Needle-shaped ultrathin piezoelectric microsystem for guided tissue targeting via mechanical sensing

Xinge Yu, Heling Wang, Xin Ning, Rujie Sun, Hassan Albadawi, Marcela Salomao, Alvin C. Silva, Yang Yu, Limei Tian, Ahyeon Koh, Chan Mi Lee, Aditya Chempakasseril, Peilin Tian, Matt Pharr, Jianghong Yuan, Yonggang Huang*, Rahmi Oklu, John A. Rogers

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

119 Scopus citations

Abstract

Needles for percutaneous biopsies of tumour tissue can be guided by ultrasound or computed tomography. However, despite best imaging practices and operator experience, high rates of inadequate tissue sampling, especially for small lesions, are common. Here, we introduce a needle-shaped ultrathin piezoelectric microsystem that can be injected or mounted directly onto conventional biopsy needles and used to distinguish abnormal tissue during the capture of biopsy samples, through quantitative real-time measurements of variations in tissue modulus. Using well-characterized synthetic soft materials, explanted tissues and animal models, we establish experimentally and theoretically the fundamental operating principles of the microsystem, as well as key considerations in materials choices and device designs. Through systematic tests on human livers with cancerous lesions, we demonstrate that the piezoelectric microsystem provides quantitative agreement with magnetic resonance elastography, the clinical gold standard for the measurement of tissue modulus. The piezoelectric microsystem provides a foundation for the design of tools for the rapid, modulus-based characterization of tissues.

Original languageEnglish (US)
Pages (from-to)165-172
Number of pages8
JournalNature Biomedical Engineering
Volume2
Issue number3
DOIs
StatePublished - Mar 1 2018

Funding

This work was supported by the Center for Bio-Integrated Electronics. R.O. acknowledges National Institutes of Health grants R01HL137193, R01EB24403, R21EB021148 and R03CA172738, and Mayo Clinic. R.S. acknowledges support from the Engineering and Physical Sciences Research Council (grant number EP/ L016028/1) and China Scholarship Council. L.T. acknowledges support from a Beckman Institute postdoctoral fellowship at the University of Illinois Urbana-Champaign. Y.H. acknowledges support from the National Science Foundation (grant numbers 1400169, 1534120 and 1635443) and National Institutes of Health (grant number R01EB019337). The authors acknowledge N. Pallace (Media Support Services at Mayo Clinic) for expert photography during the experiments.

ASJC Scopus subject areas

  • Bioengineering
  • Biotechnology
  • Biomedical Engineering
  • Medicine (miscellaneous)
  • Computer Science Applications

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