In-Silico Analysis of Optimal Configurations for Rotational Bioinspired Bone Marrow Biopsy Needle Designs: An ANN Approach.

Abstract

Medical needle innovations have utilized rotating motion to enhance tissue-cutting capabilities, reducing cutting force and improving clinical outcomes. This study analyzes the effects of six essential factors on insertion and extraction forces during bone marrow biopsy (BMB) procedures. The study uses Taguchi's L32 orthogonal array and numerically simulates the BMB process using the Lagrangian surface-based method on a three-dimensional (3D) heterogeneous Finite Element (FE) model of the human iliac crest. The study evaluates cutting forces in needle insertion and extraction using uni-directional (360° rotation) and bidirectional (180° clock and anti-clock rotation) bioinspired BMB needles. This work aims to create an AI tool that assists researchers and clinicians in selecting the most suitable and safe design parameters for a bio-inspired barbed biopsy needle. An efficient Graphical User Interface (GUI) has been developed for easy use and seamless interaction with the AI tool. With a remarkable accuracy rate exceeding 98%, the tool's predictions hold significant value in facilitating the development of environmentally conscious biopsy needles. The tool demonstrates significantly higher efficiency compared to Abaqus, rendering it a valuable asset for researchers and clinicians engaged in bio-inspired biopsy needle development.