Unsupervised Learning-Based Measurement of Ultrasonic Axial Transmission Velocity in Neonatal Bone.

OBJECTIVES: To develop a robust algorithm for estimating ultrasonic axial transmission velocity from neonatal tibial bone, and to investigate the relationships between ultrasound velocity and neonatal anthropometric measurements as well as clinical biochemical markers of skeletal health. METHODS: This study presents an unsupervised learning approach for the automatic detection of first arrival time and estimation of ultrasonic velocity from axial transmission waveforms, which potentially indicates bone quality. The proposed method combines the ReliefF algorithm and fuzzy C-means clustering. It was first validated using an in vitro dataset measured from a Sawbones phantom. It was subsequently applied on in vivo signals collected from 40 infants, comprising 21 males and 19 females. The extracted neonatal ultrasonic velocity was subjected to statistical analysis to explore correlations with the infants' anthropometric features and biochemical indicators. RESULTS: The results of in vivo data analysis revealed significant correlations between the extracted ultrasonic velocity and the neonatal anthropometric measurements and biochemical markers. The velocity of first arrival signals showed good associations with body weight (ρ = 0.583, P value <.001), body length (ρ = 0.583, P value <.001), and gestational age (ρ = 0.557, P value <.001). CONCLUSION: These findings suggest that fuzzy C-means clustering is highly effective in extracting ultrasonic propagating velocity in bone and reliably applicable in in vivo measurement. This work is a preliminary study that holds promise in advancing the development of a standardized ultrasonic tool for assessing neonatal bone health. Such advancements are crucial in the accurate diagnosis of bone growth disorders.

Nonlinear simulation for contrast ultrasound imaging.

Contrast ultrasound (CUS) has received much interest because of its sensitivity enhancement for blood flow imaging. However, there is still a lack of nonlinear simulation method for CUS, as conventional simulators cannot deal with the microbubble acoustic nonlinearity. In this paper, a nonlinear simulation method of CUS is developed based on a combination strategy of the k-space pseudospectral method and Rayleigh-Plesset Marmottant model. Different contrast pulse sequence strategies as well as the radial modulation imaging are simulated and compared using the proposed method. For blood flow imaging, simulations under different scenarios such as power Doppler and ultrasound localization microscopy are also carried out. Furthermore, a face-to-face comparison is performed between simulations and phantom experiments to validate the proposed method.

Allicin protects against LPS-induced cardiomyocyte injury by activating Nrf2-HO-1 and inhibiting NLRP3 pathways.

BACKGROUND: Allicin is a bioactive compound with potent antioxidative activity and plays a protective effect in myocardial damage and fibrosis. The role and mechanism of Allicin in septic cardiomyopathy are unclear. In this study, we investigated the effects and underlying mechanisms of Allicin on lipopolysaccharide (LPS) induced injury in H9c2 cardiomyocytes. METHODS: H9c2 cardiomyocyte cells were pretreated with Allicin (0, 25, 50, and 100 µM) for 2 h, followed by incubation with LPS (10 µg/mL) for 24 h at 37 °C. Cell viability (cell counting kit-8 [CCK-8]), apoptosis (TUNEL staining), oxidative stress (malondialdehyde [MDA] and superoxide dismutase [SOD]), and cytokines release (Interleukin beta [IL-ß], Interleukin 6 [IL-6], and tumor necrosis factor-alpha [TNF-α]) were determined. The mRNA and protein expression of nuclear factor erythroid 2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), and NLR family pyrin domain containing 3 (NLRP3) signaling pathway molecules were quantified by real-time quantitative PCR (RT-qPCR) and western blot, respectively. RESULTS: Allicin had no effect on H9c2 cell viability but attenuated LPS-induced injury, with increased cell viability, reduction in inflammatory cytokines release, apoptosis, reduced MDA, and increased SOD (P < 0.05). Additionally, Allicin increased Nrf2 and cellular HO-1 expressions in LPS-treated H9c2 cells. Moreover, Allicin modulated the NLRP3 inflammasome, increased the cleaved caspase-1 (p10) protein, and attenuated the LPS-induced increase in NLRP3, pro-IL-1ß, and IL-1ß proteins. Silencing of Nrf2 by siRNA (siNrf2) significantly attenuated Allicin-induced increase in cell viability and HO-1 and decrease in NLRP3 protein in LPS-stimulated H9c2 cells. CONCLUSIONS: Allicin protects cardiomyocytes against LPS­induced injury through activation of Nrf2/HO-1 and inhibition of NLRP3 signaling pathways.

Frequency-domain full-waveform inversion-based musculoskeletal ultrasound computed tomography.

Recently, full-waveform inversion (FWI) has become a promising tool for ultrasound computed tomography (USCT). However, as a computationally intensive technique, FWI suffers from computational burden, especially in conventional time-domain full-waveform inversion (TDFWI). On the contrary, frequency-domain full-waveform inversion (FDFWI) provides a relatively high computational efficiency as the propagation of discrete frequencies is much cheaper than full time-domain modeling. FDFWI has already been applied in soft tissue imaging, such as breast, but for the musculoskeletal model with high impedance contrast between hard and soft tissues, there is still a lack of an effective source estimation method. In this paper, a water-referenced data calibration method is proposed to address the source estimation challenge in the presence of bones, which achieves consistency between the measured and simulated data before the FDFWI procedure. To avoid the cycle-skipping local minimum effect and facilitate the algorithm convergence, a starting frequency criterion for musculoskeletal FDFWI is further proposed. The feasibility of the proposed method is demonstrated by numerical studies on retrieving the anatomies of the leg models and different musculoskeletal lesions. The study extends the advanced FDFWI method to the musculoskeletal system and provides an alternative solution for musculoskeletal USCT imaging with high computational efficiency.

Signal Processing Techniques Applied to Axial Transmission Ultrasound.

A new application of ultrasonography has been emerging in the bone quantitative ultrasound arena in the last twenty years: cortical bone characterization using axial transmission ultrasound (ATU). Although challenged by the complicated cortical tissue-ultrasonic wave interaction, ATU has proved to have promising potential to be a valuable diagnostic tool in the assessment of cortical bones. This chapter reviews the main landmarks of axial transmission signal processing in the past decade to provide a guide to the diversity of available techniques. In order to increase the readability of the chapter, the signal processing methods are categorized based on the experimental settings: single and multiple transmitter-receiver configuration. The review considers the key stages required for the analysis of bone guided-wave ultrasound data namely dispersion energy imaging, modal filtering, dispersion curve inversion, and measurement automation with integrated artificial intelligence concepts. Besides discussing the recent signal processing advances in the field of bone assessment by axial transmission, this communication offers developments that might be anticipated in the near future.

An Electromagnetic Fiber Acoustic Transducer with Dual Modes of Loudspeaker and Microphone.

A flexible fiber acoustic transducer is created by designing a parallel configuration of a Rubidium iron boron (NdFeB) magnet fiber and an aluminum fiber. The former provides a stable magnet field, while the latter vibrates to phonate upon applying alternating current or generates alternating voltage in the sound field. This single device exhibits dual functions as a loudspeaker or a microphone. As a fiber loudspeaker, it can generate 40-60 dB of audible (20 Hz-20 kHz) and directional sounds which can be used for blind navigation and controllable sound field distribution. The fiber acoustic transducer functions as a microphone when external sound waves force the aluminum fiber to vibrate. After the fiber microphones are woven into several different positions of a piece of clothing, the sound source can be accurately located based on the time differences reaching different microphones. This wearable fiber acoustic transducer is promising to be used to quickly search people in trouble during emergency rescue activities such as earthquakes or fires.

Risk Factors of Multidrug-Resistant Bacteria in Lower Respiratory Tract Infections: A Systematic Review and Meta-Analysis.

BACKGROUND: Multidrug-resistant (MDR) bacteria are the main cause of lower respiratory tract infections (LRTIs) with high mortality. The purpose of this study is to identify the risk factors associated with MDR by performing a systematic review and meta-analysis. METHODS: PubMed, EMBASE (via Ovid), and Cochrane Library were systematically searched for studies on the risk factors for MDR bacteria in LRTIs as of November 30, 2019. Literature screening, data abstraction, and quality assessment of the eligible studies were performed independently by two researchers. RESULTS: A total of 3,607 articles were retrieved, of which 21 articles representing 20 cohort studies published in English were included after title/abstract and full-text screening. Among the 21 articles involving 7,650 patients and 1,360 MDR organisms, ten reported the risk factors for MDR Gram-positive bacteria (GPB) and Gram-negative bacteria (GNB), ten for MDR GNB, and one for MDR GPB. The meta-analysis results suggested that prior antibiotic treatment, inappropriate antibiotic therapy, chronic lung disease, chronic liver disease and cerebral disease, prior MDR and PA infection/colonization, recent hospitalization, longer hospitalization stay, endotracheal tracheostomy and mechanical ventilation, tube feeding, nursing home residence, and higher disease severity score were independent risk factors for MDR bacteria. CONCLUSIONS: This review identified fourteen clinical factors that might increase the risk of MDR bacteria in patients with LRTIs. Clinicians could take into account these factors when selecting antibiotics for patients and determine whether coverage for MDR bacteria is required. More well-designed studies are needed to confirm the various risk factors for MDR bacteria in the future.

Differential Structure of Inductive Proximity Sensor.

The inductive proximity sensor (IPS) is applicable to displacement measurements in the aviation field due to its non-mechanical contact, safety, and durability. IPS can increase reliability of position detection and decrease maintenance cost of the system effectively in aircraft applications. Nevertheless, the specialty in the aviation field proposes many restrictions and requirements on the application of IPS, including the temperature drift effect of the resistance component of the IPS sensing coil. Moreover, reliability requirements of aircrafts restrict the use of computational-intensive algorithms and avoid the use of process control components. Furthermore, the environment of airborne electronic equipment restricts measurements driven by large current and proposes strict requirements on emission tests of radio frequency (RF) energy. For these reasons, a differential structured IPS measurement method is proposed in this paper. This measurement method inherits the numerical separation of the resistance and inductance components of the IPS sensing coil to improve the temperature adaptation of the IPS. The computational complexity is decreased by combining the dimension-reduced look-up table method to prevent the use of process control components. The proposed differential structured IPS is equipped with a differential structure of distant and nearby sensing coils to increase the detection accuracy. The small electric current pulse excitation decreases the RF energy emission. Verification results demonstrate that the differential structured IPS realizes the numerical decoupling calculation of the vector impedance of the sensing coil by using 61 look-up table units. The measuring sensitivity increased from 135.5 least significant bits (LSB)/0.10 mm of a single-sensing-coil structured IPS to 1201.4 LSB/0.10 mm, and the linear approximation distance error decreased from 99.376 µm to -3.240 µm. The proposed differential structured IPS method has evident comparative advantages compared with similar measuring techniques.

Effect of dexmedetomidine on rats with convulsive status epilepticus and association with activation of cholinergic anti-inflammatory pathway.

Convulsive status epilepticus (CSE) is a neurological disease with contraction and extension of limbs, leading to damage of hippocampus and cognition. This study aimed to explore the effects of dexmedetomidine (DEX) on the cognitive function and neuroinflammation in CSE rats. All rats were divided into control group, CSE group and DEX group. Morris water maze test was used to measure cognitive function. Acute hippocampal slices were made to detect long-term potentiation (LTP). Immunohistochemistry was used to determine the expression of α7-nicotinic acetylcholine receptor (α7-nAChR) and interleukin-1ß (IL-1ß). Enzyme-linked immunosorbent assay (ELISA) was used to measure serum levels of IL-1ß, tumor necrosis factor-α (TNF-α), S-100ß and brain-derived neurotrophic factor (BDNF). Our results showed that DEX improved the memory damage caused by CSE. DEX reduced seizure severity and increased the amplitudes and sustainable time of LTP, and also inhibited the hippocampal expression of α7-nAChR and IL-1ß in CSE rats. DEX treatment decreased serum IL-1ß, TNF-α and S-100ß levels and increased BDNF levels. The effects of DEX on seizure severity and LTP could be simulated by nicotine or attenuated by concurrent α-bungarotoxin (α-BGT) treatment. In conclusions, DEX significantly improved spatial cognitive dysfunction, reduced seizure severity and increased LTP in CSE rats. Improvements by DEX were closely related to enhancement of cholinergic anti-inflammatory pathway.

Clinical significance and prognosis of serum tenascin-C in patients with sepsis.

BACKGROUND: Tenascin-C is a pro-inflammatory glycoprotein with various biological functions. High expression of tenascin-C is found in inflammation, tissue remodeling, and autoimmune diseases. However, its expression and clinical significance in sepsis remain unclear. This study was designed to investigate the relationship between serum tenascin-C levels and disease severity and prognosis in patients with sepsis. METHODS: A total of 167 patients with sepsis admitted to the ICU were enrolled. Lood samples were collected within 24 h of admission. Serum tenascin-C levels were measured by enzyme-linked immunosorbent assay (ELISA). Follow-up was performed to observe 30-day mortality. RESULTS: Serum tenascin-C levels were significantly elevated in patients with sepsis compared with non-sepsis controls (P < 0.001). Serum tenascin-C levels were higher in nonsurvivors (58 cases) who died within 30 days (34.5%) compared to survivors (109 cases) (P < 0.001). In patients with sepsis, serum tenascin-C levels were significantly positively correlated with SOFA scores (P = 0.011), serum creatinine (P = 0.006), C-reactive protein (CRP) (P = 0.001), interleukin-6 (IL-6) (P < 0.001), and tumor necrosis factor α (TNF-α) (P = 0.026). Logistic multivariate regression models showed that serum tenascin-C levels were independent contributor of 30-day mortality. Kaplan-Meier curves showed that septic patients with high levels of serum tenascin-C (≥56.9 pg/mL) had significantly higher 30-day mortality than those with lower serum tenascin-C (< 56.9 pg/mL) (P < 0.001). CONCLUSION: Elevated serum tenascin-C was found in septic patients and associated with severity and poor prognosis.

Dispersive Radon transform.

Dispersion results in the spreading and overlapping of the wave-packets, which often limits the capability of signal interpretation; on the other hand, such a phenomenon can also be used for structure or media evaluation. In this study, the authors propose an original dispersive Radon transform (DRT), which is formulated as integration transform along a set of dispersion curves. Multichannel dispersive signals of each individual mode can be concentrated to a well localized region in the DRT domain. The proposed DRT establishes the sparse projection of the dispersive components and provides an efficient solution for mode separation, noise filtering, and missing data reconstruction. Particularly the DRT method allows projecting the temporal signals of dispersive waves on the space of parameters of interest, which can be used to solve the inverse problem for waveguide or media property estimation. The least-square procedure and sparse scheme of the DRT are introduced. A high-resolution DRT is designed based on an iterative reweighting inversion scheme, which resembles the infinite-aperture velocity gather. The proposed method is applied by analyzing ultrasonic guided waves in plate-like structures and in a human radius specimen. The results suggest that the DRT method can significantly enhance the interpretation of dispersive signals.

Dimension-Reduced Analog-Digital Mixed Measurement Method of Inductive Proximity Sensor.

Inductive proximity sensors (IPSs) present a unique no-contact advantage. They are widely preferred for displacement measurement in various industrial fields (e.g., aviation and aerospace), and they are improved continuously. When the inductance and resistance components of the IPS sensing core are separated, the influence of temperature drift on measurement can be eliminated. The complexity of online computation of component separation can be reduced using a two-dimensional look-up table method. However, this method exhibits disadvantages, such as large capacity of the look-up table, dependency on precision measurement of sensing core parameter, and nonlinear distribution of measurement resolution. This study aims to overcome these disadvantages by examining the nonlinear relationship between the response of the sensing core and the ambient temperature, and proposes a dimension-reduced measurement method. The proposed method extracts the characteristics of the response curves at two temperatures and calculates the characteristics of the response curves at any temperature using a linear approximation. The look-up table capacity is less than 0.37% of the two-dimensional look-up table capacity (condensed) under the same condition; dimension reduction enables the construction of a complete look-up table directly by calibration procedures and avoids precise measurement on sensing core parameters; the calibration procedures establish uniform mapping of the distribution of measurement resolution. The experiment shows that, when the measurement ranges are 0-6, 0-5, and 0-4 mm, the maximum measurement errors are 0.140, 0.065, and 0.040 mm, respectively, under temperature ranging from 20 ∘ C to 110 ∘ C. This study extends the measurement range from 0-5 mm to 0-7 mm and improves the measurement accuracy over 0.1 mm (50% at 5 mm) compared with the two-dimensional look-up table method. Therefore, the proposed method not only inherits the advantages of the original method but also achieves the above-mentioned expected capacity improvements effectively.

Multichannel processing for dispersion curves extraction of ultrasonic axial-transmission signals: Comparisons and case studies.

Some pioneering studies have shown the clinical feasibility of long bones evaluation using ultrasonic guided waves. Such a strategy is typically designed to determine the dispersion information of the guided modes to infer the elastic and structural characteristics of cortical bone. However, there are still some challenges to extract multimode dispersion curves due to many practical limitations, e.g., high spectral density of modes, limited spectral resolution and poor signal-to-noise ratio. Recently, two representative signal processing methods have been proposed to improve the dispersion curves extraction. The first method is based on singular value decomposition (SVD) with advantages of multi-emitter and multi-receiver configuration for enhanced mode extraction; the second one uses linear Radon transform (LRT) with high-resolution imaging of the dispersion curves. To clarify the pros and cons, a face to face comparison was performed between the two methods. The results suggest that the LRT method is suitable to separate the guided modes at low frequency-thickness-product ( fh) range; for multimode signals in broadband fh range, the SVD-based method shows more robust performances for weak mode enhancement and noise filtering. Different methods are valuable to cover the entire fh range for processing ultrasonic axial transmission signals measured in long cortical bones.

VoxelMorph-Based Deep Learning Motion Correction for Ultrasound Localization Microscopy of Spinal Cord.

Accurate assessment of spinal cord vasculature is important for the urgent diagnosis of injury and subsequent treatment. Ultrasound localization microscopy (ULM) offers super-resolution imaging of microvasculature by localizing and tracking individual microbubbles across multiple frames. However, a long data acquisition often involves significant motion artifacts caused by breathing and heartbeat, which further impairs the resolution of ULM. This effect is particularly pronounced in spinal cord imaging due to respiratory movement. We propose a VoxelMorph-based deep learning motion correction method to enhance ULM performance in spinal cord imaging. Simulations were conducted to demonstrate the motion estimation accuracy of the proposed method, achieving a mean absolute error of 8 µm. Results from in vivo experiments show that the proposed method efficiently compensates for rigid and nonrigid motion, providing improved resolution with smaller vascular diameters and enhanced microvessel reconstruction after motion correction. Nonrigid deformation fields with varying displacement magnitudes were applied to in vivo data for assessing the robustness of the algorithm.

Association between musculoskeletal pain and exposures to awkward postures during work: a compositional analysis approach.

OBJECTIVES: This study aimed to explore the association between arm elevation and neck/shoulder pain, and trunk forwarding bending and low back pain among home care workers. METHODS: Home care workers (N = 116) from 11 home care units in Trondheim, Norway, filled in pain assessment and working hours questionnaire, and wore 3 accelerometers for up to 7 consecutive days. Work time was partitioned into upright awkward posture, nonawkward posture, and nonupright time, i.e. sitting. Within a compositional approach framework, posture time compositions were expressed in terms of log-ratio coordinates for statistical analysis and modeling. Poisson generalized linear mixed models were used to analyze the relationship between arm elevation in upright postures and neck/shoulder pain, and between trunk forward bending in upright postures and low back pain, respectively. Isotemporal substitution analysis was used to investigate the association of pain assessment with the reallocation of time spent in the different postures. RESULTS: Time spent in awkward postures was modest, especially for the more extreme angles (60° and 90°). Adjusting for age, gender, and body mass index, our study suggested that the compositions of time spent by home care workers in awkward postures were significantly associated with pain assessment (P < 0.01). Isotemporal substitution analysis showed that reallocating 5 min from upright posture with arms elevated below to above 60° and 90° was associated with a 6.8% and 19.9% increase in the neck/shoulder pain score, respectively. Reallocating 5 min from a forward bending posture while upright below to above 30°, 60°, and 90° was associated with 1.8%, 3.5%, and 4.0% increase in low back pain, respectively. CONCLUSIONS: Although the exposure to awkward postures was modest, our results showed an association between increased time spent in awkward postures and an increase in neck/shoulder pain and low back pain in home care workers. As musculoskeletal pain is the leading cause of sickness absence, these findings suggest that home care units could benefit from re-organizing work to avoid excessive arm elevation and trunk forward bending in workers.

Transcranial ultrafast ultrasound Doppler imaging: A phantom study.

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.

Transcriptomic effects of paternal cocaine-seeking on the reward circuitry of male offspring.

It has been previously established that paternal development of a strong incentive motivation for cocaine can predispose offspring to develop high cocaine-seeking behavior, as opposed to sole exposure to the drug that results in drug resistance in offspring. However, the adaptive changes of the reward circuitry have not been fully elucidated. To infer the key nuclei and possible hub genes that determine susceptibility to addiction in offspring, rats were randomly assigned to three groups, cocaine self-administration (CSA), yoked administration (Yoke), and saline self-administration (SSA), and used to generate F1. We conducted a comprehensive transcriptomic analysis of the male F1 offspring across seven relevant brain regions, both under drug-naïve conditions and after cocaine self-administration. Pairwise differentially expressed gene analysis revealed that the orbitofrontal cortex (OFC) exhibited more pronounced transcriptomic changes in response to cocaine exposure, while the dorsal hippocampus (dHip), dorsal striatum (dStr), and ventral tegmental area (VTA) exhibited changes that were more closely associated with the paternal voluntary cocaine-seeking behavior. Consistently, these nuclei showed decreased dopamine levels, elevated neuronal activation, and elevated between-nuclei correlations, indicating dopamine-centered rewiring of the midbrain circuit in the CSA offspring. To determine if possible regulatory cascades exist that drive the expression changes, we constructed co-expression networks induced by paternal drug addiction and identified three key clusters, primarily driven by transcriptional factors such as MYT1L, POU3F4, and NEUROD6, leading to changes of genes regulating axonogenesis, synapse organization, and membrane potential, respectively. Collectively, our data highlight vulnerable neurocircuitry and novel regulatory candidates with therapeutic potential for disrupting the transgenerational inheritance of vulnerability to cocaine addiction.

Frame rate effects and their compensation on super-resolution microvessel imaging using ultrasound localization microscopy.

Ultrasound localization microscopy (ULM) breaks the diffraction limit and allows imaging microvasculature at micrometric resolution while preserving the penetration depth. Frame rate plays an important role for high-quality ULM imaging, but there is still a lack of review and investigation of the frame rate effects on ULM. This work aims to clarify how frame rate influences the performance of ULM, including the effects of microbubble detection, localization and tracking. The performance of ULM was evaluated using an in vivo rat brain dataset (15.6 MHz, 3 tilted plane waves (-5°, 0°, +5°), at a compounded frame rate of 1000 Hz) with different frame rates. Quantification methods, including Fourier ring correlation and saturation parameter, were applied to analyze the spatial resolution and reconstruction efficiency, respectively. In addition, effects on each crucial step in ULM processing were further analyzed. Results showed that when frame rates dropped from 1000 Hz to 250 Hz, the spatial resolution deteriorated from 9.9 µm to 15.0 µm. Applying a velocity constraint was able to improve the ULM performance, but inappropriate constraint may artificially result in high apparent resolution. For the dataset, compared with the results of 1000 Hz frame rate, the velocity was underestimated at 100 Hz with 47.18% difference and the saturation was reduced from 55.00% at 1000 Hz to 43.34% at 100 Hz. Analysis showed that inadequate frame rate generated unreliable microbubble detection, localization and tracking as well as incomplete track reconstruction, resulting in the deterioration in spatial resolution, the underestimation in velocity measurement and the decrease in saturation. Finally, a guidance of determining the frame rate requirement was discussed by considering the required spatial sampling points based on vessel morphology, clutter filtering method, tracking algorithm and acquisition time, which provides indications for future clinical application of ULM method.

Ultrafast Doppler Imaging of Brain Arteriovenous Malformation.

Ultrafast ultrasound Doppler imaging offers a new and advantageous intraoperative method for brain lesions. Compared to the conventional color Doppler ultrasound system, the ultrafast Doppler allows us to image hemodynamics in small vasculature in an unprecedented high spatio-temporal resolution without using contrast agent. This report presents an intraoperative ultrafast ultrasound Doppler image of a 53-year-old male with a language eloquent area brain arteriovenous malformation. The advanced ultrafast Doppler method provides the nidus vasculature hemodynamics with a spatial resolution of 300 µm at thousands of framerates per second. The image also demonstrates that no abnormal vessels infiltrated the eloquent gyrus as the piamatral small vessels outlined the intact boundary. Successful removal of the nidus with full language function preservation highlights the potentials of ultrafast Doppler imaging to improve diagnostic capabilities and surgical outcomes for patients with intracranial lesions.

Super-resolution Ultrasound Microvascular Angiography for Spinal Cord Penumbra Imaging.

OBJECTIVE: After spinal cord injury (SCI) or ischemia, timely intervention in the penumbra, such as recanalization and tissue reperfusion, is essential for preservation of its function. However, limited by imaging resolution and micro-blood flow sensitivity, golden standard angiography modalities, including magnetic resonance angiography (MRA) and digital subtraction angiography (DSA), are still not applicable for spinal cord microvascular imaging. Regarding spinal cord penumbra, to the best of authors' knowledge, currently, there is no efficient in vivo imaging modality for its evaluation. With tens-of-micrometer resolution and deep penetration, advanced ultrasound localization microscopy (ULM) could potentially meet the needs of emergent diagnosis and long-term monitoring of spinal cord penumbra. METHODS: ULM microvasculature imaging was performed on rats with all laminae removed to obtain the blood supply in major spinal cord segments (C5-L5). For adult rats with spinal cord penumbra induced by compression injury (1 s, 10 s and 15 s), ULM imaging was conducted. The corresponding angiography results are investigated in terms of microvessel saturation, morphology, and flow velocity. The Basso/Beattie/Bresnahan (BBB) locomotor rating scale and hematoxylin and eosin staining were utilized for model validation and comparison. RESULTS: The feasibility of ULM enabling spinal cord penumbra imaging and development monitoring was demonstrated. The focal injury core and penumbra can be clearly identified using the proposed method. Significant difference of perfusion can be observed after 1 s, 10 s and 15 s compression. Quantitative results show a high correlation between in vivo ultrasonic angiography, BBB functional evaluation and ex vivo histology assessment under different compression duration. CONCLUSION: It is demonstrated that the super-resolution ULM micro-vasculature imaging can be used to evaluate the penumbra in spinal cord at acute and early stage of chronic phase, providing an efficient modality for micro-hemodynamics monitoring of the spinal cord.