Pressure Difference Estimation in Non-stenotic Carotid Bifurcation Phantoms Using Vector Flow Imaging.

Local pressure differences estimated using vector flow imaging (VFI) and direct catheterization in seven carotid bifurcation phantoms were compared with simulated pressure fields. VFI correlated strongly with simulated peak pressure differences (r = 0.99, p < 0.00001), with an average overestimation of 12.3 Pa (28.6%). The range between the lowest and highest pressure difference of VFI underestimated simulations by 4.6 Pa (8.06%; r = 0.99, p < 0.0001). The catheter method exhibited no correlation (r = -0.09, p = 0.85). Ten repeated measurements on one phantom revealed a small standard deviation (SD) for VFI (SD = 8.4%, mean estimated SD = 11.5%), but not for the catheter method (SD = 785.6%). An in vivo peak systolic pressure difference of 97.9 Pa (estimated SD = 30%) was measured using VFI in one healthy individual. This study indicates that VFI pressure difference estimation is feasible in phantoms and in vivo and realistic estimates of the SD can be attained from the data.

Transthoracic Vector Flow Imaging in Pediatric Patients with Valvular Stenosis - A Proof of Concept Study.

Purpose Continuous wave Doppler ultrasound is routinely used to detect cardiac valve stenoses. Vector flow imaging (VFI) is an angle-independent real-time ultrasound method that can quantify flow complexity. We aimed to evaluate if quantification of flow complexity could reliably assess valvular stenosis in pediatric patients. Materials and Methods Nine pediatric patients with echocardiographically confirmed valvular stenosis were included in the study. VFI and Doppler measurements were compared with transvalvular peak-to-peak pressure differences derived from invasive endovascular catheterization. Results Vector concentration correlated with the catheter measurements before intervention after exclusion of one outlier (r=-0.83, p=0.01), whereas the Doppler method did not (r=0.49, p=0.22). The change in vector concentration after intervention correlated strongly with the change in the measured catheter pressure difference (r=-0.86, p=0.003), while Doppler showed a tendency for a moderate correlation (r=0.63, p=0.07). Conclusion Transthoracic flow complexity quantification calculated from VFI data is feasible and may be useful for assessing valvular stenosis severity in pediatric patients.

Common Carotid Artery Volume Flow: A Comparison Study between Ultrasound Vector Flow Imaging and Phase Contrast Magnetic Resonance Imaging.

Volume flow estimation in the common carotid artery (CCA) can assess the absolute hemodynamic effect of a carotid stenosis. The aim of this study was to compare a commercial vector flow imaging (VFI) setup against the reference method magnetic resonance phase contrast angiography (MRA) for volume flow estimation in the CCA. Ten healthy volunteers were scanned with VFI and MRA over the CCA. VFI had an improved precision of 19.2% compared to MRA of 31.9% (p = 0.061). VFI estimated significantly lower volume flow than MRA (mean difference: 63.2 mL/min, p = 0.017), whilst the correlation between VFI and MRA was strong (R2 = 0.81, p < 0.0001). A Bland-Altman plot indicated a systematic bias. After bias correction, the percentage error was reduced from 41.0% to 25.2%. This study indicated that a VFI setup for volume flow estimation is precise and strongly correlated to MRA volume flow estimation, and after correcting for the systematic bias, VFI and MRA become interchangeable.

Carotid Stenosis Assessment with Vector Concentration before and after Stenting.

Digital subtraction angiography (DSA) is considered the reference method for the assessment of carotid artery stenosis; however, the procedure is invasive and accompanied by ionizing radiation. Velocity estimation with duplex ultrasound (DUS) is widely used for carotid artery stenosis assessment since no radiation or intravenous contrast is required; however, the method is angle-dependent. Vector concentration (VC) is a parameter for flow complexity assessment derived from the angle independent ultrasound method vector flow imaging (VFI), and VC has shown to correlate strongly with stenosis degree. The aim of this study was to compare VC estimates and DUS estimated peak-systolic (PSV) and end-diastolic velocities (EDV) for carotid artery stenosis patients, with the stenosis degree obtained with DSA. Eleven patients with symptomatic carotid artery stenosis were examined with DUS, VFI, and DSA before and after stent treatment. Compared to DSA, VC showed a strong correlation (r = -0.79, p < 0.001), while PSV (r = 0.68, p = 0.002) and EDV (r = 0.51, p = 0.048) obtained with DUS showed a moderate correlation. VFI using VC calculations may be a useful ultrasound method for carotid artery stenosis and stent patency assessment.

Flow Complexity Estimation in Dysfunctional Arteriovenous Dialysis Fistulas using Vector Flow Imaging.

Non-invasive assessment is preferred for monitoring arteriovenous dialysis fistulas (AVFs). Vector concentration assesses flow complexity, which may correlate with stenosis severity. We determined whether vector concentration could assess stenosis severity in dysfunctional AVFs. Vector concentration was estimated in four stenotic phantoms at different pulse repetition frequencies. Spectral Doppler peak velocity and vector concentration were measured in 12 patients with dysfunctional AVFs. Additionally, 5 patients underwent digital subtraction angiography (DSA). In phantoms, vector concentration exhibited an inverse relationship with stenosis severity and was less affected by aliasing in severe stenoses. In nine stenoses of 5 patients undergoing DSA, vector concentration correlated strongly with stenosis severity (first stenosis: r = -0.73, p = 0.04; other stenoses; r = -0.69, p = 0.02) and mid-stenotic diameter (first stenosis: r = 0.87, p = 0.006; other stenoses: r = 0.70, p = 0.02) as opposed to peak velocities (p > 0.05). Vector concentration is less affected by aliasing in severe stenoses and correlates with DSA in patients with dysfunctional AVF.

Automatic Detection of B-Lines in In Vivo Lung Ultrasound.

This paper proposes an automatic method for accurate detection and visualization of B-lines in ultrasound lung scans, which provides a quantitative measure for the number of B-lines present. All the scans used in this study were acquired using a BK3000 ultrasound scanner (BK Ultrasound, Herlev, Denmark) driving a 5.5-MHz linear transducer (BK Ultrasound). Four healthy subjects and four patients, after major surgery with pulmonary edema, were scanned at four locations on each lung for B-line examination. Eight sequences of 50 frames were acquired for each subject yielding 64 sequences in total. The proposed algorithm was applied to all 3200 in-vivo lung ultrasound images. The results showed that the average number of B-lines was 0.28±0.06 (Mean±Std) in scans belonging to the patients compared to 0.03 ± 0.06 (Mean ± Std) in the healthy subjects. Also, the Mann-Whitney test showed a significant difference between the two groups with the p -value of 0.015, and indicating that the proposed algorithm was able to differentiate between the healthy volunteers and the patients. In conclusion, the method can be used to automatically and to quantitatively characterize the distribution of B-lines for diagnosing pulmonary edema.

Portable Vector Flow Imaging Compared With Spectral Doppler Ultrasonography.

In this study, a vector flow imaging (VFI) method developed for a portable ultrasound scanner was used for estimating peak velocity values and variation in beam-to-flow angle over the cardiac cycle in vivo on healthy volunteers. Peak-systolic velocity (PSV), end-diastolic velocity (EDV), and resistive index (RI) measured with VFI were compared to spectral Doppler ultrasonography (SDU). Seventeen healthy volunteers were scanned on the left and right common carotid arteries (CCAs). The standard deviation (SD) of VFI measurements averaged over the cardiac cycle was 7.3% for the magnitude and 3.84° for the angle. Bland-Altman plots showed a positive bias for the PSV measured with SDU (mean difference: 0.31 ms -1 ), and Pearson correlation analysis showed a highly significant correlation ( r = 0.6 ; ). A slightly positive bias was found for EDV and RI measured with SDU (mean difference: 0.08 ms -1 and -0.01 ms -1 , respectively). However, the correlation was low and not significant. The beam-to-flow angle was estimated over the systolic part of the cardiac cycle, and its variations were for all measurements larger than the precision of the angle estimation. The range spanned deviations from -25.2° (-6.0 SD) to 23.7° (4.2 SD) with an average deviation from -15.2° to 9.7°. This can significantly affect PSV values measured by SDU as the beam-to-flow angle is not constant and not aligned with the vessel surface. The study demonstrates that the proposed VFI method can be used in vivo for the measurement of PSV in the CCAs, and that angle variations across the cardiac cycle can lead to significant errors in SDU velocity estimates.

Evaluation of Peak Reflux Velocities with Vector Flow Imaging and Spectral Doppler Ultrasound in Varicose Veins.

Purpose Spectral Doppler ultrasound (SDUS) is used for quantifying reflux in lower extremity varicose veins. The technique is angle-dependent opposed to the new angle-independent Vector Flow Imaging (VFI) method. The aim of this study was to compare peak reflux velocities obtained with VFI and SDUS in patients with chronic venous disease, i. e., pathological retrograde blood flow caused by incompetent venous valves. Materials and Methods 64 patients with chronic venous disease were scanned with VFI and SDUS in the great or the small saphenous vein, and reflux velocities were compared to three assessment tools for chronic venous disease. A flow rig was used to assess the accuracy and precision of the two methods. Results The mean peak reflux velocities differed significantly (VFI: 47.4 cm/s vs. SDUS: 62.0 cm/s, p<0.001). No difference in absolute precision (p=0.18) nor relative precision (p=0.79) was found. No correlation to disease severity, according to assessment tools, was found for peak reflux velocities obtained with either method. In vitro, VFI was more accurate but equally precise when compared to SDUS. Conclusion Both VFI and SDUS detected the pathologic retrograde flow in varicose veins but measured different reflux velocities with equal precision. VFI may play a role in evaluating venous disease in the future.

Respiratory variability of peak velocities in the common femoral vein estimated with vector flow imaging and Doppler ultrasound.

Respiratory variability of peak velocities (RVPV) in the common femoral vein measured with ultrasound can reveal venous outflow obstruction. Pulse wave (PW) Doppler is the gold standard for venous velocity estimation of the lower extremities. PW Doppler measurements are angle dependent, whereas vector flow imaging (VFI) can yield angle-independent measures. The hypothesis of the present study was that VFI can provide RVPV estimations without the angle dependency of PW Doppler for an improved venous disease assessment. Sixty-seven patients with symptomatic chronic venous disease were included in the study. On average, VFI measured a lower RVPV than PW Doppler (VFI: 14.11 cm/s; PW: 17.32 cm/s, p = 0.002) with a non-significant improved precision compared with PW Doppler (VFI: 21.09%; PW: 26.49%, p = 0.08). In a flow phantom, VFI had improved accuracy (p < 0.01) and equal precision compared with PW Doppler. The study indicated that VFI can characterize the hemodynamic fluctuations in the common femoral vein.

Real-Time 2-D Phased Array Vector Flow Imaging.

Echocardiography examination of the blood flow is currently either restricted to 1-D techniques in real-time or experimental offline 2-D methods. This paper presents an implementation of transverse oscillation for real-time 2-D vector flow imaging (VFI) on a commercial BK Ultrasound scanner. A large field-of-view (FOV) sequence for studying flow dynamics at 11 frames per second (fps) and a sequence for studying peak systolic velocities (PSVs) with a narrow FOV at 36 fps were validated. The VFI sequences were validated in a flow rig with continuous laminar parabolic flow and in a pulsating flow pump system before being tested in vivo, where measurements were obtained on two healthy volunteers. Mean PSV from 11 cycles was 155 cms-1 with a precision of ±9.0% for the pulsating flow pump. In vivo, PSV estimated in the ascending aorta was 135 cms-1 ± 16.9% for eight cardiac cycles. Furthermore, in vivo flow dynamics of the left ventricle and in the ascending aorta were visualized. In conclusion, angle independent 2-D VFI on a phased array has been implemented in real time, and it is capable of providing quantitative and qualitative flow evaluations of both the complex and fully transverse flow.

A Comparison Study of Vector Velocity, Spectral Doppler and Magnetic Resonance of Blood Flow in the Common Carotid Artery.

Magnetic resonance phase contrast angiography (MRA) is the gold standard for blood flow evaluation. Spectral Doppler ultrasound (SDU) is the first clinical choice, although the method is angle dependent. Vector flow imaging (VFI) is an angle-independent ultrasound method. The aim of the study was to compare VFI- and SDU-estimated peak systolic velocities (PSV) of the common carotid artery (CCA) with PSV obtained by MRA. Furthermore, intra- and inter-observer agreement was determined. MRA estimates were significantly different from SDU estimates (left CCA: p < 0.001, right CCA: p < 0.001), but not from VFI estimates (left CCA: p = 0.28, right CCA: p = 0.18). VFI measured lower PSV in both CCAs compared with SDU (p < 0.001) with improved precision (VFI: left: 24%, right: 18%; SDU: left 38%, right: 23%). Intra- and inter-observer agreement was almost perfect for VFI and SDU (inter-observer correlation coefficient: VFI 0.88, SDU 0.91; intra-observer correlation coefficient: VFI 0.96, SDU 0.97). VFI is more accurate than SDU in evaluating PSV compared with MRA.

Accuracy and Precision of a Plane Wave Vector Flow Imaging Method in the Healthy Carotid Artery.

The objective of the study described here was to investigate the accuracy and precision of a plane wave 2-D vector flow imaging (VFI) method in laminar and complex blood flow conditions in the healthy carotid artery. The approach was to study (i) the accuracy for complex flow by comparing the velocity field from a computational fluid dynamics (CFD) simulation to VFI estimates obtained from the scan of an anthropomorphic flow phantom and from an in vivo scan; (ii) the accuracy for laminar unidirectional flow in vivo by comparing peak systolic velocities from VFI with magnetic resonance angiography (MRA); (iii) the precision of VFI estimation in vivo at several evaluation points in the vessels. The carotid artery at the bifurcation was scanned using both fast plane wave ultrasound and MRA in 10 healthy volunteers. The MRA geometry acquired from one of the volunteers was used to fabricate an anthropomorphic flow phantom, which was also scanned using the fast plane wave sequence. The same geometry was used in a CFD simulation to calculate the velocity field. Results indicated that similar flow patterns and vortices were estimated with CFD and VFI in the phantom for the carotid bifurcation. The root-mean-square difference between CFD and VFI was within 0.12 m/s for velocity estimates in the common carotid artery and the internal branch. The root-mean-square difference was 0.17 m/s in the external branch. For the 10 volunteers, the mean difference between VFI and MRA was -0.17 m/s for peak systolic velocities of laminar flow in vivo. The precision in vivo was calculated as the mean standard deviation (SD) of estimates aligned to the heart cycle and was highest in the center of the common carotid artery (SD = 3.6% for velocity magnitudes and 4.5° for angles) and lowest in the external branch and for vortices (SD = 10.2% for velocity magnitudes and 39° for angles). The results indicate that plane wave VFI measures flow precisely and that estimates are in good agreement with a CFD simulation and MRA.

Vector Flow Imaging Compared with Pulse Wave Doppler for Estimation of Peak Velocity in the Portal Vein.

The study described here investigated whether angle-independent vector flow imaging (VFI) technique estimates peak velocities in the portal vein comparably to pulsed wave Doppler (PWD). Furthermore, intra- and inter-observer agreement was assessed in a substudy. VFI and PWD peak velocities were estimated with from intercostal and subcostal views for 32 healthy volunteers, and precision analyses were conducted. Blinded to estimates, three physicians rescanned 10 volunteers for intra- and inter-observer agreement analyses. The precision of VFI and PWD was 18% and 28% from an intercostal view and 23% and 77% from a subcostal view, respectively. Bias between VFI and PWD was 0.57 cm/s (p = 0.38) with an intercostal view and 9.89 cm/s (p <0.001) with a subcostal view. Intra- and inter-observer agreement was highest for VFI (inter-observer intra-class correlation coefficient: VFI 0.80, PWD 0.3; intra-observer intra-class correlation coefficient: VFI 0.90, PWD 0.69). Regardless of scan view, VFI was more precise than PWD.

Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysis.

This paper presents an automated algorithm for robustly detecting and segmenting free-lying cell nuclei in bright-field microscope images of Pap smears. This is an essential initial step in the development of an automated screening system for cervical cancer based on malignancy associated change (MAC) analysis. The proposed segmentation algorithm makes use of gray-scale annular closings to identify free-lying nuclei-like objects together with marker-based watershed segmentation to accurately delineate the nuclear boundaries. The algorithm also employs artifact rejection based on size, shape, and granularity to ensure only the nuclei of intermediate squamous epithelial cells are retained. An evaluation of the performance of the algorithm relative to expert manual segmentation of 33 fields-of-view from 11 Pap smear slides is also presented. The results show that the sensitivity and specificity of nucleus detection is 94.71% and 85.30% respectively, and that the accuracy of segmentation, measured using the Dice coefficient, of the detected nuclei is 97.30±1.3%.