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<p>Bone healing is a complex process regulated by intricate biological and mechanical factors and spatially varied regions over time. This scoping review synthesizes current computational models that incorporate cytokines and growth factors, examining their role in bone healing. Through a systematic analysis of 71 studies, this review identifies and categorizes the modeling methodologies used, including mathematical, finite element, agent-based, mechanobiological, pharmacobiological, and hybrid approaches. The findings highlight the predominant use of mathematical models while noting a recent shift toward more sophisticated techniques like finite element and agent-based models. Key cytokines and growth factors, such as TGF-β, RANK-RANKL-OPG, and PTH, are repeatedly used, underscoring their essential roles in regulating cellular processes. This review also analyzes parameter selection and validation strategies, identifying gaps in current practices and emphasizing the need for high-quality experimental validation to improve model reliability. Some bibliometric analyses provide insights into citation networks and keyword co-occurrence, illustrating influential studies in the field and central themes. The findings offer a foundation for future research to enhance model accuracy, aiming toward more predictive and clinically relevant models accounting for biology and mechanics in bone healing.</p>

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Advances in computational modeling of cytokine and growth factor dynamics in bone healing: a scoping review

  • 期刊论文

  • 发表日期：

    2025年3月14日

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  • Ahmad Hedayatzadeh Razavi,
  • Nazanin Nafisi,
  • Maria Velasquez-Hammerle,
  • Mohammad Javad Shariyate,
  • Mohammad Khak,
  • Alireza Mirahmadi,
  • Megan McNichol,
  • Edward K. Rodrogiuez,
  • Ara Nazarian

摘要

Bone healing is a complex process regulated by intricate biological and mechanical factors and spatially varied regions over time. This scoping review synthesizes current computational models that incorporate cytokines and growth factors, examining their role in bone healing. Through a systematic analysis of 71 studies, this review identifies and categorizes the modeling methodologies used, including mathematical, finite element, agent-based, mechanobiological, pharmacobiological, and hybrid approaches. The findings highlight the predominant use of mathematical models while noting a recent shift toward more sophisticated techniques like finite element and agent-based models. Key cytokines and growth factors, such as TGF-β, RANK-RANKL-OPG, and PTH, are repeatedly used, underscoring their essential roles in regulating cellular processes. This review also analyzes parameter selection and validation strategies, identifying gaps in current practices and emphasizing the need for high-quality experimental validation to improve model reliability. Some bibliometric analyses provide insights into citation networks and keyword co-occurrence, illustrating influential studies in the field and central themes. The findings offer a foundation for future research to enhance model accuracy, aiming toward more predictive and clinically relevant models accounting for biology and mechanics in bone healing.