Physics in medicine and biology最新文献

{"title":"IPEM topical report: guidance for the use of linac manufacturer integrated quality control.","authors":"Michael Pearson, Michael P Barnes, Kirstie F Brown, Richard Delany, Simon W Stevens, Rakesh Kizhakke Veetil, Steven Weston, J R Whitbourn","doi":"10.1088/1361-6560/adc8f7","DOIUrl":"10.1088/1361-6560/adc8f7","url":null,"abstract":"<p><p>This report provides guidance for users of linear accelerator (linac) manufacturer integrated quality control (MIQC) tools. MIQC tools have been developed and introduced by radiotherapy linac vendors, and have the potential to improve both the quality and efficiency of linac quality control (QC). They usually utilise the Electronic Portal Imaging Device (EPID), but may acquire data from other sources, and automatically perform and analyse tests of various treatment machine QC parameters. The currently available systems meeting this definition are Varian machine performance check, CyberKnife automated quality assurance /end-to-end, TomoTherapy Quality Assurance, and Elekta machine QA (also known as AQUA). This guidance report covers the commissioning and implementation of MIQC. The guidance has been developed by a radiotherapy special interest group working party on behalf of the Institute of Physics and Engineering in Medicine. Recommendations within the report are derived from the experience of the working party members, existing guidance, literature, and a United Kingdom survey conducted in 2022 (Pearson<i>et al</i>2023<i>Phys. Med. Biol.</i><b>68</b>245018). Topics covered include developing an understanding of the QC system, independence review of MIQC, commissioning, implementation, ongoing QC and calibration, software upgrades and periodic review. The commissioning section covers detector commissioning, repeatability and reproducibility, baseline and tolerance setting, concordance with existing QC, sensitivity testing, cost-benefits analysis, and risk assessment methods. In order to offer practical guidance, case studies covering each aspect of commissioning are included. They are real-world examples or experiences from early adopters, each applied to a different example MIQC system. The examples will be directly applicable to users of that specific MIQC system, but also provide practical guidance on clinical implementation to users of the other systems.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-view collaborative ensemble classification for EEG signals based on 3D second-order difference plot and CSP.","authors":"Yu Pang, Xiaoling Wang, Ze Zhao, Changqing Han, Nuo Gao","doi":"10.1088/1361-6560/adcafa","DOIUrl":"https://doi.org/10.1088/1361-6560/adcafa","url":null,"abstract":"<p><p><i>Objective.</i>EEG signal analysis methods based on electrical source imaging (ESI) technique have significantly improved classification accuracy and response time. However, for the refined and informative source signals, the current studies have not fully considered their dynamic variability in feature extraction and lacked an effective integration of their dynamic variability and spatial characteristics. Additionally, the adaptability and complementarity of classifiers have not been considered comprehensively. These two aspects lead to the issue of insufficient decoding of source signals, which still limits the application of brain-computer interface (BCI). To address these challenges, this paper proposes a multi-view collaborative ensemble classification method for EEG signals based on three-dimensional second-order difference plot (3D SODP) and common spatial pattern.<i>Approach.</i>First, EEG signals are mapped to the source domain using the ESI technique, and then the source signals in the region of interest are obtained. Next, features from three viewpoints of the source signals are extracted, including 3D SODP features, spatial features, and the weighted fusion of both. Finally, the extracted multi-view features are integrated with subject-specific sub-classifier combination, and a voting mechanism is used to determine the final classification.<i>Main results.</i>The results show that the proposed method achieves classification accuracy of 81.3% and 82.6% respectively in two sessions of the OpenBMI dataset, which is nearly 5% higher than the state-of-the-art method, and maintains the analysis response time required for online BCI.<i>Significance.</i>This paper employs multi-view feature extraction to fully capture the characteristics of the source signals and enhances feature utilization through collaborative ensemble classification. The results demonstrate high accuracy and robust performance, providing a novel approach for online BCI.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":"70 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144029198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity of a deep-learning-based breast cancer risk prediction model.","authors":"Zan Klanecek, Yao-Kuan Wang, Tobias Wagner, Lesley Cockmartin, Nicholas Marshall, Brayden Schott, Ali Deatsch, Andrej Studen, Katja Jarm, Mateja Krajc, Miloš Vrhovec, Hilde Bosmans, Robert Jeraj","doi":"10.1088/1361-6560/adc9f8","DOIUrl":"10.1088/1361-6560/adc9f8","url":null,"abstract":"<p><p><i>Objective.</i>When it comes to the implementation of deep-learning based breast cancer risk (BCR) prediction models in clinical settings, it is important to be aware that these models could be sensitive to various factors, especially those arising from the acquisition process. In this work, we investigated how sensitive the state-of-the-art BCR prediction model is to realistic image alterations that can occur as a result of different positioning during the acquisition process.<i>Approach.</i>5076 mammograms (1269 exams, 650 participants) from the Slovenian and Belgium (University Hospital Leuven) Breast Cancer Screening Programs were collected. The Original MIRAI model was used for 1-5 year BCR estimation. First, BCR was predicted for the original mammograms, which were not changed. Then, a series of different image alteration techniques was performed, such as swapping left and right breasts, removing tissue below the inframammary fold, translations, cropping, rotations, registration and pectoral muscle removal. In addition, a subset of 81 exams, where at least one of the mammograms had to be retaken due to inadequate image quality, served as an approximation of a test-retest experiment. Bland-Altman plots were used to determine prediction bias and 95% limits of agreement (LOA). Additionally, the mean absolute difference in BCR (Mean AD) was calculated. The impact on the overall discrimination performance was evaluated with the AUC.<i>Results.</i>Swapping left and right breasts had no impact on the predicted BCR. The removal of skin tissue below the inframammary fold had minimal impact on the predicted BCR (1-5 year LOA: [-0.02, 0.01]). The model was sensitive to translation, rotation, registration, and cropping, where LOAs of up to ±0.1 were observed. Partial pectoral muscle removal did not have a major impact on predicted BCR, while complete removal of pectoral muscle introduced substantial prediction bias and LOAs (1 year LOA: [-0.07, 0.04], 5 year LOA: [-0.06, 0.03]). The approximation of a real test-retest experiment resulted in LOAs similar to those of simulated image alterations. None of the alterations impacted the overall BCR discrimination performance; the initial 1 year AUC (0.90 [0.88, 0.92]) and 5 year AUC (0.77 [0.75, 0.80]) remained unchanged.<i>Significance.</i>While tested image alterations do not impact overall BCR discrimination performance, substantial changes in predicted 1-5 year BCR can occur on an individual basis.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143803995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On energy dependency, spectral properties, and orientation dependency of EBT3, EBT-XD, MD-V3, and HD-V2 radiochromic films.","authors":"Arash Darafsheh","doi":"10.1088/1361-6560/adcafc","DOIUrl":"https://doi.org/10.1088/1361-6560/adcafc","url":null,"abstract":"<p><p><i>Objective</i>. Radiochromic films (RCFs) are indispensable dosimeters for two-dimensional and small field dosimetry. Different models of RCFs with associated dynamic ranges are commercially available to support various dosimetry needs. Here, we study energy dependency, absorption spectra, and orientation dependency of EBT3, EBT-XD, MD-V3, and HD-V2 RCFs.<i>Approach</i>. RCF pieces were irradiated at various dose levels, depending on their dynamic range, using a 6 MV photon beam and a 220 kVp x-ray beam. Films were scanned using a flatbed scanner to obtain the optical density at red, green, and blue color channels. A visible spectrometer was used to measure the absorption spectra of the films. A subset of RCF pieces were scanned at various orientation to investigate the orientation dependency.<i>Main results</i>. In all four models an under-response to the kV beam was observed compared to the MV beam. A noticeable dose-dependent shift in the peak absorption spectrum was noted in MD-V3 and HD-V2 films. An orientation dependency was noted in all models which can be modeled by assuming a polarization axis in the films.<i>Significance</i>. The presented work provides valuable information on the characteristics of different models of RCF.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":"70 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144025660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum: Effect of interstitial fluid pressure on shear wave elastography: an experimental and computational study (2024<i>Phys. Med. Biol.</i>69075001).","authors":"Ariana Cihan, Kristyna Holko, Luxi Wei, Hendrik J Vos, Charlotte Debbaut, Annette Caenen, Patrick Segers","doi":"10.1088/1361-6560/adc9f7","DOIUrl":"https://doi.org/10.1088/1361-6560/adc9f7","url":null,"abstract":"","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":"70 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144025285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Penumbra-effect induced spectral mixing in x-ray computed tomography: a multi-ray spectrum estimation model and subsampled weighting algorithm.","authors":"Yifan Deng, Hao Zhou, Hewei Gao","doi":"10.1088/1361-6560/adc96f","DOIUrl":"10.1088/1361-6560/adc96f","url":null,"abstract":"<p><p><i>Objective.</i>With the development of spectral CT, various spectral imaging technologies have been proposed. Among these, filter-based spectral imaging methods have been greatly advanced in recent years, such as split filters used in clinical diagnose, spectral modulators studied for spectral imaging and scatter correction. However, due to the finite size of the focal spot of x-ray source, spectral filters cause spectral mixing in the penumbra region. Traditional spectrum estimation methods fail to account for it, resulting in reduced spectral accuracy. To address this challenge, we develop a multi-ray spectrum estimation model and propose an Adaptive Subsampled WeIghting of Filter Thickness (A-SWIFT) method.<i>Approach.</i>First, we estimate the unfiltered spectrum using traditional methods. Next, we model the final spectra as a weighted summation of spectra attenuated by multiple filters. The weights and equivalent lengths are obtained by x-ray transmission measurements taken with altered spectra using different kVp or flat filters. Finally, the spectra are approximated by using the multi-ray model. To mimic the penumbra effect, we used a spectral modulator (0.2 mm Mo, 0.6 mm Mo), a split filter (0.07 mm Au, 0.7 mm Sn), and the abdominal images of an XCAT phantom in simulations; in experiments, we used spectral modulators made by molybdenum or copper along with a pure water phantom, a Gammex multi-energy CT phantom and a Kyoto chest phantom for validation.<i>Main results.</i>Simulation results show that the mean energy bias in the penumbra region decreased from 7.43 keV using the previous Spectral Compensation for Modulator (SCFM) method to 0.72 keV using the A-SWIFT method for the split filter, and from 1.98 keV to 0.61 keV for the spectral modulator. In physics experiments, for the pure water phantom with a molybdenum modulator, the average error of the mean values (ERMSE) in selected regions of interests decreased from 77 to 7 Hounsfield units (HU) using the A-SWIFT method compared with SCFM method; for the Gammex phantom,ERMSEin iodine images was 0.2 mg ml^-1using A-SWIFT method, and 1.5 mg ml^-1using SCFM method; for the chest phantom with an added 5 mg ml^-1iodine cylinder, the estimated material density of the iodine inserts was 5.0 mg ml^-1using A-SWIFT method, and 5.9 mg ml^-1using SCFM method.<i>Significance.</i>Based on a multi-ray spectrum estimation model, the A-SWIFT method provides an accurate and robust spectrum estimation in the penumbra region, contributing to enhanced spectral imaging performance of CT systems utilizing spectral filters.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of manufacturing tolerances on Monte Carlo calculatedkQ,Q0factors for plane-parallel ionisation chambers in proton beams.","authors":"Guillaume Houyoux, Sébastien Penninckx, Séverine Rossomme, Kevin Souris, Hugo Palmans, Nick Reynaert","doi":"10.1088/1361-6560/adc86b","DOIUrl":"10.1088/1361-6560/adc86b","url":null,"abstract":"<p><p><i>Objective.</i>In the recent update of the TRS-398 Code of Practice (CoP), Monte Carlo results were incorporated into the derivation of recommended beam quality correction factors for ionisation chambers (IC) in proton beams. While the underlying Monte Carlo simulations implement detailed models only based on the nominal geometries from manufacturer blueprints, this paper considers the potential geometric deviations in plane-parallel IC arising from manufacturing tolerances that can reach 10%.<i>Approach.</i>A representative model of a plane-parallel IC has been designed using the Monte Carlo code GATE/Geant4, from which beam quality correction factors have been derived. Subsequently, the results of a reference geometry are compared to those of perturbed geometries, in which the parameters are modified according to the tolerances specified in a standard.<i>Main results.</i>The comparison between the reference and perturbed geometries reveals no significant differences, as they show an agreement within one standard deviation for all the cases studied, with relative deviations not exceeding 0.5%. From these results, we estimate the maximum added uncertainty from manufacturing tolerances on Monte Carlo calculated<i>k_Q</i>factors to be about 0.7%.<i>Significance.</i>Overall, the current use of nominal dimensions of plane-parallel IC from manufacturer's blueprints remains consistent for beam quality correction factor calculations via Monte Carlo simulations, which therefore support the latest results recommended by the TRS-398 CoP.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143772959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards improved prescription metrics in novel radiotherapy techniques: a machine learning study.","authors":"Alfredo Fernandez-Rodriguez, Yolanda Prezado","doi":"10.1088/1361-6560/adc96c","DOIUrl":"10.1088/1361-6560/adc96c","url":null,"abstract":"<p><p><i>Objective.</i>FLASH radiotherapy (RT), microbeam RT (MRT) and minibeam RT (MBRT) are novel RT techniques that have been shown to reduce normal tissue complication probabilities, by modulating the dose distributions through different parameters in space and time. This study aims to investigate the importance of these parameters for predicting biological outcomes using a machine learning (ML) approach and to compare the findings with previous correlation analyses in the context of the current understanding of these techniques.<i>Approach.</i>A ML algorithm was trained for predicting normal tissue toxicity, tumor control and increased lifespan (ILS) quantitative metrics on published datasets of preclinical MRT, MBRT and FLASH RT data. The influence of different variables on the performance of the model over unseen data was quantified, and their importance on its predictive power was ranked.<i>Main results.</i>An accuracy of 70% or superior was achieved for the prediction of most metrics, reduced for normal tissue toxicity to 60% in MBRT and 40% in FLASH RT. In MRT, valley dose was found as the most influencing physical parameter for normal tissue sparing, while in MBRT the peak dose was highlighted as one of the most influential parameters. Valley dose showed the greatest impact over ILS in a conjoint study of both techniques. In FLASH RT, the total dose, along with the tissue characteristics, were identified as the most influencing variables for tumor control and normal tissue toxicity. The importance of dose rate increased when considering therapeutic index.<i>Significance.</i>These results agree with previous studies that highlight how dose heterogeneity prevents normal tissue damage in MBRT and MRT and the need of prescribing under critical tissue specific valley and peak dose values respectively for optimal sparing and tumor control. The described findings are also consistent with FLASH RT tumor control being driven by the same mechanisms as in conventional RT.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A dual-branch hybrid network with bilateral-difference awareness for collateral scoring on CT angiography of acute ischemic stroke patients.","authors":"Hulin Kuang, Bin Hu, Wenfang Wan, Shulin Liu, Shuai Yang, Weihua Liao, Li Yuan, Guanghua Luo, Wu Qiu","doi":"10.1088/1361-6560/adc8f5","DOIUrl":"10.1088/1361-6560/adc8f5","url":null,"abstract":"<p><p><i>Objective.</i>Acute ischemic stroke (AIS) patients with good collaterals tend to have better outcomes after endovascular therapy. Existing collateral scoring methods rely mainly on vessel segmentation and convolutional neural networks (CNNs), often ignoring bilateral brain differences. This study aims to develop an automated collateral scoring model incorporating bilateral-difference awareness to improve prediction accuracy.<i>Approach.</i>In this paper, we propose a new dual-branch hybrid network to achieve vessel-segmentation-free collateral scoring on the CT Angiography (CTA) of 255 AIS patients. Specifically, we first adopt a data preprocessing method based on maximum intensity projection. To capture the differences between the left and right sides of the brain, we propose a novel bilateral-difference awareness module (BDAM). Then we design a hybrid network that consists of a multi-scale module, a CNN branch, a transformer branch and a feature interaction enhancement module in each stage. In addition, to learn more effective features, we propose a novel local enhancement module and a novel global enhancement module (GEM) to strengthen the local features captured by the CNN branch and the global features of the transformer branch, respectively.<i>Main results.</i>Experiments on a private clinical dataset with CTA images of 255 AIS patients show that our proposed method achieves an accuracy of 85.49% and an intraclass correlation coefficient of 0.9284 for 3-point collateral scoring, outperforming 13 state-of-the-art methods. Besides, for the binary classification tasks (good vs. non-good collateral scoring, poor vs. non-poor collateral scoring), our proposed method also achieves the best accuracies (89.02% and 92.94%).<i>Significance.</i>In this paper, we propose a novel dual-branch hybrid network that incorporates distinct local and GEMs, along with a BDAM, to achieve collateral scoring without the need for vessel segmentation. Our experimental evaluation shows that our model achieves state-of-the-art performance, providing valuable support for improving the efficiency of stroke treatment.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reference dosimetry for MRI-Linacs: an addendum to the 2020 IPEM code of practice for high-energy photon therapy dosimetry.","authors":"Ilias Billas, Geoff Budgell, Ben George, Russell A S Thomas, Simon Duane, David J Eaton","doi":"10.1088/1361-6560/adc0e0","DOIUrl":"10.1088/1361-6560/adc0e0","url":null,"abstract":"<p><p>The 2020 Institute of Physics and Engineering in Medicine code of practice (COP) for megavoltage dosimetry (<i>Eaton et al</i>2020<i>Phys. Med. Biol.</i><b>65</b>195006) provides standardised and practical methods for measurement of absorbed dose to water, linked to calibration by the National Physical Laboratory. This report extends the use of that COP to MRI-Linacs through the addition of two correction factors: (1) to account for the influence of the magnetic field on the absorbed dose and model-specific chamber response; and (2) to account for differences in chamber response in the beam spectrum of the MRI-Linac and the Linac where the cross-calibration is performed. Guidance is provided on practical aspects of chamber calibration and dose measurement in MRI-Linac beams, including the use of liquid water, consistent chamber orientation and corrections for other influence quantities. Using this approach uncertainties are similar to other applications of the COP.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}