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  • 2015-2019  (11)
  • 2010-2014  (1)
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  • 1
    Online Resource
    Online Resource
    Singapore :Springer Singapore Pte. Limited,
    Keywords: Artificial intelligence-Congresses. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (498 pages)
    Edition: 1st ed.
    ISBN: 9789811500770
    Series Statement: Smart Innovation, Systems and Technologies Series ; v.165
    Language: English
    Note: Intro -- Organizing Committee -- Preface -- Contents -- About the Editors -- 1 Comparison of Different Image Segmentation Techniques on MRI Image -- 1.1 Introduction -- 1.2 Methodology -- 1.2.1 Preprocessing -- 1.2.2 Segmentation Techniques -- 1.3 Results and Discussion -- 1.4 Conclusion -- References -- 2 PSO-ANN-Based Computer-Aided Diagnosis and Classification of Diabetes -- 2.1 Introduction -- 2.1.1 Literature Survey -- 2.2 Feature Selection Approaches -- 2.3 Particle Swarm Optimization (PSO) -- 2.4 Proposed Feature Selection Algorithm -- 2.5 Experimental Results -- 2.6 Conclusion -- References -- 3 Round Robin Scheduling Based on Remaining Time and Median (RRRT& -- M) for Cloud Computing -- 3.1 Introduction -- 3.2 Related Works -- 3.3 Scheduling Algorithms -- 3.4 Experimental Setup and Result Discussions -- 3.4.1 Experimental Setup -- 3.4.2 Performance Metrics -- 3.4.3 Result Discussions -- 3.5 Summary -- References -- 4 Business-Driven Blockchain-Mempool Model for Cooperative Optimization in Smart Grids -- 4.1 Introduction -- 4.2 Related Work -- 4.3 Virtual Power Plant Dispatch Schedules -- 4.3.1 Cost Function Based Optimization -- 4.4 Blockchain -- 4.4.1 Consensus -- 4.5 Consensus and Cooperative Scheduling -- 4.6 Mempool Model -- 4.7 Evaluation and Future Work -- 4.8 Conclusion -- References -- 5 Research of Institutional Technology Diffusion Rules Based on Patent Citation Network-A Case Study of AI Field -- 5.1 Introduction -- 5.2 Data and Method -- 5.3 Results and Discussion -- 5.3.1 Comparative Analysis of Technical Force -- 5.3.2 Technology Diffusion Network and Visualization -- 5.3.3 Measurement of Technology Diffusion Capacity -- 5.4 Conclusion and Limitation -- References -- 6 Impact on the Information Security Management Due to the Use of Social Networks in a Public Organization in Ecuador -- 6.1 Introduction. , 6.2 Materials and Methods -- 6.2.1 Materials -- 6.2.2 Methods -- 6.3 Results -- 6.4 Discussion -- 6.5 Future Work and Conclusion -- References -- 7 Appropriate Security Protocols to Mitigate the Risks in Electronic Money Management -- 7.1 Introduction -- 7.2 Materials and Methods -- 7.2.1 Materials -- 7.2.2 Methods -- 7.3 Results -- 7.4 Discussion -- 7.5 Future Works and Conclusion -- 7.5.1 Future Works -- 7.5.2 Conclusions -- References -- 8 Acceptance and Readiness of Thai Farmers Toward Digital Technology -- 8.1 Introduction -- 8.2 Research Model -- 8.3 Method -- 8.3.1 Questionnaire Instrument -- 8.3.2 Data Analysis -- 8.4 Results -- 8.5 Conclusion -- References -- 9 Neural Network Classifier for Diagnosis of Diabetic Retinopathy -- 9.1 Introduction -- 9.2 Classification -- 9.3 Conclusion -- References -- 10 Comparative Analysis of Data Mining Classification Techniques for Prediction of Heart Disease Using the Weka and SPSS Modeler Tools -- 10.1 Introduction -- 10.2 Literature Review -- 10.2.1 Data Mining Classification Techniques -- 10.3 Experimental Analysis -- 10.3.1 Dataset -- 10.3.2 Result Analysis -- References -- 11 An Automated Framework to Uncover Malicious Traffic for University Campus Network -- 11.1 Introduction -- 11.2 Study Goals -- 11.3 Methodology -- 11.4 Experimental Setup -- 11.5 Observations and Analysis of Framework in Campus Network on Real-Time Basis -- 11.5.1 Dashboard Visualization for Analysis -- 11.6 Conclusion -- 11.7 Future Scope -- References -- 12 Comparative Analysis of K-Means Algorithm and Particle Swarm Optimization for Search Result Clustering -- 12.1 Introduction -- 12.2 Related Work -- 12.3 Experimental Result and Analysis -- 12.3.1 Dataset Details -- 12.3.2 Preprocessing -- 12.3.3 Performance Evaluation -- 12.4 Conclusion -- References. , 13 Design and Implementation of Rule-Based Hindi Stemmer for Hindi Information Retrieval -- 13.1 Introduction -- 13.2 Stemming Approaches -- 13.2.1 Affix Removal Approach -- 13.2.2 N-Gram -- 13.2.3 Suffix Stripping Approach -- 13.2.4 Suffix Substitution Approach -- 13.2.5 Brute-Force Approach -- 13.2.6 Hybrid Approach -- 13.3 Related Work -- 13.4 Proposed Methodology and Implementation -- 13.5 Analysis and Conclusion -- References -- 14 Research on the Development Trend of Ship Integrated Power System Based on Patent Analysis -- 14.1 Introduction -- 14.2 Data and Methods -- 14.3 Results and Discussion -- 14.3.1 Life Cycle Analysis of Patent Technology Development of Foreign Ship Integrated Power System -- 14.3.2 Analysis of Patent Technology Research and Development Direction of Foreign Ship Integrated Power System -- 14.4 Summary -- References -- 15 Detection of Data Anomalies in Fog Computing Architectures -- 15.1 Introduction -- 15.2 Fog Architecture Overview -- 15.3 Anomaly Detection -- 15.3.1 Anomalies -- 15.3.2 Preliminaries for Detection Algorithm -- 15.3.3 Detection Procedure -- 15.4 Computation Algorithm -- 15.5 Related Work -- 15.6 Conclusion -- References -- 16 Cloud Data for Marketing in Tourism Sector -- 16.1 Introduction -- 16.2 Consumer Behavioral Study for the Tourism Industry -- 16.3 Sources of Data -- 16.3.1 Methods of Sourcing Data from Internet -- 16.4 Model for Marketing Data Capture -- 16.4.1 Prediction Theories -- 16.4.2 Marketing -- 16.5 Results -- 16.6 Conclusion -- References -- 17 Road Travel Time Prediction Method Based on Random Forest Model -- 17.1 Introduction -- 17.2 The Principle of Random Forest Algorithm -- 17.3 The Principle of DBSCAN -- 17.4 The Prediction Model of RF-DBSCAN -- 17.4.1 Data Sources -- 17.4.2 Feature Selection -- 17.4.3 The Principle of RF-DBSCAN -- 17.4.4 Comparison of Experiment Results. , 17.5 Conclusions -- References -- 18 Video Synchronization and Alignment Using Motion Detection and Contour Filtering -- 18.1 Introduction -- 18.1.1 Overview -- 18.1.2 Problem Statement -- 18.1.3 Objectives -- 18.1.4 Existing System -- 18.1.5 Proposed System -- 18.2 Literature Survey -- 18.3 System Design -- 18.4 Dataflow of Video Change Detection -- 18.5 Class Diagrams -- 18.6 Experimental Results -- 18.7 Conclusion -- References -- 19 Mutichain Enabled EHR Management System and Predictive Analytics -- 19.1 Introduction -- 19.2 Related Work -- 19.2.1 Verifying the Authenticity of Returned Drugs by Tracking Supply of Authorized Drugs in Supply Chain -- 19.2.2 Transparency and Traceability of Consent in Clinical Trials -- 19.2.3 Incentivized Access to Medical Data -- 19.3 Problem Setting -- 19.4 Proposed Architecture -- 19.4.1 Multichain -- 19.4.2 Off-Chain Storage -- 19.4.3 Hashing -- 19.4.4 Data Analysis -- 19.4.5 Machine Learning -- 19.4.6 Workflow -- 19.5 Conclusion -- References -- 20 Quick Insight of Research Literature Using Topic Modeling -- 20.1 Introduction -- 20.2 Literature Survey -- 20.3 Methodology -- 20.3.1 Preprocessing-Natural Language Processing -- 20.3.2 Topic Modeling -- 20.3.3 Latent Dirichlet Allocation -- 20.4 System Development -- 20.5 Experimental Results -- 20.6 Conclusion -- References -- 21 Secure Cloud-Based E-Healthcare System Using Ciphertext-Policy Identity-Based Encryption (CP-IBE) -- 21.1 Introduction -- 21.1.1 An Overview -- 21.2 Related Work -- 21.3 Proposed Methodology -- 21.3.1 Developing an Efficient Data Storage Scheme -- 21.3.2 Developing a Ciphertext Database Scheme -- 21.4 Conclusion -- References -- 22 Security Vulnerabilities of OpenStack Cloud and Security Assessment Using Different Software Tools -- 22.1 Introduction -- 22.2 Software Architecture -- 22.2.1 Components of OpenStack. , 22.2.2 OpenStack Usage in Cloud Platform -- 22.3 Vulnerabilities in OpenStack -- 22.3.1 Known Vulnerabilities in OpenStack -- 22.3.2 Assessment for Security -- 22.3.3 Network Vulnerability Scanners -- 22.4 Conclusion -- References -- 23 Smart Physical Intruder Detection System for Highly Sensitive Area -- 23.1 Introduction -- 23.2 Literature Survey -- 23.3 Proposed Methodology -- 23.3.1 Working of PIR Motion Sensor -- 23.3.2 Face Recognition Using Viola-Jones Algorithm and KNN Algorithm -- 23.4 Conclusion and Future Scope -- References -- 24 Two-level Classification of Radar Targets Using Machine Learning -- 24.1 Introduction -- 24.2 Phased Array Radar -- 24.3 Design of Multilevel Classifier -- 24.3.1 Signal Level Classification: Level ``0'' -- 24.3.2 Classification Level 1 Using Raw Detection -- 24.3.3 Level 2 Classifier Using Track Data -- 24.4 Fusion of Information with Signal Level Classifier -- 24.5 Simulation and Results -- 24.5.1 Results for Level 1 Classification -- 24.5.2 Classification Level 2 Using Radar Track and Signal Data -- 24.6 Conclusion -- References -- 25 A Cognitive Semantic-Based Approach for Human Event Detection in Videos -- 25.1 Introduction -- 25.2 Methodology -- 25.2.1 Frame Generation -- 25.2.2 Fuzzy C-Mean Clustering (FCM) -- 25.2.3 Feature Extraction -- 25.2.4 CNN Classifier -- 25.3 Test Results and Discussions -- 25.4 Conclusions -- References -- 26 Analysis of Adequate Bandwidths to Guarantee an Electoral Process in Ecuador -- 26.1 Introduction -- 26.2 Materials and Methods -- 26.2.1 Materials -- 26.2.2 Methods -- 26.3 Results -- 26.4 Discussion -- 26.5 Work Futures and Conclusions -- References -- 27 Load and Renewable Energy Forecasting for System Modelling, an Effort in Reducing Renewable Energy Curtailment -- 27.1 Introduction -- 27.2 Literature Review -- 27.3 Proposed Work. , 27.3.1 Neural Network-Based Load Forecasting.
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  • 2
    Publication Date: 2018-06-02
    Description: Entropy, Vol. 20, Pages 427: Refrigeration Performance and Entropy Generation Analysis for Reciprocating Magnetic Refrigerator with Gd Plates Entropy doi: 10.3390/e20060427 Authors: Yonghua You Zhongda Wu Yong Yang Jie Yu Dong Zhang Zhuang Zhang In the current work, a novel 2D numerical model of stationary grids was developed for reciprocating magnetic refrigerators, with Gd plates, in which the magneto-caloric properties, derived from the Weiss molecular field theory, were adopted for the built-in energy source of the magneto-caloric effect. The numerical simulation was conducted under the conditions of different structural and operational parameters, and the effects of the relative fluid displacement (φ) on the specific refrigeration capacity (qref) and the Coefficient of Performance (COP) were obtained. Besides the variations of entropy, the generation rate and number were studied and the contours of the local entropy generation rate are presented for discussion. From the current work, it is found that with an increase in φ, both the qref and COP followed the convex variation trend, while the entropy generation number (Ns) varied concavely. As for the current cases, the maximal qref and COP were equal to 151.2 kW/m3 and 9.11, respectively, while the lowest Ns was the value of 2.4 × 10−4 K−1. However, the optimal φ for the largest qref and COP, and for the lowest Ns, were inconsistent, thus, some compromises need be made in the optimization of magnetic refrigerators.
    Electronic ISSN: 1099-4300
    Topics: Chemistry and Pharmacology , Physics
    Published by MDPI Publishing
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  • 3
    Publication Date: 2015-09-05
    Description: Background To compare intravoxel incoherent motion (IVIM) and pharmacokinetic analysis dynamic contrast-enhanced MR imaging (DCE-MRI) in distinguishing lung cancer (LC) from benign solitary pulmonary lesions (SPL). Methods This prospective study was approved by the institutional review board, and written informed consent was obtained. Eighty-one consecutive patients considered for SPL underwent DW-IVIM and DCE-3T MRI. ADC, D, D*, and f were calculated with mono- and bi-exponential models. K trans , k ep , v e , and v p were calculated with the modified Tofts model. Receiver operating characteristic (ROC) analysis was constructed to determine the diagnostic performance of IVIM and DCE-MRI in discriminating LC from benignity. Results There were 29 patients with a total of 48 benign SPL and 52 LCs: 4 small cell carcinomas (SCLC), 19 squamous cell carcinomas (SCC), and 29 adenocarcinomas (Adeno-Ca). Both Adeno-Ca (ADC: 1.19 ± 0.23 × 10 −3 mm 2 /s; D:1.12 ± 0.35 × 10 −3 mm 2 /s; v e :0.27 ± 0.13; K trans :0.24 ± 0.09 min −1 ; k ep :0.90 ± 0.45 min −1 ) and SCC (1.13± 0.28 × 10 −3 mm 2 /s; 1.02 ± 0.32 10 −3 mm 2 /s; 0.32 ± 0.14; 0.26 ± 0.08 min −1 ; 0.90 ± 0.48 min −1 ) had significantly lower ADC, D, v e and larger K trans , k ep than benignity (1.37 ± 0.38 × 10 −3 mm 2 /s; 1.34 ± 0.45 × 10 −3 mm 2 /s; 0.42 ± 0.19; 0.19 ± 0.08 min −1 ; 0.53 ± 0.26 min −1 ). D (72.2%) had significantly higher accuracy (72.2%) and higher sensitivity (91.3%) than other imaging indices (accuracy: 55.5–68.0%; sensitivity: 41.3–78.3%; all P  〈 0.01) except for accuracy in k ep (70.8%; P  〉 0.05) in discriminating LC from benignity. K trans exhibited significantly higher specificity (84.6%) than the other indices (38.5–73.1%; P  〈 0.01). These results can be improved by combined D and K trans , leading to a sensitivity, specificity and accuracy of 94.2%, 92%, and 93.5%, respectively. Conclusion IVIM-derived D and DCE-derived K trans are two promising parameters for differentiating LC from benignity. J. Magn. Reson. Imaging 2015.
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    Electronic ISSN: 1522-2586
    Topics: Medicine
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  • 4
    Publication Date: 2017-01-06
    Description: Purpose To evaluate the diagnostic performance of extended models of diffusion-weighted (DW) imaging to help differentiate the epidermal growth factor receptor (EGFR) mutation status in stage IIIA-IV lung adenocarcinoma. Materials and Methods This retrospective study had institutional research board approval and was HIPAA compliant. Preoperative extended DW imaging including intravoxel incoherent motion (IVIM) and diffusional kurtosis imaging (DKI) 3 Tesla MRI were retrospectively evaluated in 53 patients with pathologically confirmed non-early stage (IIIA-IV) lung adenocarcinoma. EGFR mutationsat exons 18–21 were determined by using polymerase chain reaction-based ARMS. Quantitative parameters (mean, kurtosis, skewness, 10 th and 90 th percentiles) of IVIM (true-diffusion coefficient D, pseudo-diffusion coefficient D*, and perfusion fraction f) and DKI (kurtosis value Kapp, kurtosis corrected diffusion coefficient Dapp) were calculated by outlining entire-volume histogram analysis. Receiver operating characteristic analysis was constructed to determine the diagnostic performance of each parameter. Multivariate logistic regression was used to differentiate the probability of EGFR mutation status. Results Twenty-four of 53 patients with lung adenocarcinoma were EGFR mutations, which occurred most often in acinar (10 of 13 [76.9%]) and papillary predominant tumors (9 of 13 [69.2%]). Patients with EGFR mutation showed significant higher 10 th percentile of D, lower D* value in terms of kurtosis, and lower K app value in terms of mean, skewness, 10 th and 90 th percentiles (all P values 〈 0.05). The 90 th K app showed significantly higher sensitivity (97%; P  〈 0.05) and Az (0.817; P  〈 0.05) value. Multivariate logistic regression showed 90 th K app was a independent factor for determining EGFR mutation with odds ratio -1.657. Conclusion Multiple IVIM and DKI parameters, especially the histogram 90 th K app value, helped differentiate EGFR mutation status in stage IIIA-IV lung adenocarcinoma. Level of Evidence: 3 J. Magn. Reson. Imaging 2017
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    Topics: Medicine
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  • 5
    Publication Date: 2017-01-20
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    Topics: Medicine
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  • 6
    Publication Date: 2018-02-14
    Description: Background Partin tables represent the most widely used predictive tool for prostate cancer stage at prostatectomy but with potential limitations. Purpose To develop a new PartinMR model for organ-confined prostate cancer (OCPCA) by incorporating Partin table and mp-MRI with a support vector machine (SVM) analysis. Study Type Retrospective. Population In all, 541 patients with biopsy-confirmed prostate cancer underwent mp-MRI. Field Strength T 2 -weighted, diffusion-weighted imaging with a 3.0T MR scanner. Assessment Candidate predictors included age, prostate-specific antigen, clinical stage, biopsy Gleason score (GS), and mp-MRI findings, ie, tumor location, Prostate Imaging and Reporting and Data System (PI-RADS) score, diameter (D-max), and 6-point MR stage. The PartinMR model with combination of a Partin table and mp-MRI findings was developed using SVM and 5-fold crossvalidation analysis. Statistical Tests The predicted ability of the PartinMR model was compared with a standard Partin and a modified Partin table (mPartin) which used for mp-MRI staging. Statistical tests were made by area under receiver operating characteristic curve (AUC), adjusted proportional hazard ratio (HR), and a cost-effective benefit analysis. Results The rate of OCPCA at prostatectomy was 46.4% (251/541). Using MR staging, mPartin table (AUC, 0.814, 95% confidence interval [CI]: 0.779–0.846, P  = 0.001) is appreciably better than the Partin table (AUC, 0.730, 95% CI: 0.690–0.767). Contrarily, adding all MR variables, the PartinMR model (AUC, 0.891, 95% CI: 0.884–0.899, P  〈 0.001) outperformed any other scheme, with 79.3% sensitivity, 75.7% specificity, 79% positive predictive value, and 76.0% negative predictive value for OCPCA. MR stage represented the most influential predictor of extracapsular extension (HR, 2.77, 95% CI: 1.54–3.33), followed by D-max (2.01, 95% CI: 1.31–2.68), biopsy GS (1.64, 95% CI: 1.35–2.12), and PI-RADS score (1.21, 95% CI: 1.01–1.98). Data Conclusion The new PartinMR model is superior to the conventional Partin table for OCPCA. Clinical implications of mp-MRI for prostate cancer stage must be confirmed in further trials. Level of Evidence : 3 Technical Efficacy : Stage 2 J. Magn. Reson. Imaging 2018.
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  • 7
    Publication Date: 2018-04-06
    Description: Entropy, Vol. 20, Pages 254: Multiple Sclerosis Identification Based on Fractional Fourier Entropy and a Modified Jaya Algorithm Entropy doi: 10.3390/e20040254 Authors: Shui-Hua Wang Hong Cheng Preetha Phillips Yu-Dong Zhang Aim: Currently, identifying multiple sclerosis (MS) by human experts may come across the problem of “normal-appearing white matter”, which causes a low sensitivity. Methods: In this study, we presented a computer vision based approached to identify MS in an automatic way. This proposed method first extracted the fractional Fourier entropy map from a specified brain image. Afterwards, it sent the features to a multilayer perceptron trained by a proposed improved parameter-free Jaya algorithm. We used cost-sensitivity learning to handle the imbalanced data problem. Results: The 10 × 10-fold cross validation showed our method yielded a sensitivity of 97.40 ± 0.60%, a specificity of 97.39 ± 0.65%, and an accuracy of 97.39 ± 0.59%. Conclusions: We validated by experiments that the proposed improved Jaya performs better than plain Jaya algorithm and other latest bioinspired algorithms in terms of classification performance and training speed. In addition, our method is superior to four state-of-the-art MS identification approaches.
    Electronic ISSN: 1099-4300
    Topics: Chemistry and Pharmacology , Physics
    Published by MDPI Publishing
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  • 8
    Publication Date: 2014-09-13
    Description: Background: Laparoscopy-assisted low anterior resection (LAR) of colorectal cancer, using a posterior surgical approach, is a difficult and controversial procedure to perform. We report successful operations on 13 patients with clear surgical margins and no serious complications. Methods: Thirteen patients [10 males and three females, age range: 48 to 69 years (median: 61 years)] with low adenocarcinoma confirmed by preoperative colonoscopic biopsy (four stage T1; nine stage T2) were resected. The distance from inferior edge of tumor to dentate line was 2 ~ 5 cm (average: 3.4 cm). Intraperitoneal laparoscopy was performed to isolate rectosigmoid and mesocolon moving toward distal end of the tumor. Perineal operation was performed in the prone clasp-knife position. Results: The circumferential resection margin (CRM) was negative in all cases. No serious postoperative complications occurred. There were four cases of perineal wound infection, two cases with superficial perineal wound dehiscence, and two cases with persistent postoperative sacral pain. All 13 patients passed the Wexner continence test and had satisfactory anal function during a mean 18-month postoperative follow-up period. Conclusion: Laparoscopic posterior LAR of colorectal cancer is a safe and reliable treatment for patients with low colorectal cancer, increasing the chance of anal functional recovery.Trial registration: Chinese Clinical Trial Register ChiCTR-ONC-14005145. Registered 19 August 2014.
    Electronic ISSN: 1471-230X
    Topics: Medicine
    Published by BioMed Central
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  • 9
    Publication Date: 2016-07-02
    Description: Purpose To investigate the physiopathological effects of low- and iso-osmolar contrast media (CM) on renal function with physiologic MRI and histologic-gene examination. Materials and Methods Forty-eight rats underwent time-course DWI and DCE-MRI at 3.0 Tesla (T) before and 5–15 min after exposure of CM or saline (Iop.370: 370 mgI/mL iopromide; Iod.320: 320 mgI/mL iodixanol; Iod.270: 270 mgI/mL iodixanol; 4 gI/kg body weight). Intrarenal viscosity was reflected by apparent diffusion coefficient (ADC). Renal physiologies were evaluated by DCE-derived glomerular filtration rate (GFR), renal blood flow (RBF), and renal blood volume (RBV). Potential acute kidney injury (AKI) was determined by histology and the expression of kidney injury molecule 1 (Kim-1). Results Iop.370 mainly increased ADC in inner-medulla (△ADC IM : 12.3 ± 11.1%; P  〈 0.001). Iod.320 and Iod.270 mainly decreased ADC in outer-medulla (△ADC IM ; Iod.320: 16.8 ± 7.5%; Iod.270: 18.1 ± 9.5%; P  〈 0.001) and inner-medulla (△ADC IM ; Iod.320: 28.4 ± 9.3%; Iod.270: 30.3 ± 6.3%; P  〈 0.001). GFR, RBF and RBV were significantly decreased by Iod.320 (△GFR: 45.5 ± 24.1%; △RBF: 44.6 ± 19.0%; △RBV: 35.2 ± 10.1%; P  〈 0.001) and Iod.270 (33.2 ± 19.0%; 38.1 ± 15.6%; 30.1 ± 10.1%; P  〈 0.001), while rarely changed by Iop.370 and saline. Formation of vacuoles and increase in Kim-1 expression was prominently detected in group of Iod.320, while rarely in Iod.270 and Iop.370. Conclusion Iso-osmolar iodixanol, given at high-dose, produced prominent AKI in nonhydrated rats. This renal dysfunction could be assessed noninvasively by physiologic MRI. J. Magn. Reson. Imaging 2016.
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  • 10
    Publication Date: 2016-09-22
    Description: Purpose To assess a magnetic resonance imaging (MRI)-based nomogram in the prediction of prostate cancer (PCa) biochemical recurrence (BCR) within 3 years after prostatectomy. Materials and Methods Between 2009 and 2013, 205 patients with biopsy-confirmed PCa had MRI before prostatectomy. BCR was defined as a PSA failure (〉0.2 ng/ml) after prostatectomy. MR features (cancer location, diameter, apparent diffusion coefficients [ADCs], PI-RADS v2 score, dynamic contrast-enhanced [DCE] type, and MR T-stage) were retrospectively evaluated for predicting 3-year BCR based on partial least square regression analysis. Second, imaging features were added to a popularized D'Amico and CAPRA scheme to determine imaging contribution to published nomograms. Lastly, a multivariable Cox regression analysis was employed to determine the independent risk factors of time to BCR. Results Three-year BCR rate (median follow-up of 44.9 mo) was 25.4% (52/205). The area under receiver operating characteristic (ROC) curve (Az) for MR nomogram (0.909, 95% confidence interval [CI]: 0.861–0.944) was higher than popularized D'Amico (0.793, 95% CI: 0.731–0.846, P = 0.001) and CAPRA (0.809, 95% CI: 0.748–0.860, P = 0.001). The performance of D'Amico (Az: 0.901, 95% CI: 0.852–0.938, P 〈 0.001) and CAPRA (Az: 0.894, 95% CI: 0.843–0.932, P = 0.004) was significantly improved by adding MR findings. Tumor ADCs (hazard ratio [HR] = 1.747; P = 0.011), PI-RADS score (HR = 4.123; P = 0.039), pathological Gleason score (HR = 3.701; P = 0.004), and surgical-T3b (HR = 6.341; P 〈 0.001) were independently associated with time to BCR. Conclusion Multiparametric MRI, when converted into a prognostic nomogram, can predict the clinical outcome in patients with PCa after prostatectomy. Level of Evidence: 3 J. Magn. Reson. Imaging 2016
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