Photoacoustics最新文献

Multispectral optoacoustic tomography (MSOT) allows non-invasive molecular disease activity assessment in adults with inflammatory bowel disease (IBD). In this prospective pilot-study, we investigated, whether increased levels of MSOT haemoglobin parameters corresponded to inflammatory activity in paediatric IBD patients, too. 23 children with suspected IBD underwent MSOT of the terminal ileum and sigmoid colon with standard validation (e.g. endoscopy). In Crohn`s disease (CD) and ulcerative colitis (UC) patients with endoscopically confirmed disease activity, MSOT total haemoglobin (HbT) signals were increased in the terminal ileum of CD (72.1 ± 13.0 a.u. vs. 32.9 ± 15.4 a.u., p = 0.0049) and in the sigmoid colon of UC patients (62.9 ± 13.8 a.u. vs. 35.1 ± 16.3 a.u., p = 0.0311) as compared to controls, respectively. Furthermore, MSOT haemoglobin parameters correlated well with standard disease activity assessment (e.g. SES-CD and MSOT HbT (r_s =0.69, p = 0.0075). Summarizing, MSOT is a novel technology for non-invasive molecular disease activity assessment in paediatric patients with inflammatory bowel disease.

Limitations associated with linear-array probes in photoacoustic tomography are partially compensated by using advanced beamformers that exploit the temporal and spatial coherence of the recorded signals, such as Delay Multiply and Sum (DMAS), Minimum Variance (MV) or coherence factor (CF), among others. However, their associated signal processing leads to an overestimation of the spatial resolution, as well as alterations in the reconstructed object size. Numerical and experimental results reported here support this hypothesis. First, we show that the Rayleigh criterion (RC) is the most suitable choice to characterize the spatial resolution instead of the Point Spread Function (PSF) when considering advanced beamformers. Then, we observe that several advanced beamformers fail to properly reconstruct target sizes slightly above the spatial resolution, underestimating their size. This work sheds light on the suitability of this type of beamformers combined with linear probes for determining sizes and morphology in photoacoustic images.

In this work, we report on the novel employment of lithium niobate tuning forks as acoustic transducers in photoacoustic spectroscopy for gas sensing. The lithium niobate tuning fork (LiNTF) exhibits a fundamental resonance frequency of 39196.6 Hz and a quality factor Q = 5900 at atmospheric pressure. The possibility to operate the LiNTF as a photoacoustic wave detector was demonstrated targeting a water vapor absorption line falling at 7181.14 cm⁻¹ (1.39 µm). A noise equivalent concentration of 2 ppm was reached with a signal integration time of 20 s. These preliminary results open the path towards integrated photonic devices for gas sensing with LiNTF-based detectors on lithium niobate platforms.

Combining the diffusive laser excitation and the photoacoustic signals detection, photoacoustic computed tomography (PACT) is uniquely suited for deep tissue imaging. A diffraction-limited ultrasound point detector is highly desirable for maximizing the spatial resolution and the field-of-view of the reconstructed volumetric images. Among all the available ultrasound detectors, micro-ring resonator (MRR) based ultrasound detectors offer the lowest area-normalized limit of detection (nLOD) in a miniature form-factor, making it an ideal candidate as an ultrasound point detector. However, despite their wide adoption for photoacoustic imaging, the underlying signal transduction process has not been systematically studied yet. Here we report a comprehensive theoretical model capturing the transduction of incident acoustic signals into digital data, and the associated noise propagation process, using experimentally calibrated key process parameters. The theoretical model quantifies the signal-to-noise ratio (SNR) and the nLOD under the influence of the key process variables, including the quality factor (Q-factor) of the MRR and the driving wavelength. While asserting the need for higher Q-factors, the theoretical model further quantifies the optimal driving wavelength for optimizing the nLOD. Given the MRR with a Q-factor of 1×10⁵, the theoretical model predicts an optimal SNR of 30.1 dB and a corresponding nLOD of 3.75×10^-2 mPa mm²/Hz^1/2, which are in good agreement with the experimental measurements of 31.0 dB and 3.39×10^-2 mPa mm²/Hz^1/2, respectively. The reported theoretical model can be used in guiding the optimization of MRR-based ultrasonic detectors and PA experimental conditions, in attaining higher imaging resolution and contrast. The optimized operating condition has been further validated by performing PACT imaging of a human hair phantom.

A proof-of-concept gas sensor based on a miniaturized and integrated fiber-optic photoacoustic detection module was introduced and demonstrated for the purpose of developing a custom tuning-fork (TF)-enhanced photoacoustic gas sensor. Instead of piezoelectric quartz tuning fork (QTF) in conventional quartz-enhanced photoacoustic spectroscopy (QEPAS), a low-cost custom aluminum alloy TF fabricated by mechanical processing was employed as a photoacoustic transducer and the vibration of TF was measured by fiber-optic Fabry-Pérot (FP) interferometer (FPI). The mechanical processing-based TF design scheme greatly increases the flexibility of the TF design with respect to the complex and expensive manufacture process of custom QTFs, and thus it can be better exploited to detect gases with slow vibrational-translational (V-T) relaxation rates and combine with light sources with poor beam quality. The resonance frequency and the quality factor of the designed custom TF at atmospheric pressure were experimentally determined to be 7.3 kHz and 4733, respectively. Dual-prong differential measurement method was proposed to double the photoacoustic signal and suppress the external same-direction noise. After detailed optimizing and investigating for the operating parameters by measuring H₂O, the feasibility of the developed sensor for gas detection was demonstrated with a H₂O minimum detection limit (MDL) of 1.2 ppm, corresponding to a normalized noise equivalent absorption (NNEA) coefficient of 3.8 × 10⁻⁸ cm⁻¹ W/Hz^1/2, which are better than the QTF-based photoacoustic sensors. The proposed gas sensing approach combined the advantages of QEPAS and fiber-optic sensing, which can greatly expand the application domains of PAS-based gas sensors.

Photoacoustic dermoscopy (PAD) is an emerging non-invasive imaging technology aids in the diagnosis of dermatological conditions by obtaining optical absorption information of skin tissues. Despite advances in PAD, it remains unclear how to obtain quantitative accuracy of the reconstructed PAD images according to the optical and acoustic properties of multilayered skin, the wavelength and distribution of excitation light, and the detection performance of ultrasound transducers. In this work, a computing method of four-dimensional (4D) spectral-spatial imaging for PAD is developed to enable quantitative analysis and optimization of structural and functional imaging of skin. This method takes the optical and acoustic properties of heterogeneous skin tissues into account, which can be used to correct the optical field of excitation light, detectable ultrasonic field, and provide accurate single-spectrum analysis or multi-spectral imaging solutions of PAD for multilayered skin tissues. A series of experiments were performed, and simulation datasets obtained from the computational model were used to train neural networks to further improve the imaging quality of the PAD system. All the results demonstrated the method could contribute to the development and optimization of clinical PADs by datasets with multiple variable parameters, and provide clinical predictability of photoacoustic (PA) data for human skin.

An all-optical non-resonant photoacoustic spectroscopy system for multicomponent gas detection based on a silicon cantilever optical microphone (SCOM) and an aseismic photoacoustic cell is proposed and demonstrated. The SCOM has a high sensitivity of over 96.25 rad/Pa with sensitivity fluctuation less than ± 1.56 dB between 5 Hz and 250 Hz. Besides, the minimal detectable pressure (MDP) of the sensor is 0.55 μPa·Hz^−1/2 at 200 Hz, which indicates that the fabricated sensor has high sensitivity and low noise level. Six different gases of CO₂, CO, CH₄, C₂H₆, C₂H₄, C₂H₂ are detected at the frequency of 10 Hz, whose detection limits (3σ) are 62.66 ppb, 929.11 ppb, 1494.97 ppb, 212.94 ppb, 1153.36 ppb and 417.61 ppb, respectively. The system achieves high sensitivity and low detection limits for trace gas detection. In addition, the system exhibits seismic performance with suppressing vibration noise by 4.5 times, and achieves long-term stable operation. The proposed non-resonant all-optical PAS multi-component gas detection system exhibits the advantages of anti-vibration performance, low gas consumption and long term stability, which provides a solution for working in complex environments with inherently safe.

We present a rapid and high-resolution photoacoustic imaging method for evaluating the liver function reserve (LFR). To validate its accuracy, we establish alcoholic liver disease (ALD) models and employ dual-wavelength spectral unmixing to assess oxygen metabolism. An empirical mathematical model fits the photoacoustic signals, obtaining liver metabolism curve and LFR parameters. Liver oxygen metabolism significantly drops in ALD with the emergence of abnormal hepatic lobular structure. ICG half-life remarkably extends from 241 to 568 s in ALD. A significant decline in LFR occurs in terminal region compared to central region, indicated by a 106.9 s delay in ICG half-life, likely due to hepatic artery and vein damage causing hypoxia and inadequate nutrition. Reduced glutathione repairs LFR with a 43% improvement by reducing alcohol-induced oxidative damage. Scalable photoacoustic imaging shows immense potential for assessing LFR in alcoholic-related diseases, providing assistance to early detection and management of liver disease.

Three-dimensional (3D) photoacoustic imaging (PAI) can provide rich information content and has gained increasingly more attention in various biomedical applications. However, current 3D PAI methods either involves pointwise scanning of the 3D volume using a single-element transducer, which can be time-consuming, or requires an array of transducers, which is known to be complex and expensive. By utilizing a 3D encoder and compressed sensing techniques, we develop a new imaging modality that is capable of single-shot 3D PAI using a single-element transducer. The proposed method is validated with phantom study, which demonstrates single-shot 3D imaging of different objects and 3D tracking of a moving object. After one-time calibration, while the system could perform single-shot 3D imaging for different objects, the calibration could remain effective over 7 days, which is highly beneficial for practical translation. Overall, the experimental results showcase the potential of this technique for both scientific research and clinical applications.

By means of an ultrafast optical technique, picosecond acoustic strain pulses in a transparent medium are tomographically visualized at GHz frequencies. The strain distribution in BK7 glass is reconstructed from time-domain reflectivity changes of 415-nm probe light as a function of the optical incidence angle with 1 ps temporal and 120 nm spatial resolutions, enabled by automated angle scanning. The latter resolution is achieved owing to the commensurate acoustic wavelength. Applications include imaging strain, carrier and temperature distributions on ultrashort timescales.