Feasibility study on a robot-assisted procedure for tumor localization using needle-rotation force signals

Xiaoyu Liu, Hongqiang Huo, Yuanjie Zhu, Lizhen Wang, Aoran Sun, Wei Yao, Yubo Fan

Research output: Contribution to journalArticle

Abstract

Accurate tumor localization is critical to early-stage cancer diagnosis and therapy. The recent force-guided technique allows to determine the depth of a suspicious tumor on the insertion path, while the spatial localization is still a great challenge. In this paper, a novel force-guided procedure was proposed to identify spatial tumor location using force signals during needle rotation. When there is a harder tumorous tissue around the needle rotation, an abnormal force signal will point to the location of the suspicious tissue. Finite element simulation and phantom experiment were conducted to test the feasibility of the procedure for the tumor localization. The simulation results showed that the harder tumorous tissue made a significant difference on the stress and deformation distributions for the surroundings, changing the needle-rotation force signals when the needle rotated towards the harder tissue. The experimental results indicated that the direction of the tumor location can be identified by the rotation-needle force signals. The intersection point of the two identified directions, derived from force signals of twice needle rotations, determined the tumor location ultimately. Also, parametric sensitivity tests were performed to examine the effective distance of the tumor location centre and the needle insertion point for the tumor localization. This procedure is expected to be used in robot-assisted system for cancer biopsy and brachytherapy.
LanguageEnglish
Pages231-237
Number of pages7
JournalBiomedical Signal Processing and Control
Volume46
Early online date10 Aug 2018
DOIs
Publication statusPublished - 25 Sep 2018

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Feasibility Studies
Needles
Tumors
Robots
Neoplasms
Tissue
Biopsy
Brachytherapy
Early Detection of Cancer

Keywords

  • tumor localization
  • force signals
  • robot assisted procedure
  • finite element simulation
  • phantom experiment

Cite this

Liu, Xiaoyu ; Huo, Hongqiang ; Zhu, Yuanjie ; Wang, Lizhen ; Sun, Aoran ; Yao, Wei ; Fan, Yubo. / Feasibility study on a robot-assisted procedure for tumor localization using needle-rotation force signals. In: Biomedical Signal Processing and Control. 2018 ; Vol. 46. pp. 231-237.
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abstract = "Accurate tumor localization is critical to early-stage cancer diagnosis and therapy. The recent force-guided technique allows to determine the depth of a suspicious tumor on the insertion path, while the spatial localization is still a great challenge. In this paper, a novel force-guided procedure was proposed to identify spatial tumor location using force signals during needle rotation. When there is a harder tumorous tissue around the needle rotation, an abnormal force signal will point to the location of the suspicious tissue. Finite element simulation and phantom experiment were conducted to test the feasibility of the procedure for the tumor localization. The simulation results showed that the harder tumorous tissue made a significant difference on the stress and deformation distributions for the surroundings, changing the needle-rotation force signals when the needle rotated towards the harder tissue. The experimental results indicated that the direction of the tumor location can be identified by the rotation-needle force signals. The intersection point of the two identified directions, derived from force signals of twice needle rotations, determined the tumor location ultimately. Also, parametric sensitivity tests were performed to examine the effective distance of the tumor location centre and the needle insertion point for the tumor localization. This procedure is expected to be used in robot-assisted system for cancer biopsy and brachytherapy.",
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Feasibility study on a robot-assisted procedure for tumor localization using needle-rotation force signals. / Liu, Xiaoyu; Huo, Hongqiang ; Zhu, Yuanjie ; Wang, Lizhen; Sun, Aoran; Yao, Wei; Fan, Yubo.

In: Biomedical Signal Processing and Control, Vol. 46, 25.09.2018, p. 231-237.

Research output: Contribution to journalArticle

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