OBJECTIVES: We propose a sparse-view cone-beam CT reconstruction algorithm based on bidirectional flow field guided projection completion (BBC-Recon) to solve the ill-posed inverse problem in sparse-view cone-beam CT imaging. METHODS: The BBC-Recon method consists of two main modules: the projection completion module and the image restoration module. Based on flow field estimation, the projection completion module, through the designed bidirectional and multi-scale correlators, fully calculates the correlation information and redundant information among projections to precisely guide the generation of bidirectional flow fields and missing frames, thus achieving high-precision completion of missing projections and obtaining pseudo complete projections. The image restoration module reconstructs the obtained pseudo complete projections and then refines the image to remove the residual artifacts and further improve the image quality. RESULTS: The experimental results on the public datasets of Mayo Clinic and Guilin Medical University showed that in the case of a 4-fold sparse angle, compared with the suboptimal method, the BBC-Recon method increased the PSNR index by 1.80% and the SSIM index by 0.29%, and reduced the RMSE index by 4.12%; In the case of an 8-fold sparse angle, the BBC-Recon method increased the PSNR index by 1.43% and the SSIM index by 1.49%, and reduced the RMSE index by 0.77%. CONCLUSIONS The BBC-Recon algorithm fully exploits the correlation information between projections to allow effective removal of streak artifacts while preserving image structure information, and demonstrates significant advantages in maintaining inter-slice consistency.
Algorithms ; Cone-Beam Computed Tomography/methods* ; Image Processing, Computer-Assisted/methods* ; Humans

OBJECTIVES: We propose a segmented backprojection tensor degradation feature encoding (SBP-MAC) model for motion artifact correction in dental cone beam computed tomography (CBCT) to improve the quality of the reconstructed images. METHODS: The proposed motion artifact correction model consists of a generator and a degradation encoder. The segmented limited-angle reconstructed sub-images are stacked into the tensors and used as the model input. A degradation encoder is used to extract spatially varying motion information in the tensor, and the generator's skip connection features are adaptively modulated to guide the model for correcting artifacts caused by different motion waveforms. The artifact consistency loss function was designed to simplify the learning task of the generator. RESULTS: The proposed model could effectively remove motion artifacts and improve the quality of the reconstructed images. For simulated data, the proposed model increased the peak signal-to-noise ratio by 8.28%, increased the structural similarity index measurement by 2.29%, and decreased the root mean square error by 23.84%. For real clinical data, the proposed model achieved the highest expert score of 4.4221 (against a 5-point scale), which was significantly higher than those of all the other comparison methods. CONCLUSIONS The SBP-MAC model can effectively extract spatially varying motion information in the tensors and achieve adaptive artifact correction from the tensor domain to the image domain to improve the quality of reconstructed dental CBCT images.
Cone-Beam Computed Tomography/methods* ; Artifacts ; Humans ; Motion ; Image Processing, Computer-Assisted/methods* ; Signal-To-Noise Ratio ; Algorithms

OBJECTIVES: We propose a low-dose CT image restoration method based on central guidance and alternating optimization (FedGP). METHODS: The FedGP framework revolutionizes the traditional federated learning model by adopting a structure without a fixed central server, where each institution alternatively serves as the central server. This method uses an institution-modulated CT image restoration network as the core of client-side local training. Through a federated learning approach of central guidance and alternating optimization, the central server leverages local labeled data to guide client-side network training to enhance the generalization capability of the CT imaging model across multiple institutions. RESULTS: In the low-dose and sparse-view CT image restoration tasks, the FedGP method showed significant advantages in both visual and quantitative evaluation and achieved the highest PSNR (40.25 and 38.84), the highest SSIM (0.95 and 0.92), and the lowest RMSE (2.39 and 2.56). Ablation study of FedGP demonstrated that compared with FedGP(w/o GP) without central guidance, the FedGP method better adapted to data heterogeneity across institutions, thus ensuring robustness and generalization capability of the model in different imaging conditions. CONCLUSIONS FedGP provides a more flexible FL framework to solve the problem of CT imaging heterogeneity and well adapts to multi-institutional data characteristics to improve generalization ability of the model under diverse imaging geometric configurations.
Tomography, X-Ray Computed/methods* ; Humans ; Radiation Dosage ; Image Processing, Computer-Assisted/methods* ; Algorithms

Objective To propose a CT truncated data reconstruction model(DDTrans)based on projection and image dual-domain Transformer coupled feature learning for reducing truncation artifacts and image structure distortion caused by insufficient field of view(FOV)in CT scanning.Methods Transformer was adopted to build projection domain and image domain restoration models,and the long-range dependency modeling capability of the Transformer attention module was used to capture global structural features to restore the projection data information and enhance the reconstructed images.We constructed a differentiable Radon back-projection operator layer between the projection domain and image domain networks to enable end-to-end training of DDTrans.Projection consistency loss was introduced to constrain the image forward-projection results to further improve the accuracy of image reconstruction.Results The experimental results with Mayo simulation data showed that for both partial truncation and interior scanning data,the proposed DDTrans method showed better performance than the comparison algorithms in removing truncation artifacts at the edges and restoring the external information of the FOV.Conclusion The DDTrans method can effectively remove CT truncation artifacts to ensure accurate reconstruction of the data within the FOV and achieve approximate reconstruction of data outside the FOV.

Objective We propose a dual-domain cone beam computed tomography(CBCT)reconstruction framework DualCBR-Net based on improved differentiable domain transform for cone-angle artifact correction.Methods The proposed CBCT dual-domain reconstruction framework DualCBR-Net consists of 3 individual modules:projection preprocessing,differentiable domain transform,and image post-processing.The projection preprocessing module first extends the original projection data in the row direction to ensure full coverage of the scanned object by X-ray.The differentiable domain transform introduces the FDK reconstruction and forward projection operators to complete the forward and gradient backpropagation processes,where the geometric parameters correspond to the extended data dimension to provide crucial prior information in the forward pass of the network and ensure the accuracy in the gradient backpropagation,thus enabling precise learning of cone-beam region data.The image post-processing module further fine-tunes the domain-transformed image to remove residual artifacts and noises.Results The results of validation experiments conducted on Mayo's public chest dataset showed that the proposed DualCBR-Net framework was superior to other comparison methods in terms of artifact removal and structural detail preservation.Compared with the latest methods,the DualCBR-Net framework improved the PSNR and SSIM by 0.6479 and 0.0074,respectively.Conclusion The proposed DualCBR-Net framework for cone-angle artifact correction allows effective joint training of the CBCT dual-domain network and is especially effective for large cone-angle region.

Objective We propose a motion artifact correction algorithm(DMBL)for reducing motion artifacts in reconstructed dental cone-beam computed tomography(CBCT)images based on deep blur learning.Methods A blur encoder was used to extract motion-related degradation features to model the degradation process caused by motion,and the obtained motion degradation features were imported in the artifact correction module for artifact removal.The artifact correction module adopts a joint learning framework for image blur removal and image blur simulation for treatment of spatially varying and random motion patterns.Comparative experiments were conducted to verify the effectiveness of the proposed method using both simulated motion data sets and clinical data sets.Results The experimental results with the simulated dataset showed that compared with the existing methods,the PSNR of the proposed method increased by 2.88%,the SSIM increased by 0.89%,and the RMSE decreased by 10.58%.The results with the clinical dataset showed that the proposed method achieved the highest expert level with a subjective image quality score of 4.417(in a 5-point scale),significantly higher than those of the comparison methods.Conclusion The proposed DMBL algorithm with a deep blur joint learning network structure can effectively reduce motion artifacts in dental CBCT images and achieve high-quality image restoration.

Objective To propose a dual-domain CBCT reconstruction framework(DualSFR-Net)based on generative projection interpolation to reduce artifacts in sparse-view cone beam computed tomography(CBCT)reconstruction.Methods The proposed method DualSFR-Net consists of a generative projection interpolation module,a domain transformation module,and an image restoration module.The generative projection interpolation module includes a sparse projection interpolation network(SPINet)based on a generative adversarial network and a full-view projection restoration network(FPRNet).SPINet performs projection interpolation to synthesize full-view projection data from the sparse-view projection data,while FPRNet further restores the synthesized full-view projection data.The domain transformation module introduces the FDK reconstruction and forward projection operators to complete the forward and gradient backpropagation processes.The image restoration module includes an image restoration network FIRNet that fine-tunes the domain-transformed images to eliminate residual artifacts and noise.Results Validation experiments conducted on a dental CT dataset demonstrated that DualSFR-Net was capable to reconstruct high-quality CBCT images under sparse-view sampling protocols.Quantitatively,compared to the current best methods,the DualSFR-Net method improved the PSNR by 0.6615 and 0.7658 and increased the SSIM by 0.0053 and 0.0134 under 2-fold and 4-fold sparse protocols,respectively.Conclusion The proposed generative projection interpolation-based dual-domain CBCT sparse-view reconstruction method can effectively reduce stripe artifacts to improve image quality and enables efficient joint training for dual-domain imaging networks in sparse-view CBCT reconstruction.

OBJECTIVE:With the popularity of simulated barefoot running,minimalist shoes have become a new way of foot exercise.As an important muscle group of the foot,the maintenance of foot muscle morphology is important for the execution of foot functions.In this paper,by combing the literature about the effect of minimalist shoes on foot muscle morphology in recent years,we systematically evaluate the effect of minimalist shoes on foot muscle morphology compared with traditional running shoes. METHODS:The relevant articles published from 2012 to 2022 were searched in Chinese and English databases(PubMed,Web of Science,ProQuest,CNKI and WanFang databases)with"minimal shoes,minimal footwear,minimalist shoes,minimalist footwear,foot muscle,feet muscle"as Chinese and English keywords,respectively.Meta-analysis,sensitivity tests were performed on the included literature using Review Manager 5.4.1 and Stata 14 software,the Egger method was used to test for publication bias in the literature,and Meta-regression was used to identify the subgroups with heterogeneity. RESULTS:Compared with traditional running shoes,minimalist shoes increased muscle circumference of the abductor hallucis[standardized mean difference=2.034,95%confidence interval(1.192,2.877),Z=4.73,P＜0.001].And the results were not reversed after clipping and patching,with a more robust combined effect size(P＜0.05).For the toe short flexors,the total combined effect size did not show a difference between traditional running shoes and minimalist shoes[standardized mean difference=0.470,95%confidence interval(-0.45,1.39),Z=1.00,P=0.318]. CONCLUSION:Compared with traditional running shoes,minimalist shoes intervention can effectively improve muscle circumference of the abductor hallucis,but the promoting effect on the flexor digitorum brevis muscle is not obvious.Running in minimalist shoes has positive implications for the maintenance of the medial longitudinal arch,but it is necessary to enrich the research content of minimalist shoes on different foot muscles and different populations in order to further explore the mechanisms by which minimalist shoe interventions promote foot function.

AIM:To investigate the effects of adipose-derived stem cells(ADSCs)with overexpression or si-lencing of long noncoding RNA(lncRNA)SNHG8 on the viability,migration,angiogenesis,and the expression of vasoac-tive factors in human umbilical vein endothelial cells(HUVECs).METHODS:Identification of ADSCs derived from morbidly obese patients(O-ADSCs)was conducted using flow cytometry and induction of lipogenesis and osteogenesis.The expression of lncRNA SNHG8 in healthy human ADSCs(H-ADSCs)and O-ADSCs was detected by RT-qPCR.Tran-swell method was used to establish the indirect co-culture system of ADSCs and HUVECs for 48 h,and the cells were di-vided into O-ADSCs+HUVECs group,H-ADSCs+HUVECs group,and HUVECs alone group.The mRNA and protein ex-pression levels of angiotensin Ⅱ(Ang Ⅱ),endothelin-1(ET-1)and endothelial nitric oxide synthase(eNOS)in HUVECs were detected by RT-qPCR and Western blot.The lncRNA SNHG8 overexpression and silencing lentiviruses were con-structed and used to infect O-ADSCs.The indirect co-cultured ADSCs and HUVECs were divided into O-ADSCs-OE-SNHG8+ HUVECs group,O-ADSCs-OE-NC+HUVECs group,O-ADSCs-sh-SNHG8+HUVECs group,and O-ADSCs-sh-NC+HUVECs group.After co-culture for 48 h,the viability,migration and tubule formation of HUVECs were detected by CCK-8,scratch and angiogenesis assays,respectively.The mRNA and protein expression levels of Ang Ⅱ,ET-1 and eNOS in HU-VECs were detected by RT-qPCR and Western blot,respectively.The nitrate reductase method was used to detect the con-tent of NO in HUVECs.RESULTS:(1)The cultured cells were identified as ADSCs.(2)Compared with H-ADSCs,ln-cRNA SNHG8 expression was significantly up-regulated in O-ADSCs(P<0.01).(3)Compared with H-ADSCs+HUVECs group and HUVECs group,the mRNA and protein expression levels of Ang Ⅱ and ET-1 in HUVECs in O-ADSCs+HU-VECs group were up-regulated(P<0.01).(4)Overexpression of lncRNA SNHG8 in O-ADSCs enhanced the viability,mi-gration and tube formation ability of HUVECs,up-regulated the mRNA and protein expression levels of Ang Ⅱ and ET-1,down-regulated the mRNA and protein expression levels of eNOS,and decreased the content of NO in HUVECs(P<0.05).However,silencing of lncRNA SNHG8 in O-ADSCs exerted opposite results(P<0.05).CONCLUSION:(1)The O-ADSCs can promote endothelial cell viability,migration and tubule formation through paracrine effects.(2)The O-ADSCs with overexpression of lncRNA SNHG8 promote the imbalance of diastolic and contractile factors secreted by endo-thelial cells,and induce the dysfunction of vascular endothelial cells.

Objective:To explore the correlation between serum levels of interleukin-9 (IL-9), platelet activating factor (PAF), total immunoglobulin E (IgE), interferon γ (IFN-γ), and interleukin-4 (IL-4) in patients with chronic spontaneous urticaria (CSU).Methods:Sixty CSU active phase patients admitted to the First Affiliated Hospital of Hebei North University from March 2018 to March 2019 were selected and included in the CSU active phase group. Based on the 7-day Urticaria Activity Score (UAS7), they were divided into three groups: 15 mild group, 25 moderate group, and 20 severe group; And 19 patients who entered the quiescent phase of the disease after 28 days of standardized antihistamine treatment were included in the CSU quiescent phase group. Another 30 healthy subjects who participated in the physical examination at the same time at our hospital′s physical examination center were selected to be included in the healthy control group. 5 ml of fasting elbow vein blood was collected from CSU active and stationary patients, as well as healthy subjects. The serum levels of IL-9, PAF, total IgE, IFN-γ, and IL-4 were detected using enzyme-linked immunosorbent assay. Pearson correlation test was used to analyze the correlation between serum IL-9, PAF levels and total IgE, IFN-γ, and IL-4 levels in CSU active patients.Results:The serum levels of IL-9, PAF, total IgE, and IL-4 in the CSU active phase group were higher than those in the CSU stationary phase group and healthy control group (all P<0.05), and the serum IFN-γ levels were lower than those in the CSU stationary phase group and healthy control group (all P<0.05). There was no statistically significant difference in the levels of the above indicators between the healthy control group and the CSU stationary group (all P>0.05). The serum levels of IL-9, PAF, total IgE, and IL-4 in the severe group were significantly higher than those in the mild and moderate groups (all P<0.05), and the serum IFN-γ levels were significantly lower than those in the mild and moderate groups (all P<0.05); The serum levels of IL-9, PAF, total IgE, and IL-4 in the moderate group were significantly higher than those in the mild group (all P<0.05), and the serum IFN-γ levels were significantly lower than those in the mild group ( P<0.05). Pearson correlation analysis showed that serum IL-9 and PAF levels were positively correlated with serum total IgE and IL-4 levels in CSU active phase patients (IL-9: r=0.726, 0.870, PAF: r=0.788, 0.795, all P<0.01), and negatively correlated with serum IFN-γ levels (IL-9: r=-0.831, PAF: r=-0.816, all P<0.01). Conclusions:The serum levels of IL-9 and PAF in patients with active CSU are elevated and correlated with total IgE, IFN-γ, and IL-4 levels, suggesting that IL-9 and PAF may be related to the occurrence and development of CSU.