Spatiotemporal analysis of contrast-enhanced ultrasound for differentiating between malignant and benign breast lesions.

OBJECTIVES: The aim of this study was to apply spatiotemporal analysis of contrast-enhanced ultrasound (CEUS) loops to quantify the enhancement heterogeneity for improving the differentiation between benign and malignant breast lesions. MATERIALS AND METHODS: This retrospective study included 120 women (age range, 18-82 years; mean, 52 years) scheduled for ultrasound-guided biopsy. With the aid of brightness-mode images, the border of each breast lesion was delineated in the CEUS images. Based on visual evaluation and quantitative metrics, the breast lesions were categorized into four grades of different levels of contrast enhancement. Grade-1 (hyper-enhanced) and grade-2 (partly-enhanced) breast lesions were included in the analysis. Four parameters reflecting enhancement heterogeneity were estimated by spatiotemporal analysis of neighboring time-intensity curves (TICs). By setting the threshold on mean parameter, the diagnostic performance of the four parameters for differentiating benign and malignant lesions was evaluated. RESULTS: Sixty-four of the 120 patients were categorized as grade 1 or 2 and used for estimating the four parameters. At the pixel level, mutual information and conditional entropy present significantly different values between the benign and malignant lesions (p < 0.001 in patients of grade 1, p = 0.002 in patients of grade 1 or 2). For the classification of breast lesions, mutual information produces the best diagnostic performance (AUC = 0.893 in patients of grade 1, AUC = 0.848 in patients of grade 1 or 2). CONCLUSIONS: The proposed spatiotemporal analysis for assessing the enhancement heterogeneity shows promising results to aid in the diagnosis of breast cancer by CEUS. CLINICAL RELEVANCE STATEMENT: The proposed spatiotemporal method can be developed as a standardized software to automatically quantify the enhancement heterogeneity of breast cancer on CEUS, possibly leading to the improved diagnostic accuracy of differentiation between benign and malignant lesions. KEY POINTS: • Advanced spatiotemporal analysis of ultrasound contrast-enhanced loops for aiding the differentiation of malignant or benign breast lesions. • Four parameters reflecting the enhancement heterogeneity were estimated in the hyper- and partly-enhanced breast lesions by analyzing the neighboring pixel-level time-intensity curves. • For the classification of hyper-enhanced breast lesions, mutual information produces the best diagnostic performance (AUC = 0.893).

Automated 3-D Ultrasound Elastography of the Breast: An In Vivo Validation Study.

OBJECTIVE: Studies have indicated that adding 2-D quasi-static elastography to B-mode ultrasound imaging improved the specificity for malignant lesion detection, as malignant lesions are often stiffer (increased strain ratio) compared with benign lesions. This method is limited by its user dependency and so unsuitable for breast screening. To overcome this limitation, we implemented quasi-static elastography in an automated breast volume scanner (ABVS), which is an operator-independent 3-D ultrasound system and is especially useful for screening women with dense breasts. The study aim was to investigate if 3-D quasi-static elastography implemented in a clinically used ABVS can discriminate between benign and malignant breast lesions. METHODS: Volumetric breast ultrasound radiofrequency data sets of 82 patients were acquired before and after automated transducer lifting. Lesions were annotated and strain was calculated using an in-house-developed strain algorithm. Two strain ratio types were calculated per lesion: using axial and maximal principal strain (i.e., strain in dominant direction). RESULTS: Forty-four lesions were detected: 9 carcinomas, 23 cysts and 12 other benign lesions. A significant difference was found between malignant (median: 1.7, range: [1.0-3.2]) and benign (1.0, [0.6-1.9]) using maximal principal strain ratios. Axial strain ratio did not reveal a significant difference between benign (0.6, [-12.7 to 4.9]) and malignant lesions (0.8, [-3.5 to 5.1]). CONCLUSION: Three-dimensional strain imaging was successfully implemented on a clinically used ABVS to obtain, visualize and analyze in vivo strain images in three dimensions. Results revealed that maximal principal strain ratios are significantly increased in malignant compared with benign lesions.

Cascaded Plane Wave Ultrasound for Blood Velocity Vector Imaging in the Carotid Artery.

Cascaded dual-polarity waves (CDWs) imaging increases the signal-to-noise ratio (SNR) by transmitting trains of pulses with different polarity order, which are combined via decoding afterward. This potentially enables velocity vector imaging (VVI) in more challenging SNR conditions. However, the motion of blood in between the trains will influence the decoding process. In this work, the use of CDW for blood VVI is evaluated for the first time. Dual-angle, plane wave (PW) ultrasound, CDW-coded, and noncoded conventional PW (cPW), was acquired using a 7.8 MHz linear array at a pulse repetition frequency (PRF) of 8 kHz. CDW-channel data were decoded prior to beamforming and cross correlation-based compound speckle tracking for VVI. Simulations of single scatterer motion show a high dependence of amplitude gain on the velocity magnitude and direction for CDW-coded transmissions. Both simulations and experiments of parabolic flow show increased SNRs for CDW imaging. As a result, CDW outperforms cPW VVI in low SNR conditions, based on both bias and standard deviation (SD). Quantitative linear regression and qualitative analyses of simulated realistic carotid artery blood flow show a similar performance of CDW and cPW for high SNR (14 dB) conditions. However, reducing the SNR to 6 dB, results in a root-mean-squared error 2.7× larger for cPW versus CDW, and an R2 of 0.4 versus 0.9. Initial in vivo evaluation of a healthy carotid artery shows increased SNR and more reliable velocity estimates for CDW versus cPW. In conclusion, this work demonstrates that CDW imaging facilitates improved VVI of deeper located carotid arteries.

Simultaneous Coherent and Displacement Compounding for 2-D Noninvasive Carotid Strain Imaging: A Proof of Principle Study.

Arteriosclerosis results from lipid buildup in artery walls, leading to plaque formation, and is a leading cause of death. Plaque rupture can cause blood clots that might lead to a stroke. Distinguishing plaque types is a challenge, but ultrasound (US) elastography can help by assessing plaque composition based on strain values. Since the artery has a circular structure, an accurate axial and lateral displacement strategy is needed to derive the radial and circumferential strains. A high-precision lateral displacement is challenging due to the lack of phase information in the lateral direction of the beamformed RF data. Previously, our group has developed a compounding technique in which the lateral displacement is estimated using triangulation of the axial displacement estimated from transmitting and beamforming US beams at ±20°. However, transmitting with a single plane wave will reduce signal-to-noise and contrast-to-noise ratio as well as lateral resolution. In this article, we combine our displacement compounding with coherent compounding. Instead of transmitting a single plane wave, multiple plane waves are transmitted at certain angles centered on the angle of the beamforming grids, and then, the backscattered wavefronts are beamformed and coherently compounded on the center of the transmit beams (-20°, +20°, and 0°). The numerical investigation using the GE9LD probe ( f0 = 5.32 MHz, pitch = 230 µ m, and width = 43.9 mm) led us to 19 plane waves spanning angles within -10° to 10° (with respect to center of the transmit beams), resulting in a total of 57 plane wave transmit (for three beamforming grids at 0° and ±20°). FIELD II simulations of a cylindrically shaped phantom (mimicking the carotid artery) at a signal-to-noise ratio (SNR) ≥ 20 dB show that the proposed method decreases the root-mean-square error (RMSE) of the lateral displacement and strain estimations by 40% and 45% compared to the previous method, respectively. The results of our experiments with a carotid artery phantom [made out of 10% polyvinyl alcohol (PVA)] show that the proposed method provides strain images with higher quality and more in agreement with the theory, with 26% lower standard deviation, especially at the peak systolic phase. The proposed method paves the path toward improved quality in vivo 2-D strain imaging using our displacement compounding technique and translating it to 3-D with a row-column array.

Performance evaluation of commercial and non-commercial shear wave elastography implementations for vascular applications.

BACKGROUND: Shear wave elastography (SWE) is mainly used for stiffness estimation of large, homogeneous tissues, such as the liver and breasts. However, little is known about its accuracy and applicability in thin (∼0.5-2 mm) vessel walls. To identify possible performance differences among vendors, we quantified differences in measured wave velocities obtained by commercial SWE implementations of various vendors over different imaging depths in a vessel-mimicking phantom. For reference, we measured SWE values in the cylindrical inclusions and homogeneous background of a commercial SWE phantom. Additionally, we compared the accuracy between a research implementation and the commercially available clinical SWE on an Aixplorer ultrasound system in phantoms and in vivo in patients. METHODS: SWE measurements were performed over varying depths (0-35 mm) using three ultrasound machines with four ultrasound probes in the homogeneous 20 kPa background and cylindrical targets of 10, 40, and 60 kPa of a multi-purpose phantom (CIRS-040GSE) and in the anterior and posterior wall of a homogeneous polyvinyl alcohol vessel-mimicking phantom. These phantom data, along with in vivo SWE data of carotid arteries in 23 patients with a (prior) head and neck neoplasm, were also acquired in the research and clinical mode of the Aixplorer ultrasound machine. Machine-specific estimated phantom stiffness values (CIRS phantom) or wave velocities (vessel phantom) over all depths were visualized, and the relative error to the reference values and inter-frame variability (interquartile range/median) were calculated. Correlations between SWE values and target/vessel wall depth were explored in phantoms and in vivo using Spearman's correlations. Differences in wave velocities between the anterior and posterior arterial wall were assessed with Wilcoxon signed-rank tests. Intra-class correlation coefficients were calculated for a sample of ten patients as a measure of intra- and interobserver reproducibility of SWE analyses in research and clinical mode. RESULTS: There was a high variability in obtained SWE values among ultrasound machines, probes, and, in some cases, with depth. Compared to the homogeneous CIRS-background, this variation was more pronounced for the inclusions and the vessel-mimicking phantom. Furthermore, higher stiffnesses were generally underestimated. In the vessel-mimicking phantom, anterior wave velocities were (incorrectly) higher than posterior wave velocities (3.4-5.6 m/s versus 2.9-5.9 m/s, p ≤ 0.005 for 3/4 probes) and remarkably correlated with measurement depth for most machines (Spearman's ρ = -0.873-0.969, p < 0.001 for 3/4 probes). In the Aixplorer's research mode, this difference was smaller (3.3-3.9 m/s versus 3.2-3.6 m/s, p = 0.005) and values did not correlate with measurement depth (Spearman's ρ = 0.039-0.659, p ≥ 0.002). In vivo, wave velocities were higher in the posterior than the anterior vessel wall in research (left p = 0.001, right p < 0.001) but not in clinical mode (left: p = 0.114, right: p = 0.483). Yet, wave velocities correlated with vessel wall depth in clinical (Spearman's ρ = 0.574-0.698, p < 0.001) but not in research mode (Spearman's ρ = -0.080-0.466, p ≥ 0.003). CONCLUSIONS: We observed more variation in SWE values among ultrasound machines and probes in tissue with high stiffness and thin-walled geometry than in low stiffness, homogeneous tissue. Together with a depth-correlation in some machines, where carotid arteries have a fixed location, this calls for caution in interpreting SWE results in clinical practice for vascular applications.

Feasibility of capturing vessel expansion with 4D-CTA: Phantom study to determine reproducibility, spatial and temporal resolution.

BACKGROUND: Dynamic Computed Tomography Angiography (4D CTA) has the potential of providing insight into the biomechanical properties of the vessel wall, by capturing motion of the vessel wall. For vascular pathologies, like intracranial aneurysms, this could potentially refine diagnosis, prognosis, and treatment decision-making. PURPOSE: The objective of this research is to determine the feasibility of a 4D CTA scanner for accurately measuring harmonic diameter changes in an in-vitro simulated vessel. METHODS: A silicon tube was exposed to a simulated heartbeat. Simulated heart rates between 40 and 100 beats-per-minute (bpm) were tested and the flow amplitude was varied, resulting in various changes of tube diameter. A 320-detector row CT system with ECG-gating captured three consecutive cycles of expansion. Image registration was used to calculate the diameter change. A vascular echography set-up was used as a reference, using a 9 MHz linear array transducer. The reproducibility of 4D CTA was represented by the Pearson correlation (r) between the three consecutive diameter change patterns, captured by 4D CTA. The peak value similarity (pvs) was calculated between the 4D CTA and US measurements for increasing frequencies and was chosen as a measure of temporal resolution. Spatial resolution was represented by the Sum of the Relative Percentual Difference (SRPD) between 4D CTA and US diameter change patterns for increasing amplitudes. RESULTS: The reproducibility of 4D CTA measurements was good (r ≥ 0.9) if the diameter change was larger than 0.3 mm, moderate (0.7 ≤ r < 0.9) if the diameter change was between 0.1 and 0.3 mm, and low (r < 0.7) if the diameter change was smaller than 0.1 mm. Regarding the temporal resolution, the amplitude of 4D CTA was similar to the US measurements (pvs ≥ 90%) for the frequencies of 40 and 50 bpm. Frequencies between 60 and 80 bpm result in a moderate similarity (70% ≤ pvs < 90%). A low similarity (pvs < 70%) is observed for 90 and 100 bpm. Regarding the spatial resolution, diameter changes above 0.30 mm result in SRPDs consistently below 50%. CONCLUSION: In a phantom setting, 4D CTA can be used to reliably capture reproducible tube diameter changes exceeding 0.30 mm. Low pulsation frequencies (40 or 50 bpm) provide an accurate measurement of the maximum tube diameter change.

Flexible large-area ultrasound arrays for medical applications made using embossed polymer structures.

With the huge progress in micro-electronics and artificial intelligence, the ultrasound probe has become the bottleneck in further adoption of ultrasound beyond the clinical setting (e.g. home and monitoring applications). Today, ultrasound transducers have a small aperture, are bulky, contain lead and are expensive to fabricate. Furthermore, they are rigid, which limits their integration into flexible skin patches. New ways to fabricate flexible ultrasound patches have therefore attracted much attention recently. First prototypes typically use the same lead-containing piezo-electric materials, and are made using micro-assembly of rigid active components on plastic or rubber-like substrates. We present an ultrasound transducer-on-foil technology based on thermal embossing of a piezoelectric polymer. High-quality two-dimensional ultrasound images of a tissue mimicking phantom are obtained. Mechanical flexibility and effective area scalability of the transducer are demonstrated by functional integration into an endoscope probe with a small radius of 3 mm and a large area (91.2×14 mm2) non-invasive blood pressure sensor.

Dynamic Computed Tomography Angiography for capturing vessel wall motion: A phantom study for optimal image reconstruction.

BACKGROUND: Reliably capturing sub-millimeter vessel wall motion over time, using dynamic Computed Tomography Angiography (4D CTA), might provide insight in biomechanical properties of these vessels. This may improve diagnosis, prognosis, and treatment decision making in vascular pathologies. PURPOSE: The aim of this study is to determine the most suitable image reconstruction method for 4D CTA to accurately assess harmonic diameter changes of vessels. METHODS: An elastic tube (inner diameter 6 mm, wall thickness 2 mm) was exposed to sinusoidal pressure waves with a frequency of 70 beats-per-minute. Five flow amplitudes were set, resulting in increasing sinusoidal diameter changes of the elastic tube, measured during three simulated pulsation cycles, using ECG-gated 4D CTA on a 320-detector row CT system. Tomographic images were reconstructed using one of the following three reconstruction methods: hybrid iterative (Hybrid-IR), model-based iterative (MBIR) and deep-learning based (DLR) reconstruction. The three reconstruction methods where based on 180 degrees (half reconstruction mode) and 360 degrees (full reconstruction mode) raw data. The diameter change, captured by 4D CTA, was computed based on image registration. As a reference metric for diameter change measurement, a 9 MHz linear ultrasound transducer was used. The sum of relative absolute differences (SRAD) between the ultrasound and 4D CTA measurements was calculated for each reconstruction method. The standard deviation was computed across the three pulsation cycles. RESULTS: MBIR and DLR resulted in a decreased SRAD and standard deviation compared to Hybrid-IR. Full reconstruction mode resulted in a decreased SRAD and standard deviations, compared to half reconstruction mode. CONCLUSIONS: 4D CTA can capture a diameter change pattern comparable to the pattern captured by US. DLR and MBIR algorithms show more accurate results than Hybrid-IR. Reconstruction with DLR is >3 times faster, compared to reconstruction with MBIR. Full reconstruction mode is more accurate than half reconstruction mode.