Multi-acoustic lens design methodology for a low cost C-scan photoacoustic imaging camera

Abstract

We have designed and implemented a novel acoustic lens based focusing technology into a prototype photoacoustic imaging camera. All photoacoustically generated waves from laser exposed absorbers within a small volume get focused simultaneously by the lens onto an image plane. We use a multi-element ultrasound transducer array to capture the focused photoacoustic signals. Acoustic lens eliminates the need for expensive data acquisition hardware systems, is faster compared to electronic focusing and enables real-time image reconstruction. Using this photoacoustic imaging camera, we have imaged more than 150 several centimeter size ex-vivo human prostate, kidney and thyroid specimens with a millimeter resolution for cancer detection. In this paper, we share our lens design strategy and how we evaluate the resulting quality metrics (on and off axis point spread function, depth of field and modulation transfer function) through simulation. An advanced toolbox in MATLAB was adapted and used for simulating a two-dimensional gridded model that incorporates realistic photoacoustic signal generation and acoustic wave propagation through the lens with medium properties defined on each grid point. Two dimensional point spread functions have been generated and compared with experiments to demonstrate the utility of our design strategy. Finally we present results from work in progress on the use of two lens system aimed at further improving some of the quality metrics of our system.

Automatic cancer tissue detection using multispectral photoacoustic imaging

“…The second reason is that light suffers less from absorption and scattering in deep tissue imaging [11,104]. In the case of the tissue imaging, four variables, namely deoxyhemoglobin, oxyhemoglobin, lipid, and water, were chosen to explain the variations and characteristics of malignant and nonmalignant regions [19,20]. In this thesis, the five wavelengths from the NIR window, namely 760 nm, 850 nm, 930 nm, 970 nm, and 800 nm, were chosen.…”

“…The first four wavelengths correspond to the peak of the absorption spectrum of deoxyhemoglobin, oxyhemoglobin, lipid, and water respectively, and the fifth wavelength corresponds to the equal of the absorption spectrum of oxyhemoglobin and deoxyhemoglobin. The wavelengths were chosen in such a way that one variable is decreasing and the other is increasing to analyze the contribution of the individual chromophores for classification of malignant and normal region [20]. The choice of five wavelengths for cancer tissue detection was already proposed and evaluated in the literature [28,75,104].…”

“…Ex-vivo tissue specimen and PA image It is important to describe the method and the resulting data structure in this section briefly because we used a unique setup to acquire PA signal data set from tissue specimens. The method, the details of which can be found in[20], is illustrated in figure(2.7). An expanded beam of 10 ns pulse of NIR laser light with delivered pulse energy below 20 mJ/cm 2 and pulse repetition rate of 10 Hz was used to expose the tissue specimen immersed in a water-filled medium[47].…”

“…The biconcave acoustic lens was used to converge the spherically diverging US wave at a transducer when light is traveling from water to lens[20]. The biconvex acoustic lens is used in the optical imaging modality where light travels from air to glass.…”

“…The object (tissue specimen) was placed at 2f location to image the tissue specimen at 2f position for a unit magnification[35]. The proper choice of tissue specimen in front of the acoustic lens removes the concern of the scaling effect[20].2.3 Ex-vivo PA acquisition and ANSI guidelinesPA imaging at five different wavelengths was performed on the freshly excised human prostate and thyroid specimens. The author received the PA dataset prior to the study and wanted to acknowledge[20,28,77,104] for providing datasets.The detailed of the experiment are described below.…”