Accurate Needle Insertion and Tissue Sampling in Biopsy

Abstract

Needle biopsy is a minimally invasive clinical procedure to acquire tissue samples from various organs, such as lymph node, lung, breast and prostate, for pathological diagnosis of cancer. Accurate needle deployment and adequate tissue sampling in biopsy are crucial for accurate diagnosis and individualized treatment decisions. Advances in medical imaging can identify suspicious cancerous lesions as targeted sites for biopsy to improve the disease assessment. As the use of targeted biopsy expands, the sub-mm accuracy for needle deployment is clinically desired but technically challenging. During the biopsy procedure, the needle insertion force deforms and moves the soft tissue and the surrounding organ. Currently available biopsy needles often induce significant needle deflection. Such deflection causes variances in targeted and actual locations of the sampled tissue core, leading to lesion undersampling, false-negative and cancer misdiagnosis. Prior researches of needle insertion have identified the needle insertion motion and needle tip geometry as the main factors affecting needle deployment accuracy. Robotic needle steering has been developed for accurate needle guidance. However, there is not yet a needle biopsy technology that can be effectively adopted for clinical use. Furthermore, relationship between needle deployment accuracy and tissue sampling volume, two key factors affecting cancer diagnostic accuracy, remains unexplored.

This dissertation aims to establish the scientific and technological foundations for accurate needle insertion and tissue sampling in biopsy. First, the effect of needle insertion motion on the tissue deformation and organ displacement was studied. The mosquito-proboscis inspired (MPI) insertion was developed to reduce the local tissue deformation and global prostate displacement during needle insertion. Second, the effect of needle tip geometry on needle deflection and tissue sampling length was investigated to understand the needle-tissue interaction in biopsy. Third, the multi-bevel needle tip geometries were explored to identify the biopsy needle design criteria enabling low needle deflection and high tissue sampling. Last, a needle-tissue interaction modeling using the Lagrangian analysis coupled with smoothed particle Galerkin method (L-SPG) was formulated to study the needle deflection and tissue deformation during needle insertion.

The MPI needle insertion demonstrated the capability to reduce the local tissue deformation and global prostate displacement, by up to 38% and 48%, respectively, when compared to the traditional direct needle insertion. The tissue separation location at the needle tip was revealed to affect both needle deflection and tissue sampling length. By varying the tissue separation location and creating a multi-bevel needle tip geometry, the bending moments could be altered to reduce the needle deflection. However, the tissue separation location also affected the tissue contact inside the needle groove, potentially reducing the tissue sampling length. Two critical design criteria for biopsy needle were identified: 1) the tissue separation point below the needle groove face and 2) the multi-bevel needle tip geometry generating the upward forces while maintaining the low separation point. A multi-bevel needle achieving the above criteria demonstrated the reduced needle deflection (with up to 88% reduction in magnitude) and equivalent tissue sampling length when compared to current biopsy needle design. Finally, the L-SPG model was established to simultaneously model the needle deflection and tissue deformation during needle insertion. This L-SPG model achieved a reasonably good prediction on the correlation of the needle tip type vs. the resultant needle deflection and tissue sampling length, matching the trend observed in the experimental results.