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Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment.

ABSTRACT: BACKGROUND:Hemodynamic patterns have been associated with cerebral aneurysm instability. For patient-specific computational fluid dynamics (CFD) simulations, the inflow rates of a patient are typically not known. The aim of this study was to analyze the influence of inter- and intra-patient variations of cerebral blood flow on the computed hemodynamics through CFD simulations and to incorporate these variations into statistical models for aneurysm rupture prediction. METHODS:Image data of 1820 aneurysms were used for patient-specific steady CFD simulations with nine different inflow rates per case, capturing inter- and intra-patient flow variations. Based on the computed flow fields, 17 hemodynamic parameters were calculated and compared for the different flow conditions. Next, statistical models for aneurysm rupture were trained in 1571 of the aneurysms including hemodynamic parameters capturing the flow variations either by defining hemodynamic "response variables" (model A) or repeatedly randomly selecting flow conditions by patients (model B) as well as morphological and patient-specific variables. Both models were evaluated in the remaining 249 cases. RESULTS:All hemodynamic parameters were significantly different for the varying flow conditions (p?

SUBMITTER: Detmer FJ

PROVIDER: S-EPMC7172014 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment.

Detmer Felicitas J FJ Mut Fernando F Slawski Martin M Hirsch Sven S Bijlenga Philippe P Cebral Juan R JR

Acta neurochirurgica 20200201 3

<h4>Background</h4>Hemodynamic patterns have been associated with cerebral aneurysm instability. For patient-specific computational fluid dynamics (CFD) simulations, the inflow rates of a patient are typically not known. The aim of this study was to analyze the influence of inter- and intra-patient variations of cerebral blood flow on the computed hemodynamics through CFD simulations and to incorporate these variations into statistical models for aneurysm rupture prediction.<h4>Methods</h4>Image ...[more]

PMID: 32008209

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Project description:BackgroundThe monocyte chemoattractant protein-1/CCR2 (chemokine receptor 2) axis plays an important role in abdominal aortic aneurysm (AAA) pathogenesis, with effects on disease progression and anatomic stability. We assessed the expression of CCR2 in a rodent model and human tissues, using a targeted positron emission tomography radiotracer (64Cu-DOTA-ECL1i).MethodsAAAs were generated in Sprague-Dawley rats by exposing the infrarenal, intraluminal aorta to PPE (porcine pancreatic elastase) under pressure to induce aneurysmal degeneration. Heat-inactivated PPE was used to generate a sham operative control. Rat AAA rupture was stimulated by the administration of ?-aminopropionitrile, a lysyl oxidase inhibitor. Biodistribution was performed in wild-type rats at 1 hour post tail vein injection of 64Cu-DOTA-ECL1i. Dynamic positron emission tomography/computed tomography imaging was performed in rats to determine the in vivo distribution of radiotracer.ResultsBiodistribution showed fast renal clearance. The localization of radiotracer uptake in AAA was verified with high-resolution computed tomography. At day 7 post-AAA induction, the radiotracer uptake (standardized uptake value [SUV]=0.91±0.25) was approximately twice that of sham-controls (SUV=0.47±0.10; P<0.01). At 14 days post-AAA induction, radiotracer uptake by either group did not significantly change (AAA SUV=0.86±0.17 and sham-control SUV=0.46±0.10), independent of variations in aortic diameter. Competitive CCR2 receptor blocking significantly decreased AAA uptake (SUV=0.42±0.09). Tracer uptake in AAAs that subsequently ruptured (SUV=1.31±0.14; P<0.005) demonstrated uptake nearly twice that of nonruptured AAAs (SUV=0.73±0.11). Histopathologic characterization of rat and human AAA tissues obtained from surgery revealed increased expression of CCR2 that was co-localized with CD68+ macrophages. Ex vivo autoradiography demonstrated specific binding of 64Cu-DOTA-ECL1i to CCR2 in both rat and human aortic tissues.ConclusionsCCR2 positron emission tomography is a promising new biomarker for the noninvasive assessment of AAA inflammation that may aid in associated rupture prediction.

Project description:BACKGROUND:Clinical and imaging surveillance practices following endovascular aneurysm repair (EVAR) for intact abdominal aortic aneurysm (AAA) vary considerably and compliance with recommended lifelong surveillance is poor. The aim of this study was to develop a dynamic prognostic model to enable stratification of patients at risk of future secondary aortic rupture or the need for intervention to prevent rupture (rupture-preventing reintervention) to enable the development of personalized surveillance intervals. METHODS:Baseline data and repeat measurements of postoperative aneurysm sac diameter from the EVAR-1 and EVAR-2 trials were used to develop the model, with external validation in a cohort from a single-centre vascular database. Longitudinal mixed-effects models were fitted to trajectories of sac diameter, and model-predicted sac diameter and rate of growth were used in prognostic Cox proportional hazards models. RESULTS:Some 785 patients from the EVAR trials were included, of whom 155 (19·7 per cent) experienced at least one rupture or required a rupture-preventing reintervention during follow-up. An increased risk was associated with preoperative AAA size, rate of sac growth and the number of previously detected complications. A prognostic model using predicted sac growth alone had good discrimination at 2?years (C-index 0·68), 3?years (C-index 0·72) and 5?years (C-index 0·75) after operation and had excellent external validation (C-index 0·76-0·79). More than 5?years after operation, growth rates above 1?mm/year had a sensitivity of over 80 per cent and specificity over 50 per cent in identifying events occurring within 2?years. CONCLUSION:Secondary sac growth is an important predictor of rupture or rupture-preventing reintervention to enable the development of personalized surveillance intervals. A dynamic prognostic model has the potential to tailor surveillance by identifying a large proportion of patients who may require less intensive follow-up.

Dataset Information

Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment.

Publications

Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment.

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