Computed tomography imaging phenotypes of hepatoblastoma identified from radiomics signatures are associated with the efficacy of neoadjuvant chemotherapy.

BACKGROUND: Though neoadjuvant chemotherapy has been widely used in the treatment of hepatoblastoma, there still lacks an effective way to predict its effect. OBJECTIVE: To characterize hepatoblastoma based on radiomics image features and identify radiomics-based lesion phenotypes by unsupervised machine learning, intended to build a classifier to predict the response to neoadjuvant chemotherapy. MATERIALS AND METHODS: In this retrospective study, we segmented the arterial phase images of 137 cases of pediatric hepatoblastoma and extracted the radiomics features using PyRadiomics. Then unsupervised k-means clustering was applied to cluster the tumors, whose result was verified by t-distributed stochastic neighbor embedding (t-SNE). The least absolute shrinkage and selection operator (LASSO) regression was used for feature selection, and the clusters were visually analyzed by radiologists. The correlations between the clusters, clinical and pathological parameters, and qualitative radiological features were analyzed. RESULTS: Hepatoblastoma was clustered into three phenotypes (homogenous type, heterogenous type, and nodulated type) based on radiomics features. The clustering results had a high correlation with response to neoadjuvant chemotherapy (P=0.02). The epithelial ratio and cystic components in radiological features were also associated with the clusters (P=0.029 and 0.008, respectively). CONCLUSIONS: This radiomics-based cluster system may have the potential to facilitate the precise treatment of hepatoblastoma. In addition, this study further demonstrated the feasibility of using unsupervised machine learning in a disease without a proper imaging classification system.

Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas.

PURPOSE: To evaluate the utility of dual-energy CT (DECT) in differentiating non-hypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs) with negative carbohydrate antigen 19-9 (CA 19-9). METHODS: This retrospective study included 26 and 39 patients with pathologically confirmed non-hypervascular PNENs and CA 19-9-negative PDACs, respectively, who underwent contrast-enhanced DECT before treatment between June 2019 and December 2021. The clinical, conventional CT qualitative, conventional CT quantitative, and DECT quantitative parameters of the two groups were compared using univariate analysis and selected by least absolute shrinkage and selection operator regression (LASSO) analysis. Multivariate logistic regression analyses were performed to build qualitative, conventional CT quantitative, DECT quantitative, and comprehensive models. The areas under the receiver operating characteristic curve (AUCs) of the models were compared using DeLong's test. RESULTS: The AUCs of the DECT quantitative (based on normalized iodine concentrations [nICs] in the arterial and portal venous phases: 0.918; 95% confidence interval [CI] 0.852-0.985) and comprehensive (based on tumour location and nICs in the arterial and portal venous phases: 0.966; 95% CI 0.889-0.995) models were higher than those of the qualitative (based on tumour location: 0.782; 95% CI 0.665-0.899) and conventional CT quantitative (based on normalized conventional CT attenuation in the arterial phase: 0.665; 95% CI 0.533-0.797; all P < 0.05) models. The DECT quantitative and comprehensive models had comparable performances (P = 0.076). CONCLUSIONS: Higher nICs in the arterial and portal venous phases were associated with higher blood supply improving the identification of non-hypervascular PNENs.

Special issue "The advance of solid tumor research in China": Prediction of Sunitinib efficacy using computed tomography in patients with pancreatic neuroendocrine tumors.

Clinically effective methods to predict the efficacy of sunitinib, for patients with metastatic or locally advanced pancreatic neuroendocrine tumors (panNET) are scarce, making precision treatment difficult. This study aimed to develop and validate a computed tomography (CT)-based method to predict the efficacy of sunitinib in patients with panNET. Pretreatment CT images of 171 lesions from 38 patients with panNET were included. CT value ratio (CT value of tumor/CT value of abdominal aorta from the same patient) and radiomics features were extracted for model development. Receiver operating curve (ROC) with area under the curve (AUC) and decision curve analysis (DCA) were used to evaluate the proposed model. Tumor shrinkage of >10% at first follow-up after sunitinib treatment was significantly associated with longer progression-free survival (PFS; P < .001) and was used as the major treatment outcome. The CT value ratio could predict tumor shrinkage with AUC of 0.759 (95% confidence interval [CI], 0.685-0.833). We then developed a radiomics signature, which showed significantly higher AUC in training (0.915; 95% CI, 0.866-0.964) and validation (0.770; 95% CI, 0.584-0.956) sets than CT value ratio. DCA also confirmed the clinical utility of the model. Subgroup analysis showed that this radiomics signature had a high accuracy in predicting tumor shrinkage both for primary and metastatic tumors, and for treatment-naive and pretreated tumors. Survival analysis showed that radiomics signature correlated with PFS (P = .020). The proposed radiomics-based model accurately predicted tumor shrinkage and PFS in patients with panNET receiving sunitinib and may help select patients suitable for sunitinib treatment.

Metabolomics to identify fingerprints of carotid atherosclerosis in nonobese metabolic dysfunction-associated fatty liver disease.

BACKGROUND/AIMS: Nonobese metabolic dysfunction-associated fatty liver disease (MAFLD) is paradoxically associated with improved metabolic and pathological features at diagnosis but similar cardiovascular diseases (CVD) prognosis to obese MAFLD. We aimed to utilize the metabolomics to identify the potential metabolite profiles accounting for this phenomenon. METHODS: This prospective multicenter cross-sectional study was conducted in China enrolling derivation and validation cohorts. Liquid chromatography coupled with mass spectrometry and gas chromatography-mass spectrometry were applied to perform a metabolomics measurement. RESULTS: The study involved 120 MAFLD patients and 60 non-MAFLD controls in the derivation cohort. Controls were divided into two groups according to the presence of carotid atherosclerosis (CAS). The MAFLD group was further divided into nonobese MAFLD with/without CAS groups and obese MAFLD with/without CAS groups. Fifty-six metabolites were statistically significant for discriminating the six groups. Among the top 10 metabolites related to CAS in nonobese MAFLD, only phosphatidylethanolamine (PE 20:2/16:0), phosphatidylglycerol (PG 18:0/20:4) and de novo lipogenesis (16:0/18:2n-6) achieved significant areas under the ROC curve (AUCs, 0.67, p = 0.03; 0.79, p = 0.02; 0.63, p = 0.03, respectively). The combination of these three metabolites and liver stiffness achieved a significantly higher AUC (0.92, p < 0.01). In obese MAFLD patients, cystine was found to be significant with an AUC of 0.69 (p = 0.015), followed by sphingomyelin (SM 16:1/18:1) (0.71, p = 0.004) and de novo lipogenesis (16:0/18:2n-6) (0.73, p = 0.004). The combination of these three metabolites, liver fat content and age attained a significantly higher AUC of 0.91 (p < 0.001). The AUCs of these metabolites remained highly significant in the independent validation cohorts involving 200 MAFLD patients and 90 controls. CONCLUSIONS: Diagnostic models combining different metabolites according to BMI categories could raise the accuracy of identifying subclinical CAS. Trial registration The study protocol was approved by the local ethics committee and all the participants have provided written informed consent (Approval number: [2014] No. 112, registered at the Chinese Clinical Trial Registry, ChiCTR-ChiCTR2000034197).

Preoperative assessment of peripheral vascular invasion of pancreatic ductal adenocarcinoma based on high-resolution MRI.

OBJECTIVES: Preoperative imaging of vascular invasion is important for surgical resection of pancreatic ductal adenocarcinoma (PDAC). However, whether MRI and CT share the same evaluation criteria remains unclear. This study aimed to compare the diagnostic accuracy of high-resolution MRI (HR-MRI), conventional MRI (non-HR-MRI) and CT for PDAC vascular invasion. METHODS: Pathologically proven PDAC with preoperative HR-MRI (79 cases, 58 with CT) and non-HR-MRI (77 cases, 59 with CT) were retrospectively collected. Vascular invasion was confirmed surgically or pathologically. The degree of tumour-vascular contact, vessel narrowing and contour irregularity were reviewed respectively. Diagnostic criteria 1 (C1) was the presence of all three characteristics, and criteria 2 (C2) was the presence of any one of them. The diagnostic efficacies of different examination methods and criteria were evaluated and compared. RESULTS: HR-MRI showed satisfactory performance in assessing vascular invasion (AUC: 0.87-0.92), especially better sensitivity (0.79-0.86 vs. 0.40-0.79) than that with non-HR-MRI and CT. HR-MRI was superior to non-HR-MRI. C2 was superior to C1 on CT evaluation (0.85 vs. 0.79, P = 0.03). C1 was superior to C2 in the venous assessment using HR-MRI (0.90 vs. 0.87, P = 0.04) and in the arterial assessment using non-HR-MRI (0.69 vs. 0.68, P = 0.04). The combination of C1-assessed HR-MRI and C2-assessed CT was significantly better than that of CT alone (0.96 vs. 0.86, P = 0.04). CONCLUSIONS: HR-MRI more accurately assessed PDAC vascular invasion than conventional MRI and may contribute to operative decision-making. C1 was more applicable to MRI scans, and C2 to CT scans. The combination of C1-assessed HR-MRI and C2-assessed CT outperformed CT alone and showed the best efficacy in preoperative examination of PDAC.

Evaluation of Hypoxia in Hepatocellular Carcinoma Using Quantitative MRI: Significances, Challenges, and Advances.

This review aimed to perform a scoping review of promising MRI methods in assessing tumor hypoxia in hepatocellular carcinoma (HCC). The hypoxic microenvironment and upregulated hypoxic metabolism in HCC are determining factors of poor prognosis, increased metastatic potential, and resistance to chemotherapy and radiotherapy. Assessing hypoxia in HCC is essential for personalized therapy and predicting prognoses. Oxygen electrodes, protein markers, optical imaging, and positron emission tomography can evaluate tumor hypoxia. These methods lack clinical applicability because of invasiveness, tissue depth, and radiation exposure. MRI methods, including blood oxygenation level-dependent, dynamic contrast-enhanced MRI, diffusion-weighted imaging, MRI spectroscopy, chemical exchange saturation transfer MRI, and multinuclear MRI, are promising noninvasive methods that evaluate the hypoxic microenvironment by observing biochemical processes in vivo, which may inform on therapeutic options. This review summarizes the recent challenges and advances in MRI techniques for assessing hypoxia in HCC and highlights the potential of MRI methods for examining the hypoxic microenvironment via specific metabolic substrates and pathways. Although the utilization of MRI methods for evaluating hypoxia in patients with HCC is increasing, rigorous validation is needed in order to translate these MRI methods into clinical use. Due to the limited sensitivity and specificity of current quantitative MRI methods, their acquisition and analysis protocols require further improvement. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 4.

Clinical outcome is distinct between radiological stricture and endoscopic stricture in ileal Crohn's disease.

OBJECTIVES: Differences in clinical adverse outcomes (CAO) based on different intestinal stricturing definitions in Crohn's disease (CD) are poorly documented. This study aims to compare CAO between radiological strictures (RS) and endoscopic strictures (ES) in ileal CD and explore the significance of upstream dilatation in RS. METHODS: This retrospective double-center study included 199 patients (derivation cohort, n = 157; validation cohort, n = 42) with bowel strictures who simultaneously underwent endoscopic and radiologic examinations. RS was defined as a luminal narrowing with wall thickening relative to the normal gut on cross-sectional imaging (group 1 (G1)), which further divided into G1a (without upstream dilatation) and G1b (with upstream dilatation). ES was defined as an endoscopic non-passable stricture (group 2 (G2)). Strictures met the definitions of RS (with or without upstream dilatation) and ES were categorized as group 3 (G3). CAO referred to stricture-related surgery or penetrating disease. RESULTS: In the derivation cohort, G1b (93.3%) had the highest CAO occurrence rate, followed by G3 (32.6%), G1a (3.2%), and G2 (0%) (p < 0.0001); the same order was found in the validation cohort. The CAO-free survival time was significantly different among the four groups (p < 0.0001). Upstream dilatation (hazard ratio, 1.126) was a risk factor for predicting CAO in RS. Furthermore, when upstream dilatation was added to diagnose RS, 17.6% of high-risk strictures were neglected. CONCLUSIONS: CAO differs significantly between RS and ES, and clinicians should pay more attention to strictures in G1b and G3. Upstream dilatation has an important impact on the clinical outcome of RS but may not be an essential factor for RS diagnosis. CLINICAL RELEVANCE STATEMENT: This study explored the definition of intestinal stricture with the greatest significance for the clinical diagnosis and prognosis of patients with CD, and consequently provided effective auxiliary information for clinicians to formulate strategies for the treatment of CD intestinal strictures. KEY POINTS: • The retrospective double-center study showed that clinical adverse outcome is different between radiological strictures and endoscopic strictures in CD. • Upstream dilatation has an important impact on the clinical outcome of radiological strictures but may not be an essential factor for diagnosis of radiological strictures. • Radiological stricture with upstream dilatation and simultaneous radiological and endoscopic stricture were at increased risk for clinical adverse outcomes; thus, closer monitoring should be considered.

Impact of skeletal muscle mass evaluating methods on severity of metabolic associated fatty liver disease in non-elderly adults.

The study aimed to explore the relationships of skeletal muscle mass with disease severity in metabolic-associated fatty liver disease (MAFLD) patients with different methods. Consecutive subjects undergoing bioelectrical impedance analysis were included. The steatosis grade and liver fibrosis were evaluated by MRI-derived proton density fat fraction and two-dimensional shear wave elastography. The appendicular skeletal muscle mass (ASM) was adjusted by height2 (ASM/H2), weight (ASM/W) and BMI (ASM/BMI). Overall, 2223 subjects (50·5 %, MAFLD; 46·9 %, male) were included, with the mean age 37·4 ± 10·6 years. In multivariate logistic regression analysis, the subjects with the lowest quartile (Q1) of ASM/W or ASM/BMI had higher risk ratios for MAFLD (OR (95 % CI) in male: 2·57 (1·35, 4·89), 2·11(1·22, 3·64); in female: 4·85 (2·33, 10·01), 4·81 (2·52, 9·16), all P < 0·05, all for Q1 v. Q4). The MAFLD patients with lower quartiles of ASM/W had the higher risk OR for insulin resistance (IR), both in male and female (2·14 (1·16, 3·97), 4·26 (1·29, 14·02) for Q4 v. Q1, both P < 0·05). While the significant OR were not observed when ASM/H2 and ASM/BMI were used. There were significant dose-dependent associations between decreased ASM/W as well as ASM/BMI and moderate-severe steatosis (2·85(1·54, 5·29), 1·90(1·09, 3·31), both P < 0·05) in male MAFLD patients. In conclusion, ASM/W is superior to ASM/H2 and ASM/BMI in predicting the degree of MAFLD. A lower ASM/W is associated with IR and moderate-severe steatosis in non-elderly male MAFLD.

Comparisons of Insulin Resistance- and Steatosis-Based Scores in Monitoring Metabolic Associated Fatty Liver Disease Treatment Response.

BACKGROUND: Quantitative measurements of liver fat contents (LFCs) by magnetic resonance imaging derived-proton density fat fraction (MRI-PDFF) are accurate but limited by availability, convenience, and expense in the surveillance of metabolic associated fatty liver (MAFLD). Insulin resistance (IR) and steatosis-associated serum indices are useful in screening for MAFLD, but their value in monitoring MAFLD with or without chronic hepatitis B virus (CHB) infection remains unclear and we aimed to evaluate these scores in predicting changes in LFC. METHODS: We conducted a prospective study between January 2015 and December 2021 with 620 consecutive participants with MAFLD (212 participants with CHB) who received a 24-week lifestyle intervention. The homeostasis model assessment of IR (HOMA-IR), HOMA2 index, glucose-insulin ratio, quantitative insulin sensitivity check index, fasting insulin resistance index, fatty liver index (FLI), hepatic steatosis index (HSI), liver fat score (LFS), visceral adiposity index, and triglycerides * glucose were calculated. RESULTS: When using endpoints such as LFS improvements of ≥5% or 10% or escalations of ≥5%, LFS had the highest area under the curve (AUC) values at all endpoints for MAFLD alone (0.756, 95% CI: 0.707-0.805; 0.761, 95% CI: 0.705-0.818; 0.807, 95% CI: 0.713-0.901, all p < 0.05, respectively). With CHB, the FLI (AUC = 0.750) and HIS (AUC = 0.770) exhibited the highest AUCs between the former two outcomes, respectively, but no score could predict LFC escalation of ≥5%. CONCLUSION: Among IR and steatosis scores, changes in LFC through lifestyle interventions can be captured with LFS possessing moderate precision but not in those with CHB.

Clinical-radiomics predictors to identify the suitability of transarterial chemoembolization treatment in intermediate-stage hepatocellular carcinoma: A multicenter study.

BACKGROUND: Although transarterial chemoembolization (TACE) is the first-line therapy for intermediate-stage hepatocellular carcinoma (HCC), it is not suitable for all patients. This study aimed to determine how to select patients who are not suitable for TACE as the first treatment choice. METHODS: A total of 243 intermediate-stage HCC patients treated with TACE at three centers were retrospectively enrolled, of which 171 were used for model training and 72 for testing. Radiomics features were screened using the Spearman correlation analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Subsequently, a radiomics model was established using extreme gradient boosting (XGBoost) with 5-fold cross-validation. The Shapley additive explanations (SHAP) method was used to visualize the radiomics model. A clinical model was constructed using univariate and multivariate logistic regression. The combined model comprising the radiomics signature and clinical factors was then established. This model's performance was evaluated by discrimination, calibration, and clinical application. Generalization ability was evaluated by the testing cohort. Finally, the model was used to analyze overall and progression-free survival of different groups. RESULTS: A third of the patients (81/243) were unsuitable for TACE treatment. The combined model had a high degree of accuracy as it identified TACE-unsuitable cases, at a sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of 0.759, 0.885, 0.906 [95% confidence interval (CI): 0.859-0.953] in the training cohort and 0.826, 0.776, and 0.894 (95% CI: 0.815-0.972) in the testing cohort, respectively. CONCLUSIONS: The high degree of accuracy of our clinical-radiomics model makes it clinically useful in identifying intermediate-stage HCC patients who are unsuitable for TACE treatment.

Development and Validation of a Novel Computed-Tomography Enterography Radiomic Approach for Characterization of Intestinal Fibrosis in Crohn's Disease.

BACKGROUND & AIMS: No reliable method for evaluating intestinal fibrosis in Crohn's disease (CD) exists; therefore, we developed a computed-tomography enterography (CTE)-based radiomic model (RM) for characterizing intestinal fibrosis in CD. METHODS: This retrospective multicenter study included 167 CD patients with 212 bowel lesions (training, 98 lesions; test, 114 lesions) who underwent preoperative CTE and bowel resection at 1 of the 3 tertiary referral centers from January 2014 through June 2020. Bowel fibrosis was histologically classified as none-mild or moderate-severe. In the training cohort, 1454 radiomic features were extracted from venous-phase CTE and a machine learning-based RM was developed based on the reproducible features using logistic regression. The RM was validated in an independent external test cohort recruited from 3 centers. The diagnostic performance of RM was compared with 2 radiologists' visual interpretation of CTE using receiver operating characteristic (ROC) curve analysis. RESULTS: In the training cohort, the area under the ROC curve (AUC) of RM for distinguishing moderate-severe from none-mild intestinal fibrosis was 0.888 (95% confidence interval [CI], 0.818-0.957). In the test cohort, the RM showed robust performance across 3 centers with an AUC of 0.816 (95% CI, 0.706-0.926), 0.724 (95% CI, 0.526-0.923), and 0.750 (95% CI, 0.560-0.940), respectively. Moreover, the RM was more accurate than visual interpretations by either radiologist (radiologist 1, AUC = 0.554; radiologist 2, AUC = 0.598; both, P < .001) in the test cohort. Decision curve analysis showed that the RM provided a better net benefit to predicting intestinal fibrosis than the radiologists. CONCLUSIONS: A CTE-based RM allows for accurate characterization of intestinal fibrosis in CD.

The role of 18F-FDG PET/CT in predicting the pathological response to neoadjuvant PD-1 blockade in combination with chemotherapy for resectable esophageal squamous cell carcinoma.

PURPOSE: Accurate assessment of residual disease of tumor and lymph nodes after neoadjuvant immunochemotherapy is crucial in the active surveillance for patients with pathological complete response (pCR) and the optimal extent of lymphadenectomy for patients with non-pCR. This post hoc analysis aimed to evaluate the performance of 18F-FDG PET/CT to predict the pathological response to neoadjuvant immunochemotherapy for esophageal squamous cell carcinoma (ESCC). METHODS: Fifty-eight resectable ESCC patients received two cycles of camrelizumab in combination with chemotherapy and were enrolled in the final analysis. The 18F-FDG PET/CT scans were acquired at baseline (scan-1) and after immunochemotherapy but prior to surgery (scan-2). Maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), tumor-to-blood pool SUVmax ratio (SUVTBR), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were evaluated for their association with the pathological response to immunochemotherapy. RESULTS: Nineteen patients (32.8%, 19/58) had pCR and thirty-nine patients (67.2%, 39/58) had non-pCR after two doses of camrelizumab and chemotherapy. At scan-2, the SUVmax, SUVmean, SUVTBR, TLG, and MTV were significantly lower in pCR than in non-pCR patients. Decrease in TLG and MTV between scan-2 and scan-1 of the same patient was significantly higher in the pCR than in the non-pCR group. In the receiver operating characteristic curve analysis, SUVmax, SUVmean, SUVTBR, TLG, and MTV in scan-2 showed excellent predictive value for the pCR of primary tumors. Furthermore, SUVmax in scan-2 were higher in positive lymph nodes than in negative ones, suggesting a high negative predictive ability (98.6%) with a cut-off value at 1.4. CONCLUSION: The parameters of 18F-FDG PET/CT have the excellent performance for predicting pCR after the combined neoadjuvant immunochemotherapy in resectable ESCC. TRIAL REGISTRATION: ChiCTR2000028900. Registered on January 6, 2020.

Non-invasive diagnosis strategy of hepatocellular carcinoma in low-risk population.

AIMS: With prevalence of hepatocellular carcinoma (HCC) in low-risk population (LRP), establishing a non-invasive diagnostic strategy becomes increasingly urgent to spare unnecessary biopsies in this population. The purposes of this study were to find characterisics of HCC and to establish a proper non-invasive method to diagnose HCC in LRP. METHODS: A total of 681 patients in LRP (defined as the population without cirrhosis, chronic HBV infection or HCC history) were collected from 2 institutions. The images of computed tomography (CT) and magnetic resonance imaging (MRI) were manually analysed. We divided the patients into the training cohort (n = 324) and the internal validating cohort (n = 139) by admission time in the first institution. The cohort in the second institution was viewed as the external validation (n = 218). A multivariate logistic regression model incorporating both imaging and clinical independent risk predictors was developed. C-statistics was used to evaluate the diagnostic performance. RESULTS: Besides the major imaging features of HCC (non-rim enhancement, washout and enhancing capsule), tumor necrosis or severe ischemia (TNSI) on imaging and two clinical characteristics (gender and alpha fetoprotein) were also independently associated with HCC diagnosis (all P < 0.01). A clinical model (including 3 major features, TNSI, gender and AFP) was built to diagnose HCC and achieved good diagnostic performance (area under curve values were 0.954 in the training cohort, 0.931 in the internal validation cohort and 0.902 in the external cohort). CONCLUSIONS: The clinical model in this study developed a satisfied non-invasive diagnostic performance for HCC in LRP.

Tumor fibrosis correlates with the survival of patients with pancreatic adenocarcinoma and is predictable using clinicoradiological features.

OBJECTIVES: To evaluate the prognostic value of fibrosis for patients with pancreatic adenocarcinoma (PDAC) and preoperatively predict fibrosis using clinicoradiological features. Tumor fibrosis plays an important role in the chemoresistance of PDAC. However, the prognostic value of tumor fibrosis remains contradiction and accurate prediction of tumor fibrosis is required. METHODS: The study included 131 patients with PDAC who underwent first-line surgery. The prognostic value of fibrosis and rounded cutoff fibrosis points for median overall survival (OS) and disease-free survival (DFS) were determined using Cox regression and receiver operating characteristic (ROC) analyses. Then the whole cohort was randomly divided into training (n = 88) and validation (n = 43) sets. Binary logistic regression analysis was performed to select independent risk factors for fibrosis in the training set, and a nomogram was constructed. Nomogram performance was assessed using a calibration curve and decision curve analysis (DCA). RESULTS: Hazard ratios of fibrosis for OS and DFS were 1.121 (95% confidence interval [CI]: 1.082-1.161) and 1.110 (95% CI: 1.067-1.155). ROC analysis identified 40% as the rounded cutoff fibrosis point for median OS and DFS. Tumor diameter, carbohydrate antigen 19-9 level, and peripancreatic tumor infiltration were independent risk factors; areas under the nomogram curve were 0.810 and 0.804 in the training and validation sets, respectively. The calibration curve indicated good agreement of the nomogram, and DCA demonstrated good clinical usefulness. CONCLUSIONS: Tumor fibrosis was associated with poor OS and DFS in patients with PDAC. The nomogram incorporating clinicoradiological features was useful for preoperatively predicting tumor fibrosis. KEY POINTS: • Tumor fibrosis is correlated with poor prognosis in patients with pancreatic adenocarcinoma. • Tumor fibrosis can be categorized according to its association with overall survival and disease-free survival. • A nomogram incorporating carbohydrate antigen 19-9 level, tumor diameter, and peripancreatic tumor infiltration is useful for preoperatively predicting tumor fibrosis.

Intestinal fibrosis classification in patients with Crohn's disease using CT enterography-based deep learning: comparisons with radiomics and radiologists.

OBJECTIVES: Accurate evaluation of bowel fibrosis in patients with Crohn's disease (CD) remains challenging. Computed tomography enterography (CTE)-based radiomics enables the assessment of bowel fibrosis; however, it has some deficiencies. We aimed to develop and validate a CTE-based deep learning model (DLM) for characterizing bowel fibrosis more efficiently. METHODS: We enrolled 312 bowel segments of 235 CD patients (median age, 33 years old) from three hospitals in this retrospective study. A training cohort and test cohort 1 were recruited from center 1, while test cohort 2 from centers 2 and 3. All patients performed CTE within 3 months before surgery. The histological fibrosis was semi-quantitatively assessed. A DLM was constructed in the training cohort based on a 3D deep convolutional neural network with 10-fold cross-validation, and external independent validation was conducted on the test cohorts. The radiomics model (RM) was developed with 4 selected radiomics features extracted from CTE images by using logistic regression. The evaluation of CTE images was performed by two radiologists. DeLong's test and a non-inferiority test were used to compare the models' performance. RESULTS: DLM distinguished none-mild from moderate-severe bowel fibrosis with an area under the receiver operator characteristic curve (AUC) of 0.828 in the training cohort and 0.811, 0.808, and 0.839 in the total test cohort, test cohorts 1 and 2, respectively. In the total test cohort, DLM achieved better performance than two radiologists (*1 AUC = 0.579, *2 AUC = 0.646; both p < 0.05) and was not inferior to RM (AUC = 0.813, p < 0.05). The total processing time for DLM was much shorter than that of RM (p < 0.001). CONCLUSION: DLM is better than radiologists in diagnosing intestinal fibrosis on CTE in patients with CD and not inferior to RM; furthermore, it is more time-saving compared to RM. KEY POINTS: • Question Could computed tomography enterography (CTE)-based deep learning model (DLM) accurately distinguish intestinal fibrosis severity in patients with Crohn's disease (CD)? • Findings In this cross-sectional study that included 235 patients with CD, DLM achieved better performance than that of two radiologists' interpretation and was not inferior to RM with significant differences and much shorter processing time. • Meaning This DLM may accurately distinguish the degree of intestinal fibrosis in patients with CD and guide gastroenterologists to formulate individualized treatment strategies for those with bowel strictures.

Utility of Quantitative Metrics From Dual-Layer Spectral-Detector CT for Differentiation of Pancreatic Neuroendocrine Tumor and Neuroendocrine Carcinoma.

BACKGROUND. The 2019 WHO classification of digestive system tumors separates neuroendocrine neoplasms (NENs) into neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs), which are considered to represent pathologically distinct entities warranting different management approaches. Dual-layer spectral-detector CT (DLCT) may aid their differentiation through specific material decomposition. OBJECTIVE. The purpose of this study was to assess the utility of quantitative metrics derived from DLCT for the differentiation of pancreatic NET and NEC. METHODS. This retrospective study included 104 patients (mean age, 51 ± 13 [SD] years; 52 women, 52 men) with pathologically confirmed NEN (89 NET, including 22 grade 1, 48 grade 2, and 19 grade 3; 15 NEC) who underwent multiphase DLCT within 15 days before biopsy or resection. Two radiologists independently placed ROIs to record tumor attenuation, iodine concentration (IC), and effective atomic number (Zeff) across phases and assessed qualitative features (composition, homogeneity, margins, calcifications, main pancreatic duct dilatation, vascular invasion, lymphadenopathy). Interobserver agreement was assessed. Mean and median values of both readers' measurements were obtained for quantitative measures; consensus was reached for qualitative features. NET and NEC were compared using multivariable regression analysis and ROC analysis. RESULTS. Interobserver agreement, expressed as intraclass correlation coefficients, ranged from 0.869 to 0.992 for quantitative metrics and, expressed as kappa coefficients, ranged from 0.723 to 0.816 for qualitative features. In multivariable analysis of qualitative and quantitative features, significant independent predictors of NEC (p < .05) were IC in the portal venous phase (median, 1.3 mg/mL for NEC vs 2.7 mg/mL for NET), Zeff in the portal venous phase (median, 8.1 vs 8.6), and attenuation in the portal venous phase (median, 78.2 vs 113.5 HU). AUC for predicting NEC was 0.897 for IC, 0.884 for Zeff, 0.921 for combination of IC and Zeff, and 0.855 for attenuation. Predicted probability based on a combination of IC and Zeff achieved sensitivity of 93.33% and specificity of 80.90% for predicting NEC. Significant independent predictors (p < .05) for differentiating grade 3 NET and NEC were IC (median, 2.0 vs 1.3 mg/mL; AUC = 0.789) and attenuation (mean, 90.3 vs 78.2 HU; AUC = 0.647), both measured in the portal venous phase. CONCLUSION. Incorporation of DLCT metrics improves differentiation of NET and NEC compared with conventional CT attenuation and qualitative features. CLINICAL IMPACT. DLCT may help select patients with pancreatic NENs for platinum-based chemotherapies.

The role of neoadjuvant conventional transarterial chemoembolization with radiofrequency ablation in the treatment of recurrent hepatocellular carcinoma after initial hepatectomy with microvascular invasion.

OBJECTIVES: Recurrent hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI)-positive primary tumor is at high risk of re-recurrence while treated with radiofrequency ablation (RFA). We aimed to investigate whether neoadjuvant conventional transarterial chemoembolization (cTACE) was effective in reducing re-recurrence after RFA for recurrent HCC patients with MVI-positive primary tumors. METHODS: In this retrospective multicenter study, 468 patients with solitary small recurrent HCC (≤3.0cm) underwent RFA alone (n = 322) or with neoadjuvant cTACE (n = 146) between June 2007 and December 2017 were included. Overall survival (OS) and recurrence-free survival (RFS) were compared. RESULTS: The 1-, 5-year OS rates were 74.8%, 42.5% for RFA with neoadjuvant cTACE group, and 53.5%, 28.7% for RFA group (P < 0.001). The corresponding RFS rates were 51.7%, 24.4% for RFA with neoadjuvant cTACE group, and 36.1%, 9.3% for RFA group (P < 0.001). In subgroup analyses, the OS and RFS for neoadjuvant cTACE group were longer than those for RFA group no matter tumor size > 2cm (HR = 0.52, 95% CI: 0.36-0.77; HR = 0.49, 95% CI: 0.36-0.67) or not (HR = 0.53, 95% CI: 0.32-0.88; HR = 0.65, 95% CI: 0.42-0.98), or the time interval of recurrence from initial treatment ≤ 1 year (HR = 0.53, 95% CI: 0.36-0.77; HR = 0.70, 95% CI: 0.52-0.94) or not (HR = 0.56, 95% CI: 0.34-0.95; HR = 0.39, 95% CI: 0.25-0.62). Multivariable analyses showed that RFA alone (HR = 1.329, P = 0.031; HR = 1.764, P = 0.004) and interval of recurrence from initial treatment > 1 year(HR = 0.642, P = 0.001; HR = 0.298, P = 0.037) were independent prognostic factors of OS and RFS. CONCLUSIONS: Neoadjuvant cTACE could effectively reduce re-recurrence after RFA, and improve the long-term survivals for patients with solitary small recurrent HCC whose primary tumor was MVI-positive. Key pointsFor recurrent hepatocellular carcinoma (HCC) patients whose primary tumor was positive for microvascular invasion, neoadjuvant conventional transarterial chemoembolization (cTACE) with radiofrequency ablation (RFA) achieved better efficacy.Multivariable analyses showed that the interval of recurrence from initial treatment > 1 year and RFA alone were independent prognostic factors of overall survival and recurrence-free survival, respectively.

Lack of Response to Transarterial Chemoembolization for Intermediate-Stage Hepatocellular Carcinoma: Abandon or Repeat?

Background Transarterial chemoembolization (TACE) is the standard treatment for intermediate-stage hepatocellular carcinoma (HCC). It is unknown whether conventional TACE (cTACE) should be continued or abandoned after initial nonresponse for intermediate-stage HCC. The optimal number of sessions before abandoning cTACE remains debated. Purpose To define the number of sessions that patients who do not respond to treatment (hereafter, nonresponders, with stable disease [SD] or progressive disease [PD]) should undergo before abandoning cTACE. Materials and Methods Patients with intermediate-stage HCC and Child-Pugh A liver function who underwent consecutive cTACE sessions between January 2005 and December 2012 were retrospectively included from three centers. Radiologic response rate to each session and its correlation with overall survival were evaluated. Response was assessed by modified Response Evaluation Criteria in Solid Tumors. A nomogram constructed by using tumor size, tumor capsule, and α-fetoprotein to predict patients who responded to treatment (hereafter, responders) was validated with sensitivity and specificity. Results This study evaluated 4154 patients (mean age, 58 years ± 6 [standard deviation]; 3777 men; primary cohort, 3442 patients [mean age, 58 years ± 6; 3129 men]; validation cohort, 712 patients [mean age, 58 years ± 7; 648 men]). Response rate to first cTACE was 35.6% (1227 of 3442, primary cohort) and 36.7% (261 of 712, validation cohort). For patients with SD who were nonresponders to first cTACE, the response rates after second cTACE were 46.1% (719 of 1560) and 48.4% (147 of 304); for patients with SD who were nonresponders to the second cTACE session, the response rates after the third cTACE session were 58.3% (591 of 1014) and 48.5% (98 of 202). For patients with SD who were nonresponders to third, fourth, and fifth cTACE sessions, response rates after fourth, fifth, and sixth cTACE sessions were less than 10%. All response rates in patients with PD who were nonresponders to the next cTACE were less than 5%. Responders to first, second, and third cTACE had higher 5-year overall survival than nonresponders (all P < .001) but responders to the fourth cTACE did not (P = .21). The sensitivity and specificity of a nomogram predicted responders to third cTACE: 75.0% and 79.4% (internal validation) and 78.6% and 87.0% (external validation), respectively. Conclusion Three sessions were recommended before abandoning conventional transarterial embolization (cTACE) for intermediate-stage hepatocellular carcinoma. The nomogram developed in this study identified responders to third cTACE. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Georgiades in this issue.

Microvascular Invasion Status and Its Survival Impact in Hepatocellular Carcinoma Depend on Tissue Sampling Protocol.

BACKGROUND: The aim of this work is to explore the impact of the number of sampling sites (NuSS) and sampling location on microvascular invasion (MVI) detection rate and long-term survival of hepatocellular carcinoma (HCC), and determine the minimum NuSS for sufficient MVI detection. PATIENTS AND METHODS: From January 2008 to March 2017, 1144 HCC patients who underwent hepatectomy were retrospectively enrolled. Associations between NuSS and MVI positive rates and overall survival were investigated. NuSS thresholds were determined by Chow test and confirmed prospectively in 305 patients from April 2017 to February 2019. In the prospective cohort, the distribution of MVI in different sampling locations and its prognostic effect was evaluated. RESULTS: MVI positive rates increased as NuSS increased, steadily reaching a plateau when NuSS reached a threshold. A threshold of four, six, eight, and eight sampling sites within paracancerous parenchyma ≤ 1 cm from tumor was required for detecting MVI in solitary tumors measuring 1.0-3.0, 3.1-4.9, and ≥ 5.0 cm and multiple tumors. Patients with adequate NuSS achieved longer survival than those with inadequate NuSS [hazard ratio (HR) = 0.75, P = 0.043]. For all MVI-positive patients, MVI could be detected positive in paracancerous parenchyma ≤ 1 cm from tumor. Patients with MVI positive in paracancerous parenchyma > 1 cm had higher recurrence risk than those with MVI positive only in parenchyma ≤ 1 cm (HR = 6.05, P < 0.001). CONCLUSIONS: Adequate NuSS is associated with higher MVI detection rate and better survival of HCC patients. We recommend four, six, eight, and eight as the cut-points for evaluating MVI sampling quality and patients' prognostic stratification in the subgroups of solitary tumors measuring 1.0-3.0 cm, 3.1-4.9 cm and ≥ 5.0 cm and multiple tumors, respectively.

Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-checkpoint inhibitor plus chemotherapy (ICI + CT) in patients with advanced esophageal squamous cell carcinoma (ESCC). METHODS: A total of 64 patients with advance ESCC receiving first-line ICI + CT at two centers between January 2019 and June 2020 were enrolled in this study. Both 2D ROIs and 3D ROIs were segmented. ComBat correction was applied to minimize the potential bias on the results due to different scan protocols. A total of 788 features were extracted and radiomics models were built on corrected/uncorrected 2D and 3D features by using 5-fold cross-validation. The performance of the radiomics models was assessed by its discrimination, calibration and clinical usefulness with independent validation. RESULTS: Five features and support vector machine algorithm were selected to build the 2D uncorrected, 2D corrected, 3D uncorrected and 3D corrected radiomics models. The 2D radiomics models significantly outperformed the 3D radiomics models in both primary and validation cohorts. When ComBat correction was used, the performance of 2D models was better (p = 0.0059) in the training cohort, and significantly better (p < 0.0001) in the validation cohort. The 2D corrected radiomics model yielded the optimal performance and was used to build the nomogram. The calibration curve of the radiomics model demonstrated good agreement between prediction and observation and the decision curve analysis confirmed the clinical utility. CONCLUSIONS: The easy-to-use 2D corrected radiomics model could facilitate noninvasive preselection of ESCC patients who would benefit from ICI + CT.