Recent Posts

NON-INVASIVE PHOTOACOUSTIC COMPUTED TOMOGRAPHY OF RAT HEART ANATOMY AND FUNCTION

Author(s): Xin Tong, Li Lin, Peng Hu, Rui Cao, Yang Zhang, Joshua Olick-Gibson, Lihong V. Wang

ABSTRACT

Non-alcoholic fatty liver disease is the most common liver disorder worldwide, which strongly correlates to obesity, diabetes, and metabolic syndromes. Complementary to mainstream liver diagnostic modalities, photoacoustic tomography (PAT) can provide high-speed images with functional optical contrast. However, PAT has not been demonstrated to study fatty liver anatomy with clear volumetric vasculatures. The livers of multiple rats are non-invasively imaged in vivo using the recently developed 3D PAT platform. The system provides isotropically high spatial resolution in 3D space, presenting clear angiographic structures of rat livers without injecting contrast agents. Furthermore, to quantitatively analyze the difference between the livers of lean and obese rats, the authors measured several PAT features and statistical differences between the two groups are observed. In addition to the anatomy, a time-gated strategy is applied to correct respiration-induced motion artifacts and extracted the hemodynamics of major blood vessels during the breathing cycles. This study demonstrates the capabilities of 3D-PAT to reveal both angiographic anatomy and function in rat livers, providing hematogenous information for fatty liver diagnosis. 3D-PAT, as a new tool for preclinical research, warrants further improvements to be transferred to human pediatric liver imaging.

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REAL-TIME, VOLUMETRIC IMAGING OF RADIATION DOSE DELIVERY DEEP INTO THE LIVER DURING CANCER TREATMENT

Authors: Wei Zhang, Ibrahim Oraiqat, Dale Litzenberg, Kai-Wei Chang, Scott Hadley, Noora Ba Sunbul, Martha M. Matuszak,  Christopher J. Tichacek, Eduardo G. Moros, Paul L. Carson, Kyle C. Cuneo, Xueding Wang, & Issam El Naqa

ABSTRACT

Ionizing radiation acoustic imaging (iRAI) allows online monitoring of radiation’s interactions with tissues during radiation therapy, providing real-time, adaptive feedback for cancer treatments. We describe an iRAI volumetric imaging system that enables mapping of the three-dimensional (3D) radiation dose distribution in a complex clinical radiotherapy treatment. The method relies on a two-dimensional matrix array transducer and a matching multi-channel preamplifier board. The feasibility of imaging temporal 3D dose accumulation was first validated in a tissue-mimicking phantom. Next, semiquantitative iRAI relative dose measurements were verified in vivo in a rabbit model. Finally, real-time visualization of the 3D radiation dose delivered to a patient with liver metastases was accomplished with a clinical linear accelerator. These studies demonstrate the potential of iRAI to monitor and quantify the 3D radiation dose deposition during treatment, potentially improving radiotherapy treatment efficacy using real-time adaptive treatment.

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MONITORING NEONATAL BRAIN HEMORRHAGE PROGRESSION BY PHOTOACOUSTIC TOMOGRAPHY

Author(s): Tianqi Shan, Hao Yang, Shixie Jiang, and Huabei Jiang

ABSTRACT

Neonatal brain hemorrhage (NBH) is the most common neurological disorder in neonates and its clinical interventions are very limited. Understanding the pathology of NBH by non-invasive in-vivo characterization of standardized animal models is essential for developing potential treatments. Currently, there is no suitable tool to provide non-invasive, non-ionizing dynamic imaging of neonatal mouse models with high resolution, high contrast, and deep imaging depth. In this study, we implemented a fast 3D photoacoustic tomography (PAT) system suitable for imaging neonatal mouse brains with good image quality and demonstrated its feasibility in non-invasive monitoring of the dynamic process of NBH in the whole neonatal mouse brain. The results present a high resolution and sensitivity for NBH detection. Both morphological and hemodynamic changes of the hematoma were accurately obtained. Our results demonstrated the potential of PAT as a powerful tool for the preclinical study of neonatal brain hemorrhage.

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CHARACTERIZING A PHOTOACOUSTIC AND FLUORESCENCE IMAGING PLATFORM FOR PRECLINICAL MURINE LONGITUDINAL STUDIES

Author(s): Weylan R. Thompson, Hans-Peter F. Brecht, Vassili Ivanov, Anthony M. Yu, Diego S. Dumani, Dylan J. Lawrence, Stanislav Y. Emelianov, Sergey A. Ermilov

ABSTRACT
SIGNIFICANCE

To effectively study preclinical animal models, medical imaging technology must be developed with a high enough resolution and sensitivity to perform anatomical, functional, and molecular assessments. Photoacoustic (PA) tomography provides high resolution and specificity, and fluorescence (FL) molecular tomography provides high sensitivity; the combination of these imaging modes will enable a wide range of research applications to be studied in small animals.

AIM

We introduce and characterize a dual-modality PA and FL imaging platform using in vivo and phantom experiments.

APPROACH

The imaging platform’s detection limits were characterized through phantom studies that determined the PA spatial resolution, PA sensitivity, optical spatial resolution, and FL sensitivity.

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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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