Simulation Program of Specifying Ischemic Stroke

Signal Processing Medical Signal Processing & Medical Imaging Paper 101531

Simulation Program of Specifying Ischemic Stroke Area from CT Perfusion images Based on Digital Image Processing Techniques 2 l l S. Fueanggan , S. Chokchaitam , and S. Muengtaweepongsa I

Department of Electrical and Computer Engineering, Thammasat University, Thailand. 2 Division of Neurology, Thammasat University, Thailand.

Abstract- This research paper presents a new designed program to initially analyze Ischemic Stroke Area from Computed Tomography Perfusion (CTP) based on Digital Image Processing Techniques. The MATLAB program is applied to develop the designed software to analyze the Ischemic Stroke Area. The new designed software can specify Ischemic Stroke Area by assigning Threshold level of CTP from CBV (Cerebral Blood Volume) , CBF (Cerebral Blood Flow) and MTT (Mean Transit Time) images. Our experimental results will be shown in N-Match (normal tissue areas),D-Match (dead tissue areas ), Mismatch (blood cot tissue areas) and Undefined area. Then, separate the brain into left and right to specify Ischemic Stroke Area. As a result of experiment in 5 Stroke patients sample by setting CBV Threshold level to 2.5 ml/lOOg (±1.5) , CBF Threshold level to 20 ml/lOOg/min (±1O) and MTT Threshold level to 7.5 sec (±4.5) , the distribution of N-Match, D-Match, Mismatch and Undefined depends on their threshold. So, it is possible to sort elementary information of left and right side of the brain to specify Ischemic Stroke Area in order to compare the results with brain specialists.

I.

C

that studied to find Ischemic Stroke Area and lead to a program that help doctors to analyze by finding Mismatch from CBV and CBF images.[5] The idea of this research is to design a program to analyze Ischemic Stroke Area, comparing image data from CT scanned images of CBV, CBF and MTT which were collected from CT Perfusion, which rely on the relationship of all three scattered data to identify Ischemic Stroke Area based on data gathered from Mismatch of CBV, CBF images and calculate the Threshold of MTT for preliminary data analysis for the doctors which is easy to use and at cheap price, also to reduce the time for doctor to analyze the case and increase the accuracy of analysis for effective treatment. II. PROCEDURE AND RELATED THEORIES A. Medical principle in CT Scan diagnosis

CTP is a blood brain status checking method after the injection of contrast media, which is expected to be clogged by checking average time of blood in brain at the point that needed to be considered. Afterward, apply the information

INTRODUCTION

to create images and show CBV , CBF and MTT in order

erebrovascular Disease : Stroke is a frequently found

to specify Ischemic Stroke Area, so the doctor could have a

disease

treatment on time.

and

becoming

a

public

health

issue

in

Thailand. According to Public Health Statistics (A.D.

2005), Stroke is in the top three of Thai people cause of death

and

like

to

rise.[l]

In

correspond

with

joint

educational research between Ministry of Public Health and WHO (World Health Organization), Stroke comes first in cause of death in female and second in male.[2] It is also the main reason of Disability Adjusted Life Year in both male and female.[3] At present, there is shortage of personnel to provide sufficient service for treatment of brain and nerve. There's also a large number of patients compared to doctors, so the doctor may made fault analysis from color value from CT-Scan images with similar color scale. Therefore, if there are tools that help to analyze Ischemic Stroke Area images from CT-Scan, it will help doctors to get more correct results. Diagnosis:

CT Scan will assist doctor to diagnose

Patient's status by comparing variable images, such as CBV images. CBF images, MTT images, TTP images and to specify Ischemic Stroke Area on the CT Scan images, doctor normally consider CBV images and CBF images then find the location of mismatch.[4] There are research

The 8th Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI) Association of Thailand - Conference 2011

(b)

(c)

Fig. 1. CT scan of brain which is replaced by color after CTP.

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Signal Processing Medical Signal Processing & Medical Imaging

From Fig. l(a) CBV image is the amount of blood per CBV

unit of brain tissue. Comparison of images is done by setting Threshold value, if any area has color value lower

t

than prescribed, will be considered as less value area. And if any area has color value than prescribed,

will be

CBV more than TH

considered as much value area.

MISMATCH • • •

+

From Fig. l(b) CBF image is the amount of blood flow

MTT

•

T�.�--------�------�

per unit of brain tissue per minute. In comparison by setting

t +

Threshold value, if any area has color value lower than prescribed, will be considered as less value area. And if any

UNDEFINED

CBV less than TH

area has color value than prescribed, will be considered as much value area as for CBV images. From Fig. I(c) MTT image was defined as the time

® �Th"

..

difference between the arterial inflow and venous outflow.

CRF less than TH

F

CRF

�

CRF more than TH

The MTT image was calculated from CBV (Cerebral Blood

Fig.2. The distribution of data which is divided into six parts gathered from

Volume) per CBF (Cerebral Blood Flow) which will be

configuring Threshold time ofMTT by comparing CBV and CBF images.

shown in equation 1.

The distribution of data in Fig.2 by comparing the Threshold value of CBV, CBF and MTT could be found in

CBV MIT =-CBF

(1)

Table I. TABLE I

If the average time value shown in MTT image is high, it means that the blood volume compared to blood flow is high. That means there is possibility of Ischemic Stroke Area. And if the average time value shown in MTT image is low, it means the blood value compared to blood flow is low, which results in good blood circulation and may not be Ischemic Stroke. In Threshold value assignment, the area with color value is lower than prescribed, will be regarded as high value are, and the area with color value is higher than prescribed, will be regarded as low value area.

INDICATION OF DISTRIBUTION DATA BY COMPARISON OF THRESHOLD VALUE OF CBV AND CBF WITHMTT IMAGES (UNDEFINED) Threshold (D-Match) (Mismatch) (N-Match) Min Min Max Max CBV Min Min Max Max CBF Max+Min Max+Min Min Max MTT 2+3 4+5 1 6 Area

Table 1 indicates the relationship of scattering data gathered from CBV, CBF and MTT images, and those area are

needed

to

be

divided

into

4

groups,

which

are

Mismatch, N-Match, D-Match and Undefined then compare appeared color to locate Mismatch of the image in order to observe severity of Ischemic Stroke Area and allows the

B. Comparison of CB V, CBF and Ischemic Stroke Area

images to specifY

doctor to determine appropriate treatment. But in this

Equation 1 shows the relationship between data from

left side of the CT Scan images to eliminate the color

MTT

comparison, each doctor may see color scale value on the

CBV, CBF and MTT images which extract information in

difference. By the way,

order to calculate the Threshold value by determining the

properties of individual.

relationship MTT(sec)

of

Equation

CBV(mlllOOg) =

1

which

is

by using the rule of three In

CBF(mIl J �Og/min)

arithmetic to compare CBV, CBF and MTT units in order to fmd using Threshold value. For example, if CBV was set CBV

to 2.5, CBF was 20, so the -

this depends on the physical

III.

OPERATION OF THE SYSTEM

A. Applying Digital Image Processing (DIP) theories with medical method Digital Image Processing used in the analysis by taking CBV , CBF and MTT images to filter out unwanted

will be 0.125, allowing the

information from the images, such as numbers, letters etc.,

MTT value discovered from conversion of time unit into

Area process to pull out the part we want to compare. Then

CBF

the same value equal to 60*0.125, so the MTT value for assigning Threshold equals to 7.5 . After that, Threshold value of CBV, CBF and MTT can be tested by bringing MTT value with higher or lower than prescribed into comparison with Threshold value of CBV and CBF. The results will be scattered into six area, as shown in Fig. 2 .


and then take CBV , CBF and MTT images into IdentifY take the interested color (RGB) from the CBV , CBF and MTT images to make comparison (Grey Scale) in order to determine the relationship from table 1 to gather D-Match, Mismatch, N-Match and Undefined area then specify the area of the brain into two part to identify Ischemic Stroke Area (Left/Right Brain), such progress is shown in Fig. 3 .

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D. Comparison on the left and right area of the brain to identifY Ischemic Stroke Area Identifying the area of left and right side of the brain can be done by dividing Region Of Interested (ROJ) image then count the number of Pixel of N-Match if there is more pixels on the left or right side. The side with more pixels indicates that the side is normal and the side with less N-Match pixels is the side with Ischemic Stroke Area.

Determination of D-Match, Mismatch, N-Match and Undefined

E.

Determination

of D-Match,

Mismatch,

N-Match and

Undefined can be done by counting pixels in D-Match, Mismatch, N-Match and Undefined area then compare each pixel group to all the pixels of the brain. The results come out as a percentage by using equation

(4).

Pixel Segmen Volume Segment (%)

Fig. 3. Block diagram of identifying Ischemic Stroke Area progress.

B.

x

Filter out unwanted information (Crop)

By

After considered CBV, CBF and MTT images, rows that

as D-Match, Mismatch and N-Match

are less than row number

and columns that are less than

more than

all images are other information such as

letters,

numbers

and

Pixel Segment is the pixels in interested group, such Pixel Brain is all the pixels of the brain

and rows that are more than

70

row number

470 430 of

stripes.

This

is

an

60

example

(4)

100

Pixel Brain

Volume Segment is percentage amount of appeared

and of

D-Match, Mismatch, N-Match and Undefined According to Fig.

3,

it designed a program that can

information that is not necessary for Mismatch, so it is

interacts with users using Graphic User Interface (GUI)

possible to filter unwanted parts out of the image by

under MATLAB program which divide execution of the program into

changing such rows and columns into black pixels. C. Pulling out parts which is needed for analysis (IdentifY Area) [6]

Take filtered CBV and CBF images into Threshold progress as shown is the equation

(2).

3

parts: data entry part, display part and image

processing part. The program execution will start from receiving DICOM data files and process images using DIP principle. Finally, the display part will show image of area assigned brain, categorized into color: D-Match will be shown in blue, Mismatch will be shown in green, N-Match will be shown in red and Undefmed will be shown in

FT [i,J]

=

if F[i,J] 0 if F[i,J] 2 T otherwise

{255

yellow. Then compare left and right side of the brain to

=

I

o

(2)

program and Ischemic Stroke analysis from CTP image is

Take filtered MTT image into Threshold progress as shown is the equation

(3).

FT [i,J]

=

F [i, j]

shown in Fig.

4. �-

Gl.Jn 1

if F[i,J] 0 if F[i,J] S T otherwise

{255

=

I

o

by

identify Ischemic Stroke Area. Operation of the designed

(3)

.: f§5U:-.�

is original image.

.

I

.

T � �

0--...._.

FT[i, j] is grey scale (Imitate Binary Image, but add

255 value for cases that do not involve the brain)

R .. ul1

T stands for Threshold value that is specified by the analysis in order to divide the area of the brain: which area has more or less in normal level and the area which is in

__ ""lUI)

N,lbtchl.

unusual level in Table 1. Such results are Imitate Binary Images.

O.... althL.

FT[i, j] which is equals to

255

M.Mal.l:hR.

� � 3.£011

indicates that the area is

NIMn.u:hL.

D..JIIIlldlR. U6J,4

MilmatcllR.

not related to the brain. Unllltl�edL

FT[i, j] which is equals to I indicates that the area of the brain is normal. FT[i, j] which is equals to

0

indicates that the area of the

brain is unusual.


l.2IJi4

Un�e(tnedA z ..m�

Fig. 4. The operation of the program when Threshold level of CBV = 3 CBF = 30 and MTT=6.

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,


IV. SIMULATION RE SULTS Tested by comparing CTP images data of the CBV , CBF and MTT images of patients who want to be analyzed. Those images are images from the same time an same CT machine. The Threshold value of CBV equals to 2.5 mliiOOg (±I.S) , Threshold value of the CBF equals to 20 mIiIOOg/min(±IO) and Threshold value of the MTT equals to 7.5 sec (±4.S) are used in the experiment. Locate the area of the brain from the left side or the right side. Splitting images of the brain that are interested (ROI) then count the number of Pixel ofN-Match to identify the side ofIschemic Stroke. Such information are shown in Table 2. and Fig.S . TABLE II

THE SCATTERING DATA OF THE LEFT/RIGHT SIDE TO IDENTIFY THE SIDE OF ISCHEMIC STROKE.

CTP

Area

TH Mismatch

N-Match

D-Match

Undefined

2V24F5M

9.3792

36.7555

1.0519

2.8134

3V30F6M

11.8024

31.3832

3.6071

3.2074

2V24F5M

11.2715

35.8394

0.6756

3V30F6M

13.8776

30.1725

2V24F5M

7.1098

3V30F6M

LIR

N-Match

D-Match

Undefined

41.3217

1.0774

1.9259

L

6.9920

35.8304

4.7634

2.4142

L

2.2135

5.2463

41.4475

1.2220

2.0841

L

3.3080

2.6419

6.4912

36.3469

4.6862

2.4757

L

39.8733

0.8157

2.2012

4.5333

42.8492

0.8618

1.7557

L

9.2036

35.3743

2.8530

2.5690

5.6431

38.4761

3.6462

2.2346

L

2V24F5M

11.4382

34.3033

1.9992

2.2592

13.1923

29.8385

2.9431

4.0262

R

3V30F6M

12.1156

26.4322

8.9405

2.5117

14.5468

22.9588

8.1526

4.3417

R

2V24F5M

11.4472

34.3681

2.8875

1.2972

12.6133

29.1738

3.6958

4.5171

R

3V30F6M

10.5138

27.8510

10.1179

1.5173

12.8452

23.6126

8.7258

4.8163

R

Mismatch

5.6751

2

3

4

5

the left or right side of the brain is in Table 2 by a margin of error depends on cutting Threshold scale of image data. V. CONCLUSIONS This research has developed a program for Ischemic (a)

(b)

Fig.5. (a) Area ofD-Match(blue), Mismatch(green), N-Match(red) and

Stroke analysis from CTP images by using DigitalImage Processing principle applied to medical imaging. And the

Undefined(yellow) after configured level of Threshold CBV=3 ,

developed program is identify which side of the brain is

CBF=30 and MTT=6 .

suffering from stroke by setting Threshold value of CBV

(b) Ischemic Stroke Area providing from comparison of the Pixel ofN-Match.

According to Table 1 between CBV , CBF and MTT images, if configure Threshold of CBV in a stable value

and CBF and specifying the percentage volume of D-Match, Mismatch, N-Match and Undefined, with acceptable accuracy compared to area identifying by brain specialists.

and Threshold of CBF into high value, the amount of

RE FERENCE

D-Match will go up and the amount of N-Match will go down and Mismatch will be higher. But if the Threshold of CBF is in low value, the amount of D-Match will be low and the amount of N-Match will be high and Mismatch will be low. Those result is relate to Fig. 2, when changing the Threshold level of CBV ,CBF and MTT into more or less . and the results of the experiment can be seen by the scatterings of the data comparing to Threshold of CBV , CBF and MTT to identify area on


r ll Viriyavcjakul 13 Supp13

A "Stroke in Asia

An Epidemiological consideration,' Clin Ncurophannacol 1990:

526-33

l2J Ministry of Public Health ."Burden of disease and injuries in Thailand Priority setting for policy"2002: A l 4 - A 16 r31 Ministry of Public Health 2002: 58

"Burden of disease and injuries in Thailand Priority setting for policy,"

r41 Judy Rosc Jamcs, Olaniyi Osuntokun, Kaoncn Yodcr, Askicl Bruno, Evan D. Morris ," A superviscd mcthod for calculation of pcrfusion/diffusion mismatch volumc in acutc strokc ," IEEE, pp 1295-129�( 2004 r51 S. Fucanggan , S.CllOkchaitam , S. Mucngtawccpongsa "Simulation program of Finding Ischcmic Strokc Arca with CT-SCAN imagc Bascd on Digital hnagc Proccssing Tcchniqucs," biomcd-con2 . Bangkok , Thailand 20 I 0 r61 Ratncsh Jain. Rangachar Kasturi hltcOlational Edition Vo14.1995

Brain G. Schunck . "machinc Vision." McGRAW-HILL

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