Digital Subtraction Angiography Images Research Articles

Preperitoneal pelvic balloon tamponade-an effective intervention to control pelvic injury hemorrhage in a swine model.

Objective: This study aimed to estimate the effects of the volume of preperitoneal balloon (PPB) on arterial and venous hemorrhage in a swine pelvic fracture model. Methods: Twenty-four swine were randomized into 0-mL, 500-mL, 800-mL, and 1000-mL intra-hematoma PPB groups. They were subjected to open-book pelvic fracture and reproducible injuries in the external iliac artery and vein. The pelvic binder and IH-PPBs with different volumes of fluid were applied to control the active hemorrhage after arterial and venous injuries. The survival time and rate during 60-min observation and digital subtraction angiography (DSA) images were the primary endpoints in this study. Secondary endpoints included survival rate within 70min, peritoneal pressure, hemodynamics, blood loss, infusion fluid, blood pH, and lactate concentration. Results: Our results indicated that the 800-mL and 1000-mL groups had a higher survival rate (0%, 50%, 100% and 100% for 0, 500, 800, and 1000-mL groups respectively; p < 0.0001) and longer survival time (13.83 ± 2.64, 24.50 ± 6.29, 55.00 ± 6.33, and 60.00 ± 0.00min for 0, 500, 800, and 1,000 groups respectively; p < 0.0005) than the 0-mL or 500-mL groups during the 60min observation. Contrastingly, survival rate and time were comparable between 800-mL and 1000-mL groups during the 60-min observation. The IH-PPB volume was associated with an increase in the pressure of the balloon and the preperitoneal pressure but had no effect on the bladder pressure. Lastly, the 1000-mL group had a higher mean arterial pressure and systemic vascular resistance than the 800-mL group. Conclusion: IH-PPB volume-dependently controls vascular bleeding after pelvic fracture in the swine model. IH-PPB with a volume of 800mL and 1000mL efficiently managed pelvic fracture-associated arterial and venous hemorrhage and enhanced survival time and rate in the swine model without evidences of visceral injury.

DFA-Net: Dual multi-scale feature aggregation network for vessel segmentation in X-ray digital subtraction angiography

Even though deep learning is fascinated in fields of coronary vessel segmentation in X-ray angiography and achieves prominent progresses, most of those models probably bring high false and missed detections due to indistinct contrast between coronary vessels and background, especially for tiny sub-branches. Image improvement technique is able to better such contrast, while boosting extraneous information, e.g., other tissues with similar intensities and noise. If incorporating features derived from original and enhanced images, the segmentation performance is improved because those images comprise complementary information from different contrasts. Accordingly, inspired from advantages of contrast improvement and encoding-decoding architecture, a dual multi-scale feature aggregation network (named DFA-Net) is introduced for coronary vessel segmentation in digital subtraction angiography (DSA). DFA-Net integrates the contrast improvement using exponent transformation into a semantic segmentation network that individually accepts original and enhanced images as inputs. Through parameter sharing, multi-scale complementary features are aggregated from different contrasts, which strengthens leaning capabilities of networks, and thus achieves an efficient segmentation. Meanwhile, a risk cross-entropy loss is enforced on the segmentation, for availably decreasing false negatives, which is incorporated with Dice loss for joint optimization of the proposed strategy during training. Experimental results demonstrate that DFA-Net can not only work more robustly and effectively for DSA images under diverse conditions, but also achieve better performance, in comparison with state-of-the-art methods. Consequently, DFA-Net has high fidelity and structure similarity to the reference, providing a way for early diagnosis of cardiovascular diseases.

Artificial Intelligence for Identification of Images with Active Bleeding in Mesenteric and Celiac Arteries Angiography.

The purpose of this study is to evaluate the efficacy of an artificial intelligence (AI) model designed to identify active bleeding in digital subtraction angiography images for upper gastrointestinal bleeding. Angiographic images were retrospectively collected from mesenteric and celiac artery embolization procedures performed between 2018 and 2022. This dataset included images showing both active bleeding and non-bleeding phases from the same patients. The images were labeled as normal versus images that contain active bleeding. A convolutional neural network was trained and validated to automatically classify the images. Algorithm performance was tested in terms of area under the curve, accuracy, sensitivity, specificity, F1 score, positive and negative predictive value. The dataset included 587 pre-labeled images from 142 patients. Of these, 302 were labeled as normal angiogram and 285 as containing active bleeding. The model's performance on the validation cohort was area under the curve 85.0 ± 10.9% (standard deviation) and average classification accuracy 77.43 ± 4.9%. For Youden's index cutoff, sensitivity and specificity were 85.4 ± 9.4% and 81.2 ± 8.6%, respectively. In this study, we explored the application of AI in mesenteric and celiac artery angiography for detecting active bleeding. The results of this study show the potential of an AI-based algorithm to accurately classify images with active bleeding. Further studies using a larger dataset are needed to improve accuracy and allow segmentation of the bleeding.

Superselective Arterial Hyaluronidase Thrombolysis is an Effective Treatment for Hyaluronic Acid-Induced Retinal Artery Occlusion: Study in a Rabbit Model.

There are serious complications associated with hyaluronic acid (HA) facial injections, including vision impairment due to retinal artery ischemia. In this study, we put forth a clinically relevant model of retinal ischemia and reperfusion in rabbit. We used this to verify the efficacy of hyaluronidase intra-artery thrombolysis in the treatment of hyaluronic acid-induced retinal artery occlusion. Retinal artery ischemia was induced by injecting HA into the ophthalmic artery (OA) of adult chinchilla rabbit, and reperfusion was achieved by intra-artery thrombolysis therapy with hyaluronidase following 60min and 4h of occlusion. Digital subtraction angiography (DSA) and fundus fluorescein angiography (FFA) were used to evaluate blood flow in the retina. Electroretinogram (ERG), hematoxylin and eosin staining and transmission electron microscope were used to evaluate the structure and function of the retina after ischemia and reperfusion following 60min and 4h of occlusion. DSA and FFA images confirmed occlusion of the ophthalmic and central retinal arteries, as well as reperfusion after hyaluronidase thrombolysis. ERG indicated retinal dysfunction following ischemia, and thrombolysis partially rescued its impairment following 4h of occlusion. Hematoxylin and eosin staining and TUNEL staining revealed ischemia-induced histological damages in the retina at different time windows, and hyaluronidase thrombolysis partially mitigated these damages. We report a method to establish a HA-induced retinal artery occlusion animal model. Hyaluronidase intra-artery thrombolysis was used to recanalize the embolized OA at different time points. Using our method, we achieved retinal reperfusion, and an improvement was observed in the visual function of rabbits after hyaluronidase thrombolysis following 4h of occlusion. We believe that hyaluronidase intra-artery thrombolysis is an effective method to treat HA-induced retinal artery occlusion in clinic. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Presurgical Simulation for Brain Arteriovenous Malformation

Surgical extirpation of brain arteriovenous malformations(AVMs)requires precise pre-surgical simulation. Utilizing image software, widely used with picture archiving and communication systems(PACS), surgeons can generate simulation images that precisely illustrate the proper feeders, passing arteries, and drainers. The crucial steps for creating informative simulation images include: (1)the free rotation of reconstructed 3D digital subtraction angiography(DSA)images; (2)removal of irrelevant arteries(the most important procedure); and(3)construction of stereo imagery of the "core images." This article presents a detailed description of these procedures.

Training of a deep learning based digital subtraction angiography method using synthetic data.

Digital subtraction angiography (DSA) is a fluoroscopy method primarily used for the diagnosis of cardiovascular diseases (CVDs). Deep learning-based DSA (DDSA) is developed to extract DSA-like images directly from fluoroscopic images, which helps in saving dose while improving image quality. It can also be applied where C-arm or patient motion is present and conventional DSA cannot be applied. However, due to the lack of clinical training data and unavoidable artifacts in DSA targets, current DDSA models still cannot satisfactorily display specific structures, nor can they predict noise-freeimages. In this study, we propose a strategy for producing abundant synthetic DSA image pairs in which synthetic DSA targets are free of typical artifacts and noise commonly found in conventional DSA targets for DDSA modeltraining. More than 7,000 forward-projected computed tomography (CT) images and more than 25,000 synthetic vascular projection images were employed to create contrast-enhanced fluoroscopic images and corresponding DSA images, which were utilized as DSA image pairs for training of the DDSA networks. The CTprojection images and vascular projection images were generated from eight whole-body CT scans and 1,584 3D vascular skeletons, respectively. All vessel skeletons were generated with stochastic Lindenmayer systems. We trained DDSA models on this synthetic dataset and compared them to the trainings on a clinical DSA dataset, which contains nearly 4,000 fluoroscopic x-ray images obtained from different models ofC-arms. We evaluated DDSA models on clinical fluoroscopic data of different anatomies, including the leg, abdomen, and heart. The results on leg data showed for different methods that training on synthetic data performed similarly and sometimes outperformed training on clinical data. The results on abdomen and cardiac data demonstrated that models trained on synthetic data were able to extract clearer DSA-like images than conventional DSA and models trained on clinical data. The models trained on synthetic data consistently outperformed their clinical data counterparts, achieving higher scores in the quantitative evaluation of peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) metrics for DDSA images, as well as accuracy, precision, and Dice scores for segmentation of the DDSAimages. We proposed an approach to train DDSA networks with synthetic DSA image pairs and extract DSA-like images from contrast-enhanced x-ray images directly. This is a potential tool to aid indiagnosis.

Abstract TP211: TICI Scoring Reliability in Proximal vs Distal Vessel Thrombectomy: A Comparative Analysis

Introduction: The extended Thrombolysis in Cerebral Infarction (eTICI) scale has been demonstrated to correlate strongly with clinical outcomes. Thrombectomy has evolved into the pursuit of not only proximal but distal vessel occlusions, however the reliability of eTICI grading for distal occlusions has not been well studied. We aim to study the interrater agreement of proximal as compared to distal occlusions. Methods: A fellowship trained Neurointerventionalist retrospectively scored the Digital Subtraction Angiography(DSA) images of consecutive patients with only isolated proximal (MCA-M1 or ICA-T) or distal occlusions (MCA-M3, ACA, or PCA) that underwent MT at a single comprehensive stroke center (2022 for proximal occlusions and 2015-2022 for distals). We assessed the agreement between the Neurointerventionalist and original report for the ordinal eTICI scale using Fleiss-Cohen’s Weighted Kappa with quadratic weights. TICI distributions were compared using Wilcoxon’s rank sum test. Results: 187 patients were included in the analysis (124 Proximal and 60 patients distal: 32-M3, 20 -ACA, 8-PCA). The distribution of eTICI 0, 2a, 2b50, 2b67, 2c and 3 were comparable between proximal(MCA-M1 or ICA-T) vs distal occlusions (MCA-M3, ACA, or PCA). The Fleiss-Cohen weighted kappa coefficients were assessed. The proximal eTICI score assessment demonstrated moderate reliability with a kappa value of 0.77 (95%CI: 0.67-0.88)(Table 1A), while the distal eTICI score assessment exhibited almost perfect agreement with kappa value of 0.87 (95%CI: 0.71-1.00)(Table 1B). Conclusion: This study underscores comparable reliability of eTICI scores in assessing reperfusion post MT for distal as compared to proximal occlusions.

The effects of anastomoses between anterior and posterior circulation on postoperative prognosis of patients with moyamoya disease.

Moyamoya disease (MMD) is a chronic ischemic cerebrovascular disease. Collateral circulation in MMD has emerged as a research focus. Our aims were to assess the impact of anastomoses between the anterior and posterior circulations on the prognosis of MMD patients. We reviewed the preoperative digital subtraction angiography images of patients with MMD who underwent revascularization surgery at our hospital between March 2014 and May 2020 and divided the patients into two groups: those with anastomoses (PtoA group) and those without anastomoses (non-PtoA group). The differences in follow-up (more than 6months) collateral vessel establishment (Matsushima grade) and the modified Rankin Scale (mRS) were compared between the two groups as well as between the patients with different degrees of anastomoses. The early complications following revascularization were also compared between the two groups. This study included 104 patients with MMD, of which 38 were non-PtoA and 66 were PtoA. There were no significant differences in Matsushima score (P = 0.252) and mRS score (P = 0.066) between the two groups. In addition, Matsushima score (P = 0.243) and mRS score (P = 0.360) did not differ significantly between patients with different degrees of anastomoses. However, the non-PtoA group had a significantly higher rate of cerebral hyperperfusion syndrome (CHS) than the PtoA group (34.2% vs 16.7%, P = 0.041). MMD patients without anastomoses between anterior and posterior circulations preoperatively should be vigilant of the occurrence of CHS in the early stages after revascularization.

Connecting the DOTs: a novel imaging sign on flat-panel detector CT indicating distal vessel occlusions after thrombectomy

BackgroundImmediate non-contrast post-interventional flat-panel detector CT (FPDCT) has been suggested as an imaging tool to assess complications after endovascular therapy (EVT). We systematically investigated a new imaging finding of focal...

3D/2D Vessel Registration Based on Monte Carlo Tree Search and Manifold Regularization.

The augmented intra-operative real-time imaging in vascular interventional surgery, which is generally performed by projecting preoperative computed tomography angiography images onto intraoperative digital subtraction angiography (DSA) images, can compensate for the deficiencies of DSA-based navigation, such as lack of depth information and excessive use of toxic contrast agents. 3D/2D vessel registration is the critical step in image augmentation. A 3D/2D registration method based on vessel graph matching is proposed in this study. For rigid registration, the matching of vessel graphs can be decomposed into continuous states, thus 3D/2D vascular registration is formulated as a search tree problem. The Monte Carlo tree search method is applied to find the optimal vessel matching associated with the highest rigid registration score. For nonrigid registration, we propose a novel vessel deformation model based on manifold regularization. This model incorporates the smoothness constraint of vessel topology into the objective function. Furthermore, we derive simplified gradient formulas that enable fast registration. The proposed technique undergoes evaluation against seven rigid and three nonrigid methods using a variety of data - simulated, algorithmically generated, and manually annotated - across three vascular anatomies: the hepatic artery, coronary artery, and aorta. Our findings show the proposed method's resistance to pose variations, noise, and deformations, outperforming existing methods in terms of registration accuracy and computational efficiency. The proposed method demonstrates average registration errors of 2.14 mm and 0.34 mm for rigid and nonrigid registration, and an average computation time of 0.51 s.

Utility of marking and fusion image-guided technique with cone-beam CT in kidney ruptured haemorrhage without extravascular leakage in angiography: a pilot study.

To explore the feasibility of using marking and fusion image-guided technique with cone-beam CT (CBCT) in cases of kidney ruptured haemorrhage without extravascular leakage in digital subtraction angiography (DSA) images. This is a retrospective case-control study that included 43 patients who underwent transcatheter arterial embolization for kidney ruptured haemorrhage and difficult haemostasis. The patients were divided into two groups: the CBCT group (cases without extravascular leakage observed in angiography) and the control group (cases with clearly identifiable target vessels in angiography). The baseline characteristics and clinical outcomes were collected and analysed. The results showed no statistically significant differences in the duration of the procedure and intraoperative blood transfusion between the control and CBCT groups (P > .05). The study clarified that the CBCT group had a significantly higher rate of improvement of gross haematuria compared to the control group (P < .05). The CBCT group showed a greater increase in haemoglobin and a lesser increase in creatinine. The clinical success rates were 87.5% in the control group and 90.9% in the CBCT group (P > .05). The marking and fusion image-guided technique is useful in cases of kidney ruptured haemorrhage without extravascular leakage of contrast agent. The technique is safe, feasible, and effective, and we believe it is superior to purely DSA-guidance. The use of the marking and fusion image-guided technique is recommended to overcome the challenge of undetectable target vessels during interventional procedures. This technique is considered as non-inferior to purely DSA-guided interventional procedures where the target vessels are clearly identifiable.

Retracted: Digital Subtraction Angiography Image Features under the Deep Learning Algorithm in Cardiovascular Interventional Treatment and Nursing for Vascular Restenosis

Retracted: Digital Subtraction Angiography Image Features under the Deep Learning Algorithm in Cardiovascular Interventional Treatment and Nursing for Vascular Restenosis

Abstract 034: Value of Immediate Flat Panel Perfusion Imaging After Endovascular Therapy: A proof of concept study

Introduction Clinical utility and diagnostic sensitivity of new‐generation flat‐panel computed tomography perfusion imaging (FPCTP) performed immediately after mechanical thrombectomy (MT) is unknown. We aimed to assess whether FPCTP obtained directly after MT could provide additional potentially relevant information on tissue reperfusion status. Methods Qualitative, single‐center analysis of all consecutive acute stroke patients admitted between 06/2019 and 03/2021 who underwent MT and post‐interventional FPCTP (n=26). A core‐lab blinded to technical details and clinical data performed reperfusion grading on post‐interventional digital subtraction angiography (DSA) images and time‐sensitive FPCTP maps. All patients were classified according to agreement between DSA and FPCTP. Results In 10/26 patients FPCTP revealed new, potentially clinically relevant information. Core‐lab adjudicated dichotomized detection of hypoperfusion (present/absent) was concurring in 21/26 (81%) patients. Of these, reperfusion findings showed perfect agreement on location and size in 16 (62%) patients, while in 5 (19%) patients with incomplete reperfusion, FPCTP showed additional hypoperfused areas missed on DSA. Of the remaining five patients subject to disagreement regarding the presence or absence of hypoperfusion, three showed complete reperfusion on DSA but hypoperfusion was noted on FPCTP, whereas two showed incomplete reperfusion on DSA without detectable hypoperfusion on FPCTP. FPCTP findings could have avoided Thrombolysis in Cerebral Infarction (TICI) overestimation in all false‐positive operator‐rated TICI3 cases. Conclusion In both core‐lab and real‐world operator assessment, FPCTP may provide additional clinically relevant information in a considerable percentage of patients undergoing MT. Hence, FPCTP may constitute a new standard for evaluating reperfusion efficacy and informed decision making in the angiography suite.

CROSS SECTIONAL RETROSPECTIVE ANALYTICAL STUDY OF MORPHOMETRY OF INTERNAL CAROTID ARTERY

Background: The internal carotid artery (ICA) is essential for diagnosing and treating cerebrovascular diseases and plays a significant role in the human head and neck circulatory system. Traditional techniques of ICA research have their limitations, but more recent developments in medical imaging—particularly retrospective angiography—offer more thorough evaluation options. Objective: This study aimed to investigate variations and morphometry of the ICA using 2D digital subtraction angiography (DSA) images, with a focus on age and gender-related differences. Methods: The 149 individuals with subarachnoid hemorrhage who had cerebral angiography were included in the research. Analysis was done on 2D ICA pictures without any obvious pathology. PACS imaging techniques were used to measure morphometric characteristics such as the length, angle, and diameter of the ICA segments. Results: According to the study, ICA length and direction were not substantially affected by age, but segment diameters were highly associated with age, indicating that segment diameters decreased with age. However, gender indicated statistically significant variations in several segment sizes, with males typically having greater diameters than females. Gender had little effect on length and orientation. Conclusion: This study sheds light on ICA changes and morphometry, emphasizing age-related diameter decreases and gender-related variations in segment diameters. These findings highlight the need to take age and gender into account when conducting clinical evaluations and cerebrovascular disease therapies.

CASMatching strategy for automated detection and quantification of carotid artery stenosis based on digital subtraction angiography

Background and objectiveAutomated detection and quantification of carotid artery stenosis is a crucial task in establishing a computer-aided diagnostic system for brain diseases. Digital subtraction angiography (DSA) is known as the "gold standard" for carotid stenosis diagnosis. It is commonly used to identify carotid artery stenosis and measure morphological indices of the stenosis. However, using deep learning to detect stenosis based on DSA images and further quantitatively predicting the morphological indices remain a challenge due the absence of prior work. In this paper, we propose a quantitative method for predicting morphological indices of carotid stenosis. MethodsOur method adopts a two-stage pipeline, first locating regions suitable for predicting morphological indices by object detection model, and then using a regression model to predict indices. A novel Carotid Artery Stenosis Matching (CASMatching) strategy is introduced into the object detection to model the matching relationship between a stenosis and multiple normal vessel segments. The proposed Match-ness branch predicts a Match-ness score for each normal vessel segment to indicate the degree of matching to the stenosis. A novel Direction Distance-IoU (2DIoU) loss based on the Distance-IoU loss is proposed to make the model focused more on the bounding box regression in the direction of vessel extension. After detection, the normal vessel segment with the highest Match-ness score and the stenosis are intercepted from the original image, then fed into a regression model to predict morphological indices and calculate the degree of stenosis. ResultsOur method is trained and evaluated on a dataset collected from three different manufacturers' monoplane X-ray systems. The results show that the proposed components in the object detector substantially improve the detection performance of normal vascular segments. For the prediction of morphological indices, our model achieves Mean Absolute Error of 0.378, 0.221, 4.9 on reference vessel diameter (RVD), minimum lumen diameter (MLD) and stenosis degree. ConclusionsOur method can precisely localize the carotid stenosis and the normal vessel segment suitable for predicting RVD of the stenosis, and further achieve accurate quantification, providing a novel solution for the quantification of carotid artery stenosis.

Potential of unilateral combined bypass surgery to accelerate contralateral radiological progression in pediatric moyamoya disease.

Surgical cerebral revascularization is recommended for treating pediatric moyamoya disease (MMD). However, whether unilateral combined bypass surgery can cause disease progression on the contralateral side is uncertain. The study aimed to investigate the vascular architecture and regional cerebral blood flow (rCBF) status of patients with pediatric MMD after successful unilateral combined bypass surgery and to identify the possible risk factors. Pediatric patients diagnosed with MMD and admitted to Xuanwu Hospital who underwent combined bypass surgery between 2019 and 2021 were enrolled. Digital subtraction angiography (DSA) and magnetic resonance imaging (MRI) with arterial spin labeling (ASL) were performed to investigate the vascular architecture and rCBF during surgery and at short-term follow-up. Suzuki's angiographic staging and moyamoya vessel grading system were both used. Progression was defined as an increase in either Suzuki stage or moyamoya vessel grade detected after unilateral surgery. All analyses were performed with conventional statistic methods. A total of 27 successive patients with a median age of 8 [interquartile range (IQR), 5-14] years old were identified. On the non-operated (non-OP) side, 11 (40.7%) patients demonstrated progression, all of whom showed an increase in the moyamoya vessel grade, and 5 also displayed Suzuki stage progression during the median 4.7 (IQR, 3.7-5.7) months follow-up. However, rCBF barely changed on the non-OP side compared to preoperation [preoperation: median, 49.6, (IQR, 42.9-61.1) mL/100 g/min; postoperation: median, 50.2, (IQR, 43.5-59.3) mL/100 g/min; P=0.445]. Combined bypass surgery might accelerate the radiological progression on the contralateral side, which occurs before the decline of rCBF. Those with earlier Suzuki stage MMD of the non-OP side are prone to rapid progression after unilateral combined revascularization.

Drawing time-density curve with Fiji/ImageJ: An alternative approach for parametric coding of cerebral digital subtraction angiography

BackgroundQuantitative spatiotemporal analysis of digital subtraction angiography could support clinical decision making for the management of cerebral vascular disease. However, there is a lack of free and user-friendly applications. The objective of our study is to devise a free and simple solution for parametric coding of digital subtraction angiography. New MethodBy driving the time-density curves in the region of interest, the digital subtraction angiography images were color-coded and quantitatively analyzed using fully open-source and free software (Fiji/ImageJ). The similarity factor (f2) was used to compare the resolution profiles between time-density curves generated with commercial software on the Siemens workstation (syngo iFlow, Siemens Healthcare, Berlin, Germany) and our method. Results and comparison with existing methodSixteen patients diagnosed with acute ischemic stroke resulting from acute occlusion of the distal internal carotid artery or the first segment of the middle cerebral artery were selected for analysis. Angiography images were successfully processed with syngo iFlow and Fiji/ImageJ. The images processed with Fiji/ImageJ provided excellent anatomic and hemodynamic details. In all patients, the similarity factor (f2) values of the time-density curves derived from the same region of interest were 99.90 (range 99.85–99.95). ConclusionsThe ImageJ/Fiji software provides a user-friendly and free alternative for parametric coding of digital subtraction angiography.

Length of Carotid Plaque Impacts Retinal Microvascular Densities of Carotid Artery Stenosis Patients.

We explored the retinal microvascular changes in carotid artery stenosis (CAS) and their relationship with carotid plaque morphology. All participants were diagnosed with carotid artery stenosis by a neurologist. Participants underwent digital subtraction angiography (DSA) and optical coherence tomography angiography (OCTA) imaging. The degree and length of carotid plaque were obtained from the DSA tool. OCTA tool measured the densities in the superficial vascular complex (SVC) and deep vascular complex (DVC). One hundred seventeen patients with CAS patients were included in our data analysis. Eyes with ipsilateral stenosis had reduced retinal microvascular densities when compared to contralateral eyes in patients with CAS (P = 0.016 for SVC, and P = 0.004 for DVC). Microvascular densities correlated with the length of carotid plaque (P = 0.015 for SVC, and P = 0.022 for DVC) in our CAS cohort, although they did not correlate with the degree of carotid plaque (P = 0.264 for SVC, and P = 0.298 for DVC). However, when stratified into moderate and severe subgroups, the degree of carotid plaque correlated with microvascular densities in patients with severe stenosis (P = 0.045 for SVC, and P = 0.038 for DVC). Our study suggests that OCTA can noninvasively detect retinal microvascular changes in patients with CAS and that these changes correlated with the length of the stenosis, but future studies are required to confirm these findings. Noninvasive and rapid acquisition of the OCTA image might have the potential to be used as a screening tool to detect microvascular changes in carotid artery stenosis.

Spatiotemporal frequency domain analysis for blood velocity measurement during embolization procedures.

Currently, determining procedural endpoints and treatment efficacy of vascular interventions is largely qualitative and relies on subjective visual assessment of digital subtraction angiography (DSA) images leading to large interobserver variabilities and poor reproducibility. Quantitative metrics such as the residual blood velocity in embolized vessel branches could help establish objective and reproducible endpoints. Recently, velocity quantification techniques based on a contrast enhanced X-ray sequence such as qDSA and 4D DSA have been proposed. These techniques must be robust, and, to avoid radiation dose concerns, they should be compatible with low dose per frame imageacquisition. To develop and evaluate a technique for robust blood velocity quantification from low dose contrast enhanced X-ray image sequences that leverages the oscillating signal created by pulsatile bloodflow. The proposed spatiotemporal frequency domain (STF) approach quantifies velocities from time attenuation maps (TAMs) representing the oscillating signal over time for all points along a vessel centerline. Due to the time it takes a contrast bolus to travel along the vessel centerline, the resulting TAM resembles a sheared sine wave. The shear angle is related to the velocity and can be determined in the spatiotemporal frequency domain after applying the 2D Fourier transform to the TAM. The approach was evaluated in a straight tube phantom using three different radiation dose levels and compared to ultrasound transit-time-based measurements. The STF velocity results were also compared to previously published approaches for the measurement of blood velocity from contrast enhanced X-ray sequences including shifted least squared (SLS) and phase shift (PHS). Additionally, an in vivo porcine study (n = 8) was performed where increasing amounts of embolic particles were injected into a hepatic or splenic artery with intermittent velocity measurements after each injection to monitor the resulting reduction invelocity. At the lowest evaluated dose level (average air kerma rate 1.3 mGy/s at the interventional reference point), the Pearson correlation between ultrasound and STF velocity measurements was . This was significantly higher ( ) than corresponding correlation results between ultrasound and the previously published SLS and PHS approaches ( and , respectively). In the in vivo study, a reduction in velocity was observed in of cases after injection of 1 mL, after 3 mL, and after 4 mL of embolicparticles. The results show good agreement of the spatiotemporal frequency domain approach with ultrasound even in low dose per frame image sequences. Additionally, the in vivo study demonstrates the ability to monitor the physiological changes due to embolization. This could provide quantitative metrics during vascular procedures to establish objective and reproducibleendpoints.

StrokeNet: An automated approach for segmentation and rupture risk prediction of intracranial aneurysm.

Intracranial Aneurysms (IA) present a complex challenge for neurosurgeons as the risks associated with surgical intervention, such as Subarachnoid Hemorrhage (SAH) mortality and morbidity, may outweigh the benefits of aneurysmal occlusion in some cases. Hence, there is a critical need for developing techniques that assist physicians in assessing the risk of aneurysm rupture to determine which aneurysms require treatment. However, a reliable IA rupture risk prediction technique is currently unavailable. To address this issue, this study proposes a novel approach for aneurysm segmentation and multidisciplinary rupture prediction using 2D Digital Subtraction Angiography (DSA) images. The proposed method involves training a fully connected convolutional neural network (CNN) to segment aneurysm regions in DSA images, followed by extracting and fusing different features using a multidisciplinary approach, including deep features, geometrical features, Fourier descriptor, and shear pressure on the aneurysm wall. The proposed method also adopts a fast correlation-based filter approach to drop highly correlated features from the set of fused features. Finally, the selected fused features are passed through a Decision Tree classifier to predict the rupture severity of the associated aneurysm into four classes: Mild, Moderate, Severe, and Critical. The proposed method is evaluated on a newly developed DSA image dataset and on public datasets to assess its generalizability. The system's performance is also evaluated on DSA images annotated by expert neurosurgeons for the rupture risk assessment of the segmented aneurysm. The proposed system outperforms existing state-of-the-art segmentation methods, achieving an 85 % accuracy against annotated DSA images for the risk assessment of aneurysmal rupture.