In-silico patient-specific and patient-appropriate engineering method to judiciously select an ameliorative implant design in a single-patient using finite element-n-of-1 (fe-n-of-1) empirical test analysis to reconstruct mid-sagittal osteochondrotomy of the sternum following cardiac surgery

Abstract

Introduction: No two patients have similar normal anatomy and physiology because of genetics, physical development, and age that the same type of surgery and reconstruction implant will perform equally well. Such a notion demands the need for individualization of treatment and a method to select an ameliorative implant prospectively. One such empirically testing method is the finite element-n-of-1 (fe-n-of-1), where a treatment plan is executed specifically and systematically for a single patient as part of pre-operative planning. Objective: It is to evaluate and discuss the method of finite element analysis to carry out the fe-n-of-1 empirical test in a fact-driven manner connecting various scientific domains. It presents a preliminary protocol how to select an ameliorative implant to mitigate sternal instability due to suboptimal standard stainless-steel cerclage wiring to reconstruct the sternum following open-heart surgery.  Methodology: The instability following the reconstruction of the sternum is a mechanical problem therefore it is appropriate to apply harmless structural engineering methods to choose a suitable implant design to fix it. This exploratory descriptive research describes finite element n-of-1 empirical testing using in-silico engineering principles applied to patient-specific and patient-appropriate mechanical loading conditions. Conclusion: Single-patient fe-n-of-1 empirical testing is a benign engineering method based on finite element modeling and finite element analysis. It is a safe mathematical evaluation free from subjective bias to select in advance the most ameliorative implant design to opt out of the suboptimal stainless steel cerclage wire as ‘standard of care’ and improve patient-based outcome and surgeon satisfaction.