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Role of blood oxygenation saturation in ovarian cancer diagnosis using multi‐spectral photoacoustic tomography
Author(s) -
Amidi Eghbal,
Yang Guang,
Uddin K. M. Shihab,
Luo Hongbo,
Middleton William,
Powell Matthew,
Siegel Cary,
Zhu Quing
Publication year - 2021
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.202000368
Subject(s) - photoacoustic imaging in biomedicine , imaging phantom , oxygenation , tomography , biomedical engineering , ultrasound , oxygen saturation , medicine , saturation (graph theory) , histogram , nuclear medicine , materials science , radiology , mathematics , computer science , optics , artificial intelligence , physics , quantum mechanics , combinatorics , oxygen , image (mathematics)
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 (%sO 2 ). 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 %sO 2 . We first perform phantom studies using blood tubes of calibrated %sO 2 to evaluate the accuracy of our %sO 2 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 %sO 2 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 %sO 2 , a spectral feature, and the score of the study radiologist.