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University of California
Radiological Sciences Dept.

Medical Science I B140
Irvine, CA 92697-5000

 
Imaging Physics Laboratory

 

 

threeHearts

 

 

Welcome to the Molloi Group at the University of California, Irvine.

 

 

Angiographic Fractional Flow Reserve

       

        Limitations in the visual assessment of intermediate severity stenoses by coronary angiography are known to suffer from intra- and inter-observer variability as well as discordance with their true physiologic importance [1-6].  Previous studies have performed functional analyses of stenoses using acquired images to predict pressure gradients [7-9], to estimate coronary flow reserve [10-12], to assess coronary flow through Thrombolysis in Myocardial Infarction (TIMI) frame count [13-15], and to assess functional improvement after coronary intervention [16, 17].  An important index not already estimated from coronary angiography is fractional flow reserve (FFR).  Pressure-based fractional flow reserve (FFR) has proven to aid the cardiologist in evaluating the flow-limiting potential of stenoses as well as the therapeutic gain of angioplasties [18, 19].  

        FFR quantifies the reduction in maximum coronary blood flow from a theoretical maximum normal flow in the presence of a stenosis.  How can FFR be determined if the maximum normal flow is unknown?  The pressure-based approach has elegantly circumvented the need to know the theoretical maximum normal flow by approximately FFR as a ratio of diseased perfusion pressure over the maximum inflow pressure from the aorta.  However, a limitation to the current pressure-based FFR method is the need to insert a pressure wire (0.014”) into distal parts of coronary arteries.

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Dual Energy Imaging

      

In x-ray imaging, pixel values represent effective attenuation measurements of an object in the beam and can be expressed by the following equation: 

N = N0e-ut

Where N is the number of detected photons, N0 is the number of photons incident on the object, u is the attenuation coefficient and is material specific and a function of energy,  tis the object thickness. When imaging two distinct materials, the equation becomes: 

N = N0e-(ujtj+uata)

Only in limited situations with specific a priori knowledge can information about the thickness of both materials be discerned from a single measurement. 

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