An optimized ultrasound detector for photoacoustic breast tomography

Photoacoustic imaging has proven to be able to detect vascularization-driven optical absorption contrast associated with tumors. In order to detect breast tumors located a few centimeter deep in tissue, a sensitive ultrasound detector is of crucial importance for photoacoustic mammography. Further, because the expected photoacoustic frequency bandwidth (a few MHz to tens of kHz) is inversely proportional to the dimensions of light absorbing structures (0.5 to 10+ mm), proper choices of materials and their geometries, and proper considerations in design have to be made for optimal photoacoustic detectors. In this study, we design and evaluate a specialized ultrasound detector for photoacoustic mammography. Based on the required detector sensitivity and its frequency response, a selection of active material and matching layers and their geometries is made leading to a functional detector models. By iteration between simulation of detector performances, fabrication and experimental characterization of functional models an optimized implementation is made and evaluated. The experimental results of the designed first and second functional detectors matched with the simulations. In subsequent bare piezoelectric samples the effect of lateral resonances was addressed and their influence minimized by sub-dicing the samples. Consequently, using simulations, the final optimized detector could be designed, with a center frequency of 1 MHz and a -6 dB bandwidth of ~80%. The minimum detectable pressure was measured to be 0.5 Pa, which will facilitate deeper imaging compared to the currrent systems. The detector should be capable of detecting vascularized tumors with resolution of 1-2 mm. Further improvements by proper electrical grounding and shielding and implementation of this design into an arrayed detector will pave the way for clinical applications of photoacoustic mammography.Comment: Accepted for publication in Medical Physics (American Association of Physicists in Medicine

Discrete Imaging Models for Three-Dimensional Optoacoustic Tomography using Radially Symmetric Expansion Functions

Optoacoustic tomography (OAT), also known as photoacoustic tomography, is an emerging computed biomedical imaging modality that exploits optical contrast and ultrasonic detection principles. Iterative image reconstruction algorithms that are based on discrete imaging models are actively being developed for OAT due to their ability to improve image quality by incorporating accurate models of the imaging physics, instrument response, and measurement noise. In this work, we investigate the use of discrete imaging models based on Kaiser-Bessel window functions for iterative image reconstruction in OAT. A closed-form expression for the pressure produced by a Kaiser-Bessel function is calculated, which facilitates accurate computation of the system matrix. Computer-simulation and experimental studies are employed to demonstrate the potential advantages of Kaiser-Bessel function-based iterative image reconstruction in OAT

Super-resolution photoacoustic imaging via flow induced absorption fluctuations

In deep tissue photoacoustic imaging the spatial resolution is inherently limited by the acoustic wavelength. We present an approach for surpassing the acoustic diffraction limit by exploiting temporal fluctuations in the sample absorption distribution, such as those induced by flowing particles. In addition to enhanced resolution, our approach inherently provides background reduction, and can be implemented with any conventional photoacoustic imaging system. The considerable resolution increase is made possible by adapting notions from super-resolution optical fluctuations imaging (SOFI) developed for blinking fluorescent molecules, to flowing acoustic emitters. By generalizing SOFI mathematical analysis to complex valued signals, we demonstrate super-resolved photoacoustic images that are free from oscillations caused by band-limited detection. The presented technique holds potential for contrast-agent free micro-vessels imaging, as red blood cells provide a strong endogenous source of naturally fluctuating absorption

An open environment CT-US fusion for tissue segmentation during interventional guidance.

Therapeutic ultrasound (US) can be noninvasively focused to activate drugs, ablate tumors and deliver drugs beyond the blood brain barrier. However, well-controlled guidance of US therapy requires fusion with a navigational modality, such as magnetic resonance imaging (MRI) or X-ray computed tomography (CT). Here, we developed and validated tissue characterization using a fusion between US and CT. The performance of the CT/US fusion was quantified by the calibration error, target registration error and fiducial registration error. Met-1 tumors in the fat pads of 12 female FVB mice provided a model of developing breast cancer with which to evaluate CT-based tissue segmentation. Hounsfield units (HU) within the tumor and surrounding fat pad were quantified, validated with histology and segmented for parametric analysis (fat: -300 to 0 HU, protein-rich: 1 to 300 HU, and bone: HU>300). Our open source CT/US fusion system differentiated soft tissue, bone and fat with a spatial accuracy of ∼1 mm. Region of interest (ROI) analysis of the tumor and surrounding fat pad using a 1 mm(2) ROI resulted in mean HU of 68±44 within the tumor and -97±52 within the fat pad adjacent to the tumor (p<0.005). The tumor area measured by CT and histology was correlated (r(2) = 0.92), while the area designated as fat decreased with increasing tumor size (r(2) = 0.51). Analysis of CT and histology images of the tumor and surrounding fat pad revealed an average percentage of fat of 65.3% vs. 75.2%, 36.5% vs. 48.4%, and 31.6% vs. 38.5% for tumors <75 mm(3), 75-150 mm(3) and >150 mm(3), respectively. Further, CT mapped bone-soft tissue interfaces near the acoustic beam during real-time imaging. Combined CT/US is a feasible method for guiding interventions by tracking the acoustic focus within a pre-acquired CT image volume and characterizing tissues proximal to and surrounding the acoustic focus

Photoacoustic computed tomography guided microrobots for targeted navigation in intestines in vivo

Tremendous progress in synthetic micro/nanomotors has been made for potential biomedical applications. However, existing micro/nanomotor platforms are inefficient for deep tissue imaging and motion control in vivo. Here, we present a photoacoustic computed tomography (PACT) guided investigation of micromotors in intestines in vivo. The micromotors enveloped in microcapsules exhibit efficient propulsion in various biofluids once released. PACT has visualized the migration of micromotor capsules toward the targeted regions in real time in vivo. The integration of the developed microrobotic system and PACT enables deep imaging and precise control of the micromotors in vivo

Graphics processing unit accelerating compressed sensing photoacoustic computed tomography with total variation

Photoacoustic computed tomography with compressed sensing (CS-PACT) is a commonly used imaging strategy for sparse-sampling PACT. However, it is very time-consuming because of the iterative process involved in the image reconstruction. In this paper, we present a graphics processing unit (GPU)-based parallel computation framework for total-variation-based CS-PACT and adapted into a custom-made PACT system. Specifically, five compute-intensive operators are extracted from the iteration algorithm and are redesigned for parallel performance on a GPU. We achieved an image reconstruction speed 24–31 times faster than the CPU performance. We performed in vivo experiments on human hands to verify the feasibility of our developed method