An investigation into the shape and insertion mechanism of a bio-inspired trephine needle for bone marrow biopsy

Abstract

Bone marrow biopsy (BMB) needles are commonly utilized for extracting tissue samples to identify lesions or abnormalities detected during medical examinations or radiological scans. During this technique, the inadequate support from the surrounding tissue results in tissue damage and displacement due to needle insertion forces. An additional challenge during the procedure is the needle deflection during insertion, leading to more pronounced tissue deformation. Tissue distortion and needle deflection frequently cause needle tip misalignment, reducing the intended targeting precision. There is a lack of studies addressing key aspects such as anxiety, pain, needle types, biopsy duration, needle deflection, recurrence rates, bone texture, tissue deformation, crack propagation, and more in the context of BMB. Drawing inspiration from the complex structures of the honeybee stinger and mosquito proboscis, our biomimetic design integrates peripheral barbs on the needle and vibration to improve tissue penetration and sample retrieval. To begin with, we conducted a prospective survey involving bone and bone marrow trephine biopsies obtained from Indian patients. The performance of the needle during BMB procedures has been assessed using the finite element method-based simulations, which analyzed factors such as insertion/extraction forces, needle deflection, tissue damage, and bone damage. The study has investigated the impact of unidirectional and bidirectional rotation on needle insertion/extraction into skin-bone tissue (iliac crest model). Through biomechanical modeling of the needle, our objective has been to optimize its design and comprehend the effects of various rotation modes and associated parameters on the efficiency and accuracy of needle insertion/extraction. Additionally, the thesis explored the application of unidirectional (360° rotation) and bidirectional (180° C.W. and C.C.W. rotation) rotation during needle insertion. Alongside the biomechanical analysis, an artificial neural network (ANN)-based AI tool has been developed to aid clinicians in selecting the optimal biopsy needle for BMB procedures. By incorporating insights from finite element simulations, the AI tool integrated the knowledge to offer recommendations based on criteria such as insertion/extraction forces, deflection, torque, and tissue damage. The primary objective of this tool is to assist clinicians in their decision making process, ultimately improving the overall success and safety of BMB procedures. The results derived from the FE simulations offer valuable insights into the performance of the bio-inspired BMB needle. This research contributes to optimizing the needle design for enhanced clinical outcomes by analyzing insertion/extraction forces, deflection characteristics, tissue damage, and bone damage. In addition, the AI tool developed in this thesis provides a novel approach to assist clinicians in choosing the most suitable needle for BMB procedures. In summary, this study synergistically integrates finite element simulations and AI-assisted decision-making tool to advance the field of bio-inspired bone marrow biopsy needles. The potential implications of these findings include more efficient and minimally invasive BMB procedures, leading to improved patient comfort and diagnostic accuracy.