Synthetic Elastography Using B-Mode Ultrasound Through a Deep Fully Convolutional Neural Network.

Shear-wave elastography (SWE) permits local estimation of tissue elasticity, an important imaging marker in biomedicine. This recently developed, advanced technique assesses the speed of a laterally traveling shear wave after an acoustic radiation force "push" to estimate local Young's moduli in an operator-independent fashion. In this work, we show how synthetic SWE (sSWE) images can be generated based on conventional B-mode imaging through deep learning. Using side-by-side-view B-mode/SWE images collected in 50 patients with prostate cancer, we show that sSWE images with a pixel-wise mean absolute error of 4.5 ± 0.96 kPa with regard to the original SWE can be generated. Visualization of high-level feature levels through t -distributed stochastic neighbor embedding reveals substantial overlap between data from two different scanners. Qualitatively, we examined the use of the sSWE methodology for B-mode images obtained with a scanner without SWE functionality. We also examined the use of this type of network in elasticity imaging in the thyroid. Limitations of the technique reside in the fact that networks have to be retrained for different organs, and that the method requires standardization of the imaging settings and procedure. Future research will be aimed at the development of sSWE as an elasticity-related tissue typing strategy that is solely based on B-mode ultrasound acquisition, and the examination of its clinical utility.

Blind Source Separation for Clutter and Noise Suppression in Ultrasound Imaging: Review for Different Applications.

Blind source separation (BSS) refers to a number of signal processing techniques that decompose a signal into several "source" signals. In recent years, BSS is increasingly employed for the suppression of clutter and noise in ultrasonic imaging. In particular, its ability to separate sources based on measures of independence rather than their temporal or spatial frequency content makes BSS a powerful filtering tool for data in which the desired and undesired signals overlap in the spectral domain. The purpose of this work was to review the existing BSS methods and their potential in ultrasound imaging. Furthermore, we tested and compared the effectiveness of these techniques in the field of contrast-ultrasound super-resolution, contrast quantification, and speckle tracking. For all applications, this was done in silico, in vitro, and in vivo. We found that the critical step in BSS filtering is the identification of components containing the desired signal and highlighted the value of a priori domain knowledge to define effective criteria for signal component selection.

Convective-Dispersion Modeling in 3D Contrast-Ultrasound Imaging for the Localization of Prostate Cancer.

Despite being the solid tumor with the highest incidence in western men, prostate cancer (PCa) still lacks reliable imaging solutions that can overcome the need for systematic biopsies. Dynamic contrast-enhanced ultrasound imaging (DCE-US) allows us to quantitatively characterize the vascular bed in the prostate, due to its ability to visualize an intravenously administered bolus of contrast agents. Previous research has demonstrated that DCE-US parameters related to the vascular architecture are useful markers for the localization of PCa lesions. In this paper, we propose a novel method to assess the convective dispersion (D) and velocity (v) of the contrast bolus spreading through the prostate from three-dimensional (3D) DCE-US recordings. By assuming that D and v are locally constant, we solve the convective-dispersion equation by minimizing the corresponding regularized least-squares problem. 3D multiparametric maps of D and v were compared with 3D histopathology retrieved from the radical prostatectomy specimens of six patients. With a pixel-wise area under the receiver operating characteristic curve of 0.72 and 0.80, respectively, the method shows diagnostic value for the localization of PCa.

A handheld SPIO-based sentinel lymph node mapping device using differential magnetometry.

Sentinel lymph node biopsy has become a staple tool in the diagnosis of breast cancer. By replacing the morbidity-plagued axillary node clearance with removing only those nodes most likely to contain metastases, it has greatly improved the quality of life of many breast cancer patients. However, due to the use of ionizing radiation emitted by the technetium-based tracer material, the current sentinel lymph node biopsy has serious drawbacks. Most urgently, the reliance on radioisotopes limits the application of this procedure to small parts of the developed world, and it imposes restrictions on patient planning and hospital logistics. Magnetic alternatives have been tested in recent years, but all have their own drawbacks, mostly related to interference from metallic instruments and electromagnetic noise coming from the human body. In this paper, we demonstrate an alternative approach that utilizes the unique nonlinear magnetic properties of superparamagnetic iron oxide nanoparticles to eliminate the drawbacks of both the traditional gamma-radiation centered approach and the novel magnetic techniques pioneered by others. Contrary to many other nonlinear magnetic approaches however, field amplitudes are limited to 5 mT, which enables handheld operation without additional cooling. We show that excellent mass sensitivity can be obtained without the need for external re-balancing of the probe to negate any influences from the human body. Additionally, we show how this approach can be used to suppress artefacts resulting from the presence of metallic instruments, which are a significant dealbreaker when using conventional magnetometry-based approaches.

Imaging modalities in Focal Therapy: Multiparametric Ultrasound.

OBJECTIVES: Prostate cancer (PCa) is the most common form of cancer among men in the US and the second most common cause of death. It has been observed that an increasing number of newly diagnosed patients exhibit low-risk features and that over-treatment with radical prostatectomy is a growing problem. The feasibility of focal therapy as an organsparing alternative, however, depends on the reliability of imaging techniques to identify, localize and monitor clinically relevant PCa lesions. The aim of this review is to investigate the potential of multiparametric ultrasound (mpUS) for focal therapy. METHODS: We briefly introduce the most common focal therapies and thoroughly discuss the ability of available ultrasound modalities to localize PCa and reflect tissue properties. The imaging requirements of the focal therapies are studied to put the performance of the US techniques into perspective. RESULTS: We found that transrectal greyscale echography, Doppler sonography, elastography, contrast-enhanced ultrasonography and computerized ultrasound have been studied for the purpose of prostate imaging. Several of these modalities are already frequently used in current clinical practice; to add to the diagnostic process of PCa, to guide and monitor the application of focal therapy or to perform follow-up after treatment. Despite their capability to detect a large fraction of the PCa lesions, none of these modalities is currently considered sufficiently accurate for stand-alone tumour detection and localization. However, although there are only few studies reporting on a combined use of different ultrasound modalities, the results of an mpUS approach seem promising. CONCLUSION: Several US modalities have been successfully applied as a viable alternative to monitor tissue destruction during and after treatment. In view of the advantages of US and the promising results of a multiparametric approach in PCa detection and localization, researchers are urged to further investigate mpUS for therapeutic purposes.