Role of blood oxygenation saturation in ovarian cancer diagnosis using multi-spectral photoacoustic tomography

Eghbal Amidi, Guang Yang, K. M.Shihab Uddin, Hongbo Luo, William Middleton, Matthew Powell, Cary Siegel, Quing Zhu

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

In photoacoustic tomography (PAT), a tunable laser typically illuminates the tissue at multiple wavelengths, and the received photoacoustic waves are used to form functional images of relative total haemoglobin (rHbT) and blood oxygenation saturation (%sO2). Due to measurement errors, the estimation of these parameters can be challenging, especially in clinical studies. In this study, we use a multi-pixel method to smooth the measurements before calculating rHbT and %sO2. We first perform phantom studies using blood tubes of calibrated %sO2 to evaluate the accuracy of our %sO2 estimation. We conclude by presenting diagnostic results from PAT of 33 patients with 51 ovarian masses imaged by our co-registered PAT and ultrasound system. The ovarian masses were divided into malignant and benign/normal groups. Functional maps of rHbT and %sO2 and their histograms as well as spectral features were calculated using the PAT data from all ovaries in these two groups. Support vector machine models were trained on different combinations of the significant features. The area under ROC (AUC) of 0.93 (0.95%CI: 0.90-0.96) on the testing data set was achieved by combining mean %sO2, a spectral feature, and the score of the study radiologist.

Original languageEnglish
Article numbere202000368
JournalJournal of Biophotonics
Volume14
Issue number4
DOIs
StatePublished - Apr 2021

Keywords

  • feature extraction
  • ovarian cancer diagnosis
  • oxygen saturation (%sO)
  • photoacoustic tomography

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