Contrast-enhanced

magnetic

resonance

imaging

of

the

breast

the

value

of

pharmacokinetic

parameters

derived

from

fast

dynamic

imaging

during

initial

enhancement

in

classifying

lesions

The

value

of

pharmacokinetic

parameters

derived

from

fast

dynamic

imaging

during

initial

enhancement

in

characterizing

breast

lesions

on

magnetic

resonance

imaging

-LRB-

MRI

-RRB-

was

evaluated

Sixty-eight

malignant

and

benign

lesions

were

included

In

the

scanning

protocol

high

temporal

resolution

imaging

was

combined

with

high

spatial

resolution

imaging

The

high

temporal

resolution

images

were

recorded

every

s

during

initial

enhancement

-LRB-

fast

dynamic

analysis

-RRB-

The

high

spatial

resolution

images

were

recorded

at

a

temporal

resolution

of

s

-LRB-

slow

dynamic

analysis

-RRB-

In

the

fast

dynamic

evaluation

pharmacokinetic

parameters

-LRB-

Ktrans

Ve

and

kep

-RRB-

were

evaluated

In

the

slow

dynamic

analysis

each

lesion

was

scored

according

to

the

BI-RADS

classification

Two

readers

evaluated

all

data

prospectively

ROC

and

multivariate

analysis

were

performed

The

slow

dynamic

analysis

resulted

in

an

AUC

of

and

respectively

The

fast

dynamic

analysis

resulted

in

an

AUC

of

in

both

readers

The

combination

of

both

the

slow

and

fast

dynamic

analyses

resulted

in

a

significant

improvement

of

diagnostic

performance

with

an

AUC

of

and

-LRB-

P

-RRB-

The

increased

diagnostic

performance

found

when

combining

both

methods

demonstrates

the

additional

value

of

our

method

in

further

improving

the

diagnostic

performance

of

breast

MRI

Introduction

Breast

cancer

is

the

most

commonly

diagnosed

cancer

in

women

and

the

most

prevalent

cancer

worldwide

-LSB-

-RSB-

In

breast

imaging

mammography

is

still

the

most

commonly

used

imaging

techniques

both

in

screening

for

and

staging

of

breast

cancer

However

dynamic

contrast-enhanced

magnetic

resonance

imaging

-LRB-

MRI

-RRB-

is

becoming

an

increasingly

important

imaging

modality

in

the

detection

and

staging

of

breast

cancer

Because

of

its

superior

sensitivity

for

the

detection

of

invasive

breast

cancer

MRI

has

become

a

very

important

modality

in

breast

imaging

-LSB-

-RSB-

However

the

classification

of

a

lesion

detected

on

MRI

as

benign

or

malignant

still

remains

a

challenge

Reported

specificities

in

clinical

studies

range

between

and

-LSB-

-RSB-

The

main

characteristics

used

for

classification

of

detected

lesions

on

MRI

are

the

lesion

morphology

and

the

enhancement

dynamics

-LSB-

-RSB-

Dynamic

evaluation

is

often

based

on

late

dynamic

characteristics

of

enhancing

lesions

In

this

approach

the

decrease

of

signal

intensity

often

referred

to

as

a

type

curve

or

washout

is

highly

suggestive

for

breast

cancer

with

the

likelihood

for

malignancy

of

-LSB-

-RSB-

This

dynamic

evaluation

makes

use

of

high-resolution

MRI

images

with

a

relatively

low

time

resolution

of

s

or

more

-LSB-

-RSB-

The

high

spatial

resolution

of

these

sequences

is

necessary

for

accurate

morphologic

evaluation

Irregular

lesion

contour

inhomogeneous

internal

enhancement

and

rim

enhancement

have

been

described

as

features

indicating

a

malignancy

-LSB-

-RSB-

Schnall

et

al.

-LSB-

-RSB-

found

focal

mass

margins

and

signal

intensity

to

be

a

highly

predictive

imaging

features

However

the

combination

of

both

dynamic

and

morphological

parameters

resulted

in

the

highest

diagnostic

accuracy

in

multivariate

analysis

The

evaluation

of

early

enhancement

using

a

high

temporal

resolution

has

also

been

a

subject

of

study

in

breast

MRI

Boetes

et

al.

-LSB-

-RSB-

found

in

a

group

of

lesions

a

sensitivity

of

a

specificity

of

and

an

overall

accuracy

of

based

on

early

enhancement

characteristics

In

this

study

a

temporal

resolution

of

s

was

achieved

using

a

turboFLASH

sequence

The

value

of

a

high

temporal

resolution

during

initial

enhancement

was

confirmed

by

Sardanelli

et

al.

-LSB-

-RSB-

who

used

a

temporal

resolution

of

s

during

the

first

minute

of

enhancement

The

overlap

between

malignant

and

benign

enhancement

curves

was

only

using

the

fast

dynamic

evaluation

compared

with

using

a

lower

temporal

resolution

of

min

The

value

of

first

pass

high

temporal

resolution

imaging

for

the

differentiation

of

benign

and

malignant

lesions

was

studied

in

a

direct

comparison

of

steady-state

dynamic

MRI

-LRB-

s

temporal

resolution

-RRB-

and

first-pass

imaging

-LRB-

s

temporal

resolution

-RRB-

of

induced

mammary

tumors

in

female

rats

by

Helbich

et

al.

-LSB-

-RSB-

In

their

study

an

estimate

of

first-pass

perfusion

using

weighted

imaging

almost

reached

a

significant

difference

between

benign

and

malignant

tumors

All

other

methods

used

including

first-pass

imaging

failed

to

differentiate

benign

from

malignant

tumors

Gibbs

et

al.

-LSB-

-RSB-

also

used

a

high

temporal

resolution

-LRB-

s

-RRB-

in

the

evaluation

of

small

breast

lesions

and

evaluated

their

data

using

a

pharmacokinetic

model

The

incorporation

of

data

from

pharmacokinetic

modeling

in

the

evaluation

of

lesions

improved

diagnostic

accuracy

in

their

group

High

temporal

resolution

sequences

often

cover

a

limited

area

of

the

breast

-LSB-

-RSB-

These

imaging

protocols

are

therefore

less

suitable

in

clinical

MRI

or

screening

For

this

study

we

adjusted

the

scanning

protocol

in

order

to

obtain

a

high

temporal

resolution

during

initial

enhancement

while

covering

both

breasts

entirely

The

aim

of

this

study

is

to

asses

the

value

of

pharmacokinetic

parameters

derived

from

fast

dynamic

contrast

enhanced

imaging

during

initial

enhancement

in

differentiating

between

benign

and

malignant

breast

lesions

on

MRI

Materials

and

methods

Patient

selection

All

lesions

detected

on

clinically

performed

breast

MRI

examinations

in

the

period

from

January

until

June

were

initially

included

All

detected

lesions

were

evaluated

based

on

the

following

inclusion

criteria

-LRB-

-RRB-

histological

confirmed

diagnosis

or

-LRB-

-RRB-

follow-up

based

on

unchanged

MRI

morphology

and

enhancement

characteristics

during

at

least

months

indicating

a

benign

nature

of

the

lesion

-LSB-

-RSB-

Lesions

that

could

not

be

classified

as

benign

or

malignant

using

these

criteria

were

excluded

The

protocol

was

approved

by

the

institutional

review

board

Imaging

protocol

All

patients

were

examined

using

a

MRI

scanner

-LRB-

Sonata

or

Symphony

Siemens

Erlangen

Germany

-RRB-

in

combination

with

a

double

breast

coil

In

premenopausal

women

the

MRI

examination

was

performed

in

the

second

week

of

the

menstrual

cycle

to

minimize

enhancement

of

normal

glandular

tissue

-LSB-

-RSB-

Prior

to

the

MRI

examination

an

intravenous

catheter

was

inserted

in

the

left

or

right

arm

All

patients

were

placed

in

the

prone

position

with

the

breasts

in

the

double

breast

coil

and

positioned

at

the

isocenter

of

the

magnet

After

localizer

images

were

obtained

in

three

directions

low

spatial

resolution

proton-density-weighted

images

were

acquired

in

the

transverse

plane

covering

both

breasts

completely

-LRB-

TE

TR

FA

FOV

slices

TA

s

image

resolution

mm

mm

mm

-RRB-

Subsequently

a

coronally

orientated

high-resolution

three-dimensional

fast

low-angle

shot

series

-LRB-

FLASH

-RRB-

was

acquired

-LRB-

TE

TR

FA

FOV

slices

TA

s

image

resolution

mm

mm

mm

-RRB-

Thereafter

high

temporal

resolution

images

-LRB-

turboFLASH

-RRB-

were

recorded

times

with

identical

spatial

resolution

and

orientation

as

the

proton-density-weighted

images

-LRB-

TE

TR

FA

FOV

slices

TA

s

-RRB-

during

an

intravenous

bolus

injection

of

a

paramagnetic

gadolinium

chelate

mmol

of

gadoterate

meglumine

-LRB-

Dotarem

Guerbet

The

Netherlands

-RRB-

per

kilogram

of

body

weight

which

was

administered

with

a

power

injector

-LRB-

Spectris

Medrad

Pittsburg

USA

-RRB-

at

ml/s

and

followed

by

a

saline

flush

Following

these

series

the

FLASH

series

was

repeated

four

times

Total

scan

time

for

this

protocol

was

min

s

including

the

time

needed

to

record

localizer

images

Image

evaluation

For

the

evaluation

the

MRI

data

were

divided

into

two

sets

of

dynamic

data

for

each

patient

The

first

dataset

contained

the

high

spatial

resolution

images

-LRB-

FLASH

-RRB-

only

These

were

used

for

the

evaluation

of

both

lesion

morphology

as

well

as

signal

intensity

versus

time

curves

This

method

will

be

further

referred

to

as

the

slow

dynamic

analysis

The

second

dataset

contained

the

proton-density-weighted

images

the

high

temporal

resolution

images

as

well

as

the

precontrast

high

spatial

resolution

sequence

A

high-resolution

subtraction

of

the

pre

and

first

postcontrast

series

prepared

on

the

MRI

scanner

was

also

included

in

this

dataset

to

aid

in

lesion

detection

The

proton-density-weighted

sequence

was

necessary

for

an

accurate

estimation

of

the

value

necessary

for

the

quantitative

analyses

The

evaluation

of

this

dataset

will

be

further

referred

to

as

the

fast

dynamic

analysis

In

this

fast

dynamic

analysis

the

last

three

postcontrast

FLASH

series

were

not

used

All

cases

were

evaluated

prospectively

by

two

experienced

breast

MRI

radiologists

-LRB-

reader

and

reader

-RRB-

Both

readers

had

over

years

of

experience

in

dynamic

breast

MRI

The

evaluation

on

the

two

workstations

was

performed

independently

in

different

sessions

with

at

least

a

time

interval

between

both

sessions

For

the

slow

dynamic

analysis

a

dedicated

breast

MRI

workstation

was

used

-LRB-

Dynacad

Invivo

Germany

-RRB-

This

workstation

creates

subtraction

images

for

all

time

points

after

contrast

administration

of

which

the

first

is

automatically

displayed

together

with

the

precontrast

acquisition

both

in

a

coronal

orientation

Furthermore

axial

reconstructions

were

displayed

for

both

the

subtracted

and

images

with

color

overlays

of

wash-in/wash-out

enhancement

characteristics

projected

over

the

images

-LSB-

-RSB-

A

maximum

intensity

projection

and

signal

intensity

versus

time

curves

were

also

displayed

This

display

protocol

resembles

the

protocol

used

in

the

clinical

workflow

of

dynamic

breast

MRI

in

our

hospital

A

BI-RADS

classification

was

assigned

for

each

lesion

based

on

their

morphology

and

enhancement

dynamics

-LSB-

-RSB-

No

clinical

information

mammography

or

prior

MRI

data

were

provided

to

the

readers

during

the

evaluation

of

the

cases

In

the

fast

dynamic

analysis

a

workstation

developed

in-house

for

the

evaluation

of

dynamic

contrast

enhanced

MRI

was

used

-LSB-

-RSB-

On

this

workstation

pharmacokinetic

parameters

derived

from

the

high

temporal

resolution

turboFLASH

series

were

automatically

calibrated

calculated

and

displayed

using

color

overlays

Examples

of

the

recorded

high

temporal

resolution

enhancement

versus

time

curves

are

presented

in

Fig.

In

the

preparation

of

this

high

temporal

resolution

data

each

MRI

signal

enhancement/time

curve

was

first

fitted

to

a

general

exponential

signal

enhancement

model

as

described

previously

-LSB-

-RSB-

This

reduces

a

curve

to

model

with

the

following

five

parameters

baseline

-LRB-

-RRB-

start

of

signal

enhancement

-LRB-

-RRB-

which

defines

the

onset

of

the

exponential

curve

time-to-peak

-LRB-

ttp

-RRB-

the

exponential

constant

peak

enhancement

-LRB-

sp

-RRB-

the

signal

amplitude

at

which

the

exponential

curve

levels

off

and

late

wash

defined

as

the

slope

of

the

late

part

of

the

exponential

curve

The

reduced

signal

enhancement/time

curve

was

converted

to

a

reduced

tracer

concentration

-LRB-

mmol/ml

-RRB-

time

curve

-LSB-

-RSB-

effectively

converting

sp

to

concentration

tracer

after

initial

rapid

wash-in

-LRB-

often

at

a

peak

or

plateau

level

-RRB-

-LRB-

Cgd

p

-RRB-

The

reduced

plasma

concentration

time

curve

was

estimated

using

the

reference

tissue

method

-LSB-

-RSB-

Deconvolution

of

the

plasma

profile

and

estimation

of

pharmacokinetic

parameters

conformed

to

the

theoretical

derivations

-LSB-

-RSB-

but

was

implemented

in

the

reduced

signal

space

as

Ve

Cgd

ptissue/Cgd

pplasma

kep

-LRB-

ttptissue

ttpplasma

-RRB-

Ktrans

Ve

Kep

Where

Ve

is

an

estimate

of

the

extracellular

volume

-LSB-

-RSB-

Ktrans

the

volume

transfer

constant

-LRB-

-RRB-

and

kep

the

rate

constant

-LRB-

-RRB-

between

extracellular

extravascular

and

plasma

space

The

subscript

tissue

stands

for

a

measurement

in

the

tissue

under

investigation

and

the

subscript

plasma

for

the

reference

tissue

plasma

estimate

The

reference

tissue

was

automatically

determined

by

selecting

a

set

of

voxels

in

the

whole

image

volume

-LSB-

relative

enhancement

-LRB-

-RRB-

-RSB-

larger

than

and

smaller

than

-RRB-

This

was

most

often

the

pectoral

muscle

sometimes

the

liver

or

spleen

The

additionally

recorded

proton

density

images

were

used

to

correct

for

the

coil

profile

The

data

were

presented

on

the

workstation

with

high-resolution

precontrast

images

in

an

axial

coronal

and

sagital

reconstruction

-LRB-

FLASH

-RRB-

as

background

Color

overlays

were

projected

over

the

images

representing

Ktrans

kep

and

Ve

parameter

values

that

were

based

on

the

high

temporal

resolution

images

-LRB-

turboFLASH

-RRB-

A

subtraction

image

based

on

the

pre

and

first

postcontrast

FLASH

series

was

presented

to

aid

in

lesion

detection

No

criteria

for

differentiating

between

benign

and

malignant

lesions

were

derived

from

the

subtracted

images

In

this

evaluation

the

readers

selected

a

region

of

interest

-LRB-

ROI

-RRB-

within

the

enhancing

lesion

The

ROIs

were

sphere-shaped

and

placed

in

an

area

within

the

lesion

where

the

parameter

values

of

Ktrans

Ve

and

kep

were

highest

based

on

the

color-overlays

The

outer

limit

of

the

lesion

was

used

as

a

boundary

of

the

ROI

to

rule

out

partial

volume

effects

-LSB-

-RSB-

This

method

of

ROI

selection

has

previously

been

referred

to

as

a

hotspot

method

-LSB-

-RSB-

Each

reader

placed

only

one

ROI

per

lesion

From

this

ROI

the

workstation

calculated

the

mean

values

for

each

of

the

pharmacokinetic

parameters

Again

no

clinical

information

mammography

or

prior

MRI

data

were

provided

to

the

readers

during

the

evaluation

of

the

cases

In

case

of

multifocality

the

tumor

was

analyzed

as

a

single

lesion

Fig.

enhancement

versus

time

curves

of

a

benign

-LRB-

a

-RRB-

and

malignant

-LRB-

b

-RRB-

lesion

Note

that

the

slope

of

enhancement

and

the

level

of

enhancement

is

higher

for

the

malignant

lesion

compared

with

the

benign

lesion

These

fast

dynamic

acquisitions

were

analyzed

as

described

in

the

Materials

and

methods

section

and

resulted

in

the

color

overlays

as

presented

in

Figs.

and

The

data

used

in

this

figure

were

respectively

derived

from

a

histopathology

proven

fibroadenoma

and

an

invasive

ductal

carcinoma

The

same

lesions

as

presented

in

Figs.

and

Statistical

analysis

Differences

in

pharmacokinetic

parameter

values

between

the

malignant

and

benign

group

were

evaluated

using

an

independent

sample

t-test

The

performance

of

both

methods

was

compared

using

a

receiver

operator

characteristic

-LRB-

ROC

-RRB-

analysis

From

the

slow

dynamic

analysis

the

reader

's

final

BI-RADS

classification

of

the

lesion

was

used

in

the

ROC

evaluation

from

the

fast

dynamic

analysis

the

mean

parameter

values

calculated

from

the

ROI

selected

by

each

reader

were

used

Multivariate

analysis

was

performed

using

logistic

regression

in

order

to

evaluate

the

possible

additional

value

of

both

methods

to

one

another

Since

the

differentiation

between

benign

and

malignant

lesions

is

more

difficult

in

smaller

lesions

a

subgroup

of

all

lesions

of

cm

and

smaller

were

also

separately

evaluated

The

comparison

of

the

various

results

including

the

interobserver

variability

was

done

by

using

the

area

under

the

ROC

curve

-LRB-

AUC

-RRB-

as

an

estimate

of

diagnostic

accuracy

A

pairwise

comparison

was

performed

to

evaluate

differences

in

the

AUC

P

values

were

considered

to

indicate

statistical

significance

Results

A

total

of

consecutive

clinical

breast

MRI

examinations

in

patients

were

performed

In

these

studies

a

total

of

lesions

were

detected

Eighty-six

lesions

could

not

be

included

due

to

lack

of

histological

diagnosis

or

insufficient

follow-up

This

resulted

in

a

total

of

lesions

in

patients

benign

and

malignant

lesions

The

mean

age

was

years

-LRB-

range

years

-RRB-

Ninety-four

lesions

were

included

based

on

histological

evaluation

eight

lesions

based

on

follow-up

Mean

lesion

size

on

MRI

for

the

malignant

group

was

mm

-LRB-

range

mm

-RRB-

and

this

was

mm

-LRB-

range

mm

-RRB-

for

the

benign

lesions

A

total

of

lesions

were

cm

or

smaller

malignant

-LRB-

mean

lesion

size

mm

range

mm

-RRB-

and

benign

-LRB-

mean

lesion

size

mm

range

mm

-RRB-

The

histological

evaluation

of

the

malignant

lesions

was

in

cases

based

only

on

the

core

biopsy

in

cases

based

on

an

excision

biopsy

or

breast

saving

surgery

specimen

and

in

cases

based

on

the

mastectomy

specimen

Histological

proven

benign

lesions

were

in

cases

based

on

a

core

biopsy

and

in

seven

cases

based

on

an

excision

biopsy

Eight

lesions

were

proven

benign

based

on

follow-up

mean

follow-up

was

months

-LRB-

range

months

-RRB-

The

histological

composition

of

the

entire

group

is

summarized

in

Table

Table

composition

of

the

benign

and

malignant

group

of

lesions

-LRB-

IDC

invasive

ductal

carcinoma

DCIS

ductal

carcinoma

in

situ

ILC

invasive

lobular

carcinoma

-RRB-

Benign

-LRB-

n

-RRB-

Malignant

-LRB-

n

-RRB-

Imaging

results

In

the

slow

dynamic

analysis

reader

classified

lesions

as

a

BI-RADS

-LRB-

benign

malignant

-RRB-

seven

as

BI-RADS

-LRB-

-RRB-

as

BI-RADS

-LRB-

-RRB-

and

an

BI-RADS

-LRB-

-RRB-

This

was

respectively

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

and

-LRB-

-RRB-

for

reader

The

ROC

analysis

for

the

slow

dynamic

analysis

resulted

in

an

AUC

of

-LRB-

CI

-RRB-

and

-LRB-

CI

-RRB-

for

reader

and

respectively

The

mean

volume

of

the

ROIs

selected

by

the

readers

in

the

fast

dynamic

evaluation

was

for

reader

-LRB-

range

SD

-RRB-

and

for

reader

-LRB-

range

SD

-RRB-

No

significant

difference

was

found

for

ROI

size

-LRB-

P

-RRB-

The

pharmacokinetic

parameters

used

in

the

fast

dynamic

analysis

showed

a

significant

difference

between

the

benign

and

malignant

group

for

both

readers

-LRB-

Table

-RRB-

The

diagnostic

performance

of

the

fast

dynamic

analysis

resulted

in

an

AUC

for

Ktrans

of

-LRB-

CI

-RRB-

and

-LRB-

CI

-RRB-

for

reader

and

For

Ve

the

AUC

was

-LRB-

CI

-RRB-

and

-LRB-

CI

-RRB-

and

for

the

kep

parameter

-LRB-

CI

-RRB-

and

-LRB-

CI

-RRB-

for

reader

and

respectively

Scatter

plots

of

Ktrans

and

V

displaying

the

parameter

values

of

benign

and

malignant

lesions

found

in

the

two

readers

are

provided

in

Fig.

The

comparison

of

the

diagnostic

performance

from

the

slow

dynamic

analysis

with

the

single

parameter

fast

dynamic

analysis

showed

no

significant

differences

for

the

Ktrans

and

V

parameter

A

significant

difference

was

found

for

reader

between

the

slow

dynamic

analysis

and

the

kep

parameter

-LRB-

P

-RRB-

the

slow

dynamic

analysis

showing

better

results

This

was

not

found

for

reader

-LRB-

P

-RRB-

Table

pharmacokinetic

parameter

values

categorized

for

malignant

and

benign

lesions

per

reader

All

parameter

values

proved

significantly

higher

in

the

malignant

group

compared

to

the

benign

group

-LRB-

P

-RRB-

Benign

-LRB-

n

-RRB-

CIMalignant

-LRB-

n

-RRB-

CIReader

Reader

Fig.

plots

from

the

extracellular

volume

-LRB-

V

-RRB-

versus

the

transfer

constant

-LRB-

Ktrans

-RRB-

for

reader

-LRB-

a

-RRB-

and

reader

-LRB-

b

-RRB-

Benign

and

malignant

cases

were

clustered

Clusters

were

summarized

with

an

iso-probability

contour

computed

from

the

cluster

mean

and

covariance

at

a

squared

normalized

radius

of

The

continuous-line

ellipsoid

represents

the

benign

subgroup

the

dotted-line

ellipsoid

represents

the

malignant

subgroup

Combining

the

pharmacokinetic

parameters

-LRB-

Ktrans

Kep

and

V

-RRB-

in

a

multivariate

analyses

resulted

in

an

AUC

of

-LRB-

CI

-RRB-

and

-LRB-

CI

-RRB-

for

reader

and

No

significant

difference

was

found

between

the

multivariate

fast

dynamic

and

the

slow

dynamic

diagnostic

performance

-LRB-

P

and

P

-RRB-

The

multivariate

analysis

from

all

pharmacokinetic

parameters

combined

with

the

slow

dynamic

analysis

-LRB-

combined

analysis

-RRB-

resulted

in

an

AUC

of

-LRB-

CI

-RRB-

and

-LRB-

CI

-RRB-

for

reader

and

respectively

The

results

from

the

combined

analysis

were

significantly

higher

when

compared

with

the

fast

dynamic

analysis

for

both

readers

-LRB-

P

and

P

-RRB-

This

was

also

found

for

the

slow

dynamic

analysis

-LRB-

P

for

both

readers

-RRB-

The

ROC

curves

are

presented

in

Fig.

Fig.

curve

for

reader

-LRB-

a

-RRB-

and

reader

-LRB-

b

-RRB-

displaying

the

fast

dynamic

slow

dynamic

and

combined

analysis

No

significant

differences

were

found

between

the

fast

and

slow

dynamic

analysis

in

both

readers

A

significant

difference

was

found

between

the

slow

dynamic

analysis

and

the

combined

analysis

for

both

readers

-LRB-

P

for

both

readers

-RRB-

The

comparison

between

the

fast

dynamic

analysis

and

the

combined

analysis

also

resulted

in

a

significant

difference

for

both

readers

-LRB-

P

and

P

-RRB-

No

significant

differences

were

found

between

the

two

readers

In

the

group

of

lesions

of

cm

and

smaller

the

slow

dynamic

analyses

resulted

in

an

AUC

of

-LRB-

CI

-RRB-

for

reader

and

-LRB-

CI

-RRB-

for

reader

Overall

the

fast

analyses

resulted

in

this

group

in

an

AUC

of

-LRB-

CI

-RRB-

and

-LRB-

CI

-RRB-

respectively

No

significant

difference

was

found

between

the

slow

and

fast

dynamic

analyses

for

both

readers

-LRB-

P

and

P

-RRB-

The

combined

analysis

resulted

in

an

AUC

of

-LRB-

CI

-RRB-

and

-LRB-

CI

-RRB-

respectively

The

results

from

the

combined

analysis

were

significantly

higher

when

compared

with

the

fast

dynamic

analysis

for

both

readers

-LRB-

P

and

P

-RRB-

This

was

also

found

when

compared

to

the

slow

dynamic

analysis

-LRB-

P

and

P

-RRB-

No

significant

differences

were

found

between

the

two

readers

in

any

of

the

analyses

An

example

of

a

benign

and

a

malignant

lesion

is

presented

in

Figs.

and

Fig.

Transverse

reconstruction

of

the

high-resolution

subtraction

sequence

of

the

right

breast

b

Time

versus

relative

enhancement

curve

of

the

slow

dynamic

series

Ktrans

-LRB-

c

-RRB-

and

V

-LRB-

d

-RRB-

color

overlay

images

of

the

right

breast

including

a

scalar

bar

to

demonstrate

the

parameter

values

The

subtraction

image

shows

a

rounded

mostly

sharp

delineated

lesion

The

time

versus

signal

intensity

curve

demonstrates

a

type

curve

indicative

for

a

benign

lesions

The

readers

classified

this

lesion

as

benign

-LRB-

BI-RADS

-RRB-

or

probably

benign

needing

follow

up

-LRB-

BI-RADS

-RRB-

based

on

the

slow

dynamic

analysis

The

Ktrans

and

V

parameter

color

overlays

demonstrate

relatively

low

values

for

both

parameters

-LRB-

see

Table

for

comparison

-RRB-

indicative

for

a

benign

lesion

Histopathology

proved

this

lesion

to

be

a

fibroadenomaFig

Transverse

reconstruction

of

the

high-resolution

subtraction

sequence

of

the

right

breast

b

Time

versus

relative

enhancement

curve

of

the

slow

dynamic

series

Ktrans

-LRB-

c

-RRB-

and

V

-LRB-

d

-RRB-

color

overlay

images

of

the

right

breast

including

a

scalar

bar

demonstrates

the

parameter

values

The

subtraction

image

shows

a

spiculated

lesion

retromammillar

The

time

versus

signal

intensity

curve

demonstrates

a

type

curve

-LRB-

wash-out

-RRB-

suggestive

for

a

malignancy

Both

readers

classified

this

lesion

as

malignant

-LRB-

BI-RADS

-RRB-

based

on

the

slow

dynamic

analysis

The

Ktrans

and

V

parameter

color

overlays

demonstrate

high

values

for

both

parameters

-LRB-

see

Table

for

comparison

-RRB-

indicative

for

a

malignant

lesion

Histopathology

proved

this

lesion

to

be

an

invasive

ductal

carcinoma

Discussion

In

this

study

we

demonstrated

that

the

pharmacokinetic

parameters

derived

from

fast

dynamic

scanning

during

initial

enhancement

were

a

valuable

additional

tool

for

the

differentiation

between

benign

and

malignant

breast

lesions

on

MRI

The

pharmacokinetic

parameters

were

significantly

higher

for

the

malignant

group

compared

with

the

benign

lesions

-LRB-

Table

-RRB-

The

diagnostic

performance

of

the

pharmacokinetic

parameters

was

compared

with

the

results

of

the

slow

dynamic

analysis

not

significantly

different

The

combination

of

both

methods

however

did

improve

the

diagnostic

performance

significantly

for

both

readers

These

results

were

also

found

in

the

subgroup

analysis

of

smaller

breast

lesions

The

slow

dynamic

analysis

resembles

the

evaluation

as

routinely

performed

in

the

clinical

workflow

in

our

hospital

The

performance

of

the

workstation

used

in

the

slow

dynamic

evaluation

has

already

been

investigated

and

proven

by

Wiener

et

al.

-LSB-

-RSB-

in

the

evaluation

of

breast

lesions

prior

to

surgical

treatment

Schnall

et

al.

-LSB-

-RSB-

evaluated

the

performance

of

both

dynamic

and

morphological

features

in

women

with

lesions

The

results

of

their

multivariate

evaluation

based

on

both

morphological

and

relatively

slow

dynamic

lesion

characteristics

resulted

in

a

similar

diagnostic

accuracy

-LRB-

AUC

values

of

and

-RRB-

compared

with

the

results

obtained

in

the

slow

dynamic

analyses

of

our

study

-LRB-

and

-RRB-

Our

results

found

in

the

slow

dynamic

analysis

are

therefore

considered

representative

for

the

diagnostic

performance

of

an

experienced

radiologist

in

this

group

of

patients

In

the

fast

dynamic

analysis

both

the

morphologic

characteristics

and

slow

dynamic

characteristics

were

not

included

in

the

evaluation

instead

a

quantitative

analysis

of

pharmacokinetic

parameters

was

used

based

on

manual

ROI

placement

within

the

lesion

In

the

literature

both

a

hot-spot

and

whole-tumor

method

for

ROI

placement

are

reported

-LSB-

-RSB-

In

this

study

we

used

a

hot-spot

method

The

importance

of

a

consistent

ROI

placing

strategy

has

been

described

by

Liney

et

al.

-LSB-

-RSB-

In

our

study

both

readers

were

instructed

with

a

simple

ROI-placing

strategy

placing

the

ROI

in

an

area

with

the

highest

parameter

values

guided

by

color

overlays

Since

no

significant

differences

were

found

in

the

ROC

analyses

in

any

of

the

pharmacokinetic

parameters

used

it

is

assumed

that

the

performance

of

the

fast

dynamic

analysis

was

not

negatively

affected

by

this

manual

ROI

selection

strategy

The

optimal

strategy

of

ROI

selection

within

a

breast

lesion

is

a

subject

that

still

needs

to

be

further

investigated

this

is

beyond

the

scope

of

this

study

Gibbs

et

al.

-LSB-

-RSB-

found

the

use

of

quantitative

pharmacokinetic

parameters

in

the

evaluation

of

sub

breast

lesions

to

be

beneficial

In

their

study

of

women

a

diagnostic

accuracy

of

was

found

combining

the

postcontrast

images

with

the

dynamic

data

in

a

logistic

regression

analysis

The

exchange

rate

constant

was

found

to

be

the

best

individual

parameter

with

a

diagnostic

accuracy

of

The

Ktrans

was

also

found

to

be

the

best

individual

parameter

in

our

study

with

a

diagnostic

accuracy

of

Furman-Haran

et

al.

-LSB-

-RSB-

concluded

in

their

study

of

lesions

that

the

quantitative

evaluation

of

perfusion

parameters

should

be

able

to

improve

breast

cancer

diagnosis

on

MRI

In

their

study

the

Ktrans

was

also

found

to

be

the

best

discriminating

parameter

Their

analysis

showed

results

of

invasive

ductal

carcinoma

versus

fibroadenomas

or

fibrocystic

changes

Unlike

our

study

the

pharmacokinetic

parameters

used

by

Furman-Haran

and

coworkers

were

derived

from

high-resolution

images

with

relatively

a

low

temporal

resolution

of

min

Although

our

analysis

used

a

more

diverse

histological

distribution

-LRB-

Table

-RRB-

compared

with

the

results

presented

by

Furman-Haran

et

al.

-LSB-

-RSB-

only

a

relatively

small

number

of

benign

lesions

could

be

included

The

diverse

histological

distribution

also

resulted

in

the

inclusion

of

benign

lesions

that

do

not

necessarily

cause

a

diagnostic

dilemma

in

daily

practice

This

can

be

seen

as

a

limitation

of

our

study

In

the

subgroup

analysis

of

smaller

lesions

a

more

equal

distribution

between

benign

and

malignant

lesions

was

found

The

analysis

performed

in

this

subgroup

also

proved

the

additional

value

of

the

fast

dynamic

analysis

in

classifying

small

breast

lesions

on

MRI

The

three-time-point

method

used

by

Kelcz

et

al.

-LSB-

-RSB-

provides

the

reader

with

a

composite

image

showing

contrast

uptake

and

wash-out

characteristics

related

to

the

product

of

microvessel

surface

area

and

permeability

as

well

as

to

the

extracellular

volume

fraction

In

their

study

the

observers

correctly

diagnosed

of

malignant

and

of

benign

lesions

-LRB-

sensitivity

specificity

-RRB-

using

the

three-time-point

method

The

evaluation

based

on

wash-in

and

wash-out

curves

in

combination

with

morphology

resulted

in

a

sensitivity

of

and

a

specificity

of

Our

results

not

only

demonstrate

a

similar

performance

of

the

pharmacokinetic

analysis

compared

with

the

evaluation

based

on

morphology

and

slow

dynamics

but

also

demonstrate

the

potential

gain

if

both

methods

are

combined

The

results

presented

by

Kelcz

et

al.

-LSB-

-RSB-

are

like

other

authors

again

derived

from

high

spatial

resolution

images

with

a

relatively

low

temporal

resolution

of

min

compared

with

our

fast

dynamic

scanning

protocol

With

a

scanning

protocol

using

only

the

fast

dynamic

evaluation

and

morphology

the

scantime

could

be

reduced

significantly

when

compared

with

a

protocol

including

the

evaluation

of

wash-out

This

without

loss

of

diagnostic

performance

when

compared

with

the

results

of

the

slow

dynamic

analysis

in

our

study

and

the

results

presented

by

other

authors

-LSB-

-RSB-

This

reduction

of

scantime

can

in

the

future

contribute

to

the

cost-effectiveness

of

MRI

screening

However

since

the

highest

diagnostic

performance

was

obtained

by

combining

both

the

fast

and

slow

dynamic

analysis

further

studies

are

needed

before

the

scantime

can

be

reduced

The

results

presented

in

this

study

are

our

initial

results

using

this

scanning

protocol

Therefore

no

cut

of

values

for

the

differentiation

between

benign

and

malignant

lesions

from

the

pharmacokinetic

parameters

were

used

in

the

evaluation

or

can

be

provided

at

this

point

The

results

presented

only

show

the

potential

of

our

method

in

differentiation

between

benign

and

malignant

lesions

in

this

group

of

patients

The

value

of

our

method

needs

to

be

further

studied

in

a

larger

group

preferably

using

a

more

even

distribution

between

benign

and

malignant

cases

and

with

lesions

that

can

be

classified

on

imaging

as

a

BI-RADS

or

higher

Unfortunately

the

study

design

used

did

not

allow

a

multivariate

analysis

combining

the

fast

dynamic

data

with

morphological

characteristics

Also

the

possible

trade-off

between

the

pharmacokinetic

parameters

based

on

initial

enhancement

and

the

wash-out

based

on

late

dynamic

characteristics

can

not

be

derived

from

these

data

Both

analyses

will

need

to

be

performed

in

future

projects

in

order

to

evaluate

the

full

potential

of

the

fast

dynamic

analysis

as

used

in

our

study.In

conclusion

pharmacokinetic

parameters

derived

from

fast

dynamic

imaging

during

initial

enhancement

have

great

potential

in

classifying

enhancing

lesions

in

the

breast

In

this

study

the

diagnostic

performance

for

the

fast

dynamic

analysis

proved

to

be

equal

to

the

results

of

experienced

radiologists

using

more

common

evaluation

methods

based

on

morphologic

characteristics

and

slow

dynamic

enhancement

characteristics

An

increased

diagnostic

performance

was

found

in

combining

both

methods

This

shows

the

additional

value

of

this

method

in

further

improving

the

diagnostic

accuracy

of

breast

MRI

O O O O O O B O O O O B O O O O B O O O O O O O O O O B O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O B O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O


Judging surface slant for placing objects : a role for motion parallax People have a variety of sources of information -LRB- cues -RRB- about surface slant at their disposal . We used a simple placing task to evaluate the relative importance of three such cues -LRB- motion parallax , binocular disparity and texture -RRB- within the space in which people normally manipulate objects . To do so , we projected a stimulus onto a rotatable screen . This allowed us to manipulate texture cues independently of binocular disparity and motion parallax . We asked people to stand in front of the screen and place a cylinder on the screen . We analysed the cylinder 's orientation just before contact . Participants mainly relied on binocular cues -LRB- weight between 50 and 90 % -RRB- , in accordance with binocular cues being known to be reliable when the stimulus surface is nearby and almost frontal . Texture cues contributed between 2 and 18 % to the estimated slant . Motion parallax was given a weight between 1 and 9 % , despite the fact that it only provided information when the head began to move , which was just before the arm did . Thus motion parallax is used to judge surface slant , even when one is under the impression of standing still . Introduction It is often important to accurately judge the slant of surfaces in our nearby environment . Whether placing our foot on the ground when we walk or climb stairs , or our fingers on an object when we grasp it and place it elsewhere , the interaction always involves making contact with surfaces . In order to interact successfully , we need to know the orientation of these surfaces . We have many ways to judge a surface 's orientation , including ones based on texture gradients , binocular disparity and motion parallax . One important cue that contributes to most people 's slant perception is binocular disparity -LRB- see Howard and Rogers 1995 for an extensive review of the literature on binocular vision -RRB- . The small differences between the images in the two eyes suffice to obtain information about the slant in depth . From the literature on grasping it could be inferred that binocular cues normally dominate our actions . For example , Servos and Goodale -LRB- 1994 -RRB- claim that binocular vision is the principal source of information for reaching and grasping movements . However , binocular information does not guarantee correct grasping -LRB- Hibbard and Bradshaw 2003 -RRB- , so there is reason to expect other cues to also play a role in guiding our actions . A second cue that contributes to slant perception is the deformation of any surface texture and of shapes ' outlines as a result of perspective . We will refer to the combined information from all such sources as the texture cue . This is the cue that allows us to have a powerful and striking impression of surface slant from a flat image , as exemplified in Fig. 1 . It is well known that surface texture provides valuable information on slant perception -LRB- Gibson 1950 ; Stevens 1981 ; Buckley et al. 1996 ; Landy and Graham 2004 -RRB- and motor control -LRB- Knill 1998a ; Watt and Bradshaw 2003 -RRB- . Fig. 1The deformation of the regular texture of a chess board provides a profound impression that the surface is slanted relative to the plane of the 2D picture Retrieving the slant of a surface from texture cues is based on the assumption that the distribution of texture elements over the surface is more or less even and that shapes are more or less symmetrical , see Rosenholtz and Malik -LRB- 1997 -RRB- . This assumption holds for a wide variety of natural and artificial objects . The third cue that we will consider is motion parallax -LRB- Rogers and Collett 1989 ; Rogers and Graham 1979 , 1982 ; Ono and Steinbach 1990 ; Gillam and Rogers 1991 ; Ujike and Ono 2001 -RRB- . For a review of the widespread use of motion parallax in the animal kingdom , see Kral -LRB- 2003 -RRB- . Movement of the head relative to a surface generates changes in the surface 's retinal image over time . These changes depend on the motion of the head relative to the items in the surrounding , and on the items ' relative distances . The latter dependency can be used to obtain information about depth and slant . Watt and Bradshaw -LRB- 2003 -RRB- have shown that motion parallax can guide human movements when binocular cues are not available . When more than one cue is available the cues are combined . It is generally accepted that the estimated slant is a weighted average of the slants indicated by various cues , and that the weight of a cue is related to its accuracy , although some details of the mechanism are still under debate -LRB- Landy et al. 1995 ; Hillis et al. 2002 ; Hogervorst and Brenner 2004 ; Rosas et al. 2005 ; Muller et al. 2007 -RRB- . The relative contribution of binocular cues and texture cues depends on the distance -LRB- Hillis et al. 2004 -RRB- and surface orientation -LRB- Knill 1998b ; Buckley and Frisby 1993 ; Ryan and Gillam 1994 -RRB- , because binocular vision is better nearby and texture gradients change least rapidly with the angle of slant for near-frontal surfaces -LRB- for purely geometrical reasons -RRB- . Knill -LRB- 2005 -RRB- measured how binocular cues and texture cues to surface orientation are combined to guide motor behaviour . Cue weights were found to be dependent on surface slant and also on the task : more weight was given to binocular cues for controlling hand movements than for making perceptual judgements . Knill used cue-consistent and cue-conflict stimuli in a virtual reality environment . We wanted to find out whether motion parallax contributes to judgement of slant in the presence of other cues -LRB- such as binocular and texture cues -RRB- under more or less natural conditions . To do so , we used a setup in which the physical slant of a surface could be manipulated independently of the slant indicated by a pronounced texture . Thus a conflict between the texture cue and all the other cues was created by violating the assumption that the distribution of texture elements is homogeneous . The judged surface slant was determined by asking participants to swiftly place a flat cylindrical probe on the slanted surface -LRB- as in Knill 2005 -RRB- . Our main interest was in the extent to which head movements and the resulting motion parallax contribute to the perceived surface slant . So , conditions in which the head could move freely were compared with one in which a head restraint was used . We compared conditions with and without binocular vision in order to be able to evaluate the importance of motion parallax in relation to this cue . Methods Participants Five people , four of whom were male , participated in the experiment . All participants gave their informed consent prior to their inclusion in the study . The experiment was part of an ongoing research program that was approved by the local ethics committee . All participants were right-handed , had normal or corrected-to-normal vision and good binocular vision -LRB- stereo acuity < 40 arcseconds -RRB- . Experimental setup Participants were standing upright in front of a large rotatable screen . A sketch of the setup is given in Fig. 2 . The screen was a plexiglass plate covered with projection foil . Images were projected from below by an Hitachi cp-x325 LCD projector with a resolution of 1024 × 768 pixels . The screen and the projector could be rotated as a whole . Participants wore computer-controlled PLATO shutter-glasses , with which we could alternate between monocular and binocular vision , see Milgram -LRB- 1987 -RRB- . A chessboard pattern was projected onto the screen -LRB- see Fig. 3 -RRB- . Slants were defined relative to the gravity-defined horizontal . A grey ring , 104 mm in diameter , indicated the target position for the probe . Two positions of the ring , one near the participant -LRB- the target 's centre 100 mm below the stimulus centre -RRB- and one further away -LRB- 100 mm above the stimulus centre -RRB- were displayed in random order to make sure that participants did not simply repeat the previous movement . Figure 3 shows the stimuli with 0 ° and 10 ° texture slant relative to the surface 's physical slant . The geometry of the stimulus was calculated by projecting the texture-defined slant on the physically rotated surface . The projection is calculated from the point of the observer 's eyes . The 0 ° stimulus was a 40 cm square , with 40 cm corresponding to a visual angle of about 27 ° . A dark grey rim was drawn around the stimulus to mask any real edges that could become visible due to reflections within the set-up . To avoid illuminating objects around the set-up , the luminance of the image at the position of the eyes was limited to 0.4 Cd m − 2 . This was achieved by placing filters in front of the projector . Fig. 2Participants were standing upright , facing the screen . They moved a probe from a starting position 50 cm to the right of the surface midline to a target position on the surface -LRB- indicated by the grey ring -RRB- . Participants wore PLATO glasses with which we could switch between no , monocular and binocular vision . During the experiment , only the slanted surface was visibleFig . 3Examples of consistent -LRB- left -RRB- and conflict -LRB- right -RRB- images . The left panel shows the 0 ° texture slant on a 0 ° surface slant as seen from above . The right panel shows the 10 ° texture slant on the 0 ° surface slant . The deformation of the stimulus is consistent with the actual viewing geometry but for clarity the image is presented as seen from above . The target -LRB- grey ring -RRB- indicates the position at which participants have to place the probe . The targets are shown at the ` near ' position . The dark grey rim 's shape is in accordance with the texture cue The probe was a flat cylinder -LRB- diameter = 104 mm , height = 22 mm , mass = 0.2 kg -RRB- . Movements of the probe were registered by an optotrak 3020 system -LRB- northern digital inc. , Waterloo , ON , Canada -RRB- . This system tracks the position of active infrared markers with an accuracy better than 0.5 mm . The 3D-positions of five markers on the probe were tracked at a rate of 200 Hz . The position , orientation and velocity of the probe were calculated from these data . Procedure Experiments were performed in a completely dark room . The dark environment and the low intensity of the stimuli ensured that there was no visible external reference frame . Participants were instructed to place the probe at the indicated target position on the surface . They were to start moving as soon as the target was visible . Stimuli were shown for 2.5 s. All movements were completed well within this interval . In order to avoid dark adaptation a bright lamp was turned on for 5 s immediately after each trial . During this period participants placed the probe at the starting position , 50 cm to the right of the midline of the screen . Then the light was turned off for about 5 s , during which time the experimenter adjusted the orientation of the screen in preparation for the next trial . Figure 4 shows the six combinations of surface slant and texture slant that were used in the experiment . The different combinations could be viewed monocularly or binocularly . The four consistent combinations -LRB- on the diagonal in Fig. 4 -RRB- were used as a standard . The physical surface slant -LRB- see Fig. 2 -RRB- was − 10 ° , 0 ° , 10 ° or 20 ° , and the image on the surface was as shown on the left in Fig. 3 . The two conflict combinations either involved presenting the image shown on the right in Fig. 3 on a horizontal surface -LRB- surface slant 0 ° ; texture slant 10 ° -RRB- or presenting a similarly transformed image -LRB- slanted in the opposite direction -RRB- on a surface with 10 ° slant . All six stimuli were presented under various conditions . In total there were four experimental conditions , each consisting of 192 trials , divided into 3 blocks of 64 trials . Within every condition 75 % of the trials were without conflict and 25 % involved a conflict between texture and the other cues present in that condition . Fig. 4The six combinations of physical surface slant -LRB- continuous lines -RRB- and slant suggested by texture -LRB- dashed lines -RRB- that were used in the experiment . In four cases there was no conflict between the cues -LRB- solid disks -RRB- . In two cases there was a conflict -LRB- open disks -RRB- . The slants have been exaggerated for clarity We used four conditions in which different combinations of the available cues were presented . The choice of conditions will become clear when we describe the data analysis . We chose three conditions with which we could calculate the five parameters of our model , and one condition to test one of our assumptions . In the ` binocular ' condition viewing was binocular and head-free in both conflict and consistent trials . In this condition all cues to slant perception were available . In the ` monocular ' condition the conflict and consistent trials were both presented monocularly and head-free . Stimuli were viewed with the left or right eye in random order . No binocular cues were available , but all other cues were present . In the ` biteboard ' condition the head was fixed in combination with monocular viewing . The biteboards were made individually with an impression of the participant 's teeth . The biteboard severely limits head movements , removing information from motion parallax . In the consistent trials of the ` mixed ' condition the screen was viewed monocularly -LRB- 75 % of all trials -RRB- , but in the conflict trials -LRB- 25 % -RRB- it was viewed binocularly . This condition was included to evaluate whether participants adapt their strategy at the level of a session rather than per trial . In the ` binocular ' condition binocular information was always reliable , so participants could have learnt to use this cue . In the ` mixed ' condition , in contrast , binocular cues were absent in the majority of trials , so participants could have learnt to use texture or motion parallax . Note that the 25 % binocular , conflict trials in the ` mixed ' condition are identical to the conflict trials in the ` binocular condition ' , whereas the 75 % consistent trials are identical to the consistent trials in the ` monocular ' condition . Thus the ` mixed ' condition serves as a control condition to test whether the weight given to the cues stays about the same under changing viewing conditions on other trials . Analysis During some moments of some trials the participant 's fingers or hand occluded one or more of the five markers . The position of each marker relative to the centre of the probe is known , so the position and orientation of the probe can be calculated from any set of at least three markers . Frames in which fewer than three marker positions were known were not analysed . Figure 5 shows a schematic side-view of the path followed by the probe . The end of the movement was defined as the first sample at which the centre of the probe was less than 2 mm from the screen . The probe orientation was averaged over all samples at which the centre of the probe was between 100 and 20 mm from its position at the end of the movement -LRB- the grey line segments in Fig. 5 -RRB- . The last 20 mm of the path were excluded to avoid considering moments at which the edge of the probe could be in contact with the real surface of the projection screen . Fig. 5The upper left panel gives a schematic side view of the probe 's path -LRB- curved thin line -RRB- towards the slanted surface -LRB- straight thick line -RRB- . The position and orientation of the probe were measured by the optotrak system . The upper right panel shows a side view of a few paths towards the ` far ' target position . The average probe orientation is determined during the last 100 to 20 mm before the end of the movement -LRB- indicated schematically by the dark-grey line segments -RRB- . The lower panels show examples of the probe orientation with time intervals of 25 ms To understand our method for determining the cue weights , consider the two extreme hypothetical outcomes shown in Fig. 6 . At the one extreme , if information from the texture cue is not used at all , probe orientations will always follow the slant of the physical surface -LRB- left panel -RRB- . At the other extreme , if the observer only relies on texture cues the orientation of the probe will follow the texture-defined slant -LRB- right panel -RRB- . In the latter case the line connecting the cue-conflict conditions has approximately the opposite slope of that for consistent conditions . Note that the probe orientations in the consistent trials may differ from the physical surface slant -LRB- grey line -RRB- . Some flattening may arise because the hand may still be rotating towards the surface slant during the last 100 mm of its trajectory . Participants may also rely to some extent on previous slopes that they encountered during the experiment . We will model these effects as a prior for a single surface slant for all conditions . Fig. 6A schematic depiction of possible results for two extreme cases : probe orientation is not affected by texture at all -LRB- left panel -RRB- or only depends on the texture slant -LRB- right panel -RRB- We assume that the weights that participants give to the different cues are the same in all conditions . This would for instance be so if observers base the weights on the reliability , as in optimal cue combination -LRB- Landy et al. 1995 -RRB- . We can therefore model the estimated slant -LRB- S -RRB- as a weighted average of the slant estimated from each of the available cues -LRB- si -RRB- , which are all assumed to give veridical estimates except for the prior for a fixed slant -LRB- as mentioned in the previous paragraph -RRB- : where wi is the weight -LRB- in arbitrary units -RRB- given to each available cue , with i ∈ -LCB- b , m , t , r , p -RCB- indicating binocular vision , motion parallax , texture , a rest category containing any other valid cues , and the prior . Note that we predict that the cue weights -LRB- wi -RRB- of all available cues will be the same in all conditions , although the relative weight given to a cue -LRB- wi / ∑ wi -RRB- will differ between conditions because it depends on the cues that are available in that condition . The slant of the prior is a constant . Its value is likely to be near the mean of the slants in all previous conditions , but this is not essential for our analysis : If s denotes the simulated slant , then the slants indicated by all other available cues are : except for the conflict trials , for which the texture differs 10 ° from all other available cues -LRB- see Fig. 4 -RRB- : Combining these equations gives : and The sums in Eqs . 5 and 6 are only over cues that were available in each condition . The slopes -LRB- β -RRB- of the regression lines in Fig. 6 are given by the first derivatives of the estimated slant : Combining Eqs . 7 and 8 yields : and Equations 9 and 10 apply to all experimental conditions as modified for cue availability , except for the ` mixed ' condition . In the ` binocular ' condition all cues yield information about the surface 's slant : Similar equations can be written for the other conditions . Binocular information is not available in the ` monocular ' condition , so wB does not occur in the equation : Similarly , motion parallax ceases to contribute to the estimated slant in the ` biteboard ' condition , giving : Since the weights are in arbitrary units , we are free to define them in such a way that the sum of all weights is one : First we determine the weight of the prior relative to that of texture -LRB- wP/wT -RRB- for each condition , using Eq . 10 . Then , the weighted average of these ratios is calculated for each participant . We found no clear evidence that the assumption that wP/wT is the same across conditions was not justified . Next , determining the ratios between the slopes in the ` binocular ' , ` monocular ' and ` biteboard ' conditions from our data allows us to use Eqs . 11 to 14 to determine the values of the weights -LRB- wB , wT , wM and wR -RRB- . The data of the ` mixed ' condition was analysed by comparing the slopes -LRB- βconflict and βconsistent -RRB- with the matching slopes in the ` binocular ' and the ` monocular ' conditions . Data for ` near ' and ` far ' target positions were pooled before calculating the slopes . The weights of the cues were calculated for individual participants . In addition , we also pooled the data of all participants before calculating the slopes , which yields the weights for ` All ' participants . Results We determined average probe orientations for each participant and condition . The slopes of probe orientation as a function of surface orientation for conflict and consistent conditions enable us to calculate the cue weights , as explained in the ` methods ' section . Conditions The upper panel of Fig. 7 shows the probe orientations in the binocular condition . Conflict -LRB- open symbols -RRB- and consistent -LRB- closed symbols -RRB- probe orientations are almost the same . The difference between the slopes is small but significant -LRB- P < 0.05 -RRB- . The second panel of Fig. 7 shows the probe orientations in the monocular condition . The slopes clearly differ between the conflict and the consistent trials -LRB- P < 0.01 -RRB- . In the ` biteboard ' condition -LRB- third panel of Fig. 7 -RRB- the conflict trials have almost the opposite slope than the consistent trials . The difference between the slopes is significant -LRB- P < 0.01 -RRB- . The cue weights were calculated using Eqs . 10 to 14 and the values of the regression slopes . Fig. 7Pooled data for all participants . Each panel is for one of the four experimental conditions . Average probe orientations are shown for surfaces with -LRB- open symbols -RRB- and without -LRB- closed symbols -RRB- conflicts between real slant and texture slant . The error bars show the overall standard deviation . Correct probe orientations for the consistent trials -LRB- grey lines -RRB- , linear regression -LRB- black lines -RRB- and regression slopes , β -LRB- numbers in lower right corner -RRB- are also shown . Asterisks indicate whether the difference between the regression slopes is significant -LRB- * P < 0.05 ; ** P < 0.01 -RRB- The ` mixed ' condition was included as a control to ascertain that the cue weights do not depend on the viewing conditions on other trials . We compared the monocular consistent trials with the identical trials in the ` monocular ' condition , and the binocular conflict trials with the identical trials in the ` binocular ' condition . The regression slope for monocular , consistent trials -LRB- βconsistent = 0.72 -RRB- is not significantly different -LRB- P > 0.05 -RRB- from the same trials in the ` monocular ' condition -LRB- βconsistent = 0.76 -RRB- . The slope of the -LRB- binocular -RRB- conflict trials in the ` mixed ' condition -LRB- βconflict = 0.61 -RRB- is slightly but significantly lower -LRB- P = 0.04 -RRB- than for conflict trials in the ` binocular ' condition -LRB- βconflict = 0.72 -RRB- . Thus the weights may not be completely independent of the conditions . The difference was small enough to accept the calculation of the weights on the basis of the assumption that the condition is irrelevant . Our analysis may however underestimate the weight given to the texture cue . Cue weights The weight of the binocular cue lies between 50 and 90 % , for individual participants -LRB- see Fig. 8 -RRB- . The average standard error is 11 % . The errors in the cue weights are calculated by the method of propagation of errors based on the errors in the regression slopes . If we determine the slopes across all participants , the binocular weight is 71 ± 6 % . The weight of the texture cue lies between 2 and 18 % with an average standard error of 3 % for individual participants . The weight given to the texture cue is 8 ± 1 % across all participants . The weight given to motion parallax lies between 1 and 9 % for individual participants with an average standard error of 6 % . The weight given to motion parallax is 8 ± 3 % across all participants . The weight attributed to the rest category of cues was only 3 ± 2 % across all participants . The prior contributed between 6 and 23 % for individual participants with an average standard error of 3 % . The weight of the prior varies between 7 and 13 % across conditions . Across all participants the weight of the prior is 10 ± 2 % . Fig. 8The weights given to the binocular , texture , motion parallax , other cues and to the prior , for each participant -LRB- horizontal axis -RRB- . The weights are obtained by substituting the slopes of conflict data and consistent data in Eqs . 10 to 14 . For ` All ' , first all participant 's data in each condition was pooled and then the weights were determined , which are all significantly different from zero . For individual participants the texture cue was not significantly different from zero in one case , the motion cue in four cases and the rest category in three cases Head movements Head movements were measured in the monocular viewing condition for three of the participants . Participants move their head considerably when placing the cylinder : EB moved on average 103 mm , JG 53 mm and DdG 37 mm in the lateral direction . Interestingly , the head movement only started just before the arm movement . Shortly before -LRB- 100 ms -RRB- the onset of arm movement -LRB- when the probe was 10 mm from the starting position -RRB- , the head had only moved 10 mm -LRB- EB -RRB- , 4 mm -LRB- JG -RRB- or 6 mm -LRB- DdG -RRB- . Thus the information from motion parallax is mainly picked up during the arm movement . None of the participants were aware of having made head movements . Discussion We used a physically rotatable screen as a surface . The projected stimulus was viewed in a completely dark environment within a space in which objects are normally manipulated . In our analysis systematic deformations that affect a single cue -LRB- like depth compression resulting from an erroneous depth estimate -RRB- were not considered . Moreover , we assume that the cue weights are the same in all conditions , so that their contributions to the percept only depend on which cues are available . We determined the contributions of binocular disparity , texture cues , motion parallax , a rest category and a prior . Under these conditions and based on these assumptions we conclude that participants mainly relied on binocular information -LRB- between 50 and 90 % -RRB- . Texture cues contributed between 2 and 18 % to the estimated slant . Motion parallax contributed up to 9 % . The prior contributed between 6 and 23 % . Residual cues may account for up to 9 % . Comparing conditions with and without head movement revealed that motion parallax plays a role in slant perception . This is evident from the weights -LRB- Fig. 8 -RRB- but also from a comparison of performance in the ` monocular ' and ` biteboard ' conditions -LRB- Fig. 7 -RRB- . It is not unusual to move the whole body , including the head , when making large arm movements . Beside mechanical reasons for doing so we here show that it may also have perceptual advantages . We included in our analysis a rest category of cues that might contain information about slant that was not manipulated . The results suggest that this category indeed includes cues that yield some information about slant . Accommodation , or the rate at which the image becomes blurred with distance from fixation , might provide such information -LRB- Mather 1997 ; Watt et al. 2005 -RRB- . However , artefacts of our setup such as the possible visible micro texture -LRB- fibres in the projection foil or pixels on the screen -RRB- and the angular distribution of the light scattered from the surface could play a role too . Taken together in a rest category such cues contribute only a few percent to the estimated slant . The probe orientations in the consistent trials in Fig. 7 are not equal to the physical surface slant . We incorporated a prior in our model to take into account behaviour that is not related to the instantaneous information , like visual or haptic information from previous trials . The slant indicated by the prior cue is a constant ; i.e. it does not depend on the stimulus . Flatter slopes indicate that the prior plays a relatively large role . The weight of the prior is about as large as the weight of the texture cue . One component of the prior could be that the hand orientation is still changing towards its final value at the moment that we sample , which is slightly before contact -LRB- Cuijpers et al. 2004 -RRB- . Any biases towards a certain orientation of the hand or towards a certain perceived slant will also contribute to the weight of the prior . The purpose of having the ` mixed ' viewing condition was to check whether the weights change under different conditions . Ernst et al. -LRB- 2000 -RRB- have shown that haptic feedback can make more weight be given to a visual slant cue that is consistent with the feedback . In our study the haptic feedback was always consistent with the physical slant of the surface , so only the texture cue was sometimes unreliable . So , with a conflict between surface slant and texture the haptic feedback may yield a bias towards other cues than texture . Our results show a small difference between the ` mixed ' condition and the comparable trials in the ` monocular ' and ` binocular ' condition . Thus here too the extent to which cues are used does probably depend to some extent on experience in previous trials . This indicates that the estimated slant does not only depend on the accuracy of the presented cues , as is often assumed in theories of optimal cue combination -LRB- Landy et al. 1995 ; Hillis et al. 2002 ; Muller et al. 2007 -RRB- . It is however possible that the difference arises from less use of motion parallax when binocular information was always available , perhaps because participants move less when there is enough information from other sources than motion parallax . We do not know whether this is the case because we did not measure head movements in all conditions . However , these differences are all too small to be taken seriously without further research . In our study binocular disparity is given most weight , which is in accordance with binocular cues being known to be reliable when the stimulus surface is nearby and almost frontal . Because experimental conditions were all in favour of binocular disparity , the role of motion parallax and texture cues is probably smaller here than in natural viewing conditions . Motion parallax and texture cues both contribute to a small but significant extent to slant perception , although marked differences between participants were observed . Motion parallax was available only shortly and began relatively late , as the head began to move only just before onset of the arm movement . From animal studies it is known that a range of animals gain depth information by moving from side to side just before the performance of an action , see Kral -LRB- 2003 -RRB- . We have shown that humans are able to use motion parallax during an action . It was known that monocular depth information can be used to guide our actions -LRB- Marotta et al. 1998 ; Dijkerman et al. 1999 ; Watt and Bradshaw 2003 -RRB- . It was not known , however , that motion parallax plays a role under conditions where other cues are dominantly available and without actively moving one 's head before starting the action . We conclude that motion parallax is used as a cue to manipulate objects in our nearby environment , even when one is under the impression of holding one 's head still . Motion parallax should therefore not be ignored in a ` static ' task unless the head is really fixated .

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