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Abstract Background To explore the capability of diffusion-based virtual MR elastography (vMRE) in the preoperative prediction of recurrence in hepatocellular carcinoma (HCC) and to investigate the underlying relevant histopathological characteristics. Methods Between August 2015 and December 2016, patients underwent preoperative MRI examination with a dedicated DWI sequence (b-values: 200,1500 s/mm2) were recruited. The ADC values and diffusion-based virtual shear modulus (μ diff ) of HCCs were calculated and MR morphological features were also analyzed. The Cox proportional hazards model was used to identify the risk factors associated with tumor recurrence. A preoperative radiologic model and postoperative model including pathological features were built to predict tumor recurrence after hepatectomy. Results A total of 87 patients with solitary surgically confirmed HCCs were included in this study. Thirty-five patients (40.2%) were found to have tumor recurrence after hepatectomy. The preoperative model included higher μ diff and corona enhancement, while the postoperative model included higher μ diff , microvascular invasion, and histologic tumor grade. These factors were identified as significant prognostic factors for recurrence-free survival (RFS) (all p 2.325 kPa showed poorer 5-year RFS after hepatectomy than patients with μ diff values ≤ 2.325 kPa (p

Abstract 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. Graphical Abstract

Abstract 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

Summary: Background: Radiology-based prognostic biomarkers play a crucial role in patient counseling, enhancing surveillance, and designing clinical trials effectively. This study aims to assess the predictive significance of preoperative CT-based tumor contour irregularity in determining clinical outcomes among patients with renal cell carcinoma (RCC). Methods: We conducted a retrospective multi-institutional review involving 2218 patients pathologically diagnosed with RCC. The training and internal validation sets included patients at Zhongshan Hospital between January 2009 and August 2019. The external test set comprised patients from the First Affiliated Hospital, Zhejiang University School of Medicine (January 2016 to January 2018), the Xiamen Branch of Zhongshan Hospital (November 2017 to June 2023), and the Cancer Imaging Archive. The contour irregularity degree (CID), quantified as the ratio of irregular cross-sections to the total tumor cross-sections, was analyzed for its prognostic relevance across different subgroups of RCC patients. A novel CID-based scoring system was developed, and its predictive efficacy was evaluated and compared with existing prognostic models. Findings: The CID exhibited significant discriminatory power in predicting overall survival (OS), recurrence-free survival (RFS), and disease-specific survival (DSS) among patients with RCC tumors measuring 3 cm or larger (all p

Abstract 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

Abstract 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

Objective: The objective of this study was to evaluate the clinical feasibility of deep learning reconstruction-accelerated thin-slice single-breath-hold half-Fourier single-shot turbo spin echo imaging (HASTEDL) for detecting pancreatic lesions, in comparison with two conventional T2-weighted imaging sequences: compressed-sensing HASTE (HASTECS) and BLADE. Methods: From March 2022 to January 2023, a total of 63 patients with suspected pancreatic-related disease underwent the HASTEDL, HASTECS, and BLADE sequences were enrolled in this retrospectively study. The acquisition time, the pancreatic lesion conspicuity (LCP), respiratory motion artifact (RMA), main pancreatic duct conspicuity (MPDC), overall image quality (OIQ), signal-to-noise ratio (SNR), and contrast-noise-ratio (CNR) of the pancreatic lesions were compared among the three sequences by two readers. Results: The acquisition time of both HASTEDL and HASTECS was 16 s, which was significantly shorter than that of 102 s for BLADE. In terms of qualitative parameters, Reader 1 and Reader 2 assigned significantly higher scores to the LCP, RMA, MPDC, and OIQ for HASTEDL compared to HASTECS and BLADE sequences; As for the quantitative parameters, the SNR values of the pancreatic head, body, tail, and lesions, the CNR of the pancreatic lesion measured by the two readers were also significantly higher for HASTEDL than for HASTECS and BLADE sequences. Conclusions: Compared to conventional T2WI sequences (HASTECS and BLADE), deep-learning reconstructed HASTE enables thin slice and single-breath-hold acquisition with clinical acceptable image quality for detection of pancreatic lesions.

Objectives: To evaluate radiation exposure, image quality, and diagnostic performance of coronary CT angiography (CCTA) using the invasive coronary angiography (ICA) as the reference standard in patients with irregular heart rhythm on a 0.25 s rotation time, 16 cm coverage, single-beat, CT scanner with AI-assisted motion correction. Methods: CCTA data-sheets of 427 patients using a CT scanner with an ECG monitoring system and motion correction algorithm were collected retrospectively. All the patients were divided into two groups: regular heart rhythm (357 patients) and irregular heart rhythm (70 patients). 22 patients in irregular heart rhythm underwent ICA. Image quality and effective dose in both groups were evaluated and compared. Image quality was evaluated on 5-point scales. The diagnostic performance of CCTA in irregular heart rhythm group was compared with the results of ICA. Results: The image quality in both groups was similar (4.34 ± 0.47 vs 4.37 ± 0.48, p > 0.05). No significant difference was observed in effective dose between two groups (2.7 ± 0.7 vs 2.9 ± 1.3, p > 0.05). The diagnostic accuracy was 90.91% in a patient-based analysis, 96.97% in a vessel-based analysis, and 98.61% in a segment-based analysis. In irregular heart rhythm group, gender was an important factor affecting the number of CCTA scans in a single examination and the radiation dose exposed to the patient. Conclusions: For patients with irregular heart rhythm, a CT scanner with an ECG monitoring system and motion correction algorithm can not only reduce the radiation dose to the same level as patients with normal heart rhythms, but also ensure that the images with high diagnostic accuracy.

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

Abstract 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 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

Background: Primary liver cancer, around 75%–85% are 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 re-shape 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 five-year survival rate for patients with liver cancer, as proposed in the "Health China 2030 Blueprint."

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 Background Epicardial adipose tissue (EAT) is known as an important imaging indicator for cardiovascular risk stratification. The present study aimed to determine whether the EAT volume (EV) and mean EAT attenuation (mEA) measured by non-contrast routine chest CT (RCCT) could be more consistent with those measured by coronary CT angiography (CCTA) by adjusting the threshold of fatty attenuation. Methods In total, 83 subjects who simultaneously underwent CCTA and RCCT were enrolled. EV and mEA were quantified by CCTA using a threshold of (N30) (− 190 HU, − 30 HU) as a reference and measured by RCCT using thresholds of N30, N40 (− 190 HU, − 40 HU), and N45 (− 190 HU, − 45 HU). The correlation and agreement of EAT metrics between the two imaging modalities and differences between patients with coronary plaques (plaque ( +)) and without plaques (plaque ( −)) were analyzed. Results EV obtained from RCCT showed very strong correlation with the reference (r = 0.974, 0.976, 0.972 (N30, N40, N45), P

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 Background T2* cardiovascular magnetic resonance (CMR) is commonly used in the diagnosis of intramyocardial hemorrhage (IMH). For quantifying IMH with T2* CMR, despite the lack of consensus studies, two different methods [subject-specific T2* (ssT2*) and absolute T2* thresholding (aT2*

Abstract Background Intramyocardial hemorrhage (IMH) within myocardial infarction (MI) is associated with major adverse cardiovascular events. Bright-blood T2*-based cardiovascular magnetic resonance (CMR) has emerged as the reference standard for non-invasive IMH detection. Despite this, the dark-blood T2*-based CMR is becoming interchangeably used with bright-blood T2*-weighted CMR in both clinical and preclinical settings for IMH detection. To date however, the relative merits of dark-blood T2*-weighted with respect to bright-blood T2*-weighted CMR for IMH characterization has not been studied. We investigated the diagnostic capacity of dark-blood T2*-weighted CMR against bright-blood T2*-weighted CMR for IMH characterization in clinical and preclinical settings. Materials and methods Hemorrhagic MI patients (n = 20) and canines (n = 11) were imaged in the acute and chronic phases at 1.5 and 3 T with dark- and bright-blood T2*-weighted CMR. Imaging characteristics (Relative signal-to-noise (SNR), Relative contrast-to-noise (CNR), IMH Extent) and diagnostic performance (sensitivity, specificity, accuracy, area-under-the-curve, and inter-observer variability) of dark-blood T2*-weighted CMR for IMH characterization were assessed relative to bright-blood T2*-weighted CMR. Results At both clinical and preclinical settings, compared to bright-blood T2*-weighted CMR, dark-blood T2*-weighted images had significantly lower SNR, CNR and reduced IMH extent (all p

ObjectiveWe aimed to develop a Radiological-Radiomics (R-R) based model for predicting the high-grade pattern (HGP) of lung adenocarcinoma and evaluate its predictive performance.MethodsThe clinical, pathological, and imaging data of 374 patients pathologically confirmed with lung adenocarcinoma (374 lesions in total) were retrospectively analyzed. The 374 lesions were assigned to HGP (n = 81) and non-high-grade pattern (n-HGP, n = 293) groups depending on the presence or absence of high-grade components in pathological findings. The least absolute shrinkage and selection operator (LASSO) method was utilized to screen features on the United Imaging artificial intelligence scientific research platform, and logistic regression models for predicting HGP were constructed, namely, Radiological model, Radiomics model, and R-R model. Also, receiver operating curve (ROC) curves were plotted on the platform, generating corresponding area under the curve (AUC), sensitivity, specificity, and accuracy. Using the platform, nomograms for R-R models were also provided, and calibration curves and decision curves were drawn to evaluate the performance and clinical utility of the model. The statistical differences in the performance of the models were compared by the DeLong test.ResultsThe R-R model for HGP prediction achieved an AUC value of 0.923 (95% CI: 0.891-0.948), a sensitivity of 87.0%, a specificity of 83.4%, and an accuracy of 84.2% in the training set. In the validation set, this model exhibited an AUC value of 0.920 (95% CI: 0.887-0.945), a sensitivity of 87.5%, a specificity of 83.3%, and an accuracy of 84.2%. The DeLong test demonstrated optimal performance of the R-R model among the three models, and decision curves validated the clinical utility of the R-R model.ConclusionIn this study, we developed a fusion model using radiomic features combined with radiological features to predict the high-grade pattern of lung adenocarcinoma, and this model shows excellent diagnostic performance. The R-R model can provide certain guidance for clinical diagnosis and surgical treatment plans, contributing to improving the prognosis of patients.

Abstract Background Multiple guidelines for pancreatic ductal adenocarcinoma (PDAC) suggest that all stages of patients need to receive postoperative adjuvant chemotherapy. S-1 is a recently emerged oral antitumour agent recommended by the guidelines. However, which population would benefit from S-1 needs to be determined, and predictors of chemotherapy response are needed for personalized precision medicine. This pilot study aimed to initially identify whether whole-tumour evaluation with MRI and radiomics features could be used for predicting the efficacy of S-1 and to find potential predictors of the efficacy of S-1 as evidence to assist personalized precision treatment. Methods Forty-six patients with PDAC (31 in the primary cohort and 15 in the validation cohort) who underwent curative resection and subsequently adjuvant chemotherapy with S-1 were included. Pre-operative abdominal contrast-enhanced MRI was performed, and radiomics features of the whole PDAC were extracted from the primary cohort. After univariable analysis and radiomics features selection, a multivariable Cox regression model for survival analysis was subsequently used to select statistically significant factors associated with postoperative disease-free survival (DFS). Predictive capacities of the factors were tested on the validation cohort by using Kaplan–Meier method. Results Multivariable Cox regression analysis identified the probability of T1WI_NGTDM_Strength and tumour location as independent predictors of the efficacy of S-1 for adjuvant chemotherapy of PDAC (p = 0.005 and 0.013) in the primary cohort, with hazard ratios (HRs) of 0.289 and 0.293, respectively. Further survival analysis showed that patients in the low-T1WI_NGTDM_Strength group had shorter DFS (median = 5.1 m) than those in the high-T1WI_NGTDM_Strength group (median = 13.0 m) (p = 0.006), and patients with PDAC on the pancreatic head exhibited shorter DFS (median = 7.0 m) than patients with tumours in other locations (median = 20.0 m) (p = 0.016). In the validation cohort, the difference in DFS between patients with low-T1WI_NGTDM_Strength and high-T1WI_NGTDM_Strength and the difference between patients with PDAC on the pancreatic head and that in other locations were approved, with marginally significant (p = 0.073 and 0.050), respectively. Conclusions Whole-tumour radiomics feature of T1WI_NGTDM_Strength and tumour location were potential predictors of the efficacy of S-1 and for the precision selection of S-1 as adjuvant chemotherapy regimen for PDAC.

PurposeThe aim of this study is to evaluate the performance of free-breathing liver MRI with a novel respiratory frequency-modulated continuous-wave radar-trigger (FT) technique on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) for both healthy volunteers and patients in comparison to navigator-trigger (NT) and belt-trigger (BT) techniques.MethodsIn this prospective study, 17 healthy volunteers and 23 patients with known or suspected liver diseases were enrolled. Six sequences (T2WI and DWI with FT, NT, and BT techniques) were performed in each subject. Quantitative evaluation and qualitative assessment were analyzed by two radiologists. Overall image quality, blurring, motion artifacts, and liver edge delineations were rated on a 4-point Likert scale. The liver and lesion signal-to-noise ratio (SNR), the lesion-to-liver contrast-to-noise ratio (CNR), as well as the apparent diffusion coefficient (ADC) value were quantitatively calculated.ResultsFor volunteers, there were no significant differences in the image quality Likert scores and quantitative parameters on T2WI and DWI with three respiratory-trigger techniques. For patients, NT was superior to other techniques for image quality on T2WI; conversely, little difference was found on DWI in qualitative assessment. The mean SNR of the liver on T2WI and DWI with BT, NT, and FT techniques was similar in patients, which is in line with volunteers. FT performed better in terms of higher SNR (705.13 ± 434.80) and higher CNR (504.41 ± 400.69) on DWI at b50 compared with BT (SNR: 651.83 ± 401.16; CNR:429.24 ± 404.11) and NT (SNR: 639.41 ± 407.98; CNR: 420.64 ± 416.61) (p < 0.05). The mean ADC values of the liver and lesion with different techniques in both volunteers and patients showed non-significant difference.ConclusionFor volunteers, the performance of T2WI as well as DWI with three respiratory-trigger techniques was similarly good. As for patients, FT-DWI is superior to BT and NT techniques in terms of higher lesion SNR and CNR at b50.

Abstract Background Coronary CT angiography (CCTA) is a complicated CT exam in comparison to other CT protocols. Exam success highly depends on image assessment of experienced radiologist and the procedure is often time-consuming. This study aims to evaluate feasibility of automatic CCTA reconstruction in 0.25 s rotation time, 16 cm coverage CT scanner with best phase selection and AI-assisted motion correction. Methods CCTA exams of 90 patients with heart rates higher than 75 bpm were included in this study. Two image series were reconstructed—one at automatically selected phase and another with additional motion correction. All reconstructions were performed without manual interaction of radiologist. A four-point Likert scale rating system was used to evaluate the image quality of coronary artery segment by two experienced radiologists, according to the 18-segment model. Analysis was done on per-segment basis. Results Total 1194 out of the 1620 segments were identified for quality evaluation in 90 patients. After automatic best phase selection, 1172 segments (98.3%) were rated as having diagnostic image quality (scores 2–4) and the average score is 3.64 ± 0.55. When motion corrections were applied, diagnostic segment number increases to 1192 (99.8%) and the average score is 3.85 ± 0.37. Conclusions With the help of 0.25 s rotation speed, 16-cm z-coverage and AI-assisted motion correction algorithm, CCTA exam reconstruction could be performed with minimum radiologist involvement and still meet image quality requirement.

Background: Primary liver cancer, around 90% are 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 (2017 Edition) in 2018, additional high-quality evidence has emerged with relevance to the diagnosis, staging, and treatment of liver cancer in and outside China that requires the guidelines to be updated. The new edition (2019 Edition) was written by more than 70 experts in the field of liver cancer in China. They reflect the real-world situation in China regarding diagnosing and treating liver cancer in recent years. Key Messages: Most importantly, the new guidelines were endorsed and promulgated by the Bureau of Medical Administration of the National Health Commission of the People’s Republic of China in December 2019.

BackgroundIntrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer with increasing incidence in the last decades. Microvascular invasion (MVI) is a poor prognostic factor for patients with ICC, which correlates early recurrence and poor prognosis, and it can affect the selection of personalized therapeutic regime.PurposeThis study aimed to develop and validate a radiomics-based nomogram for predicting MVI in ICC patients preoperatively.MethodsA total of 163 pathologically confirmed ICC patients (training cohort: n = 130; validation cohort: n = 33) with postoperative Ga-DTPA-enhanced MR examination were enrolled, and a time-independent test cohort (n = 24) was collected for external validation. Univariate and multivariate analyses were used to determine the independent predictors of MVI status, which were then incorporated into the MVI prediction nomogram. Least absolute shrinkage and selection operator logistic regression was performed to select optimal features and construct radiomics models. The prediction performances of models were assessed by receiver operating characteristic (ROC) curve analysis. The performance of the MVI prediction nomogram was evaluated by its calibration, discrimination, and clinical utility.ResultsLarger tumor size (p = 0.003) and intrahepatic duct dilatation (p = 0.002) are independent predictors of MVI. The final radiomics model shows desirable and stable prediction performance in the training cohort (AUC = 0.950), validation cohort (AUC = 0.883), and test cohort (AUC = 0.812). The MVI prediction nomogram incorporates tumor size, intrahepatic duct dilatation, and the final radiomics model and achieves excellent predictive efficacy in training cohort (AUC = 0.953), validation cohort (AUC = 0.861), and test cohort (AUC = 0.819), fitting well in calibration curves (p > 0.05). Decision curve and clinical impact curve further confirm the clinical usefulness of the nomogram.ConclusionThe nomogram incorporating tumor size, intrahepatic duct dilatation, and the final radiomics model is a potential biomarker for preoperative prediction of the MVI status in ICC patients.

Abstract Background The presence of microvascular invasion (MVI) in intrahepatic cholangiocarcinoma (ICC) is a significant adverse prognostic factor. This study sought to investigate the correlation between preoperative imaging parameters and MVI in ICC. Methods A total of 108 patients with surgically resected single ICC tumors (34 MVI-positive and 74 MVI-negative lesions) who underwent MRI examination, including T1WI, T2WI, DWI, and dynamic enhancement imaging, were enrolled in this retrospective study. The following qualitative and quantitative characteristics were evaluated: tumor morphology, signal features on T1WI and T2WI, intrahepatic duct dilatation, hepatic capsule retraction, target sign on DWI, dynamic enhancement pattern, arterial phase enhancement pattern, dot−/band-like enhancement inside the tumor, visible vessel penetration inside the tumor (hepatic artery, portal vein, or hepatic vein), integrity of the enhancement edge of the arterial phase, peripheral hepatic enhancement, tumor size, maximum enhancement edge thickness, arterial edge enhancement ratio, and delayed phase enhancement ratio. Other clinicopathological features were also used to predict and evaluate MVI in ICC. Chi-square test, Fisher’s exact test, and independent t-test were used for univariate analysis to determine the relationships among the presence of MVI and these MR parameters. Logistic regression analysis was used to identify predictors of MVI among these MR parameters. Results Among MRI characteristics, tumor morphology, intrahepatic duct dilatation, arterial phase enhancement pattern, visible hepatic artery penetration sign, maximum diameter of the tumor and the arterial phase edge enhancement ratio were correlated with MVI (P = 0.007, 0.003, 0.008, 0.000, 0.003, and 0.002, respectively). Furthermore, higher CA19–9 levels (≥37 U/ml) and pathological tumor grade III were also related to MVI (P = 0.014 and 0.004, respectively). However, multivariate logistic regression analysis demonstrated that none of the parameters were independent risk factors for the diagnosis of MVI in ICCs. Conclusion For the preoperative prediction of MVI in ICC, six qualitative and quantitative data obtained on preoperative MRI, as well as one tumorigenic marker and the pathological tumor grade, were statistically significant. More research is needed to identify MR characteristics that can be used as independent risk factors.

ObjectiveThis study aims to develop and externally validate a contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics-based model for preoperative differentiation between fat-poor angiomyolipoma (fp-AML) and hepatocellular carcinoma (HCC) in patients with noncirrhotic livers and to compare the diagnostic performance with that of two radiologists.MethodsThis retrospective study was performed with 165 patients with noncirrhotic livers from three medical centers. The dataset was divided into a training cohort (n = 99), a time-independent internal validation cohort (n = 24) from one center, and an external validation cohort (n = 42) from the remaining two centers. The volumes of interest were contoured on the arterial phase (AP) images and then registered to the venous phase (VP) and delayed phase (DP), and a total of 3,396 radiomics features were extracted from the three phases. After the joint mutual information maximization feature selection procedure, four radiomics logistic regression classifiers, including the AP model, VP model, DP model, and combined model, were built. The area under the receiver operating characteristic curve (AUC), diagnostic accuracy, sensitivity, and specificity of each radiomics model and those of two radiologists were evaluated and compared.ResultsThe AUCs of the combined model reached 0.789 (95%CI, 0.579–0.999) in the internal validation cohort and 0.730 (95%CI, 0.563–0.896) in the external validation cohort, higher than the AP model (AUCs, 0.711 and 0.638) and significantly higher than the VP model (AUCs, 0.594 and 0.610) and the DP model (AUCs, 0.547 and 0.538). The diagnostic accuracy, sensitivity, and specificity of the combined model were 0.708, 0.625, and 0.750 in the internal validation cohort and 0.619, 0.786, and 0.536 in the external validation cohort, respectively. The AUCs for the two radiologists were 0.656 and 0.594 in the internal validation cohort and 0.643 and 0.500 in the external validation cohort. The AUCs of the combined model surpassed those of the two radiologists and were significantly higher than that of the junior one in both validation cohorts.ConclusionsThe proposed radiomics model based on triple-phase CE-MRI images was proven to be useful for differentiating between fp-AML and HCC and yielded comparable or better performance than two radiologists in different centers, with different scanners and different scanning parameters.

Abstract Purpose The goal of this study was to investigate the Liver Imaging Reporting and Data System (LI-RADS) v.2017 for the categorization of hepatocellular carcinomas (HCCs) with gadoxetic acid compared with gadopentetate dimeglumine-enhanced 1.5-T magnetic resonance imaging (MRI). Material and methods We included 141 high-risk patients with 145 pathologically-confirmed HCCs who first underwent gadopentetate dimeglumine-enhanced 1.5-T followed by gadoxetic acid-enhanced 1.5-T MRI. Two independent radiologists evaluated the presence or absence of major HCC features and assigned LI-RADS categories after considering ancillary features on both MRIs. Finally, the sensitivity of LI-RADS category 5 (LR-5) and the frequencies of major HCC features were compared between gadoxetic acid- and gadopentetate dimeglumine-enhanced 1.5-T MRI using the Wilcoxon test. Results The sensitivity of LR-5 for diagnosing HCCs was significantly different between gadoxetic acid- and gadopentetate dimeglumine-enhanced MRI (73.8% [107/145] vs 26.2% [38/145], P

Background We assessed the clinical presentations, biomarkers, and Gd-EOB-DTPA-enhanced MRI features that were associated with oxaliplatin-induced sinusoidal obstruction syndrome (SOS) to detect chemotherapy-associated SOS in a timely manner. Methods Fifty-seven patients who underwent oxaliplatin-based chemotherapy and Gd-EOB-DTPA-enhanced MRI were included. Post-oxaliplatin heterogeneity in liver parenchyma was scored on a grading scale of 0 to 3. Abnormal clinical findings, including splenomegaly, hepatomegaly, gall bladder wall thickening, and hepatic vein narrowing, were also assessed. Additionally, alanine transaminase (ALT) levels, aspartate aminotransferase (AST) levels, and platelet counts were measured. Results For SOS, 21 patients were scored grade 0, 24 were grade 1, seven were grade 2, and five were grade 3. Hepatomegaly, splenomegaly, gall bladder wall thickening, and hepatic vein narrowing were significantly correlated with the grade for non-tumorous hepatic parenchymal heterogeneity. For laboratory findings, ALT and AST levels, the AST-to-platelet ratio index score, and platelet counts were significantly associated with a high grade (≥2) of non-tumorous hepatic parenchymal heterogeneity. Conclusions We assessed the clinical presentations, biomarkers, and Gd-EOB-DTPA-enhanced MRI features that were associated with oxaliplatin-induced sinusoidal obstruction syndrome (SOS) to detect chemotherapy-associated SOS in a timely manner. Additionally, specific laboratory findings were significantly associated with a high grade (≥2).

Abstract We describe multi-institutional experience using free-breathing, 3D Spiral GRAPPA-based quantitative perfusion MRI in characterizing neoplastic liver masses. 45 patients (age: 48–72 years) were prospectively recruited at University Hospitals, Cleveland, USA on a 3 Tesla (T) MRI, and at Zhongshan Hospital, Shanghai, China on a 1.5 T MRI. Contrast-enhanced volumetric T1-weighted images were acquired and a dual-input single-compartment model used to derive arterial fraction (AF), distribution volume (DV) and mean transit time (MTT) for the lesions and normal parenchyma. The measurements were compared using two-tailed Student’s t-test, with Bonferroni correction applied for multiple-comparison testing. 28 hepatocellular carcinoma (HCC) and 17 metastatic lesions were evaluated. No significant difference was noted in perfusion parameters of normal liver parenchyma and neoplastic masses at two centers (p = 0.62 for AF, 0.015 for DV, 0.42 for MTT for HCC, p = 0.13 for AF, 0.97 for DV, 0.78 for MTT for metastases). There was statistically significant difference in AF, DV, and MTT of metastases and AF and DV of HCC compared to normal liver parenchyma (p

Microvascular invasion (MVI) is a critical risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). Preknowledge of MVI would assist tailored surgery planning in HCC management. In this multicenter study, we aimed to explore the validity of deep learning (DL) in MVI prediction using two imaging modalities—contrast-enhanced computed tomography (CE-CT) and gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI). A total of 750 HCCs were enrolled from five Chinese tertiary hospitals. Retrospective CE-CT (n = 306, collected between March, 2013 and July, 2019) and EOB-MRI (n = 329, collected between March, 2012 and March, 2019) data were used to train two DL models, respectively. Prospective external validation (n = 115, collected between July, 2015 and February, 2018) was performed to assess the developed models. Furthermore, DL-based attention maps were utilized to visualize high-risk MVI regions. Our findings revealed that the EOB-MRI-based DL model achieved superior prediction outcome to the CE-CT-based DL model (area under receiver operating characteristics curve (AUC): 0.812 vs. 0.736, p = 0.038; sensitivity: 70.4% vs. 57.4%, p = 0.015; specificity: 80.3% vs. 86.9%, p = 0.052). DL attention maps could visualize peritumoral high-risk areas with genuine histopathologic confirmation. Both DL models could stratify high and low-risk groups regarding progression free survival and overall survival (p < 0.05). Thus, DL can be an efficient tool for MVI prediction, and EOB-MRI was proven to be the modality with advantage for MVI assessment than CE-CT.

Background The aim of this study was to assess the feasibility and safety of dynamic volumetric computed tomography angiography (DV‐CTA) for endoleaks detected but not classified by conventional CTA in patients after endovascular aortic repair. Methods and Results From January 2016 to October 2017, 24 patients with endoleaks with aneurysm sac enlargement detected but not classified by conventional CTA were randomly assigned to the conventional CTA group and the DV‐CTA group for further evaluation. The amount of contrast agent, radiation dosage, and changes in creatinine during the operation were compared between the 2 groups. Reintervention was performed according to the endoleak classification followed by the 6‐ and 12‐month follow‐up. The accuracy of classifying endoleaks by DV‐CTA was comparable to that by digital subtraction angiography. Additionally, the total amount of contrast agent and the radiation dosage in the DV‐CTA group during the operation were diminished by 14.0% (P=0.007) and 12.1% (P=0.004), respectively, compared with those in the conventional CTA group. No contrast‐induced nephropathy was observed. All endoleaks were treated instantly after identification. No endoleaks were found in any of the patients during follow‐up. Conclusions DV‐CTA could replace digital subtraction angiography as an alternative method for the classification of endoleaks that cannot be differentiated by conventional CTA. Additionally, the amount of contrast agent and the total radiation dosage were substantially reduced, which improved safety among operators and patients.

Differentiating early-stage Parkinson's disease (PD) from essential tremor (ET) remains challenging. In the current study, we aimed to evaluate whether visual analyses of neuromelanin-sensitive magnetic resonance imaging (NM-MRI) combined with nigrosome-1 (N1) imaging using quantitative susceptibility mapping (QSM) in the substantia nigra (SN) are of diagnostic value in the differentiation of de novo PD from untreated ET. Sixty-eight patients with de novo PD, 25 patients with untreated ET, and 34 control participants underwent NM-MRI and QSM. NM and N1 signals in the SN on MR images were visually evaluated using a 3-point ordinal scale. Receiver operating characteristic (ROC) analyses were performed to determine the diagnostic values of the visual ratings of NM and N1. The diagnostic values of the predicted probabilities were calculated via logistic regression analysis using the combination of NM and N1 visual ratings, as well as their quadratic items. The proportions of invisible NM and invisible N1 were significantly higher in the PD group than those in the ET and control groups (p < 0.001). The sensitivity/specificity for differentiating PD from ET was 0.882/0.800 for NM and 0.794/0.920 for N1, respectively. Combining the two biomarkers, the area under the curve (AUC) of the predicted probabilities was 0.935, and the sensitivity/specificity was 0.853/0.920 when the cutoff value was set to 0.704. Our findings demonstrate that visual analyses combing NM and N1 imaging in the SN may aid in differential diagnosis of PD and ET. Furthermore, our results suggest that patients with PD exhibit larger iron deposits in the SN than those with ET.

Background and objective The aim of this study is to explore the reproducibility of volume-based quantitative measurement of non-small cell lung cancer (NSCLC) perfusion at 64-slice CT. Methods Fourteen patients with proved advanced NSCLC were enrolled in this dynamic first pass volume-based CT perfusion (CTP) study (8×5 mm collimation), and they underwent the second scan within 24 h. According to the longest diameters, those patients were classified to ≤3 cm and >3 cm groups, and each group had 7 patients. Intraclass correlation coefficient (ICC) and Bland-Altman statistics were used to evaluate the reproducibility of CTP imaging. Results In both groups of advanced NSCLC, the reproducibility with BF, BV, and PS values were good (ICC >0.75 for all), but mean transit time (MTT) values. For advanced NSCLC (≤3 cm), repeatability coefficient (RC) values with blood flow (BF), blood volume (BV), MTT and permeability surface area product (PS) values were 56%, 45%, 114%, and 78%, respectively, and the 95% change intervals of RC were -39%-53%, -29%-62%, -83%-145%, and -57%-98%, respectively. For advanced NSCLC (>3 cm), those values were 46%, 30%, 59%, and 33%, respectively, and the 95% change intervals of RC were -48%-45%, -33%-26%, -54%-64%, and -18%-48%. Conclusion There is greater reproducibility of tumor size >3 cm than that of ≤3 cm. BF and BV could be addressed for reliable clinical application in antiangiogenesis therapeutic monitoring with advanced NSCLC patients.

Mesoblastic nephroma (MN) presenting in an adult is extremely rare. The computed tomography (CT) and magnetic resonance imaging (MRI) features of this tumor in adulthood have not been widely reported. We present two additional cases of adult MN and describe the multiphasic contrast-enhanced CT and MRI findings.

Fibroblasts growth factor 21 (FGF21), a liver-secreted endocrine factor involved in regulating glucose and lipid metabolism, has been shown to be elevated in patients with non-alcoholic fatty liver disease (NAFLD). This study aimed to evaluate the quantitative correlation between serum FGF21 level and hepatic fat content.A total of 138 subjects (72 male and 66 female) aged from 18 to 65 years with abnormal glucose metabolism and B-ultrasonography diagnosed fatty liver were enrolled in the study. Serum FGF21 levels were determined by an in-house chemiluminescence immunoassay and hepatic fat contents were measured by proton magnetic resonance spectroscopy.Serum FGF21 increased progressively with the increase of hepatic fat content, but when hepatic fat content increased to the fourth quartile, FGF21 tended to decline. Serum FGF21 concentrations were positively correlated with hepatic fat content especially in subjects with mild/moderate hepatic steatosis (r = 0.276, p = 0.009). Within the range of hepatic steatosis from the first to third quartile, FGF21 was superior to any other traditional clinical markers including ALT to reflect hepatic fat content. When the patients with severe hepatic steatosis (the fourth quartile) were included, the quantitative correlation between FGF21 and hepatic fat content was weakened.Serum FGF21 was a potential biomarker to reflect the hepatic fat content in patients with mild or moderate NAFLD. In severe NAFLD patients, FGF21 concentration might decrease due to liver inflammation or injury.