The aluminum shielded room has been an important part of ultra-low-field magnetic resonance imaging （ULF MRI） based on the superconducting quantum interference device （SQUID）. The shielded room is effective to att...The aluminum shielded room has been an important part of ultra-low-field magnetic resonance imaging （ULF MRI） based on the superconducting quantum interference device （SQUID）. The shielded room is effective to attenuate the external radio-frequency field and keep the extremely sensitive detector, SQUID, working properly. A high-performance shielded room can increase the signal-to-noise ratio （SNR） and improve image quality. In this study, a circular coil with a diameter of 50 cm and a square coil with a side length of 2.0 m was used to simulate the magnetic fields from the nearby electric apparatuses and the distant environmental noise sources. The shielding effectivenesses （SE） of the shielded room with different thicknesses of aluminum sheets were calculated and simulated. A room using 6-mm-thick aluminum plates with a dimension of 1.5 m x 1.5 m x 2.0 m was then constructed. The SE was experimentally measured by using three-axis SQUID magnetometers, with tranisent magnetic field induced in the aluminum plates by the strong pre-polarization pulses. The results of the measured SE agreed with that from the simulation. In addition, the introduction of a 0.5-mm gap caused the obvious reduction of SE indicating the importance of door design. The nuclear magnetic resonance （NMR） signals of water at 5.9 kHz were measured in free space and in a shielded room, and the SNR was improved from 3 to 15. The simulation and experimental results will help us design an aluminum shielded room which satisfies the requirements for future ULF human brain imaging. Finally, the cancellation technique of the transient eddy current was tried, the simulation of the cancellation technique will lead us to finding an appropriate way to suppress the eddy current fields.展开更多
BACKGROUND Multiple linear stapler firings during double stapling technique(DST)after laparoscopic low anterior resection(LAR)are associated with an increased risk of anastomotic leakage(AL).However,it is difficult to...BACKGROUND Multiple linear stapler firings during double stapling technique(DST)after laparoscopic low anterior resection(LAR)are associated with an increased risk of anastomotic leakage(AL).However,it is difficult to predict preoperatively the need for multiple linear stapler cartridges during DST anastomosis.AIM To develop a deep learning model to predict multiple firings during DST anastomosis based on pelvic magnetic resonance imaging(MRI).METHODS We collected 9476 MR images from 328 mid-low rectal cancer patients undergoing LAR with DST anastomosis,which were randomly divided into a training set(n=260)and testing set(n=68).Binary logistic regression was adopted to create a clinical model using six factors.The sequence of fast spin-echo T2-weighted MRI of the entire pelvis was segmented and analyzed.Pure-image and clinical-image integrated deep learning models were constructed using the mask region-based convolutional neural network segmentation tool and three-dimensional convolutional networks.Sensitivity,specificity,accuracy,positive predictive value(PPV),and area under the receiver operating characteristic curve(AUC)was calculated for each model.RESULTS The prevalence of≥3 linear stapler cartridges was 17.7%(58/328).The prevalence of AL was statistically significantly higher in patients with≥3 cartridges compared to those with≤2 cartridges(25.0%vs 11.8%,P=0.018).Preoperative carcinoembryonic antigen level>5 ng/mL(OR=2.11,95%CI 1.08-4.12,P=0.028)and tumor size≥5 cm(OR=3.57,95%CI 1.61-7.89,P=0.002)were recognized as independent risk factors for use of≥3 linear stapler cartridges.Diagnostic performance was better with the integrated model(accuracy=94.1%,PPV=87.5%,and AUC=0.88)compared with the clinical model(accuracy=86.7%,PPV=38.9%,and AUC=0.72)and the image model(accuracy=91.2%,PPV=83.3%,and AUC=0.81).CONCLUSION MRI-based deep learning model can predict the use of≥3 linear stapler cartridges during DST anastomosis in laparoscopic LAR surgery.This model might help determine the best anastomosis strategy by avoiding DST when there is a high probability of the need for≥3 linear stapler cartridges.展开更多
Carbon capture,utilization and storage (CCUS) is considered as a very important technology for mitigating global climate change.Carbon dioxide (CO2) injected into an underground reservoir will induce changes in its ph...Carbon capture,utilization and storage (CCUS) is considered as a very important technology for mitigating global climate change.Carbon dioxide (CO2) injected into an underground reservoir will induce changes in its physical properties and the migration of CO2 will be affected by many factors.Accurately understanding these changes and migration characteristics of CO2 is crucial for selecting a CCUS project site,estimating storage capacity and ensuring storage security.In this paper,the basic principles of nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) technologies are briefly introduced in the context of laboratory experiments related to CCUS.The types of NMR apparatus,experimental samples and testing approaches applied worldwide are discussed and analyzed.Then two typical NMR core analysis systems used in CCUS field and a self-developed high-pressure,low-field NMR rock core flooding experimental system are compared.Finally,a summary of the current deficiencies related to NMR applied to CCUS field is given and future research plans are proposed.展开更多
大豆含油率的高低直接影响榨油与育种结果。为探究大豆含油率的最佳检测方法与构建含油率高低判别模型,该研究基于不同维度低场核磁共振(low field nuclear magnetic resonance,LF-NMR)技术,以国标法为对照,利用LF-NMR波谱和LF-NMR含油...大豆含油率的高低直接影响榨油与育种结果。为探究大豆含油率的最佳检测方法与构建含油率高低判别模型,该研究基于不同维度低场核磁共振(low field nuclear magnetic resonance,LF-NMR)技术,以国标法为对照,利用LF-NMR波谱和LF-NMR含油含水率软件检测大豆含油率;核磁共振成像(magnetic resonance imaging,MRI)结合深度学习,建立大豆含油率高低判别模型。引入低场二维核磁共振(low field two-dimensional nuclear magnetic resonance,LF-2D-NMR)技术,定性分析一维波谱中信号重叠无法区分组分的问题。试验结果表明,LF-NMR含油含水率软件能快速准确检测大豆含油率,T1-T2二维核磁图谱成功解决了自由水和油信号重叠问题。利用U-net++深度学习模型对MRI成像的矢状面、冠状面、横截面以及三面混合数据集进行训练,其中横截面评价指标与其他数据集相比更优,语义分割部分中平均交并比(mean intersection over union,mIoU)约0.9058,全局准确率0.9980,训练后的模型能够将MRI图像识别并分割,快速判别大豆含油率高低。试验证明,LF-NMR及MRI能够快速无损掌握大豆含油率信息,为大豆的高油育种提供了新思路和技术支持。展开更多
该文对不同发酵阶段的黄酒样品进行低场核磁共振(low-field nuclear magnetic resonance,LF-NMR)检测,比较了陈酿时间、酒精度和品牌对黄酒低场核磁弛豫特性的影响,最后对9个品牌黄酒的LF-NMR弛豫信息进行了主成分分析。结果表明,发酵...该文对不同发酵阶段的黄酒样品进行低场核磁共振(low-field nuclear magnetic resonance,LF-NMR)检测,比较了陈酿时间、酒精度和品牌对黄酒低场核磁弛豫特性的影响,最后对9个品牌黄酒的LF-NMR弛豫信息进行了主成分分析。结果表明,发酵后样品的单组分弛豫时间(T_(2W))显著缩短,而陈酿后黄酒的T_(2W)又相对延长。多组分弛豫图谱(T_(2))表明,对照组和浸米样品均只有1个峰。发酵后样品的T_(2)图谱均出现2个峰。从第一次发酵到煎酒期间,T_(21)和T_(22)不断缩短,而陈酿期间T_(21)和T_(22)相对延长。同一品牌及陈酿时间的黄酒,酒精度越大,体系的T_(2W),T_(21)和T_(22)越短;同一品牌及酒精度下,陈酿时间仅对T_(21)有一定影响。不同品牌黄酒因酿造工艺的区别而使弛豫分布有一定特点。主成分分析表明,不同酒精度、陈酿时间、品牌及种类的黄酒的弛豫特性的PCA分布及间距不同。说明应用LF-NMR技术可实现对不同工艺生产的黄酒的快速辨别。展开更多
基金Project supported in part by the Strategic Priority Research Program(B)of the Chinese Academy of Sciences(Grant No.XDB04020200)in part by the National Natural Science Foundation of China(Grant No.11204339)
文摘The aluminum shielded room has been an important part of ultra-low-field magnetic resonance imaging （ULF MRI） based on the superconducting quantum interference device （SQUID）. The shielded room is effective to attenuate the external radio-frequency field and keep the extremely sensitive detector, SQUID, working properly. A high-performance shielded room can increase the signal-to-noise ratio （SNR） and improve image quality. In this study, a circular coil with a diameter of 50 cm and a square coil with a side length of 2.0 m was used to simulate the magnetic fields from the nearby electric apparatuses and the distant environmental noise sources. The shielding effectivenesses （SE） of the shielded room with different thicknesses of aluminum sheets were calculated and simulated. A room using 6-mm-thick aluminum plates with a dimension of 1.5 m x 1.5 m x 2.0 m was then constructed. The SE was experimentally measured by using three-axis SQUID magnetometers, with tranisent magnetic field induced in the aluminum plates by the strong pre-polarization pulses. The results of the measured SE agreed with that from the simulation. In addition, the introduction of a 0.5-mm gap caused the obvious reduction of SE indicating the importance of door design. The nuclear magnetic resonance （NMR） signals of water at 5.9 kHz were measured in free space and in a shielded room, and the SNR was improved from 3 to 15. The simulation and experimental results will help us design an aluminum shielded room which satisfies the requirements for future ULF human brain imaging. Finally, the cancellation technique of the transient eddy current was tried, the simulation of the cancellation technique will lead us to finding an appropriate way to suppress the eddy current fields.
基金Shanghai Jiaotong University,No.YG2019QNB24This study was reviewed and approved by Ruijin Hospital Ethics Committee(Approval No.2019-82).
文摘BACKGROUND Multiple linear stapler firings during double stapling technique(DST)after laparoscopic low anterior resection(LAR)are associated with an increased risk of anastomotic leakage(AL).However,it is difficult to predict preoperatively the need for multiple linear stapler cartridges during DST anastomosis.AIM To develop a deep learning model to predict multiple firings during DST anastomosis based on pelvic magnetic resonance imaging(MRI).METHODS We collected 9476 MR images from 328 mid-low rectal cancer patients undergoing LAR with DST anastomosis,which were randomly divided into a training set(n=260)and testing set(n=68).Binary logistic regression was adopted to create a clinical model using six factors.The sequence of fast spin-echo T2-weighted MRI of the entire pelvis was segmented and analyzed.Pure-image and clinical-image integrated deep learning models were constructed using the mask region-based convolutional neural network segmentation tool and three-dimensional convolutional networks.Sensitivity,specificity,accuracy,positive predictive value(PPV),and area under the receiver operating characteristic curve(AUC)was calculated for each model.RESULTS The prevalence of≥3 linear stapler cartridges was 17.7%(58/328).The prevalence of AL was statistically significantly higher in patients with≥3 cartridges compared to those with≤2 cartridges(25.0%vs 11.8%,P=0.018).Preoperative carcinoembryonic antigen level>5 ng/mL(OR=2.11,95%CI 1.08-4.12,P=0.028)and tumor size≥5 cm(OR=3.57,95%CI 1.61-7.89,P=0.002)were recognized as independent risk factors for use of≥3 linear stapler cartridges.Diagnostic performance was better with the integrated model(accuracy=94.1%,PPV=87.5%,and AUC=0.88)compared with the clinical model(accuracy=86.7%,PPV=38.9%,and AUC=0.72)and the image model(accuracy=91.2%,PPV=83.3%,and AUC=0.81).CONCLUSION MRI-based deep learning model can predict the use of≥3 linear stapler cartridges during DST anastomosis in laparoscopic LAR surgery.This model might help determine the best anastomosis strategy by avoiding DST when there is a high probability of the need for≥3 linear stapler cartridges.
基金supported by the Open Research Fund of State Key Laboratory of Geomechanics and GeotechnicalEngineering, IRSM, CAS (Grant No. Z017002)the National Natural Science Foundation of China (Grant Nos. 41872210 and 41274111)financial support from the China-Australia Geological Storage of CO_2 (CAGS) Project funded by the Australian Government under the auspices of the China-Australia Joint Coordination Group on Clean Coal Technology
文摘Carbon capture,utilization and storage (CCUS) is considered as a very important technology for mitigating global climate change.Carbon dioxide (CO2) injected into an underground reservoir will induce changes in its physical properties and the migration of CO2 will be affected by many factors.Accurately understanding these changes and migration characteristics of CO2 is crucial for selecting a CCUS project site,estimating storage capacity and ensuring storage security.In this paper,the basic principles of nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) technologies are briefly introduced in the context of laboratory experiments related to CCUS.The types of NMR apparatus,experimental samples and testing approaches applied worldwide are discussed and analyzed.Then two typical NMR core analysis systems used in CCUS field and a self-developed high-pressure,low-field NMR rock core flooding experimental system are compared.Finally,a summary of the current deficiencies related to NMR applied to CCUS field is given and future research plans are proposed.
文摘大豆含油率的高低直接影响榨油与育种结果。为探究大豆含油率的最佳检测方法与构建含油率高低判别模型,该研究基于不同维度低场核磁共振(low field nuclear magnetic resonance,LF-NMR)技术,以国标法为对照,利用LF-NMR波谱和LF-NMR含油含水率软件检测大豆含油率;核磁共振成像(magnetic resonance imaging,MRI)结合深度学习,建立大豆含油率高低判别模型。引入低场二维核磁共振(low field two-dimensional nuclear magnetic resonance,LF-2D-NMR)技术,定性分析一维波谱中信号重叠无法区分组分的问题。试验结果表明,LF-NMR含油含水率软件能快速准确检测大豆含油率,T1-T2二维核磁图谱成功解决了自由水和油信号重叠问题。利用U-net++深度学习模型对MRI成像的矢状面、冠状面、横截面以及三面混合数据集进行训练,其中横截面评价指标与其他数据集相比更优,语义分割部分中平均交并比(mean intersection over union,mIoU)约0.9058,全局准确率0.9980,训练后的模型能够将MRI图像识别并分割,快速判别大豆含油率高低。试验证明,LF-NMR及MRI能够快速无损掌握大豆含油率信息,为大豆的高油育种提供了新思路和技术支持。
文摘该文对不同发酵阶段的黄酒样品进行低场核磁共振(low-field nuclear magnetic resonance,LF-NMR)检测,比较了陈酿时间、酒精度和品牌对黄酒低场核磁弛豫特性的影响,最后对9个品牌黄酒的LF-NMR弛豫信息进行了主成分分析。结果表明,发酵后样品的单组分弛豫时间(T_(2W))显著缩短,而陈酿后黄酒的T_(2W)又相对延长。多组分弛豫图谱(T_(2))表明,对照组和浸米样品均只有1个峰。发酵后样品的T_(2)图谱均出现2个峰。从第一次发酵到煎酒期间,T_(21)和T_(22)不断缩短,而陈酿期间T_(21)和T_(22)相对延长。同一品牌及陈酿时间的黄酒,酒精度越大,体系的T_(2W),T_(21)和T_(22)越短;同一品牌及酒精度下,陈酿时间仅对T_(21)有一定影响。不同品牌黄酒因酿造工艺的区别而使弛豫分布有一定特点。主成分分析表明,不同酒精度、陈酿时间、品牌及种类的黄酒的弛豫特性的PCA分布及间距不同。说明应用LF-NMR技术可实现对不同工艺生产的黄酒的快速辨别。
