abstract: characterization of coronary artery’s motion is important to obtain optimal coronary ct...

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Abstract: Abstract: Characterization of coronary artery’s motion is important to obtain optimal coronary CT images. Previous studies have mainly performed 2D analysis. The objectives of this study were to investigate each coronary artery’s velocity by analysis of three different methods (Registration, Junction and Curvature) in order to obtain a typical time dependent coronary‘s velocity graph. Based on previous studies the velocity minima were expected approximately in phases 40% (end systole) and 75% (mid diastole) of the cardiac cycle. Our initial work achieved best results by the registration method and we have encountered problems with the curvature method. Introduction Introduction : : The coronary arteries surround our heart and provide it with blood. Therefore there is major importance to diagnose disorders in these arteries. MDCT provides true 3D non-invasive imaging of the artery's cavity and it‘s walls. Heart imaging requires high temporal resolution to reduce motion artifacts and high spatial resolution to detect pathology (atherosclerosis) in the relatively narrow coronary arteries (<4mm diameter). To minimize motion artifacts, scanning is usually executed in a very short time interval in mid-diastole, when heart activity is minimal, however exact locations of motion minima vary according to heart rate and coronary artery. Objectives Objectives : : 1. Investigation of coronary artery’s velocity using three different analysis methods. 2. Obtaining typical time and geometry dependent Feature, movement and velocity of coronary arteries during the cardiac Feature, movement and velocity of coronary arteries during the cardiac cycle cycle Dr. Jonathan Lessick, MD DSC, Philips Healthcare Maya Baranes, Shiran Levi, Yasmin Noonoo, Tel Aviv Uni., Bio-medical engineering department Methods Methods : An R-R interval of a heart beat was divided into 20 phases (of 5%). The location on the arteries' centerlines were acquired in a semi automatic method using Philips' CT workstation. Two assumptions were made: 1. The origin of each artery, its branch-points (junctions) and local curvature maxima represent tissue fiducial points which may be used as a basis for calculating local velocities. 2. Based on these markers each artery can be subdivided into subsegments of constant length throughout all heart phases. Prior to data analysis, the centerlines were improved using registration by MSE and by the location of the junction points. The velocities were obtained using three different methods: Registration – The average Euclidian distance between points on the artery in two adjacent phases was used to obtain the velocity by dividing it by the duration of the phase (5%). Junctions – The location of the junction point between two arteries was found in two consecutive phases by an automatic algorithm. Results were visually confirmed to ensure conformity of results (regulation). The velocity of the junction was calculated from the Euclidian distance between the junctions in two consecutive phases. The velocity of a segment around the junction was calculated as well. Curvature - The curve of each point of the artery respective to its neighborhood was found by: Then points of local max curvature in every artery were found using empirical thresholds. The Euclidian distance between max curve points in two consecutive phases was divided by the duration of the phase (5%) to calculate the point's velocity. The results were tested by: visual and clinical matching, graph’s continuousness and agreement with the theory. Results Results : Junction - Junction - registration registration r v t r v t Conclusions : Preliminary analysis shows best results obtained while using the registration method. There is a problem with the curvature method which may require adaptations to the algoritm. Error factors: Quantity of the data. Quality of the data. Decision threshold. Unfixable data. 1 2 1 2 sin (,) arcsin( ) tt t t dist Mean velocity of the LAD Mean velocity of 3 segments of the LAD: First (blue), middle (red) and last (green) r v t r v t Results - Junctions Results - Junctions Results – Curvature Results – Curvature Self regulation velociti es Junction’s location in all phases: LAD and D2 Junction’s index in all phases: LAD and LCX LAD (blue) and D1 (red) by segment around the junction LAD and D1 junction’s velocity Max curvature point for RCA phase 0 Velocity of max curvature - RCA Phase [%] Velocity [mm/%] X [mm] y [mm] z [mm]

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Page 1: Abstract: Characterization of coronary artery’s motion is important to obtain optimal coronary CT images. Previous studies have mainly performed 2D analysis

Abstract:Abstract:Characterization of coronary artery’s motion is important to obtain

optimal coronary CT images. Previous studies have mainly performed 2D analysis. The objectives of this study were to investigate each coronary artery’s velocity by analysis of three different methods (Registration, Junction and Curvature) in order to obtain a typical time dependent coronary‘s velocity graph. Based on previous studies the velocity minima were expected approximately in phases 40% (end systole) and 75% (mid diastole) of the cardiac cycle.

Our initial work achieved best results by the registration method and we have encountered problems with the curvature method.

IntroductionIntroduction::The coronary arteries surround our heart and provide it with blood.

Therefore there is major importance to diagnose disorders in these arteries. MDCT provides true 3D non-invasive imaging of the artery's cavity and it‘s walls. Heart imaging requires high temporal resolution to reduce motion artifacts and high spatial resolution to detect pathology (atherosclerosis) in the relatively narrow coronary arteries (<4mm diameter). To minimize motion artifacts, scanning is usually executed in a very short time interval in mid-diastole, when heart activity is minimal, however exact locations of motion minima vary according to heart rate and coronary artery.

ObjectivesObjectives::1. Investigation of coronary artery’s velocity using three different

analysis methods.2. Obtaining typical time and geometry dependent velocity curves per

coronary artery.

HypothesisHypothesis::• The minimum velocity is expected in phases 40% (end systole) and

75% (mid diastole) of the cardiac cycle.• The optimal method will fit the geometric structure of every artery.

Feature, movement and velocity of coronary arteries during the cardiac cycleFeature, movement and velocity of coronary arteries during the cardiac cycleDr. Jonathan Lessick, MD DSC, Philips Healthcare

Maya Baranes, Shiran Levi, Yasmin Noonoo, Tel Aviv Uni., Bio-medical engineering department

MethodsMethods: An R-R interval of a heart beat was divided into 20 phases (of

5%). The location on the arteries' centerlines were acquired in a semi automatic method using Philips' CT workstation.

Two assumptions were made: 1. The origin of each artery, its branch-points (junctions) and local

curvature maxima represent tissue fiducial points which may be used as a basis for calculating local velocities.

2. Based on these markers each artery can be subdivided into subsegments of constant length throughout all heart phases.

Prior to data analysis, the centerlines were improved using

registration by MSE and by the location of the junction points.The velocities were obtained using three different methods:

Registration – The average Euclidian distance between points on the artery in two adjacent phases was used to obtain the velocity by dividing it by the duration of the phase (5%).

Junctions – The location of the junction point between two arteries was found in two consecutive phases by an automatic algorithm. Results were visually confirmed to ensure conformity of results (regulation). The velocity of the junction was calculated from the Euclidian distance between the junctions in two consecutive phases. The velocity of a segment around the junction was calculated as well.

Curvature - The curve of each point of the artery respective to its neighborhood was found by:

Then points of local max curvature in every artery were found using empirical thresholds. The Euclidian distance between max curve points in two consecutive phases was divided by the duration of the phase (5%) to calculate the point's velocity.

The results were tested by: visual and clinical matching, graph’s continuousness and agreement with the theory.

ResultsResults: Junction - registrationJunction - registration

rv

t

r

vt

Conclusions:Preliminary analysis shows best results obtained while using the registration method.There is a problem with the curvature method which may require adaptations to the algoritm.

Error factors:Quantity of the data.Quality of the data.Decision threshold. Unfixable data.

1 2

1 2

sin ( , )arcsin( )

t tt t

dist

Mean velocity of the LADMean velocity of 3 segments of the LAD: First (blue), middle (red) and last (green)

rv

t

r

vt

Results - JunctionsResults - Junctions

Results – CurvatureResults – Curvature

Self regulation

velocities

Junction’s location in all phases: LAD and D2

Junction’s index in all phases: LAD and LCX

LAD (blue) and D1 (red) by segment around the junction LAD and D1 junction’s velocity

Max curvature point for RCA phase 0 Velocity of max curvature - RCA

Phase [%]

Vel

ocity

[mm

/%]

X [mm]y [mm]

z [m

m]