PREGNANT WOMAN NUMERICAL MO - Telecom Paris

Numerical model of the pregnant woman based on

medical Images

Jérémie Anquez, Elsa Angelini, Isabelle Bloch (CNRS UMR 5141 LTCI, ENST Paris)

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Outline

1. EMFs influence on human body2. Pregnant woman model3. Uterus/Fetus segmentation

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1. EMFs influence on human body

EMFs represent one of the most common and fastest growing

environmental influences, about which anxiety and speculation are spreading

Examples of FAQ on WHO website:

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The “International EMF Project” has been launched in 1996 to assess the scientific evidence of possible health

effects of EMF

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Different areas involved in the assessment of EMF influence on health

Biology (studies on cells, on animals…)Physics (measures on physical phantoms and numerical models)Mathematics/Informatics(elaboration of models)

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Equipment certification : phantoms are used for in situ Specific Absorption Rate (SAR) measurements. SAR is the rate at which RF energy is imparted to a

unit mass of a biological body

ρσ 2E.

SAR =ρ

E

σElectric field strength in the tissue

Conductivity of the tissue

Mass density of the tissue


(W.kg-1)

1

2

3

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Anthropomorphic models are used for simulated SAR measurements. Two different

kinds of models exist:

Stylized models

VS

Voxelized models

Advantages:

• Scalable

• Easy to morph

Drawbacks:

• Simplification of human

anatomy (shape,

variability…)

Advantages:

• Accurate representation

of human anatomy

Drawbacks:

• Patient dependant

• Difficult to morph

• Time consuming task

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Anthropomorphic models are used for simulated SAR measurements


SAR

E2

ρσ

Anthropomorphic

model

Simulated electric

field

ρσ 2E.

SAR =

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2. Pregnant woman modeling

• Pregnant woman models needed• Available models• Hybrid model description

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1. Studies on EMF exposure of the adult

“Mobile Communications and Biology”, COMOBIO project [1999-2002]

2. Studies on EMF exposure of the children

“Dosimetric analysis of 3rd generation mobile phones ”, ADONIS project [2003-2006]

3. Studies on EMF exposure of the pregnant woman

WHO priority : need for adequate models

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Existing real-shaped phantom: abdomen composed of three layers, mother’s body,

amniotic fluid and fetus (Kawai [2005]).


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Existing stylized models (Stabin [1995]; Kainz [2003])

Surface equations CAD model


13Segmentation of CT data

Existing voxelized model (Cech [2005]; Xu [2004])


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Uterus/Fetus model: coarse fetus model due to large spatial spacing in CT scan [Xu]

No detailed fetus models available


Resolution :

1 x 1 x 10 mm3

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Designing the pregnant woman model from a whole-body acquisition is challenging

• Uterus pressure on patient’s cave vena

Need to assemble a hybrid model including:

• a Uterus/Fetus voxelized model (MRI, US)

• a stylized woman body (coarse body shape including skin, muscle and fat information)


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Stylized

model

Voxelized

model

Hybrid model


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3. Uterus/Fetus segmentation

Available data for uterus/fetus segmentation:• MRI data (Saint Vincent de Paul hospital): good

image quality but forbidden before 22 GW

• Ultrasound data (Philips Medical Systems): weak image quality but authorized anytime

Modalities used for differents gestational ages

Gestational

age (weeks)

Number of

Cases

40302010

US MRI

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Uterus/fetus segmentation based on MRI data (Cochin hospital partership)

• Large field of view

• Good overall contrast

• High resolution

MRI sequence requirements:

• Ultra-fast acquisition

• Little sensitivity to motion artifacts


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Motion related artifacts

Coarse resolutionLow overall contrast

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True FISP (Siemens) / Fiesta (GE) satisfies all requirements…

… but inhomogeneity correction needed

Slice

10/30

Slice

15/30

Slice

20/30

1

30

130

Resolution (mm3):

0.8 x 0.8 x 3

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Poor results using usual methods

• Brain inhomogeneity correction oriented

• User interaction needed (Dawant [1993])

• High computational cost (Zhang [2001])

• Parameters tuning needed (Mangin [2000])

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Segmentation using basic tools to study tissues intensity

Segmentation result 3D reconstruction

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Torso antenna generate a quasi parallel magnetic field

B1

Patient

Upper torso coil

Lower torso coil

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Tissues intensity mean and standard deviation trend in Z (slice acquisition direction)

Brain LungsUrinary

bladder

Intra-uterine

tissuesSame decreasing trend in Z

for every tissues : similar

trend for intra-uterine

tissues

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Hypothesis: • Intensity variation depends on Z only

• Same gray level distribution in any slice

Correction based on a surface fitting like method

kµ : kth slice mean

k

kji

kji

ss

µ,,'

,, =

Uterus

segmentation on

T2 Thick slab

Uterus extraction

on Fiesta data

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Inhomogeneity correction influence on intra-uterine tissues

Corrected dataOriginal data

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Inhomogeneity

correction

Corrected data

Original data

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Brain LungsUrinary

bladder

Inhomogeneity

correction

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The standard deviation of the intensity in 3D is lessened in every tissue

Advantages: • Easy implementation

• Very fast

• Robust

Drawbacks: • Variations in X and Y not considered

• Gray level distribution of intra-uterine tissues is not strictly equal from one slice to another

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Starting point

• Sequential segmentation with anatomical spatial relationship

• Complex scene with many different structures

• Need for a starting point eyes

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Eyes characteristics

• High intensity and good contrast with surrounding tissues

• Spherical morphology

• Weak variability (diameter, number…)

• Small organ (Z resolution)

X

Y

Z

Y

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Eyes detection algorithm

• Binary objects extraction using thresholding and connex component

• Object list reduction considering the objects volume or surface

• Object pair detection computing a score based on shape and distance between objects

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Threshold consequences

Must be high enough to disconnect the eyes from close structures but not too high, not to exclude peripheral voxels, and to preserve the objects spherical shape

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Threshold consequences (2)

Even using the second mode value as threshold, connections to the brain remain in 3D because of partial volume effect

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Threshold consequences (3)• Disconnection with morphological opening spoils the object shape

• Partial volume artifact has no influence on center slice

Eye median slice localization

X

Y

Z

Y

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Threshold, object extraction & object list reduction

VVV *3.1*7.0 ≤≤ with zyxRV ∆∆∆Π= .)..).(( 2

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Best object pair extraction• Compactness computation for each object

( ) ( )( )2..4OiS

OiVOiC Π=

• Measure computation for each object pair, based on distance between objects center

)),((.)(.)(),( jijiji ccdOCOCOOS µ=

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Final result

Good results on 10 datasets

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Median sagittal plane reconstruction using the eyes

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Brain detection on median sagittal plane…

… using a close neighborhood

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• Brain and spine segmentation to set fetus global position

• Segmentation of abdominal organs

• Segmentation of the head and the torso

• Challenging : segmentation of the limbs

Fetus

Uterus• Different objects to segment: placenta, amniotic fluid,

umbilical cord and uterus walls

Future works

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Uterus/fetus segmentation based on ultrasound data


Deformable model with statistical measures:

• Initialization

• Image-based information

• Implementation

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Segmentation of 3D ultrasound data

• Tool: 3D Slicer open source software (www.slicer.org)

• Segmentation based on basic operations: thresholding, manual contouring.

• Smoothing with mathematical morphology operators.

• Coarse segmentation: final model includes maternal tissues, amniotic fluid and fetal tissues

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Merge surface model segmented and image information to provide a good initialization

• Tool: Blender open source software (www.blender.org)

• Determine a set of visual landmarks corresponding to the key articulations in the data (neck, pelvis, elbow…).

• Morph the model’s articulations towards the landmarks


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Fetus model positioning


Mesh morphing using Blender

with definition of an associated

armature

Posing the

armature

morphes mesh

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Deformable model with statistical measures

• Levelset-based method using a priori knowledge of statistical distribution of grey levels in ultrasound data

• To model gray level behavior of ultrasound images, the Rayleigh distribution is classically considered (Bovik [1988], Chesnaud [1999])

Preliminary work : validation of the Rayleigh distribution on the data

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The Rayleigh distribution fits well when we consider the whole fetus…

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…but the body and the head have really different distributions

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Exponential distribution suits better for maternal tissues…

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…and perfectly for amniotic fluid intensities

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Preliminary studies using level set method based on those distributions are in progress

Segmentation

result

Original data

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• Implementation of an automatic detection of landmarks in data before morphing (head, spine, elbows, knees…) to initialize the model

• Validation of the statistic distributions observed, studying other data

• Evaluation of the method robustness at uterus/fetus interface

• Segmentation of fetal organs


Future works

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Pregnant woman model generation

• Methodology to apply to merge the uterus/fetus model and the woman stylized model

• Merging of the uterus fetus/model in an existing woman voxelized model

• Model morphing (simulation of different positions)

• Dosimetric studies when the model is exposed to different EMF sources; utilization in different applications (car accidents, photon exposure…)

Conclusion

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QUESTIONS ?

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PREGNANT WOMAN NUMERICAL MO - Telecom Paris