4D-DSA: Development and Current Neurovascular Applications

Simulation-informed learning for time-resolved angiographic contrast agent concentration reconstruction

Three-dimensional Digital Subtraction Angiography (3D-DSA) is a well-established X-ray-based technique for visualizing vascular anatomy. Recently, four-dimensional DSA (4D-DSA) reconstruction algorithms have been developed to enable the visualization of volumetric contrast flow dynamics through time-series of volumes. This reconstruction problem is ill-posed mainly due to vessel overlap in the projection direction and geometric vessel foreshortening, which leads to information loss in the recorded projection images. However, knowledge about the underlying fluid dynamics can be leveraged to constrain the solution space. In our work, we implicitly include this information in a neural network-based model that is trained on a dataset of image-based blood flow simulations. The model predicts the spatially averaged contrast agent concentration for each centerline point of the vasculature over time, lowering the overall computational demand. The trained network enables the reconstruction of relative contrast agent concentrations with a mean absolute error of 0.02±0.02 and a mean absolute percentage error of 5.31±9.25 %. Moreover, the network is robust to varying degrees of vessel overlap and vessel foreshortening. Our approach demonstrates the potential of the integration of machine learning and blood flow simulations in time-resolved angiographic contrast agent concentration reconstruction.

Advances in Vascular Diagnostics using Magnetic Particle Imaging (MPI) for Blood Circulation Assessment

Rapid and accurate assessment of conditions characterized by altered blood flow, cardiac blood pooling, or internal bleeding is crucial for diagnosing and treating various clinical conditions. While widely used imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound offer unique diagnostic advantages, they fall short for specific indications due to limited penetration depth and prolonged acquisition times. Magnetic particle imaging (MPI), an emerging tracer-based technique, holds promise for blood circulation assessments, potentially overcoming existing limitations with reduction in background signals and high temporal and spatial resolution, below the millimeter scale. Successful imaging of blood pooling and impaired flow necessitates tracers with diverse circulation half-lives optimized for MPI signal generation. Recent MPI tracers show potential in imaging cardiovascular complications, vascular perforations, ischemia, and stroke. The impressive temporal resolution and penetration depth also position MPI as an excellent modality for real-time vessel perfusion imaging via functional MPI (fMPI). This review summarizes advancements in optimized MPI tracers for imaging blood circulation and analyzes the current state of pre-clinical applications. This work discusses perspectives on standardization required to transition MPI from a research endeavor to clinical implementation and explore additional clinical indications that may benefit from the unique capabilities of MPI.

Reconstructing blood flow in data-poor regimes: a vasculature network kernel for Gaussian process regression

Blood flow reconstruction in the vasculature is important for many clinical applications. However, in clinical settings, the available data are often quite limited. For instance, transcranial Doppler ultrasound is a non-invasive clinical tool that is commonly used in clinical settings to measure blood velocity waveforms at several locations. This amount of data is grossly insufficient for training machine learning surrogate models, such as deep neural networks or Gaussian process regression. In this work, we propose a Gaussian process regression approach based on empirical kernels constructed by data generated from physics-based simulations-enabling near-real-time reconstruction of blood flow in data-poor regimes. We introduce a novel methodology to reconstruct the kernel within the vascular network. The proposed kernel encodes both spatiotemporal and vessel-to-vessel correlations, thus enabling blood flow reconstruction in vessels that lack direct measurements. We demonstrate that any prediction made with the proposed kernel satisfies the conservation of mass principle. The kernel is constructed by running stochastic one-dimensional blood flow simulations, where the stochasticity captures the epistemic uncertainties, such as lack of knowledge about boundary conditions and uncertainties in vasculature geometries. We demonstrate the performance of the model on three test cases, namely, a simple Y-shaped bifurcation, abdominal aorta and the circle of Willis in the brain.

Most Promising Approaches to Improve Brain AVM Management: ARISE I Consensus Recommendations

Brain arteriovenous malformations (bAVMs) are complex, and rare arteriovenous shunts that present with a wide range of signs and symptoms, with intracerebral hemorrhage being the most severe. Despite prior societal position statements, there is no consensus on the management of these lesions. ARISE (Aneurysm/bAVM/cSDH Roundtable Discussion With Industry and Stroke Experts) was convened to discuss evidence-based approaches and enhance our understanding of these complex lesions. ARISE identified the need to develop scales to predict the risk of rupture of bAVMs, and the use of common data elements to perform prospective registries and clinical studies. Additionally, the group underscored the need for comprehensive patient management with specialized centers with expertise in cranial and spinal microsurgery, neurological endovascular surgery, and stereotactic radiosurgery. The collection of prospective multicenter data and gross specimens was deemed essential for improving bAVM characterization, genetic evaluation, and phenotyping. Finally, bAVMs should be managed within a multidisciplinary framework, with clinical studies and research conducted collaboratively across multiple centers, harnessing the collective expertise and centralization of resources.

ARISE I Consensus Review on the Management of Intracranial Aneurysms

BACKGROUND

Intracranial aneurysms (IAs) remain a challenging neurological diagnosis associated with significant morbidity and mortality. There is a plethora of microsurgical and endovascular techniques for the treatment of both ruptured and unruptured aneurysms. There is no definitive consensus as to the best treatment option for this cerebrovascular pathology. The Aneurysm, Arteriovenous Malformation, and Chronic Subdural Hematoma Roundtable Discussion With Industry and Stroke Experts discussed best practices and the most promising approaches to improve the management of brain aneurysms.

METHODS

A group of experts from academia, industry, and federal regulators convened to discuss updated clinical trials, scientific research on preclinical system models, management options, screening and monitoring, and promising novel device technologies, aiming to improve the outcomes of patients with IA.

RESULTS

Aneurysm, Arteriovenous Malformation, and Chronic Subdural Hematoma Roundtable Discussion With Industry and Stroke Experts suggested the incorporation of artificial intelligence to capture sequential aneurysm growth, identify predictors of rupture, and predict the risk of rupture to guide treatment options. The consensus strongly recommended nationwide systemic data collection of unruptured IA radiographic images for the analysis and development of machine learning algorithms for rupture risk. The consensus supported centers of excellence for preclinical multicenter trials in areas such as genetics, cellular composition, and radiogenomics. Optical coherence tomography and magnetic resonance imaging contrast-enhanced 3T vessel wall imaging are promising technologies; however, more data are needed to define their role in IA management. Ruptured aneurysms are best managed at large volume centers, which should include comprehensive patient management with expertise in microsurgery, endovascular surgery, neurology, and neurocritical care.

CONCLUSIONS

Clinical and preclinical studies and scientific research on IA should engage high-volume centers and be conducted in multicenter collaborative efforts. The future of IA diagnosis and monitoring could be enhanced by the incorporation of artificial intelligence and national radiographic and biologic registries. A collaborative effort between academic centers, government regulators, and the device industry is paramount for the adequate management of IA and the advancement of the field.

Interdisciplinary Management of Vascular Anomalies in the Head and Neck

Vascular anomalies in the head and neck area are usually rare diseases and pose a particular diagnostic and therapeutic challenge. They are divided into vascular tumours and vascular malformations. A distinction is made between benign tumours, such as infantile haemangioma, and rare malignant tumours, such as angiosarcoma. Vascular malformations are categorised as simple malformations, mixed malformations, large vessel anomalies and those associated with other anomalies. Treatment is interdisciplinary and various modalities are available. These include clinical observation, sclerotherapy, embolisation, ablative and coagulating procedures, surgical resection and systemic drug therapy. Treatment is challenging, as vascular anomalies in the head and neck region practically always affect function and aesthetics. A better understanding of the genetic and molecular biological basis of vascular anomalies has recently led to clinical research into targeted drug therapies. This article provides an up-to-date overview of the diagnosis, clinic and treatment of vascular anomalies in the head and neck region.

Enhancing cerebral vasculature analysis with pathlength-corrected 2D angiographic parametric imaging: A feasibility study

BACKGROUND

2D angiographic parametric imaging (API) quantitatively extracts imaging biomarkers related to contrast flow and is conventionally applied to 2D digitally subtracted angiograms (DSA's). In the interventional suite, API is typically performed using 1-2 projection views and is limited by vessel overlap, foreshortening, and depth-integration of contrast motion.

PURPOSE

This work explores the use of a pathlength-correction metric to overcome the limitations of 2D-API: the primary objective was to study the effect of converting 3D contrast flow to projected contrast flow using a simulated angiographic framework created with computational fluid dynamics (CFD) simulations, thereby removing acquisition variability.

METHODS

The pathlength-correction framework was applied to in-silico angiograms, generating a reference (i.e., ground-truth) volumetric contrast distribution in four patient-specific intracranial aneurysm geometries. Biplane projections of contrast flow were created from the reference volumetric contrast distributions, assuming a cone-beam geometry. A Parker-weighted reconstruction was performed to obtain a binary representation of the vessel structure in 3D. Standard ray tracing techniques were then used to track the intersection of a ray from the focal spot with each voxel of the reconstructed vessel wall to a pixel in the detector plane. The lengths of each ray through the 3D vessel lumen were then projected along each ray-path to create a pathlength-correction map, where the pixel intensity in the detector plane corresponds to the vessel width along each source-detector ray. By dividing the projection sequences with this correction map, 2D pathlength-corrected in-silico angiograms were obtained. We then performed voxel-wise (3D) API on the ground-truth contrast distribution and compared it to pixel-wise (2D) API, both with and without pathlength correction for each biplane view. The percentage difference (PD) between the resultant API biomarkers in each dataset were calculated within the aneurysm region of interest (ROI).

RESULTS

Intensity-based API parameters, such as the area under the curve (AUC) and peak height (PH), exhibited notable changes in magnitude and spatial distribution following pathlength correction: these now accurately represent conservation of mass of injected contrast media within each arterial geometry and accurately reflect regions of stagnation and recirculation in each aneurysm ROI. Improved agreement was observed between these biomarkers in the pathlength-corrected biplane maps: the maximum PD within the aneurysm ROI is 3.3% with pathlength correction and 47.7% without pathlength correction. As expected, improved agreement with ROI-averaged ground-truth 3D counterparts was observed for all aneurysm geometries, particularly large aneurysms: the maximum PD for both AUC and PH was 5.8%. Temporal parameters (mean transit time, MTT, time-to-peak, TTP, time-to-arrival, TTA) remained unaffected after pathlength correction.

CONCLUSIONS

This study indicates that the values of intensity-based API parameters obtained with conventional 2D-API, without pathlength correction, are highly dependent on the projection orientation, and uncorrected API should be avoided for hemodynamic analysis. The proposed metric can standardize 2D API-derived biomarkers independent of projection orientation, potentially improving the diagnostic value of all acquired 2D-DSA's. Integration of a pathlength correction map into the imaging process can allow for improved interpretation of biomarkers in 2D space, which may lead to improved diagnostic accuracy during procedures involving the cerebral vasculature.

Interleaved x-ray imaging: A method for simultaneous acquisition of quantitative and diagnostic digital subtraction angiography

BACKGROUND

Flow altering angiographic procedures suffer from ill-defined, qualitative endpoints. Quantitative digital subtraction angiography (qDSA) is an emerging technology that aims to address this issue by providing intra-procedural blood velocity measurements from time-resolved, 2D angiograms. To date, qDSA has used 30 frame/s DSA imaging, which is associated with high radiation dose rate compared to clinical diagnostic DSA (up to 4 frame/s).

PURPOSE

The purpose of this study is to demonstrate an interleaved x-ray imaging method which decreases the radiation dose rate associated with high frame rate qDSA while simultaneously providing low frame rate diagnostic DSA images, enabling the acquisition of both datasets in a single image sequence with a single injection of contrast agent.

METHODS

Interleaved x-ray imaging combines low radiation dose image frames acquired at a high rate with high radiation dose image frames acquired at a low rate. The feasibility of this approach was evaluated on an x-ray system equipped with research prototype software for x-ray tube control. qDSA blood velocity quantification was evaluated in a flow phantom study for two lower dose interleaving protocols (LD1:3.7 ± 0.02 mGy / s $3.7 \pm 0.02\ {\mathrm{mGy}}/{\mathrm{s}}$ and LD2:1.7 ± 0.04 mGy / s $1.7 \pm 0.04{\mathrm{\ mGy}}/{\mathrm{s}}$ ) and one conventional (full dose) protocol (11.4 ± 0.04 mGy / s ) $11.4 \pm 0.04{\mathrm{\ mGy}}/{\mathrm{s}})$ . Dose was measured at the interventional reference point. Fluid velocities ranging from 24 to 45 cm/s were investigated. Gold standard velocities were measured using an ultrasound flow probe. Linear regression and Bland-Altman analysis were used to compare ultrasound and qDSA.

RESULTS

The LD1 and LD2 interleaved protocols resulted in dose rate reductions of -67.7% and -85.5%, compared to the full dose qDSA scan. For the full dose protocol, the Bland-Altman limits of agreement (LOA) between qDSA and ultrasound velocities were [0.7, 6.7] cm/s with a mean difference of 3.7 cm/s. The LD1 interleaved protocol results were similar (LOA: [0.3, 6.9] cm/s, bias: 3.6 cm/s). The LD2 interleaved protocol resulted in slightly larger LOA: [-2.5, 5.5] cm/s with a decrease in the bias: 1.5 cm/s. Linear regression analysis showed a strong correlation between ultrasound and qDSA derived velocities using the LD1 protocol, with aR 2 ${R}^2$ of0.96 $0.96$ , a slope of1.05 $1.05$ and an offset of1.9 $1.9$  cm/s. Similar values were also found for the LD2 protocol, with aR 2 ${R}^2$ of0.93 $0.93$ , a slope of0.98 $0.98$ and an offset of2.0 $2.0$  cm/s.

CONCLUSIONS

The interleaved method enables simultaneous acquisition of low-dose high-rate images for intra-procedural blood velocity quantification (qDSA) and high-dose low-rate images for vessel morphology evaluation (diagnostic DSA).

Experimental study using phantom models of cerebral aneurysms and 4D-DSA to measure blood flow on 3D-color-coded images

BACKGROUND

The current 3D-iFlow application can only measure the arrival time of contrast media through intensity values. If the flow rate could be estimated by 3D-iFlow, patient-specific hemodynamics could be determined within the scope of normal diagnostic management, eliminating the need for additional resources for blood flow rate estimation.

OBJECTIVE

The aim of this study is to develop and validate a method for measuring the flow rate by data obtained from 3D-iFlow images - a prototype application in Four-dimensional digital subtraction angiography (4D-DSA).

METHODS

Using phantom model and experimental circuit with circulating glycerin solution, an equation for the relationship between contrast media intensity and flow rate was developed. Applying the equation to the aneurysm phantom models, the derived flow rate was evaluated.

RESULTS

The average errors between the derived flow rate and setting flow rate became larger when the glycerin flow and the X-rays from the X-ray tube of the angiography system were parallel to each other or when the measurement point included overlaps with other contrast enhanced areas.

CONCLUSION

Although the error increases dependent on the imaging direction and overlap of contrast enhanced area, the developed equation can estimate the flow rate using the image intensity value measured on 3D-iFlow based on 4D-DSA.

Rupture-Risk Stratifying Patients with Cerebral Arteriovenous Malformations Using Quantitative Hemodynamic Flow Measurements

Arteriovenous malformations (AVMs) are high-pressure, low-resistance arterial-venous shunts without intervening capillaries. Up to 60% of AVMs present with an intracranial hemorrhage; however, noninvasive neuroimaging has increasingly diagnosed incidental AVMs. AVM management depends on weighing the lifetime rupture risk against the risks of intervention. Although AVM rupture risk relies primarily on angioarchitectural features, measuring hemodynamic flow is gaining traction. Accurate understanding of AVM hemodynamic flow parameters will help endovascular neurosurgeons and interventional neuroradiologists stratify patients by rupture risk and select treatment plans. This review examines various neuroimaging modalities and their capabilities to quantify AVM flow, as well as the relationship between AVM flow and rupture risk. Quantitative hemodynamic studies on the relationship between AVM flow and rupture risk have not reached a clear consensus; however, the preponderance of data suggests that higher arterial inflow and lower venous outflow in the AVM nidus contribute to increased hemorrhagic risk. Future studies should consider using larger sample sizes and standardized definitions of hemodynamic parameters to reach a consensus. In the meantime, classic angioarchitectural features may be more strongly correlated with AVM rupture than the amount of blood flow.

Feasibility of 4D HDR brachytherapy source tracking using x-ray tomosynthesis: Monte Carlo investigation

PURPOSE

High dose rate (HDR) brachytherapy rapidly delivers dose to targets with steep dose gradients. This treatment method must adhere to prescribed treatment plans with high spatiotemporal accuracy and precision, as failure to do so may degrade clinical outcomes. One approach to achieving this goal is to develop imaging techniques to track HDR sources in vivo in reference to surrounding anatomy. This work investigates the feasibility of using an isocentric C-arm x-ray imager and tomosynthesis methods to track Ir-192 HDR brachytherapy sources in vivo over time (4D).

METHODS

A tomosynthesis imaging workflow was proposed and its achievable source detectability, localization accuracy, and spatiotemporal resolution were investigated in silico. An anthropomorphic female XCAT phantom was modified to include a vaginal cylinder applicator and Ir-192 HDR source (0.5 × 0.5 × 5.0 mm3 ), and the workflow was carried out using the MC-GPU Monte Carlo image simulation platform. Source detectability was characterized using the reconstructed source signal-difference-to-noise-ratio (SDNR), localization accuracy by the absolute 3D error in its measured centroid location, and spatiotemporal resolution by the full-width-at-half-maximum (FWHM) of line profiles through the source in each spatial dimension considering a maximum C-arm angular velocity of 30° per second. The dependence of these parameters on acquisition angular range (θtot = 0°-90°), number of views, angular increment between views (Δθ = 0°-15°), and volumetric constraints imposed in reconstruction was evaluated. Organ voxel doses were tallied to derive the workflow's attributable effective dose.

RESULTS

The HDR source was readily detected and its centroid was accurately localized with the proposed workflow and method (SDNR: 10-40, 3D error: 0-0.144 mm). Tradeoffs were demonstrated for various combinations of image acquisition parameters; namely, increasing the tomosynthesis acquisition angular range improved resolution in the depth-encoded direction, for example from 2.5 mm to 1.2 mm between θtot = 30o and θtot = 90o , at the cost of increasing acquisition time from 1 to 3 s. The best-performing acquisition parameters (θtot = 90o , Δθ = 1°) yielded no centroid localization error, and achieved submillimeter source resolution (0.57 × 1.21 × 5.04 mm3 apparent source dimensions, FWHM). The total effective dose for the workflow was 263 µSv for its required pre-treatment imaging component and 7.59 µSv per mid-treatment acquisition thereafter, which is comparable to common diagnostic radiology exams.

CONCLUSIONS

A system and method for tracking HDR brachytherapy sources in vivo using C-arm tomosynthesis was proposed and its performance investigated in silico. Tradeoffs in source conspicuity, localization accuracy, spatiotemporal resolution, and dose were determined. The results suggest this approach is feasible for localizing an Ir-192 HDR source in vivo with submillimeter spatial resolution, 1-3 second temporal resolution and minimal additional dose burden.

Super-resolution Ultrasound Microvascular Angiography for Spinal Cord Penumbra Imaging

OBJECTIVE

After spinal cord injury (SCI) or ischemia, timely intervention in the penumbra, such as recanalization and tissue reperfusion, is essential for preservation of its function. However, limited by imaging resolution and micro-blood flow sensitivity, golden standard angiography modalities, including magnetic resonance angiography (MRA) and digital subtraction angiography (DSA), are still not applicable for spinal cord microvascular imaging. Regarding spinal cord penumbra, to the best of authors' knowledge, currently, there is no efficient in vivo imaging modality for its evaluation. With tens-of-micrometer resolution and deep penetration, advanced ultrasound localization microscopy (ULM) could potentially meet the needs of emergent diagnosis and long-term monitoring of spinal cord penumbra.

METHODS

ULM microvasculature imaging was performed on rats with all laminae removed to obtain the blood supply in major spinal cord segments (C5-L5). For adult rats with spinal cord penumbra induced by compression injury (1 s, 10 s and 15 s), ULM imaging was conducted. The corresponding angiography results are investigated in terms of microvessel saturation, morphology, and flow velocity. The Basso/Beattie/Bresnahan (BBB) locomotor rating scale and hematoxylin and eosin staining were utilized for model validation and comparison.

RESULTS

The feasibility of ULM enabling spinal cord penumbra imaging and development monitoring was demonstrated. The focal injury core and penumbra can be clearly identified using the proposed method. Significant difference of perfusion can be observed after 1 s, 10 s and 15 s compression. Quantitative results show a high correlation between in vivo ultrasonic angiography, BBB functional evaluation and ex vivo histology assessment under different compression duration.

CONCLUSION

It is demonstrated that the super-resolution ULM micro-vasculature imaging can be used to evaluate the penumbra in spinal cord at acute and early stage of chronic phase, providing an efficient modality for micro-hemodynamics monitoring of the spinal cord.

Head and Neck Arteriovenous Malformations: Clinical Manifestations and Endovascular Treatments

Arteriovenous malformations (AVMs) are vascular malformations that present high-flow direct communication between the arteries and veins, not involving the capillary beds. They can be progressive and lead to various manifestations, including abnormal skin or mucosal findings, ischemia, hemorrhage, and high-output heart failure in severe cases. AVMs often involve the head and neck region. Head and neck AVMs can present region-specific clinical manifestations, angioarchitecture, and complications, especially in cosmetic appearance and ingestion, respiratory, and neuronal functions. Therefore, when planning endovascular treatment of head and neck AVMs, physicians should consider not only the treatment strategy but also the preservation of the cosmetic appearance and critical functions. Knowledge of the functional vascular anatomy as well as treatment techniques should facilitate a successful management. This review summarizes AVMs' clinical manifestations, imaging findings, treatment strategy, and complications.

Imaging of intracranial aneurysms in animals: a systematic review of modalities

Intracranial aneurysm (IA) animal models are paramount to study IA pathophysiology and to test new endovascular treatments. A number of in vivo imaging modalities are available to characterize IAs at different stages of development in these animal models. This review describes existing in vivo imaging techniques used so far to visualize IAs in animal models. We systematically searched for studies containing in vivo imaging of induced IAs in animal models in PubMed and SPIE Digital library databases between 1 January 1945 and 13 July 2022. A total of 170 studies were retrieved and reviewed in detail, and information on the IA animal model, the objective of the study, and the imaging modality used was collected. A variety of methods to surgically construct or endogenously induce IAs in animals were identified, and 88% of the reviewed studies used surgical methods. The large majority of IA imaging in animals was performed for 4 reasons: basic research for IA models, testing of new IA treatment modalities, research on IA in vivo imaging of IAs, and research on IA pathophysiology. Six different imaging techniques were identified: conventional catheter angiography, computed tomography angiography, magnetic resonance angiography, hemodynamic imaging, optical coherence tomography, and fluorescence imaging. This review presents and discusses the advantages and disadvantages of all in vivo IA imaging techniques used in animal models to help future IA studies finding the most appropriate IA imaging modality and animal model to answer their research question.

Validation of SART 3.5D algorithm for cerebrovascular dynamics and artery versus vein classification in presurgical 3D digital subtraction angiographies

Classification of arteries and veins in cerebral angiograms can increase the safety of neurosurgical procedures, such as StereoElectroEncephaloGraphy, and aid the diagnosis of vascular pathologies, as arterovenous malformations. We propose a new method for vessel classification using the contrast medium dynamics in rotational digital subtraction angiography (DSA). After 3D DSA and angiogram segmentation, contrast enhanced projections are processed to suppress soft tissue and bone structures attenuation effect and further enhance the CM flow. For each voxel labelled as vessel, a time intensity curve (TIC) is obtained as a linear combination of temporal basis functions whose weights are addressed by simultaneous algebraic reconstruction technique (SART 3.5D), expanded to include dynamics. Each TIC is classified by comparing the areas under the curve in the arterial and venous phases. Clustering is applied to optimize the classification thresholds. On a dataset of 60 patients, a median value of sensitivity (90%), specificity (91%), and accuracy (92%) were obtained with respect to annotated arterial and venous voxels up to branching order 4–5. Qualitative results are also presented about CM arrival time mapping and its distribution in arteries and veins respectively. In conclusion, this study shows a valuable impact, at no protocol extra-cost or invasiveness, concerning surgical planning related to the enhancement of arteries as major organs at risk. Also, it opens a new scope on the pathophysiology of cerebrovascular dynamics and its anatomical relationships.

Digital subtraction angiography in cerebrovascular disease: current practice and perspectives on diagnosis, acute treatment and prognosis

Digital Subtraction Angiography (DSA) is the gold-standard imaging modality in acute cerebrovascular diagnosis. The role of DSA has become increasingly prominent since the incorporation of endovascular therapy in standards of care for acute ischemic stroke. It is used in the assessment of cerebral vessel patency; however, the therapeutic role of DSA from a prognostic standpoint merits further investigation. The current paper provides an update on current practice on diagnostic, therapeutic and prognostic use of DSA in acute cerebrovascular diseases and various indications and perspectives that may apply, or limit its use, in ongoing surveillance or prognosis. Pre-clinical and clinical studies on the aspects, including but not limited to the morphology of cerebrovasculature in acute ischaemic stroke, are required to delineate and inform its prognostic role.

Ultrasonic Image Feature Analysis under Deep Learning Algorithm to Evaluate the Efficacy of Drug-Coated Balloon for Treatment of Arteriosclerotic Occlusion

In order to explore the adoption of ultrasonic images under deep learning (DL) algorithm to evaluate the efficacy of drug-coated balloon (DCB) for treatment of arteriosclerotic occlusion, 56 patients who underwent DCB surgery of lower limb artery were selected and all the patients received the examinations of algorithmic ultrasound and digital subtraction angiography (DSA) before surgery. According to the examination methods, they were classified into algorithmic ultrasound group and DSA group. One to two months after DCB surgery, ultrasound examination was performed with the region-based faster convolutional neural network (faster R-CNN) target detection algorithm to check the therapeutic effect. The results showed that the image effect processed by the target detection algorithm based on DL was signally better than that of traditional ultrasonic processing algorithm in Dice, precision (Pre), and sensitivity, with significant difference (P < 0.05). Compared with DSA, algorithmic ultrasound showed better consistency between the two groups in the diagnosis of common femoral artery, superficial femoral artery, and popliteal artery stenosis, with statistical significance (P < 0.05). However, for the diagnosis of anterior tibial artery stenosis, the consistency between algorithmic ultrasound and DSA was general. The residual stenosis of each artery segment decreased obviously in postoperative review compared with that before surgery, and the difference was statistically significant (P < 0.05). Besides, both the pulsatility index (PI) and the blood flow velocity of the dorsalis pedis artery increased after surgery, compared with those before surgery, with significant differences (P < 0.05). To sum up, ultrasound based on DL target detection algorithm had good imaging effect and good consistency with DSA, which was of the clinical reference value. Additionally, DCB surgery was helpful to treat arteriosclerosis occlusion and improve limb blood supply, which had clinical adoption value.

Automated detection of arterial landmarks and vascular occlusions in patients with acute stroke receiving digital subtraction angiography using deep learning

BACKGROUND

Digital subtraction angiography (DSA) is the gold-standard method of assessing arterial blood flow and blockages prior to endovascular thrombectomy.

OBJECTIVE

To detect anatomical features and arterial occlusions with DSA using artificial intelligence techniques.

METHODS

We included 82 patients with acute ischemic stroke who underwent DSA imaging and whose carotid terminus was visible in at least one run. Two neurointerventionalists labeled the carotid location (when visible) and vascular occlusions on 382 total individual DSA runs. For detecting the carotid terminus, positive and negative image patches (either containing or not containing the internal carotid artery terminus) were extracted in a 1:1 ratio. Two convolutional neural network architectures (ResNet-50 pretrained on ImageNet and ResNet-50 trained from scratch) were evaluated. Area under the curve (AUC) of the receiver operating characteristic and pixel distance from the ground truth were calculated. The same training and analysis methods were used for detecting arterial occlusions.

RESULTS

The ResNet-50 trained from scratch most accurately detected the carotid terminus (AUC 0.998 (95% CI 0.997 to 0.999), p<0.00001) and arterial occlusions (AUC 0.973 (95% CI 0.971 to 0.975), p<0.0001). Average pixel distances from ground truth for carotid terminus and occlusion localization were 63±45 and 98±84, corresponding to approximately 1.26±0.90 cm and 1.96±1.68 cm for a standard angiographic field-of-view.

CONCLUSION

These results may serve as an unbiased standard for clinical stroke trials, as optimal standardization would be useful for core laboratories in endovascular thrombectomy studies, and also expedite decision-making during DSA-based procedures.

Endovascular treatment in the multimodality management of brain arteriovenous malformations: report of the Society of NeuroInterventional Surgery Standards and Guidelines Committee

BACKGROUND

The purpose of this review is to summarize the data available for the role of angiography and embolization in the comprehensive multidisciplinary management of brain arteriovenous malformations (AVMs METHODS: We performed a structured literature review for studies examining the indications, efficacy, and outcomes for patients undergoing endovascular therapy in the context of brain AVM management. We graded the quality of the evidence. Recommendations were arrived at through a consensus conference of the authors, then with additional input from the full Society of NeuroInterventional Surgery (SNIS) Standards and Guidelines Committee and the SNIS Board of Directors.

RESULTS

The multidisciplinary evaluation and treatment of brain AVMs continues to evolve. Recommendations include: (1) Digital subtraction catheter cerebral angiography (DSA)-including 2D, 3D, and reformatted cross-sectional views when appropriate-is recommended in the pre-treatment assessment of cerebral AVMs. (I, B-NR) . (2) It is recommended that endovascular embolization of cerebral arteriovenous malformations be performed in the context of a complete multidisciplinary treatment plan aiming for obliteration of the AVM and cure. (I, B-NR) . (3) Embolization of brain AVMs before surgical resection can be useful to reduce intraoperative blood loss, morbidity, and surgical complexity. (IIa, B-NR) . (4) The role of primary curative embolization of cerebral arteriovenous malformations is uncertain, particularly as compared with microsurgery and radiosurgery with or without adjunctive embolization. Further research is needed, particularly with regard to risk for AVM recurrence. (III equivocal, C-LD) . (5) Targeted embolization of high-risk features of ruptured brain AVMs may be considered to reduce the risk for recurrent hemorrhage. (IIb, C-LD) . (6) Palliative embolization may be useful to treat symptomatic AVMs in which curative therapy is otherwise not possible. (IIb, B-NR) . (7) The role of AVM embolization as an adjunct to radiosurgery is not well-established. Further research is needed. (III equivocal, C-LD) . (8) Imaging follow-up after apparent cure of brain AVMs is recommended to assess for recurrence. Although non-invasive imaging may be used for longitudinal follow-up, DSA remains the gold standard for residual or recurrent AVM detection in patients with concerning imaging and/or clinical findings. (I, C-LD) . (9) Improved national and international reporting of patients of all ages with brain AVMs, their treatments, side effects from treatment, and their long-term outcomes would enhance the ability to perform clinical trials and improve the rigor of research into this rare condition. (I, C-EO) .

CONCLUSIONS

Although the quality of evidence is lower than for more common conditions subjected to multiple randomized controlled trials, endovascular therapy has an important role in the management of brain AVMs. Prospective studies are needed to strengthen the data supporting these recommendations.

Imaging Modalities for Intracranial Aneurysm: More Than Meets the Eye

Intracranial aneurysms (IA) are often asymptomatic and have a prevalence of 3 to 5% in the adult population. The risk of IA rupture is low, however when it occurs half of the patients dies from subarachnoid hemorrhage (SAH). To avoid this fatal evolution, the main treatment is an invasive surgical procedure, which is considered to be at high risk of rupture. This risk score of IA rupture is evaluated mainly according to its size and location. Therefore, angiography and anatomic imaging of the intracranial aneurysm are crucial for its diagnosis. Moreover, it has become obvious in recent years that several other factors are implied in this complication, such as the blood flow complexity or inflammation. These recent findings lead to the development of new IA imaging tools such as vessel wall imaging, 4D-MRI, or molecular MRI to visualize inflammation at the site of IA in human and animal models. In this review, we will summarize IA imaging techniques used for the patients and those currently in development.

Virtual injections using 4D flow MRI with displacement corrections and constrained probabilistic streamlines

PURPOSE

Streamlines from 4D-flow MRI have been used clinically for intracranial blood-flow tracking. However, deterministic and stochastic errors degrade streamline quality. The purpose of this study is to integrate displacement corrections, probabilistic streamlines, and novel fluid constraints to improve selective blood-flow tracking and emulate "virtual bolus injections."

METHODS

Both displacement artifacts (deterministic) and velocity noise (stochastic) inherently occur during phase-contrast MRI acquisitions. Here, two displacement correction methods, single-step and iterative, were tested in silico with simulated displacements and were compared with ground-truth velocity fields. Next, the effects of combining displacement corrections and constrained probabilistic streamlines were performed in 10 healthy volunteers using time-averaged 4D-flow data. Measures of streamline length and depth into vasculature were then compared with streamlines generated with no corrections and displacement correction alone using one-way repeated-measures analysis of variance and Friedman's tests. Finally, virtual injections with improved streamlines were generated for three intracranial pathology cases.

RESULTS

Iterative displacement correction outperformed the single-step method in silico. In volunteers, the combination of displacement corrections and constrained probabilistic streamlines allowed for significant improvements in streamline length and increased the number of streamlines entering the circle of Willis relative to streamlines with no corrections and displacement correction alone. In the pathology cases, virtual injections with improved streamlines were qualitatively similar to dynamic arterial spin labeling images and allowed for forward/reverse selective flow tracking to characterize cerebrovascular malformations.

CONCLUSION

Virtual injections with improved streamlines from 4D-flow MRI allow for flexible, robust, intracranial flow tracking.

Flat-panel conebeam CT in the clinic: history and current state

Research into conebeam CT concepts began as soon as the first clinical single-slice CT scanner was conceived. Early implementations of conebeam CT in the 1980s focused on high-contrast applications where concurrent high resolution ( < 200    μ m ), for visualization of small contrast-filled vessels, bones, or teeth, was an imaging requirement that could not be met by the contemporaneous CT scanners. However, the use of nonlinear imagers, e.g., x-ray image intensifiers, limited the clinical utility of the earliest diagnostic conebeam CT systems. The development of consumer-electronics large-area displays provided a technical foundation that was leveraged in the 1990s to first produce large-area digital x-ray detectors for use in radiography and then compact flat panels suitable for high-resolution and high-frame-rate conebeam CT. In this review, we show the concurrent evolution of digital flat panel (DFP) technology and clinical conebeam CT. We give a brief summary of conebeam CT reconstruction, followed by a brief review of the correction approaches for DFP-specific artifacts. The historical development and current status of flat-panel conebeam CT in four clinical areas-breast, fixed C-arm, image-guided radiation therapy, and extremity/head-is presented. Advances in DFP technology over the past two decades have led to improved visualization of high-contrast, high-resolution clinical tasks, and image quality now approaches the soft-tissue contrast resolution that is the standard in clinical CT. Future technical developments in DFPs will enable an even broader range of clinical applications; research in the arena of flat-panel CT shows no signs of slowing down.