BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

Objective: This study compares the effects of lithium disilicate glass ceramic onlays and full crowns in restoring cracked teeth that have undergone root canal therapy, providing a reference for the restoration method of cracked teeth that have undergone root canal therapy. Methods: This study was approved by the hospital’s medical ethics committee, and all patients signed the informed consent form. Patients with cracked teeth who underwent root canal treatment in our hospital from January 2022 to January 2023 were enrolled in this study. According to the inclusion and exclusion criteria, 60 patients were screened and enrolled, with a total of 60 affected teeth. The patients were divided into the onlay group and full crown group at a ratio of 2:3 using the random number table method. Lithium disilicate glass ceramic onlays were used to restore the affected teeth in the onlay group (24 cases), and lithium disilicate glass ceramic full crowns were used to restore the affected teeth in the full crown group (36 cases). At 3, 6, and 12 months after the repair, the restoration effect was evaluated and compared with the modified USPH Standard (the aesthetic, functional, and biological aspects of restorations). According to the biological definition of survival, survival analysis was conducted on the affected teeth in both groups. Results: At 3, 6, and 12 months after the repair, 85% of cases in the onlay group achieved grade A, while 80% of cases in the full crown group achieved grade A. There was no statistically significant difference in the restoration effects between the onlay group and the full crown group (P > 0.05). The 12-month survival rate of cracked teeth in the onlay group reached 95.65%, and the 12-month survival rate of cracked teeth in the full crown group reached 94.12%. There was no statistically significant difference in the retention of the affected teeth (P > 0.05). There was no significant effect of age, gender, tooth position, dentition, direction of cracks, the number of marginal ridges associated with cracks, or the type of restoration on the survival status of cracked teeth. (P > 0.05). Conclusion For cracked teeth that have undergone root canal therapy, the short-term effect of lithium disilicate glass ceramic onlays is comparable to that of full crowns, and both have good short-term effects. Onlays are less invasive and are expected to become an alternative restoration method to full crowns.

Objective:To investigate and summarize the imaging and pathological features of non-acute occlusion following flow diverter (FD) implantation in animal models.Methods:Four experimental pigs (experimental group) that experienced non-acute occlusion (occlusion time exceeding 24 hours) within the FD stent implanted in the common carotid artery, and 19 pigs (control group) that did not experience stent occlusion during the same period were involved. Using an interventional approach under digital subtraction angiography (DSA), the 4 occluded FD lumens were mechanically opened. Optical coherence tomography (OCT), intravascular ultrasound (IVUS) and histopathological examinations were performed to evaluate the intraluminal composition and characteristics of the occlusive tissues. These findings were compared with non-occluded FD stents to summarize the imaging and pathological changes within the occluded FD lumen.Results:The occlusion times of the FD stents in the 4 experimental pigs were 16 weeks, 20 weeks, 20 weeks, and 24 weeks postoperatively. All occluded stents were successfully recanalized under DSA, with a technical success rate of 4/4. Among the 19 non-occluded FD stents, OCT and IVUS revealed uniform (16 stents) or non-uniform (3 stents) neointimal coverage of the stent struts, presenting as homogeneous high/slightly high signal intensity or medium echogenicity. Histopathological examination indicated that the neointima was primarily composed of smooth muscle cells and a small amount of fibrous connective tissues. In contrast, the 4 occluded FD stents demonstrated excessive neointimal proliferation and plaque formation, leading to luminal loss, as shown by OCT and IVUS. The occlusion tissues predominantly presented as homogeneous high signal intensity with weak attenuation (fibrous plaques) on OCT, with some regions showing blurred low signal intensity and strong attenuation (lipid plaques). IVUS presented homogeneous echogenicity (fibrous plaques) and hypoechogenic zones (lipid plaques). Histopathological examination showed that the occlusion tissues mainly consisted of smooth muscle cells, fibrous connective tissues, and lipids, accompanied by numerous foam cells and a minor presence of inflammatory cells.Conclusions:Histopathological examinations confirm that non-acute occlusion of FD is mainly caused by excessive hyperplasia of intima along with the formation of fibrous plaques and lipid plaques. OCT and IVUS have typical finding in imaging that can assist in determining the cause of stent occlusion as well as the lesion's nature, thereby providing crucial guidance for subsequent clinical treatment and drug selection.

Objective:To observe the early clinical efficacy of 3D-printed modular supporting prosthesis for reconstruction of lacunar bone defect caused by giant cell tumor of the distal femur.Methods:From May 2018 to July 2023, a total of 9 patients with giant cell tumor of the distal femur were treated with 3D-printed modular supporting prosthesis to reconstruct lacunar bone defects in the Department of Orthopedics, West China Hospital, Sichuan University. There were 4 males and 5 females, aged 30.8±6.1 years (range, 24-44 years), 5 cases on the left side, 4 cases on the right side, 2 cases of Campanacci grade I, 7 cases of Campanacci grade II. The anteroposterior and lateral X-ray films and T-SMART tomosynthesis imaging of the knee joint were taken to observe the bone graft healing and osseointegration after operation. Musculoskeletal Tumor Society (MSTS)-93 was used to evaluate knee function, and visual analogue scale (VAS) was used to evaluate knee pain.Results:All patients were successfully operated and followed up for an average of 30.8±7.5 months (range, 18-42 months). The operation time was 124.2±23.6 min, and the intraoperative blood loss was 105.6±17.4 ml. All autografts showed bony union at the graft-host junction, and the healing time was 3.3±0.4 months (range, 3.0-4.0 months). At 6 months after surgery, T-SMART tomosynthesis imaging showed that the gap between the prosthesis-bone interface was less than 1 mm in all patients. At the last follow-up, the thickness of residual subchondral bone was 5.7±1.3 mm, which was greater than that before operation 2.2±0.8 mm, and the difference was statistically significant ( t=10.823, P<0.001). At the last follow-up, the score of MSTS-93 was 26.7±2.4, which was higher than that before operation 18.8±3.7, and the difference was statistically significant ( t=5.367, P<0.001). At the last follow-up, the range of motion of the knee joint was 122.8°±9.1°, which was higher than that before operation 108.3°±6.1°, and the difference was statistically significant ( t=3.970, P<0.001). All patients were able to walk normally, go up and down stairs and other daily activities, and 7 patients were able to complete squats. At the last follow-up, there was no local tumor recurrence, distant metastasis, death, joint infection, pain (VAS score was 0), delayed wound healing, joint degeneration, prosthesis loosening or articular surface collapse. Conclusion:Reconstruction of lacunar bone defect caused by giant cell tumor of distal femur with 3D-printed modular supporting prosthesis can effectively improve knee joint function and osseointegration, and the short-term clinical results are satisfactory.

Objective:To explore the early and mid-term efficacy of three-dimensional printed customized porous prosthesis with preserved articular in the reconstruction of ultra-long segmental bone defect around the metaphysis of peri-knee.Methods:A retrospective analysis was conducted on the data of 24 patients who underwent reconstruction of ultra-long segmental bone defect around the metaphysis of peri-knee using 3D-printed customized porous prostheses at West China Hospital of Sichuan University from June 2015 to June 2021. There were 14 female cases and 10 male cases, with an average age of 28.9±16.5 years (range, 12-61 years), 12 cases at the distal end of the femur and 12 cases at the proximal end of the tibia. Tumor types: 16 cases of osteosarcoma, 4 cases of Ewing's sarcoma, 2 cases of chondrosarcoma, and 2 case of parosteal osteosarcoma. All patients were classified as Enneking stage IIB. Record the oncology results of the patients, the length of tumor segment resection, and the remaining bone length at the distal femur or proximal tibia, as well as complications, systemic metastasis and imaging changes. The bone integration at the prosthesis-bone interface was evaluated by tomosynthesis-shimadzu metal artifact reduction technology (T-SMART). Limb function was evaluated using the Musculoskeletal Tumor Society (MSTS)-93 score and knee range of motion assessment.Results:All 24 patients successfully completed the surgery and were followed up, with an average follow-up time of 51.8±12.7 months (range, 32-99 months). The length of femoral osteotomy was 241.1±66.2 mm (range, 150.6-333.4 mm), and the length of tibial osteotomy was 198.6±35.6 mm (range, 156.6-287.6 mm). The remaining bone length at the epiphyseal end around the knee joint (from the knee joint plane to the osteotomy plane of the distal femur or proximal tibia) was 52.6±11.0 mm (range, 31.1-77.5 mm). At the last follow-up, 23 patients survived tumor-free, while one patient died due to lung metastasis 54 months after the operation. One patient had prosthesis fracture 75 months after the operation, two patients had aseptic loosening 6 and 8 months after the operation, and the T-SMART of the remaining 20 patients showed that the implanted prostheses all achieved good osseointegration. At the last follow-up, the range of motion of the knee joint was 126.2°±7.5° (range, 110.0°-140.0°), and the MSTS-93 score was 26.7±1.8 points (range, 23-30 points). Among them, the MSTS-93 score of the femoral prosthesis was 26.7±1.6 points (range, 24-29 points), and the MSTS-93 score of the tibial prosthesis was 26.9±1.9 points (range, 23-30 points). The average knee range of motion was 126.2°±7.5° (range, 110°-140°), and the MSTS-93 functional score was 26.7±1.8 points (range, 23-30 points) at the last follow-up. The femoral component had an average score of 26.7±1.6 points (range, 24-29 points), while the tibial component had an average score of 26.9±1.9 points (range, 23-30 points).Conclusion:The application three-dimensional printed customized porous prosthesis with preserved articular in the reconstruction of ultra-long segmental bone defect around the metaphysis of peri-knee can preserve the joint, restore limb function well, and have a low incidence of prosthesis complications, with good clinical efficacy in the early and middle stages.

OBJECTIVE: To evaluate the feasibility and short-term effectiveness of three-dimensional (3D)-printed customized porous acetabular components for reconstruction of extensive acetabular bone defects during primary total hip arthroplasty (THA). METHODS: The clinical data of 8 patients with extensive acetabular bone defects, who were treated with 3D-printed individualized porous acetabular components between July 2018 and January 2022, were retrospectively analyzed. The cohort comprised 4 males and 4 females with an average age of 48 years ranging from 34 to 56 years. Acetabular bone defects were classified as Paprosky type ⅢA in 3 cases and type ⅢB in 5 cases. The causes of acetabular destruction were hip tuberculosis (5 cases), pigmented villonodular synovitis (2 cases), and syphilitic arthritis (1 case). Visual analogue scale (VAS) score and Harris hip score (HHS) were used to evaluate the pain relief and hip function before and after operation. Reconstruction outcomes were further assessed by imaging results [X-ray film and Tomosynthesis Shimadzumetal artefact reduction technology (T-SMART)], and the mechanical properties were evaluated by finite element analysis. RESULTS: The operation time ranged from 174 to 195 minutes (mean, 187 minutes), and intraoperative blood loss ranged from 390 to 530 mL (mean, 465 mL). All 8 patients were follow-up 26-74 months (mean, 44 months). Among the 5 patients with tuberculosis, none experienced postoperative recurrence. At last follow-up, the VAS score was 0.3±0.5 and the HHS score was 87.9±3.7, both significantly improved compared to preoperative values ( t=25.170, P<0.001; t=-28.322, P<0.001). X-ray films at 2 years after operation demonstrated satisfactory matching between the 3D-printed customized acetabular component and the acetabulum. The postoperative center of rotation of the operated hip was shifted by (2.1±0.5) mm horizontally and (2.0±0.7) mm vertically relative to the contralateral side, with both offsets showing significant differences compared to preoperative values ( t=24.700, P<0.001; t=55.230, P<0.001). T-SMART imaging showed satisfactory osseointegration at the implant-host bone interface. No complications such as aseptic loosening or screw breakage was observed during follow-up. Finite element analysis showed that the acetabular component had good mechanical properties. CONCLUSION The application of 3D-printed individualized porous acetabular components in the reconstruction of extensive acetabular bone defects demonstrated precise anatomical reconstruction, stable mechanical support, and good functional performance in short-term follow-up, offering a potential alternative for acetabular defect reconstruction in primary THA.
Humans ; Middle Aged ; Male ; Female ; Printing, Three-Dimensional ; Arthroplasty, Replacement, Hip/instrumentation* ; Acetabulum/diagnostic imaging* ; Adult ; Follow-Up Studies ; Retrospective Studies ; Hip Prosthesis ; Prosthesis Design ; Porosity ; Treatment Outcome ; Plastic Surgery Procedures/methods*

The NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, a high-molecular-weight protein complex in the cytoplasm, is composed of three core components: the sensor protein NLRP3, the adaptor protein apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC) and the effector protein caspase-1. It plays a critical role in regulating host immune and inflammatory responses. Studies have shown that the NLRP3 inflammasome has increasingly become a focal point in tumor molecular biology field. A growing body of evidence indicates that the increased expression and activation of the NLRP3 inflammasome is closely associated with the pathogenesis of head and neck squamous cell carcinoma (HNSCC) and the tumor microenvironment (TME). It may promote tumor proliferation, invasion, migration, and other biological behaviors through various regulatory mechanisms while influencing tumor immune evasion and therapy resistance, which holds promise as a prognostic biomarker for patients. This review explores the current effect and mechanism of the NLRP3 inflammasome and its signaling pathways in head and neck cancer, providing insights into clinical targeted drug development and molecular immunotherapy.
Humans ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Inflammasomes/metabolism* ; Head and Neck Neoplasms/pathology* ; Squamous Cell Carcinoma of Head and Neck/metabolism* ; Tumor Microenvironment ; Signal Transduction ; Animals

Objective:This study investigated the expression of C-X-C motif chemokine receptor 3 (CXCR3) on CD45RO? T cells in the peripheral blood of patients with Alzheimer′s disease (AD) and its association with clinical features.Methods:A total of 41 AD patients and 30 age-and sex-matched healthy controls (HCs) were recruited from the Department of Neurology at the Medical Division of PLA General Hospital between September 2022 and March 2024. Flow cytometry was used to quantify CXCR3 expression on CD45RO? T cell subsets in peripheral blood. Dementia severity in AD patients was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Spearman correlation analysis examined the relationship between CD45RO?CXCR3? T cell levels and cognitive function in the AD group. Receiver operating characteristic (ROC) curve analysis determined the predictive utility of CD45RO?CXCR3? T cells for AD, quantified by the area under the curve (AUC).Results:Compared to healthy controls, AD patients exhibited significantly elevated levels of CD8?CD45RO?CXCR3? T cells [17.8% (7.2%, 40.3%) vs. 8.2% (5.1%, 12.3%), Z=-2.59, P<0.05]. However, no significant differences were observed for CD4?CD45RO?CXCR3? T cells, CD4?CD45RO?CXCR3? T cells, or CD8?CD45RO?CXCR3? T cells ( P>0.05). Spearman correlation analysis revealed a negative correlation between CD8?CD45RO?CXCR3? T cell levels and cognitive scores (MMSE: r=-0.72, P<0.05; MoCA: r=-0.70, P<0.05). ROC analysis demonstrated an AUC of 0.81 for CD8?CD45RO?CXCR3? T cells in predicting AD, with a sensitivity of 59.0% and specificity of 93.3%. Conclusions:CXCR3 expression is significantly upregulated on CD8?CD45RO? T cells in AD patients, and its levels correlate with cognitive impairment severity. These findings suggest that CD8?CD45RO?CXCR3? T cells may serve as a potential biomarker for AD diagnosis and progression monitoring.