Hugues Albini Lomami1, Camille Damour2, Giuseppe Rosi2, Anne-Sophie Poudrel2, Arnaud Dubory3, Charles-Henri Flouzat-Lachaniette3, Guillaume Haiat4. 1. CNRS, Laboratoire de Modélisation et de Simulation Multi-Echelle, UMR CNRS 8208, 61 Avenue du Général de Gaulle, Créteil 94010, France; INSERM U955, IMRB Université Paris-Est, 51 avenue du Maréchal de Lattre de Tassigny, 94000 Créteil, France. 2. CNRS, Laboratoire de Modélisation et de Simulation Multi-Echelle, UMR CNRS 8208, 61 Avenue du Général de Gaulle, Créteil 94010, France. 3. INSERM U955, IMRB Université Paris-Est, 51 avenue du Maréchal de Lattre de Tassigny, 94000 Créteil, France; Service de Chirurgie Orthopédique et Traumatologique, Hôpital Henri Mondor AP-HP, CHU Paris 12, Université Paris-Est, 51 avenue du Maréchal de Lattre de Tassigny, 94000 Créteil, France. 4. CNRS, Laboratoire de Modélisation et de Simulation Multi-Echelle, UMR CNRS 8208, 61 Avenue du Général de Gaulle, Créteil 94010, France. Electronic address: guillaume.haiat@univ-paris-est.fr.
Abstract
BACKGROUND: The success of cementless hip arthroplasty depends on the primary stability of the femoral stem. It remains difficult to assess the optimal number of impacts to guarantee the femoral stem stability while avoiding bone fracture. The aim of this study is to validate a method using a hammer instrumented with a force sensor to monitor the insertion of femoral stem in bovine femoral samples. METHODS: Different cementless femoral stem were impacted into five bovine femur samples, leading to 99 configurations. Three methods were used to quantify the insertion endpoint: the impact hammer, video motion tracking and the surgeon proprioception. For each configuration, the number of impacts performed by the surgeon until he felt a correct insertion was noted Nsurg. The insertion depth E was measured through video motion tracking, and the impact number Nvid corresponding to the end of the insertion was estimated. Two indicators, noted I and D, were determined from the analysis of the time variation of the force, and the impact number Nd corresponding to a threshold reached in D variation was estimated. FINDINGS: The pullout force of the femoral stem was significantly correlated with I (R2 = 0.81). The values of Nsurg, Nvid and Nd were similar for all configurations. INTERPRETATION: The results validate the use of the impact hammer to assess the primary stability of the femoral stem and the moment when the surgeon should stop the impaction procedure for an optimal insertion, which could lead to the development of a decision support system.
BACKGROUND: The success of cementless hip arthroplasty depends on the primary stability of the femoral stem. It remains difficult to assess the optimal number of impacts to guarantee the femoral stem stability while avoiding bone fracture. The aim of this study is to validate a method using a hammer instrumented with a force sensor to monitor the insertion of femoral stem in bovine femoral samples. METHODS: Different cementless femoral stem were impacted into five bovine femur samples, leading to 99 configurations. Three methods were used to quantify the insertion endpoint: the impact hammer, video motion tracking and the surgeon proprioception. For each configuration, the number of impacts performed by the surgeon until he felt a correct insertion was noted Nsurg. The insertion depth E was measured through video motion tracking, and the impact number Nvid corresponding to the end of the insertion was estimated. Two indicators, noted I and D, were determined from the analysis of the time variation of the force, and the impact number Nd corresponding to a threshold reached in D variation was estimated. FINDINGS: The pullout force of the femoral stem was significantly correlated with I (R2 = 0.81). The values of Nsurg, Nvid and Nd were similar for all configurations. INTERPRETATION: The results validate the use of the impact hammer to assess the primary stability of the femoral stem and the moment when the surgeon should stop the impaction procedure for an optimal insertion, which could lead to the development of a decision support system.
Authors: Steven Leuridan; Quentin Goossens; Leonard Cezar Pastrav; Michiel Mulier; Wim Desmet; Jos Vander Sloten; Kathleen Denis Journal: IEEE J Transl Eng Health Med Date: 2021-11-15 Impact factor: 3.316