1.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
Objective:
This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery.
Methods:
This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression.
Results:
Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability.
Conclusion
Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.
2.Material basis and action mechanism of drug-containing serum of Modified Erxian Pill inhibiting macrophage pyroptosis
Siyuan LI ; Yuru WANG ; Ye XU ; Di GUO ; Nan NAN ; Yang LIU ; Jie ZHAO ; Huiqin HAO
Chinese Journal of Tissue Engineering Research 2025;29(19):4029-4037
BACKGROUND:Our previous study found that Modified Erxian Pill could alleviate inflammation in collagen-induced arthritis rats,but its mechanism needs to be further verified. OBJECTIVE:To analyze the components absorbed in the blood of Modified Erxian Pill,and observe the effect of the drug-containing serum of Modified Erxian Pill on pyroptosis of J774A.1 macrophages. METHODS:(1)Analysis of components absorbed in the blood of Modified Erxian Pill:Ultra-high performance liquid chromatography-high resolution mass spectrometry was used to detect and identify Modified Erxian Pill and its components absorbed in the blood.(2)Effect of the drug-containing serum of Modified Erxian Pill on pyroptosis of J774A.1 macrophages:Molecular docking technology was used to initially verify the sesquiterpenoids and NLRP3 in components absorbed in the blood of Modified Erxian Pill.J774A.1 macrophages were randomly divided into blank control group,lipopolysaccharide+adenosine triphosphate group,and lipopolysaccharide+adenosine triphosphate+Modified Erxian Pill with low(2.5%),medium(5%),and high(10%)dose groups.The release of lactate dehydrogenase in the cell supernatant of each group was detected according to the kit instructions.The levels of interleukin-1β and interleukin-18 in cell supernatant were detected in each group by ELISA.The cell membrane damage was detected by Hoechst/PI staining.The expression levels of NLRP3,Caspase-1,GSDMD,and GSDMD-N protein in the cells of each group were detected by western blot assay. RESULTS AND CONCLUSION:(1)A total of 32 active components of Modified Erxian Pill were identified,and 21 components entered the blood.The main components into blood included a variety of sesquiterpenoids.(2)Molecular docking results showed that 3-O-Acetyl-13-deoxyphomenone,Incensol oxide,Atractylenolide III,Rupestonic acid,and 3,7-Dihydroxy-9,11-eremophiladien-8-one had good binding activity with NLRP3.(3)Compared with the blank control group,lactate dehydrogenase activity and the expression levels of interleukin-1β and interleukin-18 were significantly increased in cell supernatant of lipopolysaccharide+adenosine triphosphate group(P<0.001).Hoechst/PI staining showed that the number of PI-positive cells was significantly increased.After the intervention of lipopolysaccharide+adenosine triphosphate+Modified Erxian Pill group,all of them showed different degrees of reduction.(4)Compared with the blank control group,NLRP3,Caspase-1,GSDMD,and GSDMD-N protein expression levels were significantly increased in the lipopolysaccharide+adenosine triphosphate group(P<0.05).Compared with lipopolysaccharide+adenosine triphosphate group,the protein expressions of NLRP3,Caspase-1,GSDMD,and GSDMD-N were significantly decreased in the lipopolysaccharide+adenosine triphosphate+Modified Erxian Pill group(P<0.05),and had a certain dose dependence.These findings verify that the drug-containing serum of Modified Erxian Pill may inhibit the pyroptosis of J774A.1 macrophages by regulating the NLRP3/Caspase-1/GSDMD pathway.
3.Network analysis of factors related to non suicidal self injury among middle school students in Guizhou Province
ZHAO Wenxin, TIAN Meng, CHEN Siyuan, WU Jinyi, GAO Ying, DENG Xiwen, ZHANG Wanzhu
Chinese Journal of School Health 2025;46(1):92-95
Objective:
To explore the relationship between related factors of non-suicidal self-injury behavior (NSSI) among middle school students in Guizhou Province, so as to provide the evidence for preventing high risk behaviors in adolescents.
Methods:
A stratified cluster random sampling method was used to select 1 034 junior and senior middle school students from Zunyi City, Qiannan Prefecture and Tongren City in Guizhou Province from April to October in 2023. Questionnaire survey was conducted to collect information including Adolescent Self injury Scale and Family Assessment Device. The R 4.4.1 software was employed for network analysis visualization, centrality indicators, and result stability assessment.
Results:
The detection rate of NSSI behavior among middle school students in Guizhou province was 29.6%, with a detection rate of 25.5% for boys and 33.1% for girls, showing a statistically significant difference ( χ 2=7.07, P <0.05). There were statistically significant differences in scores of emotional communication, egoism, family rules, positive communication, problem solving, expression of positive emotions and management of negative emotions self-efficacy, and bullying victimization in various dimensions between middle school students with and without NSSI ( Z =-13.66 to -7.05, P <0.01). NSSI among middle school students was positively correlated with social/relational bullying, depression and anxiety, and there were relatively close connections in the network ( r =0.35, 0.43, 0.42, P <0.01). Centrality indicators showed that the highest in strength and closeness centrality were stress ( Z =1.29, 1.58), the highest in betweenness centrality was for emotional communication ( Z =1.91), and the highest in expected influence index was for physical bullying ( Z =1.44)( P < 0.05).
Conclusions
Stress, emotional communication and physical bullying have significant impacts in the network of factors related to NSSI. Social/relational bullying, depression and anxiety have strong direct correlations with NSSI behavior among middle school students.
4.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
Objective:
This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery.
Methods:
This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression.
Results:
Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability.
Conclusion
Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.
5.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
Objective:
This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery.
Methods:
This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression.
Results:
Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability.
Conclusion
Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.
6.WANG Jianmin's Experience in Treating Cathartic Colon from the Perspective of "Keeping Sweet to Return Liquid"
Siyuan ZHANG ; Ming LI ; Kun TANG ; Ran TANG ; Yueyue ZHANG ; Yue ZHAO ;
Journal of Traditional Chinese Medicine 2025;66(11):1104-1108
To summarize Professor WANG Jianmin's experience in cathartic colon from "keeping sweet to return liquid". It is believed that the key to the pathogenesis of cathartic colon is fluid consumption and intestinal dryness, including yin depletion of spleen earth, and lack of sources for body fluids production; discordance of water and fire in kidneys, and irregular distribution of body fluids; and closure of the lungs and liver leads to inability of the flow of fluids. The treatment is based on the principle of "keeping sweet to return liquid", using sweet medicinals mainly, assistant with sour, bland and acrid medicinals, and self-prescribed Lipi Shengjin Decoction (理脾生津汤), Wenshen Runchang Decoction (温肾润肠汤), Kaifei Shunchang Decoction (开肺顺肠汤), Rougan Tongbian Decoction (柔肝通便汤) could be used to regulate spleen yin by the sweet and bland, and establish qi and promote fluid production; the sweet and warm medicinals can replenish water and fire, transform into qi, and distribute body fluids; the acrid and sweet can open lung depression, descend qi, and flow the body fluids; the sour and sweet can emolliate liver, move qi, and transform fluids.
7.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
Objective:
This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery.
Methods:
This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression.
Results:
Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability.
Conclusion
Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.
8.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
Objective:
This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery.
Methods:
This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression.
Results:
Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability.
Conclusion
Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.
9.Characteristics of mortality of injury in Gusu District from 2013 to 2023
ZHAO Siyuan ; XU Yan ; ZHANG Qiu
Journal of Preventive Medicine 2024;36(6):532-535
Objective:
To investigate the characteristics of mortality of injury among residents in Gusu District, Suzhou City, Jiangsu Province from 2013 to 2023, so as to provide the evidence for developing targeted measures of injury prevention and control.
Methods:
Gender, age and underlying cause of deaths due to injury in Gusu District were collected through Death Reporting Information System of Chinese Disease Prevention and Control Information System and Jiangsu Death Reporting Information System from January 1, 2013 to December 31, 2023. The crude mortality, Chinese-standardized mortality and world-standardized mortality of injury were analyzed, and the trend in mortality was analyzed using annual percent change (APC).
Results:
Totally 4 217 deaths due to injury were reported in Gusu District from 2013 to 2023. The crude, Chinese-standardized and world-standardized mortality rates were 51.58/105, 23.24/105 and 21.98/105, respectively, all showing a tendency towards a rise (APC=6.802%, 2.688% and 2.823%, all P<0.05). The crude mortality rate of injury was higher in women than in men (54.61/105 vs. 48.41/105, P<0.05). The five most common causes of injury included fall (32.99/105), traffic accidents (6.03/105), suicide (4.23/105), drowning (3.00/105) and asphyxia (2.16/105), accounting for 93.86% of the total number of deaths. The crude mortality rates of fall, suicide and asphyxia appeared a tendency towards a rise (APC=9.724%, 6.333% and 5.638%, all P<0.05). The crude mortality rates of injury among men, women and overall residents appeared a tendency towards a rise with age (all P<0.05). Fall was the primary cause of injury death among residents aged 65 years and above, and suicide was the primary cause of injury death among residents aged 15 to 44 years.
Conclusions
The crude mortality of injury appeared a tendency towards a rise in Gusu District from 2013 to 2023. The main causes of death were fall, traffic accidents, suicide, drowning and asphyxia, with the crude mortality of fall, suicide and asphyxia showing an upward trend.
10.Application of a deep learning-based three-phase CT image models for the automatic segmentation of gross tumor volumes in nasopharyngeal carcinoma
Guorong YAO ; Kai SHEN ; Feng ZHAO ; Siyuan WANG ; Zhongjie LU ; Kejie HUANG ; Senxiang YAN
Chinese Journal of Radiological Medicine and Protection 2024;44(2):111-118
Objective:To investigate the effectiveness and feasibility of a 3D U-Net in conjunction with a three-phase CT image segmentation model in the automatic segmentation of GTVnx and GTVnd in nasopharyngeal carcinoma.Methods:A total of 645 sets of computed tomography (CT) images were retrospectively collected from 215 nasopharyngeal carcinoma cases, including three phases: plain scan (CT), contrast-enhanced CT (CTC), and delayed CT (CTD). The dataset was grouped into a training set consisting of 172 cases and a test set comprising 43 cases using the random number table method. Meanwhile, six experimental groups, A1, A2, A3, A4, B1, and B2, were established. Among them, the former four groups used only CT, only CTC, only CTD, and all three phases, respectively. The B1 and B2 groups used phase fine-tuning CTC models. The Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD95) served as quantitative evaluation indicators.Results:Compared to only monophasic CT (group A1/A2/A3), triphasic CT (group A4) yielded better result in the automatic segmentation of GTVnd (DSC: 0.67 vs. 0.61, 0.64, 0.64; t = 7.48, 3.27, 4.84, P < 0.01; HD95: 36.45 vs. 79.23, 59.55, 65.17; t = 5.24, 2.99, 3.89, P < 0.01), with statistically significant differences ( P < 0.01). However, triphasic CT (group A4) showed no significant enhancement in the automatic segmentation of GTVnx compared to monophasic CT (group A1/A2/A3) (DSC: 0.73 vs. 0.74, 0.74, 0.73; HD95: 14.17 mm vs. 8.06, 8.11, 8.10 mm), with no statistically significant difference ( P > 0.05). For the automatic segmentation of GTVnd, group B1/B2 showed higher automatic segmentation accuracy compared to group A1 (DSC: 0.63, 0.63 vs. 0.61, t = 4.10, 3.03, P<0.01; HD95: 58.11, 50.31 mm vs. 79.23 mm, t = 2.75, 3.10, P < 0.01). Conclusions:Triphasic CT scanning can improve the automatic segmentation of the GTVnd in nasopharyngeal carcinoma. Additionally, phase fine-tuning models can enhance the automatic segmentation accuracy of the GTVnd on plain CT images.


Result Analysis
Print
Save
E-mail