2016
DOI: 10.7863/ultra.15.09059
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Evaluation of Frequency Domain Analysis of a Multiwavelength Photoacoustic Signal for Differentiating Malignant From Benign and Normal Prostates

Abstract: Objectives The purpose of this study was to investigate the feasibility of differentiating malignant prostate from benign prostatic hyperplasia (BPH) and normal prostate tissue by performing frequency domain analysis of photoacoustic images acquired at 2 different wavelengths. Methods We performed multiwavelength photoacoustic imaging on freshly excised human prostate specimens taken from a total of 30 patients undergoing prostatectomy for biopsy-confirmed prostate cancer. Histologic slides marked by a genit… Show more

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Cited by 29 publications
(31 citation statements)
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“…Therefore, the superficial illumination approach used in our previous studies is not applicable in the in vivo prostate imaging scenario. Most of the previous studies on the PA imaging of prostate cancer were performed with sliced prostate tissues ex vivo . Our recently developed needle PA probe facilitates the delivery of relatively uniform illumination along a fiber optic diffuser, and the reception of the high frequency PA signals with a needle hydrophone from nearby tissues .…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, the superficial illumination approach used in our previous studies is not applicable in the in vivo prostate imaging scenario. Most of the previous studies on the PA imaging of prostate cancer were performed with sliced prostate tissues ex vivo . Our recently developed needle PA probe facilitates the delivery of relatively uniform illumination along a fiber optic diffuser, and the reception of the high frequency PA signals with a needle hydrophone from nearby tissues .…”
Section: Introductionmentioning
confidence: 99%
“…Exploiting the spectrum of PA signal amplitude at a range of PA wave frequency, frequency domain analysis has shown potential in determining important parameters, such as the size and concentration, of the optical absorber and thus enabling the quantitative characterization of the prostate tissue, as demonstrated by Kumon et al, Sinha et al, and Patterson et al [87][88][89] Several challenges, however, are faced in the development of both PAI spectroscopy and frequency domain analysis towards clinical implementation. The spectral parameters are likely to be di®erent in an in vivo system, due to the overlying tissue; the algorithm for chromophore PA image reconstrucion is more complicated in reality, given that there are more components than dHb, HbO 2 , lipids, and water in biological tissues.…”
Section: Pai Of Prostate Cancer Using Endogenous Contrastmentioning
confidence: 99%
“…The spectral parameters are likely to be di®erent in an in vivo system, due to the overlying tissue; the algorithm for chromophore PA image reconstrucion is more complicated in reality, given that there are more components than dHb, HbO 2 , lipids, and water in biological tissues. 88,90 Additionally, in going from a 1D transducer to a 2D or 3D transducer array used in in vivo prostate imaging, the di±culty in image processing must be overcome. 88 Although studies have shown e®ective endogenous contrast for tumor visualization, these biological ¼ 800 nm, 6 Â 12 mm).…”
Section: Pai Of Prostate Cancer Using Endogenous Contrastmentioning
confidence: 99%
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“…Using simulation and experiments involving osteoporotic rat femoral heads, Feng et al explored the capability of photoacoustic spectral parameters to perform bone microstructure characterization. Sinha et al differentiated among malignant, benign, and normal prostate tissue using photoacoustic spectral parameters in an ex vivo multiwavelength photoacoustic study with actual human patients. In an ex vivo study, Xu et al used a frequency domain analysis of photoacoustic signals for fatty liver diagnosis in a mouse model.…”
mentioning
confidence: 99%