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24 February 2009 Photoacoustic characterization of ovarian tissue
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Ovarian cancer has the highest mortality of all gynecologic cancers with a five-year survival rate of only 30%. Because current imaging techniques (ultrasound, CT, MRI, PET) are not capable of detecting ovarian cancer early, most diagnoses occur in later stages (III/IV). Thus many women are not correctly diagnosed until the cancer becomes widely metastatic. On the other hand, while the majority of women with a detectable ultrasound abnormality do not harbor a cancer, they all undergo unnecessary oophorectomy. Hence, new imaging techniques that can provide functional and molecular contrasts are needed for improving the specificity of ovarian cancer detection and characterization. One such technique is photoacoustic imaging, which has great potential to reveal early tumor angiogenesis through intrinsic optical absorption contrast from hemoglobin or extrinsic contrast from conjugated agents binding to appropriate molecular receptors. To better understand the cancer disease process of ovarian tissue using photoacoustic imaging, it is necessary to first characterize the properties of normal ovarian tissue. We have imaged ex-vivo ovarian tissue using a 3D co-registered ultrasound and photoacoustic imaging system. The system is capable of volumetric imaging by means of electronic focusing. Detecting and visualizing small features from multiple viewing angles is possible without the need for any mechanical movement. The results show strong optical absorption from vasculature, especially highly vascularized corpora lutea, and low absorption from follicles. We will present correlation of photoacoustic images from animals with histology. Potential application of this technology would be the noninvasive imaging of the ovaries for screening or diagnostic purposes.
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Andres Aguirre, John Gamelin, Puyun Guo, Shikui Yan, Mary Sanders, Molly Brewer, and Quing Zhu "Photoacoustic characterization of ovarian tissue", Proc. SPIE 7177, Photons Plus Ultrasound: Imaging and Sensing 2009, 717708 (24 February 2009);

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