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High-probability grants
According to our matching algorithm, Yueh Z. Lee is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2020 |
Lee, Yueh Z |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Stationary Digital Tomosynthesis For Transbronchial Biopsy Guidance @ Univ of North Carolina Chapel Hill
ABSTRACT The recent expansion of lung cancer screening programs in the United States has led to a significant increase in the number of lung lesions requiring sampling to evaluate their malignancy status. Bronchoscopic based peripheral lung biopsy offers the lowest rate of procedural complication. However, diagnostic yields have remained moderate, primarily due to the lack of high resolution, real-time imaging guidance. Techniques such as endobronchial ultrasound and electromagnetic navigational bronchoscopy offer some guidance for the interventionalist, but remain limited for the necessary fine localization of the biopsy needle tip and lesion just prior to sampling. Standard CT based imaging approaches are too expensive and cumbersome for intra- procedural use. We have developed a stationary digital chest tomosynthesis imaging approach based on the linear x-ray array based on the carbon nanotube field emission sources. Our approach offers the potential for rapid, high resolution in-plane imaging combined with low-dose stereoscopic imaging, all without the need for any physical motion of the x-ray source or detector. We seek to refine our stationary chest tomosynthesis system, evaluate rapid CT to tomosynthesis image registration techniques and integrate the software control and guidance system in a system for pre-clinical large animal evaluation. Our academic-industrial partnership will incorporate a team of physicists, computer scientists, radiologists and interventional pulmonologists to develop this system.
|
0.988 |
2021 |
Lee, Yueh Z |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Arterial Input Function Independent Measures of Perfusion With Physics Driven Models @ Univ of North Carolina Chapel Hill
ABSTRACT Acute Ischemic Stroke (AIS) affects approximately 700,000 patients each year in the United States. [Benjamin EJ 2019, Circulation] Though the introduction of intravenous thrombolytics improved patient outcomes, the development of effective treatment regimens with mechanical thrombectomy has significantly altered the clinical management of AIS patients, especially when appropriate patients are selected for intervention. The current treatment selection approaches utilize patient specific data heavily relies on quantitative neuroimaging approaches, derived from either Computer Tomography (CT), or to a lesser extent magnetic resonance imaging (MRI). CT, with its relative availability within the US, has been the primary modality used for stroke patient triage. Brain perfusion imaging has been central to the evaluation of the ischemic penumbra and infarct core enabling precision in patient selection for intra-arterial thrombolysis. Typically dynamic CT perfusion scans with repeated scans 40 to 60 time points with the administration of iodinated contrast are obtained upon the arrival in the emergency room. These images are automatically or semi-automatically post-processed into perfusion metrics, using a number of FDA approved software packages. These packages all essentially rely on a similar post-processing pathway for the dynamically acquired images, consisting of motion correction, arterial input function selection and some form of deconvolution post-processing. A set of perfusion maps are generated, typically including cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT) and time to the maximum contrast concentration (Tmax). The software packages then apply thresholds to the CBF and Tmax maps to generate a presumed ischemic ?core? from the CBF and ?penumbra? from the Tmax. However, the dependence of these values on the arterial input function (AIF) selected has resulted in extensive efforts to automate AIF selection, or explore systematic methods to produce local AIFs to improve perfusion measurements. Defining a perfusion metric that is independent of AIF selection could substantially improve stroke perfusion analysis, and reduce patient radiation exposure. The goal of this study is to evaluate a physics based model of cerebral perfusion for evaluating perfusion parameters from CT perfusion modalities. The critical requirements of the new technique include independence from AIF selection, quantitative and stable measurements of perfusion that are clinically relevant and predictive of stroke outcomes.
|
0.988 |