ULTRA-SR Challenge: Assessment of Ultrasound Localization and TRacking Algorithms for Super-Resolution Imaging.

With the widespread interest and uptake of super-resolution ultrasound (SRUS) through localization and tracking of microbubbles, also known as ultrasound localization microscopy (ULM), many localization and tracking algorithms have been developed. ULM can image many centimeters into tissue in-vivo and track microvascular flow non-invasively with sub-diffraction resolution. In a significant community effort, we organized a challenge, Ultrasound Localization and TRacking Algorithms for Super-Resolution (ULTRA-SR). The aims of this paper are threefold: to describe the challenge organization, data generation, and winning algorithms; to present the metrics and methods for evaluating challenge entrants; and to report results and findings of the evaluation. Realistic ultrasound datasets containing microvascular flow for different clinical ultrasound frequencies were simulated, using vascular flow physics, acoustic field simulation and nonlinear bubble dynamics simulation. Based on these datasets, 38 submissions from 24 research groups were evaluated against ground truth using an evaluation framework with six metrics, three for localization and three for tracking. In-vivo mouse brain and human lymph node data were also provided, and performance assessed by an expert panel. Winning algorithms are described and discussed. The publicly available data with ground truth and the defined metrics for both localization and tracking present a valuable resource for researchers to benchmark algorithms and software, identify optimized methods/software for their data, and provide insight into the current limits of the field. In conclusion, Ultra-SR challenge has provided benchmarking data and tools as well as direct comparison and insights for a number of the state-of-the art localization and tracking algorithms.

Development of artificial intelligence tools for invasive Doppler-based coronary microvascular assessment.

Aims: Coronary flow reserve (CFR) assessment has proven clinical utility, but Doppler-based methods are sensitive to noise and operator bias, limiting their clinical applicability. The objective of the study is to expand the adoption of invasive Doppler CFR, through the development of artificial intelligence (AI) algorithms to automatically quantify coronary Doppler quality and track flow velocity. Methods and results: A neural network was trained on images extracted from coronary Doppler flow recordings to score signal quality and derive values for coronary flow velocity and CFR. The outputs were independently validated against expert consensus. Artificial intelligence successfully quantified Doppler signal quality, with high agreement with expert consensus (Spearman's rho: 0.94), and within individual experts. Artificial intelligence automatically tracked flow velocity with superior numerical agreement against experts, when compared with the current console algorithm [AI flow vs. expert flow bias -1.68 cm/s, 95% confidence interval (CI) -2.13 to -1.23 cm/s, P < 0.001 with limits of agreement (LOA) -4.03 to 0.68 cm/s; console flow vs. expert flow bias -2.63 cm/s, 95% CI -3.74 to -1.52, P < 0.001, 95% LOA -8.45 to -3.19 cm/s]. Artificial intelligence yielded more precise CFR values [median absolute difference (MAD) against expert CFR: 4.0% for AI and 7.4% for console]. Artificial intelligence tracked lower-quality Doppler signals with lower variability (MAD against expert CFR 8.3% for AI and 16.7% for console). Conclusion: An AI-based system, trained by experts and independently validated, could assign a quality score to Doppler traces and derive coronary flow velocity and CFR. By making Doppler CFR more automated, precise, and operator-independent, AI could expand the clinical applicability of coronary microvascular assessment.

Non-invasive Assessment by B-Mode Ultrasound of Arterial Pulse Wave Intensity and Its Reduction During Ventricular Dysfunction.

Arterial pulse waves contain clinically useful information about cardiac performance, arterial stiffness and vessel tone. Here we describe a novel method for non-invasively assessing wave properties, based on measuring changes in blood flow velocity and arterial wall diameter during the cardiac cycle. Velocity and diameter were determined by tracking speckles in successive B-mode images acquired with an ultrafast scanner and plane-wave transmission. Blood speckle was separated from tissue by singular value decomposition and processed to correct biases in ultrasound imaging velocimetry. Results obtained in the rabbit aorta were compared with a conventional analysis based on blood velocity and pressure, employing measurements obtained with a clinical intra-arterial catheter system. This system had a poorer frequency response and greater lags but the pattern of net forward-traveling and backward-traveling waves was consistent between the two methods. Errors in wave speed were also similar in magnitude, and comparable reductions in wave intensity and delays in wave arrival were detected during ventricular dysfunction. The non-invasive method was applied to the carotid artery of a healthy human participant and gave a wave speed and patterns of wave intensity consistent with earlier measurements. The new system may have clinical utility in screening for heart failure.

Contrast Agent-Free Assessment of Blood Flow and Wall Shear Stress in the Rabbit Aorta using Ultrasound Image Velocimetry.

Blood flow velocity and wall shear stress (WSS) influence and are influenced by vascular disease. Their measurement is consequently useful in the laboratory and clinic. Contrast-enhanced ultrasound image velocimetry (UIV) can estimate them accurately but the need to inject contrast agents limits utility. Singular value decomposition and high-frame-rate imaging may render contrast agents dispensable. Here we determined whether contrast agent-free UIV can measure flow and WSS. In simulation, accurate measurements were achieved with a signal-to-noise ratio of 13.5 dB or higher. Signal intensity in the rabbit aorta increased monotonically with mechanical index; it was lowest during stagnant flow and uneven across the vessel. In vivo measurements with contrast-free and contrast-enhanced UIV differed by 4.4% and 1.9% for velocity magnitude and angle and by 9.47% for WSS. Bland-Altman analysis of waveforms revealed good agreement between contrast-free and contrast-enhanced UIV. In five rabbits, the root-mean-square errors were as low as 0.022 m/s (0.81%) and 0.11 Pa (1.7%). This study indicates that with an optimised protocol, UIV can assess flow and WSS without contrast agents. Unlike contrast-enhanced UIV, contrast-free UIV could be routinely employed.

Clinical quantitative cardiac imaging for the assessment of myocardial ischaemia.

Cardiac imaging has a pivotal role in the prevention, diagnosis and treatment of ischaemic heart disease. SPECT is most commonly used for clinical myocardial perfusion imaging, whereas PET is the clinical reference standard for the quantification of myocardial perfusion. MRI does not involve exposure to ionizing radiation, similar to echocardiography, which can be performed at the bedside. CT perfusion imaging is not frequently used but CT offers coronary angiography data, and invasive catheter-based methods can measure coronary flow and pressure. Technical improvements to the quantification of pathophysiological parameters of myocardial ischaemia can be achieved. Clinical consensus recommendations on the appropriateness of each technique were derived following a European quantitative cardiac imaging meeting and using a real-time Delphi process. SPECT using new detectors allows the quantification of myocardial blood flow and is now also suited to patients with a high BMI. PET is well suited to patients with multivessel disease to confirm or exclude balanced ischaemia. MRI allows the evaluation of patients with complex disease who would benefit from imaging of function and fibrosis in addition to perfusion. Echocardiography remains the preferred technique for assessing ischaemia in bedside situations, whereas CT has the greatest value for combined quantification of stenosis and characterization of atherosclerosis in relation to myocardial ischaemia. In patients with a high probability of needing invasive treatment, invasive coronary flow and pressure measurement is well suited to guide treatment decisions. In this Consensus Statement, we summarize the strengths and weaknesses as well as the future technological potential of each imaging modality.