Shear-wave imaging of viscoelasticity using local impulse response identification

\u3cp\u3eImaging technologies that allow assessment of the elastic properties of soft tissue provide clinicians with an important asset for several diagnostic applications. A quantitative measure of stiffness can be obtained by shear-wave (SW) elasticity imaging, a method that uses acoustic radiation force to produce laterally-propagating shear waves that can be tracked to obtain the velocity, which in turn is related to the shear modulus. If one considers the medium to be purely elastic, its local shear modulus can be estimated by determining the local SW velocity. However, this assumption does not hold for many tissue types, whenever the shear viscosity plays an important role. In fact, there is increasing evidence that viscosity itself could be an important marker for malignancy [1]. In this work, we therefore aim at providing a joint local estimate of tissue elasticity and viscosity based on SW elastography.\u3c/p\u3

EFSUMB Young Investigator Award 2019

The winner at EUROSON 2019 of the Young Investigator 3000 euro prize was Rogier R Wildeboer, The Netherlands for the abstract entitled : 3 D Multiparametric Ultrasound for Prostate Cancer Diagnosi

Artificial intelligence in multiparametric prostate cancer imaging with focus on deep-learning methods

\u3cp\u3eProstate cancer represents today the most typical example of a pathology whose diagnosis requires multiparametric imaging, a strategy where multiple imaging techniques are combined to reach an acceptable diagnostic performance. However, the reviewing, weighing and coupling of multiple images not only places additional burden on the radiologist, it also complicates the reviewing process. Prostate cancer imaging has therefore been an important target for the development of computer-aided diagnostic (CAD) tools. In this survey, we discuss the advances in CAD for prostate cancer over the last decades with special attention to the deep-learning techniques that have been designed in the last few years. Moreover, we elaborate and compare the methods employed to deliver the CAD output to the operator for further medical decision making.\u3c/p\u3

3-D multi-parametric contrast-enhanced ultrasound for the prediction of prostate cancer

Trans-rectal ultrasound-guided 12-core systematic biopsy (SBx) is the standard diagnostic pathway for prostate cancer (PCa) because of a lack of sufficiently accurate imaging. Quantification of 3-D dynamic contrast-enhanced ultrasound (US) might open the way for a targeted procedure in which biopsies are directed at lesions suspicious on imaging. This work describes the expansion of contrast US dispersion imaging algorithms to 3-D and compares its performance against malignant and benign disease. Furthermore, we examined the feasibility of a multi-parametric approach to predict SBx-core outcomes using machine learning. An area under the receiver operating characteristic (ROC) curve of 0.76 and 0.81 was obtained for all PCa and significant PCa, respectively, an improvement over previous US methods. We found that prostatitis, in particular, was a source of false-positive readings

Three-dimensional histopathological reconstruction as a reliable ground truth for prostate cancer studies

To validate new imaging modalities for prostate cancer, images must be three-dimensionally correlated with the histological ground truth. In this work, an interpolation algorithm is described to construct a reliable three-dimensional reference from two-dimensional (2D) histological slices. Eight clinically relevant in silico phantoms were designed to represent difficult-to-reconstruct tumour structures. These phantoms were subjected to different slicing procedures. Additionally, controlled errors were added to investigate the impact of varying slicing distance, front-face orientation, and inter-slice misalignment on the reconstruction performance. Using a radial-basis-function interpolation algorithm, the 2D data were reconstructed in three dimensions. Our results demonstrate that slice thicknesses up to 4 mm can be used to reliably reconstruct tumours of clinically significant size; the surfaces lay within a 1.5 mm 90%-error margin from each other and the volume difference between the original and reconstructed tumour structures does not exceed 10%. With these settings, Dice coefficients above 0.85 are obtained. The presented interpolation algorithm is able to reconstruct clinically significant tumour structures from 2D histology slices. Errors occurring are in the order of magnitude of common registration artefacts. The method’s applicability to real histopathological data is also shown in two resected prostates. An inter-slice spacing of 4 mm or less is recommended during histopathology; the use of a 1.5 mm error margin along the tumour contours can then ensure reliable mapping of the ground truth

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

\u3cp\u3eSentinel 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.\u3c/p\u3

PT150 - 3D multiparametric contrast ultrasound predicts the histopathological outcome of systematic biopsy

Introduction & Objectives: A non-targeted 12-core systematic biopsy (SBx) procedure guided by transrectal ultrasound (TRUS) is currently guideline-recommended for prostate cancer (PCa) diagnosis. Despite the risk of complications, underdiagnosis, and overtreatment associated with SBx, until now image-based targeted biopsy has not proven sufficiently accurate to replace SBx. Three-dimensional (3D) dynamic contrastenhanced ultrasound (DCE-US) was recently introduced for prostate imaging, permitting to image the entire gland with a single bolus injection. Quantitative two-dimensional DCE-US has already shown promising for PCa localization. Here, we present a new method for PCa localization by multiparametric analysis of 3D DCE-US