7/27/2019 uog12484

1/6

This article is protected by copyright. All rights reserved

Towards improved ultrasound-based analysis and 3D visualization

of the fetal brain using 3D Slicer

Rie Oyama1

, Marianna Jakab2

, Miuki Terata1

, Chizuko Isurugi1

, Yoshitaka Kaido1

, Tomonobu

Knasugi1, Akihiko Kikuchi1, Toru Sugiyama1, Ron Kikinis2, Sonia Pujol2

1. Iwate Medical University, Obstetrics and Gynecology Department, Morioa, Japan

2. Harvard Medical School, Brigham and Women's Hospital, Radiology Department, Boston,

Massachusetts, USA

Corresponding author: Rie Oyama, Iwate Medical University, Obstetrics and Gynecology,

19-1 Uchimaru Morioka 0208505, Japan

Telephone: 81196515111 Fax: 81196221900

Email: oyamariegm@gmail.com

This article has been accepted for publication and undergone full peer review but has not

been through the copyediting, typesetting, pagination and proofreading process, which

may lead to differences between this version and the Version of Record. Please cite this

article as doi: 10.1002/uog.12484

Copyright 2013 ISUOG. Published by John Wiley & Sons, Ltd.

7/27/2019 uog12484

2/6

This article is protected by copyright. All rights reserved

The fetal choroid plexus and cerebrum are important organs involved in the diagnosis of

pathologies such as chromosomal anomalies, choroid plexus cyst, and cerebral hypoplasia.

Magnetic Resonance Imaging (MRI) provides useful three-dimensional (3D) information, but

has some restrictions posed by MRI safety issues for pregnancy at various gestational age. In

addition, fetal movements can create artifacts on MR images and the image quality depends

on the position of the fetus and placenta. In the past decade, 3D ultrasound imaging has been

used in clinical practice to investigate the formation and volumetric size of critical anatomical

structures of the fetus. However, current techniques rely mainly on sub-volumes of interest

that do not integrate anatomical information on the shape of these structures. In this paper,

we present a workflow for semi-automated segmentation and 3D visualization of fetal

ultrasound images at second trimester using the 3DSlicer open-source software1. Our

workflow allows quantitative image analysis of the choroid plexus and cerebrum from 3D

ultrasound images.

3D ultrasound images were acquired on five healthy pregnant women at 12 (n=2), 14 (n=2)

and 19 (n=1) weeks of gestation. Informed consent was obtained for each case. We used a

Voluson E6 (GE Healthcare, Zipf, Austria) ultrasound machine with RAB4-8-D/OB 3D/4D

8MHz trans-abdominal transducer. Our workflow (Figure1) was implemented in the 3DSlicer2

software, and consisted of four steps. Step1, we imported the DICOM ultrasound images to

3DSlice. Step2, we used the Grow Cut Segmentation Algorithm3 of the interactive Editor

module to extract critical structures from ultrasound images. Step3 we reconstructed 3D

surface models from the segmented regions using the Marching Cubes algorithm4, and Step4

7/27/2019 uog12484

3/6

This article is protected by copyright. All rights reserved

we computed the volume of the 3D anatomical models using the Label statistics module of

the software.

Figure2 shows the 3D surface models of the choroid plexus and cerebrum reconstructed

from the original 3D ultrasound images. The corresponding volumes of these structures at 12 ,

14 and 19 weeks were as follows: 431.14, 698.94 and 1203.27 mm3 (choroid plexus); 183.63,

282.82 and 469.83 mm3 (cerebrum).

Our workflow allows for patient-specific quantitative analysis and 3D visualization of

anatomical structures of the fetal brain from 3D ultrasound image data. In the future, we will

create segmentation that accurately matches the anatomy, using different methods. We

believe this method combined with Ultrasound or MRI data will be helpful for monitoring the

fetal brain development and detecting the fetal cerebral anomaly.

7/27/2019 uog12484

4/6

This article is protected by copyright. All rights reserved

References

1. Pieper S, Halle M, Kikinis R. 3DSlicer. Proc IEEE Int Symposium on Biomed Imaging:

From Nano to Macro2004; 1:632-635.

2. 3DSlicer.net. http://www.slicer.org. net. [October 9, 2011].

3. Vladimie V, Vadim K. Grow-Cut Interactive Multi-Label N-D image Segmentation. Proc.

Graphicon 2005; 150-156.

4. Lorensen WE, Cline HE. Marching cubes: A high resolution 3D surface construction

algorithm.ACM Siggraph Computer Graphics 1987; 21:163-169.

7/27/2019 uog12484

5/6

This article is protected by copyright. All rights reserved

Flowchart of Workflow of the 3DSlicer software in this study.

7/27/2019 uog12484

6/6