A statistical model in detecting small blood vessels with Power Doppler Imaging

Department of Medical Biophysics07/04/10

OutlineIntroductionObjectiveMethods

◦ Power Doppler Imaging◦ Example

Methods◦ Mathematical Model

ResultsDiscussionConclusionAcknowledgements

IntroductionAngiogenesisCancer research Imaging these small blood

vessels can provide valuable information to their spatial distribution in the vasculature

ObjectiveTo improve the statistical model

in determining the blood flow in a small vessel

Develop another Gaussian distribution to account for the region that lies between the background and vessel

Methods and Apparatus

Power Doppler Imaging

Example

MethodsFlow phantoms were developed

with the following properties;◦vessel sizes:

160, 200, 250, 300, 360 µm

◦ flow velocity 4, 3, 2, 1, 0.5 mm/s

◦transducer frequency 30 and 40 MHz

Mathematical Model

Single Vessel

Multiple Vessel

Results

Results

Consideration of the extra region lead to the statistical model, more closely reflecting the actual data

DiscussionConsideration of an extra region

lead to the increase in accuracy between the statistical model and empirical data

Changes made are reflected by the considering a greater range of data

The standard statistical model for a specific vessel size can act to determine the actual vessel as opposed to the background

Further Research and ImplicationsWorking with multiple layer

tissueDeveloping a standard model but

taking into consideration the vessel sizes

Differentiation between vessels in tortuous vessels

ConclusionAddition of a new region to the

statistical model led to results which reflected the empirical data much closer

AcknowledgementsDr. James Lacefield PhDMai Elfarnawany Masters

Candidate

Questions and/or Comments?