Conventional B-mode Ultrasound Imaging Research Articles

Demonstration Study of Reflector-Based Volumetric Speed-of-Sound Imaging With Linear Ultrasound Arrays

Conventional B-mode ultrasound imaging has difficulty in delineating homogeneous soft tissues with similar acoustic impedances, as the reflectivity depends on the acoustic impedance at the interface. As a quantitative imaging biomarker sensitive to alteration of biomechanical properties, speed-of-sound (SoS) holds promising potential for tissue and disease differentiation such as delineation of different breast tissue types with similar acoustic impedance. Compared to two-dimensional (2D) SoS images, three-dimensional (3D) volumetric SoS images achieved through a full-angle ultrasound scan can reveal more intricate morphological structures of tissues; however, they generally require a ring transducer. In this study, we introduce a 3D SoS reconstruction system that utilizes hand-held linear arrays instead. This system employs a passive reflector positioned opposite the linear arrays, serving as an echogenic reference for time-of-flight (ToF) measurements, and a high-definition camera to track the location corresponding to each group of transmit-receive data. To merge these two streams of ToF measurements and location tracking, a voxel-based reconstruction algorithm is implemented. Experimental results with gelatin phantom and ex vivo tissue have demonstrated the stability of our proposed method. Moreover, the results underscore the potential of this system as a complementary diagnostic modality, particularly in the context of diseases such as breast cancer.

First-in-human diagnostic study of hepatic steatosis with computed ultrasound tomography in echo mode

BackgroundNon-alcoholic fatty liver disease is rapidly emerging as the leading global cause of chronic liver disease. Efficient disease management requires low-cost, non-invasive techniques for diagnosing hepatic steatosis accurately. Here, we propose quantifying liver speed of sound (SoS) with computed ultrasound tomography in echo mode (CUTE), a recently developed ultrasound imaging modality adapted to clinical pulse-echo systems. CUTE reconstructs the spatial distribution of SoS by measuring local echo phase shifts when probing tissue at varying steering angles in transmission and reception.MethodsIn this first-in-human phase II diagnostic study, we evaluated the liver of 22 healthy volunteers and 22 steatotic patients. We used conventional B-mode ultrasound images and controlled attenuation parameter (CAP) to diagnose the presence (CAP≥ 280 dB/m) or absence (CAP < 248 dB/m) of steatosis in the liver. A fully integrated convex-probe CUTE implementation was developed on the ultrasound system to estimate liver SoS. We investigated its diagnostic value via the receiver operating characteristic (ROC) analysis and correlation to CAP measurements.ResultsWe show that liver CUTE-SoS estimates correlate strongly (r = −0.84, p = 8.27 × 10−13) with CAP values and have 90.9% (95% confidence interval: 84–100%) sensitivity and 95.5% (81–100%) specificity for differentiating between normal and steatotic livers (area under the ROC curve: 0.93–1.0).ConclusionsOur results demonstrate that liver CUTE-SoS is a promising quantitative biomarker for diagnosing liver steatosis. This is a necessary first step towards establishing CUTE as a new quantitative add-on to diagnostic ultrasound that can potentially be as versatile as conventional ultrasound imaging.

A Data-Driven Approach for Estimating Temperature Variations Based on B-mode Ultrasound Images and Changes in Backscattered Energy.

Thermal treatments that use ultrasound devices as a tool have as a key point the temperature control to be applied in a specific region of the patient's body. This kind of procedure requires caution because the wrong regulation can either limit the treatment or aggravate an existing injury. Therefore, determining the temperature in a region of interest in real-time is a subject of high interest. Although this is still an open problem, in the field of ultrasound analysis, the use of machine learning as a tool for both imaging and automated diagnostics are application trends. In this work, a data-driven approach is proposed to address the problem of estimating the temperature in regions of a B-mode ultrasound image as a supervised learning problem. The proposal consists in presenting a novel data modeling for the problem that includes information retrieved from conventional B-mode ultrasound images and a parametric image built based on changes in backscattered energy (CBE). Then, we compare the performance of classic models in the literature. The computational results presented that, in a simulated scenario, the proposed approach that a Gradient Boosting model would be able to estimate the temperature with a mean absolute error of around 0.5°C, which is acceptable in practical environments both in physiotherapic treatments and high intensity focused ultrasound (HIFU).

Estimators of tissue absorption parameters power-law prefactor and power-law exponent from medical ultrasonic images

Abstract Ultrasound is a mechanical wave propagating in tissue which is influenced in its propagation behavior by the locally prevailing acousto-mechanical conditions. By suitable processing of the back-scattered signals received by the ultrasound transducer, tissue parameters such as local bulk modulus, mass density, speed of sound, isotropic scattering coefficient, and also the locally acting tissue absorption can be inferred. A discipline that has received increasing attention in the medical ultrasonic imaging discipline and its scientific publications in recent years is quantitative ultrasound (QUS) which tries to estimate with great accuracy these local acting tissue parameters. In this paper we analyze different algorithms for estimation of high spatial resolution tissue absorption parameters. On the one hand, there is a simple absorption estimator based on the evaluation of the quotient of the power density spectra calculated for different depth regions (spectral-log-difference estimator), which, however, assumes a linearly with frequency increasing absorption, this is contrasted with an estimator which also allows to estimate a polynomial increase of the absorption with frequency (method-of-moments estimator). Since a closed-form solution cannot be given for this, a maximum-likelihood estimator for which there is always an estimate that can be computed numerically efficiently is developed. The results, tissue attenuation, are presented as a color-coded overlay on conventional B-mode ultrasound images showing only morphology.

Emerging Role of Quantitative Ultrasound-Based Imaging Techniques for Characterizing Rotator Cuff Tears: A Scoping Review

Rotator cuff myosteatosis following cuff tears is very common and one of the most important prognostic factors in clinical management. Quantitative ultrasound-based imaging techniques (QUBIT) are frequently used along with magnetic resonance imaging (MRI) to evaluate rotator cuff fatty degeneration. However, the examination of rotator cuff tissue integrity by QUBIT is lacking a standardized imaging protocol and procedural methodologies. In this scoping review, we synthesized the current state of QUBIT against the reference imaging modalities in patients with rotator cuff tears. The literature search was extracted from 963 studies, with 22 studies included in the final review in accordance with the preferred reporting items for systematic reviews and meta-analyses extensions for scoping reviews. The selected studies included human participants and focused on measuring at least one prognostic or diagnostic factor using ultrasonography-based imaging with reference to MRI. The findings suggest both conventional B-mode ultrasound and shear wave elastography imaging were comparable to MRI-based imaging techniques for the evaluation of fatty infiltration and rotator cuff tear characterization. This review establishes guidelines for reporting shoulder-specific QUBIT aimed at developing a standardized imaging protocol. The objective was to enhance the diagnostic and prognostic capabilities of QUBIT in the clinical setting.

The Spectrum-Beamformer for Conventional B-Mode Ultrasound Imaging System: Principle, Validation, and Robustness.

Fast and efficient imaging techniques are important for real-time ultrasound imaging. The delay and sum (DAS) beamformer is the most widely-used strategy in focused ultrasound imaging (FUI) modality. However, calculating the time delays and coherently summing the amplitude response in DAS is computationally expensive and generally require a high-performance processor to realize real-time processing. In this study, an efficient spectrum beamformer, namely full-matrix capture (FMC)-stolt, is proposed in FUI system with a linear phased array. The imaging performance of FMC-stolt was validated with the point-scatter simulation and in vitro point and cyst phantoms, and then compared with that of five beamformers, that is, Multiline acquisition (MLA), retrospective transmit beamforming (RTB) in the FUI modality, as well as DAS, Garcia's frequency-wavenumber (f-k), Lu's f-k in the coherent plane wave compounding imaging (CPWCI) modality, under specific conditions. We show that the imaging performance of FMC-stolt is better than MLA-DAS in non-transmit-focal regions, and comparable with RTB-DAS at all imaging depths. FMC-stolt also shows better discontinuity alleviation than MLA and RTB. In addition, FMC-stolt has similar imaging characteristics (e.g., off-axis resolution, computational cost) as the f-k beamformers. The computational complexity and actual computational time indicate that FMC-stolt is comparable to Garcia's f-k, Lu's f-k, and faster than RTB and CPWCI-DAS if the transmitting numbers are close for FUI and CPWCI. The study demonstrates that the proposed FMC-stolt could achieve good reconstruction speed while preserving high-quality images and thus provide a choice for software beamforming for conventional B-mode ultrasound imaging, especially for hand-held devices with limited performance processors.

Morphological characterization of breast tumors using conventional B-mode ultrasound images.

This work aims to develop and test a vendor-independent computer-aided diagnosis (CAD) system that uses conventional B-mode ultrasound images to distinguish between benign and malignant breast tumors. Three morphological features were extracted from 323 breast tumor lesions including the perimeter, regularity variance, and circularity range ratio. Lesions were segmented using the active contour method via semi- andfully-automated algorithms. Then, the support vector machine classifier was used to identify breast lesions. Results of the CAD system exhibited accuracies of 95.98% and 95.67%using the semi- and fully-automated segmentation, respectively. Based on the preliminary results, this CAD system with such unique combination of geometrical features shall improve the diagnostic decisions and may reduce the need of unnecessary needle biopsies.

Multi-covariate Imaging of Sub-resolution Targets.

Conventional B-mode ultrasound imaging assumes that targets consist of collections of point scatterers. Diffraction, however, presents a fundamental limit on a scanner's ability to resolve individual scatterers in most clinical imaging environments. Well-known optics and ultrasound literature has characterized these diffuse scattering targets as spatially incoherent and statistically stationary. In this paper, we apply a piecewise-stationary statistical model to diffuse scattering targets, in which the covariance of backscattered echoes can be described as the linear superposition of constituent components corresponding to echoes from distinct spatial regions in the field. Using this framework, we present Multi-covariate Imaging of Sub-resolution Targets (MIST), a novel estimation-based method to image the statistical properties of diffuse scattering targets, based on a decomposition of aperture domain spatial covariance. The mathematical foundations of the estimator are analytically derived, and MIST is evaluated in phantom, simulation, and in vivo studies, demonstrating consistent improvements in contrast-to-noise ratio and speckle statistics across imaging targets, without an apparent loss in resolution.

Wavelet-based computationally-efficient computer-aided characterization of liver steatosis using conventional B-mode ultrasound images

Hepatic steatosis occurs when lipids accumulate in the liver leading to steatohepatitis, which can evolve into cirrhosis and consequently may end with hepatocellular carcinoma. Several automatic classification algorithms have been proposed to detect liver diseases. However, some algorithms are manufacturer-dependent, while others require extensive calculations and consequently prolonged computational time. This may limit the development of real-time and manufacturer-independent computer-aided detection of liver steatosis. This work demonstrates the feasibility of a computationally-efficient and manufacturer-independent wavelet-based computer-aided liver steatosis detection system using conventional B-mode ultrasound (US) imaging. Seven features were extracted from the approximation part of the second-level wavelet packet transform (WPT) of US images. The proposed technique was tested on two datasets of ex-vivo mice livers with and without gelatin embedding, in addition to a third dataset of in-vivo human livers acquired using two different US machines. Using the gelatin-embedded mice liver dataset, the technique exhibited 98.8% accuracy, 97.8% sensitivity, and 100% specificity, and the frame classification time was reduced from0.4814s using original US images to 0.1444s after WPT preprocessing. When the other mice liver dataset was used, the technique showed 85.74% accuracy, 84.4% sensitivity, and 88.5% specificity, and the frame classification time was reduced from 0.5612s to 0.2903s. Using human liver image data, the best classifier exhibited 92.5% accuracy, 93.0% sensitivity, 91.0% specificity, and the classification time was reduced from 0.660s to 0.146s. This technique can be useful for developing computationally-efficient and manufacturer-independent noninvasive CAD systems for fatty liver detection.

Short-lag Spatial Coherence Imaging in 1.5-D and 1.75-D Arrays: Elevation Performance and Array Design Considerations.

Short-lag spatial coherence (SLSC) imaging has demonstrated improved performance over conventional B-Mode ultrasound imaging. Previous work has evaluated the performance of SLSC using 2-D matrix arrays in simulation and in vivo studies across various levels of subaperture beamforming, demonstrating improved contrast-to-noise ratio (CNR) and speckle signal-to-noise ratio (SNR) over 1-D arrays. This work explores the application of SLSC imaging in 1.5-D and 1.75-D arrays to quantify the impacts of elevation element count, mirroring, and Fresnel element spacing on SLSC image quality. Through simulation and in vivo studies, increased elevation element count was shown to improve CNR and speckle SNR relative to 1-D SLSC and B-Mode images. Elevation mirroring (1.5-D) was shown to force the inclusion of long lags into the SLSC calculation, introducing additional decorrelation and reducing image quality relative to 1.75-D arrays with individually-connected elements. These results demonstrate the effectiveness of SLSC imaging in 1.5-D and 1.75-D arrays.

A review of ultrasound detection methods for breast microcalcification.

Breast microcalcifications are one of the important imaging features of early breast cancer and are a key to early breast cancer diagnosis. Ultrasound imaging has been widely used in the detection and diagnosis of breast diseases because of its low cost, nonionizing radiation, and real-time capability. However, due to factors such as limited spatial resolution and speckle noise, it is difficult to detect breast microcalcifications using conventional B-mode ultrasound imaging. Recent studies show that new ultrasound technologies improved the visualization of microcalcifications over conventional B-mode ultrasound imaging. In this paper, a review of the literature on the ultrasonic detection methods of microcalcifications was conducted. The reviewed methods were broadly divided into high-frequency B-mode ultrasound imaging techniques, B-mode ultrasound image processing techniques, ultrasound elastography techniques, time reversal techniques, high spatial frequency techniques, second-order ultrasound field imaging techniques, and photoacoustic imaging techniques. The related principles and research status of these methods were introduced, and the characteristics and limitations of the various methods were discussed and analyzed. Future developments of ultrasonic breast microcalcification detection are suggested.

Spatial domain reconstruction for imaging speed-of-sound with pulse-echo ultrasound: simulation and in vivo study

Despite many uses of ultrasound, some pathologies such as breast cancer still cannot reliably be diagnosed in either conventional B-mode ultrasound imaging nor with more recent ultrasound elastography methods. Speed-of-sound (SoS) is a quantitative imaging biomarker, which is sensitive to structural changes due to pathology, and hence could facilitate diagnosis. Full-angle ultrasound computed tomography (USCT) was proposed to obtain spatially-resolved SoS images, however, its water-bath setup involves practical limitations. To increase clinical utility and for widespread use, recently, a limited-angle Fourier-domain SoS reconstruction was proposed, however, it suffers from significant image reconstruction artifacts. In this work, we present a SoS reconstruction strategy, where the forward problem is formulated using differential time-of-flight measurements based on apparent displacements along different ultrasound wave propagation paths, and the inverse problem is solved in spatial-domain using a proposed total-variation scheme with spatially-varying anisotropic weighting to compensate for geometric bias from limited angle imaging setup. This is shown to be robust to missing displacement data and easily allow for incorporating any prior geometric information. In numerical simulations, SoS values in inclusions are accurately reconstructed with 90% accuracy up to a noise level of 50%. With respect to Fourier-domain reconstruction, our proposed method improved contrast ratio from 0.37 to 0.67 for even high noise levels such as 50%. Numerical full-wave simulation and our preliminary in vivo results illustrate the clinical applicability of our method in a breast cancer imaging setting. Our proposed method requires single-sided access to the tissue and can be implemented as an add-on to conventional ultrasound equipment, applicable to a range of transducers and applications.

Automated detection and classification of liver fibrosis stages using contourlet transform and nonlinear features

Background and objectiveLiver fibrosis is a type of chronic liver injury that is characterized by an excessive deposition of extracellular matrix protein. Early detection of liver fibrosis may prevent further growth toward liver cirrhosis and hepatocellular carcinoma. In the past, the only method to assess liver fibrosis was through biopsy, but this examination is invasive, expensive, prone to sampling errors, and may cause complications such as bleeding. Ultrasound-based elastography is a promising tool to measure tissue elasticity in real time; however, this technology requires an upgrade of the ultrasound system and software. In this study, a novel computer-aided diagnosis tool is proposed to automatically detect and classify the various stages of liver fibrosis based upon conventional B-mode ultrasound images. MethodsThe proposed method uses a 2D contourlet transform and a set of texture features that are efficiently extracted from the transformed image. Then, the combination of a kernel discriminant analysis (KDA)-based feature reduction technique and analysis of variance (ANOVA)-based feature ranking technique was used, and the images were then classified into various stages of liver fibrosis. ResultsOur 2D contourlet transform and texture feature analysis approach achieved a 91.46% accuracy using only four features input to the probabilistic neural network classifier, to classify the five stages of liver fibrosis. It also achieved a 92.16% sensitivity and 88.92% specificity for the same model. The evaluation was done on a database of 762 ultrasound images belonging to five different stages of liver fibrosis. ConclusionsThe findings suggest that the proposed method can be useful to automatically detect and classify liver fibrosis, which would greatly assist clinicians in making an accurate diagnosis.

Value of ultrasound elastography versus transrectal prostatic biopsy in prostatic cancer detection

ObjectiveTo detect the impact of ultrasound elastography in diagnosis of prostatic cancer, and to evaluate its capability in differentiating benign from malignant lesions. Materials and methodsFifty patients with different prostatic lesions suspicious for malignancy were included. All patients had a conventional B-mode ultrasound examination and color Doppler imaging, and then real time ultrasound elastography was performed in the same session. Finally, the results were compared to the histo-pathological results of those lesions. ResultsThe addition of Strain ratio parameter for evaluating the elastography images showed the highest sensitivity of 74.2%, specificity of 73.7% and accuracy of 74.0% at a best cutoff point of 5.5 between benign and malignant lesions. ConclusionBased on our results, prostate US combined with elastography can be a helpful tool for finding malignant lesions. Also it can help in targeting the biopsy site.

Focal masses in a non-cirrhotic liver: The additional benefit of CEUS over baseline imaging

Incidentally detected focal liver lesions are commonly encountered in clinical practice presenting a challenge in the daily department work flow. Guidelines for the management of incidental focal liver lesions have been published but comments, illustrations and recommendations regarding practical issues are crucial. The unique features of contrast-enhanced ultrasound in non-invasive assessment of focal liver lesion enhancement throughout the vascular phases in real-time has allowed an impressive improvement in the diagnostic accuracy of ultrasound.We highlight the additional benefit of contrast-enhanced ultrasound over conventional B-mode ultrasound imaging in detection, characterization, differential and final diagnosis of focal liver lesions, as well as for liver metastases screening. The current roles of cross-sectional imaging are explained in detail, with indications and limitations for each procedure. The advantages of CEUS, such as non-ionizing radiation exposure, cost benefits, non-iodinate contrast agents, and repeatability are also described ultimately improving patient management.

Advances in Lower Extremity Ultrasound

Diagnostic ultrasound techniques used in the evaluation of the musculoskeletal system are rapidly evolving. Conventional B-mode and Doppler ultrasound imaging methods are workhorses in the diagnosis and treatment decision making for traumatic and pathologic conditions of joints, tendons, muscles, ligaments, and peripheral nerves. Recently developed sonoelastography techniques enable the qualitative and quantitative evaluation of the material properties of musculoskeletal tissues . The recent availability of sonoelastography on clinical machines will facilitate its progressive utilization in routine clinical practice. Exciting new developments in ultrasound imaging enable real-time fusion with imported magnetic resonance or computed tomography images, facilitating ultrasound-guided interventional procedures and teaching of ultrasound anatomy to trainees. In this review article, the authors discuss new advances in sonoelastography of the lower extremity with emphasis on shear wave imaging and briefly the exciting features of ultrasound fusion imaging with computed tomography and magnetic resonance imaging.

Automatic extraction of bone surfaces from 3D ultrasound images in orthopaedic trauma cases.

3D ultrasound (US) imaging has the potential to become a powerful alternative imaging modality in orthopaedic surgery as it is radiation-free and can produce 3D images (in contrast to fluoroscopy) in near-real time. Conventional B-mode US images, however, are characterized by high levels of noise and reverberation artifacts, image quality is user-dependent, and bone surfaces are blurred, which makes it difficult to both interpret images and to use them as a basis for navigated interventions. 3D US has great potential to assist orthopaedic care, possibly assisting during surgery if the anatomical structures of interest could be localized and visualized with sufficient accuracy and clarity and in a highly automated rapid manner. In this paper, we present clinical results for a novel 3D US segmentation technique we have recently developed based on multi-resolution analysis to localize bone surfaces in 3D US volumes. Our method is validated on scans obtained from 29 trauma patients with distal radius and pelvic ring fractures. Qualitative and quantitative results demonstrate remarkably clear segmentations of bone surfaces with an average surface fitting error of 0.62 mm (standard deviation (SD) of 0.42 mm) for pelvic patients and 0.21 mm (SD 0.14 mm) for distal radius patients. These results suggest that our technique is sufficiently accurate for potential use in orthopaedic trauma applications.

Receiver operating characteristic analysis for the detectability of malignant breast lesions in acousto-optic transmission ultrasound breast imaging

Conventional B-mode ultrasound imaging has proven to be a valuable supplement to x-ray mammography for the detection of malignant breast lesions in premenopausal women with high breast density. We have developed a high-resolution transmission ultrasound breast imaging system employing a novel acousto-optic (AO) liquid crystal detector to enable rapid acquisition of full-field breast ultrasound images during routine cancer screening. In this study, a receiver operating characteristic (ROC) analysis was performed to assess the diagnostic utility of our prototype system. Using a comprehensive system model, we simulated the AO transmission ultrasound images expected for a 1-mm malignant lesion contained within a dense breast consisting of 75% normal breast parenchyma and 25% fat tissue. A Gaussian noise model was assumed with SNRs ranging from 0 to 30. For each unique SNR, an ROC curve was constructed and the area under the curve (AUC) was computed to assess the lesion detectability of our system. For SNRs in excess of 10, the analysis revealed AUCs greater than 0.8983, thus demonstrating strong detectability. Our results indicate the potential for using an imaging system of this kind to improve breast cancer screening efforts by reducing the high false negative rate of mammography in premenopausal women.

P.13.9 Acoustic radiation force impulse imaging for the differentiation of muscle tissue stiffness in neuromuscular disorders

Acoustic Radiation Force Impulse (ARFI)-Imaging is an ultrasound-based elastography method enabling quantitative measurement of tissue stiffness. It involves the mechanical excitation of tissue using acoustic pulses to generate localized displacements resulting in shear-wave propagation, which is tracked using correlation-based methods and recorded in meters/s. The aim of this study is to evaluate the sensitivity and specificity of ARFI-imaging for muscle tissue stiffness differentiation (fat vs. fibrous tissue) in select muscles of patients unaffected by muscle disease vs. those affected by collagen 6 myopathy (COL6), LAMA2 related muscular dystrophy (LAMA2), or Duchenne muscular dystrophy (DMD). Inclusion criteria were: 5–18 year old boys and girls unaffected by muscle disease and age matched children with diagnosed with COL6, LAMA2, or DMD based on muscle biopsy or genetic testing. All patients received conventional B-Mode ultrasound and ARFI imaging at specific anatomical landmarks for the greatest bulk of the biceps, triceps, rectus femoris, vastus lateralis, tibialis anterior, and medial and lateral gastrocnemius muscles. Data from 85 (20 COL6; 10 DMD, 15 LAMA2, 40 unaffected) children will be available for analysis. To date, the mean averaged velocity of all assessed muscles with ARFI imaging in healthy muscle tissue was 1.43 m/s, in COL6 was 1.21 m/s and in DMD was 1.53 m/s. For muscles assess individually, the most reproducibly distinguishing values were noted in the tibialis anterior muscle with average muscle velocities of 1.55 m/s in unaffected muscle tissue, vs. 1.17 m/s in COL6 and 2.29 m/s in DMD. ARFI can be used as an additional tool for the noninvasive assessment of muscle in neuromuscular disorders. Further testing regarding longitudinal data over time, validation as an outcome measure and comparison to MRI data and motor function testing as it relates to this cohort is pending.

Compound Imaging Technology and Echogenic Needle Design

Needle visualization in ultrasound-guided regional anesthesia can be improved by using needles of echogenic design with higher rate of reflection of ultrasound waves. Imaging solutions such as compound imaging might further improve imaging of both needle and tissue; these effects have not yet been studied. We hypothesized that compound imaging would significantly improve needle visibility, regardless of the insertion angle or needle type used. The effects of compound imaging on needle artifacts and tissue imaging were also investigated. A total of 200 video clips of in-plane needle insertions were obtained in embalmed cadavers with a conventional needle and an echogenic needle at 5 different insertion angles, with both conventional B-mode ultrasound imaging and compound imaging technology. Visibility of the needle shaft and needle tip as well as the needle artifact rate were assessed by a blinded investigator on a 4-point ordinal scale. The effects on tissue image quality and speckle artifacts were also assessed. Stepwise linear regression was performed to differentiate effects on needle visibility scores. Imaging of the needle shaft and tip was significantly enhanced when compound imaging technology was used (P < 0.0001). Use of echogenically designed needles or shallow needle insertion angles improved visibility of both shaft and tip (both P < 0.0001). With compound imaging, there are fewer needle artifacts, and tissue imaging quality and speckle artifact rate are significantly improved. Compound imaging technology enhances needle imaging with both echogenic and conventional needles. Tissue imaging and speckle artifacts are also optimized. Echogenic needle design results in better needle visibility scores in both B-mode and compound imaging.