Computer-Assisted Scheme for Automated Determination of Imaging Planes in Cervical Spinal Cord MRI Masaki Tsurumaki *a, Du-Yih Tsai*b, Yongbum Leeb, Masaru Sekiyab, Kiyoko Kazamaa a
Nakajo Central Hospital, 12-1 Nishihonjo Nakajo-machi Tainai City, Niigata, 959-2656, Japan b Dept of Radiological Technology, School of Health Sciences, Niigata University, 2-746 Asahimachi-dori, Niigata City, Niigata, 951-8518, Japan ABSTRACT
This paper presents a computerized scheme to assist MRI operators in accurate and rapid determination of sagittal sections for MRI exam of cervical spinal cord. The algorithm of the proposed scheme consisted of 6 steps: (1) extraction of a cervical vertebra containing spinal cord from an axial localizer image; (2) extraction of spinal cord with sagittal image from the extracted vertebra; (3) selection of a series of coronal localizer images corresponding to various, involved portions of the extracted spinal cord with sagittal image; (4) generation of a composite coronal-plane image from the obtained coronal images; (5) extraction of spinal cord from the obtained composite image; (6) determination of oblique sagittal sections from the detected location and gradient of the extracted spinal cord. Cervical spine images obtained from 25 healthy volunteers were used for the study. A perceptual evaluation was performed by five experienced MRI operators. Good agreement between the automated and manual determinations was achieved. By use of the proposed scheme, average execution time was reduced from 39 seconds/case to 1 second/case. The results demonstrate that the proposed scheme can assist MRI operators in performing cervical spinal cord MRI exam accurately and rapidly. Keywords: Magnetic resonance image (MRI), cervical spine cord, oblique sagittal imaging plane, automatic determination, assisting MRI operation
1. INTRODUCTION Magnetic resonance imaging (MRI) technology has improved rapidly since its introduction into clinical practice in the early 1980s. One advantage of MRI is its capability to produce images in any desired plane. MRI provides the maximum amount of information when evaluating patients with suspected spinal disorders [1, 2]. Therefore, MRI is used as the optimal imaging investigation for most kinds of spinal lesions [3-12]. Spine MRI provides high-resolution, multi-axial, multi-planar views that have high contrast between soft tissues. However, determination of an anatomically accurate imaging plane by an operator needs experience and expertise. In particular, the determination of the imaging plane by an inexpert may result in the increase of not only unnecessary scanning but also constraint time given to the patients. In our previous study, we have proposed a method for automatic determination of the imaging plane from the lumbar vertebra 3-plane localizer image in lumbar MRI [13]. The agreement between the automatic and manual determination is strong. Our preliminary results have demonstrated the usefulness and advantages of the proposed method for assisting radiological technologists in their routine work to automatically determine the imaging plane in lumbar MRI. The present wok is an extension of our previous work. The purpose of this study is to present a computer-aided scheme for MRI operators to help them in accurately and automated setting sagittal sections for MRI exam of cervical spinal cord . Cervical spine images obtained from 25 healthy volunteers were used for the study. To validate the usefulness of our proposed method, manual determination of the imaging plane was also conducted by five experienced radiological technologists for comparison. *
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2. MATERIALS AND METHODS 2.1 Image data acquisition Twenty five (25) healthy volunteers (10 women and 15 men) participated in the present study. All of them were fully informed and explained the purpose of the study. Figure 1 shows an example of 3-plane localizer images obtained from the pre-set axes. The study was conducted on a Signa Profile 0.2T system (GE Yokogawa Medical). The MR acquisition utilizes a T1 weighted sequence (TR/TE 115/7 msec, matrix 256×128, FOV 26 cm, flip angle 70˚, bandwidth 5.12 kHZ, and slice thickness 5mm.
Axial
Sagittal
Coronal Fig. 1 3-plane localizer images.
2.2 Proposed algorithm The algorithm of our proposed scheme consists of 6 major steps: (1) extraction of vertebra containing a cervical vertebra containing spinal cord is extracted from an axial localizer image pre-selected from the initially obtained 3-Plane localizer images (Fig. 2); (2) the spinal cord with sagittal image is then extracted from the sagittal localizer image corresponding to the R-L location of the extracted vertebra and spinal cord (Figs. 3 and 4); (3) A series of coronal localizer images corresponding to the various, involved portions of the extracted spinal cords with a sagittal image are selected (Fig. 5(a)); (4) a composite coronal-plane image is generated using the obtained coronal images (Fig. 5(b)); (5) the spinal cord is extracted from the obtained composite image (Figs. 6(a) and 6(b); (6) location and gradient of the extracted spinal cord are detected using the least square method (Figs. 6(c) and 6(d), followed by the determination of oblique sagittal sections for imaging. A number of image processing techniques such as, histogram analysis, profile analysis, and edge detection were also employed in the scheme.
Fig.2 Extraction of vertebra containing the spinal cord from an axial localizer image. (a) A preset axial localizer image. (b) An extracted area containing the spinal cord (indicated by an arrow).
(a)
(b) Fig. 3 Selection of a sagittal plane image corresponding to the same location of the spinal cord in the axial plane. (a) Locations of the sagittal planes corresponding to the axial plane (solid lines) and the location of the sagittal plane containing the spinal cord (dashed line). (b) Sagittal-plane image containing the selected spinal cord (indicated by a circle ○).
Fig. 4 Extraction of the spinal cord in the sagittal localizer image. (a) A sagittal localizer image containing the spinal cord selected from the axial plane. (b) Extraction of the spinal cord by employing edge detection processing.
(a)
(b)
Fig. 5 The process of generating a composite coronal-plane localizer image for the cervical spinal cord. (a) Selection of a series of coronal-plane localizer images based on the selected sagittal-plane localizer image. (b) Generation of a composite coronal-plane localizer image.
(a)
(c)
(b)
(d)
Fig. 6 Extraction of the feature of the spinal cord. (a) Composite coronal-plane localizer image. (b) Extraction of the spinal cord. (c) The center of the spinal cord. (d) The approximation line obtained using the least square method.
Fig. 7 Four examples of automated determination of the imaging plane in cervical spinal cord MRI.
localizer images scan
localizer images scan
image selection
automatic images selection & Automatic determination
position setting
No check
adjustment Yes
angle setting
no. of slices setting
confirmation
subsequent work
subsequent work
Fig. 8 An overview of the manual and automated operations. (a) Procedure for the manual operation. (b) Procedure for the automated operation.
2.3 Qualitative analysis The automatically determined slice lines for MR imaging of the cervical spine were visually evaluated by five radiological technologists with 4 to 10 years of experience. The readers were asked to rank the image on which the determined slice lines had been shown. The evaluation was based on the necessity of making further angle- or positioning-adjustment manually. The ranking was defined as: (A) the automatically determined imaging plane can be used as is. (B) the angle of the automatically determined imaging plane needs to be manually adjusted. (C) the position of the automatically determined imaging plane needs to be further manually adjusted. (D) both the angle and position of the automatically determined imaging plane need to be manually adjusted.
3. RESULTS AND DISCUSSION Cervical spine images obtained from 25 healthy volunteers were used for the study. Fig. 7 shows four examples of automated determination of the imaging plane in cervical spinal cord MRI. A perceptual evaluation was performed by five experienced MRI operators to validate the usefulness of the proposed scheme. All the readers ranked as A (automatically determined imaging plane can be used as is) for the 25 cases. This means that our experimental results showed that the concordance rate between the manual setting and automatic determination reached to 100%. Moreover, by use of the proposed scheme, average execution time was reduced from 39 seconds/case to 1 second/case. A remarkable reduction in execution time for imaging-plane determination was achieved. Conventional MRI examination was performed according to the following procedures: (a) to let a patient lie down on the bed of the MR scanner; (b) to determine the imaging plane in sagittal section based on the image been obtained beforehand for positioning. For an experienced radiological technologist, it needs approximately 39 seconds to determine the imaging plane. If the optimal imaging plane for cervical spinal cord MR imaging can be automatically determined, the decrease in scanning time and in constraint time given to the patients can be achieved. Consequently, the rate of operation of the MR scanner can be improved. An overview of the conventional, manual operation and the automatic operation for determination of the imaging plane in cervical spinal cord MRI is given in Figs. 8(a) and 8(b).
4. CONCLUSIONS
We have proposed a computerized scheme to assist MRI operators in accurate and rapid determination of sagittal sections for MRI exam of cervical spinal cord. Cervical spine images obtained from 25 healthy volunteers were used for the study. A perceptual evaluation was performed by five experienced MRI operators. Good agreement between the automated and manual determinations was achieved. By use of the proposed scheme, average execution time was reduced from 39 seconds/case to 1 second/case. The results demonstrate that the proposed scheme can assist MRI operators in performing cervical spinal cord MRI exam accurately and rapidly, particularly for the operator, who is not proficient in the operation of the machine for an emergency MRI.
ACKNOWLEDGMENT The authors wish to thank the radiological technologists from Nakajo Central Hospital for their support in conducting the performance evaluation of this work.
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