Super-Resolution Contrast-Enhanced Ultrasound Methodology for the Identification of In Vivo Vascular Dynamics in 2D

Abstract

Objectives The aim of this study was to provide an ultrasound-based super-resolution methodology that can be implemented using clinical 2-dimensional ultrasound equipment and standard contrast-enhanced ultrasound modes. In addition, the aim is to achieve this for true-to-life patient imaging conditions, including realistic examination times of a few minutes and adequate image penetration depths that can be used to scan entire organs without sacrificing current super-resolution ultrasound imaging performance. Methods Standard contrast-enhanced ultrasound was used along with bolus or infusion injections of SonoVue (Bracco, Geneva, Switzerland) microbubble (MB) suspensions. An image analysis methodology, translated from light microscopy algorithms, was developed for use with ultrasound contrast imaging video data. New features that are tailored for ultrasound contrast image data were developed for MB detection and segmentation, so that the algorithm can deal with single and overlapping MBs. The method was tested initially on synthetic data, then with a simple microvessel phantom, and then with in vivo ultrasound contrast video loops from sheep ovaries. Tracks detailing the vascular structure and corresponding velocity map of the sheep ovary were reconstructed. Images acquired from light microscopy, optical projection tomography, and optical coherence tomography were compared with the vasculature network that was revealed in the ultrasound contrast data. The final method was applied to clinical prostate data as a proof of principle. Results Features of the ovary identified in optical modalities mentioned previously were also identified in the ultrasound super-resolution density maps. Follicular areas, follicle wall, vessel diameter, and tissue dimensions were very similar. An approximately 8.5-fold resolution gain was demonstrated in vessel width, as vessels of width down to 60 μm were detected and verified (λ = 514 μm). Best agreement was found between ultrasound measurements and optical coherence tomography with 10% difference in the measured vessel widths, whereas ex vivo microscopy measurements were significantly lower by 43% on average. The results were mostly achieved using video loops of under 2-minute duration that included respiratory motion. A feasibility study on a human prostate showed good agreement between density and velocity ultrasound maps with the histological evaluation of the location of a tumor. Conclusions The feasibility of a 2-dimensional contrast-enhanced ultrasound-based super-resolution method was demonstrated using in vitro, synthetic and in vivo animal data. The method reduces the examination times to a few minutes using state-of-the-art ultrasound equipment and can provide super-resolution maps for an entire prostate with similar resolution to that achieved in other studies.

Three-Dimensional Super-Resolution Imaging Using a Row–Column Array

“…The acquisition time was between 1 and 10 minutes for a 2-D image, with 1 minute giving an overall rough view of the vasculature and 10 minutes giving precise quantitative data for the blood flow. We predict that the same scan times can be kept with the method presented here for a full volume, and maybe with a shorter time when employing more advanced SRI [36][37][38].…”

“…The acquisition length could be reduced, if more detections could be made per second. Methods for increasing the number of bubble detections have been the topic of a number of articles [36][37][38]. Such approaches can also be employed here, as full RF data are acquired and can be processed using more advanced schemes.…”

Super-resolution Ultrasound Imaging

“…These methods can be performed at both conventional clinical imaging frame rates (100 Hz 2016; Harput et al 2018;Opacic et al 2018;Kanoulas et al 2019) and higher frame rates using plane-wave imaging (>100 Hz) (Errico et al 2015;Christensen-Jeffries et al 2017b).…”

Improved microbubble (MB) Localisation Using Particle Detecting algorithm: Evaluation of Algorithm Performance for Different Beamforming Methods

“…(particle detection) on contrast enhanced ultrasound (CEUS) images could be enhanced in combination with the use of the right beamformer (BF). The current study investigates the best performing combination of a particle detecting algorithm (Kanoulas et al 2019) with four beamformers (BFs), classical and adaptive. In a series of in silico experiments, adjacent MBs are placed in distances comparable to the lateral resolution limit, the CEUS images of the MBs were simulated in FieldII, and finally beamformed with the four methods.…”

“…Keywords-medical, beamforming, resolution, imageprocessing, microbubble tracking I. INTRODUCTION CEUS images can be processed with the particle detecting algorithm based on Kanoulas et al 2019 [1] that provides an estimation of microbubble (MB) position and allows the identification of sub-resolution vessel structures in the image. The input image data quality affects both the accuracy of detection and localisation which in turn will affect the vessel mapping.…”