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King's College London

Tissue Diagnosis Probe Based on Stiffness Measurement Using Vision and Force Sensing Modalities

Abstract

dc:description.abstract

This thesis presents the creation of a novel tissue diagnosis probe based on the measurement of stiffness and force during mechanical tool-tissue interactions. The probe using force and vision sensing modalities was created to be used for tissue diagnosis in medical applications, especially for robot-assisted minimallyinvasive surgery (MIS) to provide the necessary sensing modalities to allow for haptic feedback. By employing the developed prototypes, estimations of the mechanical properties of ex-vivo human prostate tissues were conducted using the finite element analysis (FEA) method and the Newton-Raphson algorithm.A clinical study of prostate tumour identification has been carried out on ex-vivo prostate samples and a study onrobotic palpation using a second prototype developed as part of this projectand comparing it to manual palpation was conducted. With the aim of measuring the indentation depth and the corresponding tissue reaction force simultaneously to obtain stiffness information,aprototype of a stiffness probe was constructedconsisting of a commercial digitalcamera and a force sensor. The effectiveness and sensitivityof the designedprobe was validatedthrough experiments on silicone phantomsand animal organs.Theresults showed that the probe could perform stiffness measurementsand localize tissue abnormalitieswhen indenting or sliding over the target surfaces. In order to investigate the mechanical properties of ex-vivo human prostate using the developed probe, a portable sliding indenter robot integrating the probe and the Phantom Omni device was created. Based on force-displacement measurements of the probe-soft tissue interaction, inversefinite element analysis (FEA)andthegeneralised Newton-Raphson algorithm were used to estimateunknown parameters including the shear modulus ofthe ex-vivo human prostate.<br/>The prostate was modelled as a nonlinear hyperelastic material (utilizing Arruda-Boyce model) inthe finite element modelling software package, ABAQUS 6.8-1. The results indicated that the proposed model can estimate the mechanical properties ofthe ex-vivo human prostate effectively. With the aim of identifying the stiffness of normal and cancerous prostate tissue, the prostates of 26 male patients were examinedusing the developed sliding indenter robot. Threedimensional (3D) stiffness maps of ex-vivo human prostate were created.The stiffness maps were correlatedwith other clinical examinations including Magnetic Resonance Imaging (MRI), Digital Rectal Examination (DRE), histology and Ultrosound-guided biopsy. The proposedprobe proved to be a promising platform to distinguish between cancerous and healthy tissue in prostate andto discriminate pathological tissue variations.In addition, the results provided quantitative information for the diagnosis and localization of prostate cancer. To ensure the proposed probe is suitable for MIS applications, a furtherprototype of the stiffness probebased on optic-fibreforce sensing replacing the commercial available force sensor was created.A studyon robotic palpation using the developed probe and comparing it tomanual palpation was conducted. The results indicated that robotic palpation was more effective than manual palpation conducted by experienced surgeons.

Degree

thesis:*
Name dc:type.qualificationname
Doctor of Philosophy
Level dc:type.qualificationlevel
Doctoral Thesis
Grantor dc:publisher.institution
King's College London
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Li, Jichun
Advisors dc:contributor.advisor
  • Seneviratne, Lakmal Dasarath
  • Althoefer, Kaspar Alexander

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
oai:kclpure.kcl.ac.uk:studenttheses/2157fcfd-4155-43c8-ab70-2d8fad7ee622
OAI identifier oai:identifier
oai:kclpure.kcl.ac.uk:studenttheses/2157fcfd-4155-43c8-ab70-2d8fad7ee622

Chain of custody

source
Harvested from
King's College London
Base URL
kclpure.kcl.ac.uk/ws/oai
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Li, Jichun. Tissue Diagnosis Probe Based on Stiffness Measurement Using Vision and Force Sensing Modalities. Doctoral Thesis thesis, King's College London, 2013. https://kclpure.kcl.ac.uk/portal/en/studentTheses/2157fcfd-4155-43c8-ab70-2d8fad7ee622