Ultrasonic Flow Imaging Research Articles

A Method for High-Frequency Mechanical Scanning Ultrasonic Flow Imaging with Motion Compensation.

Mechanical scanning with a single transducer is an alternative method for high-frequency ultrasound imaging, which is simple in structure, convenient to implement, and low in cost. However, traditional mechanical scanning ultrasonic imaging introduces additional Doppler shift due to the movement of the transducer, which brings a challenge for blood velocity measurement. An improved mechanical scanning system for high-frequency ultrasonic color Doppler flow imaging is developed in this paper. The mechanical scanning system has a scanning stroke range of 15 mm, a maximum scanning speed of 168 mm/s, and an imaging depth of 20 mm. Since the mechanical scanning of the system is not in uniform motion, motion compensation was applied to achieve high-precision imaging both in B-mode and Doppler mode. The experiment results show that the system imaging resolution can reach about 140 μm in B-mode imaging, the relative velocity error is less than 5% in color Doppler flow imaging at different flow rates, and the CNR of power Doppler flow imaging of this system is greater than 15 dB. The proposed mechanical scanning imaging system can achieve high-resolution structure imaging and color flow imaging, which can provide more diagnostic information for the practical diagnosis and broaden the application range of mechanical scanning ultrasound imaging.

Diagnostic Value of Multi-Mode Ultrasonic Flow Imaging Examination in Solid Renal Tumors of Different Sizes.

Purposes: To explore the value of Microflow Imaging (MFI) in renal solid tumors. Methods: A total of 195 patients with 199 lesions pathologically confirmed masses were retrospectively analyzed. The 199 masses were divided into the tumor ≤ 4 cm group (n = 104) and tumor > 4 cm group (n = 95). The diagnostic efficacy of Color Doppler Flow Imaging (CDFI), Power Doppler Imaging (PDI) and MFI in renal tumors sizes were compared by determining the Adler grade, vascular morphology and peripheral blood flow. Results: Among 199 tumors, 161 lesions were malignant and 38 lesions were benign. MFI in malignant tumor ≤ 4 cm demonstrated statistically significant differences in Adler grade and vascular morphology as compared to CDFI and PDI (p < 0.05). In malignant tumor > 4 cm group, MFI showed significant difference in vascular morphology compared with CDFI (p < 0.05). MFI showed a significant difference in the peripheral annular blood flow of malignant tumors when compared to CDFI and PDI (p < 0.05). In addition, the malignant tumors of the two sizes by MFI in peripheral annular blood flow detection showed significant difference (p < 0.05). The area under the curve of ROC by MFI in the tumor ≤ 4 cm was 0.771, which was higher than CDFI and PDI (p < 0.05), but no obvious difference among the tumor > 4 cm (p > 0.05). Conclusion: MFI provides a new method for the differential diagnosis of small renal carcinoma. Based on the convenience and non-radiation of MFI, we can choose MFI as an imaging diagnostic tool for patients who need long-term active surveillance (AS) follow-up.

The role of multimodal ultrasonic flow imaging in Thyroid Imaging Reporting and Data System (TI-RADS) 4 nodules.

Color Doppler imaging (CDFI), contrast-enhanced ultrasound (CEUS), and superb micro-vascular imaging (SMI) are used to observe blood flow characteristics in Thyroid Imaging Reporting and Data System (TI-RADS) 4 nodules. The ability of these techniques to distinguish benign from malignant nodules was investigated. A total of 75 TI-RADS 4 nodules were examined using CDFI, SMI, and CEUS. The blood flow characteristics shown by the three methods were added to the current TI-RADS classification to establish a new TI-RADS classification. The value of the three methods and the diagnostic accuracy of the new and old TI-RADS classification were compared. SMI better captured type II flow in benign nodules and type III flow in malignant nodules relative to CDFI. Malignant nodules detected with CEUS manifested mainly with hypo-enhancement, whereas benign nodules showed iso- and hyper-enhancement. The areas under the receiver operating characteristic (ROC) curves (AUC) obtained through the aforementioned flow distribution models were 0.690 (CDFI), 0.840 (SMI), 0.910 (CEUS), and 0.903 (CEUS and SMI combined mode), respectively. The diagnostic value of CEUS was the highest. Joint inspection using SMI with CEUS showed certain advantages in sensitivity, although the overall accuracy was equal to that of CEUS alone. Except for CDFI, the AUC of the new TI-RADS classification was significantly higher than that of the old one. Perforating vessels and low enhancement were independent predictors of thyroid carcinoma. Both SMI and CEUS visualized lower-velocity blood flow within TI-RADS 4 nodules. The new TI-RADS classification described here could improve diagnostic accuracy.

非浸潤性乳管癌(DCIS)の鑑別における超音波フローイメージング分類の役割

非浸潤性乳管癌(DCIS)の鑑別における超音波フローイメージング分類の役割

Placement of pediatric PICC with ultrasonic blood flow imaging technology

Objective To discuss the application of ultrasonic blood flow imaging technology in pediatric Peripherally Inserted Central Catheter (PICC)placement.Methods 90 patients divided into two groups, the control group and the study group.Control group received PICC with routine method while study group received PICC with ultrasound-guided placement.The indicators including successful rate of puncture, operation time and the rate of local issue damage were compared between two groups.Results Study group had higher successful rate of puncture, shorter operation time and lower rate of local issue damage.Conclusions The method of pediatric PICC placement with ultrasonic blood flow imaging technology is safe, reliable, effective and feasible. Key words: PICC; Ultrasound Technology; Childran; Nursing

Assessment of Numerical Simulation Strategies for Ultrasonic Color Blood Flow Imaging, Based on a Computer and Experimental Model of the Carotid Artery

Ultrasonic Doppler techniques are well established and allow qualitative and quantitative flow analysis. However, due to inherent limitations of the imaging process, the actual flow dynamics and the ultrasound (US) image do not always correspond. To investigate the performance of ultrasonic flow imaging methods, computational fluid dynamics (CFD) can play an important role. CFD simulations can be directly processed to mimic ultrasonic images or can be further coupled to ultrasound simulation models. We studied both approaches in the clinically relevant setting of a carotid artery using color flow images (CFI). The first order approach consisted of producing ultrasound images by color-coding CFD-simulations. For the second order approach, CFI was simulated using an ultrasound simulator, which models blood as a collection of point scatterers moving according to the CFD velocity fields. Color flow images were also measured in an experimental setup of the same carotid geometry for comparison. Results showed that during dynamic stages of the cardiac cycle, realistic ultrasound data can only be achieved when incorporating both the dynamic image formation and the measurement statistics into the simulations.

Vector-velocity estimation in swept-scan using a K-space approach

The swept-scan technique (i.e., continuously moving a single-crystal transducer during pulse-echo data acquisition) is used in high-frequency, ultrasonic flow imaging. Relative to the conventional step-scan technique, swept scanning improves the rate of data acquisition and enables near-real-time, high-frequency color flow mapping. However, the continuous transducer movement may have non-negligible effects on accuracy of velocity estimation. This paper introduces a spatial frequency domain (i.e., k-space) approach that quantifies the effects of both lateral and axial motions in a swept scan. It is shown that the k-space representation is equivalent to a Doppler-radio frequency (RF) frequency domain representation, and that transducer movement in the swept-scan technique results in a change in Doppler bandwidth. In addition, a vector velocity estimator is developed based on the proposed k-space approach. Both simulations and flow-phantom experiments were performed to evaluate the performance of the proposed vector velocity estimator. A 45-MHz transducer was scanned at 20 mm/s. The Doppler angle ranged from 29 degrees to 90 degrees, and the flow velocities ranged from 15 to 30 mm/s. The results show that the proposed k-space vector velocity estimator exhibited a mean error of 2.6 degrees for flow-direction estimation, with the standard deviation ranging from 2.2 degrees to 8.2 degrees. In comparison, for the conventional spectral-broadening-based vector velocity estimator ignoring the swept-scan effect, the mean error became 15 degrees and the standard deviations were from 2.7 degrees to 6.6 degrees.

Implementation issues in ultrasonic flow imaging

This article addresses several implementation issues in ultrasonic flow imaging. We discuss frequency-dependent scattering and attenuation, use of interpolation for computation intensive methods and implications of the use of chirps to increase bandwidth. We also discuss wall filtering issues; our observations show that the butterfly search estimator may be capable of detecting flow in the vicinity of strong stationary scatterers (clutter) without additional processing such as wall-filtering. Illustrative examples are given for simulated and experimental data. (E-mail: parker@ece.rochester.edu)