Dynamic Contrast Enhanced Dynamic Contrast Enhanced Imaging and its applicationsImaging and its applications

Image Retreat June-05Image Retreat June-05-Ramtilak Gattu-Ramtilak Gattu

ImagesImages

Dynamic Flip Angle 5 Flip Angle 13

Subtracted T1 Roi Image

Flowchart & EquationsFlowchart & Equations

t2

IAUC = ∫ c (t) dt t1

IAUC Graph CIAUC Graph

IAUC – Integrated Area Under the CurveCIAUC – Cumulative Area Under the Curve

Iauc graph comaprisions for all the dated studies with fixed T1(0)=1000 msec

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Iauc in mMol-sec

% #

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pix

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Tumor for fixed T1(0) on 11-15-04

Tumor for fixed T1(0) on 11-09-04

Ciauc graph comaprisions for all the dated studies with fixed T1(0)=1000 msec

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0 2 4 6 8 10

CIauc in mMol-sec

% #

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Tumor for fixed T1(0) on 11-15-04

Tumor for fixed T1(0) on 11-09-04

Flowchart & EquationsFlowchart & Equations

t2

IAUC = ∫ c (t) dt t1

IAUC Graph CIAUC Graph

IAUC – Integrated Area Under the CurveCIAUC – Cumulative Area Under the Curve

Iauc graph comaprisions for all the dated studies with fixed T1(0)=1000 msec

0

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0 0.5 1 1.5 2

Iauc in mMol-sec

% #

of

pix

els

MUscle for fixed T1(0) on11-09-04

MUscle for fixed T1(0) on11-15-04

Ciauc graph comaprisions for all the dated studies with fixed T1(0)=1000 msec

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20

40

60

80

100

120

0 0.5 1 1.5 2 2.5 3

CIauc in mMol-sec

% #

of

pix

els

MUscle for fixed T1(0) on11-09-04

MUscle for fixed T1(0) on11-15-04

Tumor Average 11-09-04

Tumor Average 11-15-04

R1=(Tumor Average 11-09-04-Tumor Average 11-15-04)/Tumor Average 11-09-04.

CIauc 50% 1.9 0.98 0.97

Muscle1 Average 11-09-04

Muscle1Average 11-15-04

R1=(Muscle1 Average 11-09-04-Muscle1 Average 11-15-04)/Muscle1 Average 11-09-04

CIauc 50% 0.23 0.21 0.02

Normalization TableNormalization Table

Volume TableVolume TableStudy

ROI LabelPixels

11-09-04Volume ml

11-09-04Pixels

11-15-04Volume ml 11-15-04

"Tumor" 7146 279.141 6778 264.766

"Muscle1" 827 32.3047 751 29.3359

Future DirectionsFuture Directions Studying the statistical variations in the error introduced by

wrong T1(0) values. Minimizing the errors and obtaining consistency results from

every slice in spite of the noise in each slice for every individual Roi.

Pharmaco-kinetic models and parameter estimation (or model fitting) should be introduced to find the most probable values for physiological parameters based

on MRI data . Comparison of semi quantitative analysis with the kinetic

parameters and studying the reproducibility techniques for consistent and accurate results and validations in DCE-MRI.

-Thank you-Thank you