Cerebral CTA with Low Tube Voltage and Low Contrast Material Volume for Detection of Intracranial Aneurysms

Neurovascular Imaging with Ultra-High-Resolution Photon-Counting CT: Preliminary Findings on Image-Quality Evaluation

BACKGROUND AND PURPOSE

The first-generation photon-counting detector CT was recently introduced into clinical practice and represents a promising innovation in high-resolution CT imaging. The purpose of this study was to assess the image quality of ultra-high-resolution photon-counting detector CT compared with energy-integrating detector CT and to explore different reconstruction kernel sharpness levels for the evaluation of intracranial aneurysms.

MATERIALS AND METHODS

Ten patients with intracranial saccular aneurysms who had previously undergone conventional energy-integrating detector CT were prospectively enrolled. CT angiograms were acquired on a clinical dual-source photon-counting detector CT in ultra-high-resolution mode and reconstructed with 4 vascular kernels (Bv36, Bv40, Bv44, Bv48). Quantitative and qualitative image-quality parameters of the intracranial arteries were evaluated. For the quantitative analysis (image noise, SNR, contrast-to-noise ratio), ROIs were manually placed at standard anatomic intracranial and extracranial locations by 1 author. In addition, vessel border sharpness was evaluated quantitatively. For the qualitative analysis, 3 blinded neuroradiologists rated photon-counting detector CT and energy-integrating detector CT image quality for the evaluation of the intracranial vessels (ie, the aneurysms and 9 standard vascular branching locations) on a 5-point Likert-type scale. Additionally, readers independently selected their preferred kernel among the 4 kernels evaluated on photon-counting detector CT.

RESULTS

In terms of quantitative image quality, Bv48, the sharpest kernel, yielded increased image noise and decreased SNR and contrast-to-noise ratio parameters compared with Bv36, the smoothest kernel. Compared with energy-integrating detector CT, the Bv48 kernel offered better quantitative image quality for the evaluation of small intracranial vessels (P < .001). Image-quality ratings of the Bv48 were superior to those of the energy-integrating detector CT and not significantly different from ratings of the B44 reconstruction kernel. When comparing side by side all 4 photon-counting detector reconstruction kernels, readers selected the B48 kernel as the best to visualize the aneurysms in 80% of cases.

CONCLUSIONS

Ultra-high-resolution photon-counting detector CT provides improved image quality for neurovascular imaging. Although the less sharp kernels provided superior SNR and contrast-to-noise ratio, the sharpest kernels delivered the best subjective image quality on photon-counting detector CT for the evaluation of intracranial aneurysms.

Application of double low-dose mode in left atrial-pulmonary venous computed tomography angiography

This study adopted a 256-slice iCT scanner with the double low-dose mode in left atrial-pulmonary venous computed tomography angiography (CTA) and explored its effect on image quality. 120 patients were included and randomly classified into the Observation group and Control group. Patients in the Control group underwent routine left atrial CTA, while patients in the Observation group performed a double low-dose mode. Other scanning parameters were consistent in the two groups. The Full model-based iterative reconstruction (MBIR) technique was applied to fulfill image reconstruction in observation group. Continuous variables, ordered categorical variables were analyzed by statistical test. The CT values of left atrial in the Observation group were significantly higher than those in the Control group. The exposure doses (ED) and iodine intake were lower in the Observation group, as compared to the Control group. The left atrial-pulmonary venous CTA with the 256-slice iCT scanner in a double low-dose mode can reduce the ED of radiation and iodine contrast while providing high quality images. Comparatively, the ED in the Observation group was reduced by 13% compared with the control, and the iodine intake was reduced by approximately 33%.

Computed Tomography of the Head : A Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose

In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head imaging only. New technological developments, broader availability, and the clinical success of CT led to a steady growth in examination numbers. Most frequent indications for non-contrast CT (NCCT) of the head include the assessment of ischemia and stroke, intracranial hemorrhage and trauma, while CT angiography (CTA) has become the standard for first-line cerebrovascular evaluation; however, resulting improvements in patient management and clinical outcomes come at the cost of radiation exposure, increasing the risk for secondary morbidity. Therefore, radiation dose optimization should always be part of technical advancements in CT imaging but how can the dose be optimized? What dose reduction can be achieved without compromising diagnostic value, and what is the potential of the upcoming technologies artificial intelligence and photon counting CT? In this article, we look for answers to these questions by reviewing dose reduction techniques with respect to the major clinical indications of NCCT and CTA of the head, including a brief perspective on what to expect from current and future developments in CT technology with respect to radiation dose optimization.

Automatic risk prediction of intracranial aneurysm on CTA image with convolutional neural networks and radiomics analysis

BACKGROUND

Intracranial aneurysm (IA) is a nodular protrusion of the arterial wall caused by the localized abnormal enlargement of the lumen of a brain artery, which is the primary cause of subarachnoid hemorrhage. Accurate rupture risk prediction can effectively aid treatment planning, but conventional rupture risk estimation based on clinical information is subjective and time-consuming.

METHODS

We propose a novel classification method based on the CTA images for differentiating aneurysms that are prone to rupture. The main contribution of this study is that the learning-based method proposed in this study leverages deep learning and radiomics features and integrates clinical information for a more accurate prediction of the risk of rupture. Specifically, we first extracted the provided aneurysm regions from the CTA images as 3D patches with the lesions located at their centers. Then, we employed an encoder using a 3D convolutional neural network (CNN) to extract complex latent features automatically. These features were then combined with radiomics features and clinical information. We further applied the LASSO regression method to find optimal features that are highly relevant to the rupture risk information, which is fed into a support vector machine (SVM) for final rupture risk prediction.

RESULTS

The experimental results demonstrate that our classification method can achieve accuracy and AUC scores of 89.78% and 89.09%, respectively, outperforming all the alternative methods.

DISCUSSION

Our study indicates that the incorporation of CNN and radiomics analysis can improve the prediction performance, and the selected optimal feature set can provide essential biomarkers for the determination of rupture risk, which is also of great clinical importance for individualized treatment planning and patient care of IA.

LIVE-Net: Comprehensive 3D vessel extraction framework in CT angiography

The extraction of vessels from computed tomography angiography (CTA) is significant in diagnosing and evaluating vascular diseases. However, due to the anatomical complexity, wide intensity distribution, and small volume proportion of vessels, vessel extraction is laborious and time-consuming, and it is easy to lead to error-prone diagnostic results in clinical practice. This study proposes a novel comprehensive vessel extraction framework, called the Local Iterative-based Vessel Extraction Network (LIVE-Net), to achieve 3D vessel segmentation while tracking vessel centerlines. LIVE-Net contains dual dataflow pathways that work alternately: an iterative tracking network and a local segmentation network. The former can generate the fine-grain direction and radius prediction of a vascular patch by using the attention-embedded atrous pyramid network (aAPN), and the latter can achieve 3D vascular lumen segmentation by constructing the multi-order self-attention U-shape network (MOSA-UNet). LIVE-Net is trained and evaluated on two datasets: the MICCAI 2008 Coronary Artery Tracking Challenge (CAT08) dataset and head and neck CTA dataset from the clinic. Experimental results of both tracking and segmentation show that our proposed LIVE-Net exhibits superior performance compared with other state-of-the-art (SOTA) networks. In the CAT08 dataset, the tracked centerlines have an average overlap of 95.2%, overlap until first error of 91.2%, overlap with the clinically relevant vessels of 98.3%, and error distance inside of 0.21 mm. The corresponding tracking overlap metrics in the head and neck CTA dataset are 96.7%, 91.0%, and 99.8%, respectively. In addition, the results of the consistent experiment also show strong clinical correspondence. For the segmentation of bilateral carotid and vertebral arteries, our method can not only achieve better accuracy with an average dice similarity coefficient (DSC) of 90.03%, Intersection over Union (IoU) of 81.97%, and 95% Hausdorff distance (95%HD) of 3.42 mm , but higher efficiency with an average time of 67.25 s , even three times faster compared to some methods applied in full field view. Both the tracking and segmentation results prove the potential clinical utility of our network.

Toward human intervention-free clinical diagnosis of intracranial aneurysm via deep neural network

Intracranial aneurysm (IA) is an enormous threat to human health, which often results in nontraumatic subarachnoid hemorrhage or dismal prognosis. Diagnosing IAs on commonly used computed tomographic angiography (CTA) examinations remains laborious and time consuming, leading to error-prone results in clinical practice, especially for small targets. In this study, we propose a fully automatic deep-learning model for IA segmentation that can be applied to CTA images. Our model, called Global Localization-based IA Network (GLIA-Net), can incorporate the global localization prior and generates the fine-grain three-dimensional segmentation. GLIA-Net is trained and evaluated on a big internal dataset (1,338 scans from six institutions) and two external datasets. Evaluations show that our model exhibits good tolerance to different settings and achieves superior performance to other models. A clinical experiment further demonstrates the clinical utility of our technique, which helps radiologists in the diagnosis of IAs.

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GLIA-Net is a deep learning method for the clinical diagnosis of IAs

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It can be applied directly to CTA images without any laborious preprocessing

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A clinical study demonstrates its effectiveness in assisting diagnosis

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An IA dataset of 1,338 CTA cases from six institutions is publicly released

Intracranial aneurysms (IAs) are enormous threats to human health with a prevalence of approximately 4%. The rupture of IAs usually causes death or severe damage to the patients. To enhance the clinical diagnosis of IAs, we present a deep learning model (GLIA-Net) for IA detection and segmentation without laborious human intervention, which achieves superior diagnostic performance validated by quantitative evaluations as well as a sophisticated clinical study. We anticipate that the publicly released data and the artificial intelligence technique would help to transform the clinical diagnostics and precision treatments of cerebrovascular diseases. They may also revolutionize the landscape of healthcare and biomedical research in the future.

Iodinated Contrast Agents Reduce the Efficacy of Intravenous Recombinant Tissue-Type Plasminogen Activator in Acute Ischemic Stroke Patients: a Multicenter Cohort Study

This study aimed to investigate whether the application of iodinated contrast agents before intravenous (IV) recombinant tissue plasminogen activator (rt-PA) reduces the efficacy in acute ischemic stroke (AIS) patients. To determine whether the application of iodinated contrast agents before intravenous rt-PA reduces the efficacy in AIS patients. We analyzed our prospectively collected data of consecutive AIS patients receiving IV rt-PA treatment in the MISSION CHINA study. Clinical outcome at 3 months was assessed with modified Rankin Scale (mRS) score and dichotomized into good outcome (0-2) and poor outcome (3-6). Symptomatic intracerebral hemorrhage (sICH) was defined as cerebral hemorrhagic transformation in combination with clinical deterioration of National Institutes of Health Stroke Scale (NIHSS) score ≥ 4 points at 24-h. We performed logistic regression analysis and propensity score matching analysis to investigate the impact of iodinated contrast agents before IV rt-PA on poor outcome and sICH, respectively. A total of 3593 patients were finally included, and iodinated contrast agents were used before IV rt-PA among 859 (23.9%) patients. Patients in the iodinated contrast group were more likely to result in poor outcome (39.9% vs 33.4%, P = 0.001) and sICH (3.4% vs 1.5%, P < 0.001), compared with non-contrast group. Binary logistic regression analysis revealed that the application of iodinated contrast agents was independently associated with poor outcome (OR 1.342; 95% CI 1.103-1.631; P = 0.003) and sICH (OR 1.929; 95% CI 1.153-3.230; P = 0.012), respectively. After propensity score matching, the application of iodinated contrast agents was still independently associated with poor outcome (OR 1.246; 95% CI 1.016-1.531; P = 0.034) and sICH (OR 1.965; 95% CI 1.118-3.456; P = 0.019). Applying iodinated contrast agents before IV rt-PA may reduce the thrombolytic efficacy in AIS patients. Further benefit-risk analysis might be needed when iodinated contrast-used imaging is considered before intravenous thrombolysis.

Radiation dose and image quality in intraoperative CT (iCT) angiography of the brain with stereotactic head frames

OBJECTIVES

Intraoperative CT (iCT) angiography of the brain with stereotactic frames is an integral part of navigated neurosurgery. Validated data regarding radiation dose and image quality in these special examinations are not available. We therefore investigated two iCT protocols in this IRB-approved study.

METHODS

Retrospective analysis of patients, who received a cerebral stereotactic iCT angiography on a 128 slice CT scanner between February 2016 and December 2017. In group A, automated tube current modulation (ATCM; reference value 410 mAs) and automated tube voltage selection (reference value 120 kV) were enabled, and only examinations with a selected voltage of 120 kV were included. In group B, fixed parameters were applied (300 mAs, 120 kV). Radiation dose was measured by assessing the volumetric CT dose index (CTDI_vol), dose length product (DLP) and effective dose (ED). Signal-to-noise ratio (SNR) and image noise were assessed for objective image quality, visibility of arteries and grey-white differentiation for subjective image quality.

RESULTS

Two hundred patients (n = 100 in each group) were included. In group A, median selected tube current was 643 mAs (group B, 300 mAs; p < 0.001). Median values of CTDI_vol, DLP and ED were 91.54 mGy, 1561 mGy cm and 2.97 mSv in group A, and 43.15 mGy, 769 mGy cm and 1.46 mSv in group B (p < 0.001). Image quality did not significantly differ between groups (p > 0.05).

CONCLUSIONS

ATCM yielded disproportionally high radiation dose due to substantial tube current increase at the frame level, while image quality did not improve. Thus, ATCM should preferentially be disabled.

KEY POINTS

• Automated tube current modulation (ATCM) yields disproportionally high radiation dose in intraoperative CT angiography of the brain with stereotactic head frames. • ATCM does not improve overall image quality in these special examinations. • ATCM is not yet optimised for CT angiography of the brain with major extracorporeal foreign materials within the scan range.

Digital subtraction CT angiography for the detection of posterior inferior cerebellar artery aneurysms: comparison with digital subtraction angiography

OBJECTIVE

To evaluate the diagnostic accuracy of digital subtraction CT angiography (DS-CTA) in detecting posterior inferior cerebellar artery (PICA) aneurysms with digital subtraction angiography (DSA) as reference standard.

METHODS

A total of 115 patients, including 56 patients diagnosed with PICA aneurysms by CTA or DSA and 59 non-PICA-aneurysm patients were included in this retrospective study. All patients underwent DS-CTA and DSA. The site of PICA aneurysms and the pattern of haemorrhage were analysed. Sensitivity and specificity of DS-CTA without and with combining haemorrhage pattern in diagnosing PICA aneurysms were evaluated on a per patient and per aneurysm basis with DSA.

RESULTS

Of 115 patients, 56 patients (48.7%) had 61 PICA aneurysms (size range, 1.1-13.5 mm; mean size, 4.9 ± 2.8 mm) on DSA. The sensitivity and specificity in depicting PICA aneurysms were 89.3% and 96.6% on a per patient basis and 90.2% and 93.4% on a per aneurysm basis, while the corresponding values were 94.6% and 96.6% on a per patient basis and 95.1% and 93.4% on a per aneurysm basis when combining with haemorrhage site.

CONCLUSION

DS-CTA has a high sensitivity and specificity in detecting PICA aneurysms compared with DSA. It may be helpful for clinical diagnosis of PICA aneurysms to combine with haemorrhage sites.

KEY POINTS

• CT angiography has a good diagnostic performance in detecting PICA aneurysms. • The haemorrhage location is helpful to detect PICA aneurysms. • Digital subtraction CTA is a preferable diagnostic means for PICA aneurysms.

Comparison of eye-lens doses imparted during interventional and non-interventional neuroimaging techniques for assessment of intracranial aneurysms

Background

A neurointerventional examination of intracranial aneurysms often involves the eye lens in the primary beam of radiation.

Objective

To assess and compare eye-lens doses imparted during interventional and non-interventional imaging techniques for the examination of intracranial aneurysms.

Methods

We performed a phantom study on an anthropomorphic phantom (ATOM dosimetry phantom 702-D; CIRS, Norfolk, Virginia, USA) and assessed eye-lens doses with thermoluminescent dosimeters (TLDs) type 100 (LiF:Mg, Ti) during (1) interventional (depiction of all cerebral arteries with triple 3D-rotational angiography and twice 2-plane DSA anteroposterior and lateral projections) and (2) non-interventional (CT angiography (CTA)) diagnosis of intracranial aneurysms. Eye-lens doses were calculated following recommendations of the ICRP 103. Image quality was analysed in retrospective by two experienced radiologists on the basis of non-interventional and interventional pan-angiography examinations of patients with incidental aneurysms (n=50) on a five-point Likert scale.

Results

The following eye-lens doses were assessed: (1) interventional setting (triple 3D-rotational angiography and twice 2-plane DSA anteroposterior and lateral projections) 12 mGy; (2) non-interventional setting (CTA) 4.1 mGy. Image quality for depiction of intracranial aneurysms (>3 mm) was evaluated as good by both readers for both imaging techniques.

Conclusions

Eye-lens doses are markedly higher during the interventional than during the non-interventional diagnosis of intracranial aneurysms. For the eye-lens dose, CTA offers considerable radiation dose savings in the diagnosis of intracranial aneurysms.