Method for estimating closed-form solutions of the light diffusion equation for turbid media of any boundary shape.

This paper reports a method of estimating an approximate closed-form solution to the light diffusion equation for any type of geometry involving Dirichlet's boundary condition with known source location. It is based on estimating the optimum locations of multiple imaginary point sources to cancel the fluence at the extrapolated boundary by constrained optimization using a genetic algorithm. The mathematical derivation of the problem to approach the optimum solution for the direct-current type of diffuse optical systems is described in detail. Our method is first applied to slab geometry and compared with a truncated series solution. After that, it is applied to hemispherical geometry and compared with Monte Carlo simulation results. The method provides a fast and sufficiently accurate fluence distribution for optical reconstruction.

Utilizing spatial and spectral features of photoacoustic imaging for ovarian cancer detection and diagnosis.

A composite set of ovarian tissue features extracted from photoacoustic spectral data, beam envelope, and co-registered ultrasound and photoacoustic images are used to characterize malignant and normal ovaries using logistic and support vector machine (SVM) classifiers. Normalized power spectra were calculated from the Fourier transform of the photoacoustic beamformed data, from which the spectral slopes and 0-MHz intercepts were extracted. Five features were extracted from the beam envelope and another 10 features were extracted from the photoacoustic images. These 17 features were ranked by their p-values from t -tests on which a filter type of feature selection method was used to determine the optimal feature number for final classification. A total of 169 samples from 19 ex vivo ovaries were randomly distributed into training and testing groups. Both classifiers achieved a minimum value of the mean misclassification error when the seven features with lowest p-values were selected. Using these seven features, the logistic and SVM classifiers obtained sensitivities of 96.39 ± 3.35% and 97.82 ± 2.26%, and specificities of 98.92 ± 1.39% and 100%, respectively, for the training group. For the testing group, logistic and SVM classifiers achieved sensitivities of 92.71 ± 3.55% and 92.64 ± 3.27%, and specificities of 87.52 ± 8.78% and 98.49 ± 2.05%, respectively.

Design of optimal light delivery system for co-registered transvaginal ultrasound and photoacoustic imaging of ovarian tissue.

A hand-held transvaginal probe suitable for co-registered photoacoustic and ultrasound imaging of ovarian tissue was designed and evaluated. The imaging probe consists of an ultrasound transducer and four 1-mm-core multi-mode optical fibers both housed in a custom-made sheath. The probe was optimized for the highest light delivery output and best beam uniformity on tissue surface, by simulating the light fluence and power output for different design parameters. The laser fluence profiles were experimentally measured through chicken breast tissue and calibrated intralipid solution at various imaging depths. Polyethylene tubing filled with rat blood mimicking a blood vessel was successfully imaged up to ∼30 mm depth through porcine vaginal tissue at 750 nm. This imaging depth was achieved with a laser fluence on the tissue surface of 20 mJ/cm(2), which is below the maximum permissible exposure (MPE) of 25 mJ/cm(2) recommended by the American National Standards Institute (ANSI). Furthermore, the probe imaging capability was verified with ex vivo imaging of benign and malignant human ovaries. The co-registered images clearly showed different vasculature distributions on the surface of the benign cyst and the malignant ovary. These results suggest that our imaging system has the clinical potential for in vivo imaging and characterization of ovarian tissues.

Light-emitting diode-based multiwavelength diffuse optical tomography system guided by ultrasound.

Laser diodes are widely used in diffuse optical tomography (DOT) systems but are typically expensive and fragile, while light-emitting diodes (LEDs) are cheaper and are also available in the near-infrared (NIR) range with adequate output power for imaging deeply seated targets. In this study, we introduce a new low-cost DOT system using LEDs of four wavelengths in the NIR spectrum as light sources. The LEDs were modulated at 20 kHz to avoid ambient light. The LEDs were distributed on a hand-held probe and a printed circuit board was mounted at the back of the probe to separately provide switching and driving current to each LED. Ten optical fibers were used to couple the reflected light to 10 parallel photomultiplier tube detectors. A commercial ultrasound system provided simultaneous images of target location and size to guide the image reconstruction. A frequency-domain (FD) laser-diode-based system with ultrasound guidance was also used to compare the results obtained from those of the LED-based system. Results of absorbers embedded in intralipid and inhomogeneous tissue phantoms have demonstrated that the LED-based system provides a comparable quantification accuracy of targets to the FD system and has the potential to image deep targets such as breast lesions.

Interlaced photoacoustic and ultrasound imaging system with real-time coregistration for ovarian tissue characterization.

Coregistered ultrasound (US) and photoacoustic imaging are emerging techniques for mapping the echogenic anatomical structure of tissue and its corresponding optical absorption. We report a 128-channel imaging system with real-time coregistration of the two modalities, which provides up to 15 coregistered frames per second limited by the laser pulse repetition rate. In addition, the system integrates a compact transvaginal imaging probe with a custom-designed fiber optic assembly for in vivo detection and characterization of human ovarian tissue. We present the coregistered US and photoacoustic imaging system structure, the optimal design of the PC interfacing software, and the reconfigurable field programmable gate array operation and optimization. Phantom experiments of system lateral resolution and axial sensitivity evaluation, examples of the real-time scanning of a tumor-bearing mouse, and ex vivo human ovaries studies are demonstrated.

Indocyanine green enhanced co-registered diffuse optical tomography and photoacoustic tomography.

To overcome the intensive light scattering in biological tissue, diffuse optical tomography (DOT) in the near-infrared range for breast lesion detection is usually combined with other imaging modalities, such as ultrasound, x-ray, and magnetic resonance imaging, to provide guidance. However, these guiding imaging modalities may depend on different contrast mechanisms compared to the optical contrast in the DOT. As a result, they cannot provide reliable guidance for DOT because some lesions may not be detectable by a nonoptical modality but may have a high optical contrast. An imaging modality that relies on optical contrast to provide guidance is desirable for DOT. We present a system that combines a frequency-domain DOT and real-time photoacoustic tomography (PAT) systems to detect and characterize deeply seated targets embedded in a turbid medium. To further improve the contrast, the exogenous contrast agent, indocyanine green (ICG), is used. Our experimental results show that the combined system can detect a tumor-mimicking phantom, which is immersed in intralipid solution with the concentrations ranging from 100 to 10 µM and with the dimensions of 0.8 cm × 0.8 cm × 0.6 cm, up to 2.5 cm in depth. Mice experiments also confirmed that the combined system can detect tumors and monitor the ICG uptake and washout in the tumor region. This method can potentially improve the accuracy to detect small breast lesions as well as lesions that are sensitive to background tissue changes, such as the lesions located just above the chest wall.

Photoacoustic imaging enhanced by indocyanine green-conjugated single-wall carbon nanotubes.

A photoacoustic contrast agent that is based on bis-carboxylic acid derivative of indocyanine green (ICG) covalently conjugated to single-wall carbon nanotubes (ICG/SWCNT) is presented. Covalently attaching ICG to the functionalized SWCNT provides a more robust system that delivers much more ICG to the tumor site. The detection sensitivity of the new contrast agent in a mouse tumor model is demonstrated in vivo by our custom-built photoacoustic imaging system. The summation of the photoacoustic tomography (PAT) beam envelope, referred to as the "PAT summation," is used to demonstrate the postinjection light absorption of tumor areas in ICG- and ICG/SWCNT-injected mice. It is shown that ICG is able to provide 33% enhancement at approximately 20 min peak response time with reference to the preinjection PAT level, while ICG/SWCNT provides 128% enhancement at 80 min and even higher enhancement of 196% at the end point of experiments (120 min on average). Additionally, the ICG/SWCNT enhancement was mainly observed at the tumor periphery, which was confirmed by fluorescence images of the tumor samples. This feature is highly valuable in guiding surgeons to assess tumor boundaries and dimensions in vivo and to achieve clean tumor margins to improve surgical resection of tumors.

Characterization of ovarian tissue based on quantitative analysis of photoacoustic microscopy images.

In this paper, human ovarian tissue with malignant and benign features was imaged ex vivo using an optical-resolution photoacoustic microscopy (OR-PAM) system. The feasibility of PAM to differentiate malignant from normal ovarian tissues was explored by comparing the PAM images morphologically. Based on the observed differences between PAM images of normal and malignant ovarian tissues in microvasculature features and distributions, seven features were quantitatively extracted from the PAM images, and a logistic model was used to classify ovaries as normal or malignant. 106 PAM images from 18 ovaries were studied. 57 images were used to train the seven-parameter logistic model, and a specificity of 92.1% and a sensitivity of 89.5% were achieved; 49 images were then tested, and a specificity of 81.3% and a sensitivity of 88.2% were achieved. These preliminary results demonstrate the feasibility of our PAM system in mapping microvasculature networks as well as characterizing the ovarian tissue, and could be extremely valuable in assisting surgeons for in vivo evaluation of ovarian tissue during minimally invasive surgery.

Co-registered pulse-echo/photoacoustic transvaginal probe for real time imaging of ovarian tissue.

We present the design and construction of a prototype imaging probe capable of co-registered pulse-echo ultrasound and photoacoustic (optoacoustic) imaging in real time. The probe consists of 36 fibers of 200 micron core diameter each that are distributed around a commercial transvaginal ultrasound transducer, and housed in a protective shield. Its performance was demonstrated by two sets of experiments. The first set involved imaging of blood flowing through a tube mimicking a blood vessel, the second set involved imaging of human ovaries ex vivo. The results suggest that the system along with the probe has great potential for imaging and characterizing of ovarian tissue in vivo.

Recognition algorithm for assisting ovarian cancer diagnosis from coregistered ultrasound and photoacoustic images: ex vivo study.

Unique features and the underlining hypotheses of how these features may relate to the tumor physiology in coregistered ultrasound and photoacoustic images of ex vivo ovarian tissue are introduced. The images were first compressed with wavelet transform. The mean Radon transform of photoacoustic images was then computed and fitted with a Gaussian function to find the centroid of a suspicious area for shift-invariant recognition process. Twenty-four features were extracted from a training set by several methods, including Fourier transform, image statistics, and different composite filters. The features were chosen from more than 400 training images obtained from 33 ex vivo ovaries of 24 patients, and used to train three classifiers, including generalized linear model, neural network, and support vector machine (SVM). The SVM achieved the best training performance and was able to exclusively separate cancerous from non-cancerous cases with 100% sensitivity and specificity. At the end, the classifiers were used to test 95 new images obtained from 37 ovaries of 20 additional patients. The SVM classifier achieved 76.92% sensitivity and 95.12% specificity. Furthermore, if we assume that recognizing one image as a cancer is sufficient to consider an ovary as malignant, the SVM classifier achieves 100% sensitivity and 87.88% specificity.

FPGA-based reconfigurable processor for ultrafast interlaced ultrasound and photoacoustic imaging.

In this paper, we report, to the best of our knowledge, a unique field-programmable gate array (FPGA)-based reconfigurable processor for real-time interlaced co-registered ultrasound and photoacoustic imaging and its application in imaging tumor dynamic response. The FPGA is used to control, acquire, store, delay-and-sum, and transfer the data for real-time co-registered imaging. The FPGA controls the ultrasound transmission and ultrasound and photoacoustic data acquisition process of a customized 16-channel module that contains all of the necessary analog and digital circuits. The 16-channel module is one of multiple modules plugged into a motherboard; their beamformed outputs are made available for a digital signal processor (DSP) to access using an external memory interface (EMIF). The FPGA performs a key role through ultrafast reconfiguration and adaptation of its structure to allow real-time switching between the two imaging modes, including transmission control, laser synchronization, internal memory structure, beamforming, and EMIF structure and memory size. It performs another role by parallel accessing of internal memories and multi-thread processing to reduce the transfer of data and the processing load on the DSP. Furthermore, because the laser will be pulsing even during ultrasound pulse-echo acquisition, the FPGA ensures that the laser pulses are far enough from the pulse-echo acquisitions by appropriate time-division multiplexing (TDM). A co-registered ultrasound and photoacoustic imaging system consisting of four FPGA modules (64-channels) is constructed, and its performance is demonstrated using phantom targets and in vivo mouse tumor models.

Target detection and quantification using a hybrid hand-held diffuse optical tomography and photoacoustic tomography system.

We present a photoacoustic tomography-guided diffuse optical tomography approach using a hand-held probe for detection and characterization of deeply-seated targets embedded in a turbid medium. Diffuse optical tomography guided by coregistered ultrasound, MRI, and x ray has demonstrated a great clinical potential to overcome lesion location uncertainty and to improve light quantification accuracy. However, due to the different contrast mechanisms, some lesions may not be detectable by a nonoptical modality but yet have high optical contrast. Photoacoustic tomography utilizes a short-pulsed laser beam to diffusively penetrate into tissue. Upon absorption of the light by the target, photoacoustic waves are generated and used to reconstruct, at ultrasound resolution, the optical absorption distribution that reveals optical contrast. However, the robustness of optical property quantification of targets by photoacoustic tomography is complicated because of the wide range of ultrasound transducer sensitivity, the orientation and shape of the targets relative to the ultrasound array, and the uniformity of the laser beam. We show in this paper that the relative optical absorption map provided by photoacoustic tomography can potentially guide the diffuse optical tomography to accurately reconstruct target absorption maps.