Literature DB >> 27573795

Evaluation of Frequency Domain Analysis of a Multiwavelength Photoacoustic Signal for Differentiating Malignant From Benign and Normal Prostates: Ex Vivo Study With Human Prostates.

Saugata Sinha1, Navalgund A Rao2, Bhargava K Chinni3, Vikram S Dogra3.   

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 genitourinary pathologist were used as ground truth to define regions of interest (ROIs) in the photoacoustic images. Primarily, 3 different prostate tissue categories, namely malignant, BPH, and normal, were considered, while a fourth category named nonmalignant was formed by combining the ROIs corresponding to BPH and normal tissue together. We extracted 3 spectral parameters, namely slope, midband fit, and intercept, from power spectra of the radiofrequency photoacoustic signals corresponding to the 3 primary tissue categories.
RESULTS: We analyzed data from 53 ROIs selected from the photoacoustic images of 30 patients. According to the histopathologic analysis, 19 ROIs were malignant, 8 were BPH, and 26 were normal. All the 3 spectral parameters and C-scan grayscale photoacoustic image pixel values were found to be significantly different (P < .01) between malignant and nonmalignant prostate as well as malignant and normal prostate.
CONCLUSIONS: Preliminary results of our ex vivo human prostate study suggest that spectral parameters obtained by performing frequency domain analysis of photoacoustic signals can be used to differentiate between malignant and nonmalignant prostate.

Entities:  

Keywords:  frequency domain analysis; genitourinary ultrasound; multiwavelength; photoacoustic imaging; power spectrum; prostate cancer

Mesh:

Year:  2016        PMID: 27573795      PMCID: PMC5651985          DOI: 10.7863/ultra.15.09059

Source DB:  PubMed          Journal:  J Ultrasound Med        ISSN: 0278-4297            Impact factor:   2.153


  23 in total

1.  Contrast-enhanced sonography for prostate cancer detection in patients with indeterminate clinical findings.

Authors:  Ahn Yi; Jeong Kon Kim; Seong Ho Park; Kyoung Won Kim; Ho Sung Kim; Jung Hoon Kim; Hyo Won Eun; Kyoung-Sik Cho
Journal:  AJR Am J Roentgenol       Date:  2006-05       Impact factor: 3.959

Review 2.  Quantitative spectroscopic photoacoustic imaging: a review.

Authors:  Ben Cox; Jan G Laufer; Simon R Arridge; Paul C Beard
Journal:  J Biomed Opt       Date:  2012-06       Impact factor: 3.170

3.  Prostate biopsy: current status and limitations.

Authors:  Joseph C Presti
Journal:  Rev Urol       Date:  2007

4.  Estimating chromophore distributions from multiwavelength photoacoustic images.

Authors:  B T Cox; S R Arridge; P C Beard
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2009-02       Impact factor: 2.129

5.  Towards accurate in vivo spectroscopy of the human prostate.

Authors:  Tomas Svensson; Erik Alerstam; Margrét Einarsdóttír; Katarina Svanberg; Stefan Andersson-Engels
Journal:  J Biophotonics       Date:  2008-08       Impact factor: 3.207

6.  Photoacoustic ultrasound spectroscopy for assessing red blood cell aggregation and oxygenation.

Authors:  Eno Hysi; Ratan K Saha; Michael C Kolios
Journal:  J Biomed Opt       Date:  2012-12       Impact factor: 3.170

7.  Frequency-domain analysis of photoacoustic imaging data from prostate adenocarcinoma tumors in a murine model.

Authors:  Ronald E Kumon; Cheri X Deng; Xueding Wang
Journal:  Ultrasound Med Biol       Date:  2011-03-03       Impact factor: 2.998

8.  The impact of real-time elastography guiding a systematic prostate biopsy to improve cancer detection rate: a prospective study of 353 patients.

Authors:  Marko Brock; Christian von Bodman; Rein Jüri Palisaar; Björn Löppenberg; Florian Sommerer; Thomas Deix; Joachim Noldus; Thilo Eggert
Journal:  J Urol       Date:  2012-04-11       Impact factor: 7.450

Review 9.  Imaging prostate cancer: a multidisciplinary perspective.

Authors:  Hedvig Hricak; Peter L Choyke; Steven C Eberhardt; Steven A Leibel; Peter T Scardino
Journal:  Radiology       Date:  2007-04       Impact factor: 11.105

10.  Photoacoustic imaging: opening new frontiers in medical imaging.

Authors:  Keerthi S Valluru; Bhargava K Chinni; Navalgund A Rao
Journal:  J Clin Imaging Sci       Date:  2011-05-06
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  7 in total

1.  Cylindrical illumination with angular coupling for whole-prostate photoacoustic tomography.

Authors:  Brittani Bungart; Yingchun Cao; Tiffany Yang-Tran; Sean Gorsky; Lu Lan; Darren Roblyer; Michael O Koch; Liang Cheng; Timothy Masterson; Ji-Xin Cheng
Journal:  Biomed Opt Express       Date:  2019-02-22       Impact factor: 3.732

2.  Frequency Domain Analysis of Multiwavelength Photoacoustic Signals for Differentiating Among Malignant, Benign, and Normal Thyroids in an Ex Vivo Study With Human Thyroids.

Authors:  Saugata Sinha; Vikram S Dogra; Bhargava K Chinni; Navalgund A Rao
Journal:  J Ultrasound Med       Date:  2017-06-08       Impact factor: 2.153

3.  Photoacoustic spectral analysis at ultraviolet wavelengths for characterizing the Gleason grades of prostate cancer.

Authors:  Janggun Jo; Javed Siddiqui; Yunhao Zhu; Linyu Ni; Sri-Rajasekhar Kothapalli; Scott A Tomlins; John T Wei; Evan T Keller; Aaron M Udager; Xueding Wang; Guan Xu
Journal:  Opt Lett       Date:  2020-11-01       Impact factor: 3.776

4.  Photoacoustic graphic equalization and application in characterization of red blood cell aggregates.

Authors:  Lokesh Basavarajappa; Kenneth Hoyt
Journal:  Photoacoustics       Date:  2022-05-09

5.  Interstitial assessment of aggressive prostate cancer by physio-chemical photoacoustics: An ex vivo study with intact human prostates.

Authors:  Shengsong Huang; Yu Qin; Yingna Chen; Jing Pan; Chengdang Xu; Denglong Wu; Wan-Yu Chao; John T Wei; Scott A Tomlins; Xueding Wang; J Brian Fowlkes; Paul L Carson; Qian Cheng; Guan Xu
Journal:  Med Phys       Date:  2018-06-23       Impact factor: 4.071

6.  Implementation of Machine Learning Mechanism for Recognising Prostate Cancer through Photoacoustic Signal.

Authors:  G Ramkumar; P Bhuvaneswari; R Radhika; S Saranya; S Vijayalakshmi; M Karpagam; Florin Wilfred
Journal:  Contrast Media Mol Imaging       Date:  2022-09-20       Impact factor: 3.009

7.  Photoacoustic tomography of intact human prostates and vascular texture analysis identify prostate cancer biopsy targets.

Authors:  Brittani L Bungart; Lu Lan; Pu Wang; Rui Li; Michael O Koch; Liang Cheng; Timothy A Masterson; Murat Dundar; Ji-Xin Cheng
Journal:  Photoacoustics       Date:  2018-08-03
  7 in total

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