A NON-INVASIVE METHOD TO RECONSTRUCT PATIENT-SPECIFIC HUMAN FEMUR WITH IN-SITU DRILLING TEMPERATURE DATA USING PROBABILITY DENSITY FUNCTION

Abstract

Drilling through bone is widely performed in orthopedic surgeries to fix the plate and implant using bone screws. Clinical observation revealed that the mechanical and thermal damages driven by the uncontrolled drilling operations loosen the implants soon after their fixations. During fracture treatment and reconstruction surgery, the quality of the hole generated is to be considered as an important metric, and therefore drill feed rate and spindle speed, apparent bone density, drill bit geometry, and skill of the surgeon are the parameters to influence the success of the bone drilling procedure. The generation of temperature due to the conversion of mechanical work around the osteotomy site leads to irreversible thermal damage to the bone tissue, when it exceeds 47∘C. So, a non-invasive method which can identify the probability to not get a thermal osteonecrosis at the chosen drill spot can help the surgeon to strongly fix the implant around the defect site. To make this happen, the in-situ bone temperatures measured in the earlier study when drilling with a 3.20[Formula: see text]mm diameter drill bit was used for the investigation. As a procedure, the test statistics and critical test statistics values were calculated, and found that the log normal and gamma density functions could best describe the bone drilling temperatures, when drilling in the radial and circumferential directions, respectively. Additionally, the CT data sets of the patient-specific femur were used to reconstruct the bone both with geometry and drilling temperature data. The Kolmogrov–Smirnov test performed to check the validity of the temperature distribution models showed a good agreement with the experimental results. The outcomes of the method can help the surgeon to choose a suitable location for the strongest fixation using CT data sets of the patient as the only input.