Sebastian Bauer

Towards Clinical Application of a Laplace Operator-Based Region of Interest Reconstruction Algorithm in C-Arm CT

It is known that a reduction of the field-of-view in 3-D X-ray imaging is proportional to a reduction in radiation dose. The resulting truncation, however, is incompatible with conventional reconstruction algorithms. Recently, a novel method for region of interest reconstruction that uses neither prior knowledge nor extrapolation has been published, named approximated truncation robust algorithm for computed tomography (ATRACT). It is based on a decomposition of the standard ramp filter into a 2-D Laplace filtering and a 2-D Radon-based residual filtering step. In this paper, we present two variants of the original ATRACT. One is based on expressing the residual filter as an efficient 2-D convolution with an analytically derived kernel. The second variant is to apply ATRACT in 1-D to further reduce computational complexity. The proposed algorithms were evaluated by using a reconstruction benchmark, as well as two clinical data sets. The results are encouraging since the proposed algorithms achieve a speed-up factor of up to 245 compared to the 2-D Radon-based ATRACT. Reconstructions of high accuracy are obtained, e.g., even real-data reconstruction in the presence of severe truncation achieve a relative root mean square error of as little as 0.92% with respect to nontruncated data.

Scaling calibration in region of interest reconstruction with the 1D and 2D ATRACT algorithm

Purposexa0xa0xa0Recently, a reconstruction algorithm for region of interest (ROI) imaging in C-arm CT was published, named Approximate Truncation Robust Algorithm for Computed Tomography (ATRACT). Even in the presence of substantial data truncation, the algorithm is able to reconstruct images without the use of explicit extrapolation or prior knowledge. However, the method suffers from a scaling and offset artifact in the reconstruction. Hence, the reconstruction results are not quantitative. It is our goal to reduce the scaling and offset artifact so that Hounsfield unit (HU) values can be used for diagnosis.Methodsxa0xa0xa0In this paper, we investigate two variants of the ATRACT method and present the analytical derivations of these algorithms in the Fourier domain. Then, we propose an empirical correction measure that can be applied to the ATRACT algorithm, to effectively compensate the scaling and offset issue. The proposed method is evaluated on ten clinical datasets in the presence of different degrees of artificial truncation.Resultsxa0xa0xa0With the proposed correction approach, we achieved an average relative root-mean-square error (rRMSE) of 2.81xa0% with respect to non-truncated Feldkamp, Davis, and Kress reconstruction, even for severely truncated data. The rRMSE is reduced to as little as 10xa0% of the image reconstructed without the scaling calibration.Conclusionsxa0xa0xa0The reconstruction results show that ROI reconstruction of high accuracy can be achieved since the scaling and offset artifact are effectively eliminated by the proposed method. With this improvement, the HU values may be used for post-processing operations such as bone or soft tissue segmentation if some tolerance is accepted.

Patient-bounded extrapolation using low-dose priors for volume-of-interest imaging in C-arm CT

PURPOSEnThree-dimensional (3D) volume-of-interest (VOI) imaging with C-arm systems provides anatomical information in a predefined 3D target region at a considerably low x-ray dose. However, VOI imaging involves laterally truncated projections from which conventional reconstruction algorithms generally yield images with severe truncation artifacts. Heuristic based extrapolation methods, e.g., water cylinder extrapolation, typically rely on techniques that complete the truncated data by means of a continuity assumption and thus appear to be ad-hoc. It is our goal to improve the image quality of VOI imaging by exploiting existing patient-specific prior information in the workflow.nnnMETHODSnA necessary initial step prior to a 3D acquisition is to isocenter the patient with respect to the target to be scanned. To this end, low-dose fluoroscopic x-ray acquisitions are usually applied from anterior-posterior (AP) and medio-lateral (ML) views. Based on this, the patient is isocentered by repositioning the table. In this work, we present a patient-bounded extrapolation method that makes use of these noncollimated fluoroscopic images to improve image quality in 3D VOI reconstruction. The algorithm first extracts the 2D patient contours from the noncollimated AP and ML fluoroscopic images. These 2D contours are then combined to estimate a volumetric model of the patient. Forward-projecting the shape of the model at the eventually acquired C-arm rotation views gives the patient boundary information in the projection domain. In this manner, we are in the position to substantially improve image quality by enforcing the extrapolated line profiles to end at the known patient boundaries, derived from the 3D shape model estimate.nnnRESULTSnThe proposed method was evaluated on eight clinical datasets with different degrees of truncation. The proposed algorithm achieved a relative root mean square error (rRMSE) of about 1.0% with respect to the reference reconstruction on nontruncated data, even in the presence of severe truncation, compared to a rRMSE of 8.0% when applying a state-of-the-art heuristic extrapolation technique.nnnCONCLUSIONSnThe method we proposed in this paper leads to a major improvement in image quality for 3D C-arm based VOI imaging. It involves no additional radiation when using fluoroscopic images that are acquired during the patient isocentering process. The model estimation can be readily integrated into the existing interventional workflow without additional hardware.

The Added Value of Volume-of-Interest C-Arm CT Imaging during Endovascular Treatment of Intracranial Aneurysms

VOI C-arm CT images were obtained in 28 patients undergoing endovascular treatment of intracranial aneurysms and the VOI images were reconstructed by using a novel prototype reconstruction algorithm to minimize truncation artifacts from double collimation. The reconstruction accuracy of VOI C-arm CT images was assessed quantitatively by comparing them with the full-head noncollimated images. Quality of VOI C-arm CT images was comparable with that of the standard Feldkamp, Davis, and Kress reconstruction of noncollimated C-arm CT images. The authors conclude that VOI imaging allows multiple 3D C-arm CT acquisitions and provides information related to device expansion, parent wall apposition, and neck coverage during the procedure, with very low additional radiation exposure to the patient. BACKGROUND AND PURPOSE: Successful endovascular treatment of intracranial aneurysms requires understanding the exact relationship of implanted devices to the aneurysm, parent artery, and other branch vessels during the treatment. Intraprocedural C-arm CT imaging has been shown to provide such information. However, its repeated use is limited due to increasing radiation exposure to the patient. The goal of this study was to evaluate a new volume-of-interest C-arm CT imaging technique, which would provide device-specific information through multiple 3D acquisitions of only the region of interest, thus reducing cumulative radiation exposure to the patient. MATERIALS AND METHODS: VOI C-arm CT images were obtained in 28 patients undergoing endovascular treatment of intracranial aneurysms. VOI images were acquired with the x-ray source collimated around the deployed device, both horizontally and vertically. The images were reconstructed by using a novel prototype robust reconstruction algorithm to minimize truncation artifacts from double collimation. The reconstruction accuracy of VOI C-arm CT images was assessed quantitatively by comparing them with the full-head noncollimated images. RESULTS: Quantitative analysis showed that the quality of VOI C-arm CT images is comparable with that of the standard Feldkamp, Davis, and Kress reconstruction of noncollimated C-arm CT images (correlation coefficient = 0.96 and structural similarity index = 0.92). Furthermore, 91.5% reduction in dose-area product was achieved with VOI imaging compared with the full-head acquisition. CONCLUSIONS: VOI imaging allows multiple 3D C-arm CT acquisitions and provides information related to device expansion, parent wall apposition, and neck coverage during the procedure, with very low additional radiation exposure to the patient.

Separating the wheat from the chaff: region of interest combined with metal artifact reduction for completion angiography following cerebral aneurysm treatment

Introduction Following complicated endovascular or microsurgical treatments, assessment of radiographic outcome can be challenging due to device resolution and metallic artifact. Two-dimensional and three-dimensional angiography can reveal information about flow and aneurysm obliteration, but may be limited by beam hardening, overlapping vessels, and image degradation in the region of metallic implants. In this study, we investigated the combination of a collimated volumetric imaging (volume of interest, VOI) protocol followed by metal artifact reduction (MAR) post-processing to evaluate the correct positioning of stents, flow diverters, coils, and clips while limiting the radiation dose to the patient. Methods 9 patients undergoing 10 procedures were included in our study. All patients underwent endovascular or surgical treatment of a cerebral aneurysm involving stents, flow diverting stents, coils, and/or clips followed by either immediate or early postoperative evaluation of our protocol. Results Image datasets corrected for metallic artifacts (VOI-MAR) were judged to be better—a statistically significant finding—than image datasets only corrected for field of view truncation (VOI alone). Qualitatively, images were more interpretable and informative with regards to device position and apposition to the vessel wall for those cases involving a pipeline, and with regards to encroachment on the parent artery and possible residual aneurysm, in all cases. Conclusions VOI acquisition combined with MAR post-processing provides for accurate and informative evaluation of cerebral aneurysm treatment while limiting the radiation dose to patients.

E-045 Separating the Wheat from the Chaff: Completion Angiography Following Complex Aneurysm Repair Using Low-Dose Volume of Interest Plus Metal Artefact Reduction Imaging

Introduction Following complex endovascular or microsurgical treatment of aneurysms, volumetric assessment of the surgical outcome in the angiography suite can be challenging due to device resolution and metallic artefact. We investigated a collimated volumetric imaging protocol followed by metal artefact suppression post processing to evaluate the correct positioning of stents, flow diverting devices, coils, and clips. Methods Under an IRB approved study protocol, ten patients who underwent endovascular or surgical treatment of a cerebral aneurysm involving stents, flow-diverting devices, coils, and/or clips, underwent angiography. This consisted of conventional 2D diagnostic imaging, followed by the acquisition of a volume of interest (VOI) collimated DynaCT. Such an acquisition yielded high-spatial resolution of implanted devices, by reducing the radiation burden depending on illuminated detector fraction. Volumetric images were reconstructed, accounting for the truncated images and artefact from dense metallic objects. Blinded readers were presented with VOI 3D images, processed with and without correction for metal artefact, and asked to score overall image quality, visibility of surrounding vasculature and aneurysm inflow, and diagnostic value. Scores were evaluated for statistical significance using a student’s T-test, testing the hypothesis that VOI + MAR is better than VOI alone. Results VOI images processed with metal artefact correction were judged better with 95% (p = 0.05) significance for overall image quality and 99% (p = 0.01) for the other three categories. Particular advantage was seen with the identification of residual aneurysm inflow as well as the ability to identify surrounding vasculature. Analysis of VOI scan dose area product (DAP) showed an average reduction of 85% compared to conventional DynaCT. Conclusion Combining VOI imaging with metal artefact suppression allows for clear imaging of complex aneurysm repair in the presence of dense metallic objects, while significantly reducing patient radiation exposure. Abstract E-045 Figure 1 VOI imaging without and with metal artefact reduction. Follow-up of surgical aneurysm repair using two clips, processed without (a) and with (b) metal artefact reduction, and follow-up of coiled aneurysm, again processed without (c) and with (d) metal artefact reduction. In both cases, metal artefact reduction processing allows a significant advantage in appreciating the metallic object with respect to the vasculature Disclosures E. Duckworth: None. D. Hoit: 1; C; Seimens. L. Elijovich: 1; C; Seimens. 2; C; Microvention, Stryker, Codman. V. Doss: None. W. Humphries: None. S. Schafer: 5; C; Seimens Medical Solutions USA. S. Bauer: 5; C; Seimens Medical Solutions USA. A. Arthur: 1; C; Seimens, Terumo. 2; C; Seimens, Johnson and Johnson, Sequent Medical, Covidian, Stryker, Terumo.

Viewpoint planning for quantitative coronary angiography

PurposeIn coronary angiography, the condition of myocardial blood supply is assessed by analyzing 2-D X-ray projections of contrasted coronary arteries. This is done using a flexible C-arm system. Due to the X-ray immanent dimensionality reduction projecting the 3-D scene onto a 2-D image, the viewpoint is critical to guarantee an appropriate view onto the affected artery and, thus, enable reliable diagnosis. In this work, we introduce an algorithm computing optimal viewpoints for the assessment of coronary arteries without the need for 3-D models.MethodsWe introduce the concept of optimal viewpoint planning solely based on a single angiographic X-ray image. The subsequent viewpoint is computed such that it is rotated precisely around a vessel, while minimizing foreshortening.ResultsOur algorithm reduces foreshortening substantially compared to the input view and completely eliminates it for

An Improved Extrapolation Scheme for Truncated CT Data Using 2D Fourier-Based Helgason-Ludwig Consistency Conditions

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