performs the bone removal fully automatically. The technique was .... Automatic bone removal workflow. Figure 3. ... notified by email in the case of a (possible).
Clinical applications
Automatic bone removal in CT angiography
EE Figure 1. CT angiography workflow.
E The software program removes the bone voxels fully automatically.
M. van Straten
Department of Medical Physics, Academic Medical Center, Amsterdam, the Netherlands
H.W.Venema
Department of Medical Physics and Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands
C. B. L. M. Majoie
Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands
L. Ciancibello K. Subramanyan
Philips Medical Systems, Cleveland OH, USA
CT angiography (CTA) allows arteries and veins in the brain and neck region to be made visible in a way that is significantly less invasive than conventional angiography. To fully comprehend the complex geometry of the vessels, a set of CTA images is often visualized using maximum intensity projection (MIP) or volume rendering (VR). In a MIP or VR image, however, the vessels are often obscured by bone, for instance in the skull base, or within the vertebrae. To obtain an unobstructed view, bone voxels are removed from the original images, prior to the generation of the MIP or VR images. This is usually done manually, using a virtual cutting tool on a graphic workstation. This is a very time-consuming procedure, and often practically impossible because bone and vessels lie very close to each other. We have developed a software program that performs the bone removal fully automatically. The technique was originally developed for CTA scans of the Circle of Willis [1,2], and has since then been developed further and extended to allow the visualization of other vascular structures. Currently, the technique is used in our hospital in all CTA examinations of the brain and neck region, including CTA of the cerebral veins [3] and the cervical arteries [4]. Materials
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The bone removal technique uses a masking process, requiring two scans of the same region. The additional scan is made prior to the injection of contrast agent, with a lower mAs value (typically 25% of the mAs value of the CTA scan) so the additional radiation dose is small. The scan is only used for the bone removal algorithm, and not for diagnostic purposes. Apart from the mAs value, the scanning parameters of the nonenhanced scan and contrast- enhanced scan are the same. An overview of the scan protocol is shown in Figure 1.
Method
Basically, the bone in the CTA images is removed using information from the additional, nonenhanced CT-scan to identify voxels that represent bone. The workflow is shown in Figure 2. The method comprises three steps. Figure 3 illustrates different stages of the algorithm with axial images of the region of the circle of Willis. The first step is a registration step to compensate for the inevitable movements of the patient
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G Figure 2. Automatic bone removal workflow.
between the scans. For this purpose the bones in the nonenhanced data set are registered with the corresponding bones in the contrast-enhanced data set. Each bone is assumed to be a rigid structure. If multiple bones are present in the volume of interest, such as vertebrae or the skull and lower jaw in a CTA examination of the neck region, the bones are separated first and then registered individually [4]. Figure 3a shows a nonenhanced CT image from a set of images that have been registered with a set of CTA images (Figure 3b). In the second step the bone voxels in the registered nonenhanced images are identified. As the nonenhanced data set does not contain vessels with a high CT value, the bone voxels can be uniquely identified by straightforward image processing techniques such as thresholding, region growing and dilation. In the third and final step the bone voxels in the contrast-enhanced data set (Figure 3b) are masked, i.e., they are given an arbitrary low value, with the exception of the voxels that are very close to the vessels. In Figure 3c the voxels to be masked are indicated by the blue overlay. The remainder of the bone voxels in the CTA scan (red overlay in Figure 3c) are removed by subtraction of the corresponding voxels in the registered nonenhanced images, followed by a restoration of the continuity of the CT values [5]. In this way the vessels that are contiguous to the bone are not affected by the bone removal technique. The processed data set is used to make MIP or VR images of the vessels.
Case reports The results achieved are demonstrated by the following cases. Case 1
Figure 4 shows MIP and VR images of the CTA scan of the circle of Willis of a female patient. This is the same patient as that shown in Figure 3a-d. After bone removal the arteries are clearly visible.
G Figure 3. Separate stages of the bone removal technique illustrated with axial images at the location of the intracranial internal carotid arteries. Scanning parameters: Mx8000 IDT, collimation 16 x 0.75 mm, rotation time 0.5 s, pitch 0.4 (0.625 for
Case 2
nonenhanced scan), voxel dimensions 0.5 mm x 0.5 mm x 0.5 mm, tube voltage 120 kV. Figure 3a. Registered nonenhanced image. Figure 3b. Contrast-enhanced image.
Figure 5 shows various images of a nonenhanced and contrast-enhanced CT scan of the cervical arteries in a 45 year old man.
Figure 3c. Mask overlay on contrastenhanced scan (see text for details). Figure 3d. Contrast-enhanced image after bone removal.
For correct registration of the scans it is necessary to register each bone in the nonenhanced scan (Figure 5a,b) individually with the corresponding bone in the contrast-enhanced scan (Figure 5c) because the bones have moved relative to each other. Without registration the bone removal would not be successful (Figure 5d). When one rigid registration is performed, almost all bones are correctly removed, with the exception of the vertebrae and the hyoid bone (Figure 5e). When all bones are registered individually, the bone removal is complete (Figure 5f ). Figure 5 g-i shows MIP images before and after automatic bone removal.
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Case 3
Figure 6 shows various images from a nonenhanced and contrast-enhanced CT scan of the cerebral veins of a 45 year old woman. Figure 6c and 6d show the result of bone removal by subtraction and masking, respectively. If subtraction is used to remove the bone, the noise in the CTA image increases considerably (Figure 6c), while removal by masking retains the original quality of the CTA image (Figure 6d). After the bone removal procedure, no bone remnants were present. The dural sinuses, cortical veins, and deep venous system were demonstrated with exquisite detail. Discussion
G Figure 4.VR and MIP of a CTA scan of the Circle of Willis, before and after bone removal (same patient as Figure 3b-d). Scanning parameters as Figure 3. Figure 4a. Coronal VR before bone removal. Figure 4b. Coronal VR after automatic bone removal. Figure 4c. Coronal slab MIP before bone removal. Figure 4d. Coronal slab MIP after automatic bone removal.
Bone removal by subtracting nonenhanced images from contrast-enhanced CT images has been described previously [6]. However, this technique has an important drawback. Subtraction always adds noise to the CTA images, as shown in Figure 6c. Consequently, the processed images have a lower image quality than the original CTA images. Other methods for removing bone without the information from an additional scan
Application of automatic bone removal in clinical practice In addition to vendor supplied visualization software, which is available on dedicated computer workstations, radiologists are showing a growing interest in scientific software that has been developed for special applications, such as the automatic bone removal in CT angiography described in this article. There is also a growing need for a user-transparent platform for this type of postprocessing of medical images. For these reasons, we have developed a framework for automated image processing and routing in our hospital. In clinical practice, medical images are archived and transferred between different systems with the aid of the DICOM protocol. This protocol is also used to communicate with our framework, which is responsible for the handling of the incoming DICOM images.
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The descriptive part of the DICOM data, which contains information regarding the patient, study, acquisition and image characteristics, is used in a rule-based way to identify the non-enhanced and contrast-enhanced scans, and to verify their suitability for the bone removal technique. The framework organizes the images internally and schedules a service for processing the data. After processing the results are cached and routed to a
workstation for review and further analysis. A web-based front-end has been developed to present the running, pending and terminated tasks. Furthermore, the system administrator is notified by email in the case of a (possible) system malfunction. Apart from the bone removal method, other automated image processing techniques are available within the framework. The authors intend to exploit computational grids to expand the capacity of the framework. These grids offer the opportunity to share external computational resources over different institutions in a coordinated way. The bone removal technique has been made available by introducing a DICOM export node on all CT scanners in our hospital and including this node by default in the CT angiography protocols. The images are automatically sent, processed and received on request of the CT scanning system. Since the introduction of the framework, the fully automatic bone removal technique is now available on a 24/7 basis. Consequently, no expert knowledge is required to apply the bone removal procedure. This improves the availability of the method in our hospital.
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have been described in the literature. These methods have to be tuned very accurately, and in spite of this there is always the risk that some vessels may be removed as well. The bone removal technique presented in this article does not suffer from these drawbacks. Because of the low mAs value used for the nonenhanced scan, the additional radiation dose is limited. The procedure is fully automatic, and the results obtained are completely independent of the operator. Consequently, the results are accurately reproducible and of high quality.
Conclusion The bone removal method presented in this article is a powerful tool for obtaining MIP and VR images of the cerebral and cervical vessels free from superimposed bone fully automatically and with only a small additional total radiation dose. Acknowledgments
The authors would like to thank M. Poulus (RT) and J.G. Snel (PhD) for their contributions to this article, and the Philips Clinical Science group in Cleveland for providing the data from the Mx8000 IDT scanner J
F Figure 5. Bone removal technique illustrated with sagittal images (a-f, i) and coronal images (g,h) of the cervical arteries. Scanning parameters: Mx8000 Quad, collimation 4 x 1 mm, rotation time 0.75 s, pitch 0.875, voxel dimensions 0.3 mm x 0.3 mm x 0.5 mm, tube voltage 120 kV. Figure 5a. Nonenhanced image. Figure 5b. Nonenhanced image after identification and separation of the bones. Figure 5c. Sagittal VR of contrastenhanced images. Figure 5d. Contrast-enhanced image after bone removal without registration of the scans. Due to motion of the patient not all bones are removed (arrows). Figure 5e: Contrast-enhanced image after bone removal with one rigid registration. Due to motion of the bones relative to each other, they are not removed completely (arrows). Figure 5f. Contrast-enhanced image after bone removal with individual registration of all bones. All bones are removed.The enhanced vessels are indicated with arrowheads. Figure 5g. Coronal slab MIP of the CTA images. Figure 5h. Coronal slab MIP of the CTA images after automatic bone removal Figure 5i. Sagittal slab MIP of the CTA images after automatic bone removal. F Figure 6. Bone removal technique illustrated with axial images (a-d) and a MIP image (e) of the cerebral veins. Scanning parameters: Mx8000 Quad, collimation 4 x 1 mm, rotation time 0.75 s, pitch 0.875, voxel dimensions 0.3 mm x 0.3 mm x 0.5 mm, tube voltage 90 kV. Figure 6a. Registered nonenhanced image. Figure 6b. Contrast-enhanced image. Figure 6c. Contrast-enhanced image minus registered nonenhanced image. Figure 6d. Contrast-enhanced image after automatic bone removal. Figure 6e. Oblique sagittal MIP of CTA images after automatic bone removal. MEDICAMUNDI 49/1 2005/5
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References [1] Venema HW, Hulsmans FJH, Den Heeten GJ. CT Angiography of the Circle of Willis and Intracranial Internal Carotid Arteries: Maximum Intensity Projections with Matched Mask Bone Elimination - Feasibility Study. Radiology 2001; 218,3: 893–898.
[4] Van Straten M, Venema HW, Streekstra GJ, Majoie CBLM, Den Heeten GJ, Grimbergen CA. Removal of Bone in CT Angiography of the Cervical Arteries by Piecewise Matched Mask Bone Elimination. Medical Physics 2004; 31,10: 2924–2933.
[2] Fazio A, Subramanyan K, Lin Z, Ciancibello L, Van Straten M, Pohlman S. Evaluation of Neuro Bone Subtraction Algorithms for CT Angiography. International Congress Series 2004; 1268: 37-42.
[5] Van Straten M, Venema HW, Streekstra GJ, Reekers JA, Den Heeten GJ, Grimbergen CA. Removal of Arterial Wall Calcifications in CT Angiography by Local Subtraction. Medical Physics 2003; 30,5: 761-770.
[3] Majoie CBLM, Van Straten M, Venema HW, Den Heeten GJ. Multisection CT Venography of the Dural Sinuses and Cerebral Veins by using Matched Mask Bone Elimination. Am. J. Neuroradiol 2004; 25: 787-791.
[6] Imakita S, Onishi Y, Hashimoto T, Motosugi S, Kuribayashi S, Takamiya M et al. Subtraction CT Angiography with ControlledOrbit Helical Scanning for Detection of Intracranial Aneurysms. American Journal Of Neuroradiology 1998; 19: 291–295.
INTERMEZZO Subtraction in the 1930s
In his doctoral thesis Planigraphy and Subtraction: Roentgenographic Differentiation Methods, published in 1934, B.G. Ziedses des Plantes addressed the problem of distinguishing between the various structures visible in a radiograph [1].
Cerebral angiography posed a particular problem, because the relatively weak contrast of the blood vessels was obscured by the overlying bony structures. Ziedses des Plantes proposed a subtraction technique in which one radiograph was made before the administration of the contrast agent, and a second radiograph was made after the contrast agent had flowed into the arteries. A positive transparency was then made of the second radiograph. The two radiographs were then superimposed on the lightbox. In this way the negative and positive images of the bony structures canceled each other out, so that the image of the blood vessels appeared against a neutral gray background. Ziedses des Plantes demonstrated that the technique worked, but various practical difficulties had to be overcome before it came into regular use in the 1960s (see page 16). [1] Ziedses des Plantes BG. Planigraphie en Subtractie: Röntgenografische Differentiatie Methoden. Thesis, Utrecht 1934.
F I Subtraction in 1934. a. Arteriogram after injection of contrast agent via the left common carotid artery. b. Subtraction, showing filling of the capillary bed.
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