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Gastric cancer (GC) is one of the most prevalent malignancies of the digestive tract. Ginsenoside Rh1 was reported to exert effects on GC. The current study set out to explore the mechanism underlying Ginsenoside Rh1 effects on GC. With oxaliplatin (OXA) serving as the positive control, human GC cells AGS were treated with 0, 10, 25, 50, 74, or 100 μM of ginsenoside Rh1 for 48 h. Proliferation, migration, invasion, and apoptosis were subsequently assessed by means of MTT, scratch test, Transwell, and TUNEL, respectively. AGS cells were further jointly treated with Rh1 and the TGF-β/Smad pathway activator Kartogenin, followed by detection of TGF-β/Smad pathway effects on AGS biological behaviours. Moreover, TGF-β/Smad pathway activation was detected with a Western blot assay. Furthermore, xenograft tumour models were established and tumour growth was recorded. Ki-67 expression patterns and apoptosis were detected with immunohistochemistry and TUNEL, respectively. In vitro, Ginsenoside Rh1 repressed AGS cell proliferation, migration, and invasion, and further promoted apoptosis, with a concentration of 50 μM Rh1 exerting the equivalent effects as OXA. In vivo, Ginsenoside Rh1 inhibited GC proliferation and induced tumour cell apoptosis. Mechanistically, Ginsenoside Rh1 reduced TGF-β1 and TGF-β2 levels and Smad2 and Smad3 phosphorylation levels. Collectively, our findings highlighted that ginsenoside Rh1 inhibited GC cell growth and tumour growth in xenograft tumour models via inhibition of the TGF-β/Smad pathway.

Purpose: To develop and validate a random forest (RF) based predictive model of early refractoriness to transarterial chemoembolization (TACE) in patients with unresectable hepatocellular carcinoma (HCC). Methods: A total of 227 patients with unresectable HCC who initially treated with TACE from three independent institutions were retrospectively included. Following a random split, 158 patients (70%) were assigned to a training cohort and the remaining 69 patients (30%) were assigned to a validation cohort. The process of variables selection was based on the importance variable scores generated by RF algorithm. A RF predictive model incorporating the selected variables was developed, and five-fold cross-validation was performed. The discrimination and calibration of the RF model were measured by a receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow test. Results: The potential variables selected by RF algorithm for developing predictive model of early TACE refractoriness included patients' age, number of tumors, tumor distribution, platelet count (PLT), and neutrophil-to-lymphocyte ratio (NLR). The results showed that the RF predictive model had good discrimination ability, with an area under curve (AUC) of 0.863 in the training cohort and 0.767 in the validation cohort, respectively. In Hosmer-Lemeshow test, the RF model had a satisfactory calibration with P values of 0.538 and 0.068 in training cohort and validation cohort, respectively. Conclusion: The RF algorithm-based model has a good predictive performance in the prediction of early TACE refractoriness, which may easily be deployed in clinical routine and help to determine the optimal patient of care.

Purpose To investigate whether the iodized oil (Lipiodol, Guerbet Group, Villepinte, France) retention pattern influences the treatment efficacy of combined transarterial Lipiodol injection (TLI) and thermal ablation in patients with hepatocellular carcinoma (HCC). Methods Data of 198 patients (280 HCC lesions), who underwent TLI plus computed tomography (CT)-guided thermal ablation at three separate medical institutions between June 2014 and September 2020, were reviewed and analyzed. The Lipiodol retention pattern was classified as complete or incomplete based on non-enhanced CT at the time of ablation. The primary outcome was local recurrence-free survival (LRFS) for lesions; the secondary outcome was overall survival (OS) for patients. Propensity score matching (PSM) was performed using a caliper width of 0.1 between the two groups. Differences in LRFS and OS between the two groups were compared using the log-rank test. Results A total of 133 lesions exhibited a complete Lipiodol retention pattern, while 147 exhibited an incomplete pattern. After PSM analysis of baseline characteristics of the lesions, 121 pairs of lesions were matched. LRFS was significantly longer for lesions exhibiting complete retention than for those exhibiting incomplete retention (P = 0.030). After PSM analysis of patient baseline characteristics, 74 pairs of patients were matched. There was no significant difference in OS between the two groups (P = 0.456). Conclusion Lipiodol retention patterns may influence the treatment efficacy of combined TLI and thermal ablation for HCC lesions. However, a survival benefit for the Lipiodol retention pattern among HCC patients was not observed and needs further confirmation.

Depression is a common occurrence in patients with Parkinson's disease (PD); however, its pathophysiology is still unclear. This study assessed the association between the integrity of white matter and depressive symptoms in patients with PD. 67 patients with PD were divided into a non-depressed PD group (ndPD, n = 30) and a depressed PD group (dPD, n = 37). The dPD group was further subdivided into a mild-moderately depressed PD (mdPD, n = 22) and a severely depressed PD group (sdPD, n = 15). Tract-Based Spatial Statistics was used to compare fractional anisotropy (FA) between groups. Region-of-interest analysis was used to explore changes in diffusivity indices in the regions showing FA abnormalities. The sdPD patients exhibited significantly reduced FA in the left superior longitudinal fasciculus, uncinate fasciculus, anterior corona radiata, corticospinal tract, and bilateral inferior fronto-occipital fasciculus when compared with the ndPD patients, but the decreased FA was within a smaller area when compared with the mdPD patients. No significant difference in FA was found between the mdPD and ndPD groups. Among the dPD patients, FA values in the left superior longitudinal fasciculus negatively correlated with BDI scores. Impaired white matter integrity in the prefronto-limbic/temporal circuitry, mainly in the left hemisphere, is associated with severe, but not mild-moderate depressive symptoms in patients with PD.

There currently lacks a noninvasive and accurate method to distinguish benign and malignant ovarian lesion prior to treatment. This study developed a deep learning algorithm that distinguishes benign from malignant ovarian lesion by applying a convolutional neural network on routine MR imaging. Five hundred forty-five lesions (379 benign and 166 malignant) from 451 patients from a single institution were divided into training, validation, and testing set in a 7:2:1 ratio. Model performance was compared with four junior and three senior radiologists on the test set. Compared with junior radiologists averaged, the final ensemble model combining MR imaging and clinical variables had a higher test accuracy (0.87 vs 0.64, p

The porous g-C3N4 (PCN) nanosheets are successfully synthesized and further modified with nano-sized Ag by a simple wet-chemical process. Interestingly, the Ag-modified porous g-C3N4 (Ag-PCN) nanosheets exhibit competitive fluorescence detection performance of chloride ion (Cl−) in aqueous solution. Under the optimized conditions, the concentration of Cl− could be quantitative analyzed with the Ag-PCN in a wide detection range from 0.5 mmol/L to 0.1 mol/L, with a low detection limitation of 0.06 mmol/L. It is confirmed that the fluorescence of PCN could be effectively decayed by the photoinduced charge transfer via the adsorbed Cl− for trapping holes, mainly by means of the time-resolved fluorescence and surface photovoltage spectra. The porous structure and modified Ag promote the adsorption of Cl− on resulting Ag-PCN, leading to excellent fluorescence detection for Cl−. This work provides a feasible route to develop a fluorescence detection of Cl− with g-C3N4 nanosheets in environment water.

The ability to reliably distinguish benign from malignant solid liver lesions on ultrasonography can increase access, decrease costs, and help to better triage patients for biopsy. In this study, we used deep learning to differentiate benign from malignant focal solid liver lesions based on their ultrasound appearance. Among the 596 patients who met the inclusion criteria, there were 911 images of individual liver lesions, of which 535 were malignant and 376 were benign. Our training set contained 660 lesions augmented dynamically during training for a total of 330,000 images; our test set contained 79 images. A neural network with ResNet50 architecture was fine-tuned using pre-trained weights on ImageNet. Non-cystic liver lesions with definite diagnosis by histopathology or MRI were included. Accuracy of the final model was compared with expert interpretation. Two separate datasets were used in training and evaluation, one with all lesions and one with lesions deemed to be of uncertain diagnosis based on the Code Abdomen rating system. Our model trained on the complete set of all lesions achieved a test accuracy of 0.84 (95% CI 0.74–0.90) compared to expert 1 with a test accuracy of 0.80 (95% CI 0.70–0.87) and expert 2 with a test accuracy of 0.73 (95% CI 0.63–0.82). Our model trained on the uncertain set of lesions achieved a test accuracy of 0.79 (95% CI 0.69–0.87) compared to expert 1 with a test accuracy of 0.70 (95% CI 0.59–0.78) and expert 2 with a test accuracy of 0.66 (95% CI 0.55–0.75). On the uncertain dataset, compared to all experts averaged, the model had higher test accuracy (0.79 vs. 0.68, p = 0.025). Deep learning algorithms proposed in the current study improve differentiation of benign from malignant ultrasound-captured solid liver lesions and perform comparably to expert radiologists. Deep learning tools can potentially be used to improve the accuracy and efficiency of clinical workflows.

Purpose: With increasing incidence of renal mass, it is important to make a pretreatment differentiation between benign renal mass and malignant tumor. We aimed to develop a deep learning model that distinguishes benign renal tumors from renal cell carcinoma (RCC) by applying a residual convolutional neural network (ResNet) on routine MR imaging. Experimental Design: Preoperative MR images (T2-weighted and T1-postcontrast sequences) of 1,162 renal lesions definitely diagnosed on pathology or imaging in a multicenter cohort were divided into training, validation, and test sets (70:20:10 split). An ensemble model based on ResNet was built combining clinical variables and T1C and T2WI MR images using a bagging classifier to predict renal tumor pathology. Final model performance was compared with expert interpretation and the most optimized radiomics model. Results: Among the 1,162 renal lesions, 655 were malignant and 507 were benign. Compared with a baseline zero rule algorithm, the ensemble deep learning model had a statistically significant higher test accuracy (0.70 vs. 0.56, P = 0.004). Compared with all experts averaged, the ensemble deep learning model had higher test accuracy (0.70 vs. 0.60, P = 0.053), sensitivity (0.92 vs. 0.80, P = 0.017), and specificity (0.41 vs. 0.35, P = 0.450). Compared with the radiomics model, the ensemble deep learning model had higher test accuracy (0.70 vs. 0.62, P = 0.081), sensitivity (0.92 vs. 0.79, P = 0.012), and specificity (0.41 vs. 0.39, P = 0.770). Conclusions: Deep learning can noninvasively distinguish benign renal tumors from RCC using conventional MR imaging in a multi-institutional dataset with good accuracy, sensitivity, and specificity comparable with experts and radiomics.

Purpose To identify risk factors for pain after transarterial chemoembolization with drug-eluting beads (DEB-TACE) for hepatocellular carcinoma (HCC). Patients and Methods In this retrospective study, a total of 118 consecutive patients who underwent DEB-TACE between June 2016 and May 2019 with post-TACE pain were included. The patients were divided into three groups based on the severity of post-TACE pain according to the distribution of pain Visual Analogue Scale/Score (VAS). Potential risk factors for post-TACE pain were primarily analyzed using the chi-square test, one-way analysis of variance, or Kruskal-Wallis test (if appropriate). For multivariate analysis, an ordinal logistic regression model was utilized. Variables with P

Purpose This study aimed to compare the efficacy and safety between transarterial chemoembolization (TACE) with CalliSpheres® microspheres (CSM-TACE) and conventional TACE (cTACE) in patients with hepatocellular carcinoma (HCC). Patients and Methods Three hundred and thirty-five HCC patients receiving CSM-TACE or cTACE were consecutively enrolled in this multi-center, retrospective cohort study, and then divided into CSM-TACE group and cTACE group accordingly. Complete response (CR), objective response (ORR) and disease control response (DCR) was assessed according to mRECIST criteria at 1 month (M1), 3 months(M3) and 6 months(M6) after treatment. Progression-free survival (PFS) and overall survival (OS) were assessed. Liver function indexes and adverse events (AEs) were also evaluated. Results CR at M3 (P=0.020) and ORR at M1 (P0.05), except that ALP (P=0.005), total bilirubin (P=0.031), pain during procedure (P=0.034) and occurrence of fever post(treatment (P=0.017) were significantly elevated in the CSM-TACE compared with cTACE group. Conclusion CSM-TACE presents with a better treatment response and similar survival profile compared with cTACE in HCC patients.

PurposeTo investigate whether incomplete thermal ablation is associated with a high risk of tumor progression in patients with hepatocellular carcinoma (HCC), and to compare the efficacy of repeated thermal ablation and transarterial chemoembolization (TACE) for residual tumor after incomplete ablation.MethodsThis retrospective study included 284 patients with unresectable HCC who underwent thermal ablation from June 2014 to September 2020. The response of the initially attempted ablation was classified into complete (n=236) and incomplete (n=48). The progression-free survival (PFS) and overall survival (OS) were compared between patients with complete and incomplete responses, before and after a one-to-one propensity score-matching (PSM), and between patients in whom repeated ablation or TACE was performed after a first attempt incomplete ablation.ResultsAfter PSM of the 284 patients, 46 pairs of patients were matched. The PFS was significantly higher in the complete response group than in the incomplete response group (PConclusionAlthough patients with incomplete ablation are associated with tumor progression compared with those with complete ablation, their OS is not affected by incomplete ablation. When patients present with residual tumors, TACE may be an alternative if repeated ablation is infeasible.

g-C3N4 nanosheet has been modified by secondary calcination at 550 °C and HNO3 treatment for effectively testing Cr(VI) in aqueous solution via the fluorescence decay according to the inner filter effects proved by the nearly-unchanged time-resolved decay process. The improved fluorescence test performance is attributed to the promoted adsorption of Cr(VI) on resulting g-C3N4 by increasing surface area and the surface positive charge sites. The limit of detection (LOD) is 0.3 μM, which is confirmed by the Stern-Volmer equation with the linear range of 1.0–100.0 μM versus the fluorescence intensity on the optimized conditions of pH = 3 and excitation wavelength of 350 nm. Moreover, at the low-concentration range of 0.2–5.0 μM, it is well linear to the fluorescence intensity by the double logarithmic plot, with the LOD of 0.06 μM. This work provides a feasible route to synthesize g-C3N4-based nanomaterials for effectively detecting Cr(VI) in the solution.

Yu-dong Xiao, Cong Ma, Zi-shu Zhang,* Jun Liu* Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha 410011, China *These authors contributed equally tothis work Objective: To evaluate the feasibility and safety of transarterial chemoembolization with drug-eluting beads (DEB-TACE) in patients with hepatocellular carcinoma (HCC) and arterioportal shunts (APSs). Materials and methods: Fifty-eight patients with unresectable HCC and APSs who were treated with DEB-TACE (n=26) or polyvinyl alcohol (PVA) plus TACE (PVA-TACE, n=32) were included in this retrospective study. The tumor response was evaluated by the modified Response Evaluation Criteria in Solid Tumors. Toxicity was graded by the Common Terminology Criteria for Adverse Events version 5.0 (CTCAE v5.0) and compared between the two groups. Survival curves were calculated by the Kaplan–Meier method and compared by the log-rank test between the two groups. The influence of potential prognostic factors on survival in the DEB-TACE group was analyzed via a multivariate Cox regression model. Results: The disease control rate was better in the DEB-TACE group than in the PVA-TACE group. The median survival times were 346 and 274 days in the DEB-TACE group and PVA-TACE group, respectively. There was no significant difference in survival rates between the two groups (P=0.081). Patients treated with DEB-TACE were significantly less likely to have fever (P=0.048) or a low-grade (grade 1–2) increase in transaminases (P=0.046) than the patients treated with PVA-TACE. The potential predictive prognostic factors in the DEB-TACE group were tumor response, APS grading, and serum bilirubin. Conclusion: DEB-TACE may be feasible and safe in HCC patients with APS. Survival in the DEB-TACE group was associated with tumor response, APS grading, and serum bilirubin levels. Keywords: carcinoma, hepatocellular, chemoembolization, therapeutic, microspheres, arteriovenous fistula

Background This study aimed to compare the live function change and adverse events (AEs) between drug-eluting beads (DEB) transarterial chemoembolization (TACE) with CalliSpheres® microspheres (CSM) and conventional TACE (cTACE) in treating hepatocellular carcinoma (HCC) patients. Methods Three hundred and thirty-five HCC patients underwent DEB-TACE with CSM (n=171, DEB-TACE group) or cTACE (n=164, cTACE group) were consecutively enrolled in this multi-center, retrospective cohort study. Liver function indexes were reviewed before treatment (W0), at 1 week (W1) and 1 month (M1) post treatment. Moreover, AEs during operation and hospitalization were retrieved as well. Results The changes of albumin (ALB) [–3.55 (–6.25 to –0.43) vs. –2.20 (–4.63–0.00), P=0.043] and total protein (TP) [–4.62 (–10.18–0.43) vs. –2.50 (–7.08–1.08), P=0.013] from W1 to W0 were lower in DEB-TACE group compared to cTACE group, while no difference was observed referring to the change of alanine aminotransferase (ALT) (P=0.494), aspartate aminotransferase (AST) (P=0.747), alkaline phosphatase (ALP) (P=0.895), total bilirubin (TBIL) (P=0.059), total bile acid (TBA) (P=0.491) from W1 to W0. And the changes of these seven indexes from M1 to W0 were all similar between DEB-TACE group and cTACE group (all P>0.05). Besides, the occurrence of pain during treatment (19.3% vs. 11.0%, P=0.034) and the occurrence of fever during hospitalization (18.1% vs. 9.1%, P=0.017) were both increased in DEB-TACE group compared to cTACE group. Conclusions DEB-TACE with CSM is non-inferior to cTACE in terms of liver function change, while DEB-TACE with CSM leads to higher incidences of pain and fever.

Objectives: To develop and validate a predictive model for early refractoriness of transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC).Methods: In this multicenter retrospective study, a total of 204 consecutive patients who initially underwent TACE were included. Early TACE refractoriness was defined as patients presented with TACE refractoriness after initial two consecutive TACE procedures. Of all patients, 147 patients (approximately 70%) were assigned to a training set, and the remaining 57 patients (approximately 30%) were assigned to a validation set. Predictive model was established using forward stepwise logistic regression and nomogram. Based on factors selected by logistic regression, a one-to-one propensity score matching (PSM) was conducted to compare progression-free survival (PFS) between patients who were present or absent of early TACE refractoriness. PFS curve was estimated by Kaplan-Meier method and compared by log-rank test.Results: Logistic regression revealed that bilobar tumor distribution (p = 0.002), more than three tumors (p = 0.005) and beyond up-to-seven criteria (p = 0.001) were significantly related to early TACE refractoriness. The discriminative abilities, as determined by the area under the receiver operating characteristic (ROC) curve, were 0.788 in the training cohort and 0.706 in the validation cohort. After PSM, the result showed that patients who were absent of early TACE refractoriness had a significantly higher PFS rate than those of patients who were present (p < 0.001).Conclusion: This study presents a predictive model with moderate accuracy to identify patients with high risk of early TACE refractoriness, and patients with early TACE refractoriness may have a poor prognosis.

Background: To develop a deep learning model to classify primary bone tumors from preoperative radiographs and compare performance with radiologists. Methods: A total of 1356 patients (2899 images) with histologically confirmed primary bone tumors and pre-operative radiographs were identified from five institutions’ pathology databases. Manual cropping was performed by radiologists to label the lesions. Binary discriminatory capacity (benign versus not-benign and malignant versus not-malignant) and three-way classification (benign versus intermediate versus malignant) performance of our model were evaluated. The generalizability of our model was investigated on data from external test set. Final model performance was compared with interpretation from five radiologists of varying level of experience using the Permutations tests. Findings: For benign vs. not benign, model achieved area under curve (AUC) of 0•894 and 0•877 on cross-validation and external testing, respectively. For malignant vs. not malignant, model achieved AUC of 0•907 and 0•916 on cross-validation and external testing, respectively. For three-way classification, model achieved 72•1% accuracy vs. 74•6% and 72•1% for the two subspecialists on cross-validation (p = 0•03 and p = 0•52, respectively). On external testing, model achieved 73•4% accuracy vs. 69•3%, 73•4%, 73•1%, 67•9%, and 63•4% for the two subspecialists and three junior radiologists (p = 0•14, p = 0•89, p = 0•93, p = 0•02, p

Pre-treatment determination of renal cell carcinoma aggressiveness may help guide clinical decision-making. We aimed to differentiate low-grade (Fuhrman I–II) from high-grade (Fuhrman III–IV) renal cell carcinoma using radiomics features extracted from routine MRI. 482 pathologically confirmed renal cell carcinoma lesions from 2008 to 2019 in a multicenter cohort were retrospectively identified. 439 lesions with information on Fuhrman grade from 4 institutions were divided into training and test sets with an 8:2 split for model development and internal validation. Another 43 lesions from a separate institution were set aside for independent external validation. The performance of TPOT (Tree-Based Pipeline Optimization Tool), an automatic machine learning pipeline optimizer, was compared to hand-optimized machine learning pipeline. The best-performing hand-optimized pipeline was a Bayesian classifier with Fischer Score feature selection, achieving an external validation ROC AUC of 0.59 (95% CI 0.49–0.68), accuracy of 0.77 (95% CI 0.68–0.84), sensitivity of 0.38 (95% CI 0.29–0.48), and specificity of 0.86 (95% CI 0.78–0.92). The best-performing TPOT pipeline achieved an external validation ROC AUC of 0.60 (95% CI 0.50–0.69), accuracy of 0.81 (95% CI 0.72–0.88), sensitivity of 0.12 (95% CI 0.14–0.30), and specificity of 0.97 (95% CI 0.87–0.97). Automated machine learning pipelines can perform equivalent to or better than hand-optimized pipeline on an external validation test non-invasively predicting Fuhrman grade of renal cell carcinoma using conventional MRI.

The ability to reliably distinguish benign from malignant solid liver lesions on ultrasonography can increase access, decrease costs, and help to better triage patients for biopsy. In this study, we used deep learning to differentiate benign from malignant focal solid liver lesions based on their ultrasound appearance.Among the 596 patients who met the inclusion criteria, there were 911 images of individual liver lesions, of which 535 were malignant and 376 were benign. Our training set contained 660 lesions augmented dynamically during training for a total of 330,000 images; our test set contained 79 images. A neural network with ResNet50 architecture was fine-tuned using pre-trained weights on ImageNet. Non-cystic liver lesions with definite diagnosis by histopathology or MRI were included. Accuracy of the final model was compared with expert interpretation. Two separate datasets were used in training and evaluation, one with all lesions and one with lesions deemed to be of uncertain diagnosis based on the Code Abdomen rating system.Our model trained on the complete set of all lesions achieved a test accuracy of 0.84 (95% CI 0.74-0.90) compared to expert 1 with a test accuracy of 0.80 (95% CI 0.70-0.87) and expert 2 with a test accuracy of 0.73 (95% CI 0.63-0.82). Our model trained on the uncertain set of lesions achieved a test accuracy of 0.79 (95% CI 0.69-0.87) compared to expert 1 with a test accuracy of 0.70 (95% CI 0.59-0.78) and expert 2 with a test accuracy of 0.66 (95% CI 0.55-0.75). On the uncertain dataset, compared to all experts averaged, the model had higher test accuracy (0.79 vs. 0.68, p = 0.025).Deep learning algorithms proposed in the current study improve differentiation of benign from malignant ultrasound-captured solid liver lesions and perform comparably to expert radiologists. Deep learning tools can potentially be used to improve the accuracy and efficiency of clinical workflows.

The purpose of the present study is to develop a predictive model for incomplete response (IR) after conventional transarterial chemoembolization (cTACE) for hepatocellular carcinoma (HCC) based on hepatic angiographic and cross-sectional imaging.Sixty patients with 139 target HCC lesions who underwent cTACE from February 2013 to March 2019 were included in this retrospective study. Hepatic angiographic features were identified: the number of feeding arteries, vascularity of the tumor, tumor staining on angiography, vascular lake phenomenon, and hepatic arterio-portal shunt. Cross-sectional imaging features were also identified: tumor extent, location, size, and enhancement pattern. Treatment response was assessed by the modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria. Logistic regression analysis was performed to determine the potential predictive factors for treatment response. To validate the predictive value of potential factors, the means of a decision tree were also calculated by Classification and Regression Tree (CART). P0.05 was considered statistically significant.The IR rate was 43.2% (60/139) in the entire study population. Logistic regression analysis showed that a tumor size50 mm (P = 0.005; odds ratio, 7.25; 95% CI 1.79-29.33), central location (P = 0.007; odds ratio, 0.14; 95% CI 0.03-0.59), and nondense tumor staining (P0.001; odds ratio, 0.08; 95% CI 0.02-0.28) were predictors of IR after cTACE. Decision tree analysis showed a good ability to classify treatment response with an accuracy of 78.4%.Tumor size50 mm, central tumor location, and nondense tumor staining were predictors of IR after cTACE. These factors should be taken into consideration when performing cTACE.

Pretreatment determination of renal cell carcinoma aggressiveness may help to guide clinical decision-making. Purpose To evaluate the efficacy of residual convolutional neural network using routine MRI in differentiating low-grade (grade I-II) from high-grade (grade III-IV) in stage I and II renal cell carcinoma. Study type Retrospective. Population In all, 376 patients with 430 renal cell carcinoma lesions from 2008-2019 in a multicenter cohort were acquired. The 353 Fuhrman-graded renal cell carcinomas were divided into a training, validation, and test set with a 7:2:1 split. The 77 WHO/ISUP graded renal cell carcinomas were used as a separate WHO/ISUP test set. Field strength/sequence 1.5T and 3.0T/T2 -weighted and T1 contrast-enhanced sequences. Assessment The accuracy, sensitivity, and specificity of the final model were assessed. The receiver operating characteristic (ROC) curve and precision-recall curve were plotted to measure the performance of the binary classifier. A confusion matrix was drawn to show the true positive, true negative, false positive, and false negative of the model. Statistical tests Mann-Whitney U-test for continuous data and the chi-square test or Fisher's exact test for categorical data were used to compare the difference of clinicopathologic characteristics between the low- and high-grade groups. The adjusted Wald method was used to calculate the 95% confidence interval (CI) of accuracy, sensitivity, and specificity. Results The final deep-learning model achieved a test accuracy of 0.88 (95% CI: 0.73-0.96), sensitivity of 0.89 (95% CI: 0.74-0.96), and specificity of 0.88 (95% CI: 0.73-0.96) in the Fuhrman test set and a test accuracy of 0.83 (95% CI: 0.73-0.90), sensitivity of 0.92 (95% CI: 0.84-0.97), and specificity of 0.78 (95% CI: 0.68-0.86) in the WHO/ISUP test set. Data conclusion Deep learning can noninvasively predict the histological grade of stage I and II renal cell carcinoma using conventional MRI in a multiinstitutional dataset with high accuracy. Level of evidence 3 TECHNICAL EFFICACY STAGE: 2.

Objectives: In this study, we developed radiomic models that utilize a combination of imaging features and clinical variables to distinguish endometrial cancer (EC) from non-EC diagnoses on computed tomography (CT). Methods: A total of 926 patients consisting of 416 EC and 510 non-EC diagnoses were included. Uterus and the endometrium were manually segmented on CT. Fourteen feature selection and ten classification methods were manually examined to select the most optimized machine learning pipeline. Automatic machine learning using Tree-Based Pipeline Optimization Tool (TPOT) was performed. 847 patients were portioned into training, validation, testing sets, and another 79 patients were as our external testing set. The performance of the machine learning pipelines on the testing sets was compared to radiologists. Results: There was significant difference in age between the EC and non-EC groups (64.0 vs. 53.7, p

Background: To develop a deep learning model to classify primary bone tumors from preoperative radiographs and compare performance with expert radiologists. Methods: A total of 1,057 patients (2,233 images) with histologically confirmed primary bone tumors and pre-operative radiographs were identified from three institutions’ pathology databases. Lesions were manually segmented by a radiologist. Binary discriminatory capacity (benign versus not-benign and malignant versus not-malignant) and three-way classification (benign versus intermediate versus malignant) performance of our model were evaluated. Final model performance was compared with two experts’ interpretation. Findings: For benign vs. not benign, the model achieved 82.3% accuracy (AUC [area under curve]: 0.895) compared to 84.1% and 81.0% for experts 1 and 2 (p=0.25 for expert 1 and p=0.34 for expert 2). For malignant vs. not malignant, the model achieved 85.6% accuracy (AUC: 0.908) vs. 84.9% and 85.5% for experts 1 and 2 (p=0.79 for expert 1 and p=0.96 for expert 2). For three-way classification, the model achieved 75.0% accuracy vs. 74.7% and 72.0% for experts 1 and 2 (p=0.76 for expert 1 and p=0.17 for expert 2). Interpretation: Deep learning can classify primary bone tumors using conventional radiographs in a multi-institutional dataset with similar accuracy compared to experts. Future study will focus on development of a fully automatic pipeline including lesion localization and further validation on additional datasets. Funding Statement: This project was supported by the National Institutes of Health under Award Number R03CA235202 and National Natural Science Foundation of China grant under Award Number 8181101287 to Harrison X. Bai. Declaration of Interests: No potential conflicts of interest were disclosed. Ethics Approval Statement: The study was conducted in accordance with Declaration of Helsinki and approved by the Institutional Review Boards at all three institutions.

Objective To investigate prognostic factors of clival chordoma using the largest patient set to date. Methods Appropriate studies were identified per search criteria, data satisfying criteria were extracted, and survival analysis was performed to investigate prognostic factors of clival chordoma. Results A total of 347 patients from the literature cohort met our inclusion criteria. Of 346 cases in which extent of resection was reported, gross total resection (GTR), subtotal resection, and biopsy were achieved in 118 (34.1%), 205 (59.2%), and 21 (6.1%) cases, respectively. Two (0.6%) subjects did not undergo surgery. Of 185 cases in which surgical approach was reported, 56 (30.3%) underwent an endoscopic transoral approach, 17 (9.2%) microscopic transsphenoidal, 45 (24.3%) endoscopic or microscopic, 45 (24.3%) craniotomy, and 22 (11.9%) other approaches. There was no significant difference in GTR rates of different surgical approaches (P = 0.101). Median follow-up was 46.6 months. The 5- and 10-year rates for progression-free survival (PFS) were 59.2% and 47.9%, respectively. The 5- and 10-year rates for overall survival (OS) were 77.3% and 63.9%, respectively. On multivariate analysis for both PFS and OS, GTR demonstrated significantly improved outcomes when compared with subtotal resection (hazard ratio 0.45, 95% confidence interval 0.22–0.90, P = 0.025 for PFS; hazard ratio 0.20, confidence interval 0.06–0.65, P = 0.008 for OS). Conclusions GTR rates were comparable in different surgical approaches. GTR was a significant predictor of longer PFS and OS in clival chordoma.

STUDY DESIGN Retrospective cohort analysis of patients with spinal astrocytoma from multi-institutional data and the literature. OBJECTIVE To determine the prognostic factors, treatment, and survival of patients. SUMMARY OF BACKGROUND DATA Our current understanding of the epidemiology, prognosis, and optimal treatment of spinal astrocytoma is limited. The literature is confined to case reports or small institutional case series. METHOD Patient demographics, tumor characteristics, treatments, and outcomes were extracted. Univariate Kaplan-Meier survival analysis was performed to identify prognostic factors followed by multivariate Cox proportional hazard analysis. Wilcoxon signed-rank test was performed on pre- and postoperational functional status as measured by McCormick score. RESULTS Ninety-four patients from four institutions and 339 patients from the literature were included. For the multi-institutional cohort, WHO grade IV tumors had shorter progression-free survival (PFS) than those of lower grades, whereas gross total resection (GTR) (hazard ratio [HR]: 0.41, 95% confidence interval [CI]: 0.14-1.27, P = 0.124) trended toward longer PFS when compared to subtotal resection (STR). Age 18 years or older, paresthesia as a presenting symptom, and higher WHO grade were associated with shorter overall survival (OS), whereas thoracic tumor location when compared to cervical tumor location, biopsy when compared to STR, and radiotherapy (HR: 0.42, 95% CI: 0.20-0.88, P = 0.022) were associated with longer OS. For the literature cohort, GTR (HR 0.43, 95% CI: 0.24-0.77, P = 0.005) was associated with longer PFS when compared to STR, whereas higher WHO grade was associated with shorter PFS. Higher WHO grade and recurrence/progression were associated with shorter OS. Postoperative McCormick score was significantly higher than preoperative score (P

// Jing Wu 1,3,* , Ting Zou 1,* , Harrison Xiao Bai 2 , Xuejun Li 5 , Zishu Zhang 6 , Bo Xiao 3 , MacLean Nasrallah 4 , Giorgos Karakousis 7 , Ya Cao 8 , Paul J. Zhang 4 and Li Yang 1 1 Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China 2 Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America 3 Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China 4 Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America 5 Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China 6 Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China 7 Department of Surgery, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America 8 Cancer Research Institute, School of Basic Medicine, Central South University, Changsha, Hunan, China * These authors have contributed equally to this study Correspondence to: Li Yang, email: // Keywords : chemoradiotherapy, anaplastic astrocytoma, National Cancer Database, radiotherapy, survival Abbreviations : RT, Radiotherapy; CRT, Chemoradiotherapy; OS, Overall Survival; AA, Anaplastic Astrocytoma. Received : December 16, 2016 Accepted : March 17, 2017 Published : April 26, 2017 Abstract Background: It has become increasingly common to incorporate adjuvant chemotherapy with radiotherapy in the treatment of resected anaplastic astrocytoma based on results from recent phase II/III randomized trials. However, whether or not combined chemoradiotherapy is associated with improved survival outcome in patients who undergo “biopsy only” is less clear. Methods: The US National Cancer Database was used to identify patients with histologically confirmed, biopsy-only anaplastic astrocytoma who received either radiotherapy alone or combined chemoradiotherapy from 2006 through 2014. Results: In total, 1896 patients with biopsy-only anaplastic astrocytoma were included, among whom 363 (19.1%) received radiotherapy alone and 1533 (80.9%) received combined chemoradiotherapy. The median age at diagnosis was 60 years. Combined chemoradiotherapy was associated with a significant survival benefit when compared with radiotherapy alone on univariable analysis (median, 13.2 versus 5.6 months; hazard ratio [HR], 0.57; 95% confidence interval [CI], 0.50-0.65; p < 0.001) and on multivariable analysis (HR, 0.62; 95% CI, 0.55-0.71; p < 0.001). A significant survival benefit for combined chemoradiotherapy persisted in a propensity score-matched analysis (HR, 0.67; 95% CI, 0.56-0.78; p

Background The low incidence of spinal chordoma precludes a prospective study of prognostic factors with a large patient cohort. Objective To perform a comprehensive integrative analysis on the prognostic factors, treatment, and outcomes of patients with spinal chordoma using data from 2 institutions and the literature. Methods Appropriate studies were identified per search criteria. The local database was retrospectively searched to include a similar patient cohort. Results Overall, 108 studies from the literature and 30 patients from our local institution were identified, resulting in a total of 682 patients. The median age was 57 years old and 35.2% were female. The median follow-up was 46 months (range: 1-408). The median progression-free survival (PFS) and overall survival (OS) were 72 months and 115 months, respectively. Significant prognostic factors for PFS on multivariate analysis included age (pediatric vs adult, hazard ratio [HR]: 2.00-14.36), tumor location (mobile spine vs sacral spine, HR: 0.31-0.87), pathology (differentiated vs classic, HR: 2.48-10.90),and chemotherapy (HR:1.11-3.85). Significant prognostic factors for OS on multivariate analysis included age (geriatric vs adult, HR: 1.52-3.45 and pediatric vs adult, HR: 1.73-9.36), bladder or bowel dysfunction (HR: 1.27-5.43), pathology (dedifferentiated vs classic, HR: 2.38-11.09), recurrence or progression (HR: 1.72-4.48), and metastases (HR: 1.11-2.47). Conclusion In patients with spinal chordoma, young age, location in sacral spine, dedifferentiated pathology, and chemotherapy were negative predictors of PFS, while young and old age, bladder or bowel dysfunction at presentation, dedifferentiated pathology, recurrence or progression, and metastases portended a worse OS.

Background To compare the efficacy and safety between conventional transarterial chemoembolization (cTACE) and drug-eluting beads TACE (DEB-TACE) in patients with infiltrative hepatocellular carcinoma (iHCC). Methods A total of 89 iHCC patients who were treated with either cTACE (n = 33) or DEB-TACE (n = 56) between April 2013 and September 2017 were included in this retrospective study. Patients with the situations that might have a poor outcome were defined as advanced disease including Child-Pugh class B, bilobar lesions, tumor size greater than 10 cm, ECOG 1–2, tumor burden of 50–70%, and the presence of ascites, arterioportal shunt (APS), and portal venous tumor thrombus (PVTT). The tumor response was measured 1-month and 3-month after the procedure. Progression-free survival (PFS) was calculated. Toxicity was graded by Common Terminology Criteria for Adverse Events v5.0 (CTCAE v5.0). The differences in tumor response, PFS, and toxicity were compared between the DEB-TACE group and cTACE group. Results At 1-month and 3-month after the procedure, the objective response rate (ORR) in the overall study population was similar in DEB-TACE group and cTACE group. The disease control rate (DCR), at 1-month after the procedure, was significantly higher in the patients treated with DEB-TACE relative to those treated with cTACE (P = 0.034), while after 3 months, the difference did not differ between two groups. DEB-TACE showed a higher DCR than cTACE in patients with tumor size greater than 10 cm (P = 0.036) or associated with APS (P = 0.030) at 1-month after the procedure, while after 3 months, the difference was only noted in patients with APS (P = 0.036). The median PFS in DEB-TACE group was 96 days, while in cTACE group was 94 days, and there was no difference in PFS between two groups (P = 0.831). In the side effect analysis, abdominal pain (P = 0.034) and fever (P = 0.009) were more frequently present in the cTACE group than DEB-TACE group, but there was no difference in high grade liver toxicity between the two groups. Conclusions Compared to cTACE, DEB-TACE offers slightly better DCR and tolerability for iHCC patients, particularly in patients associated with APS and large tumor size. However, DEB-TACE does not provide higher PFS than cTACE.

To explore the mechanism for changes in brain microstructure in long-term abstinent from methamphetamine-dependence by using the diffusion tensor imaging (DTI). Methods: A total of 26 patients with long-term abstinent methamphetamine-dependence, whose abstinence time more than 14 months, and 26 normal controls all underwent cognitive executive function tests and DTI scans. We used voxel-based analysis to compare the fractional anisotropy (FA) and mean diffusivity (MD) to obtain the abnormal brain regions of DTI parameters between the two groups. Spearman correlation analysis was used to explore the correlation between FA, MD of the brain regions with abnormal parameters and cognitive executive function tests. Results: There were no statistical differences in the cognitive executive function tests between the two groups (P0.05). Compared with the normal control group, the long-term abstinent from methamphetamine-dependence group showed the decreased FA in the right precuneus, right superior frontal gyrus, right calcarine, left inferior temporal gyrus and the increased MD in the right triangular part of inferior frontal gyrus, right precuneus, right posterior cingulate, right middle temporal gyrus, bilateral middle occipital gyrus, left superior parietal lobule, and lobule VIII of cerebellar hemisphere. The MD values of the right middle temporal gyrus in the long-term abstinent group were negatively correlated with the number of completions within 60 seconds (r=-0.504) and within 120 seconds (r=-0.464) . Conclusion: The DTI parameters in multiple brain regions from the methamphetamine-dependence patients are still abnormal after a long-term abstinence. DTI can provide imaging evidence for brain microstructural abnormalities in long-term abstinent from methamphetamine-dependence.目的：探究长期戒断甲基苯丙胺依赖者大脑微观结构的影像改变机制。方法：对26例长期戒断依赖者(戒断时间长于14个月)和26例对照组进行认知执行功能测试和扩散张量成像(diffusion-tensor imaging，DTI)检查，利用基于体素的分析方法对两组的部分各向异性(fractional anisotropy，FA)和平均扩散率(mean diffusivity， MD)进行比较，获得组间参数差异脑区，将长期戒断甲基苯丙胺组异常脑区参数值与测试结果行Spearman相关分析。结果：长期戒断甲基苯丙胺组和对照组的认知执行功能测试结果差异无统计学意义(P0.05)；相比对照组，长期戒断甲基苯丙胺依赖组右侧楔前叶、背外侧额上回、距状裂周围皮质及左侧颞下回FA降低；右侧三角部额下回、楔前叶、后扣带回、颞中回、双侧枕中回、左侧顶上回及小脑半球8区MD升高。长期戒断甲基苯丙胺组右侧颞中回MD与数字符号60 s(r=–0.504)和120 s(r=–0.464)内完成个数均呈负相关。结论：甲基苯丙胺依赖者经长期戒断后多个脑区微结构仍存在异常，DTI可为长期戒断甲基苯丙胺依赖者脑微观结构异常提供影像学证据。.

Purpose To develop and validate a deep learning model based on routine magnetic resonance (MR) imaging obtained before uterine fibroid embolization to predict procedure outcome. Materials and Methods Clinical data were collected on patients treated with uterine fibroid embolization at the Hospital of the University of Pennsylvania from 2007 to 2018. Fibroids for each patient were manually segmented by an abdominal radiologist on a T1-weighted contrast-enhanced (T1C) sequence and a T2-weighted sequence of MR imaging obtained before and after embolization. A residual convolutional neural network (ResNet) model to predict clinical outcome was trained using MR imaging obtained before the procedure. Results Inclusion criteria were met by 727 fibroids in 409 patients. At clinical follow-up, 85.6% (n = 350) of 409 patients (590 of 727 fibroids; 81.1%) experienced symptom resolution or improvement, and 14.4% (n = 59) of 409 patients (137 of 727 fibroids; 18.9%) had no improvement or worsening symptoms. The T1C trained model achieved a test accuracy of 0.847 (95% confidence interval [CI], 0.745–0.914), sensitivity of 0.932 (95% CI, 0.833–0.978), and specificity of 0.462 (95% CI, 0.232–0.709). In comparison, the average of 4 radiologists achieved a test accuracy of 0.722 (95% CI, 0.609–0.813), sensitivity of 0.852 (95% CI, 0.737–0.923), and specificity of 0.135 (95% CI, 0.021–0.415). Conclusions This study demonstrates that deep learning based on a ResNet model achieves good accuracy in predicting outcome of uterine fibroid embolization. If further validated, the model may help clinicians better identify patients who can most benefit from this therapy and aid clinical decision making.

Alcohol-related white matter (WM) microstructural changes have not been fully elucidated in adolescents. We aimed to investigate influences of subclinical alcohol use during adolescence on WM microstructure and to characterize those with serum metabolic alterations. 35 moderate-to-heavy drinkers (15 males, 20 females) and 27 controls (12 males, 15 females) were selected based on their ten-year Alcohol Use Disorders Identification Test scores measured at three time points. Magnetic resonance imaging was conducted at endpoint time. Whole brain analysis of fractional anisotropy (FA) was performed. Diffusivity indices in the significant regions were computed for between-group comparisons and correlation analyses with serum metabolite concentrations. Decreased FA was found in moderate-to-heavy drinking men in anterior corpus callosum, superior/anterior corona radiata and right inferior fronto-occipital fasciculus, accompanied by increased radial diffusivity and a smaller area of reduced axial diffusivity, which correlated with serum metabolites playing roles in energy metabolism, myelination and axonal degeneration. No significant difference in FA was detected between female or mixed-gender moderate-to-heavy drinking subjects and controls, supporting gender differences in the relationship between adolescent alcohol use and neurodevelopmental trajectories. Future researches with longitudinal imaging data are warranted for comprehensive evaluation on potentially reversible effects of alcohol use over adolescent brain.

Summary Background Transarterial chemoembolization (TACE) is widely applied in hepatocellular carcinoma (HCC) patients who are not suitable for surgical treatment. We aimed to investigate the treatment outcomes and comprehensive prognostic factors of CalliSpheres® microspheres (CSM) drug-eluting bead TACE (DEB-TACE) treatment and conventional TACE (cTACE) treatment in HCC patients. Methods Three hundred and thirty-five HCC patients received DEB-TACE or cTACE treatment were consecutively enrolled in multi-center, retrospective cohort study. Treatment response was conducted at M1, M3 or M6 after treatment. Progression free survival (PFS) and overall survival (OS) were recorded. Thirty-seven baseline factors including demographic characteristics, clinical features, biochemical indexes and previous treatment histories were selected. Results In total patients, history of drink and largest nodule size ≥ 7 cm independently predicted worse ORR, DEB-TACE predicted better OS, while largest nodule size ≥ 7 cm, increased Child-Pugh stage, ALB abnormal, ALP abnormal or AFP abnormal predicted worse survival. For DEB-TACE group, previous cTACE and ANC abnormal independently predicted worse ORR, and hepatic vein invasion, increased Child-Pugh stage or AFP abnormal independently predicted poor survival. For cTACE group, largest nodule size ≥ 7 cm independently predicted poor ORR, and multifocal disease as well as ALB abnormal predicted poor OS. Conclusions History of drink, largest nodule size ≥ 7 cm, DEB-TACE, increased Child-Pugh stage, abnormal ALB, ALP or AFP are potential prognostic factors in total patients, previous cTACE and ANC abnormal, hepatic vein invasion, increased Child-Pugh stage or AFP abnormal are potential prognostic factors in DEB-TA group, and largest nodule size ≥ 7 cm, multifocal disease and ALB abnormal are potential prognostic factors in cTACE group.

Purpose To compare overall survival (OS) of ablation with no treatment for patients with advanced stage non-small cell lung cancer. Methods Patients with clinical stage IIIB (T1–4N3M0, T4N2M0) and stage IV (T1–4N0–3M1) non-small cell lung cancer, in accordance with the American Joint Committee on Cancer, 7th edition, who did not receive treatment or who received ablation as their sole primary treatment besides chemotherapy from 2004 to 2014, were identified from the National Cancer Data Base. OS was estimated using the Kaplan-Meier method and evaluated by log-rank test, univariate and multivariate Cox proportional hazard regression, and propensity score-matched analysis. Relative survival analyses comparing age- and sex-matched United States populations were performed. Results A total of 140,819 patients were included. The 1-, 2-, 3- and 5-year survival rates relative to age- and sex-matched United States population were 28%, 18%, 12%, and 10%, respectively, for ablation (n = 249); and 30%, 15%, 9%, and 5%, respectively for no treatment (n = 140,570). Propensity score matching resulted in 249 patients in the ablation group versus 498 patients in the no-treatment group. After matching, ablation was associated with longer OS than that in the no-treatment group (median, 5.9 vs 4.7 months, respectively; hazard ratio, 0.844; 95% confidence interval, 0.719–0.990; P = .037). These results persisted in patients with an initial tumor size of ≤3 cm. Conclusions Preliminary results suggest ablation may be associated with longer OS in patients with late-stage non-small cell lung cancer than survival in those who received no treatment.

A simple method was developed to prepare fluorescent nitrogen/boron-doped carbon dots (N,B-CDs) in the gram scale. The results showed that the CDs exhibited blue photoluminescence (PL) under 365 nm ultraviolet radiation and excitation-dependent emission. Heteroatoms entered the CDs to enhance the photochemical properties, and their positive properties can be attributed to the presence of guanidino group and functionalized with boronic acid for realizing their utilization in certain applications. These materials could be applied to monitor Fe3+ via static PL quenching, yielding a limit of detection (LOD) of 0.74 μM. Furthermore, the charged and boronic acid groups on the prepared N,B-CDs enabled their use as recognition elements to bind with the bacteria through electrostatic interaction and allowed covalent interactions to form the corresponding boronate ester with E. coli (E. coli) bacterial membrane. This method could satisfy a linear range of 102–107 with LOD of 165 cfu ml−1 for E. coli. This method was applied for the determination of E. coli in tap water and orange juice samples, and satisfactory results were obtained.