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2023 Vol. 42, No. 2 Published: 2023-04-20

Reviews Communications Regular Papers

Regular Papers

	129	Research of Joint-Dataset Abdominal Multi-Organ Segmentation Method
		Wu Zejing, Chen Chunxiao, Chen Zhiying, Xu Junqi, Fu Xue
		DOI: 10.3969/j.issn.0258-8021.2023.02.001
		Abdominal multi-organ segmentation of medical images is essential for clinical applications such as surgical treatment planning and assisted diagnosis. Most published medical image datasets label partial organs only, which is difficult for accurate multiple organs segmentation of medical images, thus the segmentation model developed by this approach is not generally applicable. In this paper, we proposed a joint-dataset-based multi-organ segmentation abdominal network: C2F-MSNet, which contained coarse segment and fine segment. During coarse segmentation, the explicit conditional control module was employed for the training of the network on multiple partially labeled datasets, while the self-attention module and the deep supervision strategy were implemented. During the fine segmentation, the fine segmentation area was indexed by rough segmentation results, and the fine segmentation was guided and the multi-scale fine segmentation network was constructed. Experiments were performed on 663 CT data obtained from KiTS, Decathlon-liver, Decathlon-spleen and Decathlon-pancreas datasets, evaluated by dice similarity coefficient (DSC) and Hausdorff distance (HD). The results of DSC reached 0.967, 0.964, 0.956, and 0.838 for kidney, liver, spleen, and pancreas, respectively, and that of HD reached 12.51, 25.02, 6.68, and 12.58, respectively. Experiment results showed that the C2F-MSNet effectively solved the training problem of multiple partially labeled datasets and achieved accurate multi-organ segmentation in the joint datasets.
		2023 Vol. 42 (2): 129-138 [Abstract] ( 254 ) HTML (1 KB) PDF (5336 KB) ( 488 )

	139	Prediction of Breast Cancer Neoadjuvant Chemotherapy Based on Dynamic Enhanced Mode Analysisof Longitudinal Time Images
		Su Tianfang, Fan Ming, Li Lihua
		DOI: 10.3969/j.issn.0258-8021.2023.02.002
		Due to its long treatment cycle, neoadjuvant chemotherapy has important clinical reference value for early and accurate prediction of the final curative effect of chemotherapy. Due to the existence of factors such as tumor heterogeneity and image partial volume effect, the traditional radiomics method makes it difficult to further improve the prediction accuracy. Features were used to predict the efficacy of neoadjuvant chemotherapy. In the experiment, images of 191 breast cancer patients collected were preprocessed to obtain images of regions of interest in tumors and glands, and radiomics features were extracted, and the longitudinal time feature change rate was calculated. The random forest model was used to predict the curative effect and combined with the AUC index to evaluate and analyze the classification performance of the model. The results showed that the best AUC of 0.791 was achieved in the task of predicting raw images before decomposition. In the image depth decomposition experiment, the distribution of longitudinal pattern changes in tumor images was more significantly different among treatment groups (P<0.01), and the best AUC of 0.888 was achieved in the prediction task of image features of different dynamic patterns. In summary, by combining the multi-regional images and longitudinal time features, compared with the images before decomposition, the images of different modes after deep decomposition improved the curative effect prediction ability based on the feature level, which was expected to provide important reference for early diagnosis of patients and program adjustment in accordance with.
		2023 Vol. 42 (2): 139-147 [Abstract] ( 214 ) HTML (1 KB) PDF (4216 KB) ( 243 )

	148	Reconstruction of Thorax Image Based on Deep CG Method for Electrical Impedance Tomography
		Wang Zichen, Fu Rong, Zhang Xinyu, Wang Di, Chen Xiaoyan
		DOI: 10.3969/j.issn.0258-8021.2023.02.003
		To improve the spatial resolution of electrical impedance tomography, a novel method based on conjugate gradient (CG) with rapid pre-reconstruction and deep stack autoencoder post-processing was proposed (Deep CG). The core idea is that the merging ofnumerical reconstruction algorithm with deeplearning-based method makes the structure and conductivity distribution of the thorax more accurate. Firstly, the mathematical reconstruction algorithm CG was adopted to pre-reconstruct the coarse image, and the mapping between boundary voltage and conductivity distribution in the chest was achieved. Next, to take full advantages of the different spatial features, the stack autoencoder was employed to connect the encoding and the decoding modules hierarchically, which realized the feature extraction (FE) and the image reconstruction (IR). Finally, to train the model, the dataset was constructed from the number of 400 clinical CT slices, a mixed supervised method was employed to adjust the model parameters, which not only avoided the dispersion of the information flow and gradient flow, but alsooptimized the parameters of Deep CG method. The relative error (RE) and correlation coefficient (CC) were adopted to evaluate the image quantitively. The images were compared to the traditionalnumerical algorithm and a full connected neural network. The results showed that the RE was decreased to 0.11 from 0.5 and 0.24, and the CC was improved to 0.96 from 0.8 and 0.9. The proposed method was able to reconstruct EIT images with higher spatial resolution and clear boundary,which is expected to put forward EIT techniques to the further applications and researches.
		2023 Vol. 42 (2): 148-157 [Abstract] ( 179 ) HTML (1 KB) PDF (7143 KB) ( 98 )

	158	Effects of Transcranial Magnetic Stimulation in Different Protocols on Causal Network Connection of Local Field Potential during Working Memory Task in Rats
		Guo Miaomiao, Ji Lihui, Zhang Tianheng, Wang Zhonghao, Xu Guizhi
		DOI: 10.3969/j.issn.0258-8021.2023.02.004
		In recent years, non-invasive clinical neuromodulation methods have attracted intensive research interests. Among the methods, transcranial magnetic stimulation can non-invasively induce an induced electric field in the cerebral cortex, thereby regulating the function of the nervous system, and its regulatory effect on cognitive function is particularly significant. In this paper, the rats in stimulation group are treated in 5 Hz repetitive transcranial magnetic stimulation (rTMS), continuous theta burst stimulation (cTBS), and intermittent theta burst stimulation (iTBS). There were 6 rats in each group. The local field potentials of rats during the working memory task were recorded. The causal connection network of local field potential in the θ band and γ band was constructed based on the directional transfer function, and the characteristic parameters of the causal network such as the DTF value, average connection density, and global efficiency of each group of rats were calculated. Furthermore, the effects of different protocols of transcranial magnetic stimulation on behavioral ability was discussed. The results showed that rats in the rTMS[(4.83±1.84) d)] and iTBS[(5.00±1.55) d] groups learned more quickly than those in the control[(7.83±2.40) d) and cTBS[(9.33±2.07) d] groups(P<0.05) during working memory behavior tasks. There was no statistical difference in the DTF values of the LFPs signal in θ band between the groups (P >0.05). The DTF value, connection density, and global network efficiency of the γ band in the rTMS and iTBS groups were higher than those in the control and cTBS groups (P<0.05). The results indicated that 5 Hz rTMS and iTBS protocol enhanced the information interaction of gamma oscillations among the neuron clusters in the prefrontal cortex, and improved the working memory ability of rats. These findings can provide references for the research of TMS in clinical application and brain cognitive function.
		2023 Vol. 42 (2): 158-167 [Abstract] ( 140 ) HTML (1 KB) PDF (5128 KB) ( 181 )

	168	Epileptic Seizure Prediction Based on Continuous Wavelet Transform and Generative Adversarial Network
		Liao Jiahui, Yang Feng, Zhan Chang'an, Zhang Liyun
		DOI: 10.3969/j.issn.0258-8021.2023.02.005
		Nowadays, semi-supervised deep learning model has been successfully applied in epileptic seizure forecasting based on electroencephalogram (EEG), however, there is still room for improvement in EEG preprocessing method and stability of semi-supervised model. This paper proposed an improved solution which combined continuous wavelet transform (CWT) and Wasserstein generative adversarial network based gradient penalty (WGAN-GP). Firstly, CWT was performed on unlabeled EEG to acquire spectrograms, and WGAN-GP was trained using the EEG dataset of specific patients to get a high-performance feature extractor. Then the trained discriminator of WGAN-GP was used as a feature extractor and two fully connected layers were used as classifier. A small amount of spectrogram of CWT of labeled EEG were used to complete the training of classifier model. Finally, the discriminator of WGAN-GP and the fully-connected network constituted a semi-supervised deep learning prediction model, carrying out epileptic seizure forecasting. The proposed semi-supervised patient-specific seizure forecasting method was evaluated by CHB-MIT scalp EEG dataset and compare the performance with present semi-supervised method. The sensitivity, specificity, accuracy and AUC of the proposed method reached 82.69%, 67.48%, 82.08% and 84.03%, respectively, improving the original performance by 14.48%, 34.45%, 7.87% and 11.4%. Compared to the present semi-supervised method, the difference of the prediction performance of CWT-WGAN-GP and current methods is showing significance (P<0.05). The result showed that the combination of CWT and WGAN-GP effectively improved the prediction performance of semi-supervised deep learning model, and played an optimized role of unsupervised feature extraction in the epileptic seizure prediction.
		2023 Vol. 42 (2): 168-179 [Abstract] ( 168 ) HTML (1 KB) PDF (5379 KB) ( 300 )

	180	Fiber Re-Tracking Based on Flow Field Distribution
		Xie Fei, Feng Yuanjing, He Jianzhong, Li Mao
		DOI: 10.3969/j.issn.0258-8021.2023.02.006
		White matter fiber tracking can reconstruct the direction of brain fibers. However, due to the limitation of resolution, the imaging voxels show zigzag boundaries, leading to the early termination of the reconstructed fiber bundles at the white matter region boundary. In addition, the lack of voxel direction information caused by signal noise also leads to premature termination of fiber tracking. In view of these problems, a fiber stop tracking algorithm was proposed to obtain more accurate result of the fiber tracking. Firstly, the flow field distribution model of the fiber local structure was established, and the fiber direction information of any point in the voxel was expressed by the flow field distribution. Next, based on the voxel flow field distribution model, the continuity of the fiber tracking stop point was calculated for the fiber tracking, and more accurate fiber results were obtained. Two experimental data sets (including ISMRM 2015 data set of 25 major fiber bundles and a set of clinical data sets from Stanford University database) were used to verify the proposed method. Firstly, the proposed algorithm was quantitatively analyzed on the simulation data set by using the tractometer quantitative index, the results showed that the effective number of valid bundles (VB), valid connections (VC) and no connections (NC) of the algorithm were 24, 51.3% and 12.9%, respectively. Compared with SD Stream, VB increased by 2 bundles, VC increased by 19.1%, and NC decreased by 22.8%. The effectiveness of this method was verified through the qualitative analysis of clinical data. The experimental results showed that the algorithm could effectively avoid the premature termination of fiber tracking, improving the effective fiber ratio of the fiber tracking, reducing the proportion of unconnected fibers, and improving the accuracy of fiber tracking results.
		2023 Vol. 42 (2): 180-188 [Abstract] ( 121 ) HTML (1 KB) PDF (13514 KB) ( 70 )

	189	Characterization of Cell Activity Distribution in Tissue Engineering Based on Scattering OCT
		Lu Ming, Wang Ling, Yang Shanshan, Xu Mingen
		DOI: 10.3969/j.issn.0258-8021.2023.02.007
		Non-invasive and label-free detection of cell activity distribution in tissue engineering is of great significance. This paper proposed a scattering optical coherence tomography (OCT) technology to quantify and characterizing the cell activity distribution in a three-dimensional tissue model, and proposed an optimized depth-resolved (ODR) scattering algorithm to reconstruct the cell/material scatter contrast enhanced images, achieving the quantitative analysis of the correlation between scattering coefficients, cell concentration and activity status, and characterize the cell activity distribution in three-dimensional tissues. The experimental results of multi-layer sample model showed that the ODR scattering algorithm was able to improve the sensitivity and depth of sample scattering imaging. The human hepatocellular carcinoma cell C3A and human dermal fibroblast cell-laden hydrogel were used to verify that the cell concentration and cell activity in the material are linearly correlated with the scattering coefficient (92.07%) and Pearson correlation coefficient (99.13%) respectively, and the scattering coefficient could be used to quantify the cell concentration and survival status in the hydrogel scaffold. ODR-based scattering OCT realized the non-invasive and label-free detect of cell activity distribution in tissue engineering scaffolds, allowing to carry out long-term research on the cell activity distribution of cell-laden scaffolds, therefore, having potentials of a powerful monitoring tool for disease model construction, drug screening and cell therapy.
		2023 Vol. 42 (2): 189-200 [Abstract] ( 121 ) HTML (1 KB) PDF (5547 KB) ( 177 )

	201	Effects of Surface Nano-Pattern Modification of Regenerated Silk Fibroin Film on CellAdhesion and Proliferation
		Ouyang Qinjun, Liu Xiaojiao, Yao Xiang, Zhang Yaopeng
		DOI: 10.3969/j.issn.0258-8021.2023.02.008
		Improving the cytocompatibility of regenerated silk fibroin (RSF) biomaterials is very important to expand its application in the biomedical fields of cell culture and tissue repair. This study prepared three kinds of special nano-island-patterned RSF films by plasma etching with different etching times, and further investigated their effects on the adhesion and proliferation of NIH3T3 cells, and all quantification experiments were set at least three replicates (n≥3). The micrograph observation results after 1 d of cell culture showed that cells on the nano-pattern modified RSF films had better adhesion morphology when compared to those on the non-modified flat RSF film. The results of OD value detected by CCK-8 after 1 and 4 d of cell culture showed that nano-pattern modified RSF films significantly promoted the cell proliferation compared to the non-modified flat RSF film. Moreover, cells on the 30 min-etched film presented the highest OD value (OD=1.13±0.32), which was much higher than that of on the non-modified flat RSF film (OD=0.46±0.03, P＜0.001). In summary, plasma etching provided a simple, rapid, and large-scale nano-pattern modification strategy to improve the cytocompatibility of RSF materials, which is expected to provide important references and guidance for the surface modification of RSF and other biomaterials.
		2023 Vol. 42 (2): 201-209 [Abstract] ( 134 ) HTML (1 KB) PDF (5998 KB) ( 187 )

Reviews

	210	Research Progress on Sensing Technology and Clinical Application of Digestive Tract PhysiologicalParameters Wireless Capsule
		Hu Xiaoyu, Feng Jie, Zhao Xiaxia, Huang Xiaojun
		DOI: 10.3969/j.issn.0258-8021.2023.02.009
		The physiological mechanism of the digestive tract has been high-profile for a long time. With the rapid development of sensors and detection technologies, there has been an increasing focus on the gastrointestinal physiological parameters wireless capsules and attempts to expand their indications to solve the problem that various physiological information in the human gastrointestinal tract can be obtained difficulty. The information related to gastrointestinal motility can be acquired by micro-devices with integrated sensors, thus the dynamic curve and even peristaltic model of the digestive tract can be established to provide clinical evidence for the diagnosis and mechanism exploration of functional gastrointestinal diseases. In this review, firstly, the types, principles, and research progress of sensors applied in wireless capsules were described according to the different types of detection information. Next, a summary of the current clinical applications research status of the wireless capsules has been made, including the detection of pH, temperature, and pressure, as well as the continuous fixed-point monitoring of the physical and chemical digestive tract environment. The functional expansion research of the wireless capsules was introduced as well, such as the detection of intestinal gases, flora, digestive enzymes, etc. Finally, the R&D challenges and corresponding strategies of the wireless capsules for physiological parameters were discussed, providing useful reference information for future research in this field.
		2023 Vol. 42 (2): 210-218 [Abstract] ( 157 ) HTML (1 KB) PDF (913 KB) ( 681 )

	219	Application Progress of Pulsed Electric Field Ablation in the Treatment of Atrial Fibrillation
		Zang Lianru, Ji Xingkai, Zhang Hao, Yan Shengjie, Wu Xiaomei
		DOI: 10.3969/j.issn.0258-8021.2023.02.010
		Atrial fibrillation (AF) is one of the most common arrhythmias in clinical practice, and pulmonary vein isolation of the left atrium is an effective method for treating atrial fibrillation. Pulsed electric field ablation (PFA) is a new ablation technique that uses high voltage and short duration to injure tissue by an irreversible electroporation mechanism. For the application of PFA in the field of AF treatment, firstly, the principle of PFA was introduced; then results of clinical experiments were used to demonstrate the advantages of PFA, including the non-thermal effect that could not only achieve effective myocardial tissue injury but also reduce the risk of injury to adjacent myocardial tissues (such as pulmonary veins, esophagus, phrenic nerves, blood vessels), fast ablation speed, and low contact dependence. The current mainstream PFA systems, the characteristics of ablation catheters corresponding to these systems, and clinical applications were also introduced. Finally, suggestions for the problems to be solved in the application of PFA in the treatment of AF at present were proposed, and perspectives for the future development of this field were provided.
		2023 Vol. 42 (2): 219-228 [Abstract] ( 177 ) HTML (1 KB) PDF (4842 KB) ( 457 )

	229	Research Progress on Inhibitory Strategies of Heat Shock Proteins in Photothermal Therapy
		Meng Yiling, Wen Tao, Xu Haiyan
		DOI: 10.3969/j.issn.0258-8021.2023.02.011
		Photothermal therapy (PTT) can kill tumor cells accurately and efficiently by using photothermal agents under the irradiation of external light source, so it has a broad application prospect in the treatment of solid tumors. However, recent studies have observed that PTT may lead to abnormal upregulation of heat shock proteins (HSPs) in the cells, which enhances the heat resistance of cells and affects the therapeutic effect. Aiming to overcome the adverse influence of HSPs on the efficiency of photothermal treatment, various strategies have been developed in recent years. In this paper, inhibitory strategies for HSPs in PTT were classified according to the different principles, and the corresponding research progresses were introduced through study cases. The strategies mainly include the application of HSPs inhibitors in PTT system, blocking the glycolysis metabolism of tumor cells, inducing the production of lipid peroxide or highly reactive oxygen species (ROS), and HSPs gene interference and gene knockout. In addition, the advantages and limitations of the various strategies were compared and summarized. At the end, perspectives of HSP inhibition in photothermal therapy systems were discussed, and we proposed that joint strategies or designing new carriers and drugs would be promising to overcome the limitations of existing strategies.
		2023 Vol. 42 (2): 229-234 [Abstract] ( 127 ) HTML (1 KB) PDF (809 KB) ( 545 )

	235	Advances and Perspectives of Nano-Drug Delivery Systems Targeting Inflammation and Oxidative Stress during Cerebral Ischemia-Reperfusion Injury
		Xiao Xinyu, Gao Yu, Jiang Ning, Peng Qiling
		DOI: 10.3969/j.issn.0258-8021.2023.02.012
		Stroke is the second leading cause of death worldwide, 80 % of which is ischemic stroke. Reperfusion injury including inflammation, oxidative stress etc. is the key to prognosis of cerebral ischemia. Recently, functionalized nano-drug delivery systems,are widely applied in the cerebral ischemia for their characteristics of biocompatibility, tractability, and strong specificity. This paper reviews the research progresses on metal nano-delivery systems, biocompatible nano-delivery systems, and polymer nano-delivery systems that inhibit inflammatory responses and eliminate oxidative stress in the ischemia/reperfusion injury. The future development prospects of nano drug-delivery systems are proposed as well.
		2023 Vol. 42 (2): 235-241 [Abstract] ( 107 ) HTML (1 KB) PDF (7157 KB) ( 200 )

	242	Research Progress onTherapeutic Peptides Loaded with Nanocarriers
		Zheng Shanshan, Cai Yue, Gong Yubei, Hong Yulu, Sun Xuanrong
		DOI: 10.3969/j.issn.0258-8021.2023.02.013
		At present, due to wide indications, high safety and remarkable efficacy, peptide drugs have been widely used in the prevention, diagnosis and treatment of tumors, hepatitis, diabetes, AIDS and many other diseases. However, natural peptides are easy to be degraded when entering biological systems and can be quickly removed through the blood circulation. Thus, peptide-based nanomedicine systems, which are fabricated by physical encapsulation and chemical conjugation, have become a hotspot for researchers to construct the novel and intelligent drug delivery systems, because of high biological safety, good biocompatibility, and easy modification. Herein, we firstly described the common biological properties of bioactive peptides, such as antibacterial, antiviral, and antitumor effects, and then summarized the research on the construction of nanomedicine for drug delivery based on the bioactive peptides. Finally, we provided perspectives on the development of peptide-based nanomedicine which shows considerably promising future in the drug delivery.
		2023 Vol. 42 (2): 242-251 [Abstract] ( 163 ) HTML (1 KB) PDF (2223 KB) ( 652 )

Communications

	252	*Preservation Duration of ex-vivo* Rat Heart Using a Novel Organ Preservation SolutionContaining Glutaraldehyde Polymerized Bovine Hemoglobin**
		You Kewei, Liu Jiaxin, Wang Wengang, Zhang Yanpeng
		DOI: 10.3969/j.issn.0258-8021.2023.02.014

		2023 Vol. 42 (2): 252-256 [Abstract] ( 147 ) HTML (1 KB) PDF (5609 KB) ( 113 )

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