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.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.
3.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.
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.Application of Histone Deacetylase Inhibitor in Acute Myeloid Leukemia
Dan-Dan CHEN ; Ke-Ning QIN ; Chun-Li LÜ ; Jian-Ye ZENG ; Xiao-Min WANG
Progress in Biochemistry and Biophysics 2024;51(6):1393-1405
Acute myeloid leukemia (AML) is a malignant clonal disease of hematopoietic stem cells, characterized by the proliferation of abnormal primordial cells of myeloid origin in bone marrow, blood and other tissues. At present, the standard induction therapy for AML mainly includes “3+7” standard treatment(anthracycline combined with cytarabine), allogeneic hematopoietic stem cell transplantation (Allo-HSCT) and targeted drug therapy. However, AML cells usually express high levels of P-glycoprotein, which mediates the efflux of chemotherapeutic drugs, which makes AML cells resistant to chemotherapy, resulting in many patients who are not sensitive to chemotherapy or relapse after complete remission. And some patients can not tolerate intensive therapy or lack of donors and can not use Allo-HSCT therapy. Therefore, it is of great clinical significance to find new drugs to improve the efficacy of AML patients. Epigenetic disorders play a key role in the pathogenesis of many diseases, especially cancer. Studies have shown that most AML patients have epigenetic regulatory gene mutations, such as DNMT3A, IDH and TET2, and these mutations are potentially reversible, which has become one of the therapeutic targets of AML. Histone deacetylase inhibitors (HDACi) can regulate the balance between histone acetylation and deacetylation, change the expression of proto-oncogenes or tumor suppressor genes that control cancer progression from epigenetics, and play an important role in many kinds of tumor therapy. At present, HDACi has shown the ability to induce differentiation, cell cycle arrest and apoptosis of AML cells. The mechanism may be mainly related to HDACi inducing chromatin conformation opening of tumor suppressor gene by inhibiting HDAC activity, promoting oncogene damage and preventing oncogene fusion protein from recruiting HDAC. Although the preclinical outcome of HDACi is promising, it is not as effective as the conventional therapy of AML. However, the combination strategy with various anticancer drugs is in clinical trials, showing significant anti-AML activity, improving efficacy through key targeting pathways in a typical synergistic or additive way, increasing AML sensitivity to chemotherapy, reducing tumor growth and metastasis potential, inhibiting cell mitotic activity, inducing cell apoptosis, regulating bone marrow microenvironment, which provides a good choice for the treatment of AML. Especially for those AML patients who are not suitable for intensive therapy and drug resistance to chemotherapy. This review introduces the relationship between HDAC and cancer; the classification of HDAC and its function in AML; the correlation between HDAC and AML; the clinical application of five types of HDACi; preclinical research results and clinical application progress of six kinds of HDACi in AML, such as Vrinota, Belinostat, Panobinostat, Valproic acid, Entinostat, and Chidamide, the mechanism of HDACi combined with other anticancer drugs in AML indicates that the current HDACi is mainly aimed at various subtypes of pan-HDAC inhibitors, with obvious side effects, such as fatigue, thrombocytopenia, nausea, vomiting, diarrhea. In recent years, the next generation of HDACi is mainly focused on the selectivity of analogues or isomers. Finding the best combination of HDACi and other drugs and the best timing of administration to balance the efficacy and adverse reactions is a major challenge in the treatment of AML, and the continued development of selective HDACi with less side effects and more accurate location is the key point for the development of this drug in the future. It is expected to provide reference for clinical treatment of AML.
7.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
8.Experience of ZHANG Boli in Staged Treating Very Early Onset Inflammatory Bowel Disease Based on the Theory of “Similar Diseases and Syndromes of Damp-Turbidity-Phlegm-Rheum”
Guangning QIN ; Yaoyuan LIU ; Ning GAO ; Ke XIONG ; Xinyao JIN ; Feng JIANG
Journal of Traditional Chinese Medicine 2023;64(22):2282-2286
This article summarizes the experience of Professor ZHANG Boli in the staged treatment of very early onset inflammatory bowel disease (VEO-IBD). Grounded in the theory of “similar diseases and syndromes of damp-turbidity-phlegm-rheum”, it is believed that dampness and turbidity are crucial pathogenic factors in VEO-IBD. During the acute phase, the core pathogenesis centers on the accumulation of turbid toxins in the intestines. The treatment focuses on dispelling dampness and clearing turbidity to eliminate turbid toxins, while also regulating the flow of qi and nourishing the spleen and kidney. During the remission phase, the core pathogenesis involves spleen and kidney deficiency, which is treated by invigorating the spleen and warming the kidney to strengthen the body resistance. Additionally, promoting blood circulation and eliminating stasis is integrated throughout the treatment process. Medications are chosen to be mild and gentle, emphasizing balance and harmony, and attention is given to the methods of administration and psychological well-being, ensuring comprehensive care for both body and mind.
9.Quick guideline for diagnosis and treatment of novel coronavirus Omicron variant infection
Guang CHEN ; Tao CHEN ; Sainan SHU ; Xiaojing WANG ; Ke MA ; Di WU ; Hongwu WANG ; Yan LIU ; Wei GUO ; Meifang HAN ; Jianxin SONG ; Tonglin LIU ; Shusheng LI ; Jianping ZHAO ; Yuancheng HUANG ; Yong XIONG ; Zuojiong GONG ; Qiaoxia TONG ; Jiazhi LIAO ; Feng FANG ; Xiaoping LUO ; Qin NING
Chinese Journal of Clinical Infectious Diseases 2023;16(1):26-32
Novel coronavirus Omicron variant infection can cause severe illness and even death in certain populations. Omicron variant infection may lead to systemic inflammatory response, coagulation disorder, multi-organ dysfunction and other pathophysiological changes, which are different from other Novel coronavirus variants to a certain extent, so therapeutic strategies should not be the same. The National Medical Center for Major Public Health Events invited experts in fields of infectious diseases, respiratory medicine, intensive care, pediatrics and fever clinic to develop this quick guideline based on the current best evidence and extensive clinical practices. This quick guideline aims to standardize the diagnosis and treatment of novel coronavirus Omicron infection, and to improve the disease management abilities of clinicians.
10.Metabolic Disease Management Guideline for National Metabolic Management Center(2nd edition)
Weiqing WANG ; Yufan WANG ; Guixia WANG ; Guang NING ; Dalong ZHU ; Ping LIU ; Libin LIU ; Jianmin LIU ; Zhaoli YAN ; Xulei TANG ; Bangqun JI ; Sunjie YAN ; Heng SU ; Jianling DU ; Sheli LI ; Li LI ; Shengli WU ; Jinsong KUANG ; Yubo SHA ; Ping ZHANG ; Yifei ZHANG ; Lei CHEN ; Zunhai ZHOU ; Chao ZHENG ; Qidong ZHENG ; Zhongyan SHAN ; Dong ZHAO ; Zhigang ZHAO ; Ling HU ; Tingyu KE ; Yu SHI ; Yingfen QIN ; Mingjun GU ; Xuejiang GU ; Fengmei XU ; Zuhua GAO ; Qijuan DONG ; Yi SHU ; Yuancheng DAI
Chinese Journal of Endocrinology and Metabolism 2023;39(6):538-554
The latest epidemiological data suggests that the situation of adult diabetes in China is severe, and metabolic diseases have become significant chronic illnesses that have a serious impact on public health and social development. After more than six years of practice, the National Metabolic Management Center(MMC) has developed distinctive approaches to manage metabolic patients and has achieved a series of positive outcomes, continuously advancing the standardized diagnosis and treatment model. In order to further improve the efficiency, based on the first edition, the second edition guideline was composed by incorporating experience of the past six years in conjunction with the latest international and domestic guidelines.

Result Analysis
Print
Save
E-mail