Functional Impairment in Small Airways Associated With the Breathlessness Symptoms in Long-Coronavirus Disease.

PURPOSE: This study aimed to determine the association between functional impairment in small airways and symptoms of dyspnea in patients with Long-coronavirus disease (COVID), using imaging and computational modeling analysis. PATIENTS AND METHODS: Thirty-four patients with Long-COVID underwent thoracic computed tomography and hyperpolarized Xenon-129 magnetic resonance imaging (HP Xe MRI) scans. Twenty-two answered dyspnea-12 questionnaires. We used a computed tomography-based full-scale airway network (FAN) flow model to simulate pulmonary ventilation. The ventilation distribution projected on a coronal plane and the percentage lobar ventilation modeled in the FAN model were compared with the HP Xe MRI data. To assess the ventilation heterogeneity in small airways, we calculated the fractal dimensions of the impaired ventilation regions in the HP Xe MRI and FAN models. RESULTS: The ventilation distribution projected on a coronal plane showed an excellent resemblance between HP Xe MRI scans and FAN models (structure similarity index: 0.87 ± 0.04). In both the image and the model, the existence of large clustered ventilation defects was not identifiable regardless of dyspnea severity. The percentage lobar ventilation of the HP Xe MRI and FAN model showed a strong correlation (ρ = 0.63, P < 0.001). The difference in the fractal dimension of impaired ventilation zones between the low and high dyspnea-12 score groups was significant (HP Xe MRI: 1.97 [1.89 to 2.04] and 2.08 [2.06 to 2.14], P = 0.005; FAN: 2.60 [2.59 to 2.64] and 2.64 [2.63 to 2.65], P = 0.056). CONCLUSIONS: This study has identified a potential association of small airway functional impairment with breathlessness in Long-COVID, using fractal analysis of HP Xe MRI scans and FAN models.

Gas exchange and ventilation imaging of healthy and COPD subjects using hyperpolarized xenon-129 MRI and a 3D alveolar gas-exchange model.

OBJECTIVES: To investigate the utility of hyperpolarized xenon-129 (HPX) gas-exchange magnetic resonance imaging (MRI) and modeling in a chronic obstructive pulmonary disease (COPD) cohort in comparison to a minimal CT-diagnosed emphysema (MCTE) cohort and a healthy cohort. METHODS: A total of 25 subjects were involved in this study including COPD (n = 8), MCTE (n = 3), and healthy (n = 14) subjects. The COPD subjects were scanned using HPX ventilation, gas-exchange MRI, and volumetric CT. The healthy subjects were scanned using the same HPX gas-exchange MRI protocol with 9 of them scanned twice, 3 weeks apart. The coefficient of variation (CV) was used to quantify image heterogeneities. A three-dimensional computational fluid dynamic (CFD) model of gas exchange was used to derive functional volumes of pulmonary tissue, capillaries, and veins. RESULTS: The CVs of gas distributions in the images showed that there was a statistically significant difference between the COPD and healthy subjects (p < 0.0001). The functional volumes of pulmonary tissue, capillaries, and veins were significantly lower in the subjects with COPD than in the healthy subjects (p < 0.001). The functional volume of pulmonary tissue was found to be (i) statistically different between the healthy and MCTE groups (p = 0.02) and (ii) dependent on the age of the subjects in the healthy group (p = 0.0008) while their CVs (p = 0.13) were not. CONCLUSION: The novel HPX gas-exchange MRI and CFD model distinguished the healthy cohort from the MCTE and COPD cohorts. The proposed technique also showed that the functional volume of pulmonary tissue decreases with aging in the healthy group. KEY POINTS: • The ventilation and gas-exchange imaging with hyperpolarized xenon-129 MRI has enabled the identification of gas-exchange variation between COPD and healthy groups. • This novel technique was promising to be sensitive to minimal CT-diagnosed emphysema and age-related changes in gas-exchange parameter in a small pilot cohort.

Numerical model for cough-generated droplet dispersion on moving escalator with multiple passengers.

To investigate the motion of virus-laden droplets between moving passengers in line, we performed numerical simulations of the distribution of airborne droplets within a geometrically detailed model similar to an actual escalator. The left and right sides and the ceiling of the escalator model were surrounded by walls, assuming a subway used by many people every day with concern to virus-laden droplets. Steps and handrails were incorporated in the model to faithfully compute the escalator-specific flow field. The ascending and descending movements of the escalator were performed with 10 or 5 passengers standing at different boarding intervals. To resolve the unsteady airflow that is excited by a moving boundary consisting of passengers, steps, and handrails, the moving computational domain method based on the moving-grid finite-volume method was applied. On the basis of the consideration that the droplets were small enough, droplet dispersion was computed by solving the equation of virus-laden droplet motion using a pre-computed velocity field, in which the flow rate of a cough, diameter distribution, and evaporation of droplets are incorporated. The simulation resolved the detailed motion of droplets in flow, and therefore, we were able to evaluate the risk of viral adhesion to following passengers. As a result, we found that the ascending escalator had a higher risk of being exposed to virus-laden droplets than the descending escalator. We also reported that the chance of viral droplet adhesion decreases as the distance from the infected person increases, emphasizing the importance of social distancing.

Lung Abnormalities Detected with Hyperpolarized 129Xe MRI in Patients with Long COVID.

Background Post-COVID-19 condition encompasses symptoms following COVID-19 infection that linger at least 4 weeks after the end of active infection. Symptoms are wide ranging, but breathlessness is common. Purpose To determine if the previously described lung abnormalities seen on hyperpolarized (HP) pulmonary xenon 129 (129Xe) MRI scans in participants with post-COVID-19 condition who were hospitalized are also present in participants with post-COVID-19 condition who were not hospitalized. Materials and Methods In this prospective study, nonhospitalized participants with post-COVID-19 condition (NHLC) and posthospitalized participants with post-COVID-19 condition (PHC) were enrolled from June 2020 to August 2021. Participants underwent chest CT, HP 129Xe MRI, pulmonary function testing, and the 1-minute sit-to-stand test and completed breathlessness questionnaires. Control subjects underwent HP 129Xe MRI only. CT scans were analyzed for post-COVID-19 interstitial lung disease severity using a previously published scoring system and full-scale airway network (FAN) modeling. Analysis used group and pairwise comparisons between participants and control subjects and correlations between participant clinical and imaging data. Results A total of 11 NHLC participants (four men, seven women; mean age, 44 years ± 11 [SD]; 95% CI: 37, 50) and 12 PHC participants (10 men, two women; mean age, 58 years ±10; 95% CI: 52, 64) were included, with a significant difference in age between groups (P = .05). Mean time from infection was 287 days ± 79 (95% CI: 240, 334) and 143 days ± 72 (95% CI: 105, 190) in NHLC and PHC participants, respectively. NHLC and PHC participants had normal or near normal CT scans (mean, 0.3/25 ± 0.6 [95% CI: 0, 0.63] and 7/25 ± 5 [95% CI: 4, 10], respectively). Gas transfer (Dlco) was different between NHLC and PHC participants (mean Dlco, 76% ± 8 [95% CI: 73, 83] vs 86% ± 8 [95% CI: 80, 91], respectively; P = .04), but there was no evidence of other differences in lung function. Mean red blood cell-to-tissue plasma ratio was different between volunteers (mean, 0.45 ± 0.07; 95% CI: 0.43, 0.47]) and PHC participants (mean, 0.31 ± 0.10; 95% CI: 0.24, 0.37; P = .02) and between volunteers and NHLC participants (mean, 0.37 ± 0.10; 95% CI: 0.31, 0.44; P = .03) but not between NHLC and PHC participants (P = .26). FAN results did not correlate with Dlco) or HP 129Xe MRI results. Conclusion Nonhospitalized participants with post-COVID-19 condition (NHLC) and posthospitalized participants with post-COVID-19 condition (PHC) showed hyperpolarized pulmonary xenon 129 MRI and red blood cell-to-tissue plasma abnormalities, with NHLC participants demonstrating lower gas transfer than PHC participants despite having normal CT findings. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Parraga and Matheson in this issue.

Impaired pulmonary ventilation beyond pneumonia in COVID-19: A preliminary observation.

BACKGROUND: Coronavirus disease 2019 (COVID-19) may severely impair pulmonary function and cause hypoxia. However, the association of COVID-19 pneumonia on CT with impaired ventilation remains unexplained. This pilot study aims to demonstrate the relationship between the radiological findings on COVID-19 CT images and ventilation abnormalities simulated in a computational model linked to the patients' symptoms. METHODS: Twenty-five patients with COVID-19 and four test-negative healthy controls who underwent a baseline non-enhanced CT scan: 7 dyspneic patients, 9 symptomatic patients without dyspnea, and 9 asymptomatic patients were included. A 2D U-Net-based CT segmentation software was used to quantify radiological futures of COVID-19 pneumonia. The CT image-based full-scale airway network (FAN) flow model was employed to assess regional lung ventilation. Functional and radiological features were compared across groups and correlated with the clinical symptoms. Heterogeneity in ventilation distribution and ventilation defects associated with the pneumonia and the patients' symptoms were assessed. RESULTS: Median percentage ventilation defects were 0.2% for healthy controls, 0.7% for asymptomatic patients, 1.2% for symptomatic patients without dyspnea, and 11.3% for dyspneic patients. The median of percentage pneumonia was 13.2% for dyspneic patients and 0% for the other groups. Ventilation defects preferentially affected the posterior lung and worsened with increasing pneumonia linearly (y = 0.91x + 0.99, R2 = 0.73) except for one of the nine dyspneic patients who had disproportionally large ventilation defects (7.8% of the entire lung) despite mild pneumonia (1.2%). The symptomatic and dyspneic patients showed significantly right-skewed ventilation distributions (symptomatic without dyspnea: 0.86 ± 0.61, dyspnea 0.91 ± 0.79) compared to the patients without symptom (0.45 ± 0.35). The ventilation defect analysis with the FAN model provided a comparable diagnostic accuracy to the percentage pneumonia in identifying dyspneic patients (area under the receiver operating characteristic curve, 0.94 versus 0.96). CONCLUSIONS: COVID-19 pneumonia segmentations from CT scans are accompanied by impaired pulmonary ventilation preferentially in dyspneic patients. Ventilation analysis with CT image-based computational modelling shows it is able to assess functional impairment in COVID-19 and potentially identify one of the aetiologies of hypoxia in patients with COVID-19 pneumonia.

Computational investigation of prolonged airborne dispersion of novel coronavirus-laden droplets.

We have performed highly accurate numerical simulations to investigate prolonged dispersion of novel coronavirus-laden droplets in classroom air. Approximately 10,900 virus-laden droplets were released into the air by a teacher coughing and tracked for 90 min by numerical simulations. The teacher was standing in front of multiple students in a classroom. To estimate viral transmission to the students, we considered the features of the novel coronavirus, such as the virus half-life. The simulation results revealed that there was a high risk of prolonged airborne transmission of virus-laden droplets when the outlet flow of the classroom ventilation was low (i.e., 4.3 and 8.6 cm/s). The rates of remaining airborne virus-laden droplets produced by the teacher coughing were 40% and 15% after 45 and 90 min, respectively. The results revealed that students can avoid exposure to the virus-laden droplets by keeping a large distance from the teacher (5.5 m), which is more than two times farther than the currently suggested social distancing rules. The results of this study provide guidelines to set a new protection plan in the classroom to prevent airborne transmission of virus-laden droplets to students.

Lobar Ventilation in Patients with COPD Assessed with the Full-Scale Airway Network Flow Model and Xenon-enhanced Dual-Energy CT.

Background The full-scale airway network (FAN) flow model shows excellent agreement with limited functional imaging data but requires further validation prior to clinical use. Purpose To validate the ventilation distributions computed with the FAN flow model with xenon ventilation from xenon-enhanced dual-energy (DE) CT in participants with chronic obstructive pulmonary disease (COPD). Materials and Methods In this prospective study, the FAN model extracted structural data from xenon-enhanced DE CT images of men with COPD scanned between June 2012 and July 2013 to compute gas ventilation dynamics. The ventilation distributions on the middle cross-section plane, percentage lobar ventilation, and ventilation heterogeneity quantified by the coefficient of variation (CV) were compared between xenon-enhanced DE CT imaging and the FAN model. The relationship between the ventilation parameters with the densitometry and pulmonary function test results was demonstrated. The agreements and correlations between the parameters were measured using the concordance correlation coefficient and the Pearson correlation coefficient. Results Twenty-two men with COPD (mean age, 67 years ± 7 [standard deviation]) were evaluated. The percentage lobar ventilation computed with FAN showed a strong positive correlation with xenon-enhanced DE CT data (r = 0.7, P < .001). Ninety-five percent of lobar ventilation CV differences lay within 95% confidence intervals. Correlations of the percentage lobar ventilation were negative for percentage emphysema (xenon-enhanced DE CT: r = -0.38, P < .001; FAN: r = -0.23, P = .02) but were positive for percentage normal tissue volume (xenon-enhanced DE CT: r = 0.78, P < .001; FAN: r = 0.45, P < .001). Lung CVs of FAN revealed negative correlations with the spirometry results (CVFAN vs percentage predicted forced expiratory volume in 1 second: r = -0.75, P < .001; CVFAN vs ratio of forced expiratory volume in 1 second to forced vital capacity: r = -0.67, P < .001). Conclusion The full-scale airway network modeled lobar ventilation in patients with chronic obstructive pulmonary disease correlated with the xenon-enhanced dual-energy CT imaging data. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Parraga and Eddy in this issue.

Anterior Pulmonary Ventilation Abnormalities in COVID-19.

Online supplemental material is available for this article.

CT-based Airway Flow Model to Assess Ventilation in Chronic Obstructive Pulmonary Disease: A Pilot Study.

Background The lack of functional information in thoracic CT remains a limitation of its use in the clinical management of chronic obstructive pulmonary disease (COPD). Purpose To compare the distribution of pulmonary ventilation assessed by a CT-based full-scale airway network (FAN) flow model with hyperpolarized xenon 129 (129Xe) MRI (hereafter, 129Xe MRI) and technetium 99m-diethylenetriaminepentaacetic acid aerosol SPECT ventilation imaging (hereafter, V-SPECT) in participants with COPD. Materials and Methods In this prospective study performed between May and August 2017, pulmonary ventilation in participants with COPD was computed by using the FAN flow model. The modeled pulmonary ventilation was compared with functional imaging data from breath-hold time-series 129Xe MRI and V-SPECT. FAN-derived ventilation images on the coronal plane and volumes of interest were compared with functional lung images. Percentage lobar ventilation estimated by the FAN model was compared with that measured at 129Xe MRI and V-SPECT. The statistical significance of ventilation distribution between FAN and functional images was demonstrated with the Spearman correlation coefficient and χ2 distance. Results For this study, nine participants (seven men [mean age, 65 years ± 5 {standard deviation}] and two women [mean age, 63 years ± 7]) with COPD that was Global Initiative for Chronic Obstructive Lung Disease stage II-IV were enrolled. FAN-modeled ventilation profile showed strong positive correlation with images from 129Xe MRI (ρ = 0.67; P < .001) and V-SPECT (ρ = 0.65; P < .001). The χ2 distances of the ventilation histograms in the volumes of interest between the FAN and 129Xe MRI and FAN and V-SPECT were 0.16 ± 0.08 and 0.28 ± 0.14, respectively. The ratios of lobar ventilations in the models were linearly correlated to images from 129Xe MRI (ρ = 0.67; P < .001) and V-SPECT (ρ = 0.59; P < .001). Conclusion A CT-based full-scale airway network flow model provided regional pulmonary ventilation information for chronic obstructive pulmonary disease and correlates with hyperpolarized xenon 129 MRI and technetium 99m-diethylenetriaminepentaacetic acid aerosol SPECT ventilation imaging. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Schiebler and Parraga in this issue.

Time-series hyperpolarized xenon-129 MRI of lobar lung ventilation of COPD in comparison to V/Q-SPECT/CT and CT.

PURPOSE: To derive lobar ventilation in patients with chronic obstructive pulmonary disease (COPD) using a rapid time-series hyperpolarized xenon-129 (HPX) magnetic resonance imaging (MRI) technique and compare this to ventilation/perfusion single-photon emission computed tomography (V/Q-SPECT), correlating the results with high-resolution computed tomography (CT) and pulmonary function tests (PFTs). MATERIALS AND METHODS: Twelve COPD subjects (GOLD stages I-IV) participated in this study and underwent HPX-MRI, V/Q-SPECT/CT, high-resolution CT, and PFTs. HPX-MRI was performed using a novel time-series spiral k-space sampling approach. Relative percentage ventilations were calculated for individual lobe for comparison to the relative SPECT lobar ventilation and perfusion. The absolute HPX-MRI percentage ventilation in each lobe was compared to the absolute CT percentage emphysema score calculated using a signal threshold method. Pearson's correlation and linear regression tests were performed to compare each imaging modality. RESULTS: Strong correlations were found between the relative lobar percentage ventilation with HPX-MRI and percentage ventilation SPECT (r = 0.644; p < 0.001) and percentage perfusion SPECT (r = 0.767; p < 0.001). The absolute CT percentage emphysema and HPX percentage ventilation correlation was also statistically significant (r = 0.695, p < 0.001). The whole lung HPX percentage ventilation correlated with the PFT measurements (FEV1 with r = - 0.886, p < 0.001*, and FEV1/FVC with r = - 0.861, p < 0.001*) better than the whole lung CT percentage emphysema score (FEV1 with r = - 0.635, p = 0.027; and FEV1/FVC with r = - 0.652, p = 0.021). CONCLUSION: Lobar ventilation with HPX-MRI showed a strong correlation with lobar ventilation and perfusion measurements derived from SPECT/CT, and is better than the emphysema score obtained with high-resolution CT. KEY POINTS: • The ventilation hyperpolarized xenon-129 MRI correlates well with ventilation and perfusion with SPECT/CT with the advantage of higher temporal and spatial resolution. • The hyperpolarized xenon-129 MRI correlates with the PFT measurements better than the high-resolution CT with the advantage of avoiding the use of ionizing radiation.

Effect of upper airway on tracheobronchial fluid dynamics.

The upper airways play a significant role in the tracheal flow dynamics. Despite many previous studies, however, the effect of the upper airways on the ventilation distribution in distal airways has remained a challenge. The aim of this study is to experimentally and computationally investigate the dynamic behaviour in the intratracheal flow induced by the upper respiratory tract and to assess its influence on the subsequent tributaries. Patient-specific images from 2 different modalities (magnetic resonance imaging of the upper airways and computed tomography of the lower airways) were segmented and combined. An experimental phantom of patient-specific airways (including the oral cavity, larynx, trachea, down to generations 6-8) was generated using 3D printing. The flow velocities in this phantom model were measured by the flow-sensitised phase contrast magnetic resonance imaging technique and compared with the computational fluid dynamics simulations. Both experimental and computational results show a good agreement in the time-averaged velocity fields as well as fluctuating velocity. The flows in the proximal trachea were complex and unsteady under both lower- and higher-flow rate conditions. Computational fluid dynamics simulations were also performed with an airways model without the upper airways. Although the flow near the carina remained unstable only when the inflow rate was high, the influence of the upper airways caused notable changes in distal flow distributions when the 2 airways models were compared with and without the upper airways. The results suggest that the influence of the upper airways should be included in the respiratory flow assessment as the upper airways extensively affect the flows in distal airways and consequent ventilation distribution in the lungs.

3D phase contrast MRI in models of human airways: Validation of computational fluid dynamics simulations of steady inspiratory flow.

BACKGROUND: Knowledge of airflow patterns in the large airways is of interest in obstructive airways disease and in the development of inhaled therapies. Computational fluid dynamics (CFD) simulations are used to study airflow in realistic airway models but usually need experimental validation. PURPOSE: To develop MRI-based methods to study airway flow in realistic 3D-printed models. STUDY TYPE: Case control. PHANTOM: Two 3D-printed lung models. FIELD STRENGTH/SEQUENCE: 1.5-3T, flow MRI. ASSESSMENT: Two human airway models, respectively including and excluding the oral cavity and upper airways derived from MR and CT imaging, were 3D-printed. 3D flow MRI was performed at different flow conditions corresponding to slow and steady airflow inhalation rates. Water was used as the working fluid to mimic airflow. Dynamic acquisition of 1D velocity profiles was also performed at different locations in the trachea to observe variability during nonsteady conditions. STATISTICAL TESTS: Linear regression analysis to compare both flow velocity fields and local flow rates from CFD simulations and experimental measurement with flow MRI. RESULTS: A good agreement was obtained between 3D velocity maps measured with flow MRI and predicted by CFD simulations, with linear regression R-squared values ranging from 0.39 to 0.94 when performing a pixel-by-pixel comparison of each velocity component. The flow distribution inside the lung models was also similar, with average slope and R-squared values of 0.96 and 0.99, respectively, when comparing local flow rates assessed at different branching locations. In the model including the upper airways, a turbulent laryngeal jet flow was observed with both methods and affected remarkably the velocity profiles in the trachea. DATA CONCLUSION: We propose flow MRI using water as a surrogate fluid to air, as a validation tool for CFD simulations of airflow in geometrically realistic models of the human airways. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1400-1409.

Dynamic flow characteristics in normal and asthmatic lungs.

Complex flow patterns exist within the asymmetric branching airway network in the lungs. These flow patterns are known to become increasingly heterogeneous during disease as a result of various mechanisms such as bronchoconstriction or alterations in lung tissue compliance. Here, we present a coupled model of tissue deformation and network airflow enabling predictions of dynamic flow properties, including temporal flow rate, pressure distribution, and the occurrence of reverse flows. We created two patient-specific airway geometries, one for a healthy subject and one for a severe asthmatic subject, derived using a combination of high-resolution CT data and a volume-filling branching algorithm. In addition, we created virtually constricted airway geometry by reducing the airway radii of the healthy subject model. The flow model was applied to these three different geometries to solve the pressure and flow distribution over a breathing cycle. The differences in wave phase of the flows in parallel airways induced by asymmetric airway geometry and bidirectional interaction between intra-acinar and airway network pressures were small in central airways but were more evident in peripheral airways. The asthmatic model showed elevated ventilation heterogeneity and significant flow disturbance. The reverse flows in the asthmatic model not only altered the local flow characteristics but also affected total lung resistance. The clinical significance of temporal flow disturbance on lung ventilation in normal airway model is obscure. However, increased flow disturbance and ventilation heterogeneity observed in the asthmatic model suggests that reverse flow may be an important factor for asthmatic lung function.

A one-dimensional model of the spinal cerebrospinal-fluid compartment.

Modeling of the cerebrospinal fluid (CSF) system in the spine is strongly motivated by the need to understand the origins of pathological conditions such as the emergence and growth of fluid-filled cysts in the spinal cord. In this study, a one-dimensional (1D) approximation for the flow in elastic conduits was used to formulate a model of the spinal CSF compartment. The modeling was based around a coaxial geometry in which the inner elastic cylinder represented the spinal cord, middle elastic tube represented the dura, and the outermost tube represented the vertebral column. The fluid-filled annuli between the cord and dura, and the dura and vertebral column, represented the subarachnoid and epidural spaces, respectively. The system of governing equations was constructed by applying a 1D form of mass and momentum conservation to all segments of the model. The developed 1D model was used to simulate CSF pulse excited by pressure disturbances in the subarachnoid and epidural spaces. The results were compared to those obtained from an equivalent two-dimensional finite element (FE) model which was implemented using a commercial software package. The analysis of linearized governing equations revealed the existence of three types of waves, of which the two slower waves can be clearly related to the wave modes identified in previous similar studies. The third, much faster, wave emanates directly from the vertebral column and has little effect on the deformation of the spinal cord. The results obtained from the 1D model and its FE counterpart were found to be in good general agreement even when sharp spatial gradients of the spinal cord stiffness were included; both models predicted large radial displacements of the cord at the location of an initial cyst. This study suggests that 1D modeling, which is computationally inexpensive and amenable to coupling with the models of the cranial CSF system, should be a useful approach for the analysis of some aspects of the CSF dynamics in the spine. The simulation of the CSF pulse excited by a pressure disturbance in the epidural space, points to the possibility that regions of the spinal cord with abnormally low stiffness may be prone to experiencing large strains due to coughing and sneezing.

Fast virtual deployment of self-expandable stents: method and in vitro evaluation for intracranial aneurysmal stenting.

INTRODUCTION: Minimally invasive treatment approaches, like the implantation of percutaneous stents, are becoming more popular every day for the treatment of intracranial aneurysms. The outcome of such treatments is related to factors like vessel and aneurysm geometry, hemodynamic conditions and device design. For this reason, having a tool for assessing stenting alternatives beforehand is crucial. METHODOLOGY: The Fast Virtual Stenting (FVS) method, which provides an estimation of the configuration of intracranial stents when released in realistic geometries, is proposed in this paper. This method is based on constrained simplex deformable models. The constraints are used to account for the stent design. An algorithm for its computational implementation is also proposed. The performance of the proposed methodology was contrasted with real stents released in a silicone phantom. RESULTS: In vitro experiments were performed on the phantom where a contrast injection was performed. Subsequently, corresponding Computational Fluid Dynamics (CFD) analyzes were carried out on a digital replica of the phantom with the virtually released stent. Virtual angiographies are used to compare in vitro experiments and CFD analysis. Contrast time-density curves for in vitro and CFD data were generated and used to compare them. CONCLUSIONS: Results of both experiments resemble very well, especially when comparing the contrast density curves. The use of FVS methodology in the clinical environment could provide additional information to clinicians before the treatment to choose the therapy that best fits the patient.

Virtual coiling of intracranial aneurysms based on dynamic path planning.

Coiling is possibly the most widespread endovascular treatment for intracranial aneurysms. It consists in the placement of metal wires inside the aneurysm to promote blood coagulation. This work presents a virtual coiling technique for pre-interventional planning and post-operative assessment of coil embolization procedure of aneurysms. The technique uses a dynamic path planning algorithm to mimic coil insertion inside a 3D aneurysm model, which allows to obtain a plausible distribution of coils within a patient-specific anatomy. The technique was tested on two idealized geometries: an sphere and a hexahedron. Subsequently, the proposed technique was applied in 10 realistic aneurysm geometries to show its reliability in anatomical models. The results of the technique was compared to digital substraction angiography images of two aneurysms.

Morphology parameters for intracranial aneurysm rupture risk assessment.

OBJECTIVE: The aim of this study is to identify image-based morphological parameters that correlate with human intracranial aneurysm (IA) rupture. METHODS: For 45 patients with terminal or sidewall saccular IAs (25 unruptured, 20 ruptured), three-dimensional geometries were evaluated for a range of morphological parameters. In addition to five previously studied parameters (aspect ratio, aneurysm size, ellipticity index, nonsphericity index, and undulation index), we defined three novel parameters incorporating the parent vessel geometry (vessel angle, aneurysm [inclination] angle, and [aneurysm-to-vessel] size ratio) and explored their correlation with aneurysm rupture. Parameters were analyzed with a two-tailed independent Student's t test for significance; significant parameters (P < 0.05) were further examined by multivariate logistic regression analysis. Additionally, receiver operating characteristic analyses were performed on each parameter. RESULTS: Statistically significant differences were found between mean values in ruptured and unruptured groups for size ratio, undulation index, nonsphericity index, ellipticity index, aneurysm angle, and aspect ratio. Logistic regression analysis further revealed that size ratio (odds ratio, 1.41; 95% confidence interval, 1.03-1.92) and undulation index (odds ratio, 1.51; 95% confidence interval, 1.08-2.11) had the strongest independent correlation with ruptured IA. From the receiver operating characteristic analysis, size ratio and aneurysm angle had the highest area under the curve values of 0.83 and 0.85, respectively. CONCLUSION: Size ratio and aneurysm angle are promising new morphological metrics for IA rupture risk assessment. Because these parameters account for vessel geometry, they may bridge the gap between morphological studies and more qualitative location-based studies.

Comparison of two stents in modifying cerebral aneurysm hemodynamics.

There is a general lack of quantitative understanding about how specific design features of endovascular stents (struts and mesh design, porosity) affect the hemodynamics in intracranial aneurysms. To shed light on this issue, we studied two commercial high-porosity stents (Tristar stent and Wallstent) in aneurysm models of varying vessel curvature as well as in a patient-specific model using Computational Fluid Dynamics. We investigated how these stents modify hemodynamic parameters such as aneurysmal inflow rate, stasis, and wall shear stress, and how such changes are related to the specific designs. We found that the flow damping effect of stents and resulting aneurysmal stasis and wall shear stress are strongly influenced by stent porosity, strut design, and mesh hole shape. We also confirmed that the damping effect is significantly reduced at higher vessel curvatures, which indicates limited usefulness of high-porosity stents as a stand-alone treatment. Finally, we showed that the stasis-inducing performance of stents in 3D geometries can be predicted from the hydraulic resistance of their flat mesh screens. From this, we propose a methodology to cost-effectively compare different stent designs before running a full 3D simulation.