Physical and Engineering Sciences in Medicine最新文献

{"title":"The declaration of Adelaide white paper: guidelines for author responsibility in peer review.","authors":"Loredana G Marcu, Chris Clement, Anna Friedl, Richard Harbron, Werner Rühm, Magdalena Stoeva, Michael Thorne, Iuliana Toma-Dasu, Jamie Trapp, Andrzej Wojcik, Gayle Woloschak","doi":"10.1007/s13246-026-01754-y","DOIUrl":"10.1007/s13246-026-01754-y","url":null,"abstract":"","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1115-1117"},"PeriodicalIF":2.4,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148649488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transfer of fractionated treatment plans from ring-gantry to L-shaped linacs using fluence map convolution.","authors":"Sirikarn Songyen, Wilai Masanga, Thunpisit Mundee, Chirapha Tannanonta, Sangutid Thongsawad","doi":"10.1007/s13246-026-01761-z","DOIUrl":"10.1007/s13246-026-01761-z","url":null,"abstract":"<p><p>Transferring treatment plans from a ring-gantry Ethos system to a standard L-shaped linear accelerator (linac), such as TrueBeam, is often a time-consuming and labor-intensive process, requiring repeated optimization steps. This study proposes a novel method for converting Ethos IMRT plans to TrueBeam IMRT plans using Fluence Map Generation (FMG) based on a fluence map convolution approach, intended to minimize treatment delays in the event of Ethos downtime. The FMG method comprises three key steps: determining an optimal convolution kernel, generating fluence maps from Ethos plans, and applying 2D convolution to simulate corresponding TrueBeam fluence maps. Forty original Ethos IMRT plans were used to validate the FMG approach, and the number of transferable fractions for each converted plan was evaluated. The FMG method successfully generated a moderate number of transferable fractions, ranging from one to six. The FMG-generated plans showed comparable dose distributions between the cumulative dose (FMG + Original) and the original Ethos plans (Original). This FMG-based conversion strategy provides a practical solution for converting Ethos IMRT plans to TrueBeam IMRT plans, helping mitigate treatment interruptions and reduce the clinical workload associated with plan re-optimization.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1511-1524"},"PeriodicalIF":2.4,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148438351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The use of Perspex-based devices in patient specific quality assurance of Acuros XB plans.","authors":"Ali N Noon, Daniel Truant, Izabela Junis, Jeffrey Barber","doi":"10.1007/s13246-026-01779-3","DOIUrl":"10.1007/s13246-026-01779-3","url":null,"abstract":"<p><p>A transition from the dose-to-water algorithm AAA to the dose-to-medium algorithm Acuros XB (AXB) presents challenges for comparison with measurements made in the dose-to-water calibrated ArcCHECK. This study evaluates the implications of this transition on patient-specific quality assurance (PSQA) measurements. A modified dose-medium calibration for the ArcCHECK to was introduced to address these limitations, by developing a formalism to compare ionisation chamber measurements to water-like plastics such as Perspex to AXB dose-to-medium calculations. A retrospective analysis was conducted on 40 VMAT plans: 5 prostate, 5 cervix, 10 head/neck, 10 lung (5 standard VMAT, 5 SBRT), and 10 breast. Plans were recalculated in AXB using a Perspex-assigned ArcCHECK phantom and compared with dose-to-water and dose-to-medium calibrated ArcCHECK measurements with a γ (3%,2 mm) criteria. Only one of 35 non-SBRT AXB dose-to-medium plans was within clinical tolerance during dose-to-water calibrated ArcCHECK comparisons, compared to 33 of 35 AAA dose-to-water plans. Applying the proposed dose-to-medium calibration improved results, with 30 of 35 AXB plans performing within tolerance. In the SBRT lung cases, no AXB dose-to-medium plans passed ArcCHECK gamma comparisons, compared to four out of five AAA plans. Applying the dose-to-medium calibration to the ArcCHECK did not improve the passing rates, suggesting limitations of AXB calculations on the ArcCHECK device. This study highlights the inadequacy of dose-to-water calibrated PSQA devices for verifying AXB dose-to-medium calculations and demonstrates practical solutions, including applying a dose-to-medium calibration for the ArcCHECK for AXB PSQA applications.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1757-1766"},"PeriodicalIF":2.4,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148763182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep unrolled regularization for limited-angle dual-panel positron emission mammography.","authors":"Fernando Moncada-Gutiérrez, Héctor Alva-Sánchez, Mercedes Rodríguez-Villafuerte, Arnulfo Martínez-Dávalos","doi":"10.1007/s13246-026-01769-5","DOIUrl":"10.1007/s13246-026-01769-5","url":null,"abstract":"<p><p>A dual-panel Positron Emission Mammography (PEM) scanner is a breast-dedicated device with better spatial resolution and sensitivity than conventional Positron Emission Tomography (PET). However, the main limitation of dual-panel PEM is the limited-angle artifacts in the cross-plane slices of the reconstructed images, arising from the acquisition geometry. This work proposes incorporating deep unrolled regularization into the image reconstruction algorithm to mitigate these artifacts. A U-Net was trained to identify and correct the artifacts in cross-plane slices. Dual-panel PEM and ring-shaped dedicated breast PET Monte Carlo (MC)-generated images served as the input and ground truth, respectively; the latter was selected because it provides an artifact-free reference due to its full-angle geometry. Data augmentation was employed to expand the training dataset to 3840 image pairs, thereby improving the model's generalization performance. The trained deep learning model was incorporated into the Forward-Backward Splitting Expectation-Maximization algorithm to regularize reconstruction and ensure agreement between the reconstructed images and the measured data. Images reconstructed with the proposed image reconstruction framework exhibited effective mitigation of limited-angle artifacts using MC-generated and experimentally measured data from a dual-panel PEM. Additionally, this framework outperformed OSEM and MAPEM as measured by metrics quantifying noise, contrast, peak-to-valley ratio, recovery coefficients, spillover ratios, and intensity profiles. To the best of our knowledge, this is the first study to address limited-angle artifacts in a dual-panel PEM incorporating deep learning-based regularization. At this stage, the present work constitutes a proof-of-concept; for clinical implementation, a model trained on anthropomorphic phantoms and further validation are required.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1595-1610"},"PeriodicalIF":2.4,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13638748/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148680555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proposing diagnostic reference levels for paediatric computed tomography in Jordan: a national multicentre analysis.","authors":"Abdel-Baset Bani Yaseen, Jamie Trapp, Davide Fontanarosa","doi":"10.1007/s13246-026-01731-5","DOIUrl":"10.1007/s13246-026-01731-5","url":null,"abstract":"<p><p>Children are more radiosensitive than adults, making dose optimisation in paediatric computed tomography (CT) essential. Although Diagnostic Reference Levels (DRLs) are internationally recommended as optimisation tools, national DRLs for paediatric CT in Jordan remain limited and outdated. This study aimed to establish national DRLs for six paediatric CT protocols, evaluate inter-hospital and age-related dose variations, and compare results with international benchmarks. A retrospective multicentre study was conducted across six Jordanian hospitals between December 2023 and September 2025, including 3794 paediatric patients stratified into four age groups (< 1, 1-4, 5-10, and 11-18 years). Volumetric CT dose index (CTDI_vol) and dose-length product (DLP) data were collected for six protocols: brain, chest, abdomen-pelvis, chest-abdomen-pelvis, sinuses, and contrast-enhanced neck soft tissue. DRLs were defined as the 75th percentile of institutional median CTDI_vol and DLP values. Inter-hospital and age group variations were analysed, and univariable regression analyses assessed acquisition parameters associated with dose variation. Dose increased with patient age for trunk protocols, whereas brain, sinuses, and neck CT showed comparatively stable patterns. Substantial inter-hospital variability was observed across protocols, with institutional median CTDIvol differing markedly between centres, particularly for trunk examinations in younger age groups. In univariable regression analyses, all four acquisition parameters (kVp, mAs, pitch, and slice thickness) were significantly associated with CTDI_vol and DLP (p ≤ 0.001), with kVp demonstrating the strongest association (R² = 0.603 for CTDI_vol; R² = 0.630 for DLP). Compared with published international DRLs, Jordanian brain CT dose metrics were higher in multiple age groups; chest comparisons should be interpreted cautiously where international benchmarks are weight-banded. This study established national paediatric CT DRLs for Jordan, highlighting the need for standardised protocols and periodic DRL review to enhance radiation protection.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1179-1190"},"PeriodicalIF":2.4,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13638739/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147575899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of an automated diagnostic display quality assurance program.","authors":"Timothy Ireland, Daniel Serra","doi":"10.1007/s13246-026-01804-5","DOIUrl":"https://doi.org/10.1007/s13246-026-01804-5","url":null,"abstract":"<p><p>The diagnostic accuracy of medical imaging is critically dependent on the performance of primary diagnostic displays. However, quality assurance (QA) programs for these displays are often limited by geographic dispersion, manual testing requirements, and inconsistent calibration practices. This study evaluates the implementation of a centralised, automated QA program aligned with AAPM Task Group 270 (TG-270) recommendations across a large health service. A four-stage process was used to assess and improve the performance of 53 diagnostic displays. This included baseline QC evaluation, internal photometer and ambient light sensor accuracy testing, implementation of a cloud-based automated QC system, and post-intervention performance testing. Internal photometers were cross-calibrated using a traceable external photometer. Initial testing revealed that 53% (28/53) of internal photometers exhibited errors >10% relative to a calibrated external photometer. As found, 67% (30/45) of connected displays reported meeting their existing QC tolerances; however, after cross-calibrating the internal photometers and repeating the same tests, only 9% (4/45) actually met those tolerances, indicating that most displays had been falsely reporting compliance. After implementing the automated program with recalibrated sensors and updated TG-270-aligned tolerances, 68% (36/53) of displays met the updated tolerances. Displays failing to meet luminance requirements were found to have high cumulative use hours, highlighting the need for lifecycle management. Automated QA systems significantly improve diagnostic display performance when combined with validated calibration protocols. Internal photometers require periodic cross-calibration to ensure reliable self-assessment. These findings support the adoption of centralised, standards-based QA programs to enhance diagnostic confidence and operational efficiency and highlight the need for defined cross-calibration intervals as part of ongoing program maintenance.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrasound swallowing assessment: the impact of image post-processing on measurement reliability.","authors":"Katharina Winiker, Sruthy Vijayan, Alan Brook, Maggie-Lee Huckabee","doi":"10.1007/s13246-026-01798-0","DOIUrl":"https://doi.org/10.1007/s13246-026-01798-0","url":null,"abstract":"<p><p>The use of ultrasound for swallowing assessment is promising; yet its application has not translated from research into routine clinical practice. While sufficient reliability is key to support implementation, insufficient reliability for swallowing measures has been documented for pocket-sized ultrasound technology. Image quality, a known prerequisite for reliability, may be compromised in small-sized ultrasound technology. This study explored the impact of ultrasound image post-processing on measurement reliability of swallowing parameters. Ultrasound images (n = 30) of hyoid excursion, thyrohyoid approximation, and submental muscles were selected from a database of images previously collected using a pocket-sized ultrasound system in healthy adults. For this pilot study, images were measured at two time points by four raters with and without experience in ultrasound imaging. For those with experience, their engagement with ultrasound was gained in the context of research data collection, rather than daily clinical practice. At both time points, raters measured each image once with and once without the application of an image processing software that was developed to improve image contrast and image features. ICCs were calculated using linear mixed effects analyses to evaluate inter- and intra-rater measurement reliability. Intra- and inter-rater ICCs were similar for processed and unprocessed images for most parameters of interest with a few ICCs being higher or lower for processed images compared to unprocessed images. There is no strong evidence to suggest general beneficial effects of post-processing on ultrasound swallowing measurement reliability. These preliminary pilot data provide a foundation and directions for further research to clarify the role of ultrasound image post-processing for swallowing evaluation. Further refinement of processing methods may produce improved results.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148841607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ACPSEM guideline: recommendations for a fluoroscopic system quality assurance program.","authors":"Mohamed K Badawy, Zoe Brady, Amanda A Perdomo, Benjamin Keir, Kam L Lee, Giles Wynn-Williams, Peter Barnes","doi":"10.1007/s13246-026-01796-2","DOIUrl":"https://doi.org/10.1007/s13246-026-01796-2","url":null,"abstract":"<p><p>Fluoroscopic systems are increasingly used for complex image-guided procedures across medical disciplines in Australia and New Zealand. The associated radiation exposure risks to patients and staff necessitate robust quality assurance (QA) programs. However, no national guidance has previously existed for a standardised fluoroscopy QA program in the Australia and New Zealand context. To provide evidence-informed recommendations for the quality assurance of fluoroscopic systems in Australia and New Zealand, addressing the absence of national standards and supporting consistent, high-quality clinical practice. This guideline was developed by the ACPSEM Fluoroscopy QA Working Group, established in February 2019 by the ACPSEM Radiology Specialty Group. Recommendations were informed by an expert-driven review of international standards and protocols, including those from the AAPM, IAEA, EFOMP, and IEC, adapted for Australia and New Zealand practice through working-group discussions and reviews. The draft guideline underwent stakeholder consultation, including circulation to ACPSEM members and relevant professional organisations. The guideline outlines recommended QA tests for medical physicists at acceptance, commissioning, and periodic intervals, along with routine quality control procedures for radiographers. Key areas include radiation dose output assessment, automatic dose rate control verification, image quality evaluation, personal protective equipment integrity testing, and clinical dose audits. A quality review meeting framework is also provided. This guideline establishes a nationally consistent framework for fluoroscopy QA that complements local regulatory requirements. Its adoption will support patient safety, staff radiation protection, and optimal equipment performance across healthcare facilities in Australia and New Zealand.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148841004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comparative study of vision transformer architectures for the detection of Alzheimer's disease using magnetic resonance images.","authors":"Murat Uçar","doi":"10.1007/s13246-026-01792-6","DOIUrl":"https://doi.org/10.1007/s13246-026-01792-6","url":null,"abstract":"<p><p>Alzheimer's disease is a neurodegenerative disease that affects millions of people worldwide. With the increasing global elderly population, early and accurate diagnosis of the disease is becoming increasingly important to slow its progression and improve patient outcomes. This study aims to present a comprehensive vision transformer-based solution proposal for the accurate and rapid detection of Alzheimer's disease using magnetic resonance images. Nine different transformer-based models, namely Vision Transformer, Pooling-based Vision Transformer, Convolutional Vision Transformer, Crossformer, Cross-attention Vision Transformer, Nested Transformers, Multi-Axis Vision Transformer, Separable Vision Transformer, and MobileViT, were used to analyse their effectiveness in diagnosing the disease in detail. Experimental results have shown that transformer-based architectures exhibit high performance in the detection of Alzheimer's disease. In binary classification results, the Multi-Axis Vision Transformer model stood out from other models by achieving the most successful performance in accuracy, sensitivity, specificity, precision, and f1-score metrics. In multi-class classification results, the Crossformer model provided the highest results in terms of sensitivity, specificity, precision, and f1-score, while the Separable Vision Transformer model was the most successful model in the accuracy metric. Furthermore, it was observed that the Mobile Vision Transformer model produced competitive results, especially in sensitivity and specificity metrics. In conclusion, this study provides a promising framework for the use of vision transformers in neuroimaging, providing an innovative solution for the early diagnosis of Alzheimer's disease.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148841781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting VMAT patient-specific quality assurance outcome using a machine learning workflow.","authors":"Suvankar Das, A Robert Xavier, B Paul Ravindran","doi":"10.1007/s13246-026-01793-5","DOIUrl":"10.1007/s13246-026-01793-5","url":null,"abstract":"<p><p>To develop a machine learning (ML)-based workflow for virtual patient-specific quality assurance (PSQA) to predict local gamma passing rates (GPRs) and QA pass/fail outcomes for Volumetric Modulated Arc Therapy (VMAT) plans. Treatment plan files from 156 double-arc VMAT cases were used, resulting in 312 beam-specific datasets. A total of 48 plan complexity metrics (PCMs), derived from DICOM RT plan files based on the UCoMX framework, were calculated for each arc. Feature selection was performed using a blended ensemble of Random Forest (RF), Gradient Boosting Decision Tree (GBDT), eXtreme Gradient Boost (XGBoost), and linear Support Vector Machine (SVM) models, yielding 15 key predictive features. Regression models using RF, GBDT, XGBoost, SVR, and an averaging ensemble were trained to predict local GPR values. Patient-level grouped train-test splitting and grouped 5-fold cross-validation were employed to prevent data leakage. Classification models were developed using a 90% GPR threshold to predict QA pass/fail outcomes. Model performance was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), ROC-AUC, sensitivity, specificity, Positive Predictive Value (PPV), and Negative Predictive Value (NPV). Among the regression models, GBDT achieved the best overall performance with an MAE of 1.85% points and an RMSE of 2.35% points, followed closely by the averaging ensemble model. Grouped 5-fold cross-validation demonstrated stable regression performance across all models. For classification analysis, grouped 5-fold cross-validation ROC-AUC values ranged from 0.721 to 0.772, with SVM achieving the highest mean cross-validation ROC-AUC. On the independent test dataset, SVM achieved the highest ROC-AUC (0.725) and specificity (0.829), while the averaging ensemble model demonstrated balanced classification performance with improved specificity and PPV. An ML-based workflow for predicting VMAT PSQA outcomes from plan complexity metrics derived from DICOM RT plans has been developed. The results demonstrate the feasibility of predicting QA outcomes with moderate accuracy and provide a framework for further development of ML-assisted PSQA. Future studies incorporating additional plan, delivery, and machine-related features, together with larger multi-institutional datasets, may further improve predictive performance and clinical applicability.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148841462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}