Ramin Moshavegh

Novel automatic detection of pleura and B-lines (comet-tail artifacts) on in vivo lung ultrasound scans

This paper presents a novel automatic method for detection of B-lines (comet-tail artifacts) in lung ultrasound scans. B-lines are the most commonly used artifacts for analyzing the pulmonary edema. They appear as laser-like vertical beams, which arise from the pleural line and spread down without fading to the edge of the screen. An increase in their number is associated with presence of edema. All the scans used in this study were acquired using a BK3000 ultrasound scanner (BK Ultrasound, Denmark) driving a 192-element 5:5 MHz wide linear transducer (10L2W, BK Ultrasound). The dynamic received focus technique was employed to generate the sequences. Six subjects, among those three patients after major surgery and three normal subjects, were scanned once and Six ultrasound sequences each containing 50 frames were acquired. The proposed algorithm was applied to all 300 in-vivo lung ultrasound images. The pleural line is first segmented on each image and then the B-line artifacts spreading down from the pleural line are detected and overlayed on the image. The resulting 300 images showed that the mean lateral distance between B-lines detected on images acquired from patients decreased by 20% in compare with that of normal subjects. Therefore, the method can be used as the basis of a method of automatically and qualitatively characterizing the distribution of B-lines.

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.

Hybrid segmentation of vessels and automated flow measures in in-vivo ultrasound imaging

Vector Flow Imaging (VFI) has received an increasing attention in the scientific field of ultrasound, as it enables angle independent visualization of blood flow. VFI can be used in volume flow estimation, but a vessel segmentation is needed to make it fully automatic. A novel vessel segmentation procedure is crucial for wall-to-wall visualization, automation of adjustments, and quantification of flow in state-of-the-art ultrasound scanners. We propose and discuss a method for accurate vessel segmentation that fuses VFI data and B-mode for robustly detecting and delineating vessels. The proposed method implements automated VFI flow measures such as peak systolic velocity (PSV) and volume flow. An evaluation of the performance of the segmentation algorithm relative to expert manual segmentation of 60 frames randomly chosen from 6 ultrasound sequences (10 frame randomly chosen from each sequence) is also presented. Dice coefficient denoting the similarity between segmentations is used for the evaluation. The coefficient ranges between 0 and 1, where 1 indicates perfect agreement and 0 indicates no agreement. The Dice coefficient was 0.91 indicating to a very agreement between automated and manual expert segmentations. The flowrig results also demonstrated that the PSVs measured from VFI had a mean relative error of 14.5% in comparison with the actual PSVs. The error for the PSVs measured from spectral Doppler was 29.5%, indicating that VFI is 15% more precise than spectral Doppler in PSV measurement.

Advanced automated gain adjustments for in-vivo ultrasound imaging

Automatic gain adjustments are necessary on the state-of-the-art ultrasound scanners to obtain optimal scan quality, while reducing the unnecessary user interactions with the scanner. However, when large anechoic regions exist in the scan plane, the sudden and drastic variation of attenuations in the scanned media complicates the gain compensation. This paper presents an advanced and automated gain adjustment method that precisely compensate for the gains on scans and dynamically adapts to the drastic attenuation variations between different media. The proposed algorithm makes use of several ultrasonic physical estimates such as scattering strength, focus gain, acoustic attenuation, and noise level to gain a more quantitative understanding of the scanned media and to provide an intuitive adjustment of gains on the scan. The proposed algorithm was applied to a set of 45 in-vivo movie sequences each containing 50 frames. The scans are acquired using a recently commercialized BK3000 ultrasound scanner (BK Ultrasound, Denmark). Matching pairs of in-vivo sequences, unprocessed and processed with the proposed method were visualized side by side and evaluated by 4 radiologists for image quality. Wilcoxon signed-rank test was then applied to the ratings provided by radiologists. The average VAS score was highly positive 12.16 (p-value: 2.09×10-23) favoring the gain-adjusted scans with the proposed algorithm.

Automated hierarchical time gain compensation for in-vivo ultrasound imaging

Time gain compensation (TGC) is essential to ensure the optimal image quality of the clinical ultrasound scans. When large fluid collections are present within the scan plane, the attenuation distribution is changed drastically and TGC compensation becomes challenging. This paper presents an automated hierarchical TGC (AHTGC) algorithm that accurately adapts to the large attenuation variation between different types of tissues and structures. The algorithm relies on estimates of tissue attenuation, scattering strength, and noise level to gain a more quantitative understanding of the underlying tissue and the ultrasound signal strength. The proposed algorithm was applied to a set of 44 in vivo abdominal movie sequences each containing 15 frames. Matching pairs of in vivo sequences, unprocessed and processed with the proposed AHTGC were visualized side by side and evaluated by two radiologists in terms of image quality. Wilcoxon signed-rank test was used to evaluate whether radiologists preferred the processed sequences or the unprocessed data. The results indicate that the average visual analogue scale (VAS) is positive ( p-value: 2.34 × 10-13) and estimated to be 1.01 (95% CI: 0.85; 1.16) favoring the processed data with the proposed AHTGC algorithm.

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.

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.

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.

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.

Optimization of synthetic aperture image quality

Synthetic Aperture (SA) imaging produces high-quality images and velocity estimates of both slow and fast flow at high frame rates. However, grating lobe artifacts can appear both in transmission and reception. These affect the image quality and the frame rate. Therefore optimization of parameters effecting the image quality of SA is of great importance, and this paper proposes an advanced procedure for optimizing the parameters essential for acquiring an optimal image quality, while generating high resolution SA images. Optimization of the image quality is mainly performed based on measures such as F-number, number of emissions and the aperture size. They are considered to be the most contributing acquisition factors in the quality of the high resolution images in SA. Therefore, the performance of image quality is quantified in terms of full-width at half maximum (FWHM) and the cystic resolution (CTR). The results of the study showed that SA imaging with only 32 emissions and maximum sweep angle of 22 degrees yields a very good image quality compared with using 256 emissions and the full aperture size. Therefore the number of emissions and the maximum sweep angle in the SA can be optimized to reach a reasonably good performance, and to increase the frame rate by lowering the required number of emissions. All the measurements are performed using the experimental SARUS scanner connected to a λ/2-pitch transducer. A wire phantom and a tissue mimicking phantom containing anechoic cysts are scanned using the optimized parameters for the transducer. Measurements coincide with simulations.