Introduction

Assessing perfusion in acute stroke is relevant to

identify patients more likely to benefit from

treatment with thrombolysis (1). Currently used

techniques either require intravenous contrast,

are unreliable, or are expensive and thus not

widely used in routine clinical practice (2).

Aim: To investigate the performance of a non-invasive method (3), which measures the relative delay in local blood oxygen level dependent (BOLD) signal using resting-state functional MRI (rsfMRI) data, for the diagnosis and

follow-up of perfusion deficits in patients with acute stroke in a clinical setting by directly comparing it to an established method for assessing brain perfusion (dynamic susceptibility contrast MRI, DSC-MRI).

Methods • 76 patients • <24 hours of ischaemic stroke onset • Perfusion (DSC-MRI) and BOLD delay (rsfMRI) maps

Results Image quality

Diagnostic agreement

Volumetric agreement

Spatial agreement

Discussion BOLD delay maps are sensitive to perfusion

deficits in acute stroke but have a high rate of

false-positives, possibly due to CSF artefacts.

BOLD delay maps agree, in terms of location, with

perfusion maps very early (<4.5h) following

stroke onset.

BOLD delay lesions underestimate perfusion

lesion volumes, resulting in low sensitivity for

perfusion-diffusion mismatch.

Head motion adversely affects the spatial

overlap between BOLD delay and perfusion

lesions, resulting in false negative BOLD delay

maps.

BOLD delay in stroke circumvents the infarct core

and specifically affects the surrounding tissue.

Contrary to previous studies (4), this suggests

that BOLD delay has neuronal rather than

vascular origins.

BOLD delay maps are reliable for following up

stroke patients, as changes in lesion volumes

between the first and second days following

stroke onset were similar between BOLD delay

and perfusion maps.

Ahmed Khalil, Ann-Christin Ostwaldt, Till Nierhaus, Kersten Villringer, and Jochen Fiebach

International Graduate Program Medical Neurosciences, Charité Universitätsmedizin Berlin

Further information ahmed-abdelrahim.khalil@charite.de

1. BOLD signal across time in one voxel (local) and whole brain (global) are extracted.

2. Signal corresponding to one repetition time (TR) at the start and end of the voxel

time series is removed.

3. Local time series is passed through the global time series in a series of sequential

steps (step=1TR).

4. For each step, the correlation between the local and global time series is calculated.

5. 1-4 repeated for each voxel, resulting in a TSA map showing the step yielding the

maximum correlation between local and global time series.

Perfusion deficits Perfusion-diffusion

mismatch

Sensitivity 82% (66 to 92%) 54% (34 to 72%)

Specificity 41% (24 to 61%) 90% (76 to 97%)

Positive predictive value 65% (50 to 78%) 79% (54 to 94%)

Negative predictive value 63% (38 to 84%) 73% (58 to 85%)

Yield 89%

Dic

e s

imil

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ty c

oe

ffic

ien

t0 .0

0 .2

0 .4

0 .6

0 .8

Dic

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imil

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< 4 .5 h rs 4 .5 -9 h rs > 9 h rs

0 .0

0 .2

0 .4

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0 .8

Longitudinal reliability

Effect of head motion

D a y 2 p e r fu s io n le s io n v o lu m e (m l)

Da

y 2

BO

LD

de

lay

le

sio

n v

olu

me

(m

l)

0 2 0 4 0 6 0 8 0

0

5 0

1 0 0

1 5 0

2 0 0

Ch

an

ge in

vo

lum

e (m

l)

Perfusion BOLD delay-50

0

50

100

150

Independent

variable

B P-value

Maximum motion -0.023 (-0.067 to -0.005) 0.023

Mean motion -0.157 (-0.308 to -0.006) 0.042

Number of

movements >0.5mm

-0.002 (-0.004 to -0.001) 0.006

Time shift analysis (TSA):

Pe

rc

en

t o

f m

ap

s (

%)

P e r fu s io n B O L D d e la y

0

2 0

4 0

6 0

8 0

1 0 0

C e rta in

U n c e rta in

U n in te rp re ta b le

Pe

rc

en

t o

f m

ap

s (

%)

P e r fu s io n B O L D d e la y

0

2 0

4 0

6 0

8 0

1 0 0

H ig h

M o d e ra te

L o w

BOLD delay Perfusion

DWI BOLD delay Perfusion

Example of a false-negative BOLD delay map associated with severe head motion. The perfusion map

shows a large lesion corresponding to the infarct on the right side.

Results of multiple logistic regression analysis: head motion is associated with decreased spatial overlap between perfusion and BOLD delay lesions. Regression coefficients (B) represent the effect sizes on the Dice similarity coefficient.

Positive correlation between BOLD delay and perfusion lesions on the second day of stroke onset (rho=0.78, p<0.0001).

Tukey boxplot showing lesion volume changes

between days 1 and 2 of stroke onset using the two

techniques (p=0.11)

Examples of high spatial overlap between BOLD delay and perfusion lesions.

Distribution of the degree of spatial overlap between BOLD delay and perfusion lesions in the study sample. Middle bar

is median, whiskers are interquartile range.

Bland-Altman plot showing the bias (20 ml, red line) and 95% limits of agreement (-117 to 157 ml , black lines) between perfusion and BOLD delay lesion volumes.

Image quality (diagnostic confidence, left; noisiness, right) of the BOLD delay and perfusion maps as assessed by the raters. The associations between map type and image quality were statistically significant (confidence, p<0.0001 ; noisiness, p<0.0001)

Coverage of the infarct core

Co

ve

ra

ge

ra

tio

P e r fu s io n B O L D d e la y

0 .0

0 .2

0 .4

0 .6

0 .8

1 .0

DWI BOLD delay Perfusion

Example of low

DWI lesion coverage by a

BOLD delay lesion and high coverage

by a perfusion lesion in the same

patient.

Tukey boxplots showing the degree of spatial overlap between BOLD delay and

perfusion lesions in patients presenting in different time

periods following stroke onset (p=0.26).

Values in brackets are 95% confidence intervals

Values in brackets are 95% confidence intervals

Acknowledgments Thanks to Peter Brunecker for the technical advice and

support, and Alexander Nave and Peter Koch for helping

with the assessment of the maps.

Proportion of voxels in the DWI lesion covered by perfusion and BOLD delay lesions (p=0.005).

NO DELAY

DELAY

Literature cited (1) Thomalla et al Stroke 2006

(2) Goyal et al Radiology 2013

(3) Lv et al Annals of Neurology 2013

(4) Amemiya et al Radiology 2013