Normalized glandular dose coefficients for digital breast tomosynthesis using detailed Chinese breast models

The rise in breast cancer diagnoses among Chinese women has necessitated the use of X-ray breast screening,which carries a radiation risk.This study aimed to provide a dosimetry protocol for the Chinese female population to replace the traditional standard that utilizes simplified breast models,for the accurate estimation of the mean glandular dose of a patient undergoing digital breast tomosynthesis(DBT).The first set of detailed Chinese female breast models and representative breast parameters was constructed.Considering backscatter radiation and computational efficiency,we improved the combination of these models and the Chinese reference adult female whole-body voxel phantom.Image acquisition for four commercial DBT systems that are widely employed in China was simulated using the Monte Carlo method to obtain the normalized glandular dose coefficients of DBT(D_(gN)^(DBT))and the glandular depth dose(D_(g)^(dep)(z))for different breast characteristics and X-ray spectra.We calculated a series of D_(gN)^(DBT) values for breasts with different percentage mass glandularities(5%,25%,50%,75%,and 100%)and compressed breast thicknesses(2,3,4,5,6,and 7 cm)at various tube potentials(25,28,30,32,35,and 49 kV)and target/filter combinations(W/Rh,W/Al,Mo/Mo,Rh/Rh,and Rh/Ag).The parameter dependence of the breast characteristics and beam conditions on D_(gN)^(DBT) in detailed breast models was investigated.The D_(gN)^(DBT) results were 14.6-51.0%lower than those of the traditional dosimetry standard in China.The difference in D_(gN)^(DBT) was mainly due to a decrease in the depth of the main energy deposition area caused by the glandular distribution along the depth direction.The results obtained in this study may be used to improve breast dosimetry in China and provide more detailed information on risk assessment during DBT.

DTS在胫骨骨折内固定术后的应用价值

目的探讨数字断层融合摄影(DTS)在胫骨骨折内固定术后复查中的应用价值。方法回顾性分析2020年10月至2023年10月在我院行胫骨骨折内固定术后的患者120例,于术后3个月及6个月时行数字化X线摄影(DR)及DTS检查,比较两种影像学方法的图像质量和骨折愈合显示情况,并对2名医师的图像质量评分结果进行一致性分析。结果2名医师在DTS及DR的图像质量评分结果上均有较好的一致性。术后3个月时,DTS图像质量评分为(3.658±1.170)分,DR图像质量评分为(2.750±1.176)分,两组差异有统计学意义(P<0.05)。DTS图像骨折愈合情况显示率为91.67%(110/120),DR图像骨折愈合情况显示率为72.50%(87/120),差异有统计学意义(P<0.05)。术后6个月时,DTS图像质量评分为(3.692±1.165)分,DR图像质量评分为(2.792±1.187)分,两组差异有统计学意义(P<0.05)。DTS图像骨折愈合情况显示率为93.33%(112/120),DR图像骨折愈合情况显示率为75.83%(91/120),差异有统计学意义(P<0.05)。结论在胫骨骨折内固定术后复查中,DTS图像质量优于DR,能更加清晰地显示术区骨质结构及骨折愈合情况,有助于临床医师更准确地评估内固定术后恢复情况,具有较好的临床应用价值。

A Dual Closed-Loop Digital Twin Construction Method for Optimizing the Copper Disc Casting Process

The copper disc casting machine is core equipment for producing copper anode plates in the copper metallurgy industry.The copper disc casting machine casting package motion curve(CPMC) is significant for precise casting and efficient production.However,the lack of exact casting modeling and real-time simulation information severely restricts dynamic CPMC optimization.To this end,a liquid copper droplet model describes the casting package copper flow pattern in the casting process.Furthermore,a CPMC optimization model is proposed for the first time.On top of this,a digital twin dual closed-loop self-optimization application framework(DT-DCS) is constructed for optimizing the copper disc casting process to achieve self-optimization of the CPMC and closed-loop feedback of manufacturing information during the casting process.Finally,a case study is carried out based on the proposed methods in the industrial field.

Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing rapidly,the competition is becoming increasingly fierce,and the digital transformation of the production line is imminent.As one of themost important components of heavy vehicles,the transmission front andmiddle case assembly lines have a high degree of automation,which can be used as a pilot for the digital transformation of production.To ensure the visualization of digital twins(DT),consistent control logic,and real-time data interaction,this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line.Firstly,theDT-based systemarchitecture is designed,and theDT model is created by constructing the visualization model,logic model,and data model of the assembly line.Then,a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line.Eventually,some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment.

Efficacy of digital breast tomosynthesis combined with magnetic resonance imaging in the diagnosis of early breast cancer

BACKGROUND The incidence and mortality rate of breast cancer in China rank 120th and 163rd,worldwide,respectively.The incidence of breast cancer is on the rise;the risk increases with age but is slightly reduced after menopause.Early screening,diagnosis,and timely determination of the best treatment plan can ensure clinical efficacy and prognosis.AIM To evaluate the clinical value of magnetic resonance imaging(MRI) combined with digital breast tomosynthesis(DBT) in diagnosing early breast cancer and the effect of breast-conserving surgery by arc incision.METHODS This study was divided into two parts.Firstly,110 patients with early breast cancer confirmed by pathological examination and 110 with benign breast diseases diagnosed simultaneously in Changzhi People’s Hospital of Shanxi Province and Shanxi Dayi Hospital from May 2019 to September 2020 were included in the breast cancer group and the benign group,respectively.Both groups underwent DBT and MRI examination,and the pathological results were used as the gold standard to evaluate the effectiveness of the combined application of DBT and MRI in the diagnosis of early breast cancer.Secondly,according to the operation method,110 patients with breast cancer were divided into either a breast-conserving group(69 patients) or a modified radical mastectomy group(41 patients).The surgical effect,cosmetic effect,and quality of life of the two groups were compared.RESULTS Among the 110 cases of breast cancer,66 were of invasive ductal carcinoma(60.00%),and 22 were of ductal carcinoma in situ(20.00%).Among the 110 cases of benign breast tumors,55 were of breast fibromas(50.00%),and 27 were of breast adenosis(24.55%).The sensitivity,specificity,and area under the curve(AUC) of DBT in the differential diagnosis of benign and malignant breast tumors were 73.64%,84.55%,and 0.791,respectively.The sensitivity,specificity,and AUC of MRI in the differential diagnosis of benign and malignant breast tumors were 84.55%,85.45%,and 0.850,respectively.The sensitivity,specificity,and AUC of DBT combined with MRI in the differential diagnosis of benign and malignant breast tumors were 97.27%,93.64%,and 0.955,respectively.The blood loss,operation time and hospitalization time of the breast-conserving group were significantly lower than those of the modified radical treatment group,and the difference was statistically significant(P < 0.05).After 3 mo of observation,the breast cosmetic effect of the breast-conserving group was better than that of the modified radical group,and the difference was statistically significant(P < 0.05).Before surgery,the quality-of-life scores of the breast-conserving and modified radical mastectomy groups did not differ(P > 0.05).Three months after surgery,the quality-of-life scores in both groups were higher than those before surgery(P < 0.05),and the quality-of-life score of the breast-conserving group was higher than that of the modified radical group(P < 0.05).In the observation of tumor recurrence rate two years after the operation,four patients in the breast-conserving group and one in the modified radical treatment group had a postoperative recurrence.There was no significant difference in the recurrence rate between the two groups(χ2 = 0.668,P = 0.414 > 0.05).CONCLUSION MRI combined with DBT in diagnosing early breast cancer can significantly improve the diagnostic efficacy compared with the two alone.Breast-conserving surgery leads to better cosmetic breast effects and reduces the impact of surgery on postoperative quality of life.

Follow-up of endovascular aortic aneurysm repair:Preliminary validation of digital tomosynthesis and contrast enhanced ultrasound in detection of medium- to long-term complications

AIM: To validate the feasibility of digital tomosynthesis of the abdomen(DTA) combined with contrast enhanced ultrasound(CEUS) in assessing complications after endovascular aortic aneurysm repair(EVAR) by using computed tomography angiography(CTA) as the gold standard.METHODS: For this prospective study we enrolled 163 patients(123 men; mean age, 65.7 years) referred for CTA for EVAR follow-up. CTA, DTA and CEUS were performed at 1 and 12 mo in all patients, with a maximum time interval of 2 d.RESULTS: Among 163 patients 33 presented complications at CTA. DTA and CTA correlated for the presence of complications in 32/33(96.96%) patients and for the absence of complications in 127/130(97.69%) patients; the sensitivity, specificity, positive predictive value(PPV), negative predictive value(NPV) and accuracy of DTA were 97%, 98%, 91%, 99%, and 98%, respectively. CEUS and CTA correlated for the presence of complications in 19/33(57.57%) patients and for the absence of complications in 129/130(99.23%) patients; the sensitivity, specificity, PPV, NPV and accuracy of CEUS were 58%, 99%, 95%, 90%, and 91%, respectively. Sensitivity, specificity and accuracy of combining DTA and CEUS together in detecting EVAR complications were 77%, 98% and 95%, respectively.CONCLUSION: Combining DTA and CEUS in EVAR follow-up has the potential to limit the use of CTA only in doubtful cases.

Comparison between Visualization of Microcalcifications by Digital Breast Tomosynthesis and Full-Field Digital Mammography

Objective: To date, few studies have compared the diagnostic performance and visibility of microcalcifications obtained using digital breast tomosynthesis (DBT) with those obtained from full-field digital mammography (FFDM). The visualization and characterization of microcalcifications with DBT remain controversial. The purpose of this study was to compare the visibility of microcalcifications and determine whether DBT exhibits a diagnostic advantage for visualizing microcalcifications over FFDM. Methods: We retrospectively reviewed 120 cases including DBT and FFDM imaging (60 histologically verified as breast cancers and 60 as benign microcalcifications or normal). DBT images with a wide scan-angle of 50° and FFDM images were obtained using a flat-panel system (MAMMOMAT Inspiration, Siemens). Images were independently reviewed by four board-certified radiologists and evaluated for the presence of microcalcifications, probability of malignancy (BI-RADS classification), and visibility. Results: In predicting the malignancy of detected microcalcifications, no significant difference was found between readers’ areas under the receiver operating characteristic curve for DBT and FFDM (p = 0.068). The visibility scores of detected microcalcifications were 3.74 ± 1.06 for DBT and 3.46 ± 0.93 for FFDM, respectively. The visibility of microcalcifications when using DBT was found to be significantly superior to that of FFDM (p < 0.05). Conclusion: Our results suggest that the image quality of DBT with a wide scan-angle is comparable or superior to that obtained with FFDM in terms of both visibility and assessment of microcalcifications.

Endogenous Security-Aware Resource Management for Digital Twin and 6G Edge Intelligence Integrated Smart Park

The integration of digital twin(DT)and 6G edge intelligence provides accurate forecasting for distributed resources control in smart park.However,the adverse impact of model poisoning attacks on DT model training cannot be ignored.To address this issue,we firstly construct the models of DT model training and model poisoning attacks.An optimization problem is formulated to minimize the weighted sum of the DT loss function and DT model training delay.Then,the problem is transformed and solved by the proposed Multi-timescAle endogenouS securiTy-aware DQN-based rEsouRce management algorithm(MASTER)based on DT-assisted state information evaluation and attack detection.MASTER adopts multi-timescale deep Q-learning(DQN)networks to jointly schedule local training epochs and devices.It actively adjusts resource management strategies based on estimated attack probability to achieve endogenous security awareness.Simulation results demonstrate that MASTER has excellent performances in DT model training accuracy and delay.

Comparison of Different Reconstruction Algorithms for Decreasing the Exposure Dose during Digital Breast Tomosynthesis: A Phantom Study

We compared reconstruction algorithms [filtered back projection (FBP), maximum likelihood expectation maximization (MLEM), and the simultaneous iterative reconstruction technique (SIRT)] in terms of the radiation dose and image quality, for exploring the possibility of decreasing the radiation dose during digital breast tomosynthesis (DBT). The three algorithms were implemented using a DBT system and experimentally evaluated using measurements, such as signal difference-to-noise ratio (SDNR) and intensity profile, on a BR3D phantom (infocus plane image). The possible radiation dose reduction, contrast improvement, and artifact reduction in DBT were evaluated using different exposure levels and the three reconstruction techniques. We performed statistical analysis (one-way analysis of variance) of the SDNR data. The effectiveness of each technique for enhancing the visibility of the BR3D phantom was quantified with regard to SDNR (FBP versus MLEM, P < 0.05;FBP vs. SIRT, P < 0.05;MLEM vs. SIRT, P = 0.945);the artifact reduction was quantified with regard to the intensity profile. MLEM and SIRT produced reconstructed images with SDNR values indicative of low-contrast visibility. The SDNR value for the half-radiation dose MLEM and SIRT images was close to that of the FBP reference radiation dose image. Artifacts were decreased in the MLEM and SIRT images (in the infocus plane) according to the intensity profiles that we obtained. With MLEM and SIRT, the radiation dose may be decreased to half comparison with FBP.

A Comparison of Reconstruction Algorithms Regarding Exposure Dose Reductions during Digital Breast Tomosynthesis

This study compared reconstruction algorithms [filtered back projection (FBP) and simultaneous iterative reconstruction technique (SIRT)] with respect to radiation doses and image quality and suggested the possibility of decreasing the exposure dose in digital breast tomosynthesis (DBT). These two existing algorithms were implemented using a DBT system and experimentally evaluated using contrast-detail (CD) phantom measurements, such as contrast-to-noise ratio (CNR), root mean square error (RMSE), intensity profile, and artifact spread function (ASF), and the results obtained with FBP and SIRT were compared. The potential dose reduction, contrast improvement, quantum noise reduction, and artifact reduction in DBT were evaluated using different exposures and the two reconstruction techniques. The effectiveness of each technique for enhancing the visibility of a CD phantom was quantified with respect to CNR and RMSE, and artifact reduction was quantified with respect to the intensity profile and ASF. SIRT produced reconstructed images with CNR values indicative of high-contrast detection. Image error was smaller in the in-focus plane SIRT images, and artifacts were decreased in these images according to the determined intensity profiles and ASF. These results suggest that when using SIRT, the exposure dose could possibly be decreased to half.

Dual-Energy Subtraction X-Ray Digital Tomosynthesis: Basic Physical Evaluation

The present study was performed to determine the potential of applying dual-energy subtraction (DES) digital tomo-synthesis to basic physical evaluations. Volumetric X-ray DES digital tomosysnthesis was used to obtain an image of a detectability phantom (an artificial lesion). The image quality of DES digital tomosynthesis was compared to that of DES radiography. The purpose of this study was to determine enhanced visibility quantified in terms of the contrast- to-noise ratio, figure-of-merit, and root-mean-square error. In the in-focus plane, the image quality is better by DES digital tomosynthesis than by DES radiography. The potential usefulness of DES digital tomosynthesis for evaluating a detectability phantom was demonstrated. Further studies are required to determine the ability of DES digital tomosyn-thesis to quantify the spatial relationships between the artificial lesion components of these devices, as well as to iden- tify lesions with diagnostic consequences.

Application of X-ray digital tomosynthesis in knee joint trauma examination

Objective: To explore the clinical value of X-ray digital tomosynthesis(DTS)in the diagnosis of knee joint fractures. Methods: A total of 28 cases of thoracic trauma, X-ray film cannot be clearly diagnosed or can confirm the diagnosis but the need for further identification of forensic diagnosis of cases of DTS scan and three-dimensional reconstruction in order to control the study. Results: 1. The reconstructed images after DTS scanning showed that the knee joint fractures were clearly diagnosed, and the detection rate of 28 knee joint fractures was 92.86%. 2. DTS scanning could clearly detect the fresh knee joint fracture's fracture line, corresponding line and broken bones. For the old fracture, DTS scanning could clearly show the condition of the fracture end's healing. Conclusions: The technique is of great value in the diagnosis of knee joint fracture, especially in the examination of complex structure, thick body and review of internal fixation after fracture.

State Accurate Representation and Performance Prediction Algorithm Optimization for Industrial Equipment Based on Digital Twin

The combination of the Industrial Internet of Things(IIoT)and digital twin(DT)technology makes it possible for the DT model to realize the dynamic perception of equipment status and performance.However,conventional digital modeling is weak in the fusion and adjustment ability between virtual and real information.The performance prediction based on experience greatly reduces the inclusiveness and accuracy of the model.In this paper,a DT-IIoT optimization model is proposed to improve the real-time representation and prediction ability of the key equipment state.Firstly,a global real-time feedback and the dynamic adjustment mechanism is established by combining DT-IIoT with algorithm optimization.Secondly,a strong screening dual-model optimization(SSDO)prediction method based on Stacking integration and fusion is proposed in the dynamic regulation mechanism.Lightweight screening and multi-round optimization are used to improve the prediction accuracy of the evolution model.Finally,tak-ing the boiler performance of a power plant in Shanxi as an example,the accurate representation and evolution prediction of boiler steam quantity is realized.The results show that the real-time state representation and life cycle performance prediction of large key equipment is optimized through these methods.The self-lifting ability of the Stacking integration and fusion-based SSDO prediction method is 15.85%on average,and the optimal self-lifting ability is 18.16%.The optimization model reduces the MSE loss from the initial 0.318 to the optimal 0.1074,and increases R2 from the initial 0.731 to the optimal 0.9092.The adaptability and reliability of the model are comprehensively improved,and better prediction and analysis results are achieved.This ensures the stable operation of core equipment,and is of great significance to comprehensively understanding the equipment status and performance.

Data-Centric Approach to Digital Twin Modeling of Production Lines

Digital twin(DT) is a virtual replica of a physical world that has become one of the most important ideas in the manufacturing industry’s digital revolution. DT modeling is a vital issue in building a DT of a production line. In this paper, a method is proposed to address the difficulties of complicated production line business and data heterogeneity. The method focuses on essential data in the production line and creates conceptual and information models based on the ArtiFlow model and AutomationML(AML). Conceptual models are mainly used to describe and analyze the business activities of the production line, and information models describe real production lines in the form of XML files. The proposed modeling approach has been applied to a real-world clothing production line to demonstrate its feasibility and effectiveness.

基于数字孪生的多自动驾驶车辆分布式协同路径规划算法

针对多辆自动驾驶车辆(AVs)在进行路径规划过程中存在的车辆之间协作难、协作训练出来的模型质量低以及所求结果直接应用到物理车辆的效果较差的问题,该文提出一种基于数字孪生(DT)的多AVs分布式协同路径规划算法,基于可信度加权去中心化的联邦强化学习方法(CWDFRL)来实现多AVs的路径规划。首先将单个AVs的路径规划问题建模成在驾驶行为约束下的最小化平均任务完成时间问题,并将其转化成马尔可夫决策过程(MDP),使用深度确定性策略梯度算法(DDPG)进行求解;然后使用联邦学习(FL)保证车辆之间的协同合作,针对集中式的FL中存在的全局模型更新质量低的问题,使用基于可信度的动态节点选择的去中心化FL训练方法改善了全局模型聚合质量低的问题;最后使用DT辅助去中心化联邦强化学习(DFRL)模型的训练,利用孪生体可以从DT环境中学习的优点,快速将训练好的模型直接部署到现实世界的AVs上。仿真结果表明,与现有的方法相比,所提训练框架可以得到一个较高的奖励,有效地提高了车辆对其本身速度的利用率,与此同时还降低了车辆群体的平均任务完成时间和碰撞概率。

数字乳腺断层摄影评估新辅助化疗后肿瘤大小的价值

目的评估新辅助化疗后数字乳腺断层摄影(DBT)、全数字化乳腺摄影(FFDM)和超声(US)检查预测残留肿瘤大小的能力。方法回顾性分析2020年1月1日至2021年12月31日病理结果确诊为乳腺癌,行新辅助化疗并接受手术治疗患者的临床及影像学资料。所有患者在新辅助化疗后均行乳腺DBT、FFDM及US检查。采用Pearson相关分析计算不同影像检查方法测量残留肿瘤大小与病理测量结果的相关性;以0.5 cm为阈值,分析不同影像检查预测残留肿瘤大小的准确率。结果85例患者,共86个病灶,去除新辅助化疗后无残留癌的病灶,共纳入72个病灶。新辅助化疗后,DBT、FFDM、US测量残留肿瘤大小与病理测量结果均呈中等程度相关。DBT、FFDM、US预测残留肿瘤大小的准确率分别为59.72%(43/72)、43.06%(31/72)、41.67%(30/72)。DBT与FFDM、US预测残留肿瘤大小的准确率比较,差异具有统计学意义(χ^(2)=4.003、4.695,P=0.045、0.030)。结论新辅助化疗后,DBT预测残留肿瘤大小的准确率优于FFDM与US。DBT在新辅助化疗后的术前评估具有良好的应用前景。

基于智能分层切片技术的数字孪生传感信息同步策略

针对传感数据在无线接入网(RAN)中传输的不可靠性与不及时性造成数字孪生(DTs)同步信息的不精确问题,该文提出一种基于智能分层切片技术的DTs传感信息同步策略。该策略在双时间尺度下,以最大化传感信息满意度和最小化切片重配置及DTs同步成本为目标,联合优化切片无线资源配置以及DTs传感信息同步问题。首先,在大时间尺度,利用网络切片为有着不同服务质量(QoS)的DTs提供隔离以及解决部署问题;在小时间尺度,通过更加灵活的无线资源分配来提高DTs传感信息同步任务对动态环境的适应性,进一步提高通信性能,建立更逼近于物理实体的DTs。其次,为了求解不同时间尺度的优化问题,该文提出一种双层深度强化学习(DRL)框架实现高效的网络资源交互,其中下层控制算法利用优先经验放回(PER)机制加快收敛速度。最后,仿真结果验证了所提策略的有效性。

工业物联网中数字孪生辅助任务卸载算法

针对工业物联网(IIoT)设备资源有限和边缘服务器资源动态变化导致的任务协同计算效率低等问题,该文提出一种工业物联网中数字孪生(DT)辅助任务卸载算法。首先,该算法构建了云-边-端3层数字孪生辅助任务卸载框架,在所创建的数字孪生层中生成近似最佳的任务卸载策略。其次,在任务计算时间和能量的约束下,从时延的角度研究了计算卸载过程中用户关联和任务划分的联合优化问题,建立了最小化任务卸载时间和服务失败惩罚的优化模型。最后,提出一种基于深度多智能体参数化Q网络(DMAPQN)的用户关联和任务划分算法,通过每个智能体不断地探索和学习,以获取近似最佳的用户关联和任务划分策略,并将该策略下发至物理实体网络中执行。仿真结果表明,所提任务卸载算法有效降低了任务协同计算时间,同时为每个计算任务提供近似最佳的卸载策略。

数字断层融合摄影技术在股骨干骨折内固定术后的应用研究

目的探讨数字断层融合摄影(DTS)在股骨干骨折内固定术后复查中的应用价值。方法收集90例股骨干骨折内固定术后患者,于术后6月时完成了数字化X线摄影(DR)及DTS检查。由两名放射科医师采用5分法对两种影像学检查方法所获图像进行图像质量评价及对比。同时由临床医师对DTS及DR的骨折愈合显示率进行对比。结果术后6月时,DTS图像质量评分为(3.689±1.148)分,DR图像质量评分为(2.778±1.197)分,两组差异具有统计学意义(P<0.05)。DTS图像骨折愈合情况显示率为95.56%(86/90),DR图像骨折愈合情况显示率为72.23%(65/90),差异具有统计学意义(P<0.05)。结论在股骨干骨折内固定术后复查中,DTS能清晰显示术区骨质结构,准确判断骨折愈合情况,图像质量较DR更优,可作为股骨干骨折内固定术后复查较为理想的影像学检查方法,临床实用性较强。