Ultrasound localization microscopy to image and assess microvasculature in a rat kidney.

The recent development of ultrasound localization microscopy, where individual microbubbles (contrast agents) are detected and tracked within the vasculature, provides new opportunities for imaging the vasculature of entire organs with a spatial resolution below the diffraction limit. In stationary tissue, recent studies have demonstrated a theoretical resolution on the order of microns. In this work, single microbubbles were localized in vivo in a rat kidney using a dedicated high frame rate imaging sequence. Organ motion was tracked by assuming rigid motion (translation and rotation) and appropriate correction was applied. In contrast to previous work, coherence-based non-linear phase inversion processing was used to reject tissue echoes while maintaining echoes from very slowly moving microbubbles. Blood velocity in the small vessels was estimated by tracking microbubbles, demonstrating the potential of this technique to improve vascular characterization. Previous optical studies of microbubbles in vessels of approximately 20 microns have shown that expansion is constrained, suggesting that microbubble echoes would be difficult to detect in such regions. We therefore utilized the echoes from individual MBs as microscopic sensors of slow flow associated with such vessels and demonstrate that highly correlated, wideband echoes are detected from individual microbubbles in vessels with flow rates below 2 mm/s

An investigation of real time ultrasound Doppler techniques for tissue motion and deformation analysis

Cardiovascular disease accounts for more than 50% of all deaths in the Western world. Atherosclerosis is responsible for the vast majority of these diseases. There are a range of risk factors for atherosclerosis that affect the endothelial lining vessel wall cells to cause endothelial dysfunction, which then predisposes to a localized build-up of 'plaque' tissue that narrows the lumen of the arteries. Plaque rupture promotes localized vasospasm, thrombosis and embolism causing downstream tissue death, resulting in severe disability or death from, for instance, heart attack (in the coronary circulation) or stroke (in the cerebral circulation). Narrowing of the lumen and plaque rupture are associated with high tissue stresses and tissue under perfusion, which will alter local arterial and myocardial wall dynamics and elastic properties. Hence visualization of tissue dynamic and deformation property changes is crucial to detect atherosclerosis in the earliest stages to prevent acute events.The objective of this dissertation research is to develop new techniques based on Doppler ultrasound to investigate and visualize changes in tissue dynamic and deformation properties due to atherosclerosis in cardiac and vascular applications. A new technique, to correct for the Doppler angle dependence for tissue motion analysis has been developed. It is based on multiple ultrasound beams, and has been validated in vitro to study tissue dynamic properties. It can measure tissue velocity magnitude with low bias (5%) and standard deviation (10%), and tissue velocity orientation with a bias less than 5 degrees and a standard deviation below 5 degrees. A new Doppler based method, called strain rate, has also been developed and validated in vitro for the quantification of regional vessel or myocardial wall deformation. Strain rate is derived from the velocity information and can assess tissue deformation with an accuracy of 5% and a standard deviation less than 10%. Some examples of cardiac strain rate imaging have been gathered and are described in this thesis. Strain rate, as all Doppler based techniques, suffers from angle dependence limitation. A method to estimate one-component strain rate in any direction in the two-dimensional image not necessarily along the ultrasound beam has been developed. The method allows correcting for the strain rate bias along any user-defined direction. It is also shown that the full strain rate tensor can theoretically be extracted from the velocity vector field acquired by multiple beam tissue vector velocity technique. In vitro experiments have shown that qualitative two-component strain rate tensor can be derived. Two-component vector velocity from the moving tissue was acquired and two two-component strain rate images were derived. The images showed agreement with the expected deformation pattern

Exploiting Temporal Image Information in Minimally Invasive Surgery

Minimally invasive procedures rely on medical imaging instead of the surgeons direct vision. While preoperative images can be used for surgical planning and navigation, once the surgeon arrives at the target site real-time intraoperative imaging is needed. However, acquiring and interpreting these images can be challenging and much of the rich temporal information present in these images is not visible. The goal of this thesis is to improve image guidance for minimally invasive surgery in two main areas. First, by showing how high-quality ultrasound video can be obtained by integrating an ultrasound transducer directly into delivery devices for beating heart valve surgery. Secondly, by extracting hidden temporal information through video processing methods to help the surgeon localize important anatomical structures. Prototypes of delivery tools, with integrated ultrasound imaging, were developed for both transcatheter aortic valve implantation and mitral valve repair. These tools provided an on-site view that shows the tool-tissue interactions during valve repair. Additionally, augmented reality environments were used to add more anatomical context that aids in navigation and in interpreting the on-site video. Other procedures can be improved by extracting hidden temporal information from the intraoperative video. In ultrasound guided epidural injections, dural pulsation provides a cue in finding a clear trajectory to the epidural space. By processing the video using extended Kalman filtering, subtle pulsations were automatically detected and visualized in real-time. A statistical framework for analyzing periodicity was developed based on dynamic linear modelling. In addition to detecting dural pulsation in lumbar spine ultrasound, this approach was used to image tissue perfusion in natural video and generate ventilation maps from free-breathing magnetic resonance imaging. A second statistical method, based on spectral analysis of pixel intensity values, allowed blood flow to be detected directly from high-frequency B-mode ultrasound video. Finally, pulsatile cues in endoscopic video were enhanced through Eulerian video magnification to help localize critical vasculature. This approach shows particular promise in identifying the basilar artery in endoscopic third ventriculostomy and the prostatic artery in nerve-sparing prostatectomy. A real-time implementation was developed which processed full-resolution stereoscopic video on the da Vinci Surgical System

Assessing the performance of ultrafast vector flow imaging in the neonatal heart via multiphysics modeling and In vitro experiments

Ultrafast vector flow imaging would benefit newborn patients with congenital heart disorders, but still requires thorough validation before translation to clinical practice. This paper investigates 2-D speckle tracking (ST) of intraventricular blood flow in neonates when transmitting diverging waves at ultrafast frame rate. Computational and in vitro studies enabled us to quantify the performance and identify artifacts related to the flow and the imaging sequence. First, synthetic ultrasound images of a neonate's left ventricular flow pattern were obtained with the ultrasound simulator Field II by propagating point scatterers according to 3-D intraventricular flow fields obtained with computational fluid dynamics (CFD). Noncompounded diverging waves (opening angle of 60 degrees) were transmitted at a pulse repetition frequency of 9 kHz. ST of the B-mode data provided 2-D flow estimates at 180 Hz, which were compared with the CFD flow field. We demonstrated that the diastolic inflow jet showed a strong bias in the lateral velocity estimates at the edges of the jet, as confirmed by additional in vitro tests on a jet flow phantom. Furthermore, ST performance was highly dependent on the cardiac phase with low flows (< 5 cm/s), high spatial flow gradients, and out-of-plane flow as deteriorating factors. Despite the observed artifacts, a good overall performance of 2-D ST was obtained with a median magnitude underestimation and angular deviation of, respectively, 28% and 13.5 degrees during systole and 16% and 10.5 degrees during diastole

FPGA-Based Portable Ultrasound Scanning System with Automatic Kidney Detection

Bedsides diagnosis using portable ultrasound scanning (PUS) offering comfortable diagnosis with various clinical advantages, in general, ultrasound scanners suffer from a poor signal-to-noise ratio, and physicians who operate the device at point-of-care may not be adequately trained to perform high level diagnosis. Such scenarios can be eradicated by incorporating ambient intelligence in PUS. In this paper, we propose an architecture for a PUS system, whose abilities include automated kidney detection in real time. Automated kidney detection is performed by training the Viola–Jones algorithm with a good set of kidney data consisting of diversified shapes and sizes. It is observed that the kidney detection algorithm delivers very good performance in terms of detection accuracy. The proposed PUS with kidney detection algorithm is implemented on a single Xilinx Kintex-7 FPGA, integrated with a Raspberry Pi ARM processor running at 900 MHz