Search

Objectives: This study aims to investigate the differences in plaque characteristics and fat attenuation index (FAI) between in patients who received revascularization versus those who did not receive revascularization and examine whether the machine learning (ML)-based model constructed by plaque characteristics and FAI can predict revascularization. Methods: This study was a post hoc analysis of a prospective single-centre registry of sequential patients undergoing coronary computed tomography angiography, referred from inpatient and emergency department settings (n = 261, 63 years ± 8; 188 men). The primary outcome was revascularization by percutaneous coronary revascularization. The computed tomography angiography (CTA) images were analysed by experienced radiologists using a dedicated workstation in a blinded fashion. The ML-based model was automatically computed. Results: The study cohort consisted of 261 subjects. Revascularization was performed in 105 subjects. Patients receiving revascularization had higher FAI value (67.35 ± 5.49 vs −80.10 ± 7.75 Hu, P < .001) as well as higher plaque length, calcified, lipid, and fibrous plaque burden and volume. When FAI was incorporated into an ML risk model based on plaque characteristics to predict revascularization, the area under the curve increased from 0.84 (95% CI, 0.68-0.99) to 0.95 (95% CI, 0.88-1.00). Conclusions: ML algorithms based on FAI and characteristics could help improve the prediction of future revascularization and identify patients likely to receive revascularization. Advances in knowledge: Pre-procedural FAI could help guide revascularization in symptomatic coronary artery disease patients. [ABSTRACT FROM AUTHOR]

Objectives: This study aims to investigate the differences in plaque characteristics and fat attenuation index (FAI) between in patients who received revascularization versus those who did not receive revascularization and examine whether the machine learning (ML)-based model constructed by plaque characteristics and FAI can predict revascularization. Methods: This study was a post hoc analysis of a prospective single-centre registry of sequential patients undergoing coronary computed tomography angiography, referred from inpatient and emergency department settings (n = 261, 63 years ± 8; 188 men). The primary outcome was revascularization by percutaneous coronary revascularization. The computed tomography angiography (CTA) images were analysed by experienced radiologists using a dedicated workstation in a blinded fashion. The ML-based model was automatically computed. Results: The study cohort consisted of 261 subjects. Revascularization was performed in 105 subjects. Patients receiving revascularization had higher FAI value (67.35 ± 5.49 vs −80.10 ± 7.75 Hu, P < .001) as well as higher plaque length, calcified, lipid, and fibrous plaque burden and volume. When FAI was incorporated into an ML risk model based on plaque characteristics to predict revascularization, the area under the curve increased from 0.84 (95% CI, 0.68-0.99) to 0.95 (95% CI, 0.88-1.00). Conclusions: ML algorithms based on FAI and characteristics could help improve the prediction of future revascularization and identify patients likely to receive revascularization. Advances in knowledge: Pre-procedural FAI could help guide revascularization in symptomatic coronary artery disease patients. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objectives: To compare the diagnostic performance of machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis. Methods: Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference. Results: The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01). Conclusion: ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis. Clinical relevance statement: ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other. Key Points: • Both machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis. • Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis. • ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objectives: Impeded diffusion fraction (IDF) is a novel and promising diffusion-weighted imaging (DWI) technique that allows for the detection of various diffusion compartments, including macromolecular coordinated water, free diffusion, perfusion, and cellular free water. This study aims to investigate the clinical potential of IDF-DWI in detecting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: 66 patients were prospectively included. Metrics derived from IDF-DWI and the apparent diffusion coefficient (ADC) were calculated. Multivariate logistic regression was employed to identify clinical risk factors. Diagnostic performance was evaluated using the area under the receiver operating characteristics curve (AUC-ROC), the area under the precision-recall curve (AUC-PR), and the calibration error (cal-error). Additionally, a power analysis was conducted to determine the required sample size. Results: The results suggested a significantly higher fraction of impeded diffusion (FID) originating from IDF-DWI in MVI-positive HCCs (p < 0.001). Moreover, the ADC was found to be significantly lower in MVI-positive HCCs (p = 0.019). Independent risk factors of MVI included larger tumor size and elevated alpha-fetoprotein (AFP) levels. The nomogram model incorporating ADC, FID, tumor size, and AFP level yielded the highest diagnostic accuracy for MVI (AUC-PR = 0.804, AUC-ROC = 0.783, cal-error = 0.044), followed by FID (AUC-PR = 0.693, AUC-ROC = 0.760, cal-error = 0.060) and ADC (AUC-PR = 0.570, AUC-ROC = 0.651, cal-error = 0.164). Conclusion: IDF-DWI shows great potential in noninvasively, accurately, and preoperatively detecting MVI in HCC and may offer clinical benefits for prognostic prediction and determination of treatment strategy. [ABSTRACT FROM AUTHOR]

Objectives: Habitat imaging allows for the quantification and visualization of various subregions within the tumor. We aim to develop an approach using diffusion-weighted imaging (DWI)–based habitat imaging for preoperatively predicting the microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Methods: Sixty-five patients were prospectively included and underwent multi-b DWI examinations. Based on the true diffusion coefficient (Dt), perfusion fraction (f), and mean kurtosis coefficient (MK), which respectively characterize cellular density, perfusion, and heterogeneity, the HCCs were divided into four habitats. The volume fraction of each habitat was quantified. The logistic regression was used to explore the risk factors from habitat fraction and clinical variables. Clinical, habitat, and nomogram models were constructed using the identified risk factors from clinical characteristics, habitat fraction, and their combination, respectively. The diagnostic accuracy was evaluated using the area under the receiver operating characteristic curves (AUCs). Results: MVI-positive HCC exhibited a significantly higher fraction of habitat 4 (f4) and a significantly lower fraction of habitat 2 (f2) (p < 0.001), which were selected as risk factors. Additionally, tumor size and elevated alpha-fetoprotein (AFP) were also included as risk factors for MVI. The nomogram model demonstrated the highest diagnostic performance (AUC = 0.807), followed by the habitat model (AUC = 0.777) and the clinical model (AUC = 0.708). Decision curve analysis indicated that the nomogram model offered more net benefit in identifying MVI compared to the clinical model. Conclusions: DWI-based habitat imaging shows clinical potential for noninvasively and preoperatively determining the MVI of HCC with high accuracy. Clinical relevance statement: The proposed strategy, diffusion-weighted imaging–based habitat imaging, can be applied for preoperatively and noninvasively identifying microvascular invasion in hepatocellular carcinoma, which offers potential benefits in terms of prognostic prediction and clinical management. Key Points: • This study proposed a strategy of DWI-based habitat imaging for hepatocellular carcinoma. • The habitat imaging–derived metrics can serve as diagnostic markers for identifying the microvascular invasion. • Integrating the habitat-based metric and clinical variable, a predictive nomogram was constructed and displayed high accuracy for predicting microvascular invasion. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: Varying diffusion curvature (VDC) MRI is an emerging diffusion-weighted imaging (DWI) technique that can capture non-Gaussian diffusion behavior and reflect tissue heterogeneity. However, its clinical utility has hardly been evaluated. We aimed to investigate the value of the VDC technique in noninvasively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: 74 patients with HCCs, including 39 MVI-positive and 35 MVI-negative HCCs were included into this prospective study. Quantitative metrics between subgroups, clinical risk factors, as well as diagnostic performance were evaluated. The power analysis was also carried out to determine the statistical power. Results: MVI-positive HCCs exhibited significantly higher VDC-derived structural heterogeneity measure, D1 (0.680 ± 0.100 × 10–3 vs 0.572 ± 0.148 × 10–3 mm2/s, p = 0.001) and lower apparent diffusion coefficient (ADC) (1.350 ± 0.166 × 10–3 vs 1.471 ± 0.322 × 10–3 mm2/s, p = 0.0495) compared to MVI-negative HCCs. No statistical significance was observed for VDC-derived diffusion coefficient, D0 between the subgroups (p = 0.562). Tumor size (odds ratio (OR) = 1.242) and alpha-fetoprotein (AFP) (OR = 2.527) were identified as risk factors for MVI. A predictive nomogram was constructed based on D1, ADC, tumor size, and AFP, which exhibited the highest diagnostic accuracy (AUC = 0.817), followed by D1 (AUC = 0.753) and ADC (AUC = 0.647). The diagnostic performance of the nomogram-based model was also validated by the calibration curve and decision curve. Conclusion: VDC can aid in the noninvasive and preoperative diagnosis of HCC with MVI, which may result in the clinical benefit in terms of prognostic prediction and clinical decision-making. [ABSTRACT FROM AUTHOR]

Background & Aims: We aimed to develop a Transformer‐based deep learning (DL) network for prognostic stratification in hepatocellular carcinoma (HCC) patients undergoing RFA. Methods: A Swin Transformer DL network was trained to establish associations between magnetic resonance imaging (MRI) datasets and the ground truth of microvascular invasion (MVI) based on 696 surgical resection (SR) patients with solitary HCC ≤3 cm, and was validated in an external cohort (n = 180). The multiphase MRI‐based DL risk outputs using an optimal threshold of.5 was employed as a MVI classifier for prognosis stratification in the RFA cohort (n = 180). Results: Over 90% of all enrolled patients exhibited hepatitis B virus infection. Liver cirrhosis was significantly more prevalent in the RFA cohort compared to the SR cohort (72.2% vs. 44.1%, p <.001). The MVI risk outputs exhibited good performance (area under the curve values =.938 and.883) for predicting MVI in the training and validation cohort, respectively. The RFA patients at high risk of MVI classified by the MVI classifier demonstrated significantly lower recurrence‐free survival (RFS) and overall survival rates at 1, 3 and 5 years compared to those classified as low risk (p <.001). Multivariate cox regression modelling of a‐fetoprotein > 20 ng/mL [hazard ratio (HR) = 1.53; 95% confidence interval (95% CI): 1.02–2.33, p =.047], high risk of MVI (HR = 3.76; 95% CI: 2.40–5.88, p <.001) and unfavourable tumour location (HR = 2.15; 95% CI: 1.40–3.29, p =.001) yielded a c‐index of.731 (bootstrapped 95% CI:.667–.778) for evaluating RFS after RFA. Among the three risk factors, MVI was the most powerful predictor for intrahepatic distance recurrence. Conclusions: The proposed MVI classifier can serve as a valuable imaging biomarker for prognostic stratification in early‐stage HCC patients undergoing RFA. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Aims: To assess the different imaging characteristics between corticosteroid‐sensitive (CS) and corticosteroid‐refractory (CR) immune checkpoint inhibitor‐associated myocarditis (ICIaM) with cardiac magnetic resonance (CMR) and the potential CMR parameters in the early detection of CR ICIaM. Methods and results: Thirty‐five patients diagnosed with ICIaM and 30 age and gender‐matched cancer patients without a history of ICI treatment were enrolled. CMR with contrast was performed within 2 days of clinical suspicion. Left ventricular ejection fraction (LVEF) and late gadolinium enhancement (LGE) were assessed by CMR. LV sub‐endocardial (GLSendo) and sub‐epicardial (GLSepi) global longitudinal strains were quantified by offline feature tracking analysis. CS and CR ICIaM were defined based on the trend of Troponin I and clinical course during corticosteroid treatment. All 35 patients presented with non‐fulminant symptoms upon initial assessment. Twenty patients (57.14%) were sensitive, and 15 (42.86%) were refractory to corticosteroids. Compared with controls, 22 patients (62.86%) with ICIaM developed LGE. LVEF decreased in CR ICIaM compared with the CS group and controls. GLSendo (−14.61 ± 2.67 vs. −18.50 ± 2.53, P < 0.001) and GLSepi (−14.75 ± 2.53 vs. −16.68 ± 2.05, P < 0.001) significantly increased in patients with CR ICIaM compared with the CS ICIaM. In patients with CS ICIaM, although GLSepi (−16.68 ± 2.05 vs. −19.31 ± 1.80, P < 0.001) was impaired compared with the controls, GLSendo was preserved. There was no difference in CMR parameters between LGE‐positive and negative groups. LVEF, GLSendo, and GLSepi were predictors of CR ICIaM. When LVEF, GLSendo, and GLSepi were included in multivariate analysis, only GLSendo remained an independent predictor of CR ICIaM (OR: 2.170, 95% CI: 1.189–3.962, P = 0.012). A GLSendo of ≥−17.10% (sensitivity, 86.7%; specificity, 80.0%; AUC, 0.860; P < 0.001) could predict CR ICIaM in the ICIaM cohort. Kaplan–Meier analysis showed that in patients with impaired GLSendo of ≥−17.10%, cardiovascular adverse events (CAEs) occurred much earlier than in patients with preserved GLSendo of <−17.10% (Log‐rank test P = 0.017). Conclusions: CR and CS ICIaM demonstrated different functional and morphological characteristics in different myocardial layers. An impaired GLSendo could be a helpful parameter in early identifying corticosteroid‐refractory individuals in the ICIaM population. [ABSTRACT FROM AUTHOR]

Background: The diagnosis of intrahepatic cholangiocarcinoma (iCCA) is challenging in hepatitis B virus (HBV)‐infected patients, due to the overlapping clinical manifestations and atypical imaging patterns compared to patients without HBV. Purpose: To investigate the preoperative imaging characteristics of iCCA in patients with HBV in comparison to those without HBV. Study Type: Retrospective. Subjects: 431 patients with histopathologically confirmed iCCA (143 HBV‐positive and 288 HBV‐negative patients) were retrospectively enrolled from three institutes, and patients were allocated to the training (n = 302) and validation (n = 129) cohorts from different institutes or time period; 100 matching HBV‐positive hepatocellular carcinoma (HCC) patients were also enrolled. Field Strength/Sequence: 1.5‐T and 3‐T, including T1‐ and T2‐weighted, diffusion‐weighted and dynamic gadopentetate dimeglumine‐enhanced imaging. Assessment: Clinical and MRI features were analyzed and compared between HBV‐positive and HBV‐negative patients with iCCA, and between HBV‐positive patients with iCCA and HCC. Statistical Tests: Univariate and multivariate logistic regression analyses with odds ratio (OR) to identify independent features for discriminating HBV‐associated iCCA. Diagnostic model generation by incorporating independent features, and the performance for discrimination was evaluated by receiver operating characteristics with the area under the curve (AUC) and 95% confidence interval (CI). AUCs were compared by the DeLong's method. A P‐value <0.05 was considered statistically significant. Results: Compared to patients without HBV, washout or degressive enhancement pattern (OR = 51.837), well‐defined tumor margin (OR = 8.758) and no peritumoral bile duct dilation (OR = 4.651) were independent significant features for discriminating HBV‐associated iCCAs. All these features were also the predominant MRI manifestations for HBV‐associated HCC. The combined index showed an AUC of 0.798 (95% CI 0.748–0.842) in the training cohort and an AUC of 0.789 (95% CI 0.708–0.856) in the validation cohort for discrimination. The sensitivity, specificity, and accuracy were all >70%, which was superior to each single feature alone in both cohorts. [Correction added after first online publication on 29 June 2023. The Field Strength/Sequence has been updated from 5‐T to 1.5‐T.] Data Conclusion: Preoperative MRI may help to discriminate HBV‐associated iCCA. Evidence Level: 3 Technical Efficacy Stage: 2 [ABSTRACT FROM AUTHOR]

Objectives: To establish a non-invasive diagnostic system for intrahepatic mass-forming cholangiocarcinoma (IMCC) via decision tree analysis. Methods: Totally 1008 patients with 504 pathologically confirmed IMCCs and proportional hepatocellular carcinomas (HCC) and combined hepatocellular cholangiocarcinomas (cHCC-CC) from multi-centers were retrospectively included (internal cohort n = 700, external cohort n = 308). Univariate and multivariate logistic regression analyses were applied to evaluate the independent clinical and MRI predictors for IMCC, and the selected features were used to develop a decision tree–based diagnostic system. Diagnostic efficacy of the established system was calculated by the receiver operating characteristic curve analysis in the internal training-testing and external validation cohorts, and also in small lesions ≤ 3 cm. Results: Multivariate analysis revealed that female, no chronic liver disease or cirrhosis, elevated carbohydrate antigen 19–9 (CA19-9) level, normal alpha-fetoprotein (AFP) level, lobulated tumor shape, progressive or persistent enhancement pattern, no enhancing tumor capsule, targetoid appearance, and liver surface retraction were independent characteristics favoring the diagnosis of IMCC over HCC or cHCC-CC (odds ratio = 3.273–25.00, p < 0.001 to p = 0.021). Among which enhancement pattern had the highest weight of 0.816. The diagnostic system incorporating significant characteristics above showed excellent performance in the internal training (area under the curve (AUC) 0.971), internal testing (AUC 0.956), and external validation (AUC 0.945) cohorts, as well as in small lesions ≤ 3 cm (AUC 0.956). Conclusions: In consideration of the great generalizability and clinical efficacy in multi-centers, the proposed diagnostic system may serve as a non-invasive, reliable, and easy-to-operate tool in IMCC diagnosis, providing an efficient approach to discriminate IMCC from other HCC-containing primary liver cancers. Clinical relevance statement: This study established a non-invasive, easy-to-operate, and explainable decision tree–based diagnostic system for intrahepatic mass-forming cholangiocarcinoma, which may provide essential information for clinical decision-making. Key Points: • Distinguishing intrahepatic mass-forming cholangiocarcinoma (IMCC) from other primary liver cancers is important for both treatment planning and outcome prediction. • The MRI-based diagnostic system showed great performance with satisfying generalization ability in the diagnosis and discrimination of IMCC. • The diagnostic system may serve as a non-invasive, easy-to-operate, and explainable tool in the diagnosis and risk stratification for IMCC. [ABSTRACT FROM AUTHOR]

Background: The assessment of tumor response to neoadjuvant chemotherapy (NACT) in locally advanced gastric cancer (LAGC) remain challenging. We aimed to explore the potential role of peri-NACT change of the largest lymph node (LN) and primary tumor (P-T) in the prediction of tumor response and patient overall survival (OS) in LAGC. Methods: A cohort of LAGC patients who underwent NACT followed by radical surgery from a prospective clinical trial were retrospectively analyzed. The percentage change of the largest LN and P-T from initial to post-NACT Computed Tomography (CT) were measured. Tumor response was defined by the change of LN (LN-response) and P-T (P-T-response), respectively. A multivariate Cox model was constructed to examine if P-T- and LN-determined response had significant predictive ability for OS when adjusting with other possible prognostic factors. Results: Of the 41 patients, 28 (68.3%) was defined as LN-responders to NACT, and 17 (41.5%) patients was defined as P-T-responders. When the cohort was stratified by LN response standard, LN-responders showed a significant longer median OS than LN-nonresponders (p = 0.031, 20.6 vs 16.6 months). When stratified by primary tumor response, no significant difference in OS was observed between P-T-responders and P-T-nonresponders (p = 0.377, 18.5 vs 19.0 months). In the multivariate analysis, number of positive LN (p = 0.004, hazard ratio [HR] = 1.284), recurrence (p = 0.024, HR =3556), LN shrinkage (p = 0.022, HR = 0.930) and LN-response (p = 0.033, HR = 0.008) were observed with independent association with OS. Conclusions: Peri-NACT change of the largest LN could reflect tumor response to NACT, and LN-defined response was useful in predicting the long-term prognosis (OS) of LAGC patients who underwent NACT followed by radical surgery. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The 10th Global Forum for Liver Magnetic Resonance Imaging (MRI) was held as a virtual 2-day meeting in October 2021, attended by delegates from North and South America, Asia, Australia, and Europe. Most delegates were radiologists with experience in liver MRI, with representation also from specialists in liver surgery, oncology, and hepatology. Presentations, discussions, and working groups at the Forum focused on the following themes: • Gadoxetic acid in clinical practice: Eastern and Western perspectives on current uses and challenges in hepatocellular carcinoma (HCC) screening/surveillance, diagnosis, and management • Economics and outcomes of HCC imaging • Radiomics, artificial intelligence (AI) and deep learning (DL) applications of MRI in HCC. These themes are the subject of the current manuscript. A second manuscript discusses multidisciplinary tumor board perspectives: how to approach early-, mid-, and late-stage HCC management from the perspectives of a liver surgeon, interventional radiologist, and oncologist (Taouli et al, 2023). Delegates voted on consensus statements that were developed by working groups on these meeting themes. A consensus was considered to be reached if at least 80% of the voting delegates agreed on the statements. Clinical relevance statement: This review highlights the clinical applications of gadoxetic acid–enhanced MRI for liver cancer screening and diagnosis, as well as its cost-effectiveness and the applications of radiomics and AI in patients with liver cancer. Key Points: • Interpretation of gadoxetic acid–enhanced MRI differs slightly between Eastern and Western guidelines, reflecting different regional requirements for sensitivity vs specificity. • Emerging data are encouraging for the cost-effectiveness of gadoxetic acid–enhanced MRI in HCC screening and diagnosis, but more studies are required. • Radiomics and artificial intelligence are likely, in the future, to contribute to the detection, staging, assessment of treatment response and prediction of prognosis of HCC—reducing the burden on radiologists and other specialists and supporting timely and targeted treatment for patients. [ABSTRACT FROM AUTHOR]

The 10th Global Forum for Liver Magnetic Resonance Imaging was held in October 2021. The themes of the presentations and discussions at this Forum are described in detail in the review by Taouli et al (2023). The focus of this second manuscript developed from the Forum is on multidisciplinary tumor board perspectives in hepatocellular carcinoma (HCC) management: how to approach early-, mid-, and late-stage management from the perspectives of a liver surgeon, an interventional radiologist, and an oncologist. The manuscript also includes a panel discussion by multidisciplinary experts on three selected cases that explore challenging aspects of HCC management. Clinical relevance statement: This review highlights the importance of a multidisciplinary team approach in liver cancer patients and includes the perspectives of a liver surgeon, an interventional radiologist, and an oncologist, including illustrative case studies. Key Points: • A liver surgeon, interventional radiologist, and oncologist presented their perspectives on the treatment of early-, mid-, and late-stage HCC. • Different perspectives on HCC management between specialties emphasize the importance of multidisciplinary tumor boards. • A multidisciplinary faculty discussed challenging aspects of HCC management, as highlighted by three case studies. [ABSTRACT FROM AUTHOR]

Background: Intrahepatic cholangiocarcinoma (iCCA) is an aggressive primary liver cancer with dismal outcome, high Ki-67 expression is associated with active progression and poor prognosis of iCCA, the application of MRE in the prediction of iCCA Ki-67 expression has not yet been investigated until now. We aimed to evaluate the value of magnetic resonance elastography (MRE) in assessing Ki-67 expression for iCCA. Results: In the whole cohort, 97 patients (57 high Ki-67 and 40 low Ki-67; 58 males, 39 females; mean age, 58.89 years, ranges 36–70 years) were included. At the multivariate analysis, tumor stiffness (odds ratio (OR) = 1.669 [95% CI: 1.307–2.131], p < 0.001) and tumor apparent diffusion coefficient (ADC) (OR = 0.030 [95% CI: 0.002, 0.476], p = 0.013) were independent significant variables associated with Ki-67. Areas under the curve of tumor stiffness for the identification of high Ki-67 were 0.796 (95% CI 0.702, 0.871). Tumor stiffness was moderately correlated with Ki-67 level (r = 0.593, p < 0.001). When both predictive variables of tumor stiffness and ADC were integrated, the best performance was achieved with area under the curve values of 0.864 (95% CI 0.780–0.926). Conclusion: MRE-based tumor stiffness correlated with Ki-67 in iCCA and could be investigated as a potential prognostic biomarker. The combined model incorporating both tumor stiffness and ADC increased the predictive performance. Critical relevance statement: MRE-based tumor stiffness might be a surrogate imaging biomarker to predict Ki-67 expression in intrahepatic cholangiocarcinoma patients, reflecting tumor cellular proliferation. The combined model incorporating both tumor stiffness and apparent diffusion coefficient increased the predictive performance. Key points: • MRE-based tumor stiffness shows a significant correlation with Ki-67. • The combined model incorporating tumor stiffness and apparent diffusion coefficient demonstrated an optimized predictive performance for Ki-67 expression. • MRE-based tumor stiffness could be investigated as a potential prognostic biomarker for intrahepatic cholangiocarcinoma. [ABSTRACT FROM AUTHOR]

Background: The clinical application of coronary MR angiography (MRA) combining diastole and systole imaging has never been described comprehensively in coronary artery disease (CAD) patients. We aimed to design an optimal non-contrast coronary MRA scan protocol combining diastolic and systolic imaging and to (1) evaluate its diagnostic performance for detecting significant coronary stenosis; (2) evaluate the feasibility of this protocol to noninvasively measure the coronary distensibility index (CDI). Methods: From June 2021 to May 2022, 33 healthy volunteers and 91 suspected CAD patients scheduled for X-ray coronary angiography (CAG) were prospectively enrolled. 3T non-contrast water-fat coronary MRA was carried out twice at diastole and systole. Significant coronary stenosis was defined as a luminal diameter reduction of ≥ 50% using CAG as the reference and was evaluated as follows: (1) by coronary MRA in diastole alone; (2) by coronary MRA in systole alone; (3) by combined coronary MRA in diastole and systole. According to CAG, the patients were divided into significant CAD patients and non-significant CAD patients. The difference in CDI among participants was evaluated. Results: Combined coronary MRA was completed in 31 volunteers and 76 patients. The per-patient sensitivity, specificity, and accuracy of combined coronary MRA were 97.5%, 83.3%, and 90.8%, respectively. Compared with single diastolic mode, combined coronary MRA showed equally high sensitivity but improved specificity on a per-patient basis (83.3% vs. 63.9%, adjusted P = 0.013). The CDI tested by coronary MRA decreased incrementally from healthy volunteers to non-significant and significant CAD patients. Conclusion: Compared with single-phase mode, 3 T non-contrast combined coronary MRA significantly improved specificity and may have potential to be a simple noninvasive method to measure CDI. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Most solid tumors show increased interstitial fluid pressure (IFP), and this increased IFP is an obstacle to treatment. A noninvasive model for measuring IFP in hepatocellular carcinoma (HCC) is an unresolved issue. Purpose: To develop a noninvasive model to measure IFP and interstitial fluid velocity (IFV) in HCC and to characterize the microvascular invasion (MVI) status by using this model. Study Type: Retrospective. Population: A total of 97 HCC patients (mean age 57.6 ± 10.9 years, 77.3% males), 53 of them with MVI and 44 of them without MVI. Field Strength/Sequence: A 3‐T, three‐dimensional spoiled gradient‐recalled echo. Assessment: MVI was defined as microscopic vascular invasion of small vessels within the peritumoral liver tissue. The volumes of interest (VOIs) were manually delineated and enclosed the tumor lesion and healthy liver parenchyma, respectively. The extended Tofts model (ETM) was used to estimate permeability parameters from all the VOIs. Subsequently, the continuity partial differential equation (PDE) was implemented and IFP and IFV were acquired. Statistical Tests: Wilcoxon signed‐ranks tests, histogram analysis, Mann–Whitney U test, Fisher's exact test, least absolute shrinkage and selection operator (LASSO) logistic regression, receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC), Youden index, DeLong test, and Benjamini–Hochberg correction. A P value <0.05 was considered statistically significant. Results: The HCC lesions exhibited elevated IFP and reduced IFV. There were no significant differences in any measured demographic and clinical features between the MVI‐positive and MVI‐negative groups, except for tumor size. Nine IFP histogram analysis‐derived parameters and seven IFV histogram analysis‐derived parameters could be used to characterize the MVI status. LASSO regression selected five features: IFP maximum, IFP 10th percentile, IFP 90th percentile, IFV SD, and IFV 10th percentile. The combination of these features showed the highest AUC (0.781) and specificity (77.3%). Data Conclusion: A noninvasive IFP and IFV measurement model for HCC was developed. Specific IFP‐ and IFV‐derived parameters exhibited significant association with the MVI status. Evidence Level: 3. Technical Efficacy: Stage 2. [ABSTRACT FROM AUTHOR]

Background: The Armed Forces Institute of Pathology (AFIP) had higher accuracy and reliability in prognostic assessment and treatment strategies for patients with gastric stromal tumors (GSTs). The AFIP classification is frequently used in clinical applications. But the risk classification is only available for patients who are previously untreated and received complete resection. We aimed to investigate the feasibility of multi-slice MSCT features of GSTs in predicting AFIP risk classification preoperatively. Methods: The clinical data and MSCT features of 424 patients with solitary GSTs were retrospectively reviewed. According to pathological AFIP risk criteria, 424 GSTs were divided into a low-risk group (n = 282), a moderate-risk group (n = 72), and a high-risk group (n = 70). The clinical data and MSCT features of GSTs were compared among the three groups. Those variables (p < 0.05) in the univariate analysis were included in the multivariate analysis. The nomogram was created using the rms package. Results: We found significant differences in the tumor location, morphology, necrosis, ulceration, growth pattern, feeding artery, vascular-like enhancement, fat-positive signs around GSTs, CT value in the venous phase, CT value increment in the venous phase, longest diameter, and maximum short diameter (all p < 0.05). Two nomogram models were successfully constructed to predict the risk of GSTs. Low- vs. high-risk group: the independent risk factors of high-risk GSTs included the location, ulceration, and longest diameter. The area under the receiver operating characteristic curve (AUC) of the prediction model was 0.911 (95% CI: 0.872–0.951), and the sensitivity and specificity were 80.0% and 89.0%, respectively. Moderate- vs. high-risk group: the morphology, necrosis, and feeding artery were independent risk factors of a high risk of GSTs, with an AUC value of 0.826 (95% CI: 0.759–0.893), and the sensitivity and specificity were 85.7% and 70.8%, respectively. Conclusions: The MSCT features of GSTs and the nomogram model have great practical value in predicting pathological AFIP risk classification between high-risk and non-high-risk groups before surgery. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the image quality of reduced field-of-view (rFOV) DWI for abdominal imaging at 5.0 Tesla (T) compared with 3.0 T. Methods: Fifteen volunteers were included into this prospective study. All the subjects underwent the 3.0 T and 5.0 T MR examinations (time interval: 2 ± 1.9 days). Free-breathing (FB), respiratory-triggered (RT), and navigator-triggered (NT) spin-echo echo-planner imaging-based rFOV-DWI examinations were conducted at 3.0 T and 5.0 T (FB3.0 T, NT3.0 T, RT3.0 T, FB5.0 T, NT5.0 T, and RT5.0 T) with two b values (b = 0 and 800 s/mm2), respectively. The signal-to-noise ratio (SNR) of different acquisition approaches were determined and statistically compared. The image quality was assessed and statistically compared with a 5-point scoring system. Results: The SNRs of any 5.0 T DWI images were significantly higher than those of any 3.0 T DWI images for same anatomic locations. Moreover, 5.0 T rFOV-DWIs had the significantly higher sharpness scores than 3.0 T rFOV-DWIs. Similar distortion scores were observed at both 3.0 T and 5.0 T. Finally, RT5.0 T displayed the best overall image quality followed by NT5.0 T, FB5.0 T, RT3.0 T, NT3.0 T and FB3.0 T (RT5.0 T = 3.9 ± 0.3, NT5.0 T = 3.8 ± 0.3, FB5.0 T = 3.4 ± 0.3, RT3.0 T = 3.2 ± 0.4, NT3.0 T = 3.1 ± 0.4, and FB3.0 T = 2.7 ± 0.4, p < 0.001). Conclusion: The 5.0 T rFOV-DWI showed better overall image quality and improved SNR compared to 3.0 T rFOV-DWI, which holds clinical potential for identifying the abdominal abnormalities in routine practice. Critical relevance statement: This study provided evidence that abdominal 5.0 Tesla reduced field of view diffusion-weighted imaging (5.0 T rFOV-DWI) exhibited enhanced image quality and higher SNR compared to its 3.0 Tesla counterparts, holding clinical promise for accurately visualizing abdominal abnormalities. Key points: • rFOV-DWI was firstly integrated with high-field-MRI for visualizing various abdominal organs. • This study indicated the feasibility of abdominal 5.0 T-rFOV-DWI. • Better image quality was identified for 5.0 T rFOV-DWI. [ABSTRACT FROM AUTHOR]

Purpose: Characterizing the composition of hepatocellular carcinoma (HCC) and peritumoral micro-environment may provide sensitive biomarkers. We aimed to predict the recurrence-free survival (RFS) of HCC (≤ 5 cm) with habitat imaging of HCC and its peritumoral micro-environment. Material and Methods: A total of 264 patients with HCC were included. Taking advantage of the enhancement ratio at the arterial and hepatobiliary phase of contrast-enhanced MRI, all HCCs and their peritumoral tissue of 3 mm and 4 mm were encoded with different habitats. Besides, the quantitative fraction of each habitat of HCC and peritumoral tissue were calculated. Univariable and multivariable Cox regression analysis was performed to select the prognostic factors. The nomogram-based predictor was established. Kaplan–Meier analysis was conducted to stratify the recurrence risk. Fivefold cross-validation was performed to determine the predictive performance with the concordance index (C-Index). Decision curve analysis was used to evaluate the net benefit. Results: Qualitatively, the spatial distribution of the habitats varied for different survival outcomes. Quantitatively, the fraction of habitat 3 in peritumoral tissue of 4 mm (f3-P4) was selected as independent risk factors (OR = 89.2, 95% CI = 14.5–549.2, p < 0.001) together with other two clinical variables. Integrating both clinical variables and f3-P4, a nomogram was constructed and showed high predictive efficacy (C-Index: 0.735, 95% CI 0.617–0.854) and extra net benefit according to the decision curve. Furthermore, patients with low f3-P4 or risk score given by nomogram have far longer RFS than those with high f3-P4 or risk score (stratification by f3-P4: 131.9 vs 55.0 months and stratification by risk score:131.9 vs 34.1 months). Conclusion: Habitat imaging of HCC and peritumoral microenvironment can be used for effectively and non-invasively estimating the RFS, which holds potential in guiding clinical management and decision making. [ABSTRACT FROM AUTHOR]

Purpose: To characterize the magnetic resonance imaging features of primary intrahepatic lymphoepithelioma-like cholangiocarcinoma (LELCC). Materials and Methods: Thirty-four patients with 38 histologically confirmed LELCCs were enrolled retrospectively from January 2014 to August 2022. We evaluated the clinical features, histologic findings, and imaging manifestations on dynamic enhanced MRI. Results: 74% (25/34) of the cases were associated with EBV infection. Moreover, patients infected with EBV exhibited a lower level of Ki-67 proliferation. The serum CA199 level was elevated in 10 patients. The median tumor diameter was 2.8 cm (range, 1.1–8.7 cm). Most tumors were well-defined with a smooth or lobulated margin and showed peripheral hyperintensity and central hypointensity on T2-weighted imaging (T2WI). T2 hyperintense foci were recognized in 8 patients. In the dynamic enhanced MRI, 21 tumors demonstrated Type A enhancement pattern (rim enhancement), 10 demonstrated Type B (rapid wash-in and wash-out), and seven demonstrated Type C (rapid wash-in without wash-out). Capsular enhancement in PVP or DP was found in 22 tumors. A few patients had satellite lesions, portal vein thrombosis, bile duct dilatation, and distal metastasis. Lymph node metastases were discovered pathologically in 11 patients. Conclusions: MRI findings of LELCC vary and are non-specific. While a majority of LELCCs exhibit typical features of intrahepatic cholangiocarcinoma (iCCA), unique findings like T2 hyperintense foci or capsular enhancement could suggest LELCC. EBV infection and elevated tumor markers can aid in differentiation. However, given the mimics of some cases of liver hypervascular lesions, histological examination remains essential for definitive diagnosis. [ABSTRACT FROM AUTHOR]

Background: Primary liver cancer, of which around 75–85% is hepatocellular carcinoma in China, is the fourth most common malignancy and the second leading cause of tumor-related death, thereby posing a significant threat to the life and health of the Chinese people. Summary: Since the publication of Guidelines for Diagnosis and Treatment of Primary Liver Cancer in China in June 2017, which were updated by the National Health Commission in December 2019, additional high-quality evidence has emerged from researchers worldwide regarding the diagnosis, staging, and treatment of liver cancer, that requires the guidelines to be updated again. The new edition (2022 Edition) was written by more than 100 experts in the field of liver cancer in China, which not only reflects the real-world situation in China but also may reshape the nationwide diagnosis and treatment of liver cancer. Key Messages: The new guideline aims to encourage the implementation of evidence-based practice and improve the national average 5-year survival rate for patients with liver cancer, as proposed in the "Health China 2030 Blueprint." [ABSTRACT FROM AUTHOR]

Purpose: To investigate the significance of the predominant component of combined hepatocellular-cholangiocarcinoma (cHCC-CC) in terms of MRI manifestation and its potential prognostic value compared to hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). Materials and methods: A total of 300 patients with chronic liver disease from two centers were retrospectively enrolled, including 100 surgically proven cases of cHCC-CC, HCC, and ICC each. Univariate and multivariate regression analyses were performed to identify independent predictors for distinguishing HCC-predominant cHCC-CC and ICC-predominant cHCC-CC from HCC and ICC, respectively. Diagnostic models were constructed based on the independent features. Recurrence-free survival (RFS) was estimated and compared between groups. Results: The predominant component was an independent predictor for RFS in cHCC-CC (hazard ratio = 1.957, P = 0.044). The presence of targetoid appearance (odds ratio(OR) = 10.907, P = 0.001), lack of enhancing capsule (OR = 0.072, P = 0.001) and arterial peritumoral enhancement (OR = 0.091, P = 0.003) were independent predictors suggestive of HCC-predominant cHCC-CC over HCC; their combination yielded an area under the curve of 0.756. No significant differences were observed in RFS between HCC-predominant cHCC-CC and HCC (P = 0.864). Male gender (OR = 4.049, P = 0.015), higher alpha fetoprotein (OR = 16.789, P < 0.001) and normal carbohydrate antigen 19–9 (OR = 0.343, P = 0.036) levels, presence of enhancing capsule (OR = 7.819, P < 0.001) and hemorrhage (OR = 23.526, P = 0.004), and lack of targetoid appearance (OR = 0.129, P = 0.005) and liver surface retraction (OR = 0.190, P = 0.021) were independent predictors suggestive of ICC-predominant cHCC-CC over ICC; their combination yielded an area under the curve value of 0.898. ICC-predominant cHCC-CC exhibited poorer survival with shorter RFS than ICC (P = 0.009). Conclusion: The predominant histopathological component is closely related to the imaging manifestation of cHCC-CC; and more importantly, it plays a significant prognostic role, which may alter the RFS prognosis of cHCC-CC. [ABSTRACT FROM AUTHOR]

Background: Microvascular invasion (MVI) is a well‐established poor prognostic factor for hepatocellular carcinoma (HCC). Preoperative prediction of MVI is important for both therapeutic and prognostic purposes, but noninvasive methods are lacking. Purpose: To develop an MR elastography (MRE)‐based nomogram for the preoperative prediction of MVI in HCC. Study Type: Prospective. Subjects: A total of 111 patients with surgically resected single HCC (52 MVI‐positive and 59 MVI‐negative), randomly allocated to training and validation cohorts (7:3 ratio). Field Strength/Sequence: 2D‐MRE and conventional sequences (T1‐weighted in‐phase and opposed phase gradient echo, T2‐weighted fast spin echo, diffusion‐weighted single‐shot spin echo echo‐planar, and dynamic contrast‐enhanced T1‐weighted gradient echo) at 3.0 T. Assessment: MRE‐stiffness and conventional qualitative and quantitative MRI features were evaluated and compared between MVI‐positive and MVI‐negative HCCs. Statistical Tests: Univariable and multivariable logistic regression analyses were applied to identify potential predictors for MVI, and a nomogram was constructed according to the predictive model. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance. Harrell's C‐index evaluated the discrimination performance of the nomogram, calibration curves analyzed its diagnostic performance and decision curve analysis determined its clinical usefulness. A P value <0.05 was considered statistically significant. Results: Tumor stiffness >6.284 kPa (odds ratio [OR] = 24.38) and the presence of arterial peritumoral enhancement (OR = 6.36) were independent variables associated with MVI. The areas under the ROC curves for tumor stiffness were 0.81 (95% confidence interval [CI]: 0.70, 0.89) and 0.77 (95% CI: 0.60, 0.90) in the training and validation cohorts, respectively. When both predictive variables were integrated, the best nomogram performance was achieved with C‐indices of 0.88 (95% CI: 0.78, 0.94) and 0.87 (95% CI: 0.71, 0.96) in the two cohorts, fitting well in calibration curves. The decision curve exhibited optimal net benefit with a wide range of threshold probabilities for the nomogram. Data Conclusion: An MRE‐based nomogram may be a potential noninvasive imaging biomarker for predicting MVI of HCC preoperatively. Evidence Level: 2. Technical Efficacy: Stage 2. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the diagnostic value of functional MRI to assess renal interstitial fibrosis in patients with chronic kidney disease (CKD). Methods: We prospectively recruited 80 CKD patients who underwent renal biopsies and 16 healthy volunteers to undergo multiparametric functional MRI examinations. The Oxford MEST-C classification was used to score the interstitial fibrosis. The diagnostic performance of functional MRI to discriminate interstitial fibrosis was evaluated by calculating the area under the receiver operating characteristic (ROC) curves. Results: IgA nephropathy (60%) accounted for the majority of pathologic type in the CKD patients. Apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) was correlated with interstitial fibrosis (rho = −0.73). Decreased renal blood flow (RBF) derived from arterial spin labeling (rho = −0.78) and decreased perfusion fraction (f) derived from DWI (rho = −0.70) were accompanied by increased interstitial fibrosis. The T1 value from T1 mapping correlated with interstitial fibrosis (rho = 0.67) (all p < 0.01). The areas under the ROC curve for the discrimination of ≤ 25% vs. > 25% and ≤ 50% vs. > 50% interstitial fibrosis were 0.87 (95% confidence interval, 0.78 to 0.94) and 0.93 (0.86 to 0.98) by ADC, 0.84 (0.74 to 0.91) and 0.94 (0.86 to 0.98) by f, 0.93 (0.85 to 0.98) and 0.90 (0.82 to 0.96) by RBF, and 0.91 (0.83 to 0.96) and 0.77 (0.66 to 0.85) by T1, respectively. Conclusions: Functional MRI parameters were strongly correlated with the interstitial fibrosis of CKD. Therefore, it might a powerful tool to assess interstitial fibrosis of CKD noninvasively. Key Points: • In CKD patients, the renal cortical ADC value decreased and T1 value increased significantly compared with healthy volunteers. • Functional MRI revealed significantly decreased renal perfusion in CKD patients compared with healthy volunteers. • The renal cortical ADC, f, RBF, and T1 values were strongly correlated with the interstitial fibrosis of CKD. [ABSTRACT FROM AUTHOR]

Background: Satisfactory magnetic resonance imaging (MRI) of those patients with involuntary head motion due to brain diseases is essential in avoiding missed diagnosis and guiding treatment. Purpose: To investigate the clinical feasibility of artificial intelligence-assisted compressed sensing single-shot fluid-attenuated inversion recovery (ACS-SS-FLAIR) in evaluating patients with involuntary head motion due to brain diseases, compared with the conventional T2-FLAIR with parallel imaging (PI-FLAIR). Material and Methods: A total of 33 uncooperative patients with brain disease were prospectively enrolled. Two readers independently reviewed images acquired with ACS-SS-FLAIR and PI-FLAIR at a 3.0-T MR scanner. In the aspects of qualitative evaluation of image quality, overall image quality and lesion conspicuity of ACS-SS-FLAIR and PI-FLAIR were assessed and then statistically compared by paired Wilcoxon rank-sum test. For quantitative evaluation, the relative contrast of lesion-to-cerebral parenchyma were calculated and compared. Results: Overall image quality scores of ACS-SS-FLAIR evaluated by two readers were 2.94 ± 0.24 and 2.91 ± 0.29, respectively, both of which were significantly higher than that of PI-FLAIR, respectively (P < 0.001 and <0.001). Lesion conspicuity scores of were 2.74 ± 0.47 and 2.79 ± 0.44, both of which were significantly higher than that of PI-FLAIR, respectively (P < 0.001 and <0.001). In the quantitative evaluation for image quality, the relative contrast of lesion-to-cerebral parenchyma was 0.34 ± 0.09 in the ACS-SS-FLAIR sequence, significantly larger than that in the PI-FLAIR sequence (P = 0.001). Conclusion: The ACS-SS-FLAIR sequence is clinically feasible in the MRI workup of those patients with involuntary head motion due to brain diseases, showing shorter image acquisition time and better image quality compared with conventional PI-FLAIR. [ABSTRACT FROM AUTHOR]

Aim: To investigate associations between MRI features and high-frequency mutations of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Methods: This study included 58 HCC patients who underwent contrast-enhanced MRI prior to surgical resection and genome sequencing. MRI features and mutation information were evaluated. Results: The top five most frequently mutated genes in HCC were TP53 (53.45%), TAF1 (24.14%), PDE4DIP (22.41%), ABCA13 (18.97%) and LRP1B (17.24%). Mutations in TP53 and LRP1B were associated with tumor necrosis (p = 0.035) and mosaic architecture (p = 0.015), respectively. Mutations in ABCA13 were associated with mosaic architecture (p = 0.025) and necrosis (p = 0.010). Conclusion: This preliminary radiogenomics analysis showed associations between MRI features and high-frequency mutations in HBV-related HCCs. Radiogenomics has been helpful for disease prevention, diagnosis, treatment, prognosis and drug development, and has shown good prospects in gene function analysis and gene therapy research. Some studies have explored the relationship between the underlying genotype and MRI features. However, few studies have indicated the relationship between the underlying genotype and MRI features of hepatocellular carcinoma (HCC) so far. In this study, the top five most frequently mutated genes in hepatitis B virus-related HCCs were TP53, TAF1, PDE4DIP, ABCA13 and LRP1B and certain associations existed between MRI features and high-frequency mutations. These results demonstrated the potential clinical value of imaging traits as surrogate markers of molecular portraits in HCC. The potential correlations between MRI features and high-frequency mutations may provide effective clinical information for hepatitis B virus-related HCCs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objectives: To prospectively investigate the capability of arterial spin labeling (ASL) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for the identification of early kidney injury in chronic kidney disease (CKD) patients with normal estimated glomerular filtration rate (eGFR). Methods: Fifty-four CKD patients confirmed by renal biopsy (normal eGFR group [eGFR ≥ 90 mL/min/1.73 m2]: n = 26; abnormal eGFR group [eGFR < 90 mL/min/1.73 m2]: n = 28) and 20 healthy volunteers (HV) were recruited. All subjects were examined by IVIM-DWI and ASL imaging. Renal blood flow (RBF) derived from ASL, true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) derived from IVIM-DWI were measured from the renal cortex. One-way analysis of variance was used to compare MRI parameters among the three groups. The correlation between eGFR and MRI parameters was evaluated by Spearman correlation analysis. Diagnostic performances of MRI parameters for detecting kidney injury were assessed by receiver operating characteristic (ROC) curves. Results: The renal cortical D, D*, f, and RBF values showed statistically significant differences among the three groups. eGFR was positively correlated with MRI parameters (D: r = 0.299, D*: r = 0.569, f: r = 0.733, RBF: r = 0.586). The areas under the curve (AUCs) for discriminating CKD patients from HV were 0.725, 0.752, 0.947, and 0.884 by D, D*, f, and RBF, respectively. D, D*, f, RBF, and eGFR identified CKD patients with normal eGFR with AUCs of 0.735, 0.612, 0.917, 0.827, and 0.733, respectively, and AUC of f value was significantly larger than that of eGFR. Conclusion: IVIM-DWI and ASL were useful for detecting underlying pathologic injury in early CKD patients with normal eGFR. Key Points: • The renal cortical f and RBF values in the control group were significantly higher than those in the normal eGFR group. • A negative correlation was observed between the renal cortical D, D*, f, and RBF values and SCr and 24 h-UPRO, while eGFR was significantly positively correlated with renal cortical D, D*, f, and RBF values. • The AUC of renal cortical f values was statistically larger than that of eGFR for the discrimination between the CKD with normal eGFR group and the control group. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Purpose: Incidence and mortality of intrahepatic cholangiocarcinoma (ICC) have been increasing over the past few decades, and Ki67 is an adverse prognostic predictor and an attractive therapeutic target for ICC patients. Thus, we aim to develop and validate a combined Ki67 prediction model for ICC patients. Materials and methods: Preoperative contrast-enhanced MR images were collected from 178 patients with postoperative pathologically confirmed ICC, and randomly divided into training and validation cohorts in a ratio of 7:3 (124:54). A time-independent test cohort of 49 ICC patients was used for validation. Independent clinicoradiological features of Ki67 status were determined by multivariate analysis. Optimal radiomics features were selected by least absolute shrinkage and selection operator logistic regression and linear discriminant analysis was used to construct combined models. The prediction efficacy of combined model was assessed by receiver operating characteristics curve, and verified by its calibration, decision and clinical impact curves. Results: HBV (p = 0.022), arterial rim enhancement (p = 0.006) and enhancement pattern (p = 0.012) are independent clinicoradiological features. The radiomics model achieves good prediction efficacy in the training cohort (AUC = 0.860) and validation cohort (AUC = 0.843). The combined Ki67 prediction model incorporates clinicoradiological and radiomics features, and it yields desirable predictive efficiency in test cohort (AUC = 0.815). Decision curves and clinical impact curves further validate that the combined Ki67 prediction model can achieve net benefits in clinical work. Conclusion: The combined Ki67 model incorporating HBV, arterial rim enhancement, enhancement pattern and radiomics features is a potential biomarker in Ki67 prediction and stratification. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Consensus report from the 10th Global Forum for Liver Magnetic Resonance Imaging: developments in HCC management." The authors of the article have decided to make it an Open Access publication under a Creative Commons Attribution 4.0 International License. The copyright of the article has been changed to © The Authors 2023. The document also includes information about obtaining permission for the use of third-party material. The publisher, Springer Nature, remains neutral regarding jurisdictional claims and institutional affiliations. [Extracted from the article]

Lung cancer is the leading cause of cancer-related death in many countries, and an accurate histopathological diagnosis is of great importance in subsequent treatment. The aim of this study was to establish the random forest (RF) model based on radiomic features to automatically classify and predict lung adenocarcinoma (ADC), lung squamous cell carcinoma (SCC), and small cell lung cancer (SCLC) on unenhanced computed tomography (CT) images. Eight hundred and fifty-two patients (mean age: 61.4, range: 29–87, male/female: 536/316) with preoperative unenhanced CT and postoperative histopathologically confirmed primary lung cancers, including 525 patients with ADC, 161 patients with SCC, and 166 patients with SCLC, were included in this retrospective study. Radiomic features were extracted, selected, and then used to establish the RF classification model to analyse and classify primary lung cancers into three subtypes, including ADC, SCC, and SCLC according to histopathological results. The training (446 ADC, 137 SCC, and 141 SCLC) and testing cohorts (79 ADC, 24 SCC, and 25 SCLC) accounted for 85% and 15% of the whole datasets, respectively. The prediction performance of the RF classification model was evaluated by F1 scores and the receiver operating characteristic (ROC) curve. On the testing cohort, the areas under the ROC curve (AUC) of the RF model in classifying ADC, SCC, and SCLC were 0.74, 0.77, and 0.88, respectively. The F1 scores achieved 0.80, 0.40, and 0.73 in ADC, SCC, and SCLC, respectively, and the weighted average F1 score was 0.71. In addition, for the RF classification model, the precisions were 0.72, 0.64, and 0.70; the recalls were 0.86, 0.29, and 0.76; and the specificities were 0.55, 0.96, and 0.92 in ADC, SCC, and SCLC. The primary lung cancers were feasibly and effectively classified into ADC, SCC, and SCLC based on the combination of RF classification model and radiomic features, which has the potential for noninvasive predicting histological subtypes of primary lung cancers. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to explore the feasibility of pancreatic imaging at 5 T and evaluate the practical improvement of T2‐weighted MRI and diffusion‐weighted imaging (DWI) at 5 T as compared with 3 T. Methods: Eighteen healthy subjects were recruited for this pilot study. MRI examinations were performed using 3 and 5 T scanners. MRI sequences included T2‐weighted fast spin‐echo and DWI with reduced field‐of‐view. Subjective image analysis using a four‐point Likert scale was performed by two experienced radiologists. The SNR, contrast ratio, and apparent diffusion coefficient (ADC) were measured in the pancreatic head, body, and tail. The coefficient of variation (CV) of the ADC was calculated. A series of paired Wilcoxon tests were used to compare the subjective image quality, mean ADC value, and CV of ADC between the 3 and 5 T measurements. p <0.05 was considered statistically significant. Results: For T2‐weighted images, there were no significant differences in image quality ratings between 3 and 5 T. On DWI images (b = 0 and 800 s/mm2), the image quality ratings were significantly higher at 5 T than at 3 T. The SNRs of both T2‐weighted and DWI images were significantly higher at 5 T. There was no significant difference in the mean ADC values and CV of ADC between 3 and 5 T. Conclusion: This initial study proved that 5 T MRI can be used to acquire pancreatic images with higher SNR and sufficient image quality compared to 3 T MRI. [ABSTRACT FROM AUTHOR]

To evaluate the prognostic value of aortic distensibility measured by cardiovascular magnetic resonance (CMR) as predictors of prophylactic aortic valve or aortic surgery in patients with bicuspid aortic valve (BAV). 110 patients with BAV were included. Distensibility of middle ascending aorta (AscAo) and proximal descending aorta (DescAo) at baseline was determined using CMR. The association between aortic distensibility and primary endpoint of aortic valve and/or aortic surgery was investigated with Cox proportional hazard regression analyses. The receiver operating characteristics curves (ROC) of the area under receiver-operator (AUC) and DeLong test were used to evaluate and compare the performance of different models. During a median follow-up of 66.5 months [IQR 13–75 months], 42 patients experienced surgical treatments. After adjusting for traditional risk factors, aortic distensibility (P = 0.003) and severe valve dysfunction (P < 0.001) were found significantly associated with aortic valve and/or aortic surgery. The model 2 (aortic distensibility and severe valve dysfunction) is slightly better in predicting primary endpoint than the model 1 (aortic diameter and severe valve dysfunction) (AUC: 0.893 vs. 0.842, P = 0.106). In BAV patients, aortic distensibility and severe valve dysfunction are valuable predictors for final aortic valve and/or aortic surgery. [ABSTRACT FROM AUTHOR]

Background: Most intrahepatic cholangiocarcinomas (ICCs) are diagnosed at advanced stage with an extremely poor prognosis. For these patients, combining targeted therapies and immunotherapy may have a promising therapeutic effect, and current Response Evaluation Criteria in Solid Tumors (RECIST) criteria have limited applicability. Purpose: To investigate the associations between pretreatment MRI features and the efficacy of combined targeted‐immunotherapy by estimating the risk of early progression (EP) in unresectable ICC, with special emphasis on diffusion‐weighted imaging. Study Type: Retrospective. Subjects: A total of 43 unresectable ICC patients (24 with EP [disease progression ≤12 months after treatment] and 19 with nonearly progression [NEP, disease progression >12 months]), who received first‐line systemic therapy with lenvatinib plus PD1 antibody combination. Field Strength/Sequence: The 0‐T scanner, including T1‐ and T2‐weighted imaging, diffusion‐weighted imaging, and dynamic gadopentetate dimeglumine‐enhanced imaging. Assessment: Clinical characteristics and MR imaging features including apparent diffusion coefficient (ADC), as well as survival analysis of EP were evaluated. Statistical Tests: Features between EP and NEP groups were compared by univariate analyses and multivariate logistic regression analysis. Diagnostic performance was analyzed by receiver operating characteristic curve. Univariate and multivariate Cox regression models were applied for survival analysis of EP. The progression‐free survival (PFS) rates were estimated using the Kaplan–Meier analysis and compared by the log‐rank test. The significance threshold was set at P < 0.05. Results: Tumor number, tumor margin, arterial peritumoral enhancement, lymphatic metastasis, and apparent diffusion coefficient (ADC) value were significantly different between EP and NEP groups. At multivariate logistic regression analysis, ADC was the only independent variable associated with EP (odds ratio = 0.012), with an area under the curve of 0.774 (optimal cutoff value was 1.028 × 10−3 mm2/sec). Multivariate Cox regression model proved that ADC value (hazard ratio = 0.140) and ill‐defined margin (hazard ratio = 2.784) were independent risk factors. ICCs with low ADC values showed shorter PFS than those with high values (χ2 = 9.368). Data Conclusion: Pretreatment MRI features were associated with EP for unresectable ICC treated with combined targeted‐immunotherapy, and decreased ADC value was an independent variable. Evidence Level: 3 Technical Efficacy: Stage 4 [ABSTRACT FROM AUTHOR]

Background: The overall survival for patients with resectable PDAC following curative surgical resection hasn’t been improved significantly, as a considerable proportion of patients develop recurrence within a year. The purpose of this study was to develop and validate a predictive model to assess recurrence risk in patients with PDAC after upfront surgery by using preoperative clinical data and CT characteristics. Methods: The predictive model was developed based on a retrospective set of 141 pancreatic cancer patients after surgery. A separate set of 77 patients was used to validate model. Between January 2017 and December 2019, all patients underwent multidetector pancreatic CT and upfront surgery. Univariable and multivariate Cox regression was used to determine the risk factors related to recurrence and then establish a nomogram to estimate the 1-year recurrence probability. The Harrell C-index was employed in evaluating the discrimination and calibration of the model. Results: A total of 218 patients in this retrospective cohort. A recurrence model in nomogram form was developed with predictors including tumor size (hazard ratio [HR], 1.277; 95% CI 1.098, 1.495; P = 0.002), tumor density in the portal vein phase (HR, 0.598; 95% CI 0.424, 0.844; P = 0.003), peripancreatic infiltration (HR, 4.151; 95% CI 2.077, 8.298; P < 0.001), suspicious metastatic lymph node (HR, 2.561; 95% CI 1.653, 3.967; P < 0.001), Neutrophils/Lymphocytes ratio (HR, 1.111; 95% CI 1.016, 1.215; P = 0.020). The predictive nomogram had good discrimination capability with these predictors with an area under curve at 1 year of 0.84 (95%CI 0.77, 0.91) in the development set and 0.82 (95% CI 0.72, 0.92) and 0.84 (95% CI 0.74, 0.94) in the validation set for two radiologists reading respectively. Conclusions: The model developed based on preoperative clinical data and CT characteristics of resectable pancreatic ductal adenocarcinoma patients, which can helpfully estimate the recurrence-free survival. It may be a useful tool for clinician to select optimal candidates for upfront surgery or neoadjuvant therapy. [ABSTRACT FROM AUTHOR]

Objective: To investigate the feasibility and accuracy of applying a computed tomography (CT) texture analysis model trained with deep‐learning reconstruction images to iterative reconstruction images for classifying pulmonary nodules. Materials and methods: CT images of 102 patients, with a total of 118 pulmonary nodules (52 benign, 66 malignant) were retrospectively reconstructed with a deep‐learning reconstruction (artificial intelligence iterative reconstruction [AIIR]) and a hybrid iterative reconstruction (HIR) technique. The AIIR data were divided into a training (n = 96) and a validation set (n = 22), and the HIR data were set as the test set (n = 118). Extracted texture features were compared using the Mann‐Whitney U test and t‐test. The diagnostic performance of the classification model was analyzed with the receiver operating characteristic curve (ROC), the area under ROC (AUC), sensitivity, specificity, and accuracy. Results: Among the obtained 68 texture features, 51 (75.0%) were not influenced by the change of reconstruction algorithm (p > 0.05). Forty‐four features were significantly different between benign and malignant nodules (p < 0.05) for the AIIR dataset, which were selected to build the classification model. The accuracy and AUC of the classification model were 92.3% and 0.91 (95% confidence interval [CI], 0.74−0.90) with the validation set, which were 80.0% and 0.80 (95% CI, 0.68−0.86) with the test set. Conclusion: With the CT texture analysis model trained with deep‐learning reconstruction (AIIR) images showing favorable diagnostic accuracy in discriminating benign and malignant pulmonary nodules, it also has certain applicability to the iterative reconstruction (HIR) images. [ABSTRACT FROM AUTHOR]

Background: Assessment of microvascular invasion (MVI) in intrahepatic cholangiocarcinoma (ICC) by using a noninvasive method is an unresolved issue. Deep learning (DL) methods based on multiparametric fusion of MR images have the potential of preoperative assessment of MVI. Purpose: To investigate whether a multiparametric fusion DL model based on MR images can be used for preoperative assessment of MVI in ICC. Study type: Retrospective. Population: A total of 519 patients (200 females and 319 males) with a single ICC were categorized as a training (n = 361), validation (n = 90), and an external test cohort (n = 68). Field strength/Sequence: A 1.5 T and 3.0 T; axial T2‐weighted turbo spin‐echo sequence, diffusion‐weighted imaging with a single‐shot spin‐echo planar sequence, and dynamic contrast‐enhanced (DCE) imaging with T1‐weighted three‐dimensional quick spoiled gradient echo sequence. Assessment: DL models of multiparametric fusion convolutional neural network (CNN) and late fusion CNN were both constructed for evaluating MVI in ICC. Gradient‐weighted class activation mapping was used for visual interpretation of MVI status in ICC. Statistical Tests: The DL model performance was assessed through the receiver operating characteristic curve (ROC) analysis, and the area under the ROC curve (AUC) with the accuracy, sensitivity, and specificity were measured. P value < 0.05 was considered as statistical significance. Results: In the external test cohort, the proposed multiparametric fusion DL model achieved an AUC of 0.888 with an accuracy of 86.8%, sensitivity of 85.7%, and specificity of 87.0% for evaluating MVI in ICC, and the positive predictive value and negative predictive value were 63.2% and 95.9%, respectively. The late fusion DL model achieved a lower AUC of 0.866, with an accuracy of 83.8%, sensitivity of 78.6%, specificity of 85.2% for evaluating MVI in ICC. Data Conclusion: Our DL model based on multiparametric fusion of MRI achieved a good diagnostic performance in the evaluation of MVI in ICC. Level of Evidence: 3 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Background: Recently, a prototype 5.0 T whole‐body MRI scanner was developed. A 5.0 T diffusion‐weighted imaging (DWI) may help overcome the issues that limit 3.0 T DWI. Purpose: To evaluate the feasibility of 5.0 T high‐field DWI in the upper abdomen and assess the agreement of the apparent diffusion coefficient (ADC) with that from 3.0 T abdominal DWI. Study type: Prospective proof of concept. Population: Nine volunteers (mean ± SD age: 37.3 ± 7.0 years, 8 M), eight healthy and one with liver and kidney cysts. Field strength/Sequence: 3.0 T and 5.0 T; respiratory‐triggered spin‐echo echo‐planar‐imaging (SE‐EPI)‐based DWI sequence. Assessment: Subjective image quality scores. The ADC values in abdominal organs (liver, pancreas, spleen, and kidney) were measured by two observers for evaluating the interobserver and interfield agreement. Statistical Tests: Wilcoxon‐rank sum test, Bland–Altman analysis, intraclass correlation coefficients (ICCs), and coefficients of variation (CVs). Results: The 5.0 T DWI displayed an increase in subjective image quality score compared to 3.0 T DWI without the significant difference (3.0 T DWI: 3.50 ± 0.47, 5.0 T DWI: 3.72 ± 0.42, P = 0.157). Both the interfield and interobserver agreements of ADC values were substantial to excellent (ICCs = 0.640–0.902). For all four upper abdominal organs, there were no significant differences between the ADC values measured by two observers and between the ADC values of 3.0 T and 5.0 T DWI (P = 0.134–1.000). The CVs of ADC measurements from 3.0 T and 5.0 T DWI were all less than 15.0% (6.7%–14.2%). Data Conclusion: The substantial to excellent agreements between the ADC values measured with 3.0 T and 5.0 T DWI for liver, pancreas, spleen, and kidney suggested that 5.0 T DWI can be applied for abdominal imaging. The ADC values from 5.0 T abdominal DWI hold the potential to serve as the quantitative markers for clinical investigations. Evidence Level: 2 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

Objectives: To distinguish MR features according to different proportions of the histopathological hepatocellular carcinoma (HCC) component and to investigate whether the proportion of the HCC component can predict the prognosis of patients with cHCC-CCA.Methods: The study enrolled 106 cHCC-CCA patients confirmed by histopathology. The MR imaging features and clinicopathological findings were retrospectively evaluated and compared between two subgroups with different proportions of the HCC component. The recurrence-free survival (RFS) and overall survival (OS) were evaluated using Kaplan-Meier survival curves and compared using the log-rank test. Moreover, whether the proportion of the HCC component was a predictor of RFS and OS was investigated using Cox regression analyses.Results: The Liver Imaging Reporting and Data System (LI-RADS) category 4/5 was more prevalent in cHCC-CCAs with an HCC component > 50% (odds ratio (OR) = 5.559, p = 0.018), 70% (OR = 4.031, p = 0.008), and 90% (OR = 6.282, p = 0.012) than in those with an HCC component ≤ 50%, 70%, and 90%, respectively. In addition, cHCC-CCAs with an HCC component > 70% (HR: 0.241, p = 0.023) had a better OS prognosis than those with an HCC component ≤ 70%.Conclusions: cHCC-CCAs categorized as LR-4/5 are mainly composed of HCC component, and cHCC-CCAs with an HCC component > 70% are associated with better OS than those with an HCC component ≤ 70%. These findings suggest that the proportion of HCC or CCA component can predict the prognosis of cHCC-CCA patients.Key Points: • cHCC-CCAs categorized as LR-4/5 are mainly composed of HCC component. • cHCC-CCAs with an HCC component > 70% are associated with better OS than those with an HCC component ≤ 70%. [ABSTRACT FROM AUTHOR]

Background: Recently, a whole-body 5 T MRI scanner was developed to open the door of abdominal imaging at high-field strength. This prospective study aimed to evaluate the feasibility of renal imaging at 5 T and compare the image quality, potential artifacts, and contrast ratios with 3 T. Methods: Forty healthy volunteers underwent MRI examination both at 3 T and 5 T. MRI sequences included T1-weighted gradient-echo (GRE), T2-weighted fast spin echo, diffusion-weighted imaging, and multi-echo GRE T2* mapping. Image quality and presence of artifacts were assessed for all sequences using four-point scales. For anatomical imaging, the signal-to-noise ratio (SNR) and contrast ratio (CR) of abdomen organ tissues were calculated. Besides, for functional imaging, the contrast-to-noise ratio of cortex/medulla was calculated. Wilcoxon signed rank-sum test was used to compare the visual evaluation scores and quantitative measurements between 3 and 5 T images. Results: Compared to 3 T examination, T1-weighted sequence at 5 T showed significantly better image quality with higher conspicuity of the renal veins and arteries, and comparable artifacts. Image quality was comparable between both field strengths on T2-weighted images, whereas a significantly higher level of artifacts was observed at 5 T. Besides, 5 T MRI contributed to higher SNR and CR for abdomen organ tissues. For functional imaging, 5 T MRI showed improved corticomedullar discrimination. There was no significant difference between apparent diffusion coefficient of renal at 3 T and 5 T, while 5 T MRI resulted in significantly shorter T2* values in both cortex and medulla. Conclusions: 5 T MRI provides anatomical and functional images of the kidney with sufficient image quality. [ABSTRACT FROM AUTHOR]