Rationale and Objectives
To develop an automated computed tomography angiography (CTA) imaging protocol that allows visualization of the whole brain vasculature and evaluate the clinical usefulness of the technique for delineation of intracranial vessels in patients with cerebrovascular disorders.
Materials and Methods
We prospectively included 100 patients who underwent automated subtraction CTA for suspected cerebrovascular disorders. The nonenhanced and contrast enhanced scans were obtained with the same table feeding speed. The x-ray tube start angles of the two scans were matched to enable accurate registration and subtraction of the CTA datasets. Subtracted CTA datasets were reformatted as three-dimensional volume rendering and maximum intensity projection images for further review. Two independent readers assessed the quality of subtraction and delineation of intracranial vessels. The visibility of ophthalmic arteries was also assessed.
Results
Subtraction was successful in all patients. The image quality of bone removal was rated excellent in 95 patients, with no or minimal bone remnants. Incomplete bone removal was observed in five patients because of severe motions between the scans. In 97 of 100 patients, arterial segments at the circle of Willis could be clearly visualized. Excellent delineation of bilateral ophthalmic arteries was possible in 81 of 100 patients.
Conclusions
The whole brain vasculature would be clearly visualized by using the optimized automated CTA protocol. Our automated, single-source, dual-energy subtraction CTA protocol is a fully automated subtraction method that is capable of delineating major intracranial vessels as well as very small arteries.
Imaging of cerebrovascular structures is important because it provides necessary information for the diagnosis and treatment of central nervous system disorders . Digital subtraction angiography (DSA) has long been considered the reference method for the diagnostic workup of patients with cerebrovascular disorders. Nevertheless, it is an invasive and time-consuming technique that is associated with a 0.5% risk of permanent neurological complications . There is an increasing need for a fast and noninvasive imaging method that could be widely implemented in clinical practice. Magnetic resonance angiography (MRA) is an alternative noninvasive imaging method that allows direct visualization of the intracranial vessels . However, the low spatial resolution and prolonged examination time makes it a less than ideal imaging method in the diagnostic workup of patients with acute stroke Another advantage of CTA is whole brain coverage, which is not yet practical with MRA within a reasonable amount of time. In contrast to DSA and MRA, computed tomography angiography (CTA) has the advantage of high spatial resolution and short examination time.
Recent technical innovations have greatly advanced the role of CTA in screening and follow-up study of patients with cerebrovascular disorders . However, CTA may be less useful than DSA for evaluation of vascular structures because of the presence of bone structures . In previous studies, several attempts, such as the section-by-section subtraction algorithm and the matched mask bone elimination technique, have been developed to eliminate bone structures . However, these techniques are operator-dependent and require specially adapted equipment or subtraction software. More recently, dual-energy CTA that allows automated subtraction of bone structures were increasingly been used in evaluation of intracranial vessels . Compared to standard CTA, dual-energy CTA have considerably improved the subtraction of bony structures at the skull base. However, the technique requires the use of dual-source CT scanners, which is unavailable in many institutions. The purpose of our study was to develop a fully automated, single-source, dual-energy subtraction CTA protocol and evaluate its clinical usefulness for visualization of the whole brain vasculature.
Materials and methods
Phantom Study
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Patient Population
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Data Acquisition
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Evaluation of Images
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Results
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Discussion
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Conclusions
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Acknowledgments
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