Recent Posts

BIODEGRADABLE AND BIOCOMPATIBLE SEMICONDUCTOR NANOCRYSTALS AS NIR-II PHOTOACOUSTIC IMAGING CONTRAST AGENTS

Author(s): Vinoin Devpaul Vincely, Swathi P. Katakam, Kristie Huda, Xingjian Zhong, Joshua C. Kays, Allison M. Dennis, Carolyn L. Bayer

ABSTRACT

Transabdominal imaging using photoacoustics (PA) is limited by optical attenuation of tissue due to high scattering and absorption in the near infrared (NIR) window. Tissue attenuation is lowered when imaging with longer wavelengths in the NIR window (> 950 nm). However, intrinsic optical contrast is limited in this range and exogenous agents such as gold nanorods (AuNRs) prove popular alternatives. AuNRs have unique optical absorption peaks, due to localized surface plasmon resonance (LSPR), which allow tuning to wavelengths with minimal tissue attenuation. However, AuNRs tend to be bulky (> 50 nm) when adjusting peak LSPR to deep NIR wavelengths leading to poor clearance. In this study, we explored PA signal generation of a biodegradable and biocompatible semiconductor contrast agent – Cu-Fe (bornite) nanocrystals. The semiconductor nature of the nanocrystals allows for particles to be small (3-8 nm) facilitating excretion through kidneys. Here, PA signal generation of bornite was compared to two conventional photoacoustic contrast agents – AuNRs and indocyanine green dye. We found that at similar mass concentrations, bornite generated PA signal 5× greater than AuNRs. In-vivo imaging of bornite showed a 2x increase in sensitivity compared to AuNRs at similar volume concentrations.

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IMPROVING PHOTOACOUSTIC IMAGING IN LOW SIGNAL-TO-NOISE RATIO BY USING SPATIAL AND POLARITY COHERENCE

Author(s): Qiuqin Mao, Weiwei Zhao, Xiaoqin Qian, Chao Tao, Xiaojun Liu

ABSTRACT

To suppress the noise and sidelobe of photoacoustic images, a method is proposed combined with spatial coherence and polarity coherence. In this method, PA signals are delayed, multiplied, then performed polarity coherence, and finally summed. The polarity of delayed-and-multiplied signals rather than the amplitude is considered in polarity coherence operation. The polarity coherence factor is calculated based on the standard deviation of the polarity. Then, the factor as weights is applied to the coherent sum output after spatial autocorrelation to finally obtain the image. The simulated and experimental results prove that the noise level can be effectively suppressed due to its relatively low polarity coherence factor. Compared with the delay-and-sum method, the quantitative results in simulations show that the image contrast and full-width at half-maximum of the proposed method increase by about 227.0 % and 56.5 % when the signal-to-noise ratio of the raw signal is 0 dB, respectively. Besides achieving a better image contrast, this method obtains improvements in sidelobe attenuation and has a narrow main lobe.

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DEEP LEARNING ENABLED REAL-TIME PHOTOACOUSTIC TOMOGRAPHY SYSTEM VIA SINGLE DATA ACQUISITION CHANNEL

Author(s): Hengrong Lan, Daohuai Jiang, Feng Gao, Fei Gao

ABSTRACT

Photoacoustic computed tomography (PACT) combines the optical contrast of optical imaging and the penetrability of sonography. In this work, we develop a novel PACT system to provide real-time imaging, which is achieved by a 120-elements ultrasound array only using a single data acquisition (DAQ) channel. To reduce the channel number of DAQ, we superimpose 30 nearby channels’ signals together in the analog domain, and shrinking to 4 channels of data (120/30 = 4). Furthermore, a four-to-one delay-line module is designed to combine these four channels’ data into one channel before entering the single-channel DAQ, followed by decoupling the signals after data acquisition. To reconstruct the image from four superimposed 30-channels’ PA signals, we train a dedicated deep learning model to reconstruct the final PA image. In this paper, we present the preliminary results of phantom and in-vivo experiments, which manifests its robust real-time imaging performance. The significance of this novel PACT system is that it dramatically reduces the cost of multi-channel DAQ module (from 120 channels to 1 channel), paving the way to a portable, low-cost and real-time PACT system.

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Y-NET: HYBRID DEEP LEARNING IMAGE RECONSTRUCTION FOR PHOTOACOUSTIC TOMOGRAPHY IN VIVO

Author(s): Hengrong Lan, Daohuai Jiang, Changchun Yang, Feng Gao, Fei Gao

ABSTRACT

Conventional reconstruction algorithms (e.g., delay-and-sum) used in photoacoustic imaging (PAI) provide a fast solution while many artifacts remain, especially for limited-view with ill-posed problem. In this paper, we propose a new convolutional neural network (CNN) framework Y-Net: a CNN architecture to reconstruct the initial PA pressure distribution by optimizing both raw data and beamformed images once. The network combines two encoders with one decoder path, which optimally utilizes more information from raw data and beamformed image. We compared our result with some ablation studies, and the results of the test set show better performance compared with conventional reconstruction algorithms and other deep learning method (U-Net). Both in-vitro and in-vivo experiments are used to validated our method, which still performs better than other existing methods. The proposed Y-Net architecture also has high potential in medical image reconstruction for other imaging modalities beyond PAI.

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RADIATION-INDUCED ACOUSTIC SIGNAL DENOISING USING A SUPERVISED DEEP LEARNING FRAMEWORK FOR IMAGING AND THERAPY MONITORING

Author(s): Zhuoran Jiang, Siqi Wang, Yifei Xu, Leshan Sun, Gilberto Gonzalez, Yong Chen, Q. Jackie Wu, Liangzhong Xiang, Lei Ren​

ABSTRACT

Radiation-induced acoustic (RA) imaging is a promising technique for visualizing radiation energy deposition in tissues, enabling new imaging modalities and real-time therapy monitoring. However, it requires measuring hundreds or even thousands of averages to achieve satisfactory signal-to-noise ratios (SNRs). This repetitive measurement increases ionizing radiation dose and degrades the temporal resolution of RA imaging, limiting its clinical utility. In this study, we developed a general deep inception convolutional neural network (GDI-CNN) to denoise RA signals to substantially reduce the number of averages. The multi-dilation convolutions in the network allow for encoding and decoding signal features with varying temporal characteristics, making the network generalizable to signals from different radiation sources. The proposed method was evaluated using experimental data of X-ray-induced acoustic, protoacoustic, and electroacoustic signals, qualitatively and quantitatively. Results demonstrated the effectiveness and generalizability of GDI-CNN: for all the enrolled RA modalities, GDI-CNN achieved comparable SNRs to the fully-averaged signals using less than 2% of the averages, significantly reducing imaging dose and improving temporal resolution. The proposed deep learning framework is a general method for few-frame-averaged acoustic signal denoising, which significantly improves RA imaging’s clinical utilities for low-dose imaging and real-time therapy monitoring.

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AUTOMATIC FORCE-CONTROLLED 3D PHOTOACOUSTIC SYSTEM FOR HUMAN PERIPHERAL VASCULAR IMAGING

Author(s): David C. Garrett, Jinhua Xu, Geng Ku, and Lihong V. Wang

ABSTRACT

We developed a system for whole-body human ultrasound tomography in reflection and transmission modes. A custom 512-element ultrasound receiver array with a rotating single-element ultrasound transmitter are used to generate 2D isotropically resolved images across the entire human cross-section. We demonstrate this technique in regions such as the abdomen and legs in healthy volunteers. Compared to handheld-probe-based ultrasonography, this approach provides a substantially larger field of view, depends less on operator training, and obtains quantitative tissue parameter profiles in addition to reflectivity images. Whole-body ultrasound tomography could be valuable in applications such as organ disease screening, image-guided needle biopsy, and treatment monitoring.

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DUAL-SCAN PHOTOACOUSTIC TOMOGRAPHY FOR THE IMAGING OF VASCULAR STRUCTURE ON FOOT

Author(s): Chuqin Huang, Yanda Cheng, Wenhan Zheng, Robert W Bing, Huijuan Zhang, Isabel Komornicki, Linda M Harris, Praveen R Arany, Saptarshi Chakraborty, Qifa Zhou, Wenyao Xu, Jun Xia

ABSTRACT

Chronic leg ulcers are affecting approximately 6.5 million Americans, and they are associated with significant mortality, reduced quality of life, and high treatment costs. Since many chronic ulcers have underlying vascular insufficiency, accurate assessment of tissue perfusion is critical to treatment planning and monitoring. This study introduces a dual-scan photoacoustic tomography system that can simultaneously image the dorsal and plantar sides of the foot to reduce imaging time. To account for the unique shape of the foot, the system employs height-adjustable and articulating base ball stages that can scan along the foot’s contour. In vivo results from healthy volunteers demonstrate the system’s ability to acquire clear images of foot vasculature, and results from patients indicate that the system can image patients with various ulcer conditions. We also investigated various photoacoustic features and examined their correlation with the foot condition. Our preliminary results indicate that vessel sharpness, occupancy, intensity, and density could all be used to assess tissue perfusion. This research demonstrated the potential of photoacoustic tomography for routine clinical tissue perfusion assessment.

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EVALUATION OF ULTRASOUND SENSORS FOR TRANSCRANIAL PHOTOACOUSTIC SENSING AND IMAGING

Author(s): Thomas Kirchner, Claus Villringer, and Jan Laufer

ABSTRACT

Significance: Biomedical photoacoustic (PA) imaging is typically used to exploit absorption-based contrast in soft tissue at depths of several centimeters. When it is applied to measuring PA waves generated in the brain, the acoustic properties of the skull bone cause not only strong attenuation but also a distortion of the wavefront, which diminishes image resolution and contrast. This effect is directly proportional to bone thickness. As a result, transcranial PA imaging in humans has been challenging to demonstrate.
Aim: We measured the acoustic constraints imposed by the human skull to design an ultrasound sensor suitable for transcranial PA imaging and sensing.
Approach: We calculated the frequency dependent losses of human cranial bones in silico and performed measurements ex vivo using broadband ultrasound sources based on PA excitation, such as a single vessel phantom with tissue-mimicking optical absorption. We imaged the phantoms using a planar Fabry-Perot sensor and employed a range of piezoelectric and optical ultrasound sensors to measure the frequency dependent acoustic transmission through human cranial bone.
Results: Transcranial PA images show typical frequency and thickness-dependent attenuation and aberration effects associated with acoustic propagation through bone. The skull insertion loss measurements showed significant transmission at low frequencies. In comparison to conventional piezoelectric sensors, the performance of plano-concave optical resonator (PCOR) ultrasound sensors was found to be highly suitable for transcranial PA measurements. They possess high acoustic sensitivity at a low acoustic frequency range that coincides with the transmission window of
human skull bone. PCOR sensors showed low noise equivalent pressures and flat frequency response which enabled them to outperform conventional piezoelectric transducers in transcranial PA sensing experiments.
Conclusions: Transcranial PA sensing and imaging requires ultrasound sensors with high sensitivity at low acoustic frequencies, and a broad and ideally uniform frequency response. We designed and fabricated PCOR sensors and demonstrated their suitability for transcranial PA sensing.

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HIGH-SPEED THREE-DIMENSIONAL PHOTOACOUSTIC COMPUTED TOMOGRAPHY FOR PRECLINICAL RESEARCH AND CLINICAL TRANSLATION

Authors: Li Lin, Peng Hu, Xin Tong, Rui Cao, Xiaoyun Yuan, David C. Garrett, Junhui Shi, Konstantin Maslov & Lihong V. Wang

ABSTRACT

Photoacoustic computed tomography (PACT) has generated increasing interest for uses in preclinical research and clinical translation. However, the imaging depth, speed, and quality of existing PACT systems have previously limited the potential applications of this technology.
To overcome these issues, we developed a three-dimensional photoacoustic computed tomography (3D-PACT) system that features large imaging depth, scalable field of view with isotropic spatial resolution, high imaging speed, and superior image quality. 3D-PACT allows for multipurpose imaging to reveal detailed angiographic information in biological tissues ranging from the rodent brain to the human breast. In the rat brain, we visualize whole brain vasculatures and hemodynamics. In the human breast, an in vivo imaging depth of 4 cm is achieved by scanning the breast within a single breath hold of 10 s. Here, we introduce the 3D-PACT system to provide a unique tool for preclinical research and an appealing prototype for clinical translation.

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LIVE PRODUCT DEMONSTRATIONS AT EMIM

Scintica is attending EMIM 2023 and is using PhotoSound Technologies, Inc products for live demonstrations!

Visit them in #Austria at the Salzburg Congress. They will be at booth 315!

Ensure a chance to speak with their preclinical research experts by booking a meeting here: https://lnkd.in/gqQ4Fz9c

European Society for Molecular Imaging-ESMI 

#EMIM2023 #EMIM #EuropeanMolecularImagingMeeting

#photoacoustic #fluorescence #imaging #biomedicalscience #biomedicalresearch #science #tomography