Epicardial fat volume is related to the degree of cardiac allograft vasculopathy.

OBJECTIVES: Increasing evidence suggests a role for epicardial fat in the development of coronary artery disease in the general population. Heart transplantation patients are at increased risk of developing a specific form of coronary artery disease, cardiac allograft vasculopathy (CAV), which has far-reaching consequences in terms of morbidity and mortality. Until now, the role of epicardial fat volume (EFV) in the development of CAV remains unknown. Hence, we investigated the relationship between EFV and CAV as well as the influence of donor/recipient sex on EFV. METHODS: Adult heart transplant patients who underwent coronary computed tomography angiography (CCTA) for CAV screening who were four or more years post-HT were included. Using the CT examinations, we quantified the EFV and the degree of CAV. Ordinal and linear regression models were used to assess the association of EFV with CAV. RESULTS: In total, 149 (median age 44.5 years, 36% women) patients were included. The median time between HT and the CT scan was 11.0 (7.3-16.1) years. CAV grade 0, 1, 2 and 3 were seen in 85 (57%), 32 (22%), 14 (9%), and 18 (12%) patients, respectively. The median EFV was 208.4 (128.9-276.0) mL. Larger EFV were related to higher degrees of CAV (median of 164.7 to 290.6 mL for CAV grade 0 and 3, respectively, OR 5.23 (2.47-11.06), p < 0.001). Male recipients had significantly more EFV than female recipients irrespective of the donor sex (232.7 mL vs. 147.2 mL respectively, p < 0.001). Determinants for EFV were recipient sex, number of rejections, donor age, time between HT and CT scan, recipient BMI, and diabetes mellitus. CONCLUSIONS: EFV was associated with higher degrees of CAV. The recipient sex influenced the EFV more than the donor sex. KEY POINTS: • Patients after heart transplantation have a high amount of epicardial fat while larger amounts of epicardial fat are related to higher grades of cardiac allograft vasculopathy. • Determinants of higher epicardial fat volume included recipient sex, number of rejections, donor age, time between HT and CT scan, recipient BMI, and diabetes mellitus. • Longitudinal studies are needed to further disentangle the role of epicardial fat in the development and progression of cardiac allograft vasculopathy. Demonstration of four patients (from CAV grade 0 to CAV grade 3) in whom epicardial fat volume was determined. In red, the voxels identified as epicardial fat.

Time dependency of automated collateral scores in computed tomography angiography and computed tomography perfusion images in patients with intracranial arterial occlusion.

PURPOSE: The assessment of collateral status may depend on the timing of image acquisition. The purpose of this study is to investigate whether there are optimal time points in CT Perfusion (CTP) for collateral status assessment, and compare collaterals scores at these time points with collateral scores from multiphase CT angiography (mCTA). METHODS: Patients with an acute intracranial occlusion who underwent baseline non-contrast CT, mCTA and CT perfusion were selected. Collateral status was assessed using an automatically computed Collateral Ratio (CR) score in mCTA, and predefined time points in CTP acquisition. CRs extracted from CTP were correlated with CRs from mCTA. In addition, all CRs were related to baseline National Institutes of Health Stroke Scale (NIHSS) and Alberta Stoke Program Early CT Score (ASPECTS) with linear regression analysis to find the optimal CR. RESULTS: In total 58 subjects (median age 74 years; interquartile range 61-83 years; 33 male) were included. When comparing the CRs from the CTP vs. mCTA acquisition, the strongest correlations were found between CR from baseline mCTA and the CR at the maximal intensity projection of time-resolved CTP (r = 0.81) and the CR at the peak of arterial enhancement point (r = 0.78). Baseline mCTA-derived CR had the highest correlation with ASPECTS (ß = 0.36 (95%CI 0.11, 0.61)) and NIHSS (ß = - 0.48 (95%CI - 0.72, - 0.16)). CONCLUSION: Collateral status assessment strongly depends on the timing of acquisition. Collateral scores obtained from mCTA imaging is close to the optimal collateral score obtained from CTP imaging.

Diagnostic performance of an algorithm for automated collateral scoring on computed tomography angiography.

OBJECTIVES: Outcome of endovascular treatment in acute ischemic stroke patients depends on collateral circulation to provide blood supply to the ischemic territory. We evaluated the performance of a commercially available algorithm for assessing the collateral score (CS) in acute ischemic stroke patients. METHODS: Retrospectively, baseline CTA scans (≤ 3-mm slice thickness) with an intracranial carotid artery (ICA), middle cerebral artery segment M1 or M2 occlusion, from the MR CLEAN Registry (n = 1627) were evaluated. All CTA scans were evaluated for visual CS (0-3) by eight expert radiologists (reference standard). A Web-based AI algorithm quantified the collateral circulation (0-100%) for correctly detected occlusion sides. Agreement between visual CS and categorized automated CS (0: 0%, 1: > 0- ≤ 50%, 2: > 50- < 100%, 3: 100%) was assessed. Area under the curve (AUC) values for classifying patients in having good (CS: 2-3) versus poor (CS: 0-1) collaterals and for predicting functional independence (90-day modified Rankin Scale 0-2) were computed. Influence of CTA acquisition timing after contrast material administration was reported. RESULTS: In the analyzed scans (n = 1024), 59% agreement was found between visual CS and automated CS. An AUC of 0.87 (95% CI: 0.85-0.90) was found for discriminating good versus poor CS. Timing of CTA acquisition did not influence discriminatory performance. AUC for predicting functional independence was 0.66 (95% CI 0.62-0.69) for automated CS, similar to visual CS 0.64 (95% CI 0.61-0.68). CONCLUSIONS: The automated CS performs similar to radiologists in determining a good versus poor collateral score and predicting functional independence in acute ischemic stroke patients with a large vessel occlusion. KEY POINTS: • Software for automated quantification of intracerebral collateral circulation on computed tomography angiography performs similar to expert radiologists in determining a good versus poor collateral score. • Software for automated quantification of intracerebral collateral circulation on computed tomography angiography performs similar to expert radiologists in predicting functional independence in acute ischemic stroke patients with a large vessel occlusion. • The timing of computed tomography angiography acquisition after contrast material administration did not influence the performance of automated quantification of the collateral status.

Inter-rater reliability for assessing intracranial collaterals in patients with acute ischemic stroke: comparing 29 raters and an artificial intelligence-based software.

PURPOSE: Outcome of endovascular treatment in acute ischemic stroke patients is depending on the collateral circulation maintaining blood flow to the ischemic territory. We evaluated the inter-rater reliability and accuracy of raters and an automated algorithm for assessing the collateral score (CS, range: 0-3) in acute ischemic stroke patients. METHODS: Baseline CTA scans with an intracranial anterior occlusion from the MR CLEAN study (n=500) were used. For each core lab CS, ten CTA scans with sufficient quality were randomly selected. After a training session in collateral scoring, all selected CTA scans were individually evaluated for a visual CS by three groups: 7 radiologists, 13 junior and 9 senior radiology residents. Two additional radiologists scored CS to be used as reference, with a third providing a CS to produce a 2 out of 3 consensus CS in case of disagreement. An automated algorithm was also used to compute CS. Inter-rater agreement was reported with intraclass correlation coefficient (ICC). Accuracy of visual and automated CS were calculated. RESULTS: 39 CTA scans were assessed (1 corrupt CTA-scan excluded). All groups showed a moderate ICC (0.689-0.780) in comparison to the reference standard. Overall human accuracy was 65± 7% and increased to 88± 5% for dichotomized CS (0-1, 2-3). Automated CS accuracy was 62%, and 90% for dichotomized CS. No significant difference in accuracy was found between groups with different levels of expertise. CONCLUSION: After training, inter-rater reliability in collateral scoring was not influenced by experience. Automated CS performs similar to residents and radiologists in determining a collateral score.

Mesenteric artery calcium scoring: a potential screening method for chronic mesenteric ischemia.

OBJECTIVE: A practical screening tool for chronic mesenteric ischemia (CMI) could facilitate early recognition and reduce undertreatment and diagnostic delay. This study explored the ability to discriminate CMI from non-CMI patients with a mesenteric artery calcium score (MACS). METHODS: This retrospective study included CTAs of consecutive patients with suspected CMI in a tertiary referral center between April 2016 and October 2019. A custom-built software module, using the Agatston definition, was developed and used to calculate the MACS for the celiac artery (CA), superior mesenteric artery (SMA), and inferior mesenteric artery. Scoring was performed by two blinded observers. Interobserver agreement was determined using 39 CTAs scored independently by both observers. CMI was defined as sustained symptom improvement after treatment. Non-CMI patients were patients not diagnosed with CMI after a diagnostic workup and patients not responding to treatment. RESULTS: The MACS was obtained in 184 patients, 49 CMI and 135 non-CMI. Interobserver agreement was excellent (intraclass correlation coefficient 0.910). The MACS of all mesenteric arteries was significantly higher in CMI patients than in non-CMI patients. ROC analysis of the combined MACS of CA + SMA showed an acceptable AUC (0.767), high sensitivity (87.8%), and high NPV (92.1%), when using a ≥ 29.7 CA + SMA MACS cutoff. Comparison of two CTAs, obtained in the same patient at different points in time with different scan and reconstruction parameters, was performed in 29 patients and revealed significant differences in MACSs. CONCLUSION: MACS seems a promising screening method for CMI, but correction for scan and reconstruction parameters is warranted. KEY POINTS: • A mesenteric artery calcium score obtained in celiac artery and superior mesenteric artery has a high negative predictive value for chronic mesenteric ischemia and could serve as a screening tool. • Interobserver agreement of the mesenteric artery calcium score is excellent. • Scan and reconstruction parameters influence the mesenteric artery calcium score and warrant the development of a method to correct for these parameters.

Validation of automated Alberta Stroke Program Early CT Score (ASPECTS) software for detection of early ischemic changes on non-contrast brain CT scans.

PURPOSE: In ASPECTS, 10 brain regions are scored visually for presence of acute ischemic stroke damage. We evaluated automated ASPECTS in comparison to expert readers. METHODS: Consecutive, baseline non-contrast CT-scans (5-mm slice thickness) from the prospective MR CLEAN trial (n = 459, MR CLEAN Netherlands Trial Registry number: NTR1804) were evaluated. A two-observer consensus for ASPECTS regions (normal/abnormal) was used as reference standard for training and testing (0.2/0.8 division). Two other observers provided individual ASPECTS-region scores. The Automated ASPECTS software was applied. A region score specificity of ≥ 90% was used to determine the software threshold for detection of an affected region based on relative density difference between affected and contralateral region. Sensitivity, specificity, and receiver-operating characteristic curves were calculated. Additionally, we assessed intraclass correlation coefficients (ICCs) for automated ASPECTS and observers in comparison to the reference standard in the test set. RESULTS: In the training set (n = 104), with software thresholds for a specificity of ≥ 90%, we found a sensitivity of 33-49% and an area under the curve (AUC) of 0.741-0.785 for detection of an affected ASPECTS region. In the test set (n = 355), the results for the found software thresholds were 89-89% (specificity), 41-57% (sensitivity), and 0.750-0.795 (AUC). Comparison of automated ASPECTS with the reference standard resulted in an ICC of 0.526. Comparison of observers with the reference standard resulted in an ICC of 0.383-0.464. CONCLUSION: The performance of automated ASPECTS is comparable to expert readers and could support readers in the detection of early ischemic changes.

Feasibility and relevance of discrete vasculature modeling in routine hyperthermia treatment planning.

Purpose: To investigate the effect of patient specific vessel cooling on head and neck hyperthermia treatment planning (HTP). Methods and materials: Twelve patients undergoing radiotherapy were scanned using computed tomography (CT), magnetic resonance imaging (MRI) and contrast enhanced MR angiography (CEMRA). 3D patient models were constructed using the CT and MRI data. The arterial vessel tree was constructed from the MRA images using the 'graph-cut' method, combining information from Frangi vesselness filtering and region growing, and the results were validated against manually placed markers in/outside the vessels. Patient specific HTP was performed and the change in thermal distribution prediction caused by arterial cooling was evaluated by adding discrete vasculature (DIVA) modeling to the Pennes bioheat equation (PBHE). Results: Inclusion of arterial cooling showed a relevant impact, i.e., DIVA modeling predicts a decreased treatment quality by on average 0.19 °C (T90), 0.32 °C (T50) and 0.35 °C (T20) that is robust against variations in the inflow blood rate (|ΔT| < 0.01 °C). In three cases, where the major vessels transverse target volume, notable drops (|ΔT| > 0.5 °C) were observed. Conclusion: Addition of patient-specific DIVA into the thermal modeling can significantly change predicted treatment quality. In cases where clinically detectable vessels pass the heated region, we advise to perform DIVA modeling.

Accuracy of semi-automated versus manual localisation of liver tumours in CT-guided ablation procedures.

OBJECTIVES: To compare the accuracy of liver tumour localisation in intraprocedural computed tomography (CT) images of computer-based rigid registration or non-rigid registration versus mental registration performed by interventional radiologists. METHODS: Retrospectively (2009-2017), 35 contrast-enhanced CT (CECT) images incorporating 56 tumours, acquired during CT-guided ablation procedures and their corresponding pre-procedural diagnostic CECTs were retrieved from the picture archiving and communication system (PACS). The original intraprocedural CECTs were de-enhanced to create a virtually unenhanced CT image (VUCT). Alignment of diagnostic CECTs to their corresponding intraprocedural VUCTs was performed with non-rigid or rigid registration. Mental registration was performed by four interventional radiologists. The original intraprocedural CECT served as the reference standard. Accuracy of tumour localisation was assessed with the target registration error (TRE). Statistical differences were analysed with the Wilcoxon signed-rank test. RESULTS: Non-rigid registration failed to register two CT datasets, incorporating four tumours. In the remaining 33 datasets, non-rigid, rigid and mental registration showed a median TRE of 3.9 mm, 9.0 mm and 10.9 mm, respectively. Non-rigid registration was significantly more accurate in tumour centre localisation in comparison to rigid (p < 0.001) or mental registration (p < 0.001). Rigid registration was not statistically different from mental registration (p = 0.169). Non-rigid registration was most accurate in localising tumour centres in 42 out of 52 tumours (80.8%), while rigid and mental registration were most accurate in only seven (13.5%) and three (5.8%) tumours, respectively. CONCLUSIONS: Computer-based non-rigid registration is statistically significantly more accurate in localising liver tumours in intraprocedural unenhanced CT images in comparison to rigid registration or interventional radiologists' mental mapping abilities. KEY POINTS: • Computer-based non-rigid registration is better (p < 0.001) in localising target tumours prior to ablation in intraprocedural CT images in comparison to rigid registration or interventional radiologists' mental mapping abilities. • Human experts perform sub-optimal localisation of target tumours when relying solely on mental mapping during challenging CT-guided procedures. • This non-rigid registration method shows promising results as a safe alternative to intravenous contrast media in liver tumour localisation prior to ablation during CT-guided procedures.

Quantitative Analysis of Geometry and Lateral Symmetry of Proximal Middle Cerebral Artery.

BACKGROUND: The purpose of our work is to quantitatively assess clinically relevant geometric properties of proximal middle cerebral arteries (pMCA), to investigate the degree of their lateral symmetry, and to evaluate whether the pMCA can be modeled by using state-of-the-art deformable image registration of the ipsi- and contralateral hemispheres. METHODS: Individual pMCA segments were identified, quantified, and statistically evaluated on a set of 55 publicly available magnetic resonance angiography time-of-flight images. Rigid and deformable image registrations were used for geometric alignment of the ipsi- and contralateral hemispheres. Lateral symmetry of relevant geometric properties was evaluated before and after the image registration. RESULTS: No significant lateral differences regarding tortuosity and diameters of contralateral M1 segments of pMCA were identified. Regarding the length of M1 segment, 44% of all subjects could be considered laterally symmetrical. Dominant M2 segment was identified in 30% of men and 9% of women in both brain hemispheres. Deformable image registration performed significantly better (P < .01) than rigid registration with regard to distances between the ipsi- and the contralateral centerlines of M1 segments (1.5 ± 1.1 mm versus 2.8 ± 1.2 mm respectively) and between the M1 and the anterior cerebral artery (ACA) branching points (1.6 ± 1.4 mm after deformable registration). CONCLUSIONS: Although natural lateral variation of the length of M1 may not allow for sufficient modeling of the complete pMCA, deformable image registration of the contralateral brain hemisphere to the ipsilateral hemisphere is feasible for localization of ACA-M1 branching point and for modeling 71 ± 23% of M1 segment.

Accurate 3D temperature dosimetry during hyperthermia therapy by combining invasive measurements and patient-specific simulations.

PURPOSE: Dosimetry during deep local hyperthermia treatments in the head and neck currently relies on a limited number of invasively placed temperature sensors. The purpose of this study was to assess the feasibility of 3D dosimetry based on patient-specific temperature simulations and sensory feedback. MATERIALS AND METHODS: The study includes 10 patients with invasive thermometry applied in at least two treatments. Based on their invasive thermometry, we optimised patient-group thermal conductivity and perfusion values for muscle, fat and tumour using a 'leave-one-out' approach. Next, we compared the accuracy of the predicted temperature (ΔT) and the hyperthermia treatment quality (ΔT50) of the optimisations based on the patient-group properties to those based on patient-specific properties, which were optimised using previous treatment measurements. As a robustness check, and to enable comparisons with previous studies, we optimised the parameters not only for an applicator efficiency factor of 40%, but also for 100% efficiency. RESULTS: The accuracy of the predicted temperature (ΔT) improved significantly using patient-specific tissue properties, i.e. 1.0 °C (inter-quartile range (IQR) 0.8 °C) compared to 1.3 °C (IQR 0.7 °C) for patient-group averaged tissue properties for 100% applicator efficiency. A similar accuracy was found for optimisations using an applicator efficiency factor of 40%, indicating the robustness of the optimisation method. Moreover, in eight patients with repeated measurements in the target region, ΔT50 significantly improved, i.e. ΔT50 reduced from 0.9 °C (IQR 0.8 °C) to 0.4 °C (IQR 0.5 °C) using an applicator efficiency factor of 40%. CONCLUSION: This study shows that patient-specific temperature simulations combined with tissue property reconstruction from sensory data provides accurate minimally invasive 3D dosimetry during hyperthermia treatments: T50 in sessions without invasive measurements can be predicted with a median accuracy of 0.4 °C.

Temperature simulations in hyperthermia treatment planning of the head and neck region: rigorous optimization of tissue properties.

BACKGROUND AND PURPOSE: Hyperthermia treatment planning (HTP) is used in the head and neck region (H&N) for pretreatment optimization, decision making, and real-time HTP-guided adaptive application of hyperthermia. In current clinical practice, HTP is based on power-absorption predictions, but thermal dose-effect relationships advocate its extension to temperature predictions. Exploitation of temperature simulations requires region- and temperature-specific thermal tissue properties due to the strong thermoregulatory response of H&N tissues. The purpose of our work was to develop a technique for patient group-specific optimization of thermal tissue properties based on invasively measured temperatures, and to evaluate the accuracy achievable. PATIENTS AND METHODS: Data from 17 treated patients were used to optimize the perfusion and thermal conductivity values for the Pennes bioheat equation-based thermal model. A leave-one-out approach was applied to accurately assess the difference between measured and simulated temperature (∆T). The improvement in ∆T for optimized thermal property values was assessed by comparison with the ∆T for values from the literature, i.e., baseline and under thermal stress. RESULTS: The optimized perfusion and conductivity values of tumor, muscle, and fat led to an improvement in simulation accuracy (∆T: 2.1 ± 1.2 °C) compared with the accuracy for baseline (∆T: 12.7 ± 11.1 °C) or thermal stress (∆T: 4.4 ± 3.5 °C) property values. CONCLUSION: The presented technique leads to patient group-specific temperature property values that effectively improve simulation accuracy for the challenging H&N region, thereby making simulations an elegant addition to invasive measurements. The rigorous leave-one-out assessment indicates that improvements in accuracy are required to rely only on temperature-based HTP in the clinic.

3D magnetic seed localization for augmented reality in surgery.

PURPOSE: For tumor resection, surgeons need to localize the tumor. For this purpose, a magnetic seed can be inserted into the tumor by a radiologist and, during surgery, a magnetic detection probe informs the distance to the seed for localization. In this case, the surgeon still needs to mentally reconstruct the position of the tumor from the probe's information. The purpose of this study is to develop and assess a method for 3D localization and visualization of the seed, facilitating the localization of the tumor. METHODS: We propose a method for 3D localization of the magnetic seed by extending the magnetic detection probe with a tracking-based localization. We attach a position sensor (QR-code or optical marker) to the probe in order to track its 3D pose (respectively, using a head-mounted display with a camera or optical tracker). Following an acquisition protocol, the 3D probe tip and seed position are subsequently obtained by solving a system of equations based on the distances and the 3D probe poses. RESULTS: The method was evaluated with an optical tracking system. An experimental setup using QR-code tracking (resp. using an optical marker) achieves an average of 1.6 mm (resp. 0.8 mm) 3D distance between the localized seed and the ground truth. Using a breast phantom setup, the average 3D distance is 4.7 mm with a QR-code and 2.1 mm with an optical marker. CONCLUSION: Tracking the magnetic detection probe allows 3D localization of a magnetic seed, which opens doors for augmented reality target visualization during surgery. Such an approach should enhance the perception of the localized region of interest during the intervention, especially for breast tumor resection where magnetic seeds can already be used in the protocol.

Talus-derived reference coordinate system for 3D calcaneal assessment: A novel approach to improve morphological measurements.

In 3D-analysis of the calcaneus, a consistent coordinate system aligned with the original anatomical directions is crucial for pre- and postoperative analysis. This importance stems from the calcaneus's key role in weight-bearing and biomechanical alignment. However, defining a reliable coordinate system based solely on fractured or surgically reconstructed calcanei presents significant challenges. Given its anatomical prominence and consistent orientation, the talus offers a potential solution to this challenge. Our work explores the feasibility of talus-derived coordinate systems for 3D-modeling of the calcaneus across its various conditions. Four methods were tested on nonfractured, fractured and surgically reconstructed calcanei, utilizing Principal Component Analysis, anatomical landmarks, bounding box, and an atlas-based approach. The methods were compared with a self-defined calcaneus reference coordinate system. Additionally, the impact of deviation of the coordinate system on morphological measurements was investigated. Among methods for constructing nonfractured calcanei coordinate systems, the atlas-based method displayed the lowest Root Mean Square value in comparison with the reference coordinate system. For morphological measures like Böhler's Angle and the Critical angle of Gissane, the atlas talus-based system closely aligned with ground truth, yielding differences of 0.6° and 1.2°, respectively, compared to larger deviations seen in other talus-based coordinate systems. In conclusion, all tested methods were feasible for creating a talus derived coordinate system. A talus derived coordinate system showed potential, offering benefits for morphological measurements and clinical scenarios involving fractured and surgically reconstructed calcanei. Further research is recommended to assess the impact of these coordinate systems on surgical planning and outcomes.

CMAN: Cascaded Multi-scale Spatial Channel Attention-guided Network for large 3D deformable registration of liver CT images.

Deformable image registration is an essential component of medical image analysis and plays an irreplaceable role in clinical practice. In recent years, deep learning-based registration methods have demonstrated significant improvements in convenience, robustness and execution time compared to traditional algorithms. However, registering images with large displacements, such as those of the liver organ, remains underexplored and challenging. In this study, we present a novel convolutional neural network (CNN)-based unsupervised learning registration method, Cascaded Multi-scale Spatial-Channel Attention-guided Network (CMAN), which addresses the challenge of large deformation fields using a double coarse-to-fine registration approach. The main contributions of CMAN include: (i) local coarse-to-fine registration in the base network, which generates the displacement field for each resolution and progressively propagates these local deformations as auxiliary information for the final deformation field; (ii) global coarse-to-fine registration, which stacks multiple base networks for sequential warping, thereby incorporating richer multi-layer contextual details into the final deformation field; (iii) integration of the spatial-channel attention module in the decoder stage, which better highlights important features and improves the quality of feature maps. The proposed network was trained using two public datasets and evaluated on another public dataset as well as a private dataset across several experimental scenarios. We compared CMAN with four state-of-the-art CNN-based registration methods and two well-known traditional algorithms. The results show that the proposed double coarse-to-fine registration strategy outperforms other methods in most registration evaluation metrics. In conclusion, CMAN can effectively handle the large-deformation registration problem and show potential for application in clinical practice. The source code is made publicly available at https://github.com/LocPham263/CMAN.git.

Automated image registration of cerebral digital subtraction angiography.

PURPOSE: Our aim is to automatically align digital subtraction angiography (DSA) series, recorded before and after endovascular thrombectomy. Such alignment may enable quantification of procedural success. METHODS: Firstly, we examine the inherent limitations for image registration, caused by the projective characteristics of DSA imaging, in a representative set of image pairs from thrombectomy procedures. Secondly, we develop and assess various image registration methods (SIFT, ORB). We assess these methods using manually annotated point correspondences for thrombectomy image pairs. RESULTS: Linear transformations that account for scale differences are effective in aligning DSA sequences. Two anatomical landmarks can be reliably identified for registration using a U-net. Point-based registration using SIFT and ORB proves to be most effective for DSA registration and are applicable to recordings for all patient sub-types. Image-based techniques are less effective and did not refine the results of the best point-based registration method. CONCLUSION: We developed and assessed an automated image registration approach for cerebral DSA sequences, recorded before and after endovascular thrombectomy. Accurate results were obtained for approximately 85% of our image pairs.

A novel method to perform morphological measurements on three-dimensional (3D) models of the calcaneus based on computed tomography (CT)-imaging.

Background: While current preoperative and postoperative assessment of the fractured and surgically reconstructed calcaneus relies on computed tomography (CT)-imaging, there are no established methods to quantify calcaneus morphology on CT-images. This study aims to develop a semi-automated method for morphological measurements of the calcaneus on three-dimensional (3D) models derived from CT-imaging. Methods: Using CT data, 3D models were created from healthy, fractured, and surgically reconstructed calcanei. Böhler's angle (BA) and Critical angle of Gissane (CAG) were measured on conventional lateral radiographs and corresponding 3D CT reconstructions using a novel point-based method with semi-automatic landmark placement by three observers. Intraobserver and interobserver reliability scores were calculated using intra-class correlation coefficient (ICC). In addition, consensus among observers was calculated for a maximal allowable discrepancy of 5 and 10 degrees for both methods. Results: Imaging data from 119 feet were obtained (40 healthy, 39 fractured, 40 reconstructed). Semi-automated measurements on 3D models of BA and CAG showed excellent reliability (ICC: 0.87-1.00). The manual measurements on conventional radiographs had a poor-to-excellent reliability (ICC: 0.22-0.96). In addition, the percentage of consensus among observers was much higher for the 3D method when compared to conventional two-dimensional (2D) measurements. Conclusions: The proposed method enables reliable and reproducible quantification of calcaneus morphology in 3D models of healthy, fractured and reconstructed calcanei.

CAVE: Cerebral artery-vein segmentation in digital subtraction angiography.

Cerebral X-ray digital subtraction angiography (DSA) is a widely used imaging technique in patients with neurovascular disease, allowing for vessel and flow visualization with high spatio-temporal resolution. Automatic artery-vein segmentation in DSA plays a fundamental role in vascular analysis with quantitative biomarker extraction, facilitating a wide range of clinical applications. The widely adopted U-Net applied on static DSA frames often struggles with disentangling vessels from subtraction artifacts. Further, it falls short in effectively separating arteries and veins as it disregards the temporal perspectives inherent in DSA. To address these limitations, we propose to simultaneously leverage spatial vasculature and temporal cerebral flow characteristics to segment arteries and veins in DSA. The proposed network, coined CAVE, encodes a 2D+time DSA series using spatial modules, aggregates all the features using temporal modules, and decodes it into 2D segmentation maps. On a large multi-center clinical dataset, CAVE achieves a vessel segmentation Dice of 0.84 (±0.04) and an artery-vein segmentation Dice of 0.79 (±0.06). CAVE surpasses traditional Frangi-based k-means clustering (P < 0.001) and U-Net (P < 0.001) by a significant margin, demonstrating the advantages of harvesting spatio-temporal features. This study represents the first investigation into automatic artery-vein segmentation in DSA using deep learning. The code is publicly available at https://github.com/RuishengSu/CAVE_DSA.

Deep reinforcement learning for cerebral anterior vessel tree extraction from 3D CTA images.

Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to treatment decision making. The purpose of our work is to develop a method that can achieve this from routinely acquired computed tomography angiography (CTA) and computed tomography perfusion (CTP) images. To this end, we regard the anterior vessel tree as a set of bifurcations and connected centerlines. The method consists of a proximal policy optimization (PPO) based deep reinforcement learning (DRL) approach for tracking centerlines, a convolutional neural network based bifurcation detector, and a breadth-first vessel tree construction approach taking the tracking and bifurcation detection results as input. We experimentally determine the added values of various components of the tracker. Both DRL vessel tracking and CNN bifurcation detection were assessed in a cross validation experiment using 115 subjects. The anterior vessel tree formation was evaluated on an independent test set of 25 subjects, and compared to interobserver variation on a small subset of images. The DRL tracking result achieves a median overlapping rate until the first error (1.8 mm off the reference standard) of 100, [46, 100] % on 8032 vessels over 115 subjects. The bifurcation detector reaches an average recall and precision of 76% and 87% respectively during the vessel tree formation process. The final vessel tree formation achieves a median recall of 68% and precision of 70%, which is in line with the interobserver agreement.

Towards quantitative digital subtraction perfusion angiography: An animal study.

BACKGROUND: X-ray digital subtraction angiography (DSA) is the imaging modality for peri-procedural guidance and treatment evaluation in (neuro-) vascular interventions. Perfusion image construction from DSA, as a means of quantitatively depicting cerebral hemodynamics, has been shown feasible. However, the quantitative property of perfusion DSA has not been well studied. PURPOSE: To comparatively study the independence of deconvolution-based perfusion DSA with respect to varying injection protocols, as well as its sensitivity to alterations in brain conditions. METHODS: We developed a deconvolution-based algorithm to compute perfusion parametric images from DSA, including cerebral blood volume (CBV D S A $_{DSA}$ ), cerebral blood flow (CBF D S A $_{DSA}$ ), time to maximum (Tmax), and mean transit time (MTT D S A $_{DSA}$ ) and applied it to DSA sequences obtained from two swine models. We also extracted the time intensity curve (TIC)-derived parameters, that is, area under the curve (AUC), peak concentration of the curve, and the time to peak (TTP) from these sequences. Deconvolution-based parameters were quantitatively compared to TIC-derived parameters in terms of consistency upon variations in injection profile and time resolution of DSA, as well as sensitivity to alterations of cerebral condition. RESULTS: Comparing to TIC-derived parameters, the standard deviation (SD) of deconvolution-based parameters (normalized with respect to the mean) are two to five times smaller, indicating that they are more consistent across different injection protocols and time resolutions. Upon ischemic stroke induced in a swine model, the sensitivities of deconvolution-based parameters are equal to, if not higher than, those of TIC-derived parameters. CONCLUSIONS: In comparison to TIC-derived parameters, deconvolution-based perfusion imaging in DSA shows significantly higher quantitative reliability against variations in injection protocols across different time resolutions, and is sensitive to alterations in cerebral hemodynamics. The quantitative nature of perfusion angiography may allow for objective treatment assessment in neurovascular interventions.

Optimized preoperative planning of double outlet right ventricle patients by 3D printing and virtual reality: a pilot study.

OBJECTIVES: In complex double outlet right ventricle (DORV) patients, the optimal surgical approach may be difficult to assess based on conventional 2-dimensional (2D) ultrasound (US) and computed tomography (CT) imaging. The aim of this study is to assess the added value of 3-dimensional (3D) printed and 3D virtual reality (3D-VR) models of the heart used for surgical planning in DORV patients, supplementary to the gold standard 2D imaging modalities. METHODS: Five patients with different DORV subtypes and high-quality CT scans were selected retrospectively. 3D prints and 3D-VR models were created. Twelve congenital cardiac surgeons and paediatric cardiologists, from 3 different hospitals, were shown 2D-CT first, after which they assessed the 3D print and 3D-VR models in random order. After each imaging method, a questionnaire was filled in on the visibility of essential structures and the surgical plan. RESULTS: Spatial relationships were generally better visualized using 3D methods (3D printing/3D-VR) than in 2D. The feasibility of ventricular septum defect patch closure could be determined best using 3D-VR reconstructions (3D-VR 92%, 3D print 66% and US/CT 46%, P < 0.01). The percentage of proposed surgical plans corresponding to the performed surgical approach was 66% for plans based on US/CT, 78% for plans based on 3D printing and 80% for plans based on 3D-VR visualization. CONCLUSIONS: This study shows that both 3D printing and 3D-VR have additional value for cardiac surgeons and cardiologists over 2D imaging, because of better visualization of spatial relationships. As a result, the proposed surgical plans based on the 3D visualizations matched the actual performed surgery to a greater extent.