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Predicting patient exposure to nickel released from cardiovascular devices using multi-scale modeling
Acta Biomaterialia ( IF 9.7 ) Pub Date : 2018-02-13 , DOI: 10.1016/j.actbio.2018.01.024
David M. Saylor , Brent A. Craven , Vaishnavi Chandrasekar , David D. Simon , Ronald P. Brown , Eric M. Sussman

Many cardiovascular device alloys contain nickel, which if released in sufficient quantities, can lead to adverse health effects. However, in-vivo nickel release from implanted devices and subsequent biodistribution of nickel ions to local tissues and systemic circulation are not well understood. To address this uncertainty, we have developed a multi-scale (material, tissue, and system) biokinetic model. The model links nickel release from an implanted cardiovascular device to concentrations in peri-implant tissue, as well as in serum and urine, which can be readily monitored. The model was parameterized for a specific cardiovascular implant, nitinol septal occluders, using in-vitro nickel release test results, studies of ex-vivo uptake into heart tissue, and in-vivo and clinical measurements from the literature. Our results show that the model accurately predicts nickel concentrations in peri-implant tissue in an animal model and in serum and urine of septal occluder patients. The congruity of the model with these data suggests it may provide useful insight to establish nickel exposure limits and interpret biomonitoring data. Finally, we use the model to predict local and systemic nickel exposure due to passive release from nitinol devices produced using a wide range of manufacturing processes, as well as general relationships between release rate and exposure. These relationships suggest that peri-implant tissue and serum levels of nickel will remain below 5 μg/g and 10 μg/l, respectively, in patients who have received implanted nitinol cardiovascular devices provided the rate of nickel release per device surface area does not exceed 0.074 μg/(cm2 d) and is less than 32 μg/d in total.

Statement of significance

The uncertainty in whether in-vitro tests used to evaluate metal ion release from medical products are representative of clinical environments is one of the largest roadblocks to establishing the associated patient risk. We have developed and validated a multi-scale biokinetic model linking nickel release from cardiovascular devices in-vivo to both peri-implant and systemic levels. By providing clinically relevant exposure estimates, the model vastly improves the evaluation of risk posed to patients by the nickel contained within these devices. Our model is the first to address the potential for local and systemic metal ion exposure due to a medical device and can serve as a basis for future efforts aimed at other metal ions and biomedical products.



中文翻译:

使用多尺度模型预测患者暴露于心血管设备释放的镍的暴露量

许多心血管器械合金均含有镍,如果镍释放量过多,可能会对健康造成不利影响。然而,从植入装置中体内释放镍以及随后镍离子向局部组织和全身循环的生物分布尚不十分清楚。为了解决这种不确定性,我们开发了一个多尺度(材料,组织和系统)生物动力学模型。该模型将镍从植入的心血管设备中释放出来与植入物周围组织以及血清和尿液中的浓度联系起来,可以很容易地对其进行监测。使用体外镍释放测试结果,研究离体对心脏组织的体内摄取以及文献中的体内和临床测量,对特定的心血管植入物,镍钛合金中隔隔块进行参数化。我们的结果表明,该模型可以准确预测动物模型中的种植体周围组织以及隔室封堵器患者的血清和尿液中的镍浓度。该模型与这些数据的一致性表明,它可以为建立镍暴露极限和解释生物监测数据提供有用的见识。最后,我们使用该模型来预测由于使用各种制造工艺生产的镍钛合金器件的被动释放而导致的局部和全身性镍暴露,以及释放速率与暴露之间的一般关系。这些关系表明,在已植入镍钛诺心血管装置的患者中,假体周围组织和血清镍水平将分别保持在5μg/ g和10μg/ l以下,前提是每个器械表面积的镍释放速率不超过0.074微克/(厘米 该模型与这些数据的一致性表明,它可以为建立镍暴露极限和解释生物监测数据提供有用的见识。最后,我们使用该模型来预测由于使用各种制造工艺生产的镍钛合金器件的被动释放而导致的局部和全身性镍暴露,以及释放速率与暴露之间的一般关系。这些关系表明,在已植入镍钛诺心血管装置的患者中,假体周围组织和血清镍水平将分别保持在5μg/ g和10μg/ l以下,前提是每个器械表面积的镍释放速率不超过0.074微克/(厘米 该模型与这些数据的一致性表明,它可以为建立镍暴露极限和解释生物监测数据提供有用的见识。最后,我们使用该模型来预测由于使用各种制造工艺生产的镍钛合金器件的被动释放而导致的局部和全身性镍暴露,以及释放速率与暴露之间的一般关系。这些关系表明,在已植入镍钛诺心血管装置的患者中,假体周围组织和血清镍水平将分别保持在5μg/ g和10μg/ l以下,前提是每个器械表面积的镍释放速率不超过0.074微克/(厘米 我们使用该模型来预测由于使用广泛的制造工艺生产的镍钛合金器件的被动释放而导致的局部和全身性镍暴露,以及释放速率与暴露之间的一般关系。这些关系表明,在已植入镍钛诺心血管装置的患者中,假体周围组织和血清镍水平将分别保持在5μg/ g和10μg/ l以下,前提是每个器械表面积的镍释放速率不超过0.074微克/(厘米 我们使用该模型来预测由于使用广泛的制造工艺生产的镍钛合金器件的被动释放而导致的局部和全身性镍暴露,以及释放速率与暴露之间的一般关系。这些关系表明,在已植入镍钛诺心血管装置的患者中,假体周围组织和血清镍水平将分别保持在5μg/ g和10μg/ l以下,前提是每个器械表面积的镍释放速率不超过0.074微克/(厘米2  d)且总量小于32μg/ d。

重要声明

用于评估医疗产品中金属离子释放的体外测试是否可以代表临床环境的不确定性是确定相关患者风险的最大障碍之一。我们已经开发并验证了一种多尺度的生物动力学模型,该模型将镍从心血管装置体内释放到植入物周围和全身的水平联系在一起。通过提供临床相关的暴露估计,该模型极大地改善了这些设备中所含镍对患者构成的风险的评估。我们的模型是第一个解决由于医疗设备引起的局部和全身性金属离子暴露的可能性的模型,并且可以作为针对其他金属离子和生物医学产品的未来努力的基础。

更新日期:2018-02-14
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