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A novel palpation-based method for tumor nodule quantification in soft tissue-computational framework and

Javier Palacio-Torralba1, Robert L Reuben1, Yuhang Chen2

  • 1Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, UK.

Medical & Biological Engineering & Computing
|April 13, 2020
PubMed
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This study introduces a computational method to identify and quantify cancerous nodules in soft tissue using instrumented palpation. The framework accurately estimates tumor size and depth without prior knowledge, aiding cancer diagnosis.

Area of Science:

  • Biomedical Engineering
  • Computational Modeling
  • Medical Diagnostics

Background:

  • Mechanical property variations in soft tissue are established cancer markers.
  • Quantifying tumor load using mechanical responses during palpation remains challenging.
  • Existing methods often require a priori knowledge of tumor geometry, size, and depth.

Purpose of the Study:

  • To propose a computational framework for identifying and quantifying cancerous nodules in soft tissue.
  • To enable tumor characterization without prior information on geometry, size, or depth.
  • To advance instrumented palpation techniques for clinical cancer diagnosis.

Main Methods:

  • Utilized instrumented palpation on prostate tissue (as an exemplar) at various indentation depths.
Keywords:
Prostate cancerQuantitative diagnosisTissue mechanicsTumor detection

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  • Developed a computational framework comparing force feedback profiles with in silico models.
  • Validated the methodology using computational models and tissue-mimicking gelatin phantoms.

    • Main Results:

    • Successfully estimated the size and depth of cancerous nodules with good accuracy.
    • Demonstrated the framework's capability to quantify tumors without a priori geometric information.
    • Validated computational models and phantom experiments showed reliable performance.

    Conclusions:

    • The proposed computational framework offers a promising approach for quantifying soft tissue tumors.
    • This method enhances clinical palpation diagnosis for various solid tumors, including breast and prostate cancer.
    • The ability to quantify tumors without prior geometric knowledge represents a significant advancement.