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

Brittani L. Bungart, Lu Lan, Pu Wang, Rui Li, Michael Koch, Liang Cheng, Timothy Masterson, Murat Dundar, Ji Xin Cheng

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Prostate cancer is poorly visualized on ultrasonography (US) so that current biopsy requires either a templated technique or guidance after fusion of US with magnetic resonance imaging. Here we determined the ability for photoacoustic tomography (PAT) and US followed by texture-based image processing to identify prostate biopsy targets. K-means clustering feature learning and testing was performed on separate datasets comprised of 1064 and 1197 nm PAT and US images of intact, ex vivo human prostates. 1197 nm PAT was found to not contribute to the feature learning, and thus, only 1064 nm PAT and US images were used for final feature testing. Biopsy targets, determined by the tumor-assigned pixels’ center of mass, located 100% of the primary lesions and 67% of the secondary lesions. In conclusion, 1064 nm PAT and US texture-based feature analysis provided successful prostate biopsy targets.

Original languageEnglish (US)
Pages (from-to)46-55
Number of pages10
JournalPhotoacoustics
Volume11
DOIs
StatePublished - Sep 1 2018

Fingerprint

Blood Vessels
Prostate
Ultrasonography
Prostatic Neoplasms
textures
tomography
cancer
Tomography
Biopsy
lesions
learning
Learning
Aptitude
center of mass
magnetic resonance
image processing
tumors
fusion
pixels
Cluster Analysis

Keywords

  • K-means clustering
  • Photoacoustic imaging
  • Prostate
  • Targeted biopsy
  • Texture image processing

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Cite this

Photoacoustic tomography of intact human prostates and vascular texture analysis identify prostate cancer biopsy targets. / Bungart, Brittani L.; Lan, Lu; Wang, Pu; Li, Rui; Koch, Michael; Cheng, Liang; Masterson, Timothy; Dundar, Murat; Cheng, Ji Xin.

In: Photoacoustics, Vol. 11, 01.09.2018, p. 46-55.

Research output: Contribution to journalArticle

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AU - Lan, Lu

AU - Wang, Pu

AU - Li, Rui

AU - Koch, Michael

AU - Cheng, Liang

AU - Masterson, Timothy

AU - Dundar, Murat

AU - Cheng, Ji Xin

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