{"title":"模拟缺陷椎体骨折风险的计算评估:基线强度和肿瘤大小的作用","authors":"Mehran Fereydoonpour, Asghar Rezaei, Areonna Schreiber, Lichun Lu, Mariusz Ziejewski, Ghodrat Karami","doi":"10.1002/cnm.70081","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Accurately predicting vertebral fracture risk in metastatic spines remains a critical challenge in clinical practice. This study developed and validated a QCT-based finite element analysis (QCT/FEA) approach to investigate the combined effects of baseline bone strength and tumor size on vertebral structural integrity. Areal bone mineral density (aBMD) was also calculated from QCT data to evaluate the reduction in bone density with increasing defect size. Nine cadaveric vertebral bodies were analyzed under varying tumor sizes (0%, 20%, 35%, and 50%). The results demonstrated a strong correlation between experimentally measured and computationally predicted failure forces (<i>r</i> = 0.97, <i>p</i> < 0.001) and aBMD values (<i>r</i> = 0.96, <i>p</i> < 0.001). Vertebral strength decreased linearly with increasing tumor size. Importantly, the study revealed that baseline vertebral strength plays a crucial role in fracture risk assessment, often surpassing the impact of tumor size alone. Tumor size reduced vertebral strength at a rate 84% faster than bone density (<i>p</i> = 0.009), highlighting a greater impact of tumor defects on bone fracture force than on bone density. These findings suggest that relying solely on tumor size for fracture risk prediction may be insufficient. Incorporating baseline bone strength into predictive models significantly enhances accuracy and reliability, providing valuable insights for clinical decision-making and personalized treatment strategies. This study underscores the importance of advanced computational tools in improving vertebral fracture risk assessment in metastatic spine cases.</p>\n </div>","PeriodicalId":50349,"journal":{"name":"International Journal for Numerical Methods in Biomedical Engineering","volume":"41 8","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computational Assessment of Fracture Risk in Vertebral Bodies With Simulated Defects: The Role of Baseline Strength and Tumor Size\",\"authors\":\"Mehran Fereydoonpour, Asghar Rezaei, Areonna Schreiber, Lichun Lu, Mariusz Ziejewski, Ghodrat Karami\",\"doi\":\"10.1002/cnm.70081\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>Accurately predicting vertebral fracture risk in metastatic spines remains a critical challenge in clinical practice. This study developed and validated a QCT-based finite element analysis (QCT/FEA) approach to investigate the combined effects of baseline bone strength and tumor size on vertebral structural integrity. Areal bone mineral density (aBMD) was also calculated from QCT data to evaluate the reduction in bone density with increasing defect size. Nine cadaveric vertebral bodies were analyzed under varying tumor sizes (0%, 20%, 35%, and 50%). The results demonstrated a strong correlation between experimentally measured and computationally predicted failure forces (<i>r</i> = 0.97, <i>p</i> < 0.001) and aBMD values (<i>r</i> = 0.96, <i>p</i> < 0.001). Vertebral strength decreased linearly with increasing tumor size. Importantly, the study revealed that baseline vertebral strength plays a crucial role in fracture risk assessment, often surpassing the impact of tumor size alone. Tumor size reduced vertebral strength at a rate 84% faster than bone density (<i>p</i> = 0.009), highlighting a greater impact of tumor defects on bone fracture force than on bone density. These findings suggest that relying solely on tumor size for fracture risk prediction may be insufficient. Incorporating baseline bone strength into predictive models significantly enhances accuracy and reliability, providing valuable insights for clinical decision-making and personalized treatment strategies. This study underscores the importance of advanced computational tools in improving vertebral fracture risk assessment in metastatic spine cases.</p>\\n </div>\",\"PeriodicalId\":50349,\"journal\":{\"name\":\"International Journal for Numerical Methods in Biomedical Engineering\",\"volume\":\"41 8\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal for Numerical Methods in Biomedical Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cnm.70081\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal for Numerical Methods in Biomedical Engineering","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cnm.70081","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
摘要
在临床实践中,准确预测转移性脊柱骨折的风险仍然是一个关键的挑战。本研究开发并验证了基于QCT的有限元分析(QCT/FEA)方法,以研究基线骨强度和肿瘤大小对椎体结构完整性的综合影响。根据QCT数据计算面骨矿物质密度(aBMD),以评估骨密度随缺损尺寸增加而减少的情况。我们分析了9个不同肿瘤大小(0%、20%、35%和50%)的尸体椎体。结果表明,实验测量和计算预测的破坏力(r = 0.97, p < 0.001)与aBMD值(r = 0.96, p < 0.001)之间存在很强的相关性。椎体强度随肿瘤大小的增加呈线性下降。重要的是,该研究表明,基线椎体强度在骨折风险评估中起着至关重要的作用,通常超过肿瘤大小的单独影响。肿瘤大小降低椎体强度的速度比骨密度快84% (p = 0.009),突出表明肿瘤缺陷对骨折力的影响大于对骨密度的影响。这些发现表明,仅仅依靠肿瘤大小来预测骨折风险可能是不够的。将基线骨强度纳入预测模型可显著提高准确性和可靠性,为临床决策和个性化治疗策略提供有价值的见解。这项研究强调了先进的计算工具在改善转移性脊柱病例椎体骨折风险评估中的重要性。
Computational Assessment of Fracture Risk in Vertebral Bodies With Simulated Defects: The Role of Baseline Strength and Tumor Size
Accurately predicting vertebral fracture risk in metastatic spines remains a critical challenge in clinical practice. This study developed and validated a QCT-based finite element analysis (QCT/FEA) approach to investigate the combined effects of baseline bone strength and tumor size on vertebral structural integrity. Areal bone mineral density (aBMD) was also calculated from QCT data to evaluate the reduction in bone density with increasing defect size. Nine cadaveric vertebral bodies were analyzed under varying tumor sizes (0%, 20%, 35%, and 50%). The results demonstrated a strong correlation between experimentally measured and computationally predicted failure forces (r = 0.97, p < 0.001) and aBMD values (r = 0.96, p < 0.001). Vertebral strength decreased linearly with increasing tumor size. Importantly, the study revealed that baseline vertebral strength plays a crucial role in fracture risk assessment, often surpassing the impact of tumor size alone. Tumor size reduced vertebral strength at a rate 84% faster than bone density (p = 0.009), highlighting a greater impact of tumor defects on bone fracture force than on bone density. These findings suggest that relying solely on tumor size for fracture risk prediction may be insufficient. Incorporating baseline bone strength into predictive models significantly enhances accuracy and reliability, providing valuable insights for clinical decision-making and personalized treatment strategies. This study underscores the importance of advanced computational tools in improving vertebral fracture risk assessment in metastatic spine cases.
期刊介绍:
All differential equation based models for biomedical applications and their novel solutions (using either established numerical methods such as finite difference, finite element and finite volume methods or new numerical methods) are within the scope of this journal. Manuscripts with experimental and analytical themes are also welcome if a component of the paper deals with numerical methods. Special cases that may not involve differential equations such as image processing, meshing and artificial intelligence are within the scope. Any research that is broadly linked to the wellbeing of the human body, either directly or indirectly, is also within the scope of this journal.