Multispectral photoacoustic (MPA) specimen imaging modality is proven successful in differentiating photoacoustic (PA) signal characteristics from a cancer and normal region. The oxy and de-oxy hemoglobin content in a human tissue captured in the MPA data are the key features for cancer detection. In this study, we propose to use deep 3D convolution neural network trained on the thyroid MPA dataset and tested on the prostate MPA dataset to evaluate this potential. The proposed algorithm first extracts the spatial, spectral, and temporal features from the thyroid MPA image data using 3D convolutional layers and detects cancer tissue using the logistic function, the last layer of the network. The model achieved an AUC (area under the curve) of the ROC (receiver operating characteristic) curve of 0.72 on the prostate MPA dataset.
Acoustic lens based focusing technology where the image reconstruction is achieved through the focusing of an acoustic lens, can potentially replace time consuming and expensive electronic focusing technology for producing high resolution real time ultrasound (US) images. A novel acoustic lens focusing based pulse echo US imaging system is explored here. In the system, a Polyvinylidene fluoride (PVDF) film transducer generates plane wave which is backscattered by the object and focused by a spherical acoustic lens on to a linear array of transducers. To improve the anticipated low signal to noise ratio (SNR) of the received US signal due to the low electromechanical coupling coefficient of the PVDF film, here we explored the possibility of implementing pulse compression technique using linear frequency modulated (FM) signals or chirp signals. Comparisons among the different SNR values obtained with short pulse and after pulse compression with chirp signal show a clear improvement of the SNR for the compressed pulse. The preliminary results show that the SNR achieved for the compressed pulse depends on time bandwidth product of the input chirp and the spectrum of the US transducers. The axial resolution obtained with compressed pulse improved with increasing sweep bandwidth of input chirp signals, whereas the lateral resolution remained almost constant. This work demonstrates the feasibility of using a PVDF film transducer as an US transmitter in an acoustic lens focusing based imaging system and implementing pulse compression technique into the same setup to improve SNR of the received US signal.
Frequency domain analysis of the photoacoustic (PA) radio frequency signals can potentially be used as a tool for characterizing microstructure of absorbers in tissue. This study investigates the feasibility of analyzing the spectrum of multiwavelength PA signals generated by excised human prostate tissue samples to differentiate between malignant and normal prostate regions. Photoacoustic imaging at five different wavelengths, corresponding to peak absorption coefficients of deoxyhemoglobin, whole blood, oxyhemoglobin, water and lipid in the near infrared (NIR) (700 nm – 1000 nm) region, was performed on freshly excised prostate specimens taken from patients undergoing prostatectomy for biopsy confirmed prostate cancer. The PA images were co-registered with the histopathology images of the prostate specimens to determine the region of interest (ROI) corresponding to malignant and normal tissue. The calibrated power spectrum of each PA signal from a selected ROI was fit to a linear model to extract the corresponding slope, midband fit and intercept parameters. The mean value of each parameter corresponding to malignant and adjacent normal prostate ROI was calculated for each of the five wavelengths. The results obtained for 9 different human prostate specimens, show that the mean values of midband fit and intercept are significantly different between malignant and normal regions. In addition, the average midband fit and intercept values show a decreasing trend with increasing wavelength. These preliminary results suggest that frequency analysis of multispectral PA signals can be used to differentiate malignant region from the adjacent normal region in human prostate tissue.
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