Photoacoustic Spectral Analysis Research Articles

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

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. 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. 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. 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 (), consistent with the histopathological results. The SVM-based categorization achieved diagnostic accuracies of 91.7% (normal), 93.3% (SCC), and 91.7% (BCC). 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.

Fabrication of a translational photoacoustic needle sensing probe for interstitial photoacoustic spectral analysis

In our previous study, we demonstrated the feasibility of using an all-optical interstitial photoacoustic (PA) needle sensing probe for quantitative study of tissue architectures with PA spectral analysis (PASA). In this work, we integrated the optical components into an 18 G steel needle sheath for clinical translation. The dimensions of the needle probe are identical to those of a core biopsy probe and are fully compatible with standard procedures such as prostate biopsy. To our knowledge, this is the first interstitial PA probe that can acquire signals with sufficient temporal length for statistics-based PASA. We treated the inner surface of the steel needle sheath and successfully suppressed the vibrational PA signals generated at the surface. Purposed at boosting the measurement sensitivity and extending sensing volume, we upgraded the Fabry-Pérot hydrophone with a plano-concave structure. The performance of the translational needle PA sensing probe was examined with phantoms containing microspheres. The trend of the linear spectral slopes shows negatively correlated to the microsphere dimensions while the midband-fits are positively correlated to microsphere diameters and concentrations. The PASA quantifications show the ability to differentiate microspheres with varied dimensions.

Molecular breast cancer subtype identification using photoacoustic spectral analysis and machine learning at the biomacromolecular level

Breast cancer threatens the health of women worldwide, and its molecular subtypes largely determine the therapy and prognosis of patients. However, an uncomplicated and accurate method to identify subtypes is currently lacking. This study utilized photoacoustic spectral analysis (PASA) based on the partial least squares discriminant algorithm (PLS-DA) to identify molecular breast cancer subtypes at the biomacromolecular level in vivo. The area of power spectrum density (APSD) was extracted to semi-quantify the biomacromolecule content. The feature wavelengths were obtained via the variable importance in projection (VIP) score and the selectivity ratio (Sratio), to identify the biomarkers. The PASA achieved an accuracy of 84%. Most of the feature wavelengths fell into the collagen-dominated absorption waveband, which was consistent with the histopathological results. This paper proposes a successful method for identifying molecular breast cancer subtypes and proves that collagen can be treated as a biomarker for molecular breast cancer subtyping.

Photoacoustic Spectral Analysis for Evaluating the Aggressiveness of Prostate Cancer Labeled by Methylene Blue Polyacrylamide Nanoparticles.

Evaluating the aggressiveness of prostate cancer (PCa) is crucial for PCa diagnosis and prognosis. Previously, studies have shown that photoacoustic spectral analysis (PASA) can assess prostate tissue microarchitecture for evaluating the aggressiveness of PCa. In this study, in a transgenic mouse (TRAMP) model of PCa, we utilized methylene blue polyacrylamide nanoparticles (MB PAA NPs) to label the cancer cells in prostate in vivo. MB PAA NPs can specifically target proliferating cancer cells as a contrast agent, allowing photoacoustic (PA) imaging to better detect PCa tumors, and also assessing prostate glandular architecture. With the PA signals from the prostates measured simultaneously by a needle hydrophone and a PA and ultrasound (US) dual-imaging system, we conducted PASA and correlated the quantified spectral parameter slopes with the cancer grading from histopathology. The PASA results from 18 mice showed significant differences between normal and cancer, and also between low-score cancer and high-score cancer. This study in the clinically relevant TRAMP model of PCa demonstrated that PA imaging and PASA, powered by MB PAA NPs that can label the PCa microarchitectures in vivo after systemic administration, can detect PCa and, more importantly, evaluate cancer aggressiveness.

Assessment of prostate cancer progression using a translational needle photoacoustic sensing probe: Preliminary study with intact human prostates ex-vivo

In our previous studies, we demonstrated the ability of an interstitial all-optical needle photoacoustic (PA) sensing probe and PA spectral analysis (PASA) to assess the aggressiveness of prostate cancer. In this clinical translation investigation, we integrated the optical components of the needle PA sensing probe into a 18G steel needle. The translational needle PA sensing probe was evaluated using intact human prostates in a simulated ultrasound-guided transperineal prostate biopsy. PA signals were acquired at 1220 nm, 1370 nm, 800 nm and 266 nm at each interstitial measurement location and quantified by PASA within the frequency range of 8–28 MHz. The measurement locations were stained for establishing spatial correlations between the quantitative measurements and the histological diagnosing. Most of the quantitative PA assessments reveal statistically significant differences between the benign and cancerous regions. Multivariate analysis combining the PASA quantifications shows an accuracy close to 90% in differentiating the benign and cancerous regions in the prostates.

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 (RAPSD)” was computed from the DWPASA results. Compared to the normal tissue, MI tissue was shown to contain more collagen, resulting in higher RAPSD 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). RAPSD 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.

Myocardial Infarct Border Demarcation by Dual-Wavelength Photoacoustic Spectral Analysis

Myocardial Infarct Border Demarcation by Dual-Wavelength Photoacoustic Spectral Analysis

Photoacoustic spectral analysis at ultraviolet wavelengths for characterizing the Gleason grades of prostate cancer.

The diagnosis of aggressive prostate cancer (PCa) has relied on microscopic architectures, namely Gleason patterns, of tissues extracted through core biopsies. Technology capable of assessing the tissue architecture without tissue extraction will reduce the invasiveness of PCa diagnosis and improve diagnostic accuracy by allowing for more sampling locations. Our recently developed photoacoustic spectral analysis (PASA) has achieved quantification of tissue architectural heterogeneity interstitially. Taking advantage of the unique optical absorption of cell nuclei at ultraviolet (UV) wavelengths, this study investigated PASA at 266 nm for quantifying the tissue architecture heterogeneity in prostates. The results have shown significant differences among the normal, early cancer, and late cancer stages in mouse prostates ex vivo and in vivo (n=20, p<0.05). The study with human samples ex vivo has shown a correlation of 0.80 (n=11, p<0.05) between PASA quantification and pathologic diagnosis.

Bone mineral density value evaluation based on photoacoustic spectral analysis combined with deep learning method

The diagnosis of osteoporosis is eventually converted to the measurement of bone mineral density (BMD) in clinical trials. Since our previous work had proved the ability of using photoacoustic spectral analysis (PASA) to efficiently detect osteoporosis, in this contribution, we proposed a fully connected multi-layer deep neural network combined with PASA to semi-quantify BMD values corresponding to varying degrees of bone loss and to further evaluate the degree of osteoporosis. Experiments were carried out on swine femur heads, and the performance of our proposed method is satisfying for future clinical screening.

Feasibility study for bone health assessment based on photoacoustic imaging method

This study investigated the feasibility of photoacoustic (PA) imaging of bone and characterization of bone features. By conducting the experiments on bovine femoral heads ex vivo, the light and ultrasonic penetration in bones was studied, together with the depth of PA imaging and measurement in bones. Then, the possibility of three-dimensional (3D) PA imaging of bones by raster scanning of the focusing transducer was studied. The micro-computerized tomography images of the bovine ribs with and without ethylenediaminetetraacetic acid (EDTA) treatment indicated that the 3D PA images could present the changes of bone microstructure resulting from the EDTA treatment. By using PA spectral analysis, the bone samples with and without the treatment of EDTA solution can be distinguished, and the microstructures can be characterized. This study was based on the bovine bone whose size is comparable to human bones, suggesting that PA technology can be used as a novel bone diagnostic technique.

Optical and photoacoustic radiofrequency spectroscopic analysis for detecting red blood cell death.

Under stress, red blood cells (RBCs) undergo programmed cell death (eryptosis). One of the signaling molecules for eryptosis, sphingomyelinase (SMase), plays an important role in monitoring the efficacy of vascular targeted cancer therapy. The high optical absorption of erythrocytes coupled with the changes of eryptotic RBCs makes RBCs ideal targets for the photoacoustic (PA) detection and characterization of vascular treatments. In this work, experiments characterizing eryptosis were performed: PA detection of high frequencies (>100 MHz) that enabled analysis at the single-cell level and of low frequencies (21 MHz) that enabled analysis at the RBC ensemble level. Ultrasound spectral analysis was performed on control and SMase-treated RBCs. Spectral unmixing was applied to quantify methemoglobin production as a by-product of RBC death. Validation was performed using a blood gas analyzer and optical spectrometry. Our results indicate that PA radiofrequency spectra could be used to differentiate the biochemically induced morphological changes as RBCs lose their native biconcave shape, and release hemoglobin into the surroundings. Spectral unmixing revealed a 7% increase in methemoglobin content for SMase-treated samples due to the oxidative stress on the RBCs. These findings suggest that PA spectral analysis of RBC death can potentially serve as a biomarker of the efficacy of vascular targeted cancer therapies.

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.

Interstitial photoacoustic spectral analysis: instrumentation and validation.

Photoacoustic (PA) spectral analysis (PASA) is a recently developed approach for quantifying molecular components and microscopic architectures in tissue. The PASA relies on signals with sufficient temporal length and narrow dynamic range for statistics based analysis. However, the optical and acoustic attenuation within the biological tissue make it difficult to acquire desirable signals from deep locations in biological tissue for PASA. This study proposes an interstitial PASA approach. By combining a fiber optics diffuser and a small aperture needle hydrophone, a fine needle PA probe facilitates PASA in deep tissue. A prototype probe has been fabricated and tested in quantifying the prostate cancer cell concentrations in vitro and lipid infiltrated hepatocyte in liver ex vivo. Experiment results show that the needle probe could potentially provide pathologic information of the tissues.

Comparison study of photoacoustic and ultrasound spectrum analysis in osteoporosis detection

Osteoporosis is a progressive bone disease, which is characterized by a decrease in the bone mass and deterioration in bone micro-architecture. In theory, photoacoustic (PA) analysis has the potential to obtain the characteristics of the bone effectively. In this study, we try to compare the PA spectral analysis (PASA) method with the quantitative ultrasound (QUS) method in osteoporosis assessment. We compare the quantified parameter slope from the PASA and broadband ultrasound attenuation from QUS among different bone models, respectively. Both the simulation and ex vivo experiment results show that bone with lower bone mineral density has the higher slope in the PASA method. Our comparison study proves that the PASA method has the same efficiency as QUS in osteoporosis assessment.

Quantifying Gleason scores with photoacoustic spectral analysis: feasibility study with human tissues.

Gleason score is a highly prognostic factor for prostate cancer describing the microscopic architecture of the tumor tissue. The standard procedure for evaluating Gleason scores, namely biopsy, is to remove prostate tissue for observation under microscope. Currently, biopsies are guided by transrectal ultrasound (TRUS). Due to the low sensitivity of TRUS to prostate cancer (PCa), non-guided and saturated biopsies are frequently employed, unavoidably causing pain, damage to the normal prostate tissues and other complications. More importantly, due to the limited number of biopsy cores, current procedure could either miss early stage small tumors or undersample aggressive cancers. Photoacoustic (PA) measurement has the unique capability of evaluating tissue microscopic architecture information at ultrasonic resolution. By frequency domain analysis of the broadband PA signal, namely PA spectral analysis (PASA), the microscopic architecture within the assessed tissue can be quantified. This study investigates the feasibility of evaluating Gleason scores by PASA. Simulations with the classic Gleason patterns and experiment measurements from human PCa tissues have demonstrated strong correlation between the PASA parameters and the Gleason scores.

Characterization of bone microstructure using photoacoustic spectrum analysis.

Osteoporosis is a progressive bone disease that is characterized by a decrease in bone mass and the deterioration in bone microarchitecture. This study investigates the feasibility of characterizing bone microstructure by analyzing the frequency spectrum of the photoacoustic (PA) signal from the bone. Modeling and numerical simulation of PA signal were performed on trabecular bone simulations and CT scans with different trabecular thicknesses. The resulting quasi-linear photoacoustic spectra were fittted by linear regression, from which the spectral parameter slope was quantified. The simulation based on two different models both demonstrate that bone specimens with thinner trabecular thicknesses have higher slope. Experiment on osteoporotic rat femoral heads with different mineral content was conducted. The finding from the experiment was in good agreement with the simulation, demonstrating that the frequency-domain analysis of PA signals can provide an objective assessment of bone microstructure and deterioration. Considering that PA measurement is non-ionizing, non-invasive, and has sufficient penetration in both calcified and non-calcified tissues, this new bone evaluation method based on photoacoustic spectral analysis holds potential for clinical management of osteoporosis and other bone diseases.

1P5-3 Photoacoustic spectral analysis of biological tissue for plaque diagnosis(Poster Session)

1P5-3 Photoacoustic spectral analysis of biological tissue for plaque diagnosis(Poster Session)

Sensitive detection of weak absorption signals in photoacoustic spectroscopy by using derivative spectroscopy and wavelet transform

This report presents a practical analytical method of photoacoustic (PA) spectroscopy that is based on wavelet transform (WT) and the first-derivative PA spectrum. An experimental setup is specially designed to obtain the first-derivative spectrum, which aims to identify some unnoticeable absorption peaks in the normal PA spectrum. To enhance the detectability of overlapping spectral bands, the WT is used to decompose the PA spectrum signals into a series of localized contributions (details and approximation) on the basis of the frequency. For the decomposed contributions do not change the absorption peak position of PA spectrum, one can retrieve the weak absorption signals by the decomposed result of WT. Because of the use of derivative spectroscopy and WT, three unnoticeable absorption peaks that are hidden in the PA spectrum of carbon absorption are precisely retrieved, the wavelengths of which are 699.7, 752.7, and 775.5nm, respectively. This analytical method, which has the virtue of using a physical method and using a computer software method, can achieve great sensitivity and accuracy for PA spectral analysis.

Generalized Two-Dimensional Fourier Transform Infrared Photoacoustic Spectral Depth-Profiling Analysis

This paper reports the first application of a generalized two-dimensional (G2D) correlation method in photoacoustic spectral depth-profiling analysis of laminate/heterogeneous samples. In this method, photoacoustic magnitude spectra at different modulation frequencies are used to generate two-dimensional (2D) correlation spectra. The relative spatial origins of correlated signals are then determined from the signs of the corresponding contours. The unique features and advantages of this technique over previously reported depth-profiling methods are demonstrated and discussed. These include simplification of step-scan photoacoustic phase-modulation experiments as well as 2D correlation-analysis rules, avoidance of phase-related negative-band ambiguities, and enhancement of both spectral and depth resolutions, etc. The recently developed software-based digital signal-processing (DSP) technique for step-scan photoacoustic measurements offers an efficient means (sampling-depth multiplexing advantage) to collect within a single scan all necessary data for this type of 2D correlation analysis. Index Headings: Photoacoustic; PAS; Two-dimensional; Step-scan; FT-IR; Depth profiling; Polymer films; DSP.