Characterization of bone microstructure using photoacoustic spectrum analysis

Adaptively multi-scale microstructure characterization of cancellous bone via Photoacoustic signal decomposition

Osteoporosis is a systemic disease with a high incidence in the elderly and seriously affects the quality of life of patients. Photoacoustic (PA) technology, which combines the advantages of light and ultrasound, can provide information about the physiological structure and chemical information of biological tissues in a non-invasive and non-radiative way. Due to the complex structural characteristics of bone tissue, PA signals generated by bone tissue are non-stationary and nonlinear. However, conventional PA signal processing methods are not effective for non-stationary signal processing. In this study, an empirical mode decomposition (EMD)-based Hilbert-Huang transform (HHT) PA signal analysis method, called HHT PA signal analysis (HPSA), was developed to assess the microstructure information of bone tissue, which is closely related to bone health. The feasibility of the HPSA method in bone health assessment was proven by numerical simulation and experimental studies on animal samples with different bone volume/total volume (BV/TV) and bone mineral densities. First, based on adaptive EMD, the different modes correlated with multi-scale information were mined from the PA signal, the correlations between different intrinsic mode function (IMF) modes and BV/TVs were analyzed, and the optimal mode for more efficient PA time-frequency analysis was selected. Second, multi-wavelength HPSA was used to assess the changes in the chemical components of the bone tissue. The results demonstrate that the HPSA method can distinguish bones with different BV/TVs and microstructure conditions adaptively with high efficiency. They further emphasize the potential of PA techniques in characterizing biological tissues in bones for early and rapid detection of bone diseases.

Development of a semi-anthropomorphic photoacoustic calcaneus phantom based on nano computed tomography and stereolithography 3D printing

Osteoporosis is a major public health threat with significant physical, psychosocial, and financial consequences. The calcaneus bone has been used as a measurement site for risk prediction of osteoporosis by noninvasive quantitative ultrasound (QUS). By adding optical contrast to QUS, our previous studies indicate that a combination of photoacoustic (PA) and QUS, that is, PAQUS, provides a novel opportunity to assess the health of human calcaneus. Calibration of the PAQUS system is crucial to realize quantitative and repeatable measurements of the calcaneus. Therefore, a phantom which simulates the optical, ultrasound, and architectural properties of the human calcaneus, for PAQUS system calibration, is required. Additionally, a controllable phantom offers researchers a versatile framework for developing versatile structures, allowing more controlled assessment of how varying bone structures cause defined alterations in PA and QUS signals. In this work, we present the first semi-anthropomorphic calcaneus phantom for PAQUS. The phantom was developed based on nano computed-tomography (nano-CT) and stereolithography 3D printing, aiming to maximize accuracy in the approximation of both trabecular and cortical bone microstructures. Compared with the original digital input calcaneus model from a human cadaveric donor, the printed model achieved accuracies of 71.15% in total structure and 87.21% in bone volume fraction. Inorganic materials including synthetic blood, mineral oil, intralipid, and agar gel were used to model the substitutes of bone marrow and soft tissue, filling and covering the calcaneus phantom. The ultrasound and optical properties of this phantom were measured, and the results were consistent with those measured by a commercialized device and from previous in vivo studies. In addition, a short-term stability test was conducted for this phantom, demonstrating that the optical and ultrasound properties of the phantom were stable without significant variation over 1 month. This semi-anthropomorphic calcaneus phantom shows structural, ultrasound, and optical properties similar to those from a human calcaneus in vivo and, thereby, can serve as an effective source for equipment calibration and the comprehensive study of human patients.

Theoretical and experimental study of attenuation in cancellous bone

Significance

Photoacoustic (PA) technology shows great potential for bone assessment. However, the PA signals in cancellous bone are complex due to its complex composition and porous structure, making such signals challenging to apply directly in bone analysis.

Aim

We introduce a photoacoustic differential attenuation spectrum (PA-DAS) method to separate the contribution of the acoustic propagation path to the PA signal from that of the source, and theoretically and experimentally investigate the propagation attenuation characteristics of cancellous bone.

Approach

We modified Biot's theory by accounting for the high frequency and viscosity. In parallel with the rabbit osteoporosis model, we build an experimental PA-DAS system featuring an eccentric excitation differential detection mechanism. Moreover, we extract a PA-DAS quantization parameter-slope-to quantify the attenuation of high- and low-frequency components.

Results

The results show that the porosity of cancellous bone can be evaluated by fast longitude wave attenuation at different frequencies and the PA-DAS slope of the osteoporotic group is significantly lower compared with the normal group (**p < 0.01 ).

Conclusions

Findings demonstrate that PA-DAS effectively differentiates osteoporotic bone from healthy bone, facilitating quantitative assessment of bone mineral density, and osteoporosis diagnosis.

Photoacoustic Imaging and Characterization of Bone in Medicine: Overview, Applications, and Outlook

Photoacoustic techniques have shown promise in identifying molecular changes in bone tissue and visualizing tissue microstructure. This capability represents significant advantages over gold standards (i.e., dual-energy X-ray absorptiometry) for bone evaluation without requiring ionizing radiation. Instead, photoacoustic imaging uses light to penetrate through bone, followed by acoustic pressure generation, resulting in highly sensitive optical absorption contrast in deep biological tissues. This review covers multiple bone-related photoacoustic imaging contributions to clinical applications, spanning bone cancer, joint pathologies, spinal disorders, osteoporosis, bone-related surgical guidance, consolidation monitoring, and transsphenoidal and transcranial imaging. We also present a summary of photoacoustic-based techniques for characterizing biomechanical properties of bone, including temperature, guided waves, spectral parameters, and spectroscopy. We conclude with a future outlook based on the current state of technological developments, recent achievements, and possible new directions.

Identification of different types of tumors based on photoacoustic spectral analysis: preclinical feasibility studies on skin tumors

Significance

Collagen and lipid are important components of tumor microenvironments (TME) and participates in tumor development and invasion. It has been reported that collagen and lipid can be used as a hallmark to diagnosis and differentiate tumors.

Aim

We aim to introduce photoacoustic spectral analysis (PASA) method that can provide both the content and structure distribution of endogenous chromophores in biological tissues to characterize the tumor-related features for identifying different types of tumors.

Approach

Ex vivo human tissues with suspected squamous cell carcinoma (SCC), suspected basal cell carcinoma (BCC), and normal tissue were used in this study. The relative lipid and collagen contents in the TME were assessed based on the PASA parameters and compared with histology. Support vector machine (SVM), one of the simplest machine learning tools, was applied for automatic skin cancer type detection.

Results

The PASA results showed that the lipid and collagen levels of the tumors were significantly lower than those of the normal tissue, and there was a statistical difference between SCC and BCC (p < 0.05 ), consistent with the histopathological results. The SVM-based categorization achieved diagnostic accuracies of 91.7% (normal), 93.3% (SCC), and 91.7% (BCC).

Conclusions

We verified the potential use of collagen and lipid in the TME as biomarkers of tumor diversity and achieved accurate tumor classification based on the collagen and lipid content using PASA. The proposed method provides a new way to diagnose tumors.

Biomedical Application of Photoacoustics: A Plethora of Opportunities

The photoacoustic (PA) technique is a non-invasive, non-ionizing hybrid technique that exploits laser irradiation for sample excitation and acquires an ultrasound signal generated due to thermoelastic expansion of the sample. Being a hybrid technique, PA possesses the inherent advantages of conventional optical (high resolution) and ultrasonic (high depth of penetration in biological tissue) techniques and eliminates some of the major limitations of these conventional techniques. Hence, PA has been employed for different biomedical applications. In this review, we first discuss the basic physics of PA. Then, we discuss different aspects of PA techniques, which includes PA imaging and also PA frequency spectral analysis. The theory of PA signal generation, detection and analysis is also detailed in this work. Later, we also discuss the major biomedical application area of PA technique.

Myocardial infarct border demarcation by dual-wavelength photoacoustic spectral analysis

Myocardial infarction (MI) is a major cause of morbidity and mortality worldwide. Modern therapeutic strategies targeting the infarct border area have been shown to benefit overall cardiac function after MI. However, there is no non-invasive diagnostic technique to precisely demarcate the MI boundary till to now. In this study, the feasibility of demarcating the MI border using dual-wavelength photoacoustic spectral analysis (DWPASA) was investigated. To quantify specific molecular characteristics before and after MI, "the ratio of the areas of the power spectral densities (R APSD)" was computed from the DWPASA results. Compared to the normal tissue, MI tissue was shown to contain more collagen, resulting in higher R APSD values (p < 0.001). Cross-sectional MI lengths and the MI area border demarcated in two dimensions by DWPASA were in substantial agreement with Masson staining (ICC = 0.76, p < 0.001, IoU = 0.72). R APSD has been proved that can be used as an indicator of disease evolution to distinguish normal and pathological tissues. These findings indicate that the DWPASA method may offer a new diagnostic solution for determining MI borders.

Bone hydration: How we can evaluate it, what can it tell us, and is it an effective therapeutic target?

Water constitutes roughly a quarter of the cortical bone by volume yet can greatly influence mechanical properties and tissue quality. There is a growing appreciation for how water can dynamically change due to age, disease, and treatment. A key emerging area related to bone mechanical and tissue properties lies in differentiating the role of water in its four different compartments, including free/pore water, water loosely bound at the collagen/mineral interfaces, water tightly bound within collagen triple helices, and structural water within the mineral. This review summarizes our current knowledge of bone water across the four functional compartments and discusses how alterations in each compartment relate to mechanical changes. It provides an overview on the advent of- and improvements to- imaging and spectroscopic techniques able to probe nano-and molecular scales of bone water. These technical advances have led to an emerging understanding of how bone water changes in various conditions, of which aging, chronic kidney disease, diabetes, osteoporosis, and osteogenesis imperfecta are reviewed. Finally, it summarizes work focused on therapeutically targeting water to improve mechanical properties.

Characterization of multi-biomarkers for bone health assessment based on photoacoustic physicochemical analysis method

Photoacoustic (PA) techniques are potential alternatives to histopathology. The physicochemical spectrogram (PCS) generated by the PA measurement at multiple wavelengths can presents the morphology and chemical composition target at multi-biomarkers simultaneously. In this work, via multi-wavelength PA measurements performed on rabbit bone models, we investigated the feasibility of using PCSs for bone health assessment. A comprehensive analysis of the PCSs, termed PA physicochemical analysis (PAPCA), was conducted. The "slope" and "relative content" were used as the PAPCA-quantified parameters to characterize the changes in the physical and chemical properties of bone tissue, respectively. The findings are consistent well with the gold-standard imaging results. It demonstrated that the PAPCA can be used to characterize both the microstructure and content of multi-biomarkers which highly related with bone health. Considering the PA technique is noninvasive and radiation-free, it has great potential in the implementation and monitoring of bone diseases progression.

Feasibility of Quantitative Tissue Characterization Using Novel Parameters Extracted From Photoacoustic Power Spectrum Considering Multiple Absorbers

Frequency domain analysis of radio frequency signal is performed to differentiate between different tissue categories in terms of spectral parameters. However, due to complex relationship between the absorber size and spectral parameters, they cannot be used for quantitative tissue characterization. In an earlier study, we showed that using linear relationship between absorber size and two new spectral parameters namely number of lobes and average lobe width, absorber size can be successfully recovered from photoacoustic signal generated by single absorber. As actual biological tissue contains multiple absorbers, in this study we extended the application of these two new spectral parameters for computing absorber size from signals generated by multiple PA absorbers. We revisited our analytical model to establish two new linear relationships between the absorber radius and number of lobes as well as average lobe width considering multiple absorbers with bandlimited acquisition. A simulation study was performed to validate these linear relationships. A retrospective ex vivo study, in which the spectral parameters were computed using multiwavelength photoacoustic signals, was performed with freshly exercised thyroid specimens from 38 actual human patients undergoing thyroidectomy after having a diagnosis of suspected thyroid lesions. From statistical analysis it is shown that both the parameters were significantly different between malignant and non-malignant thyroid and malignant and normal thyroid tissue. Performance of the supervised classification with the computed spectral parameters showed that the extracted parameters could be successfully used to differentiate malignant thyroid tissue from normal thyroid tissue with reasonable degree of accuracy.

Detection of collagen by multi-wavelength photoacoustic analysis as a biomarker for bone health assessment

Collagen is an important biomarker of osteoporosis progression. Noninvasive, multispectral, photoacoustic (PA) techniques use pulsed laser light to induce PA signals to facilitate the visualization of chemical components that are strongly related to tissue health. In this study, the feasibility of multi-wavelength PA (MWPA) measurement of the collagen in bone, using the wavelength range of 1300-1800 nm, was investigated. First, the feasibility of this approach for detecting the collagen content of bone was demonstrated by means of numerical simulation. Then, ex vivo experiments were conducted on both animal and human bone specimens with different bone densities using the MWPA method. The relative collagen content was extracted and compared with the results of micro-computed tomography (micro-CT) and histology. The results showed that the "relative collagen content" parameter obtained using the MWPA approach correlated well with the bone volume ratio obtained from micro-CT images and histological analysis results. This study highlights the potential of the proposed PA technique for determining the collagen content of bones as a biomarker for bone health assessment.

The feasibility study of the transmission mode photoacoustic measurement of human calcaneus bone in vivo

The photoacoustic (PA) technique is uniquely positioned for biomedical applications primarily due to its ability to visualize optical absorption contrast in deep tissue at ultrasound resolution. In this work, via both three-dimensional (3D) numerical simulations and in vivo experiments on human subjects, we investigated the possibility of PA measurement of human calcaneus bones in vivo in a non-invasive manner, as well as its feasibility to differentiate osteoporosis patients from normal subjects. The results from the simulations and the experiments both demonstrated that, when one side of the heel is illuminated by laser with light fluence under the ANSI safety limit, the PA signal generated in the human calcaneus bone can be detected by an ultrasonic transducer at the other side of the heel (i.e. transmission mode). Quantitative power spectral analyses of the calcaneus bone PA signals were also conducted, demonstrating that the microarchitectural changes in calcaneus bone due to osteoporosis can be detected, as reflected by enhanced high frequency components in detected PA bone signal. Further statistical analysis of the experimental results from 10 osteoporosis patients and 10 healthy volunteers showed that the weighted frequency as a quantified PA spectral parameter can differentiate the two subject groups with statistical significance.

Prostate cancer identification via photoacoustic spectroscopy and machine learning

Photoacoustic spectroscopy can generate abundant chemical and physical information about biological tissues. However, this abundance of information makes it difficult to compare these tissues directly. Data mining methods can circumvent this problem. We describe the application of machine-learning methods (including unsupervised hierarchical clustering and supervised classification) to the diagnosis of prostate cancer by photoacoustic spectrum analysis. We focus on the content and distribution of hemoglobin, collagen, and lipids, because these molecules change during the development of prostate cancer. A higher correlation among the ultrasonic power spectra of these chemical components is observed in cancerous than in normal tissues, indicating that the microstructural distributions in cancerous tissues are more consistent. Different classifiers applied in cancer-tissue diagnoses achieved an accuracy of 82 % (better than that of standard clinical methods). The technique thus exhibits great potential for painless early diagnosis of aggressive prostate cancer.

Optoacoustic imaging in endocrinology and metabolism

Imaging is an essential tool in research, diagnostics and the management of endocrine disorders. Ultrasonography, nuclear medicine techniques, MRI, CT and optical methods are already used for applications in endocrinology. Optoacoustic imaging, also termed photoacoustic imaging, is emerging as a method for visualizing endocrine physiology and disease at different scales of detail: microscopic, mesoscopic and macroscopic. Optoacoustic contrast arises from endogenous light absorbers, such as oxygenated and deoxygenated haemoglobin, lipids and water, or exogenous contrast agents, and reveals tissue vasculature, perfusion, oxygenation, metabolic activity and inflammation. The development of high-performance optoacoustic scanners for use in humans has given rise to a variety of clinical investigations, which complement the use of the technology in preclinical research. Here, we review key progress with optoacoustic imaging technology as it relates to applications in endocrinology; for example, to visualize thyroid morphology and function, and the microvasculature in diabetes mellitus or adipose tissue metabolism, with particular focus on multispectral optoacoustic tomography and raster-scan optoacoustic mesoscopy. We explain the merits of optoacoustic microscopy and focus on mid-infrared optoacoustic microscopy, which enables label-free imaging of metabolites in cells and tissues. We showcase current optoacoustic applications within endocrinology and discuss the potential of these technologies to advance research and clinical practice.

Photoacoustic power azimuth spectrum for microvascular evaluation

The tubular structures and dendritic distributions of blood vessels emit anisotropic photoacoustic (PA) signals with different intensities and frequency components at different angles. Therefore, spectral analysis of PA signals from a single angle cannot accurately determine the physical characteristics of microvessels. This study investigated the feasibility of using the PA power azimuth spectrum (PA-PAS) method to evaluate microvessel structures. We mapped the acoustic power spectrum of the PA signals along the azimuth direction. Based on a frequency-domain analysis of the broadband PA signal, we calculated the spectral parameter power-weighted mean frequency (PWMF). The results demonstrate that the PA signal information of the microvessel is mainly concentrated in the direction of its width. In addition, the PWMF decreases linearly with the microvascular size. The experimental findings exhibit good agreement with the simulation results, thus demonstrating that this approach can effectively differentiate the sizes of microvessels.

Wavelet transform-based photoacoustic time-frequency spectral analysis for bone assessment

In this study, we investigated the feasibility of using photoacoustic time-frequency spectral analysis (PA-TFSA) for evaluating the bone mineral density (BMD) and bone structure. Simulations and ex vivo experiments on bone samples with different BMDs and mean trabecular thickness (MTT) were conducted. All photoacoustic signals were processed using the wavelet transform-based PA-TFSA. The power-weighted mean frequency (PWMF) was evaluated to obtain the main frequency component at different times. The y-intercept, midband-fit, and slope of the linearly fitted curve of the PWMF over time were also quantified. The results show that the osteoporotic bone samples with lower BMD and thinner MTT have higher frequency components and lower acoustic frequency attenuation over time, thus higher y-intercept, midband-fit, and slope. The midband-fit and slope were found to be sensitive to the BMD; therefore, both parameters could be used to distinguish between osteoporotic and normal bones (p < 0.05).

Role of blood oxygenation saturation in ovarian cancer diagnosis using multi-spectral photoacoustic tomography

In photoacoustic tomography (PAT), a tunable laser typically illuminates the tissue at multiple wavelengths, and the received photoacoustic waves are used to form functional images of relative total haemoglobin (rHbT) and blood oxygenation saturation (%sO2 ). Due to measurement errors, the estimation of these parameters can be challenging, especially in clinical studies. In this study, we use a multi-pixel method to smooth the measurements before calculating rHbT and %sO2 . We first perform phantom studies using blood tubes of calibrated %sO2 to evaluate the accuracy of our %sO2 estimation. We conclude by presenting diagnostic results from PAT of 33 patients with 51 ovarian masses imaged by our co-registered PAT and ultrasound system. The ovarian masses were divided into malignant and benign/normal groups. Functional maps of rHbT and %sO2 and their histograms as well as spectral features were calculated using the PAT data from all ovaries in these two groups. Support vector machine models were trained on different combinations of the significant features. The area under ROC (AUC) of 0.93 (0.95%CI: 0.90-0.96) on the testing data set was achieved by combining mean %sO2 , a spectral feature, and the score of the study radiologist.

Technical considerations in the Verasonics research ultrasound platform for developing a photoacoustic imaging system

Photoacoustic imaging (PAI) is an emerging functional and molecular imaging technology that has attracted much attention in the past decade. Recently, many researchers have used the vantage system from Verasonics for simultaneous ultrasound (US) and photoacoustic (PA) imaging. This was the motivation to write on the details of US/PA imaging system implementation and characterization using Verasonics platform. We have discussed the experimental considerations for linear array based PAI due to its popularity, simple setup, and high potential for clinical translatability. Specifically, we describe the strategies of US/PA imaging system setup, signal generation, amplification, data processing and study the system performance.

Functional Photoacoustic and Ultrasonic Assessment of Osteoporosis: A Clinical Feasibility Study

Objective and Impact Statement. To study the feasibility of combined functional photoacoustic (PA) and quantitative ultrasound (US) for diagnosis of osteoporosis in vivo based on the detection of chemical and microarchitecture (BMA) information in calcaneus bone. Introduction. Clinically available X-ray or US technologies for the diagnosis of osteoporosis do not report important parameters such as chemical information and BMA. With unique advantages, including good sensitivity to molecular and metabolic properties, PA bone assessment techniques hold a great potential for clinical translation. Methods. By performing multiwavelength PA measurements, the chemical information in the human calcaneus bone, including mineral, lipid, oxygenated-hemoglobin, and deoxygenated-hemoglobin, were assessed. In parallel, by performing PA spectrum analysis, the BMA as an important bone physical property was quantified. An unpaired t -test and a two-way ANOVA test were conducted to compare the outcomes from the two subject groups. Results. Multiwavelength PA measurement is capable of assessing the relative contents of several chemical components in the trabecular bone in vivo, including both minerals and organic materials such as oxygenated-hemoglobin, deoxygenated-hemoglobin, and lipid, which are relevant to metabolic activities and bone health. In addition, PA measurements of BMA show good correlations (R 2 up to 0.65) with DEXA. Both the chemical and microarchitectural measurements from PA techniques can differentiate the two subject groups. Conclusion. The results from this initial clinical study suggest that PA techniques, by providing additional chemical and microarchitecture information relevant to bone health, may lead to accurate and early diagnosis, as well as sensitive monitoring of the treatment of osteoporosis.

Multiple information extracted from photoacoustic radio-frequency signal and the application on tissue classification

Photoacoustic imaging is a hybrid biomedical imaging technique, combining rich optical contrasts and good acoustic resolution in deep tissues. As a noninvasive and nonionized imaging method, photoacoustic imaging has shown great potentials in biomedicine in the past decade. In this review, we give a brief introduction of the physical principle and three major implementations of photoacoustic imaging. Then, we present pictures of some recent progress about the extraction of new imaging parameters from photoacoustic radio-frequency signals. These parameters are highly associated with the tissue microstructure characteristics, including characteristic size, number density, and elasticity. This information could give us insight into various properties of tissue in-depth and be applied to tissue classification for basic research and clinical settings.

Towards Clinical Translation of LED-Based Photoacoustic Imaging: A Review

Photoacoustic imaging, with the capability to provide simultaneous structural, functional, and molecular information, is one of the fastest growing biomedical imaging modalities of recent times. As a hybrid modality, it not only provides greater penetration depth than the purely optical imaging techniques, but also provides optical contrast of molecular components in the living tissue. Conventionally, photoacoustic imaging systems utilize bulky and expensive class IV lasers, which is one of the key factors hindering the clinical translation of this promising modality. Use of LEDs which are portable and affordable offers a unique opportunity to accelerate the clinical translation of photoacoustics. In this paper, we first review the development history of LED as an illumination source in biomedical photoacoustic imaging. Key developments in this area, from point-source measurements to development of high-power LED arrays, are briefly discussed. Finally, we thoroughly review multiple phantom, ex-vivo, animal in-vivo, human in-vivo, and clinical pilot studies and demonstrate the unprecedented preclinical and clinical potential of LED-based photoacoustic imaging.

Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments

Solid tumors are typically supplied nutrients by a network of irregular blood vessels. By targeting these vascular networks, it might be possible to hinder cancer growth and metastasis. Vascular disrupting agents induce intertumoral hemorrhaging, making photoacoustic (PA) imaging well positioned to detect bleeding due to its sensitivity to hemoglobin and its various states. We introduce a fractal-based numerical model of intertumoral hemorrhaging to simulate the PA signals from disrupted tumor blood vessels. The fractal model uses bifurcated cylinders to represent vascular trees. To mimic bleeding from blood vessels, hemoglobin diffusion from microvessels was simulated. In the simulations, the PA signals were detected by a linear array transducer (30 MHz center frequency) of four different vascular trees. The power spectrum of each beamformed PA signal was computed and fitted to a straight line within the −6-dB bandwidth of the receiving transducer. The spectral slope and midband fit (MBF) based on the fit decreased by 0.11  dB  /  MHz and 2.12 dB, respectively, 1 h post bleeding, while the y-intercept increased by 1.21 dB. The results suggest that spectral PA analysis can be used to measure changes in the concentration and spatial distribution of hemoglobin in tissue without the need to resolve individual vessels. The simulations support the feasibility of using PA imaging and spectral analysis in cancer treatment monitoring by detecting microvessel disruption.

Assessing the development and treatment of rheumatoid arthritis using multiparametric photoacoustic and ultrasound imaging

Rheumatoid arthritis (RA), characterized by polyarthritis, is a chronic, systemic and inflammatory autoimmune disease. In this study, we developed a dual-modality multiparametric photoacoustic and ultrasound imaging technique, and successfully derived multiple parameters such as relative concentration of total hemoglobin (C_HbT ), ratio of angiogenesis, joint size and area of synovia to assess the development and treatment of RA. We established a model of adjuvant arthritis using a total number of 15 rats and randomly divided them into three groups: (a) targeted group in which the rats received targeted antirheumatic drugs; (b) nontargeted group in which the rats were treated with nontargeted antirheumatic drugs; (c) control group. We longitudinally monitored the joints of the rats in all three groups for up to 20 days and carried out quantitative analysis to evaluate the development and treatment of RA based on the derived parameters. The results suggest that the proposed dual-modality imaging technique is able to assess the effectiveness of the RA treatment using quantitative hemodynamic and morphological parameters. To show the clinical feasibility of this technique, we performed in vivo joint studies of health volunteers to visualize both structures and inside hemodynamics of the distal interphalangeal joint.

Quantification of number density of random microstructure from a photoacoustic signal by using Nakagami statistics

Tissue microstructure characterization is a valuable tool in diagnosis and staging of many diseases. In this study, we propose a photoacoustic Nakagami statistics method to noninvasively evaluate the number density of random microstructure. The Nakagami parameters are acquired by fitting the photoacoustic signal envelope histogram with Nakagami distribution function. Theoretical calculations and phantom experiments demonstrate that the Nakagami shape parameter is only related to the number density of random microstructure and monotonically increases with the number density. Based on this finding, we propose a photoacoustic tomography modality with the imaging contrast of the Nakagami shape parameter. Experiments show that the proposed method can provide more comprehensive and accurate description of tissue microstructure.

Classification of human ovarian cancer using functional, spectral, and imaging features obtained from in vivo photoacoustic imaging

We report in this pilot study the diagnostic results of in vivo imaging of patients with ovarian lesions, using a co-registered photoacoustic and ultrasound (PAT/US) system. A total of 39 ovaries from 24 patients were imaged in vivo. PAT functional features, i.e., blood oxygen saturation (sO2) and relative total hemoglobin (rHbT), PAT image features, and PAT spectral features within a region of interest (ROI) in each ovarian tissue were extracted. To select the significant features, a t-test on each feature was performed, and the independent predictors were determined by evaluating correlation between each pair of predictors. To classify the ovarian lesions, we employed a generalized linear model (GLM) and a support vector machine (SVM). We used these classifiers first to distinguish benign/normal lesions from ovaries with invasive epithelial tumors and then to separate normal/benign lesions from all types of ovarian tumors. We developed classifiers once by inclusion of PAT functional features to assess the best diagnostic performance of the classifiers when multiple wavelengths data are available. Second time, we excluded the PAT functional features from the features set to evaluate the best diagnostic performance if only a single wavelength is available. Our results show that using functional features improves the classification performance, especially for distinguishing normal/benign ovarian lesions from all types of tumors. In this case, an area under ROC curve (AUC) of 0.92, 0.93 of testing data was achieved using a GLM and SVM classifier when functional features were included in the feature set while excluding these features resulted in an AUC of 0.89, 0.92, respectively.

Review of Photoacoustic Imaging for Imaging-Guided Spinal Surgery

This review introduces the current technique of photoacoustic imaging as it is applied in imaging-guided surgery (IGS), which provides the surgeon with image visualization and analysis capabilities during surgery. Numerous imaging techniques have been developed to help surgeons perform complex operations more safely and quickly. Although surgeons typically use these kinds of images to visualize targets hidden by bone and other tissues, it is nonetheless more difficult to perform surgery with static reference images (e.g., computed tomography scans and magnetic resonance images) of internal structures. Photoacoustic imaging could enable real-time visualization of regions of interest during surgery. Several researchers have shown that photoacoustic imaging has potential for the noninvasive diagnosis of various types of tissues, including bone. Previous studies of the surgical application of photoacoustic imaging have focused on cancer surgery, but photoacoustic imaging has also recently attracted interest for spinal surgery, because it could be useful for avoiding pedicle breaches and for choosing an appropriate starting point before drilling or pedicle probe insertion. This review describes the current instruments and clinical applications of photoacoustic imaging. Its primary objective is to provide a comprehensive overview of photoacoustic IGS in spinal surgery.

Adipocyte Size Evaluation Based on Photoacoustic Spectral Analysis Combined with Deep Learning Method

Adipocyte size, i.e., the cell area of adipose tissue, is correlated directly with metabolic disease risk in obese humans. This study proposes an approach of processing the photoacoustic (PA) signal power spectrum using a deep learning method to evaluate adipocyte size in human adipose tissue. This approach has the potential to provide noninvasive assessment of adipose tissue dysfunction, replacing traditional invasive methods of evaluating adipose tissue via biopsy and histopathology. A deep neural network with fully connected layers was used to fit the relationship between PA spectrum and average adipocyte size. Experiments on human adipose tissue specimens were performed, and the optimal parameters of the deep learning method were applied to establish the relationship between the PA spectrum and average adipocyte size. By studying different spectral bands in the entire spectral range using the deep network, a spectral band mostly sensitive to the adipocyte size was identified. A method of combining all frequency components of PA spectrum was tested to achieve a more accurate evaluation.

Photoacoustic imaging of a human vertebra: implications for guiding spinal fusion surgeries

It is well known that there are structural differences between cortical and cancellous bone. However, spinal surgeons currently have no reliable method to non-invasively determine these differences in real-time when choosing the optimal starting point and trajectory to insert pedicle screws and avoid surgical complications associated with breached or weakened bone. This paper explores 3D photoacoustic imaging of a human vertebra to noninvasively differentiate cortical from cancellous bone for this surgical task. We observed that signals from the cortical bone tend to appear as compact, high-amplitude signals, while signals from the cancellous bone have lower amplitudes and are more diffuse. In addition, we discovered that the location of the light source for photoacoustic imaging is a critical parameter that can be adjusted to non-invasively determine the optimal entry point into the pedicle. Once inside the pedicle, statistically significant differences in the contrast and SNR of signals originating from the cancellous core of the pedicle (when compared to signals originating from the surrounding cortical bone) were obtained with laser energies of 0.23-2.08 mJ (p  <  0.05). Similar quantitative differences were observed with an energy of 1.57 mJ at distances  ⩾6 mm from the cortical bone of the pedicle. These quantifiable differences between cortical and cancellous bone (when imaging with an ultrasound probe in direct contact with each bone type) can potentially be used to ensure an optimal trajectory during surgery. Our results are promising for the introduction and development of photoacoustic imaging systems to overcome a wide range of longstanding challenges with spinal surgeries, including challenges with the occurrence of bone breaches due to misplaced pedicle screws.

Frequency Domain Analysis of Multiwavelength Photoacoustic Signals for Differentiating Among Malignant, Benign, and Normal Thyroids in an Ex Vivo Study With Human Thyroids

OBJECTIVES

This study investigated the capability of spectral parameters, extracted by frequency domain analysis of photoacoustic signals, to differentiate among malignant, benign, and normal thyroid tissue.

METHODS

We acquired multiwavelength photoacoustic images of freshly excised thyroid specimens collected from 50 patients who underwent thyroidectomy after having a diagnosis of suspected thyroid lesions. A thyroid cytopathologist marked histologic slides of each tissue specimen. These marked slides were used as ground truth to identify the regions of interest (ROIs) corresponding to malignant, benign, and normal thyroid tissue. Three spectral parameters: namely, slope, midband fit, and intercept, were extracted from photoacoustic signals corresponding to different ROIs.

RESULTS

Spectral parameters were extracted from a total of total of 65 ROIs. According to the ground truth, 12 of 65 ROIs belonged to malignant thyroids; 28 of 65 ROIs belonged to benign thyroids; and 25 of 65 ROIs belonged to normal thyroids. Besides slope, the other 2 spectral parameters and grayscale photoacoustic image pixel values were found to be significantly different (P < .05) between malignant and normal thyroids. Between benign and normal thyroids, all 3 spectral parameters and photoacoustic pixel values were significantly different (P < .05).

CONCLUSIONS

Preliminary results of our ex vivo human thyroid study show that the spectral parameters extracted from radiofrequency photoacoustic signals as well as the pixel values of 2-dimensional photoacoustic images can be used for differentiating among malignant, benign, and normal thyroid tissue.

Noninvasive photoacoustic identification and imaging of gut microbes

Homeostasis of the gut microbiota is indispensable for various physiological functions. Its composition and activity co-develop with the host, and especially associate with human colorectal cancer. However, current composition identification methods are complicated and not timely without spatial distribution information. In this Letter, we explored the photoacoustic imaging (PAI) technique to characterize the composition and quantify the proportions of the gut microbes after optical probe labeling. Our experimental results demonstrated that PAI has the potential to identify different gut bacterial species on the spot.