Long-term prognostic implications of hemodynamic and plaque assessment using coronary CT angiography.

BACKGROUND AND AIMS: Hemodynamic and plaque characteristics can be analyzed using coronary CT angiography (CTA). We aimed to explore long-term prognostic implications of hemodynamic and plaque characteristics using coronary CT angiography (CTA). METHODS: Invasive fractional flow reserve (FFR) and CTA-derived FFR (FFRCT) were undertaken for 136 lesions in 78 vessels and followed-up to 10 years until December 2020. FFRCT, wall shear stress (WSS), change in FFRCT across the lesion (ΔFFRCT), total plaque volume (TPV), percent atheroma volume (PAV), and low-attenuation plaque volume (LAPV) for target lesions [L] and vessels [V] were obtained by independent core laboratories. Their collective influence was evaluated for the clinical endpoints of target vessel failure (TVF) and target lesion failure (TLF). RESULTS: During a median follow-up of 10.1 years, PAV[V] (per 10% increase, HR 2.32 [95% CI 1.11-4.86], p = 0.025), and FFRCT[V] (per 0.1 increase, HR 0.56 [95% CI 0.37-0.84], p = 0.006) were independent predictors of TVF for the per-vessel analysis, and WSS[L] (per 100 dyne/cm2 increase, HR 1.43 [1.09-1.88], p = 0.010), LAPV[L] (per 10 mm3 increase, HR 3.81 [1.16-12.5], p = 0.028), and ΔFFRCT[L] (per 0.1 increase, HR 1.39 [1.02-1.90], p = 0.040) were independent predictors of TLF for the per-lesion analysis after adjustment for clinical and lesion characteristics. The addition of both plaque and hemodynamic predictors improved the predictability for 10-year TVF and TLF of clinical and lesion characteristics (all p < 0.05). CONCLUSIONS: Vessel- and lesion-level hemodynamic characteristics, and vessel-level plaque quantity, and lesion-level plaque compositional characteristics assessed by CTA offer independent and additive long-term prognostic value.

Association Among Local Hemodynamic Parameters Derived From CT Angiography and Their Comparable Implications in Development of Acute Coronary Syndrome.

Background: Association among local hemodynamic parameters and their implications in development of acute coronary syndrome (ACS) have not been fully investigated. Methods: A total of 216 lesions in ACS patients undergoing coronary CT angiography (CCTA) before 1-24 months from ACS event were analyzed. High-risk plaque on CCTA was defined as a plaque with ≥2 of low-attenuation plaque, positive remodeling, spotty calcification, and napkin-ring sign. With the use of computational fluid dynamics analysis, fractional flow reserve (FFR) derived from CCTA (FFRCT) and local hemodynamic parameters including wall shear stress (WSS), axial plaque stress (APS), pressure gradient (PG) across the lesion, and delta FFRCT across the lesion (ΔFFRCT) were obtained. The association among local hemodynamics and their discrimination ability for culprit lesions from non-culprit lesions were compared. Results: A total of 66 culprit lesions for later ACS and 150 non-culprit lesions were identified. WSS, APS, PG, and ΔFFRCT were strongly correlated with each other (all p < 0.001). This association was persistent in all lesion subtypes according to a vessel, lesion location, anatomical severity, high-risk plaque, or FFRCT ≤ 0.80. In discrimination of culprit lesions causing ACS from non-culprit lesions, WSS, PG, APS, and ΔFFRCT were independent predictors after adjustment for lesion characteristics, high-risk plaque, and FFRCT ≤ 0.80; and all local hemodynamic parameters significantly improved the predictive value for culprit lesions of high-risk plaque and FFRCT ≤ 0.80 (all p < 0.05). The risk prediction model for culprit lesions with FFRCT ≤ 0.80, high-risk plaque, and ΔFFRCT had a similar or superior discrimination ability to that with FFRCT ≤ 0.80, high-risk plaque, and WSS, APS, or PG; and the addition of WSS, APS, or PG into ΔFFRCT did not improve the model performance. Conclusions: Local hemodynamic indices were significantly intercorrelated, and all indices similarly provided additive and independent predictive values for ACS risk over high-risk plaque and impaired FFRCT.

CT Angiographic and Plaque Predictors of Functionally Significant Coronary Disease and Outcome Using Machine Learning.

OBJECTIVES: The goal of this study was to investigate the association of stenosis and plaque features with myocardial ischemia and their prognostic implications. BACKGROUND: Various anatomic, functional, and morphological attributes of coronary artery disease (CAD) have been independently explored to define ischemia and prognosis. METHODS: A total of 1,013 vessels with fractional flow reserve (FFR) measurement and available coronary computed tomography angiography were analyzed. Stenosis and plaque features of the target lesion and vessel were evaluated by an independent core laboratory. Relevant features associated with low FFR (≤0.80) were identified by using machine learning, and their predictability of 5-year risk of vessel-oriented composite outcome, including cardiac death, target vessel myocardial infarction, or target vessel revascularization, were evaluated. RESULTS: The mean percent diameter stenosis and invasive FFR were 48.5 ± 17.4% and 0.81 ± 0.14, respectively. Machine learning interrogation identified 6 clusters for low FFR, and the most relevant feature from each cluster was minimum lumen area, percent atheroma volume, fibrofatty and necrotic core volume, plaque volume, proximal left anterior descending coronary artery lesion, and remodeling index (in order of importance). These 6 features showed predictability for low FFR (area under the receiver-operating characteristic curve: 0.797). The risk of 5-year vessel-oriented composite outcome increased with every increment of the number of 6 relevant features, and it had incremental prognostic value over percent diameter stenosis and FFR (area under the receiver-operating characteristic curve: 0.706 vs. 0.611; p = 0.031). CONCLUSIONS: Six functionally relevant features, including minimum lumen area, percent atheroma volume, fibrofatty and necrotic core volume, plaque volume, proximal left anterior descending coronary artery lesion, and remodeling index, help define the presence of myocardial ischemia and provide better prognostication in patients with CAD. (CCTA-FFR Registry for Risk Prediction; NCT04037163).

Relevance of anatomical, plaque, and hemodynamic characteristics of non-obstructive coronary lesions in the prediction of risk for acute coronary syndrome.

OBJECTIVES: We explored the anatomical, plaque, and hemodynamic characteristics of high-risk non-obstructive coronary lesions that caused acute coronary syndrome (ACS). METHODS: From the EMERALD study which included ACS patients with available coronary CT angiography (CCTA) before the ACS, non-obstructive lesions (percent diameter stenosis < 50%) were selected. CCTA images were analyzed for lesion characteristics by independent CCTA and computational fluid dynamics core laboratories. The relative importance of each characteristic was assessed by information gain. RESULTS: Of the 132 lesions, 24 were the culprit for ACS. The culprit lesions showed a larger change in FFRCT across the lesion (ΔFFRCT) than non-culprit lesions (0.08 ± 0.07 vs 0.05 ± 0.05, p = 0.012). ΔFFRCT showed the highest information gain (0.051, 95% confidence interval [CI] 0.050-0.052), followed by low-attenuation plaque (0.028, 95% CI 0.027-0.029) and plaque volume (0.023, 95% CI 0.022-0.024). Lesions with higher ΔFFRCT or low-attenuation plaque showed an increased risk of ACS (hazard ratio [HR] 3.25, 95% CI 1.31-8.04, p = 0.010 for ΔFFRCT; HR 2.60, 95% CI 1.36-4.95, p = 0.004 for low-attenuation plaque). The prediction model including ΔFFRCT, low-attenuation plaque and plaque volume showed the highest ability in ACS prediction (AUC 0.725, 95% CI 0.724-0.727). CONCLUSION: Non-obstructive lesions with higher ΔFFRCT or low-attenuation plaque showed a higher risk of ACS. The integration of anatomical, plaque, and hemodynamic characteristics can improve the noninvasive prediction of ACS risk in non-obstructive lesions. KEY POINTS: • Change in FFR CT across the lesion (ΔFFR CT ) was the most important predictor of ACS risk in non-obstructive lesions. • Non-obstructive lesions with higher ΔFFR CT or low-attenuation plaque were associated with a higher risk of ACS. • The integration of anatomical, plaque, and hemodynamic characteristics can improve the noninvasive prediction of ACS risk.

Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics.

OBJECTIVES: The authors investigated the utility of noninvasive hemodynamic assessment in the identification of high-risk plaques that caused subsequent acute coronary syndrome (ACS). BACKGROUND: ACS is a critical event that impacts the prognosis of patients with coronary artery disease. However, the role of hemodynamic factors in the development of ACS is not well-known. METHODS: Seventy-two patients with clearly documented ACS and available coronary computed tomographic angiography (CTA) acquired between 1 month and 2 years before the development of ACS were included. In 66 culprit and 150 nonculprit lesions as a case-control design, the presence of adverse plaque characteristics (APC) was assessed and hemodynamic parameters (fractional flow reserve derived by coronary computed tomographic angiography [FFRCT], change in FFRCT across the lesion [△FFRCT], wall shear stress [WSS], and axial plaque stress) were analyzed using computational fluid dynamics. The best cut-off values for FFRCT, △FFRCT, WSS, and axial plaque stress were used to define the presence of adverse hemodynamic characteristics (AHC). The incremental discriminant and reclassification abilities for ACS prediction were compared among 3 models (model 1: percent diameter stenosis [%DS] and lesion length, model 2: model 1 + APC, and model 3: model 2 + AHC). RESULTS: The culprit lesions showed higher %DS (55.5 ± 15.4% vs. 43.1 ± 15.0%; p < 0.001) and higher prevalence of APC (80.3% vs. 42.0%; p < 0.001) than nonculprit lesions. Regarding hemodynamic parameters, culprit lesions showed lower FFRCT and higher △FFRCT, WSS, and axial plaque stress than nonculprit lesions (all p values <0.01). Among the 3 models, model 3, which included hemodynamic parameters, showed the highest c-index, and better discrimination (concordance statistic [c-index] 0.789 vs. 0.747; p = 0.014) and reclassification abilities (category-free net reclassification index 0.287; p = 0.047; relative integrated discrimination improvement 0.368; p < 0.001) than model 2. Lesions with both APC and AHC showed significantly higher risk of the culprit for subsequent ACS than those with no APC/AHC (hazard ratio: 11.75; 95% confidence interval: 2.85 to 48.51; p = 0.001) and with either APC or AHC (hazard ratio: 3.22; 95% confidence interval: 1.86 to 5.55; p < 0.001). CONCLUSIONS: Noninvasive hemodynamic assessment enhanced the identification of high-risk plaques that subsequently caused ACS. The integration of noninvasive hemodynamic assessments may improve the identification of culprit lesions for future ACS. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary CT Angiography and Computational Fluid Dynamic [EMERALD]; NCT02374775).

Lumen boundaries extracted from coronary computed tomography angiography on computed fractional flow reserve (FFRCT): validation with optical coherence tomography.

AIMS: The aim of this study was to evaluate the accuracy of minimum lumen area (MLA) by coronary computed tomography angiography (cCTA) and its impact on fractional flow reserve (FFRCT). METHODS AND RESULTS: Fifty-seven patients (118 lesions, 72 vessels) who underwent cCTA and optical coherence tomography (OCT) were enrolled. OCT and cCTA were co-registered and MLAs were measured with both modalities. FFROCT was calculated using OCT-updated models with cCTA-based lumen geometry replaced by OCT-derived geometry. Lesions were grouped by Agatston score (AS) and minimum lumen diameter (MLD) using the OCT catheter and guidewire size (1.0 mm) as a threshold. For all lesions, the average absolute difference between cCTA and OCT MLA was 0.621±0.571 mm2. Pearson correlation coefficients between cCTA and OCT MLAs in lesions with low-intermediate and high AS were 0.873 and 0.787, respectively (both p<0.0001). Irrespective of AS score, excellent correlations were observed for MLA (r=0.839, p<0.0001) and FFR comparisons (r=0.918, p<0.0001) in lesions with MLD ≥1.0 mm but not for lesions with MLD <1.0 mm. CONCLUSIONS: The spatial resolution of cCTA or calcification does not practically limit the accuracy of lumen boundary identification by cCTA or FFRCT calculations for MLD ≥1.0 mm. The accuracy of cCTA MLA could not be adequately assessed for lesions with MLD <1.0 mm.

Impact of Longitudinal Lesion Geometry on Location of Plaque Rupture and Clinical Presentations.

OBJECTIVES: This study sought to investigate the impact of longitudinal lesion geometry on the location of plaque rupture and clinical presentation and its mechanism. BACKGROUND: The relationships among lesion geometry, external hemodynamic forces acting on the plaque, location of plaque rupture, and clinical presentation have not been comprehensively investigated. METHODS: This study enrolled 125 patients with plaque rupture documented by intravascular ultrasound. Longitudinal locations of plaque rupture were identified and categorized by intravascular ultrasound. Patients' clinical presentations and TIMI (Thrombolysis In Myocardial Infarction) flow grade in an initial angiogram were compared according to the location of plaque rupture. Longitudinal lesion asymmetry was quantitatively assessed by the luminal radius change over the segment length (radius gradient [RG]). Lesions with a steeper radius change in the upstream segment compared with the downstream segment (RGupstream > RGdownstream) were defined as upstream-dominant lesions. RESULTS: On the basis of the site of maximum rupture aperture, 56.0%, 16.0%, and 28.0% of the patients had upstream, minimal lumen area, and downstream rupture, respectively. Patients with upstream rupture more frequently presented with ST-segment elevation myocardial infarction (45.7%, 40.0%, 22.9%; p = 0.030) and with TIMI flow grade <3 (32.9%, 20.0%, 17.1%; p = 0.042). According to the ratio of upstream and downstream RG, 69.5% of lesions were classified as upstream-dominant lesions, and 30.5% were classified as downstream-dominant lesions. Among the 66 upstream-dominant lesions, 65 cases (98.5%) had upstream rupture, and the RG ratio (RGupstream/RGdownstream) was an independent predictor of upstream rupture (odds ratio: 1.481; 95% confidence interval: 1.035 to 2.120; p = 0.032). Upstream-dominant lesions more frequently manifested with ST-segment elevation myocardial infarction than did downstream-dominant lesions (48.5% vs. 24.1%; p = 0.026). CONCLUSIONS: Both clinical presentation and degree of flow limitation were associated with the location of plaque rupture. Longitudinal lesion asymmetry assessed by RG, which can affect regional distribution of hemodynamic stress, was associated with the location of rupture and with clinical presentation.

Computational fluid dynamic measures of wall shear stress are related to coronary lesion characteristics.

OBJECTIVE: To assess the distribution of pressure and shear-related forces acting on atherosclerotic plaques and their association with lesion characteristics using coronary CT angiography (cCTA)-based computational fluid dynamics (CFD) model of epicardial coronary arteries. METHODS: Patient-specific models of epicardial coronary arteries were reconstructed from cCTA in 80 patients (12 women, 63.8±9.0 years). The pressure and wall shear stress (WSS) in left anterior descending coronary arteries were assessed using CFD. High-risk plaques were defined as the presence of at least one of the following adverse plaque characteristics: low-density plaque, positive remodelling, napkin-ring sign and spotty calcification. RESULTS: At resting condition, 39.5% of stenotic segments (% diameter stenosis 52.3±14.4%) were exposed to high WSS (>40 dyne/cm(2)). When the stenotic lesion was subdivided into three segments, the distribution of WSS was different from that of pressure change and its magnitude was highest at minimal lumen area (p<0.001). High pressure gradient, proximal location, small lumen and short length were independent determinants of WSS (all p<0.05). The plaques exposed to the highest WSS tertile had a significantly greater proportion of high-risk plaques. The addition of WSS to % diameter stenosis significantly improved the measures of discrimination and reclassification of high-risk plaques (area under the curves from 0.540 to 0.718, p=0.031; net reclassification index 0.827, p<0.001). CONCLUSIONS: The cCTA-based CFD method can improve the identification of high-risk plaques and the risk stratification for coronary artery disease patients by providing non-invasive measurements of WSS affecting coronary plaques.

Three-Dimensional Modeling Analysis of Visceral Arteries and Kidneys during Respiration.

BACKGROUND: Visceral arteries are commonly involved in endovascular repair of complex abdominal aortic aneurysms (AAAs). To improve repair techniques and reduce long-term complications involving visceral arteries, it is crucial to understand in vivo arterial geometry and the deformations due to visceral organ movement with respiration. This study quantifies deformation of the celiac, superior mesenteric (SMA), and renal arteries during respiration and correlates the deformations with diaphragmatic excursion. METHODS: Sixteen patients with small AAAs underwent magnetic resonance angiography during inspiratory and expiratory breathholds. From geometric models of the aorta and visceral arteries, vessel length, branch angle, curvature, and positions were computed, along with degree of diaphragmatic excursion as indicated by kidney translation. RESULTS: From inspiration to expiration, the celiac artery exhibited axial shortening of 4.8 ± 6.4% (P < 0.001) and a mean curvature increase of 0.03 ± 0.02 mm(-1), greater than other visceral arteries (P < 0.01). With expiration, the SMA, left and right renal arteries (LRA and RRA) angled upward by -9.8 ± 6.4°, -6.4 ± 6.4°, and -5.2 ± 5.0°, respectively (P < 0.005). All vessels translated superiorly (P < 0.0005) and posteriorly (P < 0.01), and the SMA translated rightward additionally (P < 0.005). The left and right kidneys translated by 22 ± 9 mm and 21 ± 9 mm, mostly superiorly (P < 0.001). Translations of all visceral arteries were moderately correlated to the right kidney (R > 0.50). Correlation of the LRA with the left kidney was greater than that of the RRA with the right kidney. CONCLUSIONS: The celiac artery exhibited less branch angle change, and greater axial and curvature deformations than the other visceral arteries, due to the vicinity to the liver and influence of the median arcuate ligament. Correlation between visceral arteries and kidney translations revealed that diaphragmatic excursion affects vessel mobility. Weaker correlation of the RRA to the right kidney indicates mechanical shielding from the inferior vena cava.

Uncertainty quantification in coronary blood flow simulations: Impact of geometry, boundary conditions and blood viscosity.

Computational fluid dynamic methods are currently being used clinically to simulate blood flow and pressure and predict the functional significance of atherosclerotic lesions in patient-specific models of the coronary arteries extracted from noninvasive coronary computed tomography angiography (cCTA) data. One such technology, FFRCT, or noninvasive fractional flow reserve derived from CT data, has demonstrated high diagnostic accuracy as compared to invasively measured fractional flow reserve (FFR) obtained with a pressure wire inserted in the coronary arteries during diagnostic cardiac catheterization. However, uncertainties in modeling as well as measurement results in differences between these predicted and measured hemodynamic indices. Uncertainty in modeling can manifest in two forms - anatomic uncertainty resulting in error of the reconstructed 3D model and physiologic uncertainty resulting in errors in boundary conditions or blood viscosity. We present a data-driven framework for modeling these uncertainties and study their impact on blood flow simulations. The incompressible Navier-Stokes equations are used to model blood flow and an adaptive stochastic collocation method is used to model uncertainty propagation in the Navier-Stokes equations. We perform uncertainty quantification in two geometries, an idealized stenosis model and a patient specific model. We show that uncertainty in minimum lumen diameter (MLD) has the largest impact on hemodynamic simulations, followed by boundary resistance, viscosity and lesion length. We show that near the diagnostic cutoff (FFRCT=0.8), the uncertainty due to the latter three variables are lower than measurement uncertainty, while the uncertainty due to MLD is only slightly higher than measurement uncertainty. We also show that uncertainties are not additive but only slightly higher than the highest single parameter uncertainty. The method presented here can be used to output interval estimates of hemodynamic indices and visualize patient-specific maps of sensitivities.

Structural Mechanics Predictions Relating to Clinical Coronary Stent Fracture in a 5 Year Period in FDA MAUDE Database.

Endovascular stents are the mainstay of interventional cardiovascular medicine. Technological advances have reduced biological and clinical complications but not mechanical failure. Stent strut fracture is increasingly recognized as of paramount clinical importance. Though consensus reigns that fractures can result from material fatigue, how fracture is induced and the mechanisms underlying its clinical sequelae remain ill-defined. In this study, strut fractures were identified in the prospectively maintained Food and Drug Administration's (FDA) Manufacturer and User Facility Device Experience Database (MAUDE), covering years 2006-2011, and differentiated based on specific coronary artery implantation site and device configuration. These data, and knowledge of the extent of dynamic arterial deformations obtained from patient CT images and published data, were used to define boundary conditions for 3D finite element models incorporating multimodal, multi-cycle deformation. The structural response for a range of stent designs and configurations was predicted by computational models and included estimation of maximum principal, minimum principal and equivalent plastic strains. Fatigue assessment was performed with Goodman diagrams and safe/unsafe regions defined for different stent designs. Von Mises stress and maximum principal strain increased with multimodal, fully reversed deformation. Spatial maps of unsafe locations corresponded to the identified locations of fracture in different coronary arteries in the clinical database. These findings, for the first time, provide insight into a potential link between patient adverse events and computational modeling of stent deformation. Understanding of the mechanical forces imposed under different implantation conditions may assist in rational design and optimal placement of these devices.

Coronary Artery Axial Plaque Stress and its Relationship With Lesion Geometry: Application of Computational Fluid Dynamics to Coronary CT Angiography.

OBJECTIVES: The purpose of this study was to characterize the hemodynamic force acting on plaque and to investigate its relationship with lesion geometry. BACKGROUND: Coronary plaque rupture occurs when plaque stress exceeds plaque strength. METHODS: Computational fluid dynamics was applied to 114 lesions (81 patients) from coronary computed tomography angiography. The axial plaque stress (APS) was computed by extracting the axial component of hemodynamic stress acting on stenotic lesions, and the axial lesion asymmetry was assessed by the luminal radius change over length (radius gradient [RG]). Lesions were divided into upstream-dominant (upstream RG > downstream RG) and downstream-dominant lesions (upstream RG < downstream RG) according to the RG. RESULTS: Thirty-three lesions (28.9%) showed net retrograde axial plaque force. Upstream APS linearly increased as lesion severity increased, whereas downstream APS exhibited a concave function for lesion severity. There was a negative correlation (r = -0.274, p = 0.003) between APS and lesion length. The pressure gradient, computed tomography-derived fractional flow reserve (FFRCT), and wall shear stress were consistently higher in upstream segments, regardless of the lesion asymmetry. However, APS was higher in the upstream segment of upstream-dominant lesions (11,371.96 ± 5,575.14 dyne/cm(2) vs. 6,878.14 ± 4,319.51 dyne/cm(2), p < 0.001), and in the downstream segment of downstream-dominant lesions (7,681.12 ± 4,556.99 dyne/cm(2) vs. 11,990.55 ± 5,556.64 dyne/cm(2), p < 0.001). Although there were no differences in FFRCT, % diameter stenosis, and wall shear stress pattern, the distribution of APS was different between upstream- and downstream-dominant lesions. CONCLUSIONS: APS uniquely characterizes the stenotic segment and has a strong relationship with lesion geometry. Clinical application of these hemodynamic and geometric indices may be helpful to assess the future risk of plaque rupture and to determine treatment strategy for patients with coronary artery disease. (Evaluation of FFR, WSS, and TPF Using CCTA; NCT01857687).

Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data.

Accurate quantification of changes in length, curvature, and bifurcation angles of coronary arteries due to cardiac motion is important for the design of coronary stents. A new method is developed to describe the dynamic characteristics of the human coronary artery. From cardiac-gated computed tomography (CT) data, 3-D surface geometry and centerline paths of the coronary arteries were constructed. For quantification of strain and twisting deformation, 3-D distortion-free vessel straightening and landmark matching algorithms were developed to compute the relative translation and rotation of distal landmarks with respect to a proximal landmark. For quantification of bending deformation, change in curvature was measured by computing a best-fit torus in the region of interest within a coronary segment. The optimal torus parameters were estimated by minimizing the standard deviation of distances from the surface mesh to the centerline of the torus. The angle between branch vessels was measured using linear fitting of centroid sets from the cross-sectional vessel lumen. The proposed methods were verified using a software phantom and applied to two patient specific CT datasets. Vascular deformations derived from these methods can provide information for designing bench-top tests for endovascular devices that better replicate the in vivo environment, thereby improving device performance prediction and leading to more durable designs.

Respiration-induced deformations of the superior mesenteric and renal arteries in patients with abdominal aortic aneurysms.

PURPOSE: To quantify respiration-induced deformations of the superior mesenteric artery (SMA), left renal artery (LRA), and right renal artery (RRA) in patients with small abdominal aortic aneurysms (AAAs). MATERIALS AND METHODS: Sixteen men with AAAs (age 73 y ± 7) were imaged with contrast-enhanced magnetic resonance angiography during inspiratory and expiratory breath-holds. Centerline paths of the aorta and visceral arteries were acquired by geometric modeling and segmentation techniques. Vessel translations and changes in branching angle and curvature resulting from respiration were computed from centerline paths. RESULTS: With expiration, the SMA, LRA, and RRA bifurcation points translated superiorly by 12.4 mm ± 9.5, 14.5 mm ± 8.8, and 12.7 mm ± 6.4 (P < .001), and posteriorly by 2.2 mm ± 2.7, 4.9 mm ± 4.2, and 5.6 mm ± 3.9 (P < .05), respectively, and the SMA translated rightward by 3.9 mm ± 4.9 (P < .01). With expiration, the SMA, LRA, and RRA angled upward by 9.7° ± 6.4, 7.5° ± 7.8, and 4.9° ± 5.3, respectively (P < .005). With expiration, mean curvature increased by 0.02 mm(-1) ± 0.01, 0.01 mm(-1) ± 0.01, and 0.01 mm(-1) ± 0.01 in the SMA, LRA, and RRA, respectively (P < .05). For inspiration and expiration, RRA curvature was greater than in other vessels (P < .025). CONCLUSIONS: With expiration, the SMA, LRA, and RRA translated superiorly and posteriorly as a result of diaphragmatic motion, inducing upward angling of vessel branches and increased curvature. In addition, the SMA exhibited rightward translation with expiration. The RRA was significantly more tortuous, but deformed less than the other vessels during respiration.

Respiratory-induced 3D deformations of the renal arteries quantified with geometric modeling during inspiration and expiration breath-holds of magnetic resonance angiography.

PURPOSE: To quantify renal artery deformation due to respiration using magnetic resonance (MR) image-based geometric analysis. MATERIALS AND METHODS: Five males were imaged with contrast-enhanced MR angiography during inspiratory and expiratory breath-holds. From 3D models of the abdominal aorta, left and right renal arteries (LRA and RRA), we quantified branching angle, curvature, peak curve angle, axial length, and locations of branch points. RESULTS: With expiration, maximum curvature changes were 0.054 ± 0.025 mm(-1) (P < 0.01), and curve angle at the most proximal curvature peak increased by 8.0 ± 4.5° (P < 0.05) in the LRA. Changes in maximum curvature and curve angles were not significant in the RRA. The first renal bifurcation point translated superiorly and posteriorly by 9.7 ± 3.6 mm (P < 0.005) and 3.5 ± 2.1 mm (P < 0.05), respectively, in the LRA, and 10.8 ± 6.1 mm (P < 0.05) and 3.6 ± 2.5 mm (P < 0.05), respectively, in the RRA. Changes in branching angle, axial length, and renal ostia locations were not significant. CONCLUSION: The LRA and RRA deformed and translated significantly. Greater deformation of the LRA as compared to the RRA may be due to asymmetric anatomy and mechanical support by the inferior vena cava. The presented methodology can extend to quantification of deformation of diseased and stented arteries to help renal artery implant development.

Virtual Interventions for Image-based Blood Flow Computation.

Image-based blood flow computation provides great promise for evaluation of vascular devices and assessment of surgical procedures. However, many previous studies employ idealized arterial and device models or only patient-specific models from the image data after device deployment, since the tools for model construction are unavailable or limited and tedious to use. Moreover, in contrast to retrospective studies from existing data, there is a pressing need for prospective analysis with the goal of surgical planning. Therefore, it is necessary to construct models with deployed devices in a fast, virtual and interactive fashion. The goal of this paper is to develop new geometric methods to deploy stents or stent grafts virtually to patient-specific geometric models constructed from a 3D segmentation of medical images. A triangular surface representing the vessel lumen boundary is extracted from the segmentation. The diseased portion is either clipped and replaced by the surface of a deployed device or rerouted in the case of a bypass graft. For diseased arteries close to bifurcations, bifurcated device models are generated. A method to map a 2D strut pattern on the surface of a device is also presented. We demonstrate three applications of our methods in personalized surgical planning for aortic aneurysms, aortic coarctation, and coronary artery stenosis using blood flow computation. Our approach enables prospective model construction and may help to expand the throughput required by routine clinical uses in the future.