Osteoporosis is a systemic metabolic disease characterized by decreased bone mass, leading to an increased risk of fractures. Although osteoporosis in children and adolescents is rare, its incidence in younger populations is showing an increasingly notable trend. The diagnostic criteria for osteoporosis in children and adolescents include a bone mineral density(BMD) Z-score of≤-2.0 accompanied by a significant fracture history, defined as two or more long bone fractures before the age of 10, three or more long bone fractures before the age of 19, or the presence of low-energy vertebral compression fractures even in the absence of low BMD. The genetic causes and underlying mechanisms of pediatric osteoporosis remain largely unknown, requiring further research to elucidate the molecular pathways involved. Such advances could help reduce the disease′s impact on growth and development and improve the quality of life in affected children and adolescents.

Osteoporosis is a systemic metabolic disease characterized by decreased bone mass, leading to an increased risk of fractures. Although osteoporosis in children and adolescents is rare, its incidence in younger populations is showing an increasingly notable trend. The diagnostic criteria for osteoporosis in children and adolescents include a bone mineral density(BMD) Z-score of≤-2.0 accompanied by a significant fracture history, defined as two or more long bone fractures before the age of 10, three or more long bone fractures before the age of 19, or the presence of low-energy vertebral compression fractures even in the absence of low BMD. The genetic causes and underlying mechanisms of pediatric osteoporosis remain largely unknown, requiring further research to elucidate the molecular pathways involved. Such advances could help reduce the disease′s impact on growth and development and improve the quality of life in affected children and adolescents.

Objective:To develop and validate a nomogram model for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) based on preoperative enhanced computed tomography imaging features and clinical data.Methods:The clinical data of 210 patients with HCC undergoing surgery in the Second Affiliated Hospital of Anhui Medical University from May 2018 to May 2022 were retrospectively analyzed, including 172 males and 38 females, aged (59±10) years old. Patients were randomly divided into the training group ( n=147) and validation group ( n=63) by systematic sampling at a ratio of 7∶3. Preoperative enhanced computed tomography imaging features and clinical data of the patients were collected. Logistic regression was conducted to analyze the risk factors for HCC with MVI, and a nomogram model containing the risk factors was established and validated. The diagnostic efficacy of predicting MVI status in patients with HCC was assessed by receiver operating characteristic (ROC) curve, calibration curves, decision curve analysis (DCA), and clinical impact curve (CIC) of the subjects in the training and validation groups. Results:The results of multifactorial analysis showed that alpha fetoprotein ≥400 μg/ml, intra-tumor necrosis, tumor length diameter ≥3 cm, unclear tumor border, and subfoci around the tumor were independent risk factors predicting MVI in HCC. A nomogram model was established based on the above factors, in which the area under the curve (AUC) of ROC were 0.866 (95% CI: 0.807-0.924) and 0.834 (95% CI: 0.729-0.939) in the training and validation groups, respectively. The DCA results showed that the predictive model thresholds when the net return is >0 ranging from 7% to 93% and 12% to 87% in the training and validation groups, respectively. The CIC results showed that the group of patients with predictive MVI by the nomogram model are highly matched with the group of patients with confirmed MVI. Conclusion:The nomogram model based on the imaging features and clinical data could predict the MVI in HCC patients prior to surgery.

Chronic refractory wound (CRW) is one of the most challengeable issues in clinic due to complex pathogenesis, long course of disease and poor prognosis. Experts need to conduct systematic summary for the diagnosis and treatment of CRW due to complex pathogenesis and poor prognosis, and standard guidelines for the diagnosis and treatment of CRW should be created. The Guideline forthe diagnosis and treatment of chronic refractory wounds in orthopedic trauma patients ( version 2023) was created by the expert group organized by the Chinese Association of Orthopedic Surgeons, Chinese Orthopedic Association, Chinese Society of Traumatology, and Trauma Orthopedics and Multiple Traumatology Group of Emergency Resuscitation Committee of Chinese Medical Doctor Association after the clinical problems were chosen based on demand-driven principles and principles of evidence-based medicine. The guideline systematically elaborated CRW from aspects of the epidemiology, diagnosis, treatment, postoperative management, complication prevention and comorbidity management, and rehabilitation and health education, and 9 recommendations were finally proposed to provide a reliable clinical reference for the diagnosis and treatment of CRW.

In the current clinical diagnosis, medical images have become an important basis for diagnosis, and different modes of medical images provide different tissue information and functional information. Single-mode images can only provide single diagnostic information, by which difficult and complicated diseases cannot be diagnosed, and comprehensive and accurate diagnostic results can be obtained only with the help of multiple diagnostic information. The multimodal fusion technology fuses multiple modes of medical images into single-mode images, and thus the single-mode images contain complementary information between multiple modes of images, so that sufficient information for clinical diagnosis can be obtained in a single image. In this paper, the multimodal medical image fusion methods are sorted into two types, namely the traditional fusion method and the fusion method based on deep learning.