Dataset Information

Ultrafast Imaging using Spectral Resonance Modulation.

ABSTRACT: CCD cameras are ubiquitous in research labs, industry, and hospitals for a huge variety of applications, but there are many dynamic processes in nature that unfold too quickly to be captured. Although tradeoffs can be made between exposure time, sensitivity, and area of interest, ultimately the speed limit of a CCD camera is constrained by the electronic readout rate of the sensors. One potential way to improve the imaging speed is with compressive sensing (CS), a technique that allows for a reduction in the number of measurements needed to record an image. However, most CS imaging methods require spatial light modulators (SLMs), which are subject to mechanical speed limitations. Here, we demonstrate an etalon array based SLM without any moving elements that is unconstrained by either mechanical or electronic speed limitations. This novel spectral resonance modulator (SRM) shows great potential in an ultrafast compressive single pixel camera.

SUBMITTER: Huang E

PROVIDER: S-EPMC4848519 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Ultrafast Imaging using Spectral Resonance Modulation.

Huang Eric E Ma Qian Q Liu Zhaowei Z

Scientific reports 20160428

CCD cameras are ubiquitous in research labs, industry, and hospitals for a huge variety of applications, but there are many dynamic processes in nature that unfold too quickly to be captured. Although tradeoffs can be made between exposure time, sensitivity, and area of interest, ultimately the speed limit of a CCD camera is constrained by the electronic readout rate of the sensors. One potential way to improve the imaging speed is with compressive sensing (CS), a technique that allows for a red ...[more]

PMID: 27122101

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Project description:PurposeTo explore, at a high field strength of 7T, the performance of various fat spectral models on the quantification of triglyceride composition and proton density fat fraction (PDFF) using chemical-shift encoded MRI (CSE-MRI).MethodsMR data was acquired from CSE-MRI experiments for various fatty materials, including oil and butter samples and in vivo brown and white adipose mouse tissues. Triglyceride composition and PDFF were estimated using various a priori 6- or 9-peak fat spectral models. To serve as references, NMR spectroscopy experiments were conducted to obtain material specific fat spectral models and triglyceride composition estimates for the same fatty materials. Results obtained using the spectroscopy derived material specific models were compared to results obtained using various published fat spectral models.ResultsUsing a 6-peak fat spectral model to quantify triglyceride composition may lead to large biases at high field strengths. When using a 9-peak model, triglyceride composition estimations vary greatly depending on the relative amplitudes of the chosen a priori spectral model, while PDFF estimations show small variations across spectral models. Material specific spectroscopy derived spectral models produce estimations that better correlate with NMR spectroscopy estimations in comparison to those obtained using non-material specific models.ConclusionAt a high field strength of 7T, a material specific 9-peak fat spectral model, opposed to a widely accepted or generic human liver model, is necessary to accurately quantify triglyceride composition when using CSE-MRI estimation methods that assume the spectral model to be known as a priori information. CSE-MRI allows for the quantification of the spatial distribution of triglyceride composition for certain in vivo applications. Additionally, PDFF quantification is shown to be independent of the chosen a priori spectral model, which agrees with previously reported results obtained at lower field strengths (e.g. 3T).

Project description:ObjectivesThe aim of this study was to investigate the potential of coronary ultrafast Doppler angiography (CUDA), a novel vascular imaging technique based on ultrafast ultrasound, to image noninvasively with high sensitivity the intramyocardial coronary vasculature and quantify the coronary blood flow dynamics.BackgroundNoninvasive coronary imaging techniques are currently limited to the observation of the epicardial coronary arteries. However, many studies have highlighted the importance of the coronary microcirculation and microvascular disease.MethodsCUDA was performed in vivo in open-chest procedures in 9 swine. Ultrafast plane-wave imaging at 2,000 frames/s was combined to an adaptive spatiotemporal filtering to achieve ultrahigh-sensitive imaging of the coronary blood flows. Quantification of the flow change was performed during hyperemia after a 30-s left anterior descending (LAD) artery occlusion followed by reperfusion and was compared to gold standard measurements provided by a flowmeter probe placed at a proximal location on the LAD (n = 5). Coronary flow reserve was assessed during intravenous perfusion of adenosine. Vascular damages were evaluated during a second set of experiments in which the LAD was occluded for 90 min, followed by 150 min of reperfusion to induce myocardial infarction (n = 3). Finally, the transthoracic feasibility of CUDA was assessed on 2 adult and 2 pediatric volunteers.ResultsUltrahigh-sensitive cine loops of venous and arterial intramyocardial blood flows were obtained within 1 cardiac cycle. Quantification of the coronary flow changes during hyperemia was in good agreement with gold standard measurements (r2 = 0.89), as well as the assessment of coronary flow reserve (2.35 ± 0.65 vs. 2.28 ± 0.84; p = NS). On the infarcted animals, CUDA images revealed the presence of strong hyperemia and the appearance of abnormal coronary vessel structures in the reperfused LAD territory. Finally, the feasibility of transthoracic coronary vasculature imaging was shown on 4 human volunteers.ConclusionsUltrafast Doppler imaging can map the coronary vasculature with high sensitivity and quantify intramural coronary blood flow changes.

Dataset Information

Ultrafast Imaging using Spectral Resonance Modulation.

Publications

Ultrafast Imaging using Spectral Resonance Modulation.

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