with preoperative gadoxetic-acid-enhanced MRI (EOB-MRI) from January 2013 to December 2021. The incidence of EOB-MRI features and pathological characteristics between the subcentimeter and 1-2 cm HCC were compared. The recurrence-free survival (RFS), including early and overall tumor recurrence, and overall survival (OS) were assessed. RESULTS: A total of 223 patients (82 with subcentimeter HCC and 141 with 1-2 cm HCC, 179 men) were enrolled. Compared with 1-2 cm HCC, subcentimeter HCC showed fewer restricted diffusion (87.8 vs. 95.7%, P = 0.027), portal-phase washout (58.5% vs. 73.8%, P = 0.013), typical enhancement pattern (50.0% vs. 66.7%, P =0.014), and microvascular invasion (4.9% vs. 14.9%, P = 0.022). Patients with subcentimeter HCC had higher RFS (P = 0.027) and better OS (P = 0.029). The estimated RFS rates at 5 years was 83.3% for subcentimeter HCC and 67.3% for 1-2 cm HCC, respectively. The estimated OS rates at 5 years was 97.3% for subcentimeter HCC and 89.5% for 1-2 cm HCC, respectively. CONCLUSION: Subcentimeter HCC showed less frequent EOB-MRI features seen typically in 1-2 cm HCC but better survival outcomes. Therefore, tailored early diagnostic criteria and immediate treatment for subcentimeter HCC may be warranted.