2.1.

LOIS-P System Description and Testing

The potential of OA imaging for detecting prostate malignancies was evaluated by imaging surgically exposed canine prostate, illuminated orthogonally, and also blood vessel phantoms imaged in both forward and backward modes. Samples were illuminated with a $Q$ -switched alexandrite laser (Ta2, Light Age Inc., Somerset, New Jersey ) producing $75\text{-}\mathrm{ns}$ laser pulses of $757\text{-}\mathrm{nm}$ wavelength at a $10\text{-}\mathrm{Hz}$ repetition rate. The laser light was delivered via a bifurcating optical fiber bundle (Dolan-Jenner, Boxborough, Massachusetts) with fluence at the sample surface about $10\mathrm{mJ}∕{\mathrm{cm}}^2$ . The fiber bundle was comprised of $50\text{-}\mu \mathrm{m}$ glass fibers, and the terminal bundles measured $4.5\mathrm{mm}$ in diameter. The laser-generated acoustic transients were collected with a commercial TRUS probe (EC7ART, Scanhead Corp., San Jose, California ), pictured in Fig. 1 . The probe contains an array of 128 piezoceramic transducer elements measure $6\times 0.2\mathrm{mm}$ each with a pitch of $0.21\mathrm{mm}$ . The transducers line the edge of a convex circular arc segment with a radius of $10\mathrm{mm}$ and total arc angle of $154\mathrm{deg}$ , as seen in the enlarged section of Fig. 1. The probe also contains an acoustic lens situated directly in front of the transducer array. The lens focuses inside the tissue onto an arc-shaped line with radius of $35\mathrm{mm}$ located in the imaging plane.

Fig. 1

(a) Commercial 128-channel endocavity ultrasound probe (EC7ART, Scanhead Corp., San Jose, California) used to collect acoustic transients for OA imaging. The piezoceramic detectors are oriented as a convex array lining the edge of the probe, as seen in the enlarged section. (b) Measured OA impulse response of a single detector in the endocavity probe, where the dashed line indicates envelope-detected signal used for estimation of the radial resolution (see text) and (c) the corresponding frequency response.

The OA signals acquired from the ultrasonic probe were amplified in two stages and digitized by a 128-channel electronics system. Both analog and digital components were developed by Fairway Medical Technologies (Houston, Texas) for the breast cancer detection system, and were described in a previous publication.²⁶ Briefly, the first stage consisted of a custom-built charge amplifier with a $30\text{-}\mathrm{dB}$ gain for low-noise amplification of capacitive sources. The second amplifier stage was a standard signal amplifier stage with a $30\text{-}\mathrm{dB}$ gain. The signals were then digitized by a $12\text{-bit}$ analog-to-digital converter with a maximum sampling rate of $41\mathrm{MHz}$ .

The impulse response of the probe was collected with a high sampling frequency $\left(1\mathrm{GHz}\right)$ using a digital oscilloscope (TDS 3014, Tektronix, Beaverton, Oregon ) operated at a high input impedance of $1\mathrm{M}\Omega$ to simulate the input of the LOIS-P amplifiers. An OA transient with a Dirac $\delta$ function profile was generated by irradiating a layer of highly absorptive India ink.²⁹ The probe’s frequency response was determined by calculating the absolute value of the impulse response’s fast Fourier transform in MATLAB (Mathworks, Natick, Massachusetts). For comparison, the frequency response was also determined for the entire LOIS-P system. In the latter case, the impulse response was collected using the commercial probe, LOIS-P electronics, and LOIS-XP software.

The custom-made LOIS-XP software was used to construct OA images from the digitized signal profiles. The program allows for various types of digital signal filtering and provides a real-time display (updating at $10\mathrm{Hz}$ ) of the processed signals from individual transducers. It uses the directivity-weighed filtered RBP algorithm to generate an image from the OA signals.^{14, 30}

We utilized digital filtering based on the third derivative of the Gaussian wavelet to process the OA signals.²⁹ In contrast to simple integration of $N$ -shaped OA signals, which produce bell-shaped profiles of velocity potential, the wavelet filter produces steep edges at the boundaries of the absorptive object, thereby increasing the sharpness of the OA image.

2.2.

OA Imaging of Phantoms in Forward and Backward Detection Modes

To evaluate the feasibility of OA imaging for prostate biopsy, we collected OA images of blood vessel phantoms using either forward or backward detection mode,¹⁶ in which laser illumination of tissue occurs on the opposite or the same side as the acoustic pressure detection, respectively. We constructed OA images of a $1\text{-}\mathrm{mm}$ tube oriented orthogonally to the imaging plane and located at various distances from the probe. Light was delivered through the terminal ends of the bifurcating fiber bundle described in Sec. 2.1. For forward mode detection, the bundle ends were positioned at stationary locations within the imaging plane roughly $7\mathrm{cm}$ away from the detector surface. The bundle ends were angled to direct light to a point $25\mathrm{mm}$ in front of the detector’s surface at the detector probe’s acoustic focus. In backward mode, the bundle ends were positioned at stationary locations within the imaging plane behind the detector surface and angled to illuminate an object $2.5\mathrm{cm}$ in front of the detector. The tube was embedded in a homogeneous absorptive and scattering liquid medium ( ${\mu }_a=0.2{\mathrm{cm}}^{-1}$ , ${\mu }_s=42.1{\mathrm{cm}}^{-1}$ , $g=0.75$ ), and contained an aqueous solution of $\mathrm{Cu}\mathrm{S}{\mathrm{O}}_4$ $({\mu }_a=8.73{\mathrm{cm}}^{-1})$ . OA signals were collected of a single target positioned at different depths, and were subsequently combined for direct visual comparison of the reconstructed OA images. To combine the images, we summed the raw signals collected for each target position and corrected the total for background.

2.3.

Computer Modeling

Using our three-step modeling procedure,²⁷ images were constructed by simulating (1) laser irradiation of prostate tissue, (2) the resultant acoustic transients, and (3) the tomographic image construction using the simulated acoustic transients.

We utilized our optical property measurements³¹ from freshly harvested prostate tissue of pigs at $\lambda =757\mathrm{nm}$ and Monte Carlo light scattering (MCLS) simulation software³² to compute the distribution of absorbed optical energy. The prostate gland was modeled as a $3.5\text{-}\mathrm{cm}$ -diam sphere ( $n=1.4$ , ${\mu }_a=0.417{\mathrm{cm}}^{-1}$ , ${\mu }_s=41.40{\mathrm{cm}}^{-1}$ , $g=0.881$ ). Bladder tissue ( $n=1.4$ , ${\mu }_a=0.014{\mathrm{cm}}^{-1}$ , ${\mu }_s=50.79{\mathrm{cm}}^{-1}$ , $g=0.872$ ) surrounded the prostate everywhere. The collapsed urethra was depicted as a cylindrical tube passing through the center of the sphere with a $3\text{-}\mathrm{mm}$ diameter ( $n=1.4$ , ${\mu }_a=0.240{\mathrm{cm}}^{-1}$ , ${\mu }_s=43.31{\mathrm{cm}}^{-1}$ , $g=0.651$ ). A $3\text{-}\mathrm{mm}$ -diam sphere represented a highly vascularized malignancy with optical properties identical to those of the prostate, with the exception of ${\mu }_a$ . It was assumed that blood is the primary absorptive tissue component in the NIR range, and that the microvessel density of the lesion was approximately twice that of the surrounding tissue. Therefore, in our Monte Carlo (MC) simulations, ${\mu }_a$ for the lesion was set to $0.834{\mathrm{cm}}^{-1}$ . Light illumination was done parallel to the urethra using a $30\text{-}\mathrm{mm}$ -diam Gaussian beam.

Using the light absorption volumes from the MC simulations, we modeled the acoustic transient signals received by the detectors.²⁷ Each cubic voxel from the MC simulation was represented in the acoustic model by the corresponding inscribed sphere. Each sphere, with radius $r_0$ , generated an $N$ -shaped acoustic transient signal proportional to the absorbed optical energy within the corresponding voxel. The signals were attenuated by acoustic diffraction with $r_0∕r$ dependence, where $r$ represents the distance from the center of the sphere to the specified point in space. Each $N$ -shaped acoustic signal was convolved with the temporal transducer window.²⁷ The signals from all spheres were added coherently based on the speed of sound in tissue $(1.54\mathrm{mm}∕\mu \mathrm{s})$ and their distance from the detector surface. The OA images were constructed from the generated OA signals using the filtered-RBP algorithm described in Sec. 2.1.

2.4.

In Vivo Imaging of Prostate Tissue

Under a protocol approved by the Institutional Animal Care and Use Committee at the University of Texas Medical Branch (Galveston, Texas), the feasibility of in vivo OA imaging of prostate tissue was explored using a live dog. The dog was anesthetized with a mixture of $20\mathrm{mg}∕\mathrm{kg}$ Pentothal IV and 0.5 to 2% halothane. To facilitate imaging, the dog’s prostate was surgically exposed and placed on the colon. After the initial imaging with LOIS-P, a 17G hypodermic needle was inserted from the superior side of the right lobe (adhering to the conventional prostate geometry utilized in urology). An abrasive brush was inserted through the needle and rotated to create a bloody lesion simulating a cancerous tumor with high blood content. The induced lesion was $3\mathrm{mm}$ in diameter and located $20\mathrm{mm}$ deep inside the prostate tissue. OA as well as the control TRUS images were acquired. Finally, the prostate was excised and the animal was humanely sacrificed by intravenous injection of $20\mathrm{cc}$ of potassium chloride solution, in accordance with recommendations from the Panel on Euthanasia of the American Veterinary Medical Association.

Irradiation of the exposed prostate tissue was performed in orthogonal detection mode, in which the laser illuminates the tissue from a direction perpendicular to the pressure detection. Illumination light was delivered through a fiber optic cable and a dispersing lens, while the OA probe was pressed firmly against the prostate from the anterior end of the animal. The optical fiber and dispersing lens provided a relatively homogeneous distribution of light within the imaging slice and, therefore, allowed to minimize the image artifacts associated with attenuation of light in the prostate. In this feasibility study, the orthogonal OA mode represented the “best-case scenario” for OA imaging of prostate.

Though TRUS currently lacks the ability to reliably distinguish malignant lesions from benign tissue, it provides detailed spatial information about the prostate. Combining the two imaging techniques has the potential to form high-contrast, high-resolution images, reliably yielding more comprehensive information of the prostate gland and the possible presence of tumors. Therefore, for comparison with OA images and to yield complementary information, ultrasonic images were collected during our in vivo imaging experiment using a commercial ultrasound system (3535, BK Medical, Herlev, Denmark) with a $30\text{-}\mathrm{mm}$ , $7.5\text{-}\mathrm{MHz}$ curved array probe. The system acquired ultrasound images at a rate of $84\text{frames}∕\mathrm{s}$ .

3.1.

System Characteristics

Figures 1 and 1 display the detected impulse response and corresponding frequency response, respectively. The frequency response, determined by the fast Fourier transform of the impulse response, shows the probe sensitivity within a $3\text{-}\text{to}9\text{-}\mathrm{MHz}$ bandwidth ( $-6\mathrm{dB}$ criterion). The frequency response also shows an undesirable sensitivity band present in the low-frequency range $(<1\mathrm{MHz})$ , known to contain large-magnitude acoustic artifacts.²⁹ Because the LOIS-P amplifier was designed to operate in wideband mode, the frequency response of the entire LOIS-P system was found to be similar to that of the probe alone (data not shown).

Using the Rayleigh criterion, the minimal distance resolvable in the radial direction of the probe (orthogonal to the array of transducers) was estimated as $a_{\min }^r=c_s{\tau }_{0.5}\approx 0.2\mathrm{mm}$ , where $c_s$ denotes the speed of sound in tissue $(1.54\mathrm{mm}∕\mu \mathrm{s})$ , and ${\tau }_{0.5}$ is the width of the impulse response, transformed to a monopolar waveform using the envelope detection, at the half-max amplitude level (measured to be $115\mathrm{ns}$ ). The maximum sensitivity of the system was measured using a calibrated²⁹ acoustic emitter (NP/OA90-3, Dapco Industries, Ridgefield, Connecticut ) at $5\mathrm{MHz}$ to be $S=2.1\mathrm{mV}∕\mathrm{Pa}$ . We assume that the minimum pressure that can be detected with our system occurs when the signal-to-noise ratio (SNR) is 1. Noise data were evaluated for the frequency range between $30\mathrm{kHz}$ and $10\mathrm{MHz}$ by collecting and processing recordings with the LOIS-P system in the absence of laser irradiation. The measured root mean squared (rms) noise was $U_{\mathrm{rms}}=3.84\pm 0.42\mathrm{mV}$ . Further analysis revealed that the noise was comprised primarily of white thermoelectric noise, with calculated spectral density of $0.558\pm 0.093\mu \mathrm{V}∕{\mathrm{Hz}}^{1∕2}$ . The minimum detectable pressure signal for the system can therefore be estimated as $p_{\min }=U_{\mathrm{rms}}∕S=1.83\mathrm{Pa}$ .

3.2.

Phantoms Imaged in Forward and Backward Detection Modes

Figure 2 shows OA images of a $1\text{-}\mathrm{mm}$ blood vessel phantom located at various distances from the probe. As seen in Fig. 2, when the tube is positioned close to the probe $(<15\mathrm{mm})$ , the cross section of the tube can be easily seen as a small $1\text{-}\mathrm{mm}$ circular source when using the backward OA mode. The deeper vessels in the image cannot be visualized at all. Also, in backward mode imaging, large low-frequency artifacts arise in the OA profiles from nonspecific light absorption in the subsurface volume of tissue and light that reflects back from the illuminated tissue and strikes the detector.²⁷ These artifacts were reduced in our further studies by proper signal processing and shielding the transducer surface with an optically opaque and acoustically thin polymer layer. In backward OA mode, the magnitudes of the detected OA signals decrease at farther distances from the probe, due to both the attenuation of light as it penetrates within the medium and acoustic diffraction. This combined attenuation effect limits the ability to visualize targets at far distances from the probe with backward mode imaging, as seen in Fig. 2.

Fig. 2

Images of combined OA signals for $1\text{-}\mathrm{mm}$ cylindrical tube (with the tube axis oriented orthogonal to the imaging plane) positioned at various depths within the aqueous medium simulating optical properties of background tissues, and illuminated using (a) backward OA mode and (b) forward OA mode. OA signals were acquired using a single target, and the images were subsequently created after combining the signals from each individual acquisition. The images are displayed using the standard $8\text{-bit}$ gray-scale palette. The axes are scaled in millimeters.

In forward mode, targets located farther from the probe and closer to the light source produce larger OA signals, as seen in Fig. 2. These signals are received by more elements of the detector array, resulting in better contrast in the constructed image. The targets located closer to the probe appear less bright with forward mode imaging also due to attenuation of excitation light. The images are shown in their unprocessed appearance with arc-shaped artifacts caused by the limited aperture of the array of ultrasound transducers. Our group has developed an iterative algorithm based on maximum angular amplitude probability for removal of arc-shaped artifacts and improve contrast and resolution of optoacoustic images.³³ Figure 2, however, is intended to demonstrate gradual loss of lateral resolution with increasing distance from the ultrasonic probe shaped as a convex arc. The dynamic range of the OA image in forward mode is greater than that in backward mode, and was sufficient to visualize all the tubes [Fig. 2].

3.3.

Computer-Modeled Images

We simulated the OA image of malignant prostate tissue under conditions similar to our in vivo experiment. Figure 3 shows the imaging slice of the absorbed optical energy in the case of the orthogonal OA mode. The lesion is clearly seen as a bright circle implying that it represents a strong OA source. On the other hand, the cross section of the collapsed urethra looks dark, indicating that it is a weak OA source compared to the surrounding prostate tissue. This is further verified by the reconstructed OA image [Fig. 3], which has major features of the model (the edges of illuminated part of the prostate, urethra, and blood-containing lesion) visible. The OA image constructed from the simulated acoustic transients [Fig. 3] strongly resembles the one constructed from in vivo canine prostate [Fig. 3]. The distances of the urethra and lesion from the surface are different between the modeled and experimental images. Furthermore, the portion of the prostate capsule proximal to the probe can be distinguished only in the modeled image. Once more, these differences most likely arise from the fact that tissue compression, which deforms the tissue, is required in the experimental case to achieve acoustic contact.

Fig. 3

Comparison of the modeled OA image with the image acquired in vivo: (a) imaging slice showing the distribution of the absorbed optical energy in a prostate model with spherical malignant lesion, determined by MC simulation; (b) OA image constructed using the simulated acoustic transients and the RBP algorithm; and (c) OA image of the dog prostate obtained in vivo after inducing a blood-rich lesion. The prostate capsule can be delineated in the OA images. The urethra and the lesion can be seen in the OA images as a dark and bright spots, respectively. The absorption difference between the lesion and surrounding tissue results in high contrast of the OA image. The low absorption in the urethra yields low OA signals. On each image, arrows indicate the prostate capsule (PC), urethra (U), and lesion (L). The images are displayed using the standard $8\text{-bit}$ gray-scale palette.

3.4.

In Vivo Images of Prostate Tissue

Figure 4 displays a photograph of the surgically excised prostate sliced through the imaging plane containing the induced lesion, representative of a malignant mass. Upon surgical exposure and without compression, the prostate measured approximately $35\mathrm{mm}$ along the dorsoventral axis and $50\mathrm{mm}$ along the dextrosinistral axis. Figure 4 shows an image acquired with a commercial ultrasound system. The urethra and the needle insertion path appear in the image as dark, hypoechoic regions. The prostate capsule can also be seen. However, the blood-containing lesion itself does not stand out on the image. Figures 4 and 4 display OA images of the prostate before and after the lesion was made. In both OA images, the prostate capsule and the urethra can be delineated. The different distances of those objects from the surface of the ultrasonic probe are likely due to slightly higher compression used to achieve acoustic contact in the case of the induced lesion [Fig. 4]. The blood-filled lesion can be resolved in Fig. 4 as the bright white area that is absent from Fig. 4. The needle insertion path is not visible in both OA images.

Fig. 4

(a) Photograph of the sliced dog prostate showing the presence of the induced lesion with blood in the right lateral lobe, the urethra is visible but contracted after surgical excision; (b) ultrasonic image of the same dog prostate obtained in vivo after the surgery. OA images of the same dog prostate obtained in vivo (c) before and (d) after the lesion was induced. The induced bloody lesion can be seen in (a) and (d). The needle insertion path is visible in (a) and (b). Due to the acoustic mismatch between tissue and air, the prostate capsule can be identified in OA images as a white band. Arrows indicate the prostate capsule (PC), urethra (U), needle insertion path (NIP), and lesion (L). The images are displayed using the standard $8\text{-bit}$ gray-scale palette.