C-Arm Conebeam CT Perfusion Imaging in the Angiographic Suite: A Comparison with Multidetector CT Perfusion Imaging

Flat-panel Detector Perfusion Imaging and Conventional Multidetector Perfusion Imaging in Patients with Acute Ischemic Stroke : A Comparative Study

PURPOSE

Flat-panel detector computed tomography (FDCT) is increasingly used in (neuro)interventional angiography suites. This study aimed to compare FDCT perfusion (FDCTP) with conventional multidetector computed tomography perfusion (MDCTP) in patients with acute ischemic stroke.

METHODS

In this study, 19 patients with large vessel occlusion in the anterior circulation who had undergone mechanical thrombectomy, baseline MDCTP and pre-interventional FDCTP were included. Hypoperfused tissue volumes were manually segmented on time to maximum (Tmax) and time to peak (TTP) maps based on the maximum visible extent. Absolute and relative thresholds were applied to the maximum visible extent on Tmax and relative cerebral blood flow (rCBF) maps to delineate penumbra volumes and volumes with a high likelihood of irreversible infarcted tissue ("core"). Standard comparative metrics were used to evaluate the performance of FDCTP.

RESULTS

Strong correlations and robust agreement were found between manually segmented volumes on MDCTP and FDCTP Tmax maps (r = 0.85, 95% CI 0.65-0.94, p < 0.001; ICC = 0.85, 95% CI 0.69-0.94) and TTP maps (r = 0.91, 95% CI 0.78-0.97, p < 0.001; ICC = 0.90, 95% CI 0.78-0.96); however, direct quantitative comparisons using thresholding showed lower correlations and weaker agreement (MDCTP versus FDCTP Tmax 6 s: r = 0.35, 95% CI -0.13-0.69, p = 0.15; ICC = 0.32, 95% CI 0.07-0.75). Normalization techniques improved results for Tmax maps (r = 0.78, 95% CI 0.50-0.91, p < 0.001; ICC = 0.77, 95% CI 0.55-0.91). Bland-Altman analyses indicated a slight systematic underestimation of FDCTP Tmax maximum visible extent volumes and slight overestimation of FDCTP TTP maximum visible extent volumes compared to MDCTP.

CONCLUSION

FDCTP and MDCTP provide qualitatively comparable volumetric results on Tmax and TTP maps; however, direct quantitative measurements of infarct core and hypoperfused tissue volumes showed lower correlations and agreement.

Extended Multimodal Flat Detector CT Imaging in Acute Ischemic Stroke: A Pilot Study

By using Flat detector computed tomography (FD-CT), a one-stop-shop approach in the diagnostic workup of acute ischemic stroke (AIS) might be achieved. Although information on upstream vessels is warranted, dedicated FD-CT protocols which include the imaging of the cervical vasculature are still lacking. We aimed to prospectively evaluate the implementation of a new multimodal FD-CT protocol including cervical vessel imaging in AIS patients. In total, 16 patients were included in this study. Eight patients with AIS due to large vessel occlusion (LVO) prospectively received a fully multimodal FD-CT imaging, including non-enhanced flat detector computed tomography (NE-FDCT), dynamic perfusion flat detector computed tomography (FD-CTP) and flat detector computed tomography angiography (FD-CTA) including cervical imaging. For comparison of time metrics and image quality, eight AIS patients, which received multimodal CT imaging, were included retrospectively. Although image quality of NE-FDCT and FD-CTA was rated slightly lower than NE-CT and CTA, all FD-CT datasets were of diagnostic quality. Intracerebral hemorrhage exclusion and LVO detection was reliably possible. Median door-to-image time was comparable for the FD-CT group and the control group (CT:30 min, IQR27-58; FD-CT:44.5 min, IQR31-55, p = 0.491). Door-to-groin-puncture time (CT:79.5 min, IQR65-90; FD-CT:59.5 min, IQR51-67; p = 0.016) and image-to-groin-puncture time (CT:44 min, IQR30-50; FD-CT:14 min, IQR12-18; p < 0.001) were significantly shorter, when patients were directly transferred to the angiosuite, where FD-CT took place. Our study indicates that using a new fully multimodal FD-CT approach including imaging of cervical vessels for first-line imaging in AIS patients is feasible and comparable to multimodal CT imaging with substantial potential to streamline the stroke workflow.

Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging

Model-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be segmented for proper visualisation and interpretation of perfusion maps. This research proposes Turbolift learning, which trains a modified version of the multi-scale Attention UNet on different liver segmentation tasks serially, following the order of the trainings CT, CBCT, CBCT TST - making the previous trainings act as pre-training stages for the subsequent ones - addressing the problem of limited number of datasets for training. For the final task of liver segmentation from CBCT TST, the proposed method achieved an overall Dice scores of 0.874±0.031 and 0.905±0.007 in 6-fold and 4-fold cross-validation experiments, respectively - securing statistically significant improvements over the model, which was trained only for that task. Experiments revealed that Turbolift not only improves the overall performance of the model but also makes it robust against artefacts originating from the embolisation materials and truncation artefacts. Additionally, in-depth analyses confirmed the order of the segmentation tasks. This paper shows the potential of segmenting the liver from CT, CBCT, and CBCT TST, learning from the available limited training data, which can possibly be used in the future for the visualisation and evaluation of the perfusion maps for the treatment evaluation of liver diseases.

A C-arm photon counting CT prototype with volumetric coverage using multi-sweep step-and-shoot acquisitions

Objective.Existing clinical C-arm interventional systems use scintillator-based energy-integrating flat panel detectors (FPDs) to generate cone-beam CT (CBCT) images. Despite its volumetric coverage, FPD-CBCT does not provide sufficient low-contrast detectability desired for certain interventional procedures. The purpose of this work was to develop a C-arm photon counting detector (PCD) CT system with a step-and-shoot data acquisition method to further improve the tomographic imaging performance of interventional systems.Approach.As a proof-of-concept, a cadmium telluride-based 51 cm × 0.6 cm PCD was mounted in front of a FPD in an Artis Zee biplane system. A total of 10 C-arm sweeps (5 forward and 5 backward) were prescribed. A motorized patient table prototype was synchronized with the C-arm system such that it translates the object by a designated distance during the sub-second rest time in between gantry sweeps. To evaluate whether this multi-sweep step-and-shoot acquisition strategy can generate high-quality and volumetric PCD-CT images without geometric distortion artifacts, experiments were performed using physical phantoms, a human cadaver head, and anin vivoswine subject. Comparison with FPD-CT was made under matched narrow beam collimation and radiation dose conditions.Main results.Compared with FPD-CT images, PCD-CT images had lower noise and improved visualization of low-contrast lesion models, as well as improved visibility of small iodinated blood vessels. Fine structures were visualized more clearly by the PCD-CT than the highest-available resolution provided by FPD-CBCT and MDCT. No perceivable geometric distortion artifacts were observed in the multi-planar PCD-CT images.Significance.This work is the first demonstration of the feasibility of high-quality and multi-planar (volumetric) PCD-CT imaging with a rotating C-arm gantry.

Advances in cerebral perfusion imaging techniques in acute ischemic stroke

The application of cerebral perfusion imaging has demonstrated significant assessment benefits and an ability to establish an appropriate triage of patients with acute ischemic stroke (AIS) and large artery occlusion (LAO) in the extended time window. Computed tomography perfusion (CTP) and magnetic resonance imaging (MRI) are routinely used to determine the ischemic core, as well as the tissue at risk, to aid in therapeutic decision-making. However, the time required to transport patients to imaging extends the door-to-reperfusion time. C-arm cone-beam CT (CBCT) is a novel tomography technology that combines 2D radiography and 3D CT imaging based on the digital subtraction angiography platform. In comparison with CT or MRI perfusion techniques, CBCT combined with catheterized angiogram or therapy can serve as a "one-stop-shop" for the diagnosis and treatment of AIS, and greatly reduce the door to reperfusion time. Here, we review the current evidence on the efficacy and theoretical basis of CBCT, as well as other perfusion techniques, with the purpose to assist clinicians to establish an effective and repaid workflow for patients with AIS and LAO in clinical practice.

Low-dose CT Perfusion with Sparse-view Filtered Back Projection in Acute Ischemic Stroke

RATIONALE AND OBJECTIVES

Radiation dose associated with computed tomography (CT) perfusion (CTP) may discourage its use despite its added diagnostic benefit in quantifying ischemic lesion volume. Sparse-view CT reduces scan dose by acquiring fewer X-ray projections per gantry rotation but is contaminated by streaking artifacts using filtered back projection (FBP). We investigated the achievable dose reduction by sparse-view CTP with FBP without affecting CTP lesion volume estimations.

MATERIALS AND METHODS

Thirty-eight consecutive patients with acute ischemic stroke and CTP were included in this simulation study. CTP projection data was simulated by forward projecting original reconstructions with 984 views and adding Gaussian noise. Full-view (984 views) and sparse-view (492, 328, 246, and 164 views) CTP studies were simulated by FBP of simulated projection data. Cerebral blood flow (CBF) and time-to-maximum of the impulse residue function (Tmax) maps were generated by deconvolution for each simulated CTP study. Ischemic volumes were measured by CBF<30% relative to the contralateral hemisphere and Tmax > 6 s. Volume accuracy was evaluated with respect to the full-view CTP study by the Friedman test with post hoc multiplicity-adjusted pairwise tests and Bland-Altman analysis.

RESULTS

Friedman and multiplicity-adjusted pairwise tests indicated that 164-view CBF < 30%, 246- and 164-view Tmax > 6 s volumes were significantly different to full-view volumes (p < 0.001). Mean difference ± standard deviation (sparse minus full-view lesion volume) ranged from -1.0 ± 2.8 ml to -4.1 ± 11.7 ml for CBF < 30% and -2.9 ± 3.8 ml to -12.5 ± 19.9 ml for Tmax > 6 s from 492 to 164 views, respectively.

CONCLUSION

By ischemic volume accuracy, our study indicates that sparse-view CTP may allow dose reduction by up to a factor of 3.

Reference-free learning-based similarity metric for motion compensation in cone-beam CT

Purpose. Patient motion artifacts present a prevalent challenge to image quality in interventional cone-beam CT (CBCT). We propose a novel reference-free similarity metric (DL-VIF) that leverages the capability of deep convolutional neural networks (CNN) to learn features associated with motion artifacts within realistic anatomical features. DL-VIF aims to address shortcomings of conventional metrics of motion-induced image quality degradation that favor characteristics associated with motion-free images, such as sharpness or piecewise constancy, but lack any awareness of the underlying anatomy, potentially promoting images depicting unrealistic image content. DL-VIF was integrated in an autofocus motion compensation framework to test its performance for motion estimation in interventional CBCT.Methods. DL-VIF is a reference-free surrogate for the previously reported visual image fidelity (VIF) metric, computed against a motion-free reference, generated using a CNN trained using simulated motion-corrupted and motion-free CBCT data. Relatively shallow (2-ResBlock) and deep (3-Resblock) CNN architectures were trained and tested to assess sensitivity to motion artifacts and generalizability to unseen anatomy and motion patterns. DL-VIF was integrated into an autofocus framework for rigid motion compensation in head/brain CBCT and assessed in simulation and cadaver studies in comparison to a conventional gradient entropy metric.Results. The 2-ResBlock architecture better reflected motion severity and extrapolated to unseen data, whereas 3-ResBlock was found more susceptible to overfitting, limiting its generalizability to unseen scenarios. DL-VIF outperformed gradient entropy in simulation studies yielding average multi-resolution structural similarity index (SSIM) improvement over uncompensated image of 0.068 and 0.034, respectively, referenced to motion-free images. DL-VIF was also more robust in motion compensation, evidenced by reduced variance in SSIM for various motion patterns (σ_DL-VIF = 0.008 versusσ_{gradient entropy} = 0.019). Similarly, in cadaver studies, DL-VIF demonstrated superior motion compensation compared to gradient entropy (an average SSIM improvement of 0.043 (5%) versus little improvement and even degradation in SSIM, respectively) and visually improved image quality even in severely motion-corrupted images.Conclusion: The studies demonstrated the feasibility of building reference-free similarity metrics for quantification of motion-induced image quality degradation and distortion of anatomical structures in CBCT. DL-VIF provides a reliable surrogate for motion severity, penalizes unrealistic distortions, and presents a valuable new objective function for autofocus motion compensation in CBCT.

Angiography suite cone-beam CT perfusion for selection of thrombectomy patients: A pilot study

BACKGROUND AND PURPOSE

The availability of cone-beam CT perfusion (CBCTP) in angiography suites may improve large-vessel occlusion (LVO) triage and reduce reperfusion times for patients presenting during extended time window. We aim to evaluate the perfusion maps correlation and agreement between multidetector CT perfusion (MDCTP) and CBCTP when obtained sequentially in patients undergoing endovascular therapy.

METHODS

This is a prospective, pilot, single-arm interventional cohort study of consecutive patients with anterior circulation LVO. All patients underwent MDCTP and CBCTP prior to endovascular therapy, generating cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and time-to-maximum/time to peak contrast concentration maps. We compared the two imaging modalities using three different methods: (1) six regions of interest (ROIs) placed in the anterior circulation territory; (2) ROIs placed in all 10 Alberta Stroke Program Early CT Score regions; and (3) ROI drawn around the entire ischemic area. ROI ratios (unaffected/affected area) were compared for all sequences in each method. We used the intraclass correlation coefficient to calculate the correlation between the studies. Bland-Altman plots were also created to measure the degree of agreement. Finally, a sensitivity analysis was done comparing both modalities in patients with low infarct growth rate.

RESULTS

Fourteen patients were included (median age 81 years [74-87], 50% males, median National Institutes of Health Stroke Scale 19 [14-22]). Median time between studies was 42 minutes (interquartile range 29-61). Independently of the method used, we found moderate to excellent correlation in CBF, CBV, and MTT between modalities. CBF correlation further improved in patients with low infarct growth.

CONCLUSION

These results demonstrate promising accuracy of CBCTP in evaluating ischemic tissue in patients presenting with LVO ischemic stroke.

Quantitative Automated Segmentation of Lipiodol Deposits on Cone Beam CT Imaging acquired during Transarterial Chemoembolization for Liver Tumors: A Deep Learning Approach

PURPOSE

The purpose of this study was to show that a deep learning-based, automated model for Lipiodol segmentation on CBCT after cTACE performs closer to the "ground truth segmentation" than a conventional thresholding-based model.

MATERIALS & METHODS

This post-hoc analysis included 36 patients with a diagnosis of HCC or other solid liver tumor who underwent cTACE with an intra-procedural CBCT. Semi-automatic segmentation of Lipiodol were obtained. Then, a convolutional U-net model was used to output a binary mask that predicts Lipiodol deposition. A threshold value of signal intensity on CBCT was used to obtain a Lipiodol mask for comparison. Dice similarity coefficient (DSC), Mean-squared error (MSE), and Center of Mass (CM), and fractional volume ratios for both masks were obtained by comparing them to the ground truth (radiologist segmented Lipiodol deposits) to obtain accuracy metrics for the two masks. These results were used to compare the model vs. the threshold technique.

RESULTS

For all metrics, the U-net outperformed the threshold technique: DSC (0.65±0.17 vs. 0.45±0.22,p<0.001) and MSE (125.53±107.36 vs. 185.98±93.82,p=0.005). Difference between the CM predicted, and the actual CM was (15.31±14.63mm vs. 31.34±30.24mm,p<0.001), with lesser distance indicating higher accuracy. The fraction of volume present ([predicted Lipiodol volume]/[ground truth Lipiodol volume]) was 1.22±0.84vs.2.58±3.52,p=0.048 for our model's prediction and threshold technique, respectively.

CONCLUSION

This study showed that a deep learning framework could detect Lipiodol in CBCT imaging and was capable of outperforming the conventionally used thresholding technique over several metrics. Further optimization will allow for more accurate, quantitative predictions of Lipiodol depositions intra-procedurally.

Potential Application of MR-MR-US Fusion Imaging Navigation with Needle Tail Intelligent Positioning in Guiding Puncture in Percutaneous Transforaminal Endoscopic Discectomy

This study sought to investigate the feasibility of using magnetic resonance-magnetic resonance-ultrasound (MR-MR-US) fusion imaging navigation (FIN) with needle tail intelligent positioning (NTIP) to guide puncture in percutaneous transforaminal endoscopic discectomy (PTED). First, in a pig experiment, we found that puncture errors in lumbar intervertebral foramen (LIF) puncture using magnetic resonance-magnetic resonance-ultrasound (MR-MR-US) FIN with NTIP for experienced and novice operators were 2.00 ± 1.00 and 2.57 ± 0.98 mm, respectively (p = 0.231), suggesting this technique was minimally dependent on experience. Then, two experienced surgeons agreed (inter-observer agreement к=0.801) that the quality of MR-MR fusion images was good or sufficient. Finally, we performed PTED in eight patients using MR-MR-US FIN with NTIP, and no significant complications were reported during LIF puncture. Overall, MR-MR-US FIN with NTIP may be a potential application for guiding puncture in PTED, but more clinical studies with a larger sample size are required to further evaluate the advantages of MR-MR-US FIN with NTIP.

Development of an Integrated C-Arm Interventional Imaging System With a Strip Photon Counting Detector and a Flat Panel Detector

Modern interventional x-ray systems are often equipped with flat-panel detector-based cone-beam CT (FPD-CBCT) to provide tomographic, volumetric, and high spatial resolution imaging of interventional devices, iodinated vessels, and other objects. The purpose of this work was to bring an interchangeable strip photon-counting detector (PCD) to C-arm systems to supplement (instead of retiring) the existing FPD-CBCT with a high quality, spectral, and affordable PCD-CT imaging option. With minimal modification to the existing C-arm, a 51×0.6 cm² PCD with a 0.75 mm CdTe layer, two energy thresholds, and 0.1 mm pixels was integrated with a Siemens Artis Zee interventional imaging system. The PCD can be translated in and out of the field-of-view to allow the system to switch between FPD and PCD-CT imaging modes. A dedicated phantom and a new algorithm were developed to calibrate the projection geometry of the narrow-beam PCD-CT system and correct the gantry wobbling-induced geometric distortion artifacts. In addition, a detector response calibration procedure was performed for each PCD pixel using materials with known radiological pathlengths to address concentric artifacts in PCD-CT images. Both phantom and human cadaver experiments were performed at a high gantry rotation speed and clinically relevant radiation dose level to evaluate the spectral and non-spectral imaging performance of the prototype system. Results show that the PCD-CT system has excellent image quality with negligible artifacts after the proposed corrections. Compared with FPD-CBCT images acquired at the same dose level, PCD-CT images demonstrated a 53% reduction in noise variance and additional quantitative imaging capability.

Usefulness of Cone-Beam CT-Based Liver Perfusion Mapping for Evaluating the Response of Hepatocellular Carcinoma to Conventional Transarterial Chemoembolization

We investigated the cone beam computed tomography (CBCT)-based-liver-perfusion-mapping usefulness during transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC) to access treatment response and predict outcomes. From October 2016 to September 2018, 42 patients with HCCs scheduled for conventional TACE were prospectively enrolled. Three reviewers evaluated the unenhanced and contrast-enhanced CBCT and CBCT-based-liver-perfusion-mapping of each tumor. Parenchymal blood volume (PBV) was measured. The operator’s judgment on the technical results was recorded. Response outcome was determined on follow-up CT or magnetic resonance imaging, according to the modified Response Evaluation Criteria in Solid Tumors. Diagnostic performance for detection of a viable tumor was evaluated using multiple logistic regression with C-statistics. CBCT-based-liver-perfusion-mapping and the maximum PBV of the tumor were significant in multiple logistic regression analysis of response (p < 0.0001, p = 0.0448, respectively), with C-statistics of 0.9540 and 0.7484, respectively. Diagnostic accuracy of operator’s judgment was 79.66% (95%CI 69.39%–89.93%). Diagnostic performance of CBCT-based-liver-perfusion-mapping showed a high concordance in three reviewers. The mean PBV of tumor, maximum PBV of tumor, and mean PBV of liver significantly decreased after TACE (each p < 0.001). In ROC curve analysis, the AUC for prediction of residual tumor by the maximum PBV of tumor after TACE was 0.7523, with 80.8% sensitivity and 60.6% specificity.

Three-dimensional regions-of-interest-based intra-operative four-dimensional soft tissue perfusion imaging using a standard x-ray system with no gantry rotation: A simulation study for a proof of concept

PURPOSE

Many interventional procedures aim at changing soft tissue perfusion or blood flow. One problem at present is that soft tissue perfusion and its changes cannot be assessed in an interventional suite because cone-beam computed tomography is too slow (it takes 4-10 s per volume scan). In order to address the problem, we propose a novel method called IPEN for Intra-operative four-dimensional soft tissue PErfusion using a standard x-ray system with No gantry rotation.

METHODS

IPEN uses two input datasets: (a) the contours and locations of three-dimensional regions-of-interest (ROIs) such as arteries and sub-sections of cancerous lesions, and (b) a series of x-ray projection data obtained from an intra-arterial contrast injection to contrast enhancement to wash-out. IPEN then estimates a time-enhancement curve (TEC) for each ROI directly from projections without reconstructing cross-sectional images by maximizing the agreement between synthesized and measured projections with a temporal roughness penalty. When path lengths through ROIs are known for each x-ray beam, the ROI-specific enhancement can be accurately estimated from projections. Computer simulations are performed to assess the performance of the IPEN algorithm. Intra-arterial contrast-enhanced liver scans over 25 s were simulated using XCAT phantom version 2.0 with heterogeneous tissue textures and cancerous lesions. The following four sub-studies were performed: (a) The accuracy of the estimated TECs with overlapped lesions was evaluated at various noise (dose) levels with either homogeneous or heterogeneous lesion enhancement patterns; (b) the accuracy of IPEN with inaccurate ROI contours was assessed; (c) we investigated how overlapping ROIs and noise in projections affected the accuracy of the IPEN algorithm; and (d) the accuracy of the perfusion indices was assessed.

RESULTS

The TECs estimated by IPEN were sufficiently accurate at a reference dose level with the root-mean-square deviation (RMSD) of 0.0027 ± 0.0001 cm^-1 or 13 ± 1 Hounsfield unit (mean ± standard deviation) for the homogeneous lesion enhancement and 0.0032 ± 0.0005 cm^-1 for the heterogeneous enhancement (N = 20 each). The accuracy was degraded with decreasing doses: The RMSD with homogeneous enhancement was 0.0220 ± 0.0003 cm^-1 for 20% of the reference dose level. Performing 3 × 3 pixel averaging on projection data improved the RMSDs to 0.0051 ± 0.0002 cm^-1 for 20% dose. When the ROI contours were inaccurate, smaller ROI contours resulted in positive biases in TECs, whereas larger ROI contours produced negative biases. The bias remained small, within ± 0.0070 cm^-1 , when the Sorenson-Dice coefficients (SDCs) were larger than 0.81. The RMSD of the TEC estimation was strongly associated with the condition of the problem, which can be empirically quantified using the condition number of a matrix A z that maps a vector of ROI enhancement values z to projection data and a weighted variance of projection data: a linear correlation coefficient (R) was 0.794 (P < 0.001). The perfusion index values computed from the estimated TECs agreed well with the true values (R ≥ 0.985, P < 0.0001).

CONCLUSION

The IPEN algorithm can estimate ROI-specific TECs with high accuracy especially when 3 × 3 pixel averaging is applied, even when lesion enhancement is heterogeneous, or ROI contours are inaccurate but the SDC is at least 0.81.

An Enhanced SMART-RECON Algorithm for Time-Resolved C-Arm Cone-Beam CT Imaging

Temporal resolution in time-resolved cone-beam CT (TR-CBCT) imaging is often limited by the time needed to acquire a complete data set for image reconstruction. With the recent developments of performing nearly limited-view artifact-free reconstruction from data in a limited-view angle range and a prior image, temporal resolution of TR-CBCT imaging can be improved. One such an example is the use of Simultaneous Multiple Artifacts Reduction in Tomographic RECONstruction (SMART-RECON) [1] technique. However, with SMART-RECON, one can only improve temporal resolution up to 1 frame per second (fps) which is an improvement of 4.5 times over that of the conventional FBP reconstruction. In this paper, a new technique referred to as enhanced SMART-RECON (eSMART-RECON) was introduced to enhance the temporal performance of SMART-RECON in a multi-sweep CBCT data acquisition protocol. Both numerical simulation studies with ground truth and in vivo human subject studies using C-arm CBCT acquisition systems were conducted to demonstrate the following key results: for a multi-sweep CBCT acquisition protocol, eSMART-RECON enables 4-7.5 fps temporal resolution for TR-CBCT which is 4-7.5 times better than that offered by the original SMART-RECON, and 18-34 times better than that offered by the conventional FBP reconstruction.

Diagnosing Early Ischemic Changes with the Latest-Generation Flat Detector CT: A Comparative Study with Multidetector CT

BACKGROUND AND PURPOSE

One-stop management of mechanical thrombectomy-eligible patients with large-vessel occlusion represents an innovative approach in acute stroke treatment. This approach reduces door-to-reperfusion times by omitting multidetector CT, using flat detector CT as pre-mechanical thrombectomy imaging. The purpose of this study was to compare the diagnostic performance of the latest-generation flat detector CT with multidetector CT.

MATERIALS AND METHODS

Prospectively derived data from patients with ischemic stroke with large-vessel occlusion and mechanical thrombectomy were analyzed in this monocentric study. All included patients underwent multidetector CT before referral to our comprehensive stroke center and flat detector CT in the angiography suite before mechanical thrombectomy. Diagnosis of early ischemic signs, quantified by the ASPECTS, was compared between modalities using cross tables, the Pearson correlation, and Bland-Altman plots. The predictive value of multidetector CT- and flat detector CT-derived ASPECTS for functional outcome was investigated using area under the receiver operating characteristic curve analysis.

RESULTS

Of 25 patients, 24 (96%) had flat detector CT with sufficient diagnostic quality. Median multidetector CT and flat detector CT ASPECTSs were 7 (interquartile range, 5.5-9 and 4.25-8, respectively) with a mean period of 143.6 ± 49.5 minutes between both modalities. The overall sensitivity was 85.1% and specificity was 83.1% for flat detector CT ASPECTS compared with multidetector CT ASPECTS as the reference technique. Multidetector CT and flat detector CT ASPECTS were strongly correlated (r = 0.849, P < .001) and moderately predicted functional outcome (area under the receiver operating characteristic curve, 0.738; P = .007 and .715; P = .069, respectively).

CONCLUSIONS

Determination of ASPECTS on flat detector CT is feasible, showing no significant difference compared with multidetector CT ASPECTS and a similar predictive value for functional outcome. Our findings support the use of flat detector CT for emergency stroke imaging before mechanical thrombectomy to reduce door-to-groin time.

Time-resolved C-arm cone beam CT angiography (TR-CBCTA) imaging from a single short-scan C-arm cone beam CT acquisition with intra-arterial contrast injection

Time-resolved C-arm cone-beam CT (CBCT) angiography (TR-CBCTA) images can be generated from a series of CBCT acquisitions that satisfy data sufficiency condition in analytical image reconstruction theory. In this work, a new technique was developed to generate TR-CBCTA images from a single short-scan CBCT data acquisition with contrast media injection. The reconstruction technique enabling this application is a previously developed image reconstruction technique, synchronized multi-artifact reduction with tomographic reconstruction (SMART-RECON). In this new application, the acquired short-scan CBCT projection data were sorted into a union of several sub-sectors of view angles and each sub-sector of view angles corresponds to an individual image volume to be reconstructed. The SMART-RECON method was then used to jointly reconstruct all of these individual image volumes under two constraints: (1) each individual image volume is maximally consistent with the measured cone-beam projection data within the corresponding view angle sector and (2) the nuclear norm of the image matrix is minimized. The difference between these reconstructed individual image volumes is used to generated the desired subtracted angiograms. To validate the technique, numerical simulation data generated from a fractal tree angiogram phantom were used to quantitatively study the accuracy of the proposed method and retrospective in vivo human subject studies were used to demonstrate the feasibility of generating TR-CBCTA in clinical practice.

Fast acquisition cone-beam computed tomography: initial experience with a 10 s protocol

Background

Cone-beam computed tomography (CBCT) facilitates the acquisition of cross-sectional imaging in angiography suites using a rotational C-arm and digital flat panel detectors. The applications are numerous, including evaluation of implanted devices and localization of cerebrovascular lesions. We present and validate the clinical utility of an alternative fast CBCT acquisition protocol in the context of neurovascular device imaging.

Methods

Contrast-enhanced (CE)-CBCT images were acquired using a new 10 s protocol in a phantom head model, swine model, and in patients. The acquisition parameters of both the 10 s and 20 s protocols were exactly the same, except for fewer projections (250 projections in 10 s vs 500 projections in 20 s), resulting in reduced scan time. Image quality was measured quantitatively in a controlled phantom study and qualitatively by blinded reviewers. The latter was performed to assess the image quality of the 10 s protocol pertinent to the device visibility and its apposition to the parent artery.

Results

10 s CBCT images were comparable to 20 s CBCT in both phantom and animal studies. Of the 25 patient images, the reviewers agreed that they were able to discern the flow diverter struts and assess the apposition in all images. The overall rating for all 10 s images was 4.28 on a 5-point scale. No images were rated as less than 3, which was the average diagnostic quality. The ratings were concordant across three blinded reviewers (κ=0.411). Additionally, contrast and spatial resolution between 10 s and 20 s images were similar in non-human models.

Conclusions

CBCT images of neurovascular devices can be obtained successfully using a 10 s acquisition protocol. In addition, the 10 s protocol offers faster acquisition, thus allowing its use in awake patients and with an added advantage of lower radiation and contrast dose.

Evaluation of Collaterals and Clot Burden Using Time-Resolved C-Arm Conebeam CT Angiography in the Angiography Suite: A Feasibility Study

BACKGROUND AND PURPOSE

The assessment of collaterals and clot burden in patients with acute ischemic stroke provides important information about treatment options and clinical outcome. Time-resolved C-arm conebeam CT angiography has the potential to provide accurate and reliable evaluations of collaterals and clot burden in the angiographic suite. Experience with this technique is extremely limited, and feasibility studies are needed to validate this technique. Our purpose was to present such a feasibility study.

MATERIALS AND METHODS

Ten C-arm conebeam CT perfusion datasets from 10 subjects with acute ischemic stroke acquired before endovascular treatment were retrospectively processed to generate time-resolved conebeam CTA. From time-resolved conebeam CTA, 2 experienced readers evaluated the clot burden and collateral flow in consensus by using previously reported scoring systems and assessed the clinical value of this novel imaging technique independently. Interobserver agreement was analyzed by using the intraclass correlation analysis method.

RESULTS

Clot burden and collateral flow can be assessed by using the commonly accepted scoring systems for all eligible cases. Additional clinical information (eg, the quantitative dynamic information of collateral flow) can be obtained from this new imaging technique. Two readers agreed that time-revolved C-arm conebeam CTA is the preferred method for evaluating the clot burden and collateral flow compared with other conventional imaging methods.

CONCLUSIONS

Comprehensive evaluations of clot burden and collateral flow are feasible by using time-resolved C-arm conebeam CTA data acquired in the angiography suite. This technique further enriches the imaging tools in the angiography suite to enable a "one-stop- shop" imaging workflow for patients with acute ischemic stroke.

Latest generation of flat detector CT as a peri-interventional diagnostic tool: a comparative study with multidetector CT

Background and purpose

Flat detector CT (FDCT) has been used as a peri-interventional diagnostic tool in numerous studies with mixed results regarding image quality and detection of intracranial lesions. We compared the diagnostic aspects of the latest generation FDCT with standard multidetector CT (MDCT).

Materials and methods

102 patients were included in our retrospective study. All patients had undergone interventional procedures. FDCT was acquired peri-interventionally and compared with postinterventional MDCT regarding depiction of ventricular/subarachnoidal spaces, detection of intracranial hemorrhage, and delineation of ischemic lesions using an ordinal scale. Ischemic lesions were quantified with the Alberta Stroke Program Early CT Scale (ASPECTS) on both examinations. Two neuroradiologists with varying grades of experience and a medical student scored the anonymized images separately, blinded to the clinical history.

Results

The two methods were of equal diagnostic value regarding evaluation of the ventricular system and the subarachnoidal spaces. Subarachnoidal, intraventricular, and parenchymal hemorrhages were detected with a sensitivity of 95%, 97%, and 100% and specificity of 97%, 100%, and 99%, respectively, using FDCT. Gray–white differentiation was feasible in the majority of FDCT scans, and ischemic lesions were detected with a sensitivity of 71% on FDCT, compared with MDCT scans. The mean difference in ASPECTS values on FDCT and MDCT was 0.5 points (95% CI 0.12 to 0.88).

Conclusions

The latest generation of FDCT is a reliable and accurate tool for the detection of intracranial hemorrhage. Gray–white differentiation is feasible in the supratentorial region.

Optimized Flat-Detector CT in Stroke Imaging: Ready for First-Line Use?

Background: Using flat-detector CT (FD-CT) for stroke imaging has the advantage that both diagnostic imaging and endovascular therapy can be performed directly within the Angio Suite without any patient transfer and time delay. Thus, stroke management could be speeded up significantly, and patient outcome might be improved. But as precondition for using FD-CT as primary imaging modality, a reliable exclusion of intracranial hemorrhage (ICH) has to be possible. This study aimed to investigate whether optimized native FD-CT, using a newly implemented reconstruction algorithm, may reliably detect ICH in stroke patients. Additionally, the potential to identify ischemic changes was evaluated. Methods: Cranial FD-CT scans were obtained in 102 patients presenting with acute ischemic stroke (n = 32), ICH (n = 45) or transient ischemic attack (n = 25). All scans were reconstructed with a newly implemented half-scan cone-beam algorithm. Two experienced neuroradiologists, unaware of clinical findings, evaluated independently the FD-CTs screening for hemorrhage or ischemic signs. The findings were correlated to CT, and rater and inter-rater agreement was assessed. Results: FD-CT demonstrated high sensitivity (95-100%) and specificity (100%) in detecting intracerebral and intraventricular hemorrhage (IVH). Overall, interobserver agreement (κ = 0.92) was almost perfect and rater agreement to CT highly significant (r = 0.81). One infratentorial ICH and 10 or 11 of 22 subarachnoid hemorrhages (SAHs) were missed of whom 7 were perimesencephalic. The sensitivity for detecting acute ischemic signs was poor in blinded readings (0 or 25%, respectively). Conclusions: Optimized FD-CT, using a newly implemented reconstruction algorithm, turned out as a reliable tool for detecting supratentorial ICH and IVH. However, detection of infratentorial ICH and perimesencephalic SAH is limited. The potential of FD-CT in detecting ischemic changes is poor in blinded readings. Thus, plain FD-CT seems insufficient as a standalone modality in acute stroke, but within a multimodal imaging approach primarily using the FD technology, native FD-CT seems capable to exclude reliably supratentorial hemorrhage. Currently, FD-CT imaging seems not yet ready for wide adoption, replacing regular CT, and should be reserved for selected patients. Furthermore, prospective evaluations are necessary to validate this approach in the clinical setting.