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Hahne C, Chabouh G, Chavignon A, Couture O, Sznitman R. RF-ULM: Ultrasound Localization Microscopy Learned From Radio-Frequency Wavefronts. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:3253-3262. [PMID: 38640052 DOI: 10.1109/tmi.2024.3391297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/21/2024]
Abstract
In Ultrasound Localization Microscopy (ULM), achieving high-resolution images relies on the precise localization of contrast agent particles across a series of beamformed frames. However, our study uncovers an enormous potential: The process of delay-and-sum beamforming leads to an irreversible reduction of Radio-Frequency (RF) channel data, while its implications for localization remain largely unexplored. The rich contextual information embedded within RF wavefronts, including their hyperbolic shape and phase, offers great promise for guiding Deep Neural Networks (DNNs) in challenging localization scenarios. To fully exploit this data, we propose to directly localize scatterers in RF channel data. Our approach involves a custom super-resolution DNN using learned feature channel shuffling, non-maximum suppression, and a semi-global convolutional block for reliable and accurate wavefront localization. Additionally, we introduce a geometric point transformation that facilitates seamless mapping to the B-mode coordinate space. To understand the impact of beamforming on ULM, we validate the effectiveness of our method by conducting an extensive comparison with State-Of-The-Art (SOTA) techniques. We present the inaugural in vivo results from a wavefront-localizing DNN, highlighting its real-world practicality. Our findings show that RF-ULM bridges the domain shift between synthetic and real datasets, offering a considerable advantage in terms of precision and complexity. To enable the broader research community to benefit from our findings, our code and the associated SOTA methods are made available at https://github.com/hahnec/rf-ulm.
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Pan Y, Qiang Y, Liang W, Huang W, Wang N, Wang X, Zhang Z, Qiu W, Zheng H. A transcranial multiple waves suppression method for plane wave imaging based on Radon transform. ULTRASONICS 2024; 143:107405. [PMID: 39059257 DOI: 10.1016/j.ultras.2024.107405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 07/07/2024] [Accepted: 07/14/2024] [Indexed: 07/28/2024]
Abstract
Transcranial ultrasound imaging presents a significant challenge due to the intricate interplay between ultrasound waves and the heterogeneous human skull. The skull's presence induces distortion, refraction, multiple scattering, and reflection of ultrasound signals, thereby complicating the acquisition of high-quality images. Extracting reflections from the entire waveform is crucial yet exceedingly challenging, as intracranial reflections are often obscured by strong amplitude direct waves and multiple scattering. In this paper, a multiple wave suppression method for ultrasound plane wave imaging is proposed to mitigate the impact of skull interference. Drawing upon prior research, we developed an enhanced high-resolution linear Radon transform using the maximum entropy principle and Bayesian method, facilitating wavefield separation. We detailed the process of wave field separation in the Radon domain through simulation of a model with a high velocity layer. When plane waves emitted at any steering angles, both multiple waves and first arrival waves manifested as distinct energy points. In the brain simulation, we contrasted the characteristic differences between skull reflection and brain-internal signal in Radon domain, and demonstrated that multiples suppression method reduces side and grating lobe levels by approximately 30 dB. Finally, we executed in vitro experiments using a monkey skull to separate weak intracranial reflection signals from strong skull reflections, enhancing the contrast-to-noise ratio by 85 % compared to conventional method using full waveform. This study deeply explores the effect of multiples on effective signal separation, addresses the complexity of wavefield separation, and verifies its efficacy through imaging, thereby significantly advancing ultrasound transcranial imaging techniques.
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Affiliation(s)
- Yue Pan
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yu Qiang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China
| | - Wenjie Liang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China
| | - Wenyue Huang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China
| | - Ningyuan Wang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China
| | - Xingying Wang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhiqiang Zhang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China
| | - Weibao Qiu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China.
| | - Hairong Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China
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Caudoux M, Demeulenaere O, Poree J, Sauvage J, Mateo P, Ghaleh B, Flesch M, Ferin G, Tanter M, Deffieux T, Papadacci C, Pernot M. Curved Toroidal Row Column Addressed Transducer for 3D Ultrafast Ultrasound Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:3279-3291. [PMID: 38640053 DOI: 10.1109/tmi.2024.3391689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/21/2024]
Abstract
3D Imaging of the human heart at high frame rate is of major interest for various clinical applications. Electronic complexity and cost has prevented the dissemination of 3D ultrafast imaging into the clinic. Row column addressed (RCA) transducers provide volumetric imaging at ultrafast frame rate by using a low electronic channel count, but current models are ill-suited for transthoracic cardiac imaging due to field-of-view limitations. In this study, we proposed a mechanically curved RCA with an aperture adapted for transthoracic cardiac imaging ( 24×16 mm2). The RCA has a toroidal curved surface of 96 elements along columns (curvature radius rC = 4.47 cm) and 64 elements along rows (curvature radius rR = 3 cm). We implemented delay and sum beamforming with an analytical calculation of the propagation of a toroidal wave which was validated using simulations (Field II). The imaging performance was evaluated on a calibrated phantom. Experimental 3D imaging was achieved up to 12 cm deep with a total angular aperture of 30° for both lateral dimensions. The Contrast-to-Noise ratio increased by 12 dB from 2 to 128 virtual sources. Then, 3D Ultrasound Localization Microscopy (ULM) was characterized in a sub-wavelength tube diameter. Finally, 3D ULM was demonstrated on a perfused ex-vivo swine heart to image the coronary microcirculation.
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Ghigo N, Ramos-Palacios G, Bourquin C, Xing P, Wu A, Cortés N, Ladret H, Ikan L, Casanova C, Porée J, Sadikot A, Provost J. Dynamic Ultrasound Localization Microscopy Without ECG-Gating. ULTRASOUND IN MEDICINE & BIOLOGY 2024; 50:1436-1448. [PMID: 38969526 DOI: 10.1016/j.ultrasmedbio.2024.05.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 05/04/2024] [Accepted: 05/22/2024] [Indexed: 07/07/2024]
Abstract
OBJECTIVE Dynamic Ultrasound Localization Microscopy (DULM) has first been developed for non-invasive Pulsatility measurements in the rodent brain. DULM relies on the localization and tracking of microbubbles (MBs) injected into the bloodstream, to obtain highly resolved velocity and density cine-loops. Previous DULM techniques required ECG-gating, limiting its application to specific datasets, and increasing acquisition time. The objective of this study is to eliminate the need for ECG-gating in DULM experiments by introducing a motion-matching method for time registration. METHODS We developed a motion-matching algorithm based on tissue Doppler that leverages the cyclic tissue motion within the brain. Tissue Doppler was estimated for each group of frames in the acquisitions, at multiple locations identified as local maxima in the skin above the skull. Subsequently, each group of frames was time-registered to a reference group by delaying it based on the maximum correlation value between their respective tissue Doppler signals. This synchronization ensured that each group of frames aligned with the brain tissue motion of the reference group, and consequently, with its cardiac cycle. As a result, velocities of MBs could be averaged to retrieve flow velocity variations over time. RESULTS Initially validated in ECG-gated acquisitions in a rat model (n = 1), the proposed method was successfully applied in a mice model in 2D (n = 3) and in a feline model in 3D (n = 1). Performing time-registration with the proposed motion-matching method or by using ECG-gating leads to similar results. For the first time, dynamic velocity and density cine-loops were extracted without the need for any information on the animal ECG, and complex dynamic markers such as the Pulsatility index were estimated. CONCLUSION Results suggest that DULM can be performed without external gating, enabling the use of DULM on any ULM dataset where enough MBs are detectable. Time registration by motion-matching represents a significant advancement in DULM techniques, making DULM more accessible by simplifying its experimental complexity.
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Affiliation(s)
- Nin Ghigo
- Department of Engineering Physics, Polytechnique Montréal, Montréal, Quebec, Canada.
| | | | - Chloé Bourquin
- Department of Engineering Physics, Polytechnique Montréal, Montréal, Quebec, Canada
| | - Paul Xing
- Department of Engineering Physics, Polytechnique Montréal, Montréal, Quebec, Canada
| | - Alice Wu
- Department of Engineering Physics, Polytechnique Montréal, Montréal, Quebec, Canada
| | - Nelson Cortés
- School of Optometry, University of Montreal, Montréal, Quebec, Canada
| | - Hugo Ladret
- School of Optometry, University of Montreal, Montréal, Quebec, Canada; Institut de Neurosciences de la Timone, UMR 7289, CNRS and Aix-Marseille Université, Marseille, France
| | - Lamyae Ikan
- School of Optometry, University of Montreal, Montréal, Quebec, Canada
| | | | - Jonathan Porée
- Department of Engineering Physics, Polytechnique Montréal, Montréal, Quebec, Canada
| | - Abbas Sadikot
- Montreal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Jean Provost
- Department of Engineering Physics, Polytechnique Montréal, Montréal, Quebec, Canada; Montreal Heart Institute, Montréal, Quebec, Canada
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Zhang G, Hu X, Ren X, Zhou B, Li B, Li Y, Luo J, Liu X, Ta D. In vivo ultrasound localization microscopy for high-density microbubbles. ULTRASONICS 2024; 143:107410. [PMID: 39084108 DOI: 10.1016/j.ultras.2024.107410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 07/04/2024] [Accepted: 07/18/2024] [Indexed: 08/02/2024]
Abstract
Ultrasound Localization Microscopy (ULM) surpasses the constraints imposed by acoustic diffraction, achieving sub-wavelength resolution visualization of microvasculature through the precise localization of minute microbubbles (MBs). Nonetheless, the analysis of densely populated regions with overlapping MB point spread responses introduces significant localization errors, limiting the use of technique to low-concentration conditions. This raises a trade-off issue between localization efficiency and MB density. In this work, we present a new deep learning framework that combines Transformer and U-Net architectures, termed ULM-TransUNet. As a non-linear model, it is able to learn the complex data patterns of overlapping MBs in dense conditions for accurate localization. To evaluate the performance of ULM-TransUNet, a series of numerical simulations and in vivo experiments are carried out. Numerical simulation results indicate that ULM-TransUNet achieves high-quality ULM imaging, with improvements of 21.93 % in detection rate, 17.36 % in detection precision, and 20.53 % in detection sensitivity, compared to previous state-of-the-art deep learning (DL) method (e.g., ULM-UNet). For the in vivo experiments, ULM-TransUNet achieves the highest spatial resolution (9.4 μm) and rapid inference speed (26.04 ms/frame). Furthermore, it consistently detects more small vessels and resolves closely spaced vessels more effectively. The outcomes of this work imply that ULM-TransUNet can potentially enhance the microvascular imaging performance on high-density MB conditions.
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Affiliation(s)
- Gaobo Zhang
- Department of Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
| | - Xing Hu
- Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai 201907, China
| | - Xuan Ren
- Academy for Engineering and Technology, Fudan University, Shanghai 200438, China
| | - Boqian Zhou
- Academy for Engineering and Technology, Fudan University, Shanghai 200438, China
| | - Boyi Li
- Academy for Engineering and Technology, Fudan University, Shanghai 200438, China
| | - Yifang Li
- Academy for Engineering and Technology, Fudan University, Shanghai 200438, China
| | - Jianwen Luo
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Xin Liu
- Academy for Engineering and Technology, Fudan University, Shanghai 200438, China; State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200032, China.
| | - Dean Ta
- Department of Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China; Academy for Engineering and Technology, Fudan University, Shanghai 200438, China.
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Qiang Y, Huang W, Liang W, Liu R, Han X, Pan Y, Wang N, Yu Y, Zhang Z, Sun L, Qiu W. An adaptive spatiotemporal filter for ultrasound localization microscopy based on density canopy clustering. ULTRASONICS 2024; 144:107446. [PMID: 39213718 DOI: 10.1016/j.ultras.2024.107446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2024] [Revised: 07/07/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024]
Abstract
Ultrasound Localization Microscopy (ULM) facilitates structural and hemodynamic imaging of microvessels with a resolution of tens of micrometers. In ULM, the extraction of effective microbubble signals is crucial for image quality. Singular Value Decomposition (SVD) is currently the most prevalent method for microbubble signal extraction in ULM. Most existing ULM studies employ a fixed SVD filter threshold using empirical values which will lead to imaging quality degradation due to the insufficient separation of blood signals. In this study, we propose an adaptive and non-threshold SVD filter based on canopy-density clustering, termed DCC-SVD. This filter automatically classifies the components of the SVD based on the density of their spatiotemporal features, eliminating the need for parameter selection. In in vitro tube phantom, DCC-SVD demonstrated its ability to adaptive separation of blood and bubble signal at varying microbubble concentrations and flow rates. We compared the proposed DCC-SVD method with the Block-match 3D (BM3D) filter and a classical adaptive method called spatial similarity matrix (SSM), using concentration-variable in vivo rat brain data, as well as open-source rat kidney and mouse tumor datasets. The proposed DCC-SVD improved the global spatial resolution by approximately 4 μm from 30.39 μm to 26.02 μm. It also captured vessel structure absent in images obtained by other methods and yielded a smoother vessel intensity profile, making it a promising spatiotemporal filter for ULM imaging.
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Affiliation(s)
- Yu Qiang
- The Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China; The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Wenyue Huang
- The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Wenjie Liang
- The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Rong Liu
- The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xuan Han
- The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yue Pan
- The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Ningyuan Wang
- The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yanyan Yu
- Department of Biomedical Engineering, Shenzhen University, Shenzhen, China.
| | - Zhiqiang Zhang
- The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China.
| | - Lei Sun
- The Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
| | - Weibao Qiu
- The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China.
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Zhou J, Guo Y, Sun Q, Lin F, Jiang C, Xu K, Ta D. Transcranial ultrafast ultrasound Doppler imaging: A phantom study. ULTRASONICS 2024; 144:107430. [PMID: 39173276 DOI: 10.1016/j.ultras.2024.107430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 07/02/2024] [Accepted: 08/09/2024] [Indexed: 08/24/2024]
Abstract
Ultrafast ultrasound Doppler imaging facilitates the assessment of cerebral hemodynamics with high spatio-temporal resolution. However, the significant acoustic impedance mismatch between the skull and soft tissue results in phase aberrations, which can compromise the quality of transcranial imaging and introduce biases in velocity and direction quantification of blood flow. This paper proposed an aberration correction method that combines deep learning-based skull sound speed modelling with ray theory to realize transcranial plane-wave imaging and ultrafast Doppler imaging. The method was validated through phantom experiments using a linear array with a center frequency of 6.25 MHz, 128 elements, and a pitch of 0.3 mm. The results demonstrated an improvement in the imaging quality of intracranial targets when using the proposed method. After aberration correction, the average locating deviation decreased from 1.40 mm to 0.27 mm in the axial direction, from 0.50 mm to 0.20 mm in the lateral direction, and the average full-width-at-half-maximum (FWHM) decreased from 1.37 mm to 0.97 mm for point scatterers. For circular inclusions, the average contrast-to-noise ratio (CNR) improved from 8.1 dB to 11.0 dB, and the average eccentricity decreased from 0.36 to 0.26. Furthermore, the proposed method was applied to transcranial ultrafast Doppler flow imaging. The results showed a significant improvement in accuracy and quality for blood Doppler flow imaging. The results in the absence of the skull were considered as the reference, and the average normalized root-mean-square errors of the axial velocity component on the five selected axial profiles were reduced from 17.67% to 8.02% after the correction.
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Affiliation(s)
- Jiangjin Zhou
- Department of Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
| | - Yuanyang Guo
- Department of Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
| | - Qiandong Sun
- Department of Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
| | - Fanglue Lin
- Ultrasound BU, Wuhan United Imaging Healthcare Co., Ltd., Wuhan 430206, China
| | - Chen Jiang
- Yiwu Research Institute of Fudan University, Zhejiang 322000, China.
| | - Kailiang Xu
- Department of Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China; Yiwu Research Institute of Fudan University, Zhejiang 322000, China; PodaMed Medical Technology Co., Ltd., Shanghai 200433, China.
| | - Dean Ta
- Department of Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China; Yiwu Research Institute of Fudan University, Zhejiang 322000, China
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Zhang C, Lei S, Ma A, Wang B, Wang S, Liu J, Shang D, Zhang Q, Li Y, Zheng H, Ma T. Evaluation of tumor microvasculature with 3D ultrasound localization microscopy based on 2D matrix array. Eur Radiol 2024; 34:5250-5259. [PMID: 38265473 DOI: 10.1007/s00330-023-10039-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 04/26/2023] [Accepted: 05/22/2023] [Indexed: 01/25/2024]
Abstract
OBJECTIVE Evaluation of tumor microvascular morphology is of great significance in tumor diagnosis, therapeutic effect prediction, and surgical planning. Recently, two-dimensional ultrasound localization microscopy (2DULM) has demonstrated its superiority in the field of microvascular imaging. However, it suffers from planar dependence and is unintuitive. We propose a novel three-dimensional ultrasound localization microscopy (3DULM) to avoid these limitations. METHODS We investigated 3DULM based on a 2D array for tumor microvascular imaging. After intravenous injection of contrast agents, all elements of the 2D array transmit and receive signals to ensure a high and stable frame rate. Microbubble signal extraction, filtering, positioning, tracking, and other processing were used to obtain a 3D vascular map, flow velocity, and flow direction. To verify the effectiveness of 3DULM, it was validated on double helix tubes and rabbit VX2 tumors. Cisplatin was used to verify the ability of 3DULM to detect microvascular changes during tumor treatment. RESULTS In vitro, the sizes measured by 3DULM at 3 mm and 13 mm were 178 μ m and 182 μ m , respectively. In the rabbit tumors, we acquired 9000 volumes to reveal vessels about 30 μ m in diameter, which surpasses the diffraction limit of ultrasound in traditional ultrasound imaging, and the results matched with micro-angiography. In addition, there were significant changes in vascular density and curvature between the treatment and control groups. CONCLUSIONS The effectiveness of 3DULM was verified in vitro and in vivo. Hence, 3DULM may have potential applications in tumor diagnosis, tumor treatment evaluation, surgical protocol guidance, and cardiovascular disease. CLINICAL RELEVANCE STATEMENT 3D ultrasound localization microscopy is highly sensitive to microvascular changes; thus, it has clinical potential for tumor diagnosis and treatment evaluation. KEY POINTS • 3D ultrasound localization microscopy is demonstrated on double helix tubes and rabbit VX2 tumors. • 3D ultrasound localization microscopy can reveal vessels about 30 μ m in diameter-far smaller than traditional ultrasound. • This form of imaging has potential applications in tumor diagnosis, tumor treatment evaluation, surgical protocol guidance, and cardiovascular disease.
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Affiliation(s)
- Changlu Zhang
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- University of the Chinese Academy of Sciences, Beijing, 100000, China
| | - Shuang Lei
- School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Aiqing Ma
- Nanomedicine and Nanoformulations Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Bing Wang
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Shuo Wang
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Jiamei Liu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Dongqing Shang
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- University of the Chinese Academy of Sciences, Beijing, 100000, China
| | - Qi Zhang
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Yongchuan Li
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Hairong Zheng
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- University of the Chinese Academy of Sciences, Beijing, 100000, China
| | - Teng Ma
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
- University of the Chinese Academy of Sciences, Beijing, 100000, China.
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Chen H, Mirg S, Gaddale P, Agrawal S, Li M, Nguyen V, Xu T, Li Q, Liu J, Tu W, Liu X, Drew PJ, Zhang N, Gluckman BJ, Kothapalli S. Multiparametric Brain Hemodynamics Imaging Using a Combined Ultrafast Ultrasound and Photoacoustic System. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2401467. [PMID: 38884161 PMCID: PMC11336909 DOI: 10.1002/advs.202401467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 04/25/2024] [Indexed: 06/18/2024]
Abstract
Studying brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help gain new insights into the mechanisms of neuro- diseases and -disorders. Nonetheless, this task is challenging, primarily due to the complexity of neurovascular coupling, which encompasses interdependent hemodynamic parameters including cerebral blood volume (CBV), cerebral blood flow (CBF), and cerebral oxygen saturation (SO2). The current brain imaging technologies exhibit inherent limitations in resolution, sensitivity, and imaging depth, restricting their capacity to comprehensively capture the intricacies of cerebral functions. To address this, a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform is reported, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map individual dynamics of CBV, CBF, and SO2 as well as contrast agent enhanced brain imaging at high spatiotemporal resolutions. Following systematic characterization, the fUSPA system is applied to study brain-wide cerebrovascular reactivity (CVR) at single-vessel resolution via relative changes in CBV, CBF, and SO2 in response to hypercapnia stimulation. These results show that cortical veins and arteries exhibit differences in CVR in the stimulated state and consistent anti-correlation in CBV oscillations during the resting state, demonstrating the multiparametric fUSPA system's unique capabilities in investigating complex mechanisms of brain functions.
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Affiliation(s)
- Haoyang Chen
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Shubham Mirg
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Prameth Gaddale
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Sumit Agrawal
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Menghan Li
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Van Nguyen
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Tianbao Xu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Qiong Li
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Jinyun Liu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Wenyu Tu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Xiao Liu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Institute for Computational and Data SciencesThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Patrick J. Drew
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of Engineering Science and MechanicsThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of BiologyThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of NeurosurgeryThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Nanyin Zhang
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Bruce J. Gluckman
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of Engineering Science and MechanicsThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of NeurosurgeryThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Sri‐Rajasekhar Kothapalli
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Penn State Cancer InstituteThe Pennsylvania State UniversityHersheyPA17033USA
- Graduate Program in AcousticsThe Pennsylvania State UniversityUniversity ParkPA16802USA
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10
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Naji MA, Taghavi I, Schou M, Praesius SK, Hansen LN, Panduro NS, Andersen SB, Sogaard SB, Gundlach C, Kjer HM, Tomov BG, Thomsen EV, Nielsen MB, Larsen NB, Dahl AB, Sorensen CM, Jensen JA. Super-Resolution Ultrasound Imaging Using the Erythrocytes-Part II: Velocity Images. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2024; 71:945-959. [PMID: 38857146 DOI: 10.1109/tuffc.2024.3411795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Abstract
Super-resolution ultrasound imaging using the erythrocytes (SURE) has recently been introduced. The method uses erythrocytes as targets instead of fragile microbubbles (MBs). The abundance of erythrocyte scatterers makes it possible to acquire SURE data in just a few seconds compared with several minutes in ultrasound localization microscopy (ULM) using MBs. A high number of scatterers can reduce the acquisition time; however, the tracking of uncorrelated and high-density scatterers is quite challenging. This article hypothesizes that it is possible to detect and track erythrocytes as targets to obtain vascular flow images. A SURE tracking pipeline is used with modules for beamforming, recursive synthetic aperture (SA) imaging, motion estimation, echo canceling, peak detection, and recursive nearest-neighbor (NN) tracker. The SURE tracking pipeline is capable of distinguishing the flow direction and separating tubes of a simulated Field II phantom with 125-25- [Formula: see text] wall-to-wall tube distances, as well as a 3-D printed hydrogel micr-flow phantom with 100-60- [Formula: see text] wall-to-wall channel distances. The comparison of an in vivo SURE scan of a Sprague-Dawley rat kidney with ULM and micro-computed tomography (CT) scans with voxel sizes of 26.5 and [Formula: see text] demonstrated consistent findings. A microvascular structure composed of 16 vessels exhibited similarities across all imaging modalities. The flow direction and velocity profiles in the SURE scan were found to be concordant with those from ULM.
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11
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Lerendegui M, Riemer K, Papageorgiou G, Wang B, Arthur L, Chavignon A, Zhang T, Couture O, Huang P, Ashikuzzaman M, Dencks S, Dunsby C, Helfield B, Jensen JA, Lisson T, Lowerison MR, Rivaz H, Samir AE, Schmitz G, Schoen S, van Sloun R, Song P, Stevens T, Yan J, Sboros V, Tang MX. ULTRA-SR Challenge: Assessment of Ultrasound Localization and TRacking Algorithms for Super-Resolution Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2970-2987. [PMID: 38607705 DOI: 10.1109/tmi.2024.3388048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/14/2024]
Abstract
With the widespread interest and uptake of super-resolution ultrasound (SRUS) through localization and tracking of microbubbles, also known as ultrasound localization microscopy (ULM), many localization and tracking algorithms have been developed. ULM can image many centimeters into tissue in-vivo and track microvascular flow non-invasively with sub-diffraction resolution. In a significant community effort, we organized a challenge, Ultrasound Localization and TRacking Algorithms for Super-Resolution (ULTRA-SR). The aims of this paper are threefold: to describe the challenge organization, data generation, and winning algorithms; to present the metrics and methods for evaluating challenge entrants; and to report results and findings of the evaluation. Realistic ultrasound datasets containing microvascular flow for different clinical ultrasound frequencies were simulated, using vascular flow physics, acoustic field simulation and nonlinear bubble dynamics simulation. Based on these datasets, 38 submissions from 24 research groups were evaluated against ground truth using an evaluation framework with six metrics, three for localization and three for tracking. In-vivo mouse brain and human lymph node data were also provided, and performance assessed by an expert panel. Winning algorithms are described and discussed. The publicly available data with ground truth and the defined metrics for both localization and tracking present a valuable resource for researchers to benchmark algorithms and software, identify optimized methods/software for their data, and provide insight into the current limits of the field. In conclusion, Ultra-SR challenge has provided benchmarking data and tools as well as direct comparison and insights for a number of the state-of-the art localization and tracking algorithms.
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12
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Kiessling F. [Experimental Environment in Radiology: Sustainable Research]. ROFO-FORTSCHR RONTG 2024; 196:787-793. [PMID: 38479410 DOI: 10.1055/a-2268-0707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/19/2024]
Abstract
Research requires large sums of money that are indirectly provided by taxpayers. It is therefore important that research is sustainable and does not just serve the career development of individuals. The aim of this article is to discuss what sustainable research in radiology is, how it can be organised and, above all, to show that it is possible.There are various approaches to achieving sustainability, ranging from purely gaining knowledge to translated devices and contrast agents, and to new clinical applications. The first step is to clarify exactly what is intended to be achieved with the research and critically weigh up the novelty value and the expected impact. This should be followed by careful, long-term planning of the project over a period of 5-15 years with the definition of clear sub-steps. Securing funding is just as important here as regular communication of the results. It often makes sense to involve the regulatory authorities and commercialisation partners in the project at an early stage.Academic radiology should not limit itself to serving as a test platform for imaging devices and contrast agents from industry, but should try to realise its own ideas and developments. Many academic centres around the world have shown that this is possible. Examples from my own research, particularly in relation to the development and translation of super-resolution ultrasound imaging and the development of diagnostics and nanopharmaceuticals, are explained in this article and challenges at various stages of development are discussed. Young radiologists are encouraged to set bigger and more long-term goals in order to influence and develop our field in a sustainable way. · Sustainable research requires creativity and careful planning. · Sustainable research can start at several stages of the technical readiness level. · Long-term planning of the overall concept (5-15 years) with clear intermediate steps is essential. · Cooperation with industry is often useful. · Acquisition of third-party funding must be ensured at the same time.
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Affiliation(s)
- Fabian Kiessling
- Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
- Aachen site, Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
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13
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Bodard S, Denis L, Chabouh G, Battaglia J, Anglicheau D, Hélénon O, Correas JM, Couture O. Visualization of Renal Glomeruli in Human Native Kidneys With Sensing Ultrasound Localization Microscopy. Invest Radiol 2024; 59:561-568. [PMID: 38214557 DOI: 10.1097/rli.0000000000001061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
OBJECTIVES Kidney diseases significantly impact individuals' quality of life and strongly reduce life expectancy. Glomeruli play a crucial role in kidney function. Current imaging techniques cannot visualize them due to their small size. Sensing ultrasound localization microscopy (sULM) has shown promising results for visualizing in vivo the glomeruli of human kidney grafts. This study aimed to evaluate the ability of sULM to visualize glomeruli in vivo in native human kidneys despite their depth and a shorter duration of ultrasound acquisition limited by the period of the patient's apnea. Sensing ultrasound localization microscopy parameters in native kidneys and kidney grafts and their consequence regarding glomeruli detection were also compared. MATERIALS AND METHODS Exploration by sULM was conducted in 15 patients with native kidneys and 5 with kidney allografts. Glomeruli were counted using a normalized distance metric projected onto sULM density maps. The difference in the acquisition time, the kidney depth, and the frame rate between native kidneys and kidney grafts and their consequence regarding glomeruli detection were assessed. RESULTS Glomerular visualization was achieved in 12 of 15 patients with native kidneys. It failed due to impossible breath-holding for 2 patients and a too-deep kidney for 1 patient. Sensing ultrasound localization microscopy found 16 glomeruli per square centimeter in the native kidneys (6-31) and 33 glomeruli per square centimeter in kidney transplant patients (18-55). CONCLUSIONS This study demonstrated that sULM can visualize glomeruli in native human kidneys in vivo. The proposed method may have many hypothetical applications, including biomarker development, assisting biopsy, or potentially avoiding it. It establishes a framework for improving the detection of local microstructural pathology, influencing the evaluation of allografts, and facilitating disease monitoring in the native kidney.
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Affiliation(s)
- Sylvain Bodard
- From the Service d'Imagerie Adulte, Hôpital Necker Enfants Malades, AP-HP, Paris, France (S.B., O.H., J.-M.C.); Laboratoire d'Imagerie Biomédicale, Sorbonne Université, CNRS, INSERM, Paris, France (S.B., L.D., G.C., J.B., J.-M.C., O.C.); Université de Paris Cité, Paris, France (S.B., D.A., O.H., J.-M.C.); and Service de Néphrologie-Transplantation Rénale Adulte, Hôpital Necker Enfants Malades, AP-HP, Paris, France (D.A.)
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14
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Glück C, Zhou Q, Droux J, Chen Z, Glandorf L, Wegener S, Razansky D, Weber B, El Amki M. Pia-FLOW: Deciphering hemodynamic maps of the pial vascular connectome and its response to arterial occlusion. Proc Natl Acad Sci U S A 2024; 121:e2402624121. [PMID: 38954543 PMCID: PMC11252916 DOI: 10.1073/pnas.2402624121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 06/04/2024] [Indexed: 07/04/2024] Open
Abstract
The pial vasculature is the sole source of blood supply to the neocortex. The brain is contained within the skull, a vascularized bone marrow with a unique anatomical connection to the brain meninges. Recent developments in tissue clearing have enabled detailed mapping of the entire pial and calvarial vasculature. However, what are the absolute flow rate values of those vascular networks? This information cannot accurately be retrieved with the commonly used bioimaging methods. Here, we introduce Pia-FLOW, a unique approach based on large-scale transcranial fluorescence localization microscopy, to attain hemodynamic imaging of the whole murine pial and calvarial vasculature at frame rates up to 1,000 Hz and spatial resolution reaching 5.4 µm. Using Pia-FLOW, we provide detailed maps of flow velocity, direction, and vascular diameters which can serve as ground-truth data for further studies, advancing our understanding of brain fluid dynamics. Furthermore, Pia-FLOW revealed that the pial vascular network functions as one unit for robust allocation of blood after stroke.
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Affiliation(s)
- Chaim Glück
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich8057, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich8057, Switzerland
| | - Quanyu Zhou
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich8057, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich8092, Switzerland
| | - Jeanne Droux
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich8057, Switzerland
- Department of Neurology, University Hospital and University of Zurich, Zurich8091, Switzerland
| | - Zhenyue Chen
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich8057, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich8092, Switzerland
| | - Lukas Glandorf
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich8057, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich8092, Switzerland
| | - Susanne Wegener
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich8057, Switzerland
- Department of Neurology, University Hospital and University of Zurich, Zurich8091, Switzerland
| | - Daniel Razansky
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich8057, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich8057, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich8092, Switzerland
| | - Bruno Weber
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich8057, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich8057, Switzerland
| | - Mohamad El Amki
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich8057, Switzerland
- Department of Neurology, University Hospital and University of Zurich, Zurich8091, Switzerland
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15
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Iyer RR, Applegate CC, Arogundade OH, Bangru S, Berg IC, Emon B, Porras-Gomez M, Hsieh PH, Jeong Y, Kim Y, Knox HJ, Moghaddam AO, Renteria CA, Richard C, Santaliz-Casiano A, Sengupta S, Wang J, Zambuto SG, Zeballos MA, Pool M, Bhargava R, Gaskins HR. Inspiring a convergent engineering approach to measure and model the tissue microenvironment. Heliyon 2024; 10:e32546. [PMID: 38975228 PMCID: PMC11226808 DOI: 10.1016/j.heliyon.2024.e32546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 05/22/2024] [Accepted: 06/05/2024] [Indexed: 07/09/2024] Open
Abstract
Understanding the molecular and physical complexity of the tissue microenvironment (TiME) in the context of its spatiotemporal organization has remained an enduring challenge. Recent advances in engineering and data science are now promising the ability to study the structure, functions, and dynamics of the TiME in unprecedented detail; however, many advances still occur in silos that rarely integrate information to study the TiME in its full detail. This review provides an integrative overview of the engineering principles underlying chemical, optical, electrical, mechanical, and computational science to probe, sense, model, and fabricate the TiME. In individual sections, we first summarize the underlying principles, capabilities, and scope of emerging technologies, the breakthrough discoveries enabled by each technology and recent, promising innovations. We provide perspectives on the potential of these advances in answering critical questions about the TiME and its role in various disease and developmental processes. Finally, we present an integrative view that appreciates the major scientific and educational aspects in the study of the TiME.
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Affiliation(s)
- Rishyashring R. Iyer
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Catherine C. Applegate
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Opeyemi H. Arogundade
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Sushant Bangru
- Department of Biochemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Ian C. Berg
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Bashar Emon
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Marilyn Porras-Gomez
- Department of Materials Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Pei-Hsuan Hsieh
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Yoon Jeong
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Yongdeok Kim
- Department of Materials Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Hailey J. Knox
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Amir Ostadi Moghaddam
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Carlos A. Renteria
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Craig Richard
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Ashlie Santaliz-Casiano
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Sourya Sengupta
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Jason Wang
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Samantha G. Zambuto
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Maria A. Zeballos
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Marcia Pool
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Rohit Bhargava
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Chemical and Biochemical Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- NIH/NIBIB P41 Center for Label-free Imaging and Multiscale Biophotonics (CLIMB), University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - H. Rex Gaskins
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Animal Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Biomedical and Translational Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Pathobiology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
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16
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Tang L, Li Q, Xiao F, Gao Y, Zhang P, Cheng G, Wang L, Lu C, Ge M, Hu L, Xiao T, Yin Z, Yan K, Zhou W. Neurosonography: Shaping the future of neuroprotection strategies in extremely preterm infants. Heliyon 2024; 10:e31742. [PMID: 38845994 PMCID: PMC11154624 DOI: 10.1016/j.heliyon.2024.e31742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 05/13/2024] [Accepted: 05/21/2024] [Indexed: 06/09/2024] Open
Abstract
This review aims to explore the current application of Cranial Ultrasound Screening (CUS) in the diagnosis and treatment of brain diseases in extremely preterm infants. It also discusses the potential role of emerging ultrasound-derived technologies such as Super Microvascular Structure Imaging (SMI), Shear Wave Elastography (SWE), Ultrafast Doppler Ultrasound (UfD), and 3D ventricular volume assessment and automated segmentation techniques in clinical practice. A systematic search of medical databases was conducted using the keywords "(preterm OR extremely preterm OR extremely low birth weight) AND (ultrasound OR ultrasound imaging) AND (neurodevelopment OR brain development OR brain diseases OR brain injury OR neuro*)" to identify relevant literature. The titles, abstracts, and full texts of the identified articles were carefully reviewed to determine their relevance to the research topic. CUS offers unique advantages in early screening and monitoring of brain diseases in extremely preterm infants, as it can be performed at the bedside without the need for anesthesia or special monitoring. This technique facilitates early detection and intervention of conditions such as intraventricular hemorrhage, white matter injury, hydrocephalus, and hypoxic-ischemic injury in critically ill preterm infants. Continuous refinement of the screening and follow-up processes provides reliable clinical decision-making support for healthcare professionals and parents. Emerging ultrasound technologies, such as SWE, SMI, and UfD, are being explored to provide more accurate and in-depth understanding of brain diseases in extremely preterm infants. SWE has demonstrated its effectiveness in assessing the elasticity of neonatal brain tissue, aiding in the localization and quantification of potential brain injuries. SMI can successfully identify microvascular structures in the brain, offering a new perspective on neurologic diseases. UfD provides a high-sensitivity and quantitative imaging method for the prevention and treatment of neonatal brain diseases by detecting subtle changes in red blood cell movement and accurately assessing the status and progression of brain diseases. CUS and its emerging technologies have significant applications in the diagnosis and treatment of brain diseases in extremely preterm infants. Future research aims to address current technical challenges, optimize and enhance the clinical decision-making capabilities related to brain development, and improve the prevention and treatment outcomes of brain diseases in extremely preterm infants.
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Affiliation(s)
- Lukun Tang
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
- Kunming Medical University Affiliated Dehong Hospital, Dehong, Yunnan, China
- Graduate School, Kunming Medical University, Kunming, Yunnan, China
| | - Qi Li
- Department of Intensive Care Medicine, The Sixth Medical Center of PLA General Hospital, China
| | - Feifan Xiao
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Yanyan Gao
- Department of Ultrasound, Children's Hospital of Fudan University, China
| | - Peng Zhang
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Guoqiang Cheng
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Laishuan Wang
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Chunmei Lu
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
- Department of Nursing, Children's Hospital of Fudan University, China
| | - Mengmeng Ge
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Liyuan Hu
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Tiantian Xiao
- Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Zhaoqing Yin
- Kunming Medical University Affiliated Dehong Hospital, Dehong, Yunnan, China
- Graduate School, Kunming Medical University, Kunming, Yunnan, China
| | - Kai Yan
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Wenhao Zhou
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
- Key Laboratory of Neonatology, National Health Care Commission, Shanghai, China
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17
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Nyúl-Tóth Á, Negri S, Sanford M, Jiang R, Patai R, Budda M, Petersen B, Pinckard J, Chandragiri SS, Shi H, Reyff Z, Ballard C, Gulej R, Csik B, Ferrier J, Balasubramanian P, Yabluchanskiy A, Cleuren A, Conley S, Ungvari Z, Csiszar A, Tarantini S. Novel intravital approaches to quantify deep vascular structure and perfusion in the aging mouse brain using ultrasound localization microscopy (ULM). J Cereb Blood Flow Metab 2024:271678X241260526. [PMID: 38867576 DOI: 10.1177/0271678x241260526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Abstract
Intra-vital visualization of deep cerebrovascular structures and blood flow in the aging brain has been a difficult challenge in the field of neurovascular research, especially when considering the key role played by the cerebrovasculature in the pathogenesis of both vascular cognitive impairment and dementia (VCID) and Alzheimer's disease (AD). Traditional imaging methods face difficulties with the thicker skull of older brains, making high-resolution imaging and cerebral blood flow (CBF) assessment challenging. However, functional ultrasound (fUS) imaging, an emerging non-invasive technique, provides real-time CBF insights with notable spatial-temporal resolution. This study introduces an enhanced longitudinal fUS method for aging brains. Using elderly (24-month C57BL/6) mice, we detail replacing the skull with a polymethylpentene window for consistent fUS imaging over extended periods. Ultrasound localization mapping (ULM), involving the injection of a microbubble (<<10 μm) suspension allows for recording of high-resolution microvascular vessels and flows. ULM relies on the localization and tracking of single circulating microbubbles in the blood flow. A FIJI-based analysis interprets these high-quality ULM visuals. Testing on older mouse brains, our method successfully unveils intricate vascular specifics even in-depth, showcasing its utility for longitudinal studies that require ongoing evaluations of CBF and vascular aspects in aging-focused research.
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Affiliation(s)
- Ádám Nyúl-Tóth
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
| | - Sharon Negri
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
| | - Madison Sanford
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
| | - Raymond Jiang
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Roland Patai
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Madeline Budda
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Cellular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Benjamin Petersen
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Jessica Pinckard
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Cellular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Siva Sai Chandragiri
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Helen Shi
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Zeke Reyff
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Cade Ballard
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Rafal Gulej
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Boglarka Csik
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
| | | | - Priya Balasubramanian
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Andriy Yabluchanskiy
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
| | - Audrey Cleuren
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Shannon Conley
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Cellular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Zoltan Ungvari
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
- Department of Public Health, Semmelweis University, Semmelweis University, Budapest, Hungary
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Anna Csiszar
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
| | - Stefano Tarantini
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
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18
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Yan J, Huang B, Tonko J, Toulemonde M, Hansen-Shearer J, Tan Q, Riemer K, Ntagiantas K, Chowdhury RA, Lambiase PD, Senior R, Tang MX. Transthoracic ultrasound localization microscopy of myocardial vasculature in patients. Nat Biomed Eng 2024; 8:689-700. [PMID: 38710839 PMCID: PMC11250254 DOI: 10.1038/s41551-024-01206-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 03/30/2024] [Indexed: 05/08/2024]
Abstract
Myocardial microvasculature and haemodynamics are indicative of potential microvascular diseases for patients with symptoms of coronary heart disease in the absence of obstructive coronary arteries. However, imaging microvascular structure and flow within the myocardium is challenging owing to the small size of the vessels and the constant movement of the patient's heart. Here we show the feasibility of transthoracic ultrasound localization microscopy for imaging myocardial microvasculature and haemodynamics in explanted pig hearts and in patients in vivo. Through a customized data-acquisition and processing pipeline with a cardiac phased-array probe, we leveraged motion correction and tracking to reconstruct the dynamics of microcirculation. For four patients, two of whom had impaired myocardial function, we obtained super-resolution images of myocardial vascular structure and flow using data acquired within a breath hold. Myocardial ultrasound localization microscopy may facilitate the understanding of myocardial microcirculation and the management of patients with cardiac microvascular diseases.
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Affiliation(s)
- Jipeng Yan
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK
| | - Biao Huang
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK
| | - Johanna Tonko
- Institute of Cardiovascular Science, University College London, London, UK
| | - Matthieu Toulemonde
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK
| | - Joseph Hansen-Shearer
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK
| | - Qingyuan Tan
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK
| | - Kai Riemer
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK
| | | | - Rasheda A Chowdhury
- Faculty of Medicine, National Heart and Lung Institute, Imperial College London, London, UK
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London, UK
| | - Roxy Senior
- Faculty of Medicine, National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton Hospital, London, UK
- Northwick Park Hospital, Harrow, UK
| | - Meng-Xing Tang
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK.
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19
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Hoyt K. Super-Resolution Ultrasound Imaging for Monitoring the Therapeutic Efficacy of a Vascular Disrupting Agent in an Animal Model of Breast Cancer. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2024; 43:1099-1107. [PMID: 38411352 DOI: 10.1002/jum.16438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/01/2024] [Accepted: 02/10/2024] [Indexed: 02/28/2024]
Abstract
OBJECTIVE Evaluate the use of super-resolution ultrasound (SRUS) imaging for the early detection of tumor response to treatment using a vascular-disrupting agent (VDA). METHODS A population of 28 female nude athymic mice (Charles River Laboratories) were implanted with human breast cancer cells (MDA-MB-231, ATCC) in the mammary fat pad and allowed to grow. Ultrasound imaging was performed using a Vevo 3100 scanner (FUJIFILM VisualSonics Inc) equipped with the MX250 linear array transducer immediately before and after receiving bolus injections of a microbubble (MB) contrast agent (Definity, Lantheus Medical Imaging) via the tail vein. Following baseline ultrasound imaging, VDA drug (combretastatin A4 phosphate, CA4P, Sigma Aldrich) or control saline was injected via the placed catheter. After 4 or 24 hours, repeat ultrasound imaging along the same tumor cross-section occurred. Direct intratumoral pressure measurements were obtained using a calibrated sensor. All raw ultrasound data were saved for offline processing and SRUS image reconstruction using custom MATLAB software (MathWorks Inc). From a region encompassing the tumor space and the entire postprocessed ultrasound image sequence, time MB count (TMC) curves were generated in addition to traditional SRUS maps reflecting MB enumeration at each pixel location. Peak enhancement (PE) and wash-in rate (WIR) were extracted from these TMC curves. At termination, intratumoral microvessel density (MVD) was quantified using tomato lectin labeling of patent blood vessels. RESULTS SRUS images exhibited a clear difference between control and treated tumors. While there was no difference in any group parameters at baseline (0 hour, P > .09), both SRUS-derived PE and WIR measurements in tumors treated with VDA exhibited significant decreases by 4 (P = .03 and P = .05, respectively) and 24 hours (P = .02 and P = .01, respectively), but not in control group tumors (P > .22). Similarly, SRUS derived microvascular maps were not different at baseline (P = .81), but measures of vessel density were lower in treated tumors at both 4 and 24 hours (P < .04). An inverse relationship between intratumoral pressure and both PE and WIR parameters were found in control tumors (R2 > .09, P < .03). CONCLUSION SRUS imaging is a new modality for assessing tumor response to treatment using a VDA.
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Affiliation(s)
- Kenneth Hoyt
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas, USA
- Department of Small Animal Clinical Sciences, Texas A&M University, College Station, Texas, USA
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20
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Xia S, Zheng Y, Hua Q, Wen J, Luo X, Yan J, Bai B, Dong Y, Zhou J. Super-resolution ultrasound and microvasculomics: a consensus statement. Eur Radiol 2024:10.1007/s00330-024-10796-3. [PMID: 38811389 DOI: 10.1007/s00330-024-10796-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 02/26/2024] [Accepted: 03/27/2024] [Indexed: 05/31/2024]
Abstract
This is a summary of a consensus statement on the introduction of "Ultrasound microvasculomics" produced by The Chinese Artificial Intelligence Alliance for Thyroid and Breast Ultrasound. The evaluation of microvessels is a very important part for the assessment of diseases. Super-resolution ultrasound (SRUS) microvascular imaging surpasses traditional ultrasound imaging in the morphological and functional analysis of microcirculation. SRUS microvascular imaging relies on contrast microbubbles to gain sensitivity to microvessels and improves the spatial resolution of ultrasound blood flow imaging for a more detailed depiction of vascular structures and hemodynamics. This method has been applied in preclinical animal models and pilot clinical studies, involving areas including neurology, oncology, nephrology, and cardiology. However, the current quantitative parameters of SRUS images are not enough for precise evaluation of microvessels. Therefore, by employing omics methods, more quantification indicators can be obtained, enabling a more precise and personalized assessment of microvascular status. Ultrasound microvasculomics - a high-throughput extraction of image features from SRUS images - is one novel approach that holds great promise but needs further validation in both bench and clinical settings. CLINICAL RELEVANCE STATEMENT: Super-resolution Ultrasound (SRUS) blood flow imaging improves spatial resolution. Ultrasound microvasculomics is possible to acquire high-throughput information of features from SRUS images. It provides more precise and abundant micro-blood flow information in clinical medicine. KEY POINTS: This consensus statement reviews the development and application of super-resolution ultrasound (SRUS). The shortcomings of the current quantification indicators of SRUS and strengths of the omics methodology are addressed. "Ultrasound microvasculomics" is introduced for a high-throughput extraction of image features from SRUS images.
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Affiliation(s)
- ShuJun Xia
- Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Er Road, 200025, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, 227 Chongqing South Road, 200025, Shanghai, China
| | - YuHang Zheng
- Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Er Road, 200025, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, 227 Chongqing South Road, 200025, Shanghai, China
| | - Qing Hua
- Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Er Road, 200025, Shanghai, China
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, 227 Chongqing South Road, 200025, Shanghai, China
| | - Jing Wen
- Department of Medical Ultrasound, Affiliated Hospital of Guizhou Medical University, 550001, Guiyang, China
| | - XiaoMao Luo
- Department of Medical Ultrasound, Yunnan Cancer Hospital & The Third Affiliated Hospital of Kunming Medical University, 650118, Kunming, China
| | - JiPing Yan
- Department of Ultrasound, Shanxi Provincial People's Hospital, 31th Shuangta Street, 030012, Taiyuan, China
| | - BaoYan Bai
- Department of Ultrasound, Affiliated Hospital of Yan 'an University, 43 North Street, Baota District, 716000, Yan'an, China
| | - YiJie Dong
- Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Er Road, 200025, Shanghai, China.
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, 227 Chongqing South Road, 200025, Shanghai, China.
| | - JianQiao Zhou
- Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Er Road, 200025, Shanghai, China.
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, 227 Chongqing South Road, 200025, Shanghai, China.
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21
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Lerendegui M, Yan J, Stride E, Dunsby C, Tang MX. Understanding the effects of microbubble concentration on localization accuracy in super-resolution ultrasound imaging. Phys Med Biol 2024; 69:115020. [PMID: 38588678 DOI: 10.1088/1361-6560/ad3c09] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 04/08/2024] [Indexed: 04/10/2024]
Abstract
Super-resolution ultrasound (SRUS) through localising and tracking of microbubbles (MBs) can achieve sub-wavelength resolution for imaging microvascular structure and flow dynamics in deep tissuein vivo. The technique assumes that signals from individual MBs can be isolated and localised accurately, but this assumption starts to break down when the MB concentration increases and the signals from neighbouring MBs start to interfere. The aim of this study is to gain understanding of the effect of MB-MB distance on ultrasound images and their localisation. Ultrasound images of two MBs approaching each other were synthesised by simulating both ultrasound field propagation and nonlinear MB dynamics. Besides the distance between MBs, a range of other influencing factors including MB size, ultrasound frequency, transmit pulse sequence, pulse amplitude and localisation methods were studied. The results show that as two MBs approach each other, the interference fringes can lead to significant and oscillating localisation errors, which are affected by both the MB and imaging parameters. When modelling a clinical linear array probe operating at 6 MHz, localisation errors between 20 and 30μm (∼1/10 wavelength) can be generated when MBs are ∼500μm (2 wavelengths or ∼1.7 times the point spread function (PSF)) away from each other. When modelling a cardiac probe operating at 1.5 MHz, the localisation errors were as high as 200μm (∼1/5 wavelength) even when the MBs were more than 10 wavelengths apart (2.9 times the PSF). For both frequencies, at smaller separation distances, the two MBs were misinterpreted as one MB located in between the two true positions. Cross-correlation or Gaussian fitting methods were found to generate slightly smaller localisation errors than centroiding. In conclusion, caution should be taken when generating and interpreting SRUS images obtained using high agent concentration with MBs separated by less than 1.7 to 3 times the PSF, as significant localisation errors can be generated due to interference between neighbouring MBs.
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Affiliation(s)
- Marcelo Lerendegui
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Jipeng Yan
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Eleanor Stride
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | | | - Meng-Xing Tang
- Department of Bioengineering, Imperial College London, London, United Kingdom
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22
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Agyeman KA, Lee DJ, Russin J, Kreydin EI, Choi W, Abedi A, Lo YT, Cavaleri J, Wu K, Edgerton VR, Liu C, Christopoulos VN. Functional ultrasound imaging of the human spinal cord. Neuron 2024; 112:1710-1722.e3. [PMID: 38458198 DOI: 10.1016/j.neuron.2024.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 11/03/2023] [Accepted: 02/15/2024] [Indexed: 03/10/2024]
Abstract
Utilizing the first in-human functional ultrasound imaging (fUSI) of the spinal cord, we demonstrate the integration of spinal functional responses to electrical stimulation. We record and characterize the hemodynamic responses of the spinal cord to a neuromodulatory intervention commonly used for treating pain and increasingly used for the restoration of sensorimotor and autonomic function. We found that the hemodynamic response to stimulation reflects a spatiotemporal modulation of the spinal cord circuitry not previously recognized. Our analytical capability offers a mechanism to assess blood flow changes with a new level of spatial and temporal precision in vivo and demonstrates that fUSI can decode the functional state of spinal networks in a single trial, which is of fundamental importance for developing real-time closed-loop neuromodulation systems. This work is a critical step toward developing a vital technique to study spinal cord function and effects of clinical neuromodulation.
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Affiliation(s)
- K A Agyeman
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA
| | - D J Lee
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA; Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - J Russin
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA; Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - E I Kreydin
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA; Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - W Choi
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - A Abedi
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Y T Lo
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore
| | - J Cavaleri
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - K Wu
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - V R Edgerton
- Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA.
| | - C Liu
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA; Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.
| | - V N Christopoulos
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA; Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neuroscience Graduate Program, University of California Riverside, Riverside, CA, USA.
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23
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Riemer K, Tan Q, Morse S, Bau L, Toulemonde M, Yan J, Zhu J, Wang B, Taylor L, Lerendegui M, Wu Q, Stride E, Dunsby C, Weinberg PD, Tang MX. 3D Acoustic Wave Sparsely Activated Localization Microscopy With Phase Change Contrast Agents. Invest Radiol 2024; 59:379-390. [PMID: 37843819 DOI: 10.1097/rli.0000000000001033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
OBJECTIVE The aim of this study is to demonstrate 3-dimensional (3D) acoustic wave sparsely activated localization microscopy (AWSALM) of microvascular flow in vivo using phase change contrast agents (PCCAs). MATERIALS AND METHODS Three-dimensional AWSALM using acoustically activable PCCAs was evaluated on a crossed tube microflow phantom, the kidney of New Zealand White rabbits, and the brain of C57BL/6J mice through intact skull. A mixture of C 3 F 8 and C 4 F 10 low-boiling-point fluorocarbon gas was used to generate PCCAs with an appropriate activation pressure. A multiplexed 8-MHz matrix array connected to a 256-channel ultrasound research platform was used for transmitting activation and imaging ultrasound pulses and recording echoes. The in vitro and in vivo echo data were subsequently beamformed and processed using a set of customized algorithms for generating 3D super-resolution ultrasound images through localizing and tracking activated contrast agents. RESULTS With 3D AWSALM, the acoustic activation of PCCAs can be controlled both spatially and temporally, enabling contrast on demand and capable of revealing 3D microvascular connectivity. The spatial resolution of the 3D AWSALM images measured using Fourier shell correlation is 64 μm, presenting a 9-time improvement compared with the point spread function and 1.5 times compared with half the wavelength. Compared with the microbubble-based approach, more signals were localized in the microvasculature at similar concentrations while retaining sparsity and longer tracks in larger vessels. Transcranial imaging was demonstrated as a proof of principle of PCCA activation in the mouse brain with 3D AWSALM. CONCLUSIONS Three-dimensional AWSALM generates volumetric ultrasound super-resolution microvascular images in vivo with spatiotemporal selectivity and enhanced microvascular penetration.
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Affiliation(s)
- Kai Riemer
- From the Department of Bioengineering, Imperial College London, London, United Kingdom (K.R., Q.T., S.M., M.T., J.Y., J.Z., B.W., L.T., M.L., P.D.W., M.-X.T.); NDORMS, University of Oxford, Oxford, United Kingdom (L.B., Q.W., E.S.); and Department of Physics, Imperial College London, London, United Kingdom (C.D.)
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24
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Zhou S, Gao X, Park G, Yang X, Qi B, Lin M, Huang H, Bian Y, Hu H, Chen X, Wu RS, Liu B, Yue W, Lu C, Wang R, Bheemreddy P, Qin S, Lam A, Wear KA, Andre M, Kistler EB, Newell DW, Xu S. Transcranial volumetric imaging using a conformal ultrasound patch. Nature 2024; 629:810-818. [PMID: 38778234 DOI: 10.1038/s41586-024-07381-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 04/02/2024] [Indexed: 05/25/2024]
Abstract
Accurate and continuous monitoring of cerebral blood flow is valuable for clinical neurocritical care and fundamental neurovascular research. Transcranial Doppler (TCD) ultrasonography is a widely used non-invasive method for evaluating cerebral blood flow1, but the conventional rigid design severely limits the measurement accuracy of the complex three-dimensional (3D) vascular networks and the practicality for prolonged recording2. Here we report a conformal ultrasound patch for hands-free volumetric imaging and continuous monitoring of cerebral blood flow. The 2 MHz ultrasound waves reduce the attenuation and phase aberration caused by the skull, and the copper mesh shielding layer provides conformal contact to the skin while improving the signal-to-noise ratio by 5 dB. Ultrafast ultrasound imaging based on diverging waves can accurately render the circle of Willis in 3D and minimize human errors during examinations. Focused ultrasound waves allow the recording of blood flow spectra at selected locations continuously. The high accuracy of the conformal ultrasound patch was confirmed in comparison with a conventional TCD probe on 36 participants, showing a mean difference and standard deviation of difference as -1.51 ± 4.34 cm s-1, -0.84 ± 3.06 cm s-1 and -0.50 ± 2.55 cm s-1 for peak systolic velocity, mean flow velocity, and end diastolic velocity, respectively. The measurement success rate was 70.6%, compared with 75.3% for a conventional TCD probe. Furthermore, we demonstrate continuous blood flow spectra during different interventions and identify cascades of intracranial B waves during drowsiness within 4 h of recording.
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Affiliation(s)
- Sai Zhou
- Materials Science and Engineering Program, University of California San Diego, La Jolla, CA, USA
| | - Xiaoxiang Gao
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Geonho Park
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Xinyi Yang
- Materials Science and Engineering Program, University of California San Diego, La Jolla, CA, USA
| | - Baiyan Qi
- Materials Science and Engineering Program, University of California San Diego, La Jolla, CA, USA
| | - Muyang Lin
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Hao Huang
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Yizhou Bian
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Hongjie Hu
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Xiangjun Chen
- Materials Science and Engineering Program, University of California San Diego, La Jolla, CA, USA
| | - Ray S Wu
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Boyu Liu
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Wentong Yue
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Chengchangfeng Lu
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Ruotao Wang
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Pranavi Bheemreddy
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Siyu Qin
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Arthur Lam
- Department of Anesthesiology and Critical Care, University of California San Diego, La Jolla, CA, USA
| | - Keith A Wear
- U.S. Food and Drug Administration, Silver Spring, MD, USA
| | - Michael Andre
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Erik B Kistler
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - David W Newell
- Department of Neurosurgery, Seattle Neuroscience Institute, Seattle, WA, USA
| | - Sheng Xu
- Materials Science and Engineering Program, University of California San Diego, La Jolla, CA, USA.
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA.
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.
- Department of Radiology, University of California San Diego, La Jolla, CA, USA.
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
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25
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Zhang Z, Hwang M, Kilbaugh TJ, Katz J. Improving sub-pixel accuracy in ultrasound localization microscopy using supervised and self-supervised deep learning. MEASUREMENT SCIENCE & TECHNOLOGY 2024; 35:045701. [PMID: 38205381 PMCID: PMC10774911 DOI: 10.1088/1361-6501/ad1671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 11/30/2023] [Accepted: 12/17/2023] [Indexed: 01/12/2024]
Abstract
With a spatial resolution of tens of microns, ultrasound localization microscopy (ULM) reconstructs microvascular structures and measures intravascular flows by tracking microbubbles (1-5 μm) in contrast enhanced ultrasound (CEUS) images. Since the size of CEUS bubble traces, e.g. 0.5-1 mm for ultrasound with a wavelength λ = 280 μm, is typically two orders of magnitude larger than the bubble diameter, accurately localizing microbubbles in noisy CEUS data is vital to the fidelity of the ULM results. In this paper, we introduce a residual learning based supervised super-resolution blind deconvolution network (SupBD-net), and a new loss function for a self-supervised blind deconvolution network (SelfBD-net), for detecting bubble centers at a spatial resolution finer than λ/10. Our ultimate purpose is to improve the ability to distinguish closely located microvessels and the accuracy of the velocity profile measurements in macrovessels. Using realistic synthetic data, the performance of these methods is calibrated and compared against several recently introduced deep learning and blind deconvolution techniques. For bubble detection, errors in bubble center location increase with the trace size, noise level, and bubble concentration. For all cases, SupBD-net yields the least error, keeping it below 0.1 λ. For unknown bubble trace morphology, where all the supervised learning methods fail, SelfBD-net can still maintain an error of less than 0.15 λ. SupBD-net also outperforms the other methods in separating closely located bubbles and parallel microvessels. In macrovessels, SupBD-net maintains the least errors in the vessel radius and velocity profile after introducing a procedure that corrects for terminated tracks caused by overlapping traces. Application of these methods is demonstrated by mapping the cerebral microvasculature of a neonatal pig, where neighboring microvessels separated by 0.15 λ can be readily distinguished by SupBD-net and SelfBD-net, but not by the other techniques. Hence, the newly proposed residual learning based methods improve the spatial resolution and accuracy of ULM in micro- and macro-vessels.
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Affiliation(s)
- Zeng Zhang
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
| | - Misun Hwang
- Departments of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Todd J Kilbaugh
- Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
| | - Joseph Katz
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
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26
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Mi J, Liu C, Chen H, Qian Y, Zhu J, Zhang Y, Liang Y, Wang L, Ta D. Light on Alzheimer's disease: from basic insights to preclinical studies. Front Aging Neurosci 2024; 16:1363458. [PMID: 38566826 PMCID: PMC10986738 DOI: 10.3389/fnagi.2024.1363458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Alzheimer's disease (AD), referring to a gradual deterioration in cognitive function, including memory loss and impaired thinking skills, has emerged as a substantial worldwide challenge with profound social and economic implications. As the prevalence of AD continues to rise and the population ages, there is an imperative demand for innovative imaging techniques to help improve our understanding of these complex conditions. Photoacoustic (PA) imaging forms a hybrid imaging modality by integrating the high-contrast of optical imaging and deep-penetration of ultrasound imaging. PA imaging enables the visualization and characterization of tissue structures and multifunctional information at high resolution and, has demonstrated promising preliminary results in the study and diagnosis of AD. This review endeavors to offer a thorough overview of the current applications and potential of PA imaging on AD diagnosis and treatment. Firstly, the structural, functional, molecular parameter changes associated with AD-related brain imaging captured by PA imaging will be summarized, shaping the diagnostic standpoint of this review. Then, the therapeutic methods aimed at AD is discussed further. Lastly, the potential solutions and clinical applications to expand the extent of PA imaging into deeper AD scenarios is proposed. While certain aspects might not be fully covered, this mini-review provides valuable insights into AD diagnosis and treatment through the utilization of innovative tissue photothermal effects. We hope that it will spark further exploration in this field, fostering improved and earlier theranostics for AD.
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Affiliation(s)
- Jie Mi
- Yiwu Research Institute, Fudan University, Yiwu, China
| | - Chao Liu
- Yiwu Research Institute, Fudan University, Yiwu, China
- Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention, Shanghai, China
| | - Honglei Chen
- Yiwu Research Institute, Fudan University, Yiwu, China
| | - Yan Qian
- Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention, Shanghai, China
| | - Jingyi Zhu
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Yachao Zhang
- Medical Ultrasound Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
| | - Yizhi Liang
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Institute of Photonics Technology, Jinan University, Guangzhou, China
| | - Lidai Wang
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Dean Ta
- Yiwu Research Institute, Fudan University, Yiwu, China
- Department of Electronic Engineering, Fudan University, Shanghai, China
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27
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Emami H, Hashemi R. Microwave photonics doppler speed measurement based on sagnac loops and four-wave mixing effect in a highly nonlinear fiber. Sci Rep 2024; 14:5734. [PMID: 38459377 PMCID: PMC11319632 DOI: 10.1038/s41598-024-56470-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 03/06/2024] [Indexed: 03/10/2024] Open
Abstract
Photonic radars are increasingly being developed and offer a promising replacement for traditional RF radars. They feature higher precision, and smaller size compared to the current microwave radars. One important part of a moving target indicating (MTI) radar is the Doppler shift measurement used to measure the radial velocity of a moving target. Therefore, for any photonic radar operating at MTI mode, it is necessary to have a Doppler measurement subsystem. In this paper, a microwave photonic Doppler frequency measurement system is conceived and implemented for this purpose specifically. The operation is based on making a Doppler shift-dependent yet low-frequency voltage component. It is all-optical and hence has the potential to be integrated into many electronic warfare systems. This feature not only makes the system independent of any sophisticated electrical device but also makes the measurement time lower than that of the electrical counterparts. The specific design presented here provides a much better stability compared to the recent works. An error as low as 0.012 Hz at a 10 GHz radar frequency was obtained, and the system performance was demonstrated up to 40 GHz, at which a 4.75 Hz error was recorded.
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Affiliation(s)
- Hossein Emami
- Department of Skill Development and Entrepreneurship, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
| | - Reza Hashemi
- Department of Computer Science, San Diego State University, San Diego, CA, 32611, USA
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28
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Lowerison MR, Vaithiyalingam Chandra Sekaran N, Dong Z, Chen X, You Q, Llano DA, Song P. Super-Resolution Ultrasound Reveals Cerebrovascular Impairment in a Mouse Model of Alzheimer's Disease. J Neurosci 2024; 44:e1251232024. [PMID: 38253533 PMCID: PMC10904092 DOI: 10.1523/jneurosci.1251-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 12/04/2023] [Accepted: 01/16/2024] [Indexed: 01/24/2024] Open
Abstract
Increasing evidence has suggested a link between cerebrovascular disease and the cognitive impairment associated with Alzheimer's disease. However, detailed descriptions of microvascular changes across brain regions and how they relate to other more traditional pathology have been lacking. Additionally, the efforts to elucidate the interplay between cerebral microvascular function and Alzheimer's disease progression are complicated by the necessity of probing deep-brain structures since early-stage Alzheimer's disease typically involves hippocampal pathology. The purpose of this study was to examine changes in microvascular dynamics in a mouse model of Alzheimer's disease using cohorts that were age-matched to wild-type controls. Data from both sexes were included in this study. Super-resolution ultrasound localization microscopy revealed microvascular functional and structural features throughout the whole brain depth to visualize and quantify. We found that functional decreases in hippocampal and entorhinal flow velocity preceded structural derangements in regional vascular density. Co-registered histological sectioning confirmed the regionalized perfusion deficits seen on ultrasound imaging, which were co-localized with amyloid beta plaque deposition. In addition to providing global vascular quantifications of deep brain structures with a high local resolution, this technology also permitted velocity-profile analysis of individual vessels and, in some cases, allowed for decoupling of arterial and venous flow contributions. These data suggest that microvascular pathology is an early and pervasive feature of Alzheimer's disease and may represent a novel therapeutic target for this disease.
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Affiliation(s)
- Matthew R Lowerison
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Departments of Electrical and Computer Engineering, Urbana, Illinois 61801
| | - Nathiya Vaithiyalingam Chandra Sekaran
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Molecular and Integrative Physiology, Urbana, Illinois 61801
| | - Zhijie Dong
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Departments of Electrical and Computer Engineering, Urbana, Illinois 61801
| | - Xi Chen
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Departments of Electrical and Computer Engineering, Urbana, Illinois 61801
| | - Qi You
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Daniel A Llano
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Molecular and Integrative Physiology, Urbana, Illinois 61801
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Pengfei Song
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Departments of Electrical and Computer Engineering, Urbana, Illinois 61801
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
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29
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Bourquin C, Porée J, Rauby B, Perrot V, Ghigo N, Belgharbi H, Bélanger S, Ramos-Palacios G, Cortes N, Ladret H, Ikan L, Casanova C, Lesage F, Provost J. Quantitative pulsatility measurements using 3D dynamic ultrasound localization microscopy. Phys Med Biol 2024; 69:045017. [PMID: 38181421 DOI: 10.1088/1361-6560/ad1b68] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 01/05/2024] [Indexed: 01/07/2024]
Abstract
A rise in blood flow velocity variations (i.e. pulsatility) in the brain, caused by the stiffening of upstream arteries, is associated with cognitive impairment and neurodegenerative diseases. The study of this phenomenon requires brain-wide pulsatility measurements, with large penetration depth and high spatiotemporal resolution. The development of dynamic ultrasound localization microscopy (DULM), based on ULM, has enabled pulsatility measurements in the rodent brain in 2D. However, 2D imaging accesses only one slice of the brain and measures only 2D-projected and hence biased velocities . Herein, we present 3D DULM: using a single ultrasound scanner at high frame rate (1000-2000 Hz), this method can produce dynamic maps of microbubbles flowing in the bloodstream and extract quantitative pulsatility measurements in the cat brain with craniotomy and in the mouse brain through the skull, showing a wide range of flow hemodynamics in both large and small vessels. We highlighted a decrease in pulsatility along the vascular tree in the cat brain, which could be mapped with ultrasound down to a few tens of micrometers for the first time. We also performed an intra-animal validation of the method by showing consistent measurements between the two sides of the Willis circle in the mouse brain. Our study provides the first step towards a new biomarker that would allow the detection of dynamic abnormalities in microvessels in the brain, which could be linked to early signs of neurodegenerative diseases.
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Affiliation(s)
- Chloé Bourquin
- Department of Engineering Physics, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
| | - Jonathan Porée
- Department of Engineering Physics, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
| | - Brice Rauby
- Department of Engineering Physics, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
| | - Vincent Perrot
- Department of Engineering Physics, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
| | - Nin Ghigo
- Department of Engineering Physics, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
| | - Hatim Belgharbi
- Department of Engineering Physics, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
- Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC 27599, United States of America
| | | | | | - Nelson Cortes
- School of Optometry, University of Montreal, Montréal, QC H3T 1P1, Canada
| | - Hugo Ladret
- School of Optometry, University of Montreal, Montréal, QC H3T 1P1, Canada
- Institut de Neurosciences de la Timone, UMR 7289, CNRS and Aix-Marseille Université, Marseille, F-13005, France
| | - Lamyae Ikan
- School of Optometry, University of Montreal, Montréal, QC H3T 1P1, Canada
| | - Christian Casanova
- School of Optometry, University of Montreal, Montréal, QC H3T 1P1, Canada
| | - Frédéric Lesage
- Department of Electrical Engineering, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
| | - Jean Provost
- Department of Engineering Physics, Polytechnique Montréal, Montréal, QC H3T 1J4, Canada
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
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30
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Eleni Karakatsani M, Estrada H, Chen Z, Shoham S, Deán-Ben XL, Razansky D. Shedding light on ultrasound in action: Optical and optoacoustic monitoring of ultrasound brain interventions. Adv Drug Deliv Rev 2024; 205:115177. [PMID: 38184194 PMCID: PMC11298795 DOI: 10.1016/j.addr.2023.115177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 12/27/2023] [Accepted: 12/31/2023] [Indexed: 01/08/2024]
Abstract
Monitoring brain responses to ultrasonic interventions is becoming an important pillar of a growing number of applications employing acoustic waves to actuate and cure the brain. Optical interrogation of living tissues provides a unique means for retrieving functional and molecular information related to brain activity and disease-specific biomarkers. The hybrid optoacoustic imaging methods have further enabled deep-tissue imaging with optical contrast at high spatial and temporal resolution. The marriage between light and sound thus brings together the highly complementary advantages of both modalities toward high precision interrogation, stimulation, and therapy of the brain with strong impact in the fields of ultrasound neuromodulation, gene and drug delivery, or noninvasive treatments of neurological and neurodegenerative disorders. In this review, we elaborate on current advances in optical and optoacoustic monitoring of ultrasound interventions. We describe the main principles and mechanisms underlying each method before diving into the corresponding biomedical applications. We identify areas of improvement as well as promising approaches with clinical translation potential.
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Affiliation(s)
- Maria Eleni Karakatsani
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland; Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland
| | - Héctor Estrada
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland; Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland
| | - Zhenyue Chen
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland; Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland
| | - Shy Shoham
- Department of Ophthalmology and Tech4Health and Neuroscience Institutes, NYU Langone Health, NY, USA
| | - Xosé Luís Deán-Ben
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland; Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland.
| | - Daniel Razansky
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland; Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland.
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31
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Brown MD, Generowicz BS, Dijkhuizen S, Koekkoek SKE, Strydis C, Bosch JG, Arvanitis P, Springeling G, Leus GJT, De Zeeuw CI, Kruizinga P. Four-dimensional computational ultrasound imaging of brain hemodynamics. SCIENCE ADVANCES 2024; 10:eadk7957. [PMID: 38232164 DOI: 10.1126/sciadv.adk7957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 12/19/2023] [Indexed: 01/19/2024]
Abstract
Four-dimensional ultrasound imaging of complex biological systems such as the brain is technically challenging because of the spatiotemporal sampling requirements. We present computational ultrasound imaging (cUSi), an imaging method that uses complex ultrasound fields that can be generated with simple hardware and a physical wave prediction model to alleviate the sampling constraints. cUSi allows for high-resolution four-dimensional imaging of brain hemodynamics in awake and anesthetized mice.
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Affiliation(s)
- Michael D Brown
- Department of Neuroscience, CUBE, Erasmus MC, Rotterdam, Netherlands
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | | | | | | | - Christos Strydis
- Department of Neuroscience, CUBE, Erasmus MC, Rotterdam, Netherlands
- Department of Quantum and Computer Engineering, TU Delft, Delft, Netherlands
| | - Johannes G Bosch
- Department of Cardiology, Thorax Biomedical Engineering, Erasmus MC, Rotterdam, Netherlands
| | - Petros Arvanitis
- Department of Neuroscience, CUBE, Erasmus MC, Rotterdam, Netherlands
| | - Geert Springeling
- Experimental Medical Instrumentation, Erasmus MC, Rotterdam, Netherlands
| | - Geert J T Leus
- Signal Processing Systems, Department of Microelectronics, TU Delft, Delft, Netherlands
| | - Chris I De Zeeuw
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands
- Netherlands Institute for Neuroscience, Royal Dutch Academy for Arts and Sciences, Amsterdam, Netherlands
| | - Pieter Kruizinga
- Department of Neuroscience, CUBE, Erasmus MC, Rotterdam, Netherlands
- Signal Processing Systems, Department of Microelectronics, TU Delft, Delft, Netherlands
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32
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Kim YJ, Lee J, Hwang JH, Chung Y, Park BJ, Kim J, Kim SH, Mun J, Yoon HJ, Park SM, Kim SW. High-Performing and Capacitive-Matched Triboelectric Implants Driven by Ultrasound. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2307194. [PMID: 37884338 DOI: 10.1002/adma.202307194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/09/2023] [Indexed: 10/28/2023]
Abstract
In implantable bioelectronics, which aim for semipermanent use of devices, biosafe energy sources and packaging materials to protect devices are essential elements. However, research so far has been conducted in a direction where they cannot coexist. Here, the development of capacitance-matched triboelectric implants driven is reported by ultrasound under 500 mW cm-2 safe intensity and realize a battery-free, miniatured, and wireless neurostimulator with full titanium (Ti) packaging. The triboelectric implant with high dielectric composite, which has ultralow output impedance, can efficiently deliver sufficient power to generate the stimulation pulse without an energy-storing battery, despite ultrasound attenuation due to the Ti, and has the highest energy transmission efficiency among those reported so far. In vivo study using a rat model demonstrated that the proposed device system is an effective solution for relieving urinary symptoms. These achievements provide a significant step toward permanently implantable devices for controlling human organs and treating various diseases.
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Affiliation(s)
- Young-Jun Kim
- School of Advanced Materials Science and Engineering, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea
| | - Jiho Lee
- Department of Convergence IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
| | - Joon-Ha Hwang
- School of Advanced Materials Science and Engineering, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea
- Research and Development Center, Energymining Co., Ltd., Suwon, 16226, Republic of Korea
| | - Youngwook Chung
- School of Advanced Materials Science and Engineering, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea
- Research and Development Center, Energymining Co., Ltd., Suwon, 16226, Republic of Korea
| | - Byung-Joon Park
- Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Junho Kim
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
| | - So-Hee Kim
- Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Junseung Mun
- Department of Convergence IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
| | - Hong-Joon Yoon
- Department of Electronic Engineering, Gachon University, Seongnam, 13120, Republic of Korea
| | - Sung-Min Park
- Department of Convergence IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
- Department of Electrical Engineering, Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
| | - Sang-Woo Kim
- Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
- Center for Human-Oriented Triboelectric Energy Harvesting, Yonsei University, Seoul, 03722, Republic of Korea
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33
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Porte C, Lisson T, Kohlen M, von Maltzahn F, Dencks S, von Stillfried S, Piepenbrock M, Rix A, Dasgupta A, Koczera P, Boor P, Stickeler E, Schmitz G, Kiessling F. Ultrasound Localization Microscopy for Breast Cancer Imaging in Patients: Protocol Optimization and Comparison with Shear Wave Elastography. ULTRASOUND IN MEDICINE & BIOLOGY 2024; 50:57-66. [PMID: 37805359 DOI: 10.1016/j.ultrasmedbio.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 07/25/2023] [Accepted: 09/02/2023] [Indexed: 10/09/2023]
Abstract
OBJECTIVE Ultrasound localization microscopy (ULM) has gained increasing attention in recent years because of its ability to visualize blood vessels at super-resolution. The field of oncology, in particular, could benefit from detailed vascular characterization, for example, for diagnosis and therapy monitoring. This study was aimed at refining ULM for breast cancer patients by optimizing the measurement protocol, identifying translational challenges and combining ULM and shear wave elastography. METHODS We computed ULM images of 11 patients with breast cancer by recording contrast-enhanced ultrasound (CEUS) sequences and post-processing them in an offline pipeline. For CEUS, two different doses and injection speeds of SonoVue were applied. The best injection protocol was determined based on quantitative parameters derived from so-called occurrence maps. In addition, a suitable measurement time window was determined, also considering the occurrence of motion. ULM results were compared with shear wave elastography and histological vessel density. RESULTS At the higher dose and injection speed, the highest number of microbubbles, number of tracks and vessel coverage were achieved, leading to the most detailed representation of tumor vasculature. Even at the highest concentration, no significant overlay of microbubble signals occurred. Motion significantly reduced the number of usable frames, thus limiting the measurement window to 3.5 min. ULM vessel coverage was comparable to the histological vessel fraction and correlated significantly with mean tumor elasticity. CONCLUSION The settings for microbubble injection strongly influence ULM images, thus requiring optimized protocols for different indications. Patient and examiner motion was identified as the main translational challenge for ULM.
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Affiliation(s)
- Céline Porte
- Institute for Experimental Molecular Imaging, University Clinic Aachen, RWTH Aachen University, Aachen, Germany
| | - Thomas Lisson
- Department of Electrical Engineering and Information Technology, Ruhr University Bochum, Bochum, Germany
| | - Matthias Kohlen
- Department of Gynecology and Obstetrics, University Clinic Aachen, RWTH Aachen University, Aachen, Germany
| | - Finn von Maltzahn
- Institute for Experimental Molecular Imaging, University Clinic Aachen, RWTH Aachen University, Aachen, Germany
| | - Stefanie Dencks
- Department of Electrical Engineering and Information Technology, Ruhr University Bochum, Bochum, Germany
| | - Saskia von Stillfried
- Institute of Pathology, University Clinic Aachen, RWTH Aachen University, Aachen, Germany
| | - Marion Piepenbrock
- Department of Electrical Engineering and Information Technology, Ruhr University Bochum, Bochum, Germany
| | - Anne Rix
- Institute for Experimental Molecular Imaging, University Clinic Aachen, RWTH Aachen University, Aachen, Germany
| | - Anshuman Dasgupta
- Institute for Experimental Molecular Imaging, University Clinic Aachen, RWTH Aachen University, Aachen, Germany
| | - Patrick Koczera
- Institute for Experimental Molecular Imaging, University Clinic Aachen, RWTH Aachen University, Aachen, Germany
| | - Peter Boor
- Institute of Pathology, University Clinic Aachen, RWTH Aachen University, Aachen, Germany
| | - Elmar Stickeler
- Department of Gynecology and Obstetrics, University Clinic Aachen, RWTH Aachen University, Aachen, Germany
| | - Georg Schmitz
- Department of Electrical Engineering and Information Technology, Ruhr University Bochum, Bochum, Germany
| | - Fabian Kiessling
- Institute for Experimental Molecular Imaging, University Clinic Aachen, RWTH Aachen University, Aachen, Germany; Fraunhofer Institute for Digital Medicine MEVIS, Aachen, Germany.
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34
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Soloukey S, Collée E, Verhoef L, Satoer DD, Dirven CMF, Bos EM, Schouten JW, Generowicz BS, Mastik F, De Zeeuw CI, Koekkoek SKE, Vincent AJPE, Smits M, Kruizinga P. Human brain mapping using co-registered fUS, fMRI and ESM during awake brain surgeries: A proof-of-concept study. Neuroimage 2023; 283:120435. [PMID: 37914090 DOI: 10.1016/j.neuroimage.2023.120435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 10/15/2023] [Accepted: 10/29/2023] [Indexed: 11/03/2023] Open
Abstract
Accurate, depth-resolved functional imaging is key in both understanding and treatment of the human brain. A new sonography-based imaging technique named functional Ultrasound (fUS) uniquely combines high sensitivity with submillimeter-subsecond spatiotemporal resolution available in large fields-of-view. In this proof-of-concept study we show that: (A) fUS reveals the same eloquent regions as found by fMRI while concomitantly visualizing in-vivo microvascular morphology underlying these functional hemodynamics and (B) fUS-based functional maps are confirmed by Electrocortical Stimulation Mapping (ESM), the current gold-standard in awake neurosurgical practice. This unique cross-modality experiment was performed using motor, visual and language-related functional tasks in patients undergoing awake brain tumor resection. The current work serves as an important milestone towards further maturity of fUS as well as a novel avenue to increase our understanding of hemodynamics-based functional brain imaging.
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Affiliation(s)
- S Soloukey
- Department of Neuroscience, Erasmus MC, Wytemaweg 80 3015 CN, Rotterdam 3015 CN, the Netherlands; Department of Neurosurgery, Erasmus MC, Rotterdam 3015 CN, the Netherlands
| | - E Collée
- Department of Neurosurgery, Erasmus MC, Rotterdam 3015 CN, the Netherlands
| | - L Verhoef
- Department of Neuroscience, Erasmus MC, Wytemaweg 80 3015 CN, Rotterdam 3015 CN, the Netherlands
| | - D D Satoer
- Department of Neurosurgery, Erasmus MC, Rotterdam 3015 CN, the Netherlands
| | - C M F Dirven
- Department of Neurosurgery, Erasmus MC, Rotterdam 3015 CN, the Netherlands
| | - E M Bos
- Department of Neurosurgery, Erasmus MC, Rotterdam 3015 CN, the Netherlands
| | - J W Schouten
- Department of Neurosurgery, Erasmus MC, Rotterdam 3015 CN, the Netherlands
| | - B S Generowicz
- Department of Neuroscience, Erasmus MC, Wytemaweg 80 3015 CN, Rotterdam 3015 CN, the Netherlands
| | - F Mastik
- Department of Neuroscience, Erasmus MC, Wytemaweg 80 3015 CN, Rotterdam 3015 CN, the Netherlands
| | - C I De Zeeuw
- Department of Neuroscience, Erasmus MC, Wytemaweg 80 3015 CN, Rotterdam 3015 CN, the Netherlands; Netherlands Institute for Neuroscience, Royal Dutch Academy for Arts and Sciences, Amsterdam 1105 BA, the Netherlands
| | - S K E Koekkoek
- Department of Neuroscience, Erasmus MC, Wytemaweg 80 3015 CN, Rotterdam 3015 CN, the Netherlands
| | - A J P E Vincent
- Department of Neurosurgery, Erasmus MC, Rotterdam 3015 CN, the Netherlands
| | - M Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam 3015 CN, the Netherlands
| | - P Kruizinga
- Department of Neuroscience, Erasmus MC, Wytemaweg 80 3015 CN, Rotterdam 3015 CN, the Netherlands.
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Jiang C, Li B, Xie L, Liu C, Xu K, Zhan Y, Ta D. Ray theory-based compounded plane wave ultrasound imaging for aberration corrected transcranial imaging: Phantom experiments and simulations. ULTRASONICS 2023; 135:107124. [PMID: 37541030 DOI: 10.1016/j.ultras.2023.107124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/06/2023]
Abstract
Compounded plane wave imaging (CPWI) allows high-frame-rate measurement and has been one of the most promising modalities for real-time brain imaging. However, ultrasonic brain imaging using the CPWI modality is usually performed with a worn thin or removal of the skull layer. Otherwise, the skull layer is expected to distort the ultrasonic wavefronts and significantly decrease intracranial imaging quality. The motivation of this study is to investigate a CPWI method for transcranial brain imaging with the skull layer. A coordinate transformation ray-tracing (CTRT) approach was proposed to track the distorted ultrasonic wavefronts and calculate the time delays for the ultrasound plane wave passing through the skull layer. With an accurate correction for the time delays in beamforming, the CTRT-based CPWI could achieve high-quality intracranial images with the presence of skulls. The proposed CTRT-based CPWI method was verified using a simplified three-layer transcranial model. The full-wave simulation demonstrated that CTRT could accurately (i.e., relative percentage error less than0.18%) track the distorted transmitting wavefront through skull. Compared with the CPWI without aberration correction, the CTRT-based CPWI provided high-quality intracranial imaging and could accurately localize intracranial point scatterers; specifically, positioning error decreases from 0.5 mm to 0.1 mm on average in the axial direction and from 0.7 mm to 0.1 mm on average in the lateral direction. As the compounded angles increased in the CTRT-based CPWI, the contrast improved by 16.2 dB on average for the region of interest, and the array performance indicator (representing resolution) decreased by 4.0 on average for the intracranial point scatterers. The CTRT is of low computational cost compared with full wave simulation. This study suggested that the proposed CTRT-based CPWI might have the potential for real-time and non-invasive transcranial aberration-corrected imaging.
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Affiliation(s)
- Chen Jiang
- Micro-nano System Center, School of Information Science and Technology, Fudan University, 200438, Shanghai, China
| | - Boyi Li
- Academy for Engineering and Technology, Fudan University, 200433, Shanghai, China
| | - Linru Xie
- Academy for Engineering and Technology, Fudan University, 200433, Shanghai, China
| | - Chengcheng Liu
- Academy for Engineering and Technology, Fudan University, 200433, Shanghai, China; State Key Laboratory of Integrated Chips and Systems, Fudan University, 201203, Shanghai, China
| | - Kailiang Xu
- Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, 200438, Shanghai, China; State Key Laboratory of Integrated Chips and Systems, Fudan University, 201203, Shanghai, China.
| | - Yiqiang Zhan
- Micro-nano System Center, School of Information Science and Technology, Fudan University, 200438, Shanghai, China
| | - Dean Ta
- Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, 200438, Shanghai, China; State Key Laboratory of Integrated Chips and Systems, Fudan University, 201203, Shanghai, China.
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Huang B, Yan J, Morris M, Sinnett V, Somaiah N, Tang MX. Acceleration-Based Kalman Tracking for Super-Resolution Ultrasound Imaging In Vivo. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2023; 70:1739-1748. [PMID: 37871098 PMCID: PMC7615377 DOI: 10.1109/tuffc.2023.3326863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Super-resolution ultrasound (SRUS) can image microvascular structure and flow at subwave-diffraction resolution based on localizing and tracking microbubbles (MBs). Currently, tracking MBs accurately under limited imaging frame rates and high MB concentrations remains a challenge, especially under the effect of cardiac pulsatility and in highly curved vessels. In this study, an acceleration-incorporated MB motion model is introduced into a Kalman tracking framework. The tracking performance was evaluated using simulated microvasculature with different MB motion parameters, concentrations, and acquisition frame rates, and in vivo human breast tumor US datasets. The simulation results show that the acceleration-based method outperformed the nonacceleration-based method at different levels of acceleration and acquisition frame rates and achieved significant improvement in true positive rate (TPR; up to 11.3%) and false negative rate (FNR; up to 13.2%). The proposed method can also reduce errors in vasculature reconstruction via the acceleration-based nonlinear interpolation, compared with linear interpolation (up to [Formula: see text]). The tracking results from temporally downsampled low frame rate in vivo datasets from human breast tumors show that the proposed method has better MB tracking performance than the baseline method, if using results from the initial high frame data as a reference. Finally, the acceleration estimated from tracking results also provides a spatial speed gradient map that may contain extra valuable diagnostic information.
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Affiliation(s)
- Biao Huang
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
| | - Jipeng Yan
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
| | - Megan Morris
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
| | | | - Navita Somaiah
- Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, UK, SM2 5NG
| | - Meng-Xing Tang
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
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Oh D, Lee D, Heo J, Kweon J, Yong U, Jang J, Ahn YJ, Kim C. Contrast Agent-Free 3D Renal Ultrafast Doppler Imaging Reveals Vascular Dysfunction in Acute and Diabetic Kidney Diseases. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2303966. [PMID: 37847902 PMCID: PMC10754092 DOI: 10.1002/advs.202303966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 08/19/2023] [Indexed: 10/19/2023]
Abstract
To combat the irreversible decline in renal function associated with kidney disease, it is essential to establish non-invasive biomarkers for assessing renal microcirculation. However, the limited resolution and/or vascular sensitivity of existing diagnostic imaging techniques hinders the visualization of complex cortical vessels. Here, a 3D renal ultrafast Doppler (UFD) imaging system that uses a high ultrasound frequency (18 MHz) and ultrahigh frame rate (1 KHz per slice) to scan the entire volume of a rat's kidney in vivo is demonstrated. The system, which can visualize the full 3D renal vascular branching pyramid at a resolution of 167 µm without any contrast agent, is used to chronically and noninvasively monitor kidneys with acute kidney injury (AKI, 3 days) and diabetic kidney disease (DKD, 8 weeks). Multiparametric UFD analyses (e.g., vessel volume occupancy (VVO), fractional moving blood volume (FMBV), vessel number density (VND), and vessel tortuosity (VT)) describe rapid vascular rarefaction from AKI and long-term vascular degeneration from DKD, while the renal pathogeneses are validated by in vitro blood serum testing and stained histopathology. This work demonstrates the potential of 3D renal UFD to offer valuable insights into assessing kidney perfusion levels for future research in diabetes and kidney transplantation.
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Affiliation(s)
- Donghyeon Oh
- Departments of Electrical EngineeringConvergence IT EngineeringMedical Science and EngineeringMechanical Engineeringand Medical Device Innovation CenterPohang University of Science and Technology (POSTECH)Cheongam‐ro 77, Nam‐guPohangGyeongbuk37673Republic of Korea
| | - Donghyun Lee
- Departments of Electrical EngineeringConvergence IT EngineeringMedical Science and EngineeringMechanical Engineeringand Medical Device Innovation CenterPohang University of Science and Technology (POSTECH)Cheongam‐ro 77, Nam‐guPohangGyeongbuk37673Republic of Korea
| | - Jinseok Heo
- Departments of Electrical EngineeringConvergence IT EngineeringMedical Science and EngineeringMechanical Engineeringand Medical Device Innovation CenterPohang University of Science and Technology (POSTECH)Cheongam‐ro 77, Nam‐guPohangGyeongbuk37673Republic of Korea
| | - Jooyoung Kweon
- Departments of Electrical EngineeringConvergence IT EngineeringMedical Science and EngineeringMechanical Engineeringand Medical Device Innovation CenterPohang University of Science and Technology (POSTECH)Cheongam‐ro 77, Nam‐guPohangGyeongbuk37673Republic of Korea
| | - Uijung Yong
- Departments of Electrical EngineeringConvergence IT EngineeringMedical Science and EngineeringMechanical Engineeringand Medical Device Innovation CenterPohang University of Science and Technology (POSTECH)Cheongam‐ro 77, Nam‐guPohangGyeongbuk37673Republic of Korea
| | - Jinah Jang
- Departments of Electrical EngineeringConvergence IT EngineeringMedical Science and EngineeringMechanical Engineeringand Medical Device Innovation CenterPohang University of Science and Technology (POSTECH)Cheongam‐ro 77, Nam‐guPohangGyeongbuk37673Republic of Korea
| | - Yong Joo Ahn
- Departments of Electrical EngineeringConvergence IT EngineeringMedical Science and EngineeringMechanical Engineeringand Medical Device Innovation CenterPohang University of Science and Technology (POSTECH)Cheongam‐ro 77, Nam‐guPohangGyeongbuk37673Republic of Korea
| | - Chulhong Kim
- Departments of Electrical EngineeringConvergence IT EngineeringMedical Science and EngineeringMechanical Engineeringand Medical Device Innovation CenterPohang University of Science and Technology (POSTECH)Cheongam‐ro 77, Nam‐guPohangGyeongbuk37673Republic of Korea
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Chen H, Mirg S, Gaddale P, Agrawal S, Li M, Nguyen V, Xu T, Li Q, Liu J, Tu W, Liu X, Drew PJ, Zhang N, Gluckman BJ, Kothapalli SR. Dissecting Multiparametric Cerebral Hemodynamics using Integrated Ultrafast Ultrasound and Multispectral Photoacoustic Imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.07.566048. [PMID: 37986863 PMCID: PMC10659547 DOI: 10.1101/2023.11.07.566048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Understanding brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help study neuro-disorders and brain functions. However, the existing brain imaging technologies have limited resolution, sensitivity, imaging depth and provide information about only one or two hemodynamic parameters. To address this, we propose a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map cerebral blood volume (CBV), cerebral blood flow (CBF), oxygen saturation (SO2) dynamics as well as contrast agent enhanced brain imaging with high spatiotemporal resolutions. After systematic characterization, the fUSPA system was applied to quantitatively study the changes in brain hemodynamics and vascular reactivity at single vessel resolution in response to hypercapnia stimulation. Our results show an overall increase in brain-wide CBV, CBF, and SO2, but regional differences in singular cortical veins and arteries and a reproducible anti-correlation pattern between venous and cortical hemodynamics, demonstrating the capabilities of the fUSPA system for providing multiparametric cerebrovascular information at high-resolution and sensitivity, that can bring insights into the complex mechanisms of neurodiseases.
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Affiliation(s)
- Haoyang Chen
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Shubham Mirg
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Prameth Gaddale
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sumit Agrawal
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Menghan Li
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Van Nguyen
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Tianbao Xu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Qiong Li
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Jinyun Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Wenyu Tu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Xiao Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Patrick J. Drew
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Neurosurgery, The Pennsylvania State University, University Park, PA 16802, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Bruce J. Gluckman
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Neurosurgery, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sri-Rajasekhar Kothapalli
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Penn State Cancer Institute, The Pennsylvania State University, Hershey, PA 17033, USA
- Graduate Program in Acoustics, The Pennsylvania State University, University Park, PA 16802, USA
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Yang J, Cherin E, Yin J, Dayton PA, Foster FS, Demore CEM. Superharmonic and Microultrasound Imaging With Plane Wave Beamforming Techniques. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2023; 70:1442-1456. [PMID: 37713228 PMCID: PMC10712286 DOI: 10.1109/tuffc.2023.3316120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/16/2023]
Abstract
Superharmonic contrast imaging (SpHI) suppresses tissue clutter and allows high-contrast visualization of the vasculature. An array-based dual-frequency (DF) probe has been developed for SpHI, integrating a 21-MHz, 256-element microultrasound imaging array with a 2-MHz, 32-element array to take advantage of the broadband nonlinear responses from microbubble (MB) contrast agents. In this work, ultrafast imaging with plane waves was implemented for SpHI to increase the acquisition frame rate. Ultrafast imaging was also implemented for microultrasound B-mode imaging (HFPW B-mode) to enable high-resolution visualization of the tissue structure. Coherent compounding was demonstrated in vitro and in vivo in both imaging modes. Acquisition frame rates of 4.5 kHz and 187 Hz in HFPW B-mode imaging were achieved for imaging up to 21 mm with one and 25 angles, respectively, and 3.5 kHz and 396 Hz in the SpHI mode with one and nine coherently compounded angles, respectively. SpHI images showed suppression of tissue clutter prior to and after the introduction of MBs in vitro and in vivo. The nine-angle coherently compounded 2-D SpHI images of contrast-filled flow channel showed a contrast-to-tissue ratio (CTR) of 26.0 dB, a 2.5-dB improvement relative to images reconstructed from 0° steering. Consistent with in vitro imaging, the nine-angle compounded 2-D SpHI of a Lewis lung cancer tumor showed a 2.6-dB improvement in contrast enhancement, relative to 0° steering, and additionally revealed a region of nonviable tissue. The 3-D display of the volumetric SpHI data acquired from a xenograft mouse tumor using both 0° steering and nine-angle compounding allowed the visualization of the tumor vasculature. A small vessel visible in the compounded SpHI image, measuring around [Formula: see text], is not visualized in the 0° steering SpHI image, demonstrating the superiority of the latter in detecting fine structures within the tumor.
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McCall JR, DeRuiter R, Ross M, Santibanez F, Hingtgen SD, Pinton GF, Dayton PA. Longitudinal 3-D Visualization of Microvascular Disruption and Perfusion Changes in Mice During the Evolution of Glioblastoma Using Super-Resolution Ultrasound. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2023; 70:1401-1416. [PMID: 37756182 DOI: 10.1109/tuffc.2023.3320034] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Glioblastoma is an aggressive brain cancer with a very poor prognosis in which less than 6% of patients survive more than five-year post-diagnosis. The outcome of this disease for many patients may be improved by early detection. This could provide clinicians with the information needed to take early action for treatment. In this work, we present the utilization of a non-invasive, fully volumetric ultrasonic imaging method to assess microvascular change during the evolution of glioblastoma in mice. Volumetric ultrasound localization microscopy (ULM) was used to observe statistically significant ( ) reduction in the appearance of functional vasculature over the course of three weeks. We also demonstrate evidence suggesting the reduction of vascular flow for vessels peripheral to the tumor. With an 82.5% consistency rate in acquiring high-quality vascular images, we demonstrate the possibility of volumetric ULM as a longitudinal method for microvascular characterization of neurological disease.
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Malferrari G, Merli N, Inchingolo V, Siniscalchi A, Laterza D, Monaco D, Arnone G, Zini A, Prada F, Azzini C, Pugliatti M. Role of Advanced Hemodynamic Ultrasound Evaluation in the Differential Diagnosis of Middle Cerebral Artery Stenosis: Introducing Morphological Criteria. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:2428-2435. [PMID: 37550172 DOI: 10.1016/j.ultrasmedbio.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 06/28/2023] [Accepted: 07/09/2023] [Indexed: 08/09/2023]
Abstract
OBJECTIVE The aim of the work described here was to determine the possible impact of the new technique advanced hemodynamic ultrasound evaluation (AHUSE) in identification of severe intracranial stenosis. Transcranial Doppler (TCD) and transcranial color-coded Doppler (TCCD) provide reliable velocimetric data, the indirect analysis of which allows us to obtain information on the patency of vessels and assumed stenosis range. However, very tight stenoses (>95%) cannot be detected with velocimetric criteria because of spectrum drops and the absence of high velocities, so that the right curve of the Spencer equation cannot be solved. Likewise, high velocities are not detected when analyzing morphologically long stenosis. Furthermore, the current classifications based on velocimetric criteria do not provide any categorization on stenoses with multiple acceleration points (MAPs). METHODS With this Technical Note we aim to introduce, in addition to velocimetric criteria, more morphological criteria based on TCCD with the algorithm of AHUSE to optimize the characterization of intracranial stenosis (IS). TCCD-AHUSE relies on intensity-based next-generation techniques and can be used to identify IS with MAPs and simultaneously perform a morphological assessment of the stenosis length. RESULTS We introduce a new technical ultrasound (U) approach that we tested in a sample of four different types of stenoses combining velocimetric data and AHUSE using Esaote Microvascularization (MicroV) technique to the M1 tract of the middle cerebral artery (MCA). CONCLUSION The authors believe that a multiparametric evaluation is more sensitive and supports the clinician by introducing the morphological concept, not just the velocimetric concept, to differentiate the IS pattern of MCA. The potential for developing a diagnostic/prognostic algorithm is discussed.
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Affiliation(s)
- Giovanni Malferrari
- Stroke Unit and Neurology Unit, Azienda Unità Sanitaria Locale-IRCCS, Reggio Emilia, Italy.
| | - Nicola Merli
- Department of Neuroscience and Rehabilitation, University of Ferrara, Italy
| | - Vincenzo Inchingolo
- Neurology Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Antonio Siniscalchi
- Department of Neurology and Stroke Unit, Annunziata Hospital, Cosenza, Italy
| | - Domenico Laterza
- Neurology and Stroke Unit, Nuovo Ospedale degli Infermi, Biella (BI), Italy
| | - Daniela Monaco
- Department of Emergency Neurology and Stroke Unit, "S. Spirito" Hospital, Pescara, Italy
| | - Giorgia Arnone
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Neurologia e Rete Stroke Metropolitana, Ospedale Maggiore, Bologna, Italy
| | - Andrea Zini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Neurologia e Rete Stroke Metropolitana, Ospedale Maggiore, Bologna, Italy
| | - Francesco Prada
- Acoustic Neuroimaging and Therapy Lab, Fondazione IRCCS Istituto Neurologico C. Besta, Milano, Italy; Department of Neurological Surgery, University of Virginia, Charlottesville, VA, USA; Focused Ultrasound Foundation, Charlottesville, VA, USA
| | - Cristiano Azzini
- Stroke Unit and Neurology Unit, S. Anna University Hospital, Ferrara Italy
| | - Maura Pugliatti
- Department of Neuroscience and Rehabilitation, University of Ferrara, Italy; S. Anna University Hospital, Ferrara Italy
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Bureau F, Robin J, Le Ber A, Lambert W, Fink M, Aubry A. Three-dimensional ultrasound matrix imaging. Nat Commun 2023; 14:6793. [PMID: 37880210 PMCID: PMC10600255 DOI: 10.1038/s41467-023-42338-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 10/05/2023] [Indexed: 10/27/2023] Open
Abstract
Matrix imaging paves the way towards a next revolution in wave physics. Based on the response matrix recorded between a set of sensors, it enables an optimized compensation of aberration phenomena and multiple scattering events that usually drastically hinder the focusing process in heterogeneous media. Although it gave rise to spectacular results in optical microscopy or seismic imaging, the success of matrix imaging has been so far relatively limited with ultrasonic waves because wave control is generally only performed with a linear array of transducers. In this paper, we extend ultrasound matrix imaging to a 3D geometry. Switching from a 1D to a 2D probe enables a much sharper estimation of the transmission matrix that links each transducer and each medium voxel. Here, we first present an experimental proof of concept on a tissue-mimicking phantom through ex-vivo tissues and then, show the potential of 3D matrix imaging for transcranial applications.
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Affiliation(s)
- Flavien Bureau
- Institut Langevin, ESPCI Paris, PSL University, CNRS, 75005, Paris, France
| | - Justine Robin
- Institut Langevin, ESPCI Paris, PSL University, CNRS, 75005, Paris, France
- Physics for Medicine, ESPCI Paris, PSL University, INSERM, CNRS, Paris, France
| | - Arthur Le Ber
- Institut Langevin, ESPCI Paris, PSL University, CNRS, 75005, Paris, France
| | - William Lambert
- Institut Langevin, ESPCI Paris, PSL University, CNRS, 75005, Paris, France
- Hologic / SuperSonic Imagine, 135 Rue Emilien Gautier, 13290, Aix-en-Provence, France
| | - Mathias Fink
- Institut Langevin, ESPCI Paris, PSL University, CNRS, 75005, Paris, France
| | - Alexandre Aubry
- Institut Langevin, ESPCI Paris, PSL University, CNRS, 75005, Paris, France.
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Søgaard SB, Andersen SB, Taghavi I, Schou M, Christoffersen C, Jacobsen JCB, Kjer HM, Gundlach C, McDermott A, Jensen JA, Nielsen MB, Sørensen CM. Super-Resolution Ultrasound Imaging of Renal Vascular Alterations in Zucker Diabetic Fatty Rats during the Development of Diabetic Kidney Disease. Diagnostics (Basel) 2023; 13:3197. [PMID: 37892017 PMCID: PMC10605617 DOI: 10.3390/diagnostics13203197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 10/08/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023] Open
Abstract
Individuals with diabetes at risk of developing diabetic kidney disease (DKD) are challenging to identify using currently available clinical methods. Prognostic accuracy and initiation of treatment could be improved by a quantification of the renal microvascular rarefaction and the increased vascular tortuosity during the development of DKD. Super-resolution ultrasound (SRUS) imaging is an in vivo technique capable of visualizing blood vessels at sizes below 75 µm. This preclinical study aimed to investigate the alterations in renal blood vessels' density and tortuosity in a type 2 diabetes rat model, Zucker diabetic fatty (ZDF) rats, as a prediction of DKD. Lean age-matched Zucker rats were used as controls. A total of 36 rats were studied, subdivided into ages of 12, 22, and 40 weeks. Measured albuminuria indicated the early stage of DKD, and the SRUS was compared with the ex vivo micro-computed tomography (µCT) of the same kidneys. Assessed using the SRUS imaging, a significantly decreased cortical vascular density was detected in the ZDF rats from 22 weeks of age compared to the healthy controls, concomitant with a significantly increased albuminuria. Already by week 12, a trend towards a decreased cortical vascular density was found prior to the increased albuminuria. The quantified vascular density in µCT corresponded with the in vivo SRUS imaging, presenting a consistently lower vascular density in the ZDF rats. Regarding vessel tortuosity, an overall trend towards an increased tortuosity was present in the ZDF rats. SRUS shows promise for becoming an additional tool for monitoring and prognosing DKD. In the future, large-scale animal studies and human trials are needed for confirmation.
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Affiliation(s)
- Stinne Byrholdt Søgaard
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (S.B.S.); (S.B.A.); (C.C.); (J.C.B.J.); (A.M.)
- Department of Diagnostic Radiology, Rigshospitalet, 2100 Copenhagen, Denmark;
| | - Sofie Bech Andersen
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (S.B.S.); (S.B.A.); (C.C.); (J.C.B.J.); (A.M.)
- Department of Diagnostic Radiology, Rigshospitalet, 2100 Copenhagen, Denmark;
| | - Iman Taghavi
- Center for Fast Ultrasound Imaging, Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark; (I.T.); (J.A.J.)
| | | | - Christina Christoffersen
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (S.B.S.); (S.B.A.); (C.C.); (J.C.B.J.); (A.M.)
- Department of Clinical Biochemistry, Rigshospitalet, 2100 Copenhagen, Denmark
| | - Jens Christian Brings Jacobsen
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (S.B.S.); (S.B.A.); (C.C.); (J.C.B.J.); (A.M.)
| | - Hans Martin Kjer
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Lyngby, Denmark;
| | - Carsten Gundlach
- Department of Physics, Technical University of Denmark, 2800 Lyngby, Denmark;
| | - Amy McDermott
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (S.B.S.); (S.B.A.); (C.C.); (J.C.B.J.); (A.M.)
| | - Jørgen Arendt Jensen
- Center for Fast Ultrasound Imaging, Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark; (I.T.); (J.A.J.)
| | - Michael Bachmann Nielsen
- Department of Diagnostic Radiology, Rigshospitalet, 2100 Copenhagen, Denmark;
- Department of Clinical Medicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Charlotte Mehlin Sørensen
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (S.B.S.); (S.B.A.); (C.C.); (J.C.B.J.); (A.M.)
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Vienneau EP, Byram BC. A Coded Excitation Framework for High SNR Transcranial Ultrasound Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:2886-2898. [PMID: 37079411 PMCID: PMC10691235 DOI: 10.1109/tmi.2023.3269022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Robust transcranial ultrasound imaging is difficult due to poor image quality. In particular, low signal-to-noise ratio (SNR) limits sensitivity to blood flow and has hindered clinical translation of transcranial functional ultrasound neuroimaging thus far. In this work, we present a coded excitation framework to increase SNR in transcranial ultrasound without negatively impacting frame rate or image quality. We applied this coded excitation framework in phantom imaging and showed SNR gains as large as 24.78 dB and signal-to-clutter ratio gains as high as 10.66 dB with a 65 bit code. We also analyzed how imaging sequence parameters can impact image quality and showed how coded excitation sequences can be designed to maximize image quality for a given application. In particular, we show that considering the number of active transmit elements and the transmit voltage is critical for coded excitation with long codes. Finally, we applied our coded excitation technique in transcranial imaging of ten adult subjects and showed an average SNR gain of 17.91 ± 0.96 dB without a significant increase in clutter using a 65 bit code. We also performed transcranial power Doppler imaging in three adult subjects and showed contrast and contrast-to-noise ratio improvements of 27.32 ± 8.08 dB and 7.25 ± 1.61 dB, respectively with a 65 bit code. These results show that transcranial functional ultrasound neuroimaging may be possible using coded excitation.
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Hikishima K, Tsurugizawa T, Kasahara K, Takagi R, Yoshinaka K, Nitta N. Brain-wide mapping of resting-state networks in mice using high-frame rate functional ultrasound. Neuroimage 2023; 279:120297. [PMID: 37500027 DOI: 10.1016/j.neuroimage.2023.120297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 06/21/2023] [Accepted: 07/25/2023] [Indexed: 07/29/2023] Open
Abstract
Functional ultrasound (fUS) imaging is a method for visualizing deep brain activity based on cerebral blood volume changes coupled with neural activity, while functional MRI (fMRI) relies on the blood-oxygenation-level-dependent signal coupled with neural activity. Low-frequency fluctuations (LFF) of fMRI signals during resting-state can be measured by resting-state fMRI (rsfMRI), which allows functional imaging of the whole brain, and the distributions of resting-state network (RSN) can then be estimated from these fluctuations using independent component analysis (ICA). This procedure provides an important method for studying cognitive and psychophysiological diseases affecting specific brain networks. The distributions of RSNs in the brain-wide area has been reported primarily by rsfMRI. RSNs using rsfMRI are generally computed from the time-course of fMRI signals for more than 5 min. However, a recent dynamic functional connectivity study revealed that RSNs are still not perfectly stable even after 10 min. Importantly, fUS has a higher temporal resolution and stronger correlation with neural activity compared with fMRI. Therefore, we hypothesized that fUS applied during the resting-state for a shorter than 5 min would provide similar RSNs compared to fMRI. High temporal resolution rsfUS data were acquired at 10 Hz in awake mice. The quality of the default mode network (DMN), a well-known RSN, was evaluated using signal-noise separation (SNS) applied to different measurement durations of rsfUS. The results showed that the SNS did not change when the measurement duration was increased to more than 210 s. Next, we measured short-duration rsfUS multi-slice measurements in the brain-wide area. The results showed that rsfUS with the short duration succeeded in detecting RSNs distributed in the brain-wide area consistent with RSNs detected by 11.7-T MRI under awake conditions (medial prefrontal cortex and cingulate cortex in the anterior DMN, retrosplenial cortex and visual cortex in the posterior DMN, somatosensory and motor cortexes in the lateral cortical network, thalamus, dorsal hippocampus, and medial cerebellum), confirming the reliability of the RSNs detected by rsfUS. However, bilateral RSNs located in the secondary somatosensory cortex, ventral hippocampus, auditory cortex, and lateral cerebellum extracted from rsfUS were different from the unilateral RSNs extracted from rsfMRI. These findings indicate the potential of rsfUS as a method for analyzing functional brain networks and should encourage future research to elucidate functional brain networks and their relationships with disease model mice.
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Affiliation(s)
- Keigo Hikishima
- Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan; Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan.
| | - Tomokazu Tsurugizawa
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
| | - Kazumi Kasahara
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
| | - Ryo Takagi
- Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
| | - Kiyoshi Yoshinaka
- Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
| | - Naotaka Nitta
- Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
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Zhang G, Liao C, Hu JR, Hu HM, Lei YM, Harput S, Ye HR. Nanodroplet-Based Super-Resolution Ultrasound Localization Microscopy. ACS Sens 2023; 8:3294-3306. [PMID: 37607403 DOI: 10.1021/acssensors.3c00418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Over the past decade, super-resolution ultrasound localization microscopy (SR-ULM) has revolutionized ultrasound imaging with its capability to resolve the microvascular structures below the ultrasound diffraction limit. The introduction of this imaging technique enables the visualization, quantification, and characterization of tissue microvasculature. The early implementations of SR-ULM utilize microbubbles (MBs) that require a long image acquisition time due to the requirement of capturing sparsely isolated microbubble signals. The next-generation SR-ULM employs nanodroplets that have the potential to significantly reduce the image acquisition time without sacrificing the resolution. This review discusses various nanodroplet-based ultrasound localization microscopy techniques and their corresponding imaging mechanisms. A summary is given on the preclinical applications of SR-ULM with nanodroplets, and the challenges in the clinical translation of nanodroplet-based SR-ULM are presented while discussing the future perspectives. In conclusion, ultrasound localization microscopy is a promising microvasculature imaging technology that can provide new diagnostic and prognostic information for a wide range of pathologies, such as cancer, heart conditions, and autoimmune diseases, and enable personalized treatment monitoring at a microlevel.
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Affiliation(s)
- Ge Zhang
- Department of Medical Ultrasound, China Resources & Wisco General Hospital, Wuhan University of Science and Technology, Wuhan 430080, People's Republic of China
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan 430065, People's Republic of China
- Physics for Medicine Paris, Inserm U1273, ESPCI Paris, PSL University, CNRS, Paris 75015, France
| | - Chen Liao
- Department of Medical Ultrasound, China Resources & Wisco General Hospital, Wuhan University of Science and Technology, Wuhan 430080, People's Republic of China
- Medical College, Wuhan University of Science and Technology, Wuhan 430065, People's Republic of China
| | - Jun-Rui Hu
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, People's Republic of China
| | - Hai-Man Hu
- Department of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, People's Republic of China
| | - Yu-Meng Lei
- Department of Medical Ultrasound, China Resources & Wisco General Hospital, Wuhan University of Science and Technology, Wuhan 430080, People's Republic of China
| | - Sevan Harput
- Department of Electrical and Electronic Engineering, London South Bank University, London SE1 0AA, U.K
| | - Hua-Rong Ye
- Department of Medical Ultrasound, China Resources & Wisco General Hospital, Wuhan University of Science and Technology, Wuhan 430080, People's Republic of China
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47
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Wang Y, Lowerison MR, You Q, Lin BZ, Llano DA, Song P. Longitudinal Awake Imaging of Deep Mouse Brain Microvasculature with Super-resolution Ultrasound Localization Microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.01.555789. [PMID: 37732191 PMCID: PMC10508721 DOI: 10.1101/2023.09.01.555789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Super-resolution ultrasound localization microscopy (ULM) is an emerging imaging modality that resolves capillary-scale microvasculature in deep tissues. However, existing preclinical ULM applications are largely constrained to anesthetized animals, introducing confounding vascular effects such as vasodilation and altered hemodynamics. As such, ULM quantifications (e.g., vessel diameter, density, and flow velocity) may be confounded by the use of anesthesia, undermining the usefulness of ULM in practice. Here we introduce a method to address this limitation and achieve ULM imaging in awake mouse brain. Pupillary monitoring was used to confirm the awake state during ULM imaging. ULM revealed that veins showed a greater degree of vascularity reduction from anesthesia to awake states than did arteries. The reduction was most significant in the midbrain and least significant in the cortex. ULM also revealed a significant reduction in venous blood flow velocity across different brain regions under awake conditions. Serial in vivo imaging of the same animal brain at weekly intervals demonstrated the highly robust longitudinal imaging capability of the proposed technique. This is the first study demonstrating longitudinal ULM imaging in the awake mouse brain, which is essential for many ULM brain applications that require awake and behaving animals.
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48
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Zheng H, Niu L, Qiu W, Liang D, Long X, Li G, Liu Z, Meng L. The Emergence of Functional Ultrasound for Noninvasive Brain-Computer Interface. RESEARCH (WASHINGTON, D.C.) 2023; 6:0200. [PMID: 37588619 PMCID: PMC10427153 DOI: 10.34133/research.0200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 07/04/2023] [Indexed: 08/18/2023]
Abstract
A noninvasive brain-computer interface is a central task in the comprehensive analysis and understanding of the brain and is an important challenge in international brain-science research. Current implanted brain-computer interfaces are cranial and invasive, which considerably limits their applications. The development of new noninvasive reading and writing technologies will advance substantial innovations and breakthroughs in the field of brain-computer interfaces. Here, we review the theory and development of the ultrasound brain functional imaging and its applications. Furthermore, we introduce latest advancements in ultrasound brain modulation and its applications in rodents, primates, and human; its mechanism and closed-loop ultrasound neuromodulation based on electroencephalograph are also presented. Finally, high-frequency acoustic noninvasive brain-computer interface is prospected based on ultrasound super-resolution imaging and acoustic tweezers.
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Affiliation(s)
- Hairong Zheng
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology,
Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Lili Niu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology,
Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Weibao Qiu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology,
Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Dong Liang
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology,
Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Xiaojing Long
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology,
Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Guanglin Li
- Shenzhen Institute of Advanced Integration Technology, Chinese Academy of Sciences and The Chinese University of Hong Kong, Shenzhen, 518055, China
| | - Zhiyuan Liu
- Shenzhen Institute of Advanced Integration Technology, Chinese Academy of Sciences and The Chinese University of Hong Kong, Shenzhen, 518055, China
| | - Long Meng
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology,
Chinese Academy of Sciences, Shenzhen, 518055, China
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49
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Song P, Rubin JM, Lowerison MR. Super-resolution ultrasound microvascular imaging: Is it ready for clinical use? Z Med Phys 2023; 33:309-323. [PMID: 37211457 PMCID: PMC10517403 DOI: 10.1016/j.zemedi.2023.04.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 05/23/2023]
Abstract
The field of super-resolution ultrasound microvascular imaging has been rapidly growing over the past decade. By leveraging contrast microbubbles as point targets for localization and tracking, super-resolution ultrasound pinpoints the location of microvessels and measures their blood flow velocity. Super-resolution ultrasound is the first in vivo imaging modality that can image micron-scale vessels at a clinically relevant imaging depth without tissue destruction. These unique capabilities of super-resolution ultrasound provide structural (vessel morphology) and functional (vessel blood flow) assessments of tissue microvasculature on a global and local scale, which opens new doors for many enticing preclinical and clinical applications that benefit from microvascular biomarkers. The goal of this short review is to provide an update on recent advancements in super-resolution ultrasound imaging, with a focus on summarizing existing applications and discussing the prospects of translating super-resolution imaging to clinical practice and research. In this review, we also provide brief introductions of how super-resolution ultrasound works, how does it compare with other imaging modalities, and what are the tradeoffs and limitations for an audience who is not familiar with the technology.
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Affiliation(s)
- Pengfei Song
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, United States; Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, United States; Department of Bioengineering, University of Illinois Urbana-Champaign, United States; Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, United States.
| | - Jonathan M Rubin
- Department of Radiology, University of Michigan, Ann Arbor, United States
| | - Matthew R Lowerison
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, United States; Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, United States
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50
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Renaudin N, Pezet S, Ialy-Radio N, Demene C, Tanter M. Backscattering amplitude in ultrasound localization microscopy. Sci Rep 2023; 13:11477. [PMID: 37455266 DOI: 10.1038/s41598-023-38531-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 07/10/2023] [Indexed: 07/18/2023] Open
Abstract
In the last decade, Ultrafast ultrasound localisation microscopy has taken non-invasive deep vascular imaging down to the microscopic level. By imaging diluted suspensions of circulating microbubbles in the blood stream at kHz frame rate and localizing the center of their individual point spread function with a sub-resolution precision, it enabled to break the unvanquished trade-off between depth of imaging and resolution by microscopically mapping the microbubbles flux and velocities deep into tissue. However, ULM also suffers limitations. Many small vessels are not visible in the ULM images due to the noise level in areas dimly explored by the microbubbles. Moreover, as the vast majority of studies are performed using 2D imaging, quantification is limited to in-plane velocity or flux measurements which hinders the accurate velocity determination and quantification. Here we show that the backscattering amplitude of each individual microbubble can also be exploited to produce backscattering images of the vascularization with a higher sensitivity compared to conventional ULM images. By providing valuable information about the relative distance of the microbubble to the 2D imaging plane in the out-of-plane direction, backscattering ULM images introduces a physically relevant 3D rendering perception in the vascular maps. It also retrieves the missing information about the out-of-plane motion of microbubbles and provides a way to improve 3D flow and velocity quantification using 2D ULM. These results pave the way to improved visualization and quantification for 2D and 3D ULM.
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Affiliation(s)
- Noemi Renaudin
- Institute Physics for Medicine Paris, Inserm U1273, ESPCI Paris-PSL, Cnrs UMR8063, 75012, Paris, France
| | - Sophie Pezet
- Institute Physics for Medicine Paris, Inserm U1273, ESPCI Paris-PSL, Cnrs UMR8063, 75012, Paris, France
| | - Nathalie Ialy-Radio
- Institute Physics for Medicine Paris, Inserm U1273, ESPCI Paris-PSL, Cnrs UMR8063, 75012, Paris, France
| | - Charlie Demene
- Institute Physics for Medicine Paris, Inserm U1273, ESPCI Paris-PSL, Cnrs UMR8063, 75012, Paris, France
| | - Mickael Tanter
- Institute Physics for Medicine Paris, Inserm U1273, ESPCI Paris-PSL, Cnrs UMR8063, 75012, Paris, France.
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