Quantification Of Flow Velocity Research Articles

Fabrication and characterization of high-sensitivity, wide-range, and flexible MEMS thermal flow velocity sensors

With the rapid development of various fields, including aerospace, industrial measurement and control, and medical monitoring, the need to quantify flow velocity measurements is increasing. It is difficult for traditional flow velocity sensors to fulfill accuracy requirements for velocity measurements due to their small ranges, susceptibility to environmental impacts, and instability. Herein, to optimize sensor performance, a flexible microelectromechanical system (MEMS) thermal flow sensor is proposed that combines the working principles of thermal loss and thermal temperature difference and utilizes a flexible cavity substrate made of a low-thermal-conductivity polyimide/SiO2 (PI/SiO2) composite porous film to broaden the measurement range and improve the sensitivity. The measurement results show that the maximum measurable flow velocity can reach 30 m/s with a resolution of 5.4 mm/s. The average sensitivities of the sensor are 59.49 mV/(m s−1) in the medium-to-low wind velocity range of 0–2 m/s and 467.31 mV/(m s−1) in the wind velocity range of 2–30 m/s. The sensor proposed in this work can enable new applications of flexible flow sensors and wearable devices.

A comparison of ultrafast and conventional spectral Doppler ultrasound to measure cerebral blood flow velocity during inguinal hernia repair in infants

BackgroundUltrafast cerebral Doppler ultrasound enables simultaneous quantification and visualization of cerebral blood flow velocity. The aim of this study is to compare the use of conventional and ultrafast spectral Doppler during anesthesia and their potential to show the effect of anesthesiologic procedures on cerebral blood flow velocities, in relation to blood pressure and cerebral oxygenation in infants undergoing inguinal hernia repair. MethodsA single-center prospective observational cohort study in infants up to six months of age. We evaluated conventional and ultrafast spectral Doppler cerebral ultrasound measurements in terms of number of successful measurements during the induction of anesthesia, after sevoflurane induction, administration of caudal analgesia, a fluid bolus and emergence of anesthesia. Cerebral blood flow velocity was quantified in pial arteries using conventional spectral Doppler and in the cerebral cortex using ultrafast Doppler by peak systolic velocity, end diastolic velocity and resistivity index. ResultsTwenty infants were included with useable conventional spectral Doppler images in 72/100 measurements and ultrafast Doppler images in 51/100 measurements. Intraoperatively, the success rates were 53/60 (88.3%) and 41/60 (68.3%), respectively. Cerebral blood flow velocity increased after emergence for both conventional (end diastolic velocity, from 2.01 to 2.75 cm/s, p < 0.001) and ultrafast spectral Doppler (end diastolic velocity, from 0.59 to 0.94 cm/s), whereas cerebral oxygenation showed a reverse pattern with a decrease after the emergence of the infant (85% to 68%, p < 0.001). ConclusionIt is possible to quantify cortical blood flow velocity during general anesthesia using conventional and ultrafast spectral Doppler cerebral ultrasound. Cerebral blood flow velocity and blood pressure decreased, while regional cerebral oxygenation increased during general anesthesia. Ultrafast spectral Doppler ultrasound offers novel insights into perfusion within the cerebral cortex, unattainable through conventional spectral ultrasound. Yet, ultrafast Doppler is curtailed by a lower success rate and a more rigorous learning curve compared to conventional method.

DNA-AgNC Loaded Liposomes for Measuring Cerebral Blood Flow Using Two-Photon Fluorescence Correlation Spectroscopy.

Unraveling the transport of drugs and nanocarriers in cerebrovascular networks is important for pharmacokinetic and hemodynamic studies but is challenging due to the complexity of sensing individual particles within the circulatory system of a live animal. Here, we demonstrate that a DNA-stabilized silver nanocluster (DNA-Ag16NC) that emits in the first near-infrared window upon two-photon excitation in the second NIR window can be used for multiphoton in vivo fluorescence correlation spectroscopy for the measurement of cerebral blood flow rates in live mice with high spatial and temporal resolution. To ensure bright and stable emission during in vivo experiments, we loaded DNA-Ag16NCs into liposomes, which served the dual purposes of concentrating the fluorescent label and protecting it from degradation. DNA-Ag16NC-loaded liposomes enabled the quantification of cerebral blood flow velocities within individual vessels of a living mouse.

Deep optoacoustic localization microangiography of ischemic stroke in mice

Super-resolution optoacoustic imaging of microvascular structures deep in mammalian tissues has so far been impeded by strong absorption from densely-packed red blood cells. Here we devised 5 µm biocompatible dichloromethane-based microdroplets exhibiting several orders of magnitude higher optical absorption than red blood cells at near-infrared wavelengths, thus enabling single-particle detection in vivo. We demonstrate non-invasive three-dimensional microangiography of the mouse brain beyond the acoustic diffraction limit (<20 µm resolution). Blood flow velocity quantification in microvascular networks and light fluence mapping was also accomplished. In mice affected by acute ischemic stroke, the multi-parametric multi-scale observations enabled by super-resolution and spectroscopic optoacoustic imaging revealed significant differences in microvascular density, flow and oxygen saturation in ipsi- and contra-lateral brain hemispheres. Given the sensitivity of optoacoustics to functional, metabolic and molecular events in living tissues, the new approach paves the way for non-invasive microscopic observations with unrivaled resolution, contrast and speed.

Non-invasive flow mapping of parasagittal meningeal lymphatics using 2D interslice flow saturation MRI

The clearance pathways of brain waste products in humans are still under debate in part due to the lack of noninvasive imaging techniques for meningeal lymphatic vessels (mLVs). In this study, we propose a new noninvasive mLVs imaging technique based on an inter-slice blood perfusion MRI called alternate ascending/descending directional navigation (ALADDIN). ALADDIN with inversion recovery (IR) at single inversion time of 2300 ms (single-TI IR-ALADDIN) clearly demonstrated parasagittal mLVs around the human superior sagittal sinus (SSS) with better detectability and specificity than the previously suggested noninvasive imaging techniques. While in many studies it has been difficult to detect mLVs and confirm their signal source noninvasively, the detection of mLVs in this study was confirmed by their posterior to anterior flow direction and their velocities and morphological features, which were consistent with those from the literature. In addition, IR-ALADDIN was compared with contrast-enhanced black blood imaging to confirm the detection of mLVs and its similarity. For the quantification of flow velocity of mLVs, IR-ALADDIN was performed at three inversion times of 2000, 2300, and 2600 ms (three-TI IR-ALADDIN) for both a flow phantom and humans. For this preliminary result, the flow velocity of the dorsal mLVs in humans ranged between 2.2 and 2.7 mm/s. Overall, (i) the single-TI IR-ALADDIN can be used as a novel non-invasive method to visualize mLVs in the whole brain with scan time of ~ 17 min and (ii) the multi-TI IR-ALADDIN can be used as a way to quantify the flow velocity of mLVs with a scan time of ~ 10 min (or shorter) in a limited coverage. Accordingly, the suggested approach can be applied to noninvasively studying meningeal lymphatic flows in general and also understanding the clearance pathways of waste production through mLVs in humans, which warrants further investigation.

Quantifying Flow Velocities in River Deltas via Remotely Sensed Suspended Sediment Concentration

AbstractDeltas are fragile ecosystems threatened by sea‐level rise, sediment starvation, and subsidence. Erosional/depositional processes in these systems mainly depend on the sediment supply and the spatial divergence in bed shear stress induced by hydrodynamic forces. Thus, quantifying the spatiotemporal variability of the flow velocity field is essential for forecasting their fate. To calibrate/validate models, field measurements alone are not sufficient because such data only characterize the hydrodynamic conditions in localized areas. Remote sensing has potential to fill this data gap. We developed a methodology to estimate flow velocities from a map of suspended sediment concentration (SSC) measured by the NASA airborne spectrometer AVIRIS‐NG within the Wax Lake Delta, Louisiana. We extracted streaklines from remotely sensed SSC estimates, and quantified water fluxes and velocities based on the distance between them. Our study demonstrates that the velocity field in deltas can be estimated by leveraging the synoptic information offered by remote sensing.

Dispersion of Heterogeneous Medium in Pulsatile Blood Flow and Absolute Pulsatile Flow Velocity Quantification.

Heterogeneous medium enhanced angiogr- ams are key diagnostic tools in clinical practice; the associated hemodynamic information is crucial for diagnosing cardiovascular diseases. However, the dynamics of such medium in physiological blood flow are poorly understood. Herein, we report a previously unnoticed dispersion pattern, which is a universal phenomenon, of a medium in pulsatile blood flow. We present a physical theory for studying the dispersion of a steadily injected heterogeneous medium into a thin tubular blood vessel in which the blood flow is pulsatile. In a thin tubular blood vessel, we demonstrate that variations of concentration associated with the heterogeneous medium obey a one-dimensional advection diffusion equation, and the diffusion has limited effect whenever a short vascular segment is considered. A distinct feature of the distribution of the medium in the axial distance-time plane is a "dilation-retraction" pattern. The time evolution signals at different axial positions exhibit distinct concentration waveforms. A numerical scheme is proposed for exploiting this information to estimate the pulsatile velocity. Artificial data are adopted to validate the scheme. Real X-ray angiography is also analyzed to support our theory and method. The theory is applicable whenever imaging protocols involve a heterogeneous medium in pulsatile flow.

Motion-resolved real-time 4D flow MRI withlow-rank and subspace modeling.

To develop a new motion-resolved real-time four-dimensional (4D) flow MRI method, which enables the quantification and visualization of blood flow velocities with three-directional flow encodings and volumetric coverage without electrocardiogram (ECG) synchronization and respiration control. An integrated imaging method is presented for real-time 4D flow MRI, which encompasses data acquisition, image reconstruction, and postprocessing. The proposed method features a specialized continuous -space acquisition scheme, which collects two sets of data (i.e., training data and imaging data) in an interleaved manner. By exploiting strong spatiotemporal correlation of 4D flow data, it reconstructs time-series images from highly-undersampled -space measurements with a low-rank and subspace model. Through data-binning-based postprocessing, it constructs a five-dimensional dataset (i.e., x-y-z-cardiac-respiratory), from which respiration-dependent flow information is further analyzed. The proposed method was evaluated in aortic flow imaging experiments with ten healthy subjects and two patients with atrial fibrillation. The proposed method achieves 2.4 mm isotropic spatial resolution and 34.4 ms temporal resolution for measuring the blood flow of the aorta. For the healthy subjects, it provides flow measurements in good agreement with those from the conventional 4D flow MRI technique. For the patients with atrial fibrillation, it is able to resolve beat-by-beat pathological flow variations, which cannot be obtained from the conventional technique. The postprocessing further provides respiration-dependent flow information. The proposed method enables high-resolution motion-resolved real-time 4D flow imaging without ECG gating and respiration control. It is able to resolve beat-by-beat blood flow variations as well as respiration-dependent flow information.

Vascular responses of penetrating vessels during cortical spreading depolarization with ultrasound dynamic ultrafast Doppler imaging.

The dynamic vascular responses during cortical spreading depolarization (CSD) are causally related to pathophysiological consequences in numerous neurovascular conditions, including ischemia, traumatic brain injury, cerebral hemorrhage, and migraine. Monitoring of the hemodynamic responses of cerebral penetrating vessels during CSD is motivated to understand the mechanism of CSD and related neurological disorders. Six SD rats were used, and craniotomy surgery was performed before imaging. CSDs were induced by topical KCl application. Ultrasound dynamic ultrafast Doppler was used to access hemodynamic changes, including cerebral blood volume (CBV) and flow velocity during CSD, and further analyzed those in a single penetrating arteriole or venule. The CSD-induced hemodynamic changes with typical duration and propagation speed were detected by ultrafast Doppler in the cerebral cortex ipsilateral to the induction site. The hemodynamics typically showed triphasic changes, including initial hypoperfusion and prominent hyperperfusion peak, followed by a long-period depression in CBV. Moreover, different hemodynamics between individual penetrating arterioles and venules were proposed by quantification of CBV and flow velocity. The negative correlation between the basal CBV and CSD-induced change was also reported in penetrating vessels. These results indicate specific vascular dynamics of cerebral penetrating vessels and possibly different contributions of penetrating arterioles and venules to the CSD-related pathological vascular consequences. We proposed using ultrasound dynamic ultrafast Doppler imaging to investigate CSD-induced cerebral vascular responses. With this imaging platform, it has the potential to monitor the hemodynamics of cortical penetrating vessels during brain injuries to understand the mechanism of CSD in advance.

Fully-automated deep learning-based flow quantification of 2D CINE phase contrast MRI

ObjectivesTime-resolved, 2D-phase-contrast MRI (2D-CINE-PC-MRI) enables in vivo blood flow analysis. However, accurate vessel contour delineation (VCD) is required to achieve reliable results. We sought to evaluate manual analysis (MA) compared to the performance of a deep learning (DL) application for fully-automated VCD and flow quantification and corrected semi-automated analysis (corSAA).MethodsWe included 97 consecutive patients (age = 52.9 ± 16 years, 41 female) with 2D-CINE-PC-MRI imaging on 1.5T MRI systems at sinotubular junction (STJ), and 28/97 also received 2D-CINE-PC at main pulmonary artery (PA). A cardiovascular radiologist performed MA (reference) and corSAA (built-in tool) in commercial software for all cardiac time frames (median: 20, total contours per analysis: 2358 STJ, 680 PA). DL-analysis automatically performed VCD, followed by net flow (NF) and peak velocity (PV) quantification. Contours were compared using Dice similarity coefficients (DSC). Discrepant cases (> ± 10 mL or > ± 10 cm/s) were reviewed in detail.ResultsDL was successfully applied to 97% (121/125) of the 2D-CINE-PC-MRI series (STJ: 95/97, 98%, PA: 26/28, 93%). Compared to MA, mean DSC were 0.91 ± 0.02 (DL), 0.94 ± 0.02 (corSAA) at STJ, and 0.85 ± 0.08 (DL), 0.93 ± 0.02 (corSAA) at PA; this indicated good to excellent DL-performance. Flow quantification revealed similar NF at STJ (p = 0.48) and PA (p > 0.05) between methods while PV assessment was significantly different (STJ: p < 0.001, PA: p = 0.04). A detailed review showed noisy voxels in MA and corSAA impacted PV results. Overall, DL analysis compared to human assessments was accurate in 113/121 (93.4%) cases.ConclusionsFully-automated DL-analysis of 2D-CINE-PC-MRI provided flow quantification at STJ and PA at expert level in > 93% of cases with results being available instantaneously.Key Points• Deep learning performed flow quantification on clinical 2D-CINE-PC series at the sinotubular junction and pulmonary artery at the expert level in > 93% of cases.• Location detection and contouring of the vessel boundaries were performed fully-automatic with results being available instantaneously compared to human assessments which approximately takes three minutes per location.• The evaluated tool indicates usability in daily practice.

Use of a novel handheld ultrasound device with continuous-wave doppler capability for the assessment of valvular heart disease

Abstract Background/Introduction Echocardiography is the primary non-invasive imaging method for the diagnosis and evaluation of valvular heart disease. Doppler echocardiography provides accurate non-invasive evaluation of valve hemodynamics. Recent technological advancements have enabled the acquisition of echocardiographic images at the point-of-care by using small handheld ultrasound devices (HUDs); their availability and relatively low cost compared to the high-end systems have made these devices attractive to use for rapid medical decision making. However, the inability to quantify flow velocity has been a major limitation for HUDs; the lack of spectral Doppler capability has so far hindered the comprehensive assessment of haemodynamic data and valve function. Purpose To evaluate for the first time the accuracy of a novel HUD with continuous-wave (CW) Doppler capability to measure flow velocity in valvular heart disease. Methods We prospectively included 56 consecutive patients who were referred to the echocardiography laboratory of a tertiary hospital. All patients were scanned with both the Kosmos HUD and the standard echocardiography cart-based system (reference standard) in a randomized order. CW Doppler measurements of maximum velocities (Vmax) were obtained from the apical five-chamber view for the aortic ejection and regurgitation and from the apical four-chamber view for the mitral and tricuspid regurgitation (presence assessed by colour Doppler), maintaining a parallel orientation between the ultrasound beam and the blood flow. All measurements were compared to assess inter-method agreement using linear regression and Bland-Altman analysis. Results The acquisition of CW Doppler signal using the HUD was feasible in 55 out of 56 patients (mean age 66±16 years old, 40% female). Among them, there were 31 cases of (at least mild) aortic stenosis and 23 cases of valvular regurgitation (4 aortic, 6 mitral and 13 tricuspid regurgitations). There was excellent correlation between the HUD and the cart-based system CW Doppler for the aortic Vmax measurements (r=0.99, p&amp;lt;0.001) and for the valvular regurgitation Vmax measurements (r=0.98, p&amp;lt;0.001). The corresponding Bland-Altman plots showed a small underestimation bias of −0.13 m/sec (p&amp;lt;0.001), with limits of agreement ±0.41 m/sec for the aortic Vmax and −0.21 m/sec (p=0.003), with limits of agreement ±0.57 m/sec for the valvular regurgitation Vmax measurements. Conclusion A novel HUD with CW Doppler spectral analysis was able to provide peak jet velocity measurements comparable to the standard cart-based echocardiography systems, in patients with valvular stenosis and regurgitation. Such expanded capabilities of HUDs show clinical potential and may lead to the improvement of the assessment of valvular pathology at the point-of-care. Funding Acknowledgement Type of funding sources: None.

Determination of roughness coefficient in 3D digital representations of rocks

The roughness property of rocks is significant in engineering studies due to their mechanical and hydraulic performance and the possibility of quantifying flow velocity and predicting the performance of wells and rock mass structures. However, the study of roughness in rocks is usually carried out through 2D linear measurements (through mechanical profilometer equipment), obtaining a coefficient that may not represent the entire rock surface. Thus, based on the hypothesis that it is possible to quantify the roughness coefficient in rock plugs reconstructed three-dimensionally by the computer vision technique, this research aims to an alternative method to determine the roughness coefficient in rock plugs. The point cloud generated from the 3D model of the photogrammetry process was used to measure the distance between each point and a calculated fit plane over the entire rock surface. The roughness was quantified using roughness parameters (R_a) calculated in hierarchically organized regions. In this hierarchical division, the greater the quantity of division analyzed, the greater the detail of the roughness. The main results show that obtaining the roughness coefficient over the entire surface of the three-dimensional model has peculiarities that would not be observed in the two-dimensional reading. From the 2D measurements, mean roughness values (R_a) of 0.35,upmu hbox {m} and 0.235,upmu hbox {m} were obtained for samples 1 and 2, respectively. By the same method, the results of the R_a coefficient applied three-dimensionally over the entire rocky surface were at most 0.165,upmu hbox {m} and 0.166,upmu hbox {m}, respectively, showing the difference in values along the surface and the importance of this approach.

Influence of Spatial Resolution and Compressed SENSE Acceleration Factor on Flow Quantification with 4D Flow MRI at 3 Tesla.

Four-dimensional (4D) flow MRI allows quantifying flow in blood vessels–non invasively and in vivo. The clinical use of 4D flow MRI in small vessels, however, is hampered by long examination times and limited spatial resolution. Compressed SENSE (CS-SENSE) is a technique that can accelerate 4D flow dramatically. Here, we investigated the effect of spatial resolution and CS acceleration on flow measurements by using 4D flow MRI in small vessels in vitro at 3 T. We compared the flow in silicon tubes (inner diameters of 2, 3, 4, and 5 mm) measured with 4D flow MRI, accelerated with four CS factors (CS = 2.5, 4.5, 6.5, and 13) and three voxel sizes (0.5, 1, and 1.5 mm3) to 2D flow MRI and a flow sensor. Additionally, the velocity field in an aneurysm model acquired with 4D flow MRI was compared to the one simulated with computational fluid dynamics (CFD). A strong correlation was observed between flow sensor, 2D flow MRI, and 4D flow MRI (rho > 0.94). The use of fewer than seven voxels per vessel diameter (nROI) resulted in an overestimation of flow in more than 5% of flow measured with 2D flow MRI. A negative correlation (rho = −0.81) between flow error and nROI were found for CS = 2.5 and 4.5. No statistically significant impact of CS factor on differences in flow rates was observed. However, a trend of increased flow error with increased CS factor was observed. In an aneurysm model, the peak velocity and stagnation zone were detected by CFD and all 4D flow MRI variants. The velocity difference error in the aneurysm sac did not exceed 11% for CS = 4.5 in comparison to CS = 2.5 for all spatial resolutions. Therefore, CS factors from 2.5–4.5 can appear suitable to improve spatial or temporal resolution for accurate quantification of flow rate and velocity. We encourage reporting the number of voxels per vessel diameter to standardize 4D flow MRI protocols.

Handheld ultrasound device with continuous-wave doppler capability: is it feasible?

Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): Hellenic Society of Cardiology Background/Introduction: Echocardiography is the key tool for the diagnosis and evaluation of valve disease, and has been the primary non-invasive imaging method for valve stenosis assessment. The antegrade systolic velocity across the aortic valve, or aortic jet velocity, is measured using continuous-wave (CW) Doppler ultrasound and is of paramount importance for diagnosis and prognosis of such patients. Recent technological advancements have enabled the acquisition of echocardiographic images at the point of care by using small handheld ultrasound devices (HUDs); their availability and relatively low cost compared to the high-end, fully equipped systems have made these devices attractive to use for rapid medical decision making. However, the inability to quantify flow velocity has been a major drawback for HUDs, since the lack of spectral Doppler capability makes assessment of valvular pathology difficult. Purpose To evaluate the feasibility and accuracy of a novel HUD with CW Doppler capability to measure aortic jet velocity. Methods We prospectively included 43 consecutive patients who were referred to the outpatient specialist valve clinic of a tertiary hospital. All patients were scanned with both the Kosmos HUD and the standard echocardiography cart-based system (reference standard) in order to obtain CW Doppler signal across the aortic valve. The peak aortic jet velocity measurements used for the analysis were acquired from the apical five-chamber view by both techniques and were compared to assess inter-method agreement using linear regression and Bland-Altman analysis. Results The acquisition of CW Doppler signal using the Kosmos HUD was feasible in 42 out of 43 patients (mean age 65 ± 15 years old, 58% male). Among them, there were 12 patients (29%) with peak aortic jet velocity &amp;gt;3 m/s (which is the cut-off to define at least moderate aortic valve stenosis). The peak aortic jet velocity was measured as 2.15 ± 1.16 m/s with the HUD CW Doppler and 2.28 ± 1.16 m/s using the cart-based system CW Doppler. There was excellent correlation between the HUD CW Doppler and the reference standard with a correlation coefficient r = 0.98, 95%CI 0.97-0.99, (p &amp;lt; 0.001). The corresponding Bland-Altman plot showed a small underestimation bias of -0.13 m/s (p &amp;lt; 0.001), with limits of agreement ±0.42 m/s for the peak aortic jet velocity. Of importance, for the subgroup of patients with aortic jet velocity &amp;gt;3 m/s the correlation remained excellent (r = 0.92, p &amp;lt; 0.001). Conclusion A novel HUD with CW Doppler spectral analysis was able to provide aortic jet velocity measurements similar to the standard cart-based echocardiography systems, including patients with high aortic jet velocities. Such expanded capabilities of HUDs show clinical potential and may lead to the improvement of the assessment of valvular pathology at the point of care. Abstract Figure. Correlation plot Abstract Figure. Bland-Altman plot

Intracranial Flow Velocity Quantification Using Non-Contrast Four-Dimensional Flow MRI: A Prospective Comparative Study with Transcranial Doppler Ultrasound.

Four-dimensional (4D) flow magnetic resonance imaging (MRI) allows three-dimensional velocity encoding to measure blood flow in a single scan, regardless of the intracranial artery direction. We compared blood flow velocity quantification by non-contrast 4D flow MRI and by transcranial Doppler ultrasound (TCD), the most widely used modality for measuring velocity. Twenty-two patients underwent both TCD and non-contrast 4D flow MRI. The mean time interval between TCD and non-contrast 4D flow MRI was 0.7 days. Subsegmental velocities were measured bilaterally in the middle cerebral and basilar arteries using TCD and non-contrast 4D flow MRI. Intracranial velocity measurements using TCD and non-contrast 4D flow MRI demonstrated a strong correlation in the bilateral M1, especially at the proximal segment (right r = 0.74, left r = 0.78; all p < 0.001). Mean velocities acquired with 4D flow MRI were approximately 8 to 10% lower than those acquired with TCD according to the location of M1. Intracranial arterial flow measurements estimated using non-contrast 4D flow MRI and TCD showed strong correlation. 4D flow MRI enables simultaneous assessment of vascular morphology and quantitative hemodynamic measurement, providing three-dimensional blood flow visualization. 4D flow MRI is a clinically useful sequence with a promising role in cerebrovascular disease.

Doppler Echocardiography Assessment of Coronary Microvascular Function in Patients With Angina and No Obstructive Coronary Artery Disease.

Echocardiographic evaluation is an essential part of the diagnostic work-up in patients with known or suspected cardiovascular disease. Transthoracic Doppler echocardiography (TTDE) enables straightforward and reliable visualization of flow in the left anterior descending artery. In the absence of obstructive coronary artery disease, low TTDE-derived coronary flow velocity reserve (CFVR) is considered a marker of coronary microvascular dysfunction (CMD). TTDE CFVR is free from ionizing radiation and widely available, utilizing high-frequency transducers, pharmacologic vasodilator stress, and pulsed-wave Doppler quantification of diastolic peak flow velocities. European Society of Cardiology guidelines recommend TTDE CFVR evaluation only following preceding anatomic invasive or non-invasive coronary imaging excluding obstructive CAD. Accordingly, clinical use of TTDE CFVR is limited and CMD frequently goes undiagnosed. An evolving body of evidence underlines that low CFVR is an important and robust predictor of adverse prognosis and continuing symptoms in angina patients both with and without obstructive CAD. The majority of angina patients have no obstructive CAD, particularly among women. This has led to the suggestion that there may be a gender-specific female atherosclerotic phenotype with less epicardial obstruction, and a low CFVR signifying CMD instead. Nevertheless, available evidence indicates low CFVR is an equally important prognostic marker in both men and women. In this review, TTDE CFVR was evaluated regarding indication, practical and technical aspects, and interpretation of results. Association with symptoms and prognosis, comparison with alternative invasive and non-invasive imaging modalities, and possible interventions in angina patients with low CFVR were discussed, and key research questions were proposed.

Quantification of peak blood flow velocity at the cardiac valve and great thoracic vessels by four-dimensional flow and two-dimensional phase-contrast MRI compared with echocardiography: a systematic review and meta-analysis

To objectively examine the agreement and correlation between four-dimensional (4D) flow magnetic resonance imaging (MRI) and traditional two-dimensional (2D) phase-contrast (PC) MRI with the reference standard of Doppler echocardiography for measuring peak blood velocity at the cardiac valve and great arteries, and to assess if 4D flow MRI offers an advantage over the traditional 2D method. The literature was searched systematically for studies that evaluate the degree of correlation and agreement between 4D flow MRI or 2D PC MRI and Doppler retrieved from PubMed, EMBASE, and the Cochrane Library. A meta-analysis was conducted to determine the peak velocity pooled bias with 95% limits of agreement (LoA) and correlation coefficient (r) for 4D flow MRI and 2D PC MRI compared with Doppler. Ten studies that compared 4D flow MRI with Doppler and 12 studies that compared 2D PC MRI with Doppler were included. 4D flow MRI showed an underestimation with bias and 95% LoA of -0.09 (-0.41, 0.24) m/s (p=0.079) while 2D PC MRI showed a poorer agreement with a bias and 95% LoA of -0.25 (-0.53, 0.03), p=0.596. 4D flow MRI and 2D PC MRI showed a strong correlation with R=0.80 (95% CI 0.75, 0.84; p<0.001) and R=0.83 (95% CI 0.79, 0.87; p<0.001), respectively. In this meta-analysis, 4D flow MRI provides improved assessment of peak velocity when compared with traditional 2D PC MRI. 4D flow MRI can be considered an important complement or substitute to Doppler echocardiography for peak velocity assessment.

Quantitative time-of-flight MR angiography for simultaneous luminal and hemodynamic evaluation of the intracranial arteries.

To report a quantitative time-of-flight (qTOF) MRA technique for simultaneous luminal and hemodynamic evaluation of the intracranial arteries. Implemented using a thin overlapping slab 3D stack-of-stars based 3-echo FLASH readout, qTOF was tested in a flow phantom and for imaging the intracranial arteries of 10 human subjects at 3 Tesla. Display of the intracranial arteries with qTOF was compared to resolution-matched and scan time-matched standard Cartesian 3D time-of-flight (TOF) MRA, whereas quantification of mean blood flow velocity with qTOF, done using a computer vision-based inter-echo image analysis procedure, was compared to 3D phase contrast MRA. Arterial-to-background contrast-to-noise ratio was measured, and intraclass correlation coefficient was used to evaluate agreement of flow velocities. For resolution-matched protocols of similar scan time, qTOF portrayed the intracranial arteries with good morphological correlation with standard Cartesian TOF, and both techniques provided superior contrast-to-noise ratio and arterial delineation compared to phase contrast (20.6 ± 3.0 and 37.8 ± 8.7 vs. 11.5 ± 2.2, P < .001, both comparisons). With respect to phase contrast, qTOF showed excellent agreement for measuring mean flow velocity in the flow phantom (intraclass correlation coefficient = 0.981, P < .001) and good agreement in the intracranial arteries (intraclass correlation coefficient = 0.700, P < .001). Stack-of-stars data sampling used with qTOF eliminated oblique in-plane flow misregistration artifacts that were seen with standard Cartesian TOF. qTOF is a new 3D MRA technique for simultaneous luminal and hemodynamic evaluation of the intracranial arteries that provides significantly greater contrast-to-noise ratio efficiency than phase contrast and eliminates misregistration artifacts from oblique in-plane blood flow that occur with standard 3D TOF.

Quantification of Blood Flow Velocity in the Human Conjunctival Microvessels Using Deep Learning-Based Stabilization Algorithm.

The quantification of blood flow velocity in the human conjunctiva is clinically essential for assessing microvascular hemodynamics. Since the conjunctival microvessel is imaged in several seconds, eye motion during image acquisition causes motion artifacts limiting the accuracy of image segmentation performance and measurement of the blood flow velocity. In this paper, we introduce a novel customized optical imaging system for human conjunctiva with deep learning-based segmentation and motion correction. The image segmentation process is performed by the Attention-UNet structure to achieve high-performance segmentation results in conjunctiva images with motion blur. Motion correction processes with two steps—registration and template matching—are used to correct for large displacements and fine movements. The image displacement values decrease to 4–7 μm during registration (first step) and less than 1 μm during template matching (second step). With the corrected images, the blood flow velocity is calculated for selected vessels considering temporal signal variances and vessel lengths. These methods for resolving motion artifacts contribute insights into studies quantifying the hemodynamics of the conjunctiva, as well as other tissues.

Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

Changes in blood flow velocity play a crucial role during pathogenesis and progression of cardiovascular diseases. Imaging techniques capable of assessing flow velocities are clinically applied but are often not accurate, quantitative, and reliable enough to assess fine changes indicating the early onset of diseases and their conversion into a symptomatic stage. Magnetic particle imaging (MPI) promises to overcome these limitations. Existing MPI-based techniques perform velocity estimation on the reconstructed images, which restricts the measurable velocity range. Therefore, we developed a novel velocity quantification method by adapting the Doppler principle to MPI. Our method exploits the velocity-dependent frequency shift caused by a tracer motion-induced modulation of the emitted signal. The fundamental theory of our method is deduced and validated by simulations and measurements of moving phantoms. Overall, our method enables robust velocity quantification within milliseconds, with high accuracy, no radiation risk, no depth-dependency, and extended range compared to existing MPI-based velocity quantification techniques, highlighting the potential of our method as future medical application.