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Feasibility of Quantitative Tissue Characterization Using Novel Parameters Extracted From Photoacoustic Power Spectrum Considering Multiple Absorbers.
Rathi, Nikita; Sinha, Saugata; Chinni, Bhargava; Dogra, Vikram; Rao, Navalgund.
Afiliación
  • Rathi N; Department of Electronics and Communication, Visvesvaraya National Institute of Technology, Nagpur, Maharashtra, India.
  • Sinha S; Department of Electronics and Communication, Visvesvaraya National Institute of Technology, Nagpur, Maharashtra, India.
  • Chinni B; Department of Imaging Sciences, University of Rochester Medical Center, Rochester, NY, USA.
  • Dogra V; Department of Imaging Sciences, University of Rochester Medical Center, Rochester, NY, USA.
  • Rao N; Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA.
Ultrason Imaging ; 44(1): 13-24, 2022 01.
Article en En | MEDLINE | ID: mdl-34711106
ABSTRACT
Frequency domain analysis of radio frequency signal is performed to differentiate between different tissue categories in terms of spectral parameters. However, due to complex relationship between the absorber size and spectral parameters, they cannot be used for quantitative tissue characterization. In an earlier study, we showed that using linear relationship between absorber size and two new spectral parameters namely number of lobes and average lobe width, absorber size can be successfully recovered from photoacoustic signal generated by single absorber. As actual biological tissue contains multiple absorbers, in this study we extended the application of these two new spectral parameters for computing absorber size from signals generated by multiple PA absorbers. We revisited our analytical model to establish two new linear relationships between the absorber radius and number of lobes as well as average lobe width considering multiple absorbers with bandlimited acquisition. A simulation study was performed to validate these linear relationships. A retrospective ex vivo study, in which the spectral parameters were computed using multiwavelength photoacoustic signals, was performed with freshly exercised thyroid specimens from 38 actual human patients undergoing thyroidectomy after having a diagnosis of suspected thyroid lesions. From statistical analysis it is shown that both the parameters were significantly different between malignant and non-malignant thyroid and malignant and normal thyroid tissue. Performance of the supervised classification with the computed spectral parameters showed that the extracted parameters could be successfully used to differentiate malignant thyroid tissue from normal thyroid tissue with reasonable degree of accuracy.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Técnicas Fotoacústicas Tipo de estudio: Observational_studies Límite: Humans Idioma: En Revista: Ultrason Imaging Año: 2022 Tipo del documento: Article País de afiliación: India

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Técnicas Fotoacústicas Tipo de estudio: Observational_studies Límite: Humans Idioma: En Revista: Ultrason Imaging Año: 2022 Tipo del documento: Article País de afiliación: India
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