BackgroundSoft tissue sarcomas (STS) exhibit significant heterogeneity and are classified as rare tumors with a high risk of metastasis. The neutrophil-to-lymphocyte ratio (NLR), a hematological marker indicative of systemic inflammation, has gained broad recognition for its prognostic utility in oncology. This ratio can be used to evaluate the dynamic changes in inflammatory markers during the diagnosis and treatment of tumors. The value of NLR fluctuations in STS has yet to be fully investigated.MethodsThis investigation involved a retrospective cohort of 231 patients with STS, all definitively diagnosed and managed at the Musculoskeletal Tumor Center of The First Affiliated Hospital of Zhengzhou University, aiming to evaluate their clinical profiles. The research focused on analyzing the impact of both baseline NLR and its dynamic changes throughout therapy on the prognostic outcomes in STS, with the aim of constructing a nomogram based on delta-NLR.ResultsThe study cohort comprised 231 individuals diagnosed with STS. Based on delta-NLR trends, participants were categorized into two cohorts: an NLR increase group (n=94) and an NLR decrease group (n=137). Analysis using time-dependent receiver operating characteristic (ROC) curves revealed that delta-NLR possessed greater predictive accuracy for prognosis relative to other hematologic parameters and clinical characteristics. Both univariate and multivariate analyses determined that Fédération Nationale des Centres de Lutte Contre le Cancer (FNCLCC) grade, patient age, and delta-NLR served as independent predictors of prognosis. A prognostic nomogram was subsequently constructed integrating these significant factors. The nomogram achieved a C-index of 0.702, and calibration curves verified its accuracy in predicting three- and five-year overall survival (OS) for STS patients. Results from decision curve analysis (DCA) and clinical impact curve assessment additionally validated that utilizing this delta-NLR-based nomogram may offer substantial clinical utility in the management of STS.ConclusionNLR is valuable for continuous monitoring, and ongoing assessment of NLR provides better survival predictions for patients with STS than using baseline NLR alone.

BackgroundThe prognosis of osteosarcoma (OS) remains heterogeneous, and the prognostic value of peripheral blood lymphocyte subsets, analyzed through machine learning (ML), is not fully explored. This study aimed to develop an ML-based prognostic model using lymphocyte subset data to improve risk stratification for OS patients.MethodsWe retrospectively analyzed data from 65 high-grade OS patients. Peripheral blood lymphocyte subsets were quantified by flow cytometry prior to treatment. Seven algorithms, including stepwise Cox, LASSO, and five ML models (RSF, GBM, XGBoost, SVM, KNN), were employed to construct prognostic models. Model performance was evaluated using the C-index, AUC, and validated via bootstrap and cross-validation.ResultsThe Gradient Boosting Machine (GBM) algorithm yielded the optimal two-variable model, incorporating CD3-CD56+ NK cells and CD8+HLA-DR+ activated cytotoxic T cells (AUC = 0.959). The resulting gbm_risk_score was an independent prognostic factor (HR = 14.516, P = 0.012) and effectively stratified patients into significantly divergent survival groups (P<0.001). Importantly, the gbm_risk_score demonstrated superior predictive performance for 3-year OS compared to traditional inflammatory indices, neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). A nomogram integrating the GBM risk group and primary metastasis status demonstrated excellent predictive accuracy (C-index: 0.883) and clinical utility, successfully identifying a high-risk subgroup among initially non-metastatic patients.ConclusionWe developed and validated a robust ML-driven prognostic model based on peripheral blood lymphocyte subsets. This model, demonstrating superior prognostic value over conventional inflammatory markers, provides a novel and practical tool for personalized risk assessment in OS, potentially guiding more tailored treatment strategies.

BackgroundOsteosarcoma (OSA) remains the most common primary malignant bone tumor in children and adolescents, with a poor prognosis for metastatic disease. While immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, their efficacy in metastatic OSA is limited and highly variable, lacking clear predictive biomarkers. Peripheral blood lymphocyte subsets, reflecting systemic immune status, show promise as non-invasive predictors of ICIs efficacy and patient prognosis, yet their dynamic changes and predictive value in metastatic OSA are largely unexplored.MethodsThis single-center, retrospective study included 14 metastatic OSA patients receiving ICIs. Peripheral blood lymphocyte subsets (CD3+, CD4+, CD8+ T cells, NK cells, and activated T cells like CD4+HLA-DR+, CD8+HLA-DR+) were quantified by flow cytometry at diagnosis, pre-ICIs, and post-ICIs. Overall survival (OS) and treatment response (RECIST 1.1) were evaluated. Statistical analyses, including univariate Cox regression, group comparisons, and Linear Mixed Models (LMM), assessed the relationship between lymphocyte subsets, their dynamic changes, and clinical outcomes.ResultsUnivariate Cox regression identified pre-ICIs CD8+HLA-DR+ cells, and post-ICIs CD3−CD56+, CD3+CD4+, and CD8+HLA-DR+ cells as protective factors for OS. At diagnosis, CD45+, CD3−CD56+, CD4+HLA-DR+, CD3+CD8+, and CD8+HLA-DR+ cells were significantly higher in patients achieving disease control rate (DCR) versus progressive disease (PD). Post-ICIs, CD3−CD56+, CD3+CD4+, and CD8+HLA-DR+ cells were significantly elevated in the DCR group. LMM revealed dynamic increases in post-ICIs CD3−CD56+ and CD8+HLA-DR+ cells were significantly associated with better treatment response (Time Point × Response P < 0.001 and P = 0.003). Relative increases in post-ICIs CD3−CD56+, CD3+CD4+, and CD8+HLA-DR+ cells were protective for OS. Extrapulmonary metastasis was a significant risk factor for poor OS (HR: 6.75, P = 0.040).ConclusionThis study provides the first systematic analysis of dynamic changes in peripheral blood lymphocyte subsets in metastatic OSA patients undergoing ICIs. Our findings suggest that elevated proportions and dynamic increases of peripheral blood CD3−CD56+ (NK cells) and CD8+HLA-DR+ (activated cytotoxic T cells) after ICIs are consistently associated with improved OS and better treatment response. These accessible biomarkers hold potential for predicting ICIs efficacy and guiding individualized treatment strategies in metastatic OSA, warranting further validation in larger, prospective cohorts.

Osteosarcoma (OS) is an aggressive bone tumor with poor prognosis, particularly in metastatic cases. Here, we identify spondin 2 (SPON2) as a key driver of OS progression. SPON2 is significantly upregulated in OS tissues and cell lines and correlates with shorter patient survival. Functional assays show that SPON2 promotes OS cell proliferation, migration, invasion, and angiogenesis by enhancing the secretion of IL10, CCL2, and CSF1, which leads to M2 macrophage polarization and an immunosuppressive tumor microenvironment. In vitro, SPON2 knockdown reduces M2 macrophage markers and attenuates EMT phenotypes, as evidenced by decreased mesenchymal markers and preserved epithelial characteristics. Mechanistically, SPON2 activates the NF-κB/VEGF signaling axis to drive both macrophage polarization and EMT, thereby promoting tumor progression. In vivo, SPON2 knockdown in OS xenografts suppresses tumor growth, lung metastasis, and M2 polarization, while increasing M1-associated markers. Lipopolysaccharide (LPS) stimulation restores cytokine secretion and EMT marker expression in SPON2-knockdown models, suggesting that SPON2 acts through inflammation-responsive pathways. Together, these findings establish SPON2 as a key regulator of both immune modulation and metastatic behavior in OS, and highlight its potential as a therapeutic target.

PurposeTo construct and validate nomograms for predicting lung metastasis probability in patients with malignant primary osseous spinal neoplasms (MPOSN) at initial diagnosis and predicting cancer-specific survival (CSS) in the lung metastasis subgroup.MethodsA total of 1,298 patients with spinal primary osteosarcoma, chondrosarcoma, Ewing sarcoma, and chordoma were retrospectively collected. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic analysis were used to identify the predictors for lung metastasis. LASSO and multivariate Cox analysis were used to identify the prognostic factors for 3- and 5-year CSS in the lung metastasis subgroup. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA) were used to estimate the accuracy and net benefits of nomograms.ResultsHistologic type, grade, lymph node involvement, tumor size, tumor extension, and other site metastasis were identified as predictors for lung metastasis. The area under the curve (AUC) for the training and validating cohorts were 0.825 and 0.827, respectively. Age, histologic type, surgery at primary site, and grade were identified as the prognostic factors for the CSS. The AUC for the 3- and 5-year CSS were 0.790 and 0.740, respectively. Calibration curves revealed good agreements, and the Hosmer and Lemeshow test identified the models to be well fitted. DCA curves demonstrated that nomograms were clinically useful.ConclusionThe nomograms constructed and validated by us could provide clinicians with a rapid and user-friendly tool to predict lung metastasis probability in patients with MPOSN at initial diagnosis and make a personalized CSS evaluation for the lung metastasis subgroup.

Objective:To explore the expression level of kinesin family member 23 (KIF23) in osteosarcoma tissue and its regulatory mode in osteosarcoma (OS).Methods:The tumor and adjacent tissue samples were collected from 30 patients with osteosarcoma who underwent surgical resection at the First Affiliated Hospital of Zhengzhou University from March 2015 to March 2023. All cases were confirmed by pathology, including 18 male patients and 12 female patients, with an average age of (14.0±1.9) years. KIF23 specific antibody was used to detect the expression of KIF23 in human OS tissues, and KIF23 short hairpin RNA (shRNA) plasmids were transfected into (U2-OS) osteosarcoma cells and human umbilical vein endothelial cells (HUVECs), respectively, to deplete the expression of KIF23. Methyl thiazolyl tetrazolium (MTT), cell counting kit-8 (CCK-8) and wound closure assays were performed to detect the effects of KIF23 on OS and endothelial cell proliferation and migration. The effects of KIF23 on HUVEC in vitro angiogenesis were further detected by the tube formation assays. Western blotting and quantitative polymerase chain reaction (qPCR) were used to detect the expression of cell proliferation and migration markers. Tumor formation in nude mice was detected after down-regulation of KIF23. Results:The mRNA level of KIF23 in OS tissue showed a statistically significant difference compared to the control group ( P<0.01). In OS cells, cell proliferation and cell migration in the transfection group were significantly different from those in the control group ( P<0.01). In HUVECs, there was a statistically significant difference in cell proliferation and migration between the transfected group and the control group ( P<0.01). There was statistically significant difference in tumor quality and volume between the KIF23 knockdown group and the control group ( P<0.01). Conclusion:KIF23 was highly expressed in OS tissues, promoted the proliferation and migration of OS and endothelial cells in vitro, and further regulated OS progression and angiogenesis.

Background:Targeting cancer stem cells (CSC) may represent a future therapeutic direction for osteosarcoma (OS), which mainly relies on the identification of CSC markers. This study aimed to classify OS based on messenger ribonucleic acid (mRNA) stemness indices (mRNAsi) and construct a mRNAsi-related risk model to predict the prognosis of OS.Methods:The one-class logistic regression (OCLR) algorithm was applied to the RNA- sequencing (seq) data of human embryonic stem cells (hESC) and induced pluripotent stem cell (iPSC) lines to calculate mRNAsi. Weighted gene co-expression network analysis (WGCNA) was performed on data obtained from the TARGET database to screen the mRNAsi-related genes. Univariate Cox regression analysis was implemented to screen mRNAsi-related genes with prognostic significance for consensus clustering of OS. The least absolute shrinkage and selection operator (LASSO) and COX regression analysis were conducted to construct a risk model based on mRNAsi-related genes.Results:Six gene modules were identified in the TARGET database. The yellow module showed the strongest negative correlation with mRNAsi and the strongest significant positive correlation with the immune score and stromal score. OS was divided into three molecular subtypes with significant survival differences based on 73 mRNAsi-related genes with prognostic value for OS. The survival rate was ranked as C3 < C1 < C2 from low to high. The levels of immune components in C2 was significantly higher than those in C1 and C3. HSD11B2, GBP1, RNF130, APBB1IP, and NPC2 in the yellow module were used as variables for building the mRNAsi-related risk model. The survival rate of the high-risk group (as defined by this model) was significantly higher than that of the low-risk group, and it had significant survival prediction ability in 28 types of cancer. In addition, the mRNAsi-related risk model was superior to the Tumor Immune Dysfunction and Exclusion (TIDE) model in predicting the prognosis and immunotherapy response in all three immunotherapy cohorts.Conclusions:This study classified OS and constructed a mRNAsi-related risk model based on mRNAsi-related genes, which provides a potential tool for more accurate risk stratification of OS and prediction of immunotherapy response.

BackgroundWe aimed to provide a new typing method for osteosarcoma (OS) based on single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the perspective of lipid metabolism and examine its potential mechanisms in the onset and progression of OS. MethodsScores for six lipid metabolic pathways were calculated by single-sample gene set enrichment analysis (ssGSEA) based on a scRNA-seq dataset and three microarray expression profiles. Subsequently, cluster typing was conducted using unsupervised consistency clustering. Furthermore, single-cell clustering and dimensionality-reduction analyses identified cell subtypes. Finally, an analysis of cellular receptors was performed using CellphoneDB to identify cellular communication. ResultsOS was classified into three subtypes based on lipid metabolic pathways. Among them, patients in clust3 showed poor prognoses, whereas those in clust1 and clust2 exhibited good prognoses. In addition, ssGSEA analysis showed that patients in clust3 had lower immune cell scores. Moreover, the Th17 cell differentiation pathway was significantly differentially enriched between clust2 and clust3, with lower enrichment scores for metabolic pathways in the former relative to clust1 and clust2. In total, 24 genes were upregulated between clust1 and clust2, whereas 20 were downregulated in clust3. These observations were validated by single-cell data analysis. Finally, through scRNA-seq data analysis, we identified nine ligand-receptor pairs particularly critical for communication between normal and malignant cells. ConclusionsThree clusters were identified and the single-cell analysis revealed that malignant cells dominated lipid metabolism patterns in tumors, thereby influencing the tumor microenvironment.

Context: Intervertebral disc degeneration (IDD) is the pathological basis of spinal degenerative diseases. Puerarin (PU) is an isoflavonoid with functions and medicinal properties. Objective: To explore the effect of PU on IDD and its potential mechanism of action. Materials and methods: Sprague-Dawley (SD) rats were divided into sham, IDD, low PU, and high PU groups. Rat nucleus pulposus cells (NPCs) were isolated and divided into control, IL-1 beta, 100 and 200 mu mol/mL PU, TAK-242 (TLR4 inhibitor), or 200 mu mol/mL PU + LPS (TLR4 activator) groups. The water content, inflammatory factors, proliferation activity, TLR4/NF-kappa B pathway activity, apoptosis rate, protein expression of apoptosis, and histology of the extracellular matrix (ECM) were analysed. Results: In vivo: Compared with the IDD group, disorganization of intervertebral disc tissue was significantly improved, water content (2.80 +/- 0.24 mg, 3.91 +/- 0.31 mg vs. 2.02 +/- 0.21 mg) and expression levels of collagen II and aggrecan were significantly increased, and the levels of inflammatory factors and the expression levels of TLR4, MyD88, and p-p65 were significantly decreased in IDD rats treated with PU. In vitro: Compared with the IL-1 beta group, the proliferation activity of IL-1 beta-treated NPCs and the expression of collagen II and aggrecan were significantly increased, while the apoptosis rate, levels of inflammatory factors, and the expression levels of TLR4, MyD88, and p-p65 were significantly decreased in IL-1 beta-treated NPCs treated with PU. LPS reversed the biological function changes of IL-1 beta-treated NPCs induced by PU. Conclusions: PU can delay the progression of IDD by inhibiting activation of the TLR4/NF-kappa B pathway.

Although the incidence of osteosarcoma (OS) is relatively low compared with other cancer types, the overall survival of metastatic OS was less than 30%. This study aimed to reveal the role of pyroptosis in osteosarcoma and develop a prognostic model related to pyroptosis. Weighted correlation network analysis (WGCNA) was applied to identify key gene modules related to pyroptosis. Univariate Cox regression analysis was used to screen prognostic genes related to pyroptosis. The least absolute shrinkage and selection operator (LASSO) and stepwise Akaike information criterion (stepAIC) were employed to optimize and construct a prognostic model. Five prognostic genes (COL13A1, TNFRSF1A, LILRA6, CTNNBIP1, and CD180) related to pyroptosis were identified. According to the 5-gene signature, OS samples were divided into high- and low-PPRS groups with differential prognosis. Immune-related pathways were more activated in the low-PPRS group. The 5-gene signature was effective and robust to predict OS prognosis. These five prognostic genes were involved in OS development and may serve as new targets for developing therapeutic drugs.

Background and objectives Chondrosarcoma is a destructive neoplasm of chondrocytes. Surgery is the principal procedure for this condition. The efficacy of traditional chemotherapy drugs is controversial. Niclosamide is an antihelminthic drug used to treat parasitic infections for nearly 50 years. However recent studies suggested that niclosamide might have the inhibitory effects of cancer. Methods We investigated the efficaciousness of niclosamide on a chondrosarcoma cell line SW1353.To determine the efficacy of niclosamide on chondrosarcoma, MTT, Flow cytometry, and DAPI assays were used to determine the effects of niclosamide. We determine the activity of niclosamide on the expression of the Raf/MEK/ERK pathway, and the phosphorylation of PDGFRβ and STAT3. Results Niclosamide dramatically inhibited cell growth and triggered apoptosis. And niclosamide down-regulated the expression of p- PDGFRβ and p-STAT3. Furthermore, niclosamide significantly reduced cyclin D1, Rb expressing, which were concurrent with the cell cycle block. We also found a decrease in p-MEK, p-ERK, Bcl-xl, and Bcl-2. Conclusion These results suggested that niclosamide effectively induced growth inhibition in vitro. And niclosamide could a new therapeutic method for chondrosarcoma.

目的 比较开放手术与CT引导下微创射频消融手术治疗骨样骨瘤的临床效果.方法 回顾性收集2017年6月至2020年2月在郑州大学第一附属医院治疗的55例骨样骨瘤患者临床资料,按手术方式将患者分为开放手术组(30例)和微创消融组(25例),开放手术组接受开放手术方式治疗,微创消融组接受CT引导下微创射频消融手术治疗.比较两组术后病理结果、手术时间、手术出血量、术后住院时间,比较治疗前和治疗后72 h、1周及1、6、12个月的视觉模拟量表(VAS)评分、并发症和复发情况.结果 两组术后活检成功率比较,差异有统计学意义(P<0.05);微创消融组手术时间、术后住院时间均短于开放手术组,手术出血量少于开放手术组(P<0.001);开放手术组有3例严重并发症(骨折)和3例复发,微创消融组无严重并发症及复发,微创消融组术后出现并发症或复发的概率低于开放手术组(P<0.05);术后72 h、1周及1、6个月,微创消融组术后VAS评分低于开放手术组(P<0.05).结论 CT引导下微创射频消融术治疗骨样骨瘤在手术时间、手术出血量、住院和康复时间、术后并发症或复发等方面较开放手术组有明显优势,可以优先考虑CT引导下微创射频消融术作为治疗骨样骨瘤的方法.

[目的]探讨影响Ⅰ级软骨肉瘤预后的因素.[方法]回顾分析2010年1月-2018年1月郑州大学第一附属医院收治的62例Ⅰ级软骨肉瘤患者的临床资料,采用Kaplan-Meier生存分析比较三类发病部位的两种手术方式对无复发生存率的影响,Cox回归分析影响生存的因素.[结果]随访时间24 ～ 96个月,平均(48.07±21.22)个月,3例患者复发后失访.随访过程中,5例患者出现远处转移,共2例患者死于肺转移,5年生存率96.77％.MSTS评分局部切除组为(28.27±0.65)分,广泛切除组为(25.68±1.45)分,两组间差异有统计学意义(P＜0.05).但是,术后5年无复发生存率,局部切除组为59.67％,广泛切除组为90.32％,差异有统计学意义(P＜0.05).患者是否复发的单因素分析表明,是否复发两组间在性别、年龄、部位、肿瘤直径、Enneking分期、位置分类方面的差异无统计学意义(P＞0.05),但复发组手术广泛切除的比率显著低于未复发组(P＜0.05).Ka-plan-Meier生存分析表明,广泛切除或局部切除对四肢肿瘤无复发生存率的影响差异无统计学意义(P＞0.05).但是,相较于局部切除,广泛切除在中轴组和胸壁组可以获得显著提升的无复发生存率(P＜0.05).Cox回归分析表明,手术方式(HR=9.495,95％CI:1.947～46.311,P＜0.05)是影响生存的独立预后因素.[结论]对四肢Ⅰ级软骨肉瘤,局部切除不增加复发风险且功能更佳.对胸壁、骨盆和脊柱Ⅰ级软骨肉瘤,应广泛切除以减少复发风险.

Osteosarcoma is a tumour of malignant origin in children and adolescents. Recent progression indicates that it is necessary to develop new therapies to improve the patient's prognosis rather than strengthen anti‐tumour chemotherapy. Researchers recently realised that cancer is a kind of disease with a metabolic disorder, and metabolic reprogramming is becoming a new cancer hallmark. Hence, our study's primary purpose is to explore the value of genes related to osteosarcoma metabolism.

We report a case of a farmer who presented with synovial osteochondromatosis of his right knee that mimicked a huge hardball. A synovial proliferative disease associated with metaplasia of cartilage resulting in sporadic multiple intra-articular and extra-articular loose bodies. Our focus is to report a rare case successfully operated which has an educational significance in clinical practice.

Background: Osteosarcoma is a malignant bone tumor common in children and adolescents. Metastatic status remains the most important guideline for classifying patients and making clinical decisions. Despite many efforts, newly diagnosed patients receive the same therapy that patients have received over the last 4 decades. With the development of high-throughput sequencing technology and the rise of immunotherapy, it is necessary to deeply explore the immune molecular mechanism of osteosarcoma. Methods: We obtained RNA-seq data and clinical information of osteosarcoma patients from TCGA database and TARGET database. With the help of co-expression analysis we identified immune-related lncRNA and then by means of univariate Cox regression analysis prognostic-related lncRNA was screened out. And also by using least absolute shrinkage and selection operator regression method a model based on immune-related lncRNA was constructed. The differences in overall survival, immune infiltration, immune checkpoint gene expression, and tumor microenvironmental immunity type between the two groups were evaluated. Results: We constructed a signature consisting of 13 lncRNA. Our results show that signatures can reliably predict the overall survival of patients with osteosarcoma and can bring net clinical benefits. Further more, the signatures can be used for further risk stratification of the metastasis patients. Patients in the low-risk group had higher immune cell infiltration and immune checkpoint gene expression. The results from gene set variation analysis show that patients in low-risk group are closely related to immune-related pathways when compared with patients in high-risk group. Finally, patients in the low-risk group are more likely to be classified as TMIT I and hence more likely to benefit from immunotherapy. Conclusion: Our signature may be a reliable marker for predicting the overall survival of patients with osteosarcoma. Keywords: Osteosarcoma, TCGA, LncRNA, Tumor immunology, Prognosis.

[目的]分析儿童及青少年骨巨细胞瘤的临床特点、影像学表现以及手术治疗效果.[方法]回顾性分析本院2011年2月-2018年10月收治的儿童及青少年骨巨细胞瘤患者31例;平均年龄(15.23±2.83)岁(7～18岁);骨骺未闭合13例(41.94％,13/31),已闭合18例(58.06％,18/31);根据骨骺闭合情况分别行刮除植骨术(骨骺未闭合),刮除骨水泥填充术(骨骺闭合)或假体置换(骨质破坏严重).[结果] 31例患者影像均表现为溶骨性骨质破坏;31例患者均顺利完成手术,其中29例获得随访,随访时间24～76个月,平均(34.22±3.67)个月;患者术后复发6例,复发率12.90％,MSTS 93系统评分肢体功能均为优良.[结论]儿童及青少年骨巨细胞瘤根据病变部位及与骨骺关系选择合适的手术方式预后良好.

Objective: The majority of giant cell tumors of bone (GCTB) occur in adult patients, especially between the ages of 20 and 40. This study aims to investigate the imaging features of GCTBs in pediatric patients and compare their characteristics with adult cases. Methods: Fifty-seven cases of patients aged 18 years old or younger were retrospectively analyzed, accounting for 12.8% of GCTBs in the First Affiliated Hospital of Zhengzhou University from 2001 to 2019. One hundred twenty-six adult patients (19 years of age and older) with GCTB occurring in long tubular bones were also included in this study. The following clinical information was identified from the medical records: age, sex, and followup data. Imaging features were reviewed by two musculoskeletal radiologists. Patient characteristics and imaging features between the two groups were compared. Results: A total of 57 patients (32 females, 25 males) were included in the study. The patients' ages ranged from 9 to 18 (median = 17 y). The majority of tumors occurred in tubular bones (n = 38, 66.7%) and the pelvis (n = 8, 14.0%). Imaging features were identified in GCTB cases occurring in the long tubular bones. Compared with adult GCTB patients, pediatric GCTB patients had a larger superior-inferior (SI) diameter (P = 0.005) and smaller left-to-right diameter/SI diameter ratio (P = 0.001). Epiphyseal involvement was relatively less common in pediatric patients with GCTBs than in adult patients (P = 0.009). The median age of patients without epiphyseal involvement was lower than the median age of patients with epiphyseal involvement (11 vs 17 y). Conclusion: GCTB in the pediatric age group is rare. This study has found that, in pediatric patients with GCTBs, the epiphysis is relatively less involved, and the tumor is more likely to grow longitudinally. These findings are helpful in the diagnosis of GCTBs in the pediatric population.