Optimizing Cutting Performance and Sampling Quality of a Coaxial Biopsy Needle with Novel Cutting Edge Geometry

  • 黃 郁銘

Student thesis: Doctoral Thesis

Abstract

Vacuum-assisted biopsy is a commonly used minimally invasive technique that uses rotational cutting as the main sampling method An accurate diagnosis of disease requires samples with good quality which is affected by the cutting force of the biopsy needle A low cutting force allows a needle to retrieve larger and non-crushed samples Studies have indicated that a needle with a convex-curved cutting edge is more suitable for rotational cutting than that with a concave-curved cutting edge However such a geometric design is not seen in the existing biopsy applications and is little investigated in the previous studies This paper proposed a novel needle design with double convex-curved cutting edges The aim is to optimize the design to extract large non-crushed samples with minimal cutting force The Taguchi method was used for the design of experiments with five factors The rotational needle insertion experiment and tissue sampling experiment were established for studying the effects of the factors on the cutting force and sampling quality respectively The correlation between the cutting force and the sampling quality was investigated The results showed that increasing K value or increasing rotation-translation ratio could significantly lower the cutting force A larger sample could be extracted at a high rotation-translation ratio or a high insertion speed but sample fragmentation could occur under high rotation speed To improve sampling quality and cutting force simultaneously the recommended strategy is to configure the cutting parameters with a higher K value a larger rotation-translation ratio and a smaller insertion speed For the cases tested in this study the optimal configuration of a needle would have a sharpened cutting edge with the K value at 0 2 rotation-translation ratio at 8 and insertion speed at 1 mm/s
Date of Award2020
Original languageEnglish
SupervisorChi-Lun Lin (Supervisor)

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