Abstract
There is a need for accurate and rapid detection of renal cancer in clinic. Here, we integrated photoacoustic tomography (PAT) with ultrasound imaging in a single system, which achieved tissue imaging depth about 3 mm and imaging speed about 3.5 cm(2)/min. We used the wavelength at 1197 nm to map lipid distribution in normal renal tissues and clear cell renal cell carcinoma (ccRCC) tissues collected from 19 patients undergone nephrectomy. Our results indicated that the photoacoustic signal from lipids was significantly higher in ccRCC tissues than that in normal tissues. Moreover, based on the quantification of lipid area ratio, we were able to differentiate normal and ccRCC with 100 % sensitivity, 80 % specificity, and area under receiver operating characteristic curve of 0.95. Our findings demonstrate that multimodal PAT can differentiate normal and ccRCC by integrating the morphologic information from ultrasound and lipid amount information from vibrational PAT.