Ultrafast Imaging Research Articles

Quantification of brain-wide vascular resistivity via ultrafast Doppler in human neonates helps early detection of white matter injury

Preterm birth is associated with cerebrovascular development disruption and can induce white matter injuries (WMI). Transfontanellar ultrasound Doppler is the most widely used clinical imaging technique to monitor neonatal cerebral vascularisation and haemodynamics based on vascular indexes such as the resistivity index (RI); however, it has poor predictive value for brain damage. Indeed, these RI measurements are currently limited to large vessels, leading to a very limited probing of the brain’s vascularisation, which may hinder prognosis. Here we show that ultrafast Doppler imaging (UfD) enables simultaneous quantification, in the whole field of view, of the local RI and vessel diameter, even in small vessels. Combining both pieces of information, we defined two new comprehensive resistivity parameters of the vascular trees. First, we showed that our technique is more sensitive in the early characterisation of the RI modifications between term and preterm neonates and for the first time we could show that the RI depends both on the vessel diameter and vascular territory. We then showed that our parameters can be used for early prediction of WMI. Our results demonstrate the potential of UfD to provide new biomarkers and pave the way for continuous monitoring of neonatal brain resistivity.

Mesoscopic architecture and molecular dynamics in focal adhesions as revealed by ultrafast single-molecule imaging

Mesoscopic architecture and molecular dynamics in focal adhesions as revealed by ultrafast single-molecule imaging

Properties and characteristics of the nanosecond discharge developing at the water–air interface: tracking evolution from a diffused streamer to a spark filament

The characteristics of nanosecond discharge propagating along the water–air interface in a unique dielectric-barrier discharge (DBD)-like configuration with coplanar electrodes submerged in deionised (DI)/tap water are studied by combining ultrafast imaging and emission spectra with electrical characteristics. Time-resolved images provide a clear signature of streamer channels excited on the water surface at either side of the blade (insulated plastic separating the anode/cathode) and propagating perpendicularly away from it towards the anode/cathode with different velocities. Later on, the streamer channels convert into a few discrete and bright discharge channels due to ionisation instability (spark phase). There is no distinctive dependence on water conductivity in the streamer phase, as the optical emission spectroscopy and images of discharges only showed an increase of the luminosity and no significant changes in morphology. However, in the spark phase, more numerous, brighter, and thicker filaments form in tap water. The time-resolved emission spectra reveal the dominance of the first and second positive system of N2 molecular bands in the streamer phase, followed by the appearance of atomic lines of hydrogen, nitrogen, and oxygen in the spark phase. The emission spectra are utilised to estimate several important parameters (gas temperature, reduced electric field ( E/N ), and electron density ( ne )). The streamer phase is characterised by a low gas temperature and a peak E/N amplitude between 700 and 850 Td. On the other hand, the subsequent spark phase is characterised by a gas temperature of ∼400/1100 K and a free electron density up to ne∼1017 –1018 cm−3 in DI/tap water.

Probing the glioma microvasculature: a case series of the comparison between perfusion MRI and intraoperative high-frame-rate ultrafast Doppler ultrasound

BackgroundWe aimed to describe the microvascular features of three types of adult-type diffuse glioma by comparing dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) with intraoperative high-frame-rate ultrafast Doppler ultrasound.MethodsCase series of seven patients with primary brain tumours underwent both DSC perfusion MRI and intra-operative high-frame-rate ultrafast Doppler ultrasound. From the ultrasound images, three-dimensional vessel segmentation was obtained of the tumour vascular bed. Relative cerebral blood volume (rCBV) maps were generated with leakage correction and normalised to the contralateral normal-appearing white matter. From tumour histograms, median, mean, and maximum rCBV ratios were extracted.ResultsLow-grade gliomas (LGGs) showed lower perfusion than high-grade gliomas (HGGs), as expected. Within the LGG subgroup, oligodendroglioma showed higher perfusion than astrocytoma. In HGG, the median rCBV ratio for glioblastoma was 3.1 while astrocytoma grade 4 showed low perfusion with a median rCBV of 1.2. On the high-frame-rate ultrafast Doppler ultrasound images, all tumours showed a range of rich and organised vascular networks with visually apparent abnormal vessels, even in LGG.ConclusionsThis unique case series revealed in vivo insights about the microvascular architecture in both LGGs and HGGs. Ultrafast Doppler ultrasound revealed rich vascularisation, also in tumours with low perfusion at DSC MRI. These findings warrant further investigations using advanced MRI postprocessing, in particular for characterising adult-type diffuse glioma.Relevance statementOur findings challenge the current assumption behind the estimation of relative cerebral blood volume that the distribution of blood vessels in a voxel is random.Key points• Ultrafast Doppler ultrasound revealed rich vascularity irrespective of perfusion dynamic susceptibility contrast MRI state.• Rich and organised vascularisation was also observed even in low-grade glioma.• These findings challenge the assumptions for cerebral blood volume estimation with MRI.Graphical

Four-Dimensional Flow Echocardiography: Blood Speckle Tracking in Congenital Heart Disease: How to Apply, How to Interpret, What Is Feasible, and What Is Missing Still.

Blood speckle tracking echocardiography (BSTE) is a new, promising 4D flow ultrafast non-focal plane imaging technique. The aim of the present investigation is to provide a review and update on potentialities and application of BSTE in children with congenital heart disease (CHD) and acquired heart disease. A literature search was performed within the National Library of Medicine using the keywords "echocardiography", "BST", and "children". The search was refined by adding the keywords "ultrafast imaging", "CHD", and "4D flow". Fifteen studies were finally included. Our analysis outlined how BSTE is highly feasible, fast, and easy for visualization of normal/abnormal flow patterns in healthy children and in those with CHD. BSTE allows for visualization and basic 2D measures of normal/abnormal vortices forming the ventricles and in the main vessel. Left ventricular vortex characteristics and aortic flow patterns have been described both in healthy children and in those with CHD. Complex analysis (e.g., energy loss, vorticity, and vector complexity) are also highly feasible with BSTE, but software is currently available only for research. Furthermore, current technology allows for BSTE only in neonates and low-weight children (e.g., <40 kg). In summary, the feasibility and potentialities of BSTE as a complementary diagnostic tool in children have been proved; however, its systemic use is hampered by the lack of (i) accessible tools for complex quantification and for acquisition at all ages/weight, (ii) data on the diagnostic/prognostic significance of BSTE, and (iii) consensus/recommendation papers indicating when and how BSTE should be employed.

Photoacoustic elastography based on laser-excited shear wave

Elastography can be used as a diagnostic method for quantitative characterization of tissue hardness information and thus, differential changes in pathophysiological states of tissues. In this study, we propose a new method for shear wave elastography (SWE) based on laser-excited shear wave, called photoacoustic shear wave elastography (PASWE), which combines photoacoustic (PA) technology with ultrafast ultrasound imaging. By using a focused laser to excite shear waves and ultrafast ultrasonic imaging for detection, high-frequency excitation of shear waves and noncontact elastic imaging can be realized. The laser can stimulate the tissue with the light absorption characteristic to produce the thermal expansion, thus producing the shear wave. The frequency of shear wave induced by laser is higher and the frequency band is wider. By tracking the propagation of shear wave, Young’s modulus of tissue is reconstructed in the whole shear wave propagation region to further evaluate the elastic information of tissue. The feasibility of the method is verified by experiments. Compared with the experimental results of supersonic shear imaging (SSI), it is proved that the method can be used for quantitative elastic imaging of the phantoms. In addition, compared with the SSI method, this method can realize the noncontact excitation of the shear wave, and the frequency of the shear wave excited by the laser is higher than that of the acoustic radiation force (ARF), so the spatial resolution is higher. Compared to the traditional PA elastic imaging method, this method can obtain a larger imaging depth under the premise of ensuring the imaging resolution, and it has potential application value in the clinical diagnosis of diseases requiring noncontact quantitative elasticity.

Observation of a single protein by ultrafast X-ray diffraction

The idea of using ultrashort X-ray pulses to obtain images of single proteins frozen in time has fascinated and inspired many. It was one of the arguments for building X-ray free-electron lasers. According to theory, the extremely intense pulses provide sufficient signal to dispense with using crystals as an amplifier, and the ultrashort pulse duration permits capturing the diffraction data before the sample inevitably explodes. This was first demonstrated on biological samples a decade ago on the giant mimivirus. Since then, a large collaboration has been pushing the limit of the smallest sample that can be imaged. The ability to capture snapshots on the timescale of atomic vibrations, while keeping the sample at room temperature, may allow probing the entire conformational phase space of macromolecules. Here we show the first observation of an X-ray diffraction pattern from a single protein, that of Escherichia coli GroEL which at 14 nm in diameter is the smallest biological sample ever imaged by X-rays, and demonstrate that the concept of diffraction before destruction extends to single proteins. From the pattern, it is possible to determine the approximate orientation of the protein. Our experiment demonstrates the feasibility of ultrafast imaging of single proteins, opening the way to single-molecule time-resolved studies on the femtosecond timescale.

Quantifying injury expansion in the cervical spinal cord with intravital ultrafast contrast-enhanced ultrasound imaging

Spinal cord injury is characterized by hemodynamic disruption at the injury epicenter and hypoperfusion in the penumbra, resulting in progressive ischemia and cell death. This degenerative secondary injury process has been well-described, though mostly using ex vivo or depth-limited optical imaging techniques. Intravital contrast-enhanced ultrasound enables longitudinal, quantitative evaluation of anatomical and hemodynamic changes in vivo through the entire spinal parenchyma. Here, we used ultrasound imaging to visualize and quantify subacute injury expansion (through 72 h post-injury) in a rodent cervical contusion model. Significant intraparenchymal hematoma expansion was observed through 72 h post-injury (1.86 ± 0.17-fold change from acute, p < 0.05), while the volume of the ischemic deficit largely increased within 24 h post-injury (2.24 ± 0.27-fold, p < 0.05). Histology corroborated these findings; increased apoptosis, tissue and vessel loss, and sustained tissue hypoxia were observed at 72 h post-injury. Vascular resistance was significantly elevated in the remaining perfused tissue, likely due in part to deformation of the central sulcal artery nearest to the lesion site. In conjunction, substantial hyperemia was observed in all perilesional areas examined except the ipsilesional gray matter. This study demonstrates the utility of longitudinal ultrasound imaging as a quantitative tool for tracking injury progression in vivo.

Increasing particle concentration enhances particle penetration depth but slows down liquid imbibition in thin fibrous filters

The transport of particles within thin, porous media is a complex process which received growing attention due to its applications in filtration, printing and microfluidics devices. The effect of particles on liquid imbibition and particle clogging can reduce the performance and lifetime of these applications. However, these processes are still not clearly understood and are challenging to investigate. The goal of this study is to increase our understanding about the effect of particle concentration on the imbibition process in thin fibrous membrane filters. In this study, an Ultra-Fast Imaging NMR method is used to study the particle penetration inside nylon membrane filters for particle suspensions with varying particle concentrations (C0). The measurements revealed that increasing the particle concentration increases the particle penetration depth S(t) as governed by a Langmuir isotherm given by S(t)=l(t)(1+κC0)/1+κ(C0+Cb,m), with Cb,m the bound particles and κ the binding constant. Secondly, in droplet penetration, particles slow down liquid penetration in a Darcy like manner where effect on viscosity (η) and surface tension (σ) determine the penetration speed rather than changes within permeability (K0). The final liquid front (l), scaled according to l2∝σt/η. The particle penetration depths were verified using scanning electron microscopy images.

An ultra-fast and energy-efficient CNTFET-based image corner detection hardware for real-time image processing applications

In image processing and machine vision, corner detection is pivotal in diverse applications, including computer vision, 3D reconstruction, face detection, object tracking, and video technologies. Despite the wide usage, the real-time and energy-efficient hardware implementation of corner detection algorithms remains a critical challenge because of the computational resource limitations. On the other hand, owing to the complicated nature of corner detection algorithms, their hardware implementation has been limited to the graphics processing unit (GPU) and field programmable gate arrays (FPGA) platforms. In this regard, this work aims to propose a novel and ultra-efficient carbon nanotube field-effect transistor (CNTFET)-based hardware for image corner detection. Thanks to the proposed corner detection algorithm, the designed hardware has been realized using 2742 transistors with competitive accuracy. The proposed corner detection hardware indicated a remarkable salt-and-pepper noise immunity without using any noise reduction circuit. Our comprehensive simulations demonstrate 78%, 87%, and 94.5% total average improvements in delay, power, and energy compared to the other related corner detection hardware. Moreover, the proposed CNTFET-based corner detection hardware shows a 43 ps propagation delay, demonstrating its real-time operation. The proposed corner detection algorithm at the system level shows suitable accuracy metrics such as Recall, Precision, and error of detection (EoD) compared to the other well-known corner detectors. Our method has established a new pathway for real-time circuit-level hardware design for image processing and machine vision applications.

Five-view three-dimensional reconstruction for ultrafast dynamic imaging of pulsed radiation sources

Multiaxial neutron/x-ray imaging and three-dimensional (3D) reconstruction techniques play a crucial role in gaining valuable insights into the generation and evolution mechanisms of pulsed radiation sources. Owing to the short emission time (∼200 ns) and drastic changes of the pulsed radiation source, it is necessary to acquire projection data within a few nanoseconds in order to achieve clear computed tomography 3D imaging. As a consequence, projection data that can be used for computed tomography image reconstruction at a certain moment are often available for only a few angles. Traditional algorithms employed in the process of reconstructing 3D images with extremely incomplete data may introduce significant distortions and artifacts into the final image. In this paper, we propose an iterative image reconstruction method using cylindrical harmonic decomposition and a self-supervised denoising network algorithm based on the deep image prior method. We augment the prior information with a 2D total variation prior and a 3D deep image prior. Single-wire Z-pinch imaging experiments have been carried out at Qin-1 facility in five views and four frames, with a time resolution of 3 ns for each frame and a time interval of 40 ns between adjacent frames. Both numerical simulations and experiments verify that our proposed algorithm can achieve high-quality reconstruction results and obtain the 3D intensity distribution and evolution of extreme ultraviolet and soft x-ray emission from plasma.

Ultrafast, Single-Event Ptychographic Imaging of Transient Electron Dynamics

Dynamic phenomena occurring on the ultrafast time scales are inherently difficult to image. While pump–probe techniques have been used for decades, probing nonrepeatable phenomena precludes this form of imaging. Additionally, many ultrafast phenomena, such as electron dynamics, exhibit low amplitude contrast in the optical wavelength range and thus require quantitative phase imaging. To better understand the underlying physics involved in a plethora of ultrafast phenomena, advanced imaging techniques must be developed to observe single events at an ultrafast time scale. Here, we present, to the best of our knowledge, the first ptychographic imaging system capable of observing ultrafast dynamics from a single event. We demonstrate ultrafast dynamic imaging by observing the conduction band electron population from a 2-photon absorption event in ZnSe pumped by a single femtosecond pulse. We verify experimental observations by comparing them to numeric solutions of a nonlinear envelope equation. Our imaging method represents a major step forward in ultrafast imaging, bringing the capabilities of ptychography to the ultrafast regime.

ULM-MbCNRT: In vivo Ultrafast Ultrasound Localization Microscopy by Combining Multi-branch CNN and Recursive Transformer.

Ultrasound localization microscopy (ULM) overcomes the acoustic diffraction limit by localizing tiny microbubbles (MBs), thus enabling the microvascular to be rendered at sub-wavelength resolution. Nevertheless, to obtain such superior spatial resolution, it is necessary to spend tens of seconds gathering numerous ultrasound (US) frames to accumulate MB events required, resulting in ULM imaging still suffering from trade-offs between imaging quality, data acquisition time and data processing speed. In this paper, we present a new deep learning (DL) framework combining multi-branch CNN and recursive Transformer, termed as ULM-MbCNRT, that is capable of reconstructing a super-resolution image directly from a temporal mean low-resolution image generated by averaging much fewer raw US frames, i.e., implement an ultrafast ULM imaging. To evaluate the performance of ULM-MbCNRT, a series of numerical simulations and in vivo experiments are carried out. Numerical simulation results indicate that ULM-MbCNRT achieves high-quality ULM imaging with ~10-fold reduction in data acquisition time and ~130-fold reduction in computation time compared to the previous DL method (e.g., the modified sub-pixel convolutional neural network, ULM-mSPCN). For the in vivo experiments, when comparing to the ULM-mSPCN, ULM-MbCNRT allows ~37-fold reduction in data acquisition time (~0.8 s) and ~2134-fold reduction in computation time (~0.87 s) without sacrificing spatial resolution. It implies that ultrafast ULM imaging holds promise for observing rapid biological activity in vivo, potentially improving the diagnosis and monitoring of clinical conditions.

Enhancing Row-column array (RCA)-based 3D ultrasound vascular imaging with spatial-temporal similarity weighting.

Ultrasound vascular imaging (UVI) is a valuable tool for monitoring the physiological states and evaluating the pathological diseases. Advancing from conventional two-dimensional (2D) to three-dimensional (3D) UVI would enhance the vasculature visualization, thereby improving its reliability. Row-column array (RCA) has emerged as a promising approach for cost-effective ultrafast 3D imaging with a low channel count. However, ultrafast RCA imaging is often hampered by high-level sidelobe artifacts and low signal-to-noise ratio (SNR), which makes RCA-based UVI challenging. In this study, we propose a spatial-temporal similarity weighting (St-SW) method to overcome these challenges by exploiting the incoherence of sidelobe artifacts and noise between datasets acquired using orthogonal transmissions. Simulation, in vitro blood flow phantom, and in vivo experiments were conducted to compare the proposed method with existing orthogonal plane wave imaging (OPW), row-column-specific frame-multiply-and-sum beamforming (RC-FMAS), and XDoppler techniques. Qualitative and quantitative results demonstrate the superior performance of the proposed method. In simulations, the proposed method reduced the sidelobe level by 31.3 dB, 20.8 dB, and 14.0 dB, compared to OPW, XDoppler, and RC-FMAS, respectively. In the blood flow phantom experiment, the proposed method significantly improved the contrast-to-noise ratio (CNR) of the tube by 26.8 dB, 25.5 dB, and 19.7 dB, compared to OPW, XDoppler, and RC-FMAS methods, respectively. In the human submandibular gland experiment, it not only reconstructed a more complete vasculature but also improved the CNR by more than 15 dB, compared to OPW, XDoppler, and RC-FMAS methods. In summary, the proposed method effectively suppresses the side-lobe artifacts and noise in images collected using an RCA under low SNR conditions, leading to improved visualization of 3D vasculatures.

Image-Derived Skeletal Muscle Activation Metric Map: a Forearm Study Using Ultra-Fast Ultrasound Imaging and High-Density Electromyography.

Quantification of the skeletal muscle response can help better understand the fundamentals of the musculoskeletal system and can serve as a diagnostic measure or recovery assessment tool during rehabilitation for neurological injuries. Surface electromyography (EMG) is commonly used to measure muscle activity, but it is limited to detecting myoelectric signals without anatomy associated information. In this study, we proposed to use ultra-fast ultrasound imaging and introduced a new image analysis methodology to quantify a muscle's spatialtemporal mechanical response. The methodology is based on analyzing the spatial-temporal change of the impulsive kinetic energy during the period of muscle contraction. The analysis can derive an anatomy-registered muscle activation metric map that localizes regions of muscle activation. To demonstrate this, we intentionally evoked regional muscle responses in five participants without disabilities by electrically stimulating the median nerve and individual forearm muscle groups, respectively. Both ultrasound images and high-density EMG (HD-EMG) data were recorded and processed. We presented the ultrasound image-derived activation localization from five participants and compared the results with HD-EMG measurements. The comparison indicates a good resemblance for describing muscle recruitment pattern. The proposed methodology can potentially become an alternative or complementary approach to surface EMG for the study of skeletal muscle activation and for diagnosis and prognosis in clinical settings.

Ultrafast scintillation at room temperature achieved in CsPbCl3-based single crystals through Br over-doping

The realization of sub-nanosecond scintillation in CsPbCl3-based single crystals by Br over-doping shows great potential for their application in ultrafast imaging.

Curved toroidal row column addressed transducer for 3D ultrafast ultrasound imaging.

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.

Electron-photon quantum interaction enables novel ultrafast electron imaging approaches

Electron-photon quantum interaction enables novel ultrafast electron imaging approaches

Physics-Guided Neural Networks for Intraventricular Vector Flow Mapping.

Intraventricular vector flow mapping (iVFM) seeks to enhance and quantify color Doppler in cardiac imaging. In this study, we propose novel alternatives to the traditional iVFM optimization scheme by utilizing physics-informed neural networks (PINNs) and a physics-guided nnU-Net-based supervised approach. When evaluated on simulated color Doppler images derived from a patient-specific computational fluid dynamics model and in vivo Doppler acquisitions, both approaches demonstrate comparable reconstruction performance to the original iVFM algorithm. The efficiency of PINNs is boosted through dual-stage optimization and pre-optimized weights. On the other hand, the nnU-Net method excels in generalizability and real-time capabilities. Notably, nnU-Net shows superior robustness on sparse and truncated Doppler data while maintaining independence from explicit boundary conditions. Overall, our results highlight the effectiveness of these methods in reconstructing intraventricular vector blood flow. The study also suggests potential applications of PINNs in ultrafast color Doppler imaging and the incorporation of fluid dynamics equations to derive biomarkers for cardiovascular diseases based on blood flow.

Deep Power-aware Tunable Weighting for Ultrasound Microvascular Imaging.

Ultrasound microvascular imaging (UMI), including ultrafast power Doppler imaging (uPDI) and ultrasound localization microscopy (ULM), obtains blood flow information through plane wave transmissions at high frame rates. However, low signal-to-noise ratio of plane waves causes low image quality. Adaptive beamformers have been proposed to suppress noise energy to achieve higher image quality accompanied by increasing computational complexity. Deep learning (DL) leverages powerful hardware capabilities to enable rapid implementation of noise suppression at the cost of flexibility. To enhance the applicability of DL-based methods, in this work, we propose a deep power-aware tunable (DPT) weighting (i.e., postfilter) for delay-and-sum (DAS) beamforming to improve UMI by enhancing plane wave images. The model, called Yformer is a hybrid structure combining convolution and Transformer. With the DAS beamformed and compounded envelope image as input, Yformer can estimate both noise power and signal power. Furthermore, we utilize the obtained powers to compute pixel-wise weights by introducing a tunable noise control factor, which is tailored for improving the quality of different UMI applications. In vivo experiments on the rat brain demonstrate that Yformer can accurately estimate the powers of noise and signal with the structural similarity index (SSIM) higher than 0.95. The performance of the DPT weighting is comparable to that of superior adaptive beamformer in uPDI with low computational cost. The DPT weighting was then applied to four different datasets of ULM, including public simulation, public rat brain, private rat brain, and private rat liver datasets, showing excellent generalizability using the model trained by the private rat brain dataset only. In particular, our method indirectly improves the resolution of liver ULM from 25.24 μm to 18.77 μm by highlighting small vessels. In addition, the DPT weighting exhibits more details of blood vessels with faster processing, which has the potential to facilitate the clinical applications of high-quality UMI.