GOAL: This research aims to validate a new biomarker of breast cancer by introducing electromechanical coupling factor of breast tissue samples as a possible additional indicator of breast cancer. Since collagen fibril exhibits a structural organization that gives rise to a piezoelectric effect, the difference in collagen density between normal and cancerous tissue can be captured by identifying the corresponding electromechanical coupling factor. METHODS: The design of a portable diagnostic tool and a microelectromechanical systems (MEMS)-based biochip, which is integrated with a piezoresistive sensing layer for measuring the reaction force as well as a microheater for temperature control, is introduced. To verify that electromechanical coupling factor can be used as a biomarker for breast cancer, the piezoelectric model for breast tissue is described with preliminary experimental results on five sets of normal and invasive ductal carcinoma (IDC) samples in the 25-45 temperature range. CONCLUSION: While the stiffness of breast tissues can be captured as a representative mechanical signature which allows one to discriminate among tissue types especially in the higher strain region, the electromechanical coupling factor shows more distinct differences between the normal and IDC groups over the entire strain region than the mechanical signature. From the two-sample -test, the electromechanical coupling factor under compression shows statistically significant differences ( 0.0039) between the two groups. SIGNIFICANCE: The increase in collagen density in breast tissue is an objective and reproducible characteristic of breast cancer. Although characterization of mechanical tissue property has been shown to be useful for differentiating cancerous tissue from normal tissue, using a single parameter may not be sufficient for practical usage due to inherent variation among biological samples. The portable breast cancer diagnostic tool reported in this manuscript shows the feasibility of measuring multiple parameters of breast tissue allowing for practical application.
GOAL: This research aims to validate a new biomarker of breast cancer by introducing electromechanical coupling factor of breast tissue samples as a possible additional indicator of breast cancer. Since collagen fibril exhibits a structural organization that gives rise to a piezoelectric effect, the difference in collagen density between normal and cancerous tissue can be captured by identifying the corresponding electromechanical coupling factor. METHODS: The design of a portable diagnostic tool and a microelectromechanical systems (MEMS)-based biochip, which is integrated with a piezoresistive sensing layer for measuring the reaction force as well as a microheater for temperature control, is introduced. To verify that electromechanical coupling factor can be used as a biomarker for breast cancer, the piezoelectric model for breast tissue is described with preliminary experimental results on five sets of normal and invasive ductal carcinoma (IDC) samples in the 25-45 temperature range. CONCLUSION: While the stiffness of breast tissues can be captured as a representative mechanical signature which allows one to discriminate among tissue types especially in the higher strain region, the electromechanical coupling factor shows more distinct differences between the normal and IDC groups over the entire strain region than the mechanical signature. From the two-sample -test, the electromechanical coupling factor under compression shows statistically significant differences ( 0.0039) between the two groups. SIGNIFICANCE: The increase in collagen density in breast tissue is an objective and reproducible characteristic of breast cancer. Although characterization of mechanical tissue property has been shown to be useful for differentiating cancerous tissue from normal tissue, using a single parameter may not be sufficient for practical usage due to inherent variation among biological samples. The portable breast cancer diagnostic tool reported in this manuscript shows the feasibility of measuring multiple parameters of breast tissue allowing for practical application.
Authors: Alicia Calzado-Martín; Mario Encinar; Javier Tamayo; Montserrat Calleja; Alvaro San Paulo Journal: ACS Nano Date: 2016-02-25 Impact factor: 15.881
Authors: Hardik J Pandya; Kihan Park; Wenjin Chen; Lauri A Goodell; David J Foran; Jaydev P Desai Journal: IEEE Trans Biomed Eng Date: 2016-02-26 Impact factor: 4.538
Authors: Salem Alowami; Sandra Troup; Sahar Al-Haddad; Iain Kirkpatrick; Peter H Watson Journal: Breast Cancer Res Date: 2003-07-23 Impact factor: 6.466
Authors: Daniel Y Joh; Jacob T Heggestad; Shengwei Zhang; Gray R Anderson; Jayanta Bhattacharyya; Suzanne E Wardell; Simone A Wall; Amy B Cheng; Faris Albarghouthi; Jason Liu; Sachi Oshima; Angus M Hucknall; Terry Hyslop; Allison H S Hall; Kris C Wood; E Shelley Hwang; Kyle C Strickland; Qingshan Wei; Ashutosh Chilkoti Journal: NPJ Breast Cancer Date: 2021-07-02