Real-Time Bioimpedance-Based Biopsy Needle Can Identify Tissue Type with High Spatial Accuracy

Sanna Halonen, Juho Kari, Petri Ahonen, Kai Kronström, Jari Hyttinen

Research output: Contribution to journalArticleScientificpeer-review


Histological analysis is meaningful in diagnosis only if the targeted tissue is obtained in the biopsy. Often, physicians have to take a tissue sample without accurate information about the location of the instrument tip. A novel biopsy needle with bioimpedance-based tissue identification has been developed to provide data for the automatic classification of the tissue type at the tip of the needle. The aim of this study was to examine the resolution of this identification method and to assess how tissue heterogeneities affect the measurement and tissue classification. Finite element method simulations of bioimpedance measurements were performed using a 3D model. In vivo data of a porcine model were gathered with a moving needle from fat, muscle, blood, liver, and spleen, and a tissue classifier was created and tested based on the gathered data. Simulations showed that very small targets were detectable, and targets of 2 × 2 × 2 mm3 and larger were correctly measurable. Based on the in vivo data, the performance of the tissue classifier was high. The total accuracy of classifying different tissues was approximately 94%. Our results indicate that local bioimpedance-based tissue classification is feasible in vivo, and thus the method provides high potential to improve clinical biopsy procedures.
Original languageEnglish
Pages (from-to)836–851
Number of pages15
JournalAnnals of Biomedical Engineering
Issue number3
Publication statusPublished - 5 Mar 2019
MoE publication typeA1 Journal article-refereed

Fingerprint Dive into the research topics of 'Real-Time Bioimpedance-Based Biopsy Needle Can Identify Tissue Type with High Spatial Accuracy'. Together they form a unique fingerprint.

Cite this