Ultra-high-resolution subtraction CT angiography in the follow-up of treated intracranial aneurysms
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In subtraction CT angiography (CTA), a non-contrast CT acquisition is subtracted from a contrast-enhanced CTA acquisition. Subtraction CTA can be applied in the detection, classification, and follow-up of intracranial aneurysms and is advantageous over conventional angiography because of its non-invasive nature, shorter examination time, and lower costs. Recently, an ultra-high-resolution CT scanner has been introduced in clinical practice offering an in-plane spatial resolution of up to 0.234 mm, approaching the resolution as seen during conventional invasive digital subtraction angiography (DSA). The twofold increase in spatial resolution as compared to a conventional CT scanner could improve the evaluation of small vascular structures and, coupled with dedicated post-processing techniques, further reduce metal artifacts. Technical considerations using a state-of-the-art high-resolution subtraction CTA protocol are discussed for application in the follow-up of surgical and endovascular treated intracranial aneurysms.
KeywordsMulti-detector row computed tomography Angiography Brain Cerebral aneurysm
Digital subtraction angiography
Forward projected model-based Iterative Reconstruction SoluTion
Metal artifact reduction
Model-based iterative reconstruction
Subtraction CT angiography
Single-energy metal artifact reduction
Head subtraction CT angiography can be applied in the follow-up of treated cerebral aneurysms and could obviate conventional angiography.
Ultra-high-resolution subtraction CT angiography is feasible and provides superior image quality in comparison to standard resolution subtraction CT angiography, at similar radiation dose.
The added value of ultra-high-resolution CT angiography still needs to be evaluated in future prospective cohort studies.
In subtraction CT angiography (sCTA), a non-contrast CT acquisition is subtracted from a contrast-enhanced CTA acquisition. sCTA has shown to produce comparable results to digital subtraction angiography (DSA) in the detection and classification of intracranial aneurysms [1, 2, 3]. sCTA is advantageous over DSA because of its non-invasive nature, shorter examination time, and lower costs. Small aneurysms and aneurysms adjacent to bony structures are more accurately detected in sCTA as compared to conventional CTA [1, 2, 3]. Furthermore, sCTA can be applied in the follow-up of treated aneurysms after surgical clip placement, endovascular stent, or coil occlusion . In order to reduce metal artifacts, metal artifact reduction (MAR) algorithms like single-energy metal artifact reduction (SEMAR) can be applied . sCTA with conventional CT systems can achieve results comparable to conventional DSA in the follow-up of flow diverter- and surgical clip-treated patients [4, 6]. However, DSA is still commonly applied in clinical practice because of its high spatial resolution and the ability of selective vessel catheterization.
Recently, an ultra-high-resolution CT (UHRCT) scanner has been introduced in clinical practice . This system provides a more than twofold increase in spatial resolution as compared to a conventional CT scanner. Coupled with dedicated post-processing techniques, this system allows non-invasive vascular imaging with fine detail, approaching the resolution as seen during invasive DSA. The increase in spatial resolution enables improved depiction of small aneurismal remnants and small caliber vessels. Accordingly, UHR sCTA may further extend the applicability of CT in the follow-up of patients with treated intracranial aneurysms. However, at this moment, experience with this novel system remains limited.
In this manuscript, we discuss technical considerations using a state-of-the-art UHR sCTA protocol for clinical application in the follow-up of treated intracranial aneurysms. Technical features of the UHRCT system and available post-processing algorithms are described followed by clinical examples illustrating our initial clinical experience with this novel system.
Ultra-high-resolution CT (UHRCT)
Recently, an UHRCT scanner (Aquilion Precision, Canon Medical Systems, Otawara, Japan) has been introduced, offering an in-plane spatial resolution of up to 0.234 mm (1024 × 1024 matrix) . This UHRCT system is a 160-row multi-detector row system with superfine detector grids providing an effective detector element size of 0.25 mm × 0.25 mm, which is half the detector element size of a conventional high-end CT system. Likewise, the system has 1792 channels as opposed to the 896 channels seen in conventional CT scanners. Ultra-thin interseptal gaps between the detector elements maximize the light-sensitive areas on the detector. Combined with a data acquisition system redesigned for UHRCT, the resulting image noise remains comparable to conventional CT. The CT system features an adaptive focal spot X-ray tube with a minimum focus size as small as 0.4 mm × 0.5 mm. Gantry rotation time of 0.35 s can be achieved. In addition to the conventional 512 × 512 matrix, reconstructions are also possible with 1024 × 1024 and 2048 × 2048 matrix sizes in order to reduce pixel size.
Image reconstruction algorithms
To reduce the patient radiation dose, new image reconstruction techniques are continuously being developed for noise reduction and image quality improvement. Iterative reconstruction (IR) techniques are therefore rapidly replacing the traditional filtered back projection (FBP) reconstructions. On UHRCT, hybrid iterative reconstruction algorithms as well as the more recent full model-based iterative reconstruction (MBIR) are available . All are optimized for UHRCT acquisitions allowing noise reduction while preserving spatial resolution and structural edges. The MBIR algorithm (FIRST, Forward projected model-based Iterative Reconstruction SoluTion) is based on a forward projection model which accurately models system geometry, optics, and cone angle and a statistical model that models the noise characteristics in the measurements. For each iteration, the image is forward projected to the projection space and then compared to the original projection data. In addition, a regularization function optimized for the anatomical region is applied. An updated image is calculated by evaluating the mismatch between the forward-projected data and original projection data. The updated images are then combined to produce a new image which is a refinement of the previous image with improved spatial resolution and reduced noise. This process repeats itself until a final optimal image is obtained. The iterative reconstruction techniques are integrated into the automatic exposure settings for optimal dose reduction.
Metal artifact reduction (MAR)
On CT, metal causes beam hardening artifacts and scattering that degrade image quality and lead to decreased diagnostic accuracy for evaluating adjacent structures. To reduce these artifacts, software-based MAR, such as single-energy metal artifact reduction (SEMAR), can be applied on both single- and dual-energy acquisitions and does not require a dedicated system or acquisition technique . Briefly, the process starts with automatic segmentation of metal parts in an original first-pass image. Then, forward projection is applied to find the metal trace in the sinogram. The metal trace is removed through linear interpolation in the sinogram using nearby non-metal measurements, and an interpolated sinogram is reconstructed to create a second-pass image. This interpolation-corrected image is then segmented into different tissue classes (air, water, bone). The combined image is forward reprojected onto the metal trace using linear integration of interpolated voxels. Using a linear baseline shift approach, the original sinogram is blended with the forward-reprojected tissue-classified image on the metal trace. The blended sinogram is reconstructed to create a third-pass image, and the metal image (without artifacts) is added to create the final image.
Subtraction is a post-processing technique to eliminate high-density structures, such as bone, from CT images. A subtraction dataset is obtained by subtracting a non-contrast acquisition (mask image) from a contrast-enhanced image. For this, accurate registration of the two datasets is essential. In contrast to DSA, subtraction CT is 3D based and therefore more challenging. In addition, the (minimal) time delay between the non-contrast and contrast acquisitions can introduce differences between scans due to patient motion or vascular pulsation. To overcome these challenges, a dedicated registration algorithm is applied. This deformable registration algorithm matches the position of bony structures and calcifications on the mask image to the contrast scan prior to subtraction. Accordingly, subtracted image data are obtained from which high-density structures have been removed and which can be used for evaluation in conjunction with the conventional contrast-enhanced images.
UHR cerebral subtraction CTA protocol
Patients with a treated intracranial aneurysm need a follow-up to evaluate the level of aneurysm occlusion, or possible recanalization . Both DSA and sCTA can be considered in the follow-up of a surgical clip or endovascular stent-treated cerebral aneurysm, whereas MRA is not reliable in these patients due to susceptibility artifacts. In our hospital, we routinely perform sCTA for this indication, and DSA is performed only in case the image quality of sCTA is suboptimal or when there is doubt about the aneurysm occlusion. Although MRA is the preferred imaging modality for the follow-up of endovascular coil-treated aneurysms, some patients cannot undergo an MRI examination due to unsafe implants (e.g., pacemaker) or because of claustrophobia. In these cases, sCTA can be considered as an alternative to DSA.
UHR sCTA is feasible and provides superior image quality in comparison to standard resolution sCTA, at similar radiation dose. It enables non-invasive vascular imaging with fine detail, approaching the resolution as seen during invasive DSA. With the application of optimized image filtering and MAR, it can be applied in the follow-up of treated cerebral aneurysms. However, the added value of UHR sCTA still needs to be evaluated in future prospective cohort studies.
We thank Jeroen Tijhaar for proofreading of the manuscript and we thank Luuk Oostveen for providing technical assistance.
The authors state that this work has not received any funding.
The scientific guarantor of this publication is F.J.A. Meijer.
Statistics and biometry
No complex statistical methods were necessary for this paper.
FM and JS drafted the manuscript. HB, JV and WW participated in the clinical implementation of the UHRCT scanner and provided significant input for the manuscript. MP conceived the project and participated in its design and coordination. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Institutional Review Board approval was not required because it does not concern a clinical study but a technical report.
Consent for publication
Written informed consent was not required for this study because it does not concern a clinical study.
The authors of this manuscript declare relationships with the following companies: M. Prokop received a grant from Canon Medical Systems Corporation (Otawara, Japan). J.D. Schuijf is a full-time research employee of Canon Medical Systems Europe. J. de Vries and H.D. Boogaarts are consultants for Stryker neurovascular. The other authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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