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.

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.

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.

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.

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.

Aromatic immunity in traditional Chinese medicine(TCM) is the medical knowledge accumulated in the process of people's struggling with diseases. It plays an important role in plague prevention, disease treatment, health preservation, and rehabilitation, and has profound TCM basic theoretical support and abundant modern scientific evidence. With the in-depth promotion of the Healthy China initiative and the succession of health needs in the post-COVID-19 era, how to practice the health concept of aromatic immunity in TCM and develop its health service resources with high quality has become an important proposition to be discussed urgently. This paper summarizes the cognitive process, puts forward the basic concept, discusses the scientific connotation and clinical application value, and looks forward to the future development trend of aromatic immunity in TCM, aiming to provide guidance for the development of great health products and promote the application of aromatic immunity in TCM in serving people's health.
Medicine, Chinese Traditional/methods* ; Humans ; COVID-19/immunology* ; China ; Drugs, Chinese Herbal/therapeutic use* ; SARS-CoV-2

Osteoporotic fractures(OPF) refer to the fractures caused by minor violence in the state of osteoporosis, seriously threatening the life and health of elderly patients. Drug and surgical therapies have limitations such as single targets, diverse adverse reactions, and poor prognosis. Kidney-tonifying traditional Chinese medicine(TCM) has good potential in the treatment of OPF. TCM can promote the healing of OPF by promoting angiogenesis in the early stage of bone healing, promoting osteogenic differentiation of bone marrow mesenchymal stem cells in the stage of bone repair, maintaining the balance of osteogenic and osteoclastic system in the stage of bone remodeling, and regulating the oxidative stress responses throughout the process of OPF healing. TCM can alleviate the pathological state of osteoporosis and promote fracture healing in OPF patients via multiple pathways and targets, demonstrating the advantages and potential of biphasic regulation.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Osteoporotic Fractures/metabolism* ; Animals ; Fracture Healing/drug effects* ; Medicine, Chinese Traditional ; Kidney/metabolism* ; Osteogenesis/drug effects*

OBJECTIVE: To evaluate the partial biomechanical properties of the posterior occipital muscles (rectus capitis posterior major, rectus capitis posterior minor, and obliquus capitis inferior) in patients with cervical vertigo. METHODS: A total of 30 patients with cervical vertigo admitted from April 2024 to September 2024 were included in the vertigo group, and 30 age-and gender-matched healthy subjects were recruited as the normal group. In the vertigo group, there were 21 females and 9 males, with an average age of (24.00±2.25) years;in the normal group, there were 22 females and 8 males, with an average age of (23.00±3.00) years. Shear wave elastography was used to measure the thickness and stiffness of the posterior occipital muscles in both groups. RESULTS: In the vertigo group, there were no statistically significant differences in the Young's modulus values (E) of stiffness of the posterior occipital muscles (rectus capitis posterior major, rectus capitis posterior minor, obliquus capitis inferior) between the left and right sides(P>0.05). The Young's modulus values(E) of stiffness of the right posterior occipital muscles (rectus capitis posterior major, rectus capitis posterior minor, obliquus capitis inferior) in the cervical vertigo group were (39.66±8.21) kPa, (45.61±5.85) kPa, and (43.73±5.22) kPa, respectively, which were significantly higher than those in the normal group 33.97(17.76) kPa, 41.38(8.99) kPa, 38.27(12.58) kPa, with statistically significant differences (P<0.05). In the vertigo group, the Young's modulus values(E) of stiffness of the left rectus capitis posterior major and left obliquus capitis inferior were (40.41±9.13) kPa and (42.11±6.20) kPa, respectively, which were significantly greater than those in the normal group (33.30±11.31) kPa, 38.94(14.62) kPa, with statistically significant differences(P<0.05);however, there was no statistically significant difference in the left rectus capitis posterior minor between the two groups(P>0.05). In the vertigo group, there were no statistically significant differences in the stiffness of the posterior occipital muscles (rectus capitis posterior major, rectus capitis posterior minor, obliquus capitis inferior) between the left and right sides(P>0.05). Additionally, there were no statistically significant differences in the thickness of the bilateral posterior occipital muscles between the vertigo group and the normal group (P>0.05). CONCLUSION The posterior occipital muscles of patients with cervical vertigo are stiffer than those of healthy individuals, while there is no significant difference in muscle thickness between the two groups.
Humans ; Female ; Male ; Elasticity Imaging Techniques/methods* ; Adult ; Vertigo/physiopathology* ; Neck Muscles/physiopathology* ; Young Adult