Toward integrated management of cerebral aneurysms

Fluid-structure interaction simulations outperform computational fluid dynamics in the description of thoracic aorta haemodynamics and in the differentiation of progressive dilation in Marfan syndrome patients

Abnormal fluid dynamics at the ascending aorta may be at the origin of aortic aneurysms. This study was aimed at comparing the performance of computational fluid dynamics (CFD) and fluid-structure interaction (FSI) simulations against four-dimensional (4D) flow magnetic resonance imaging (MRI) data; and to assess the capacity of advanced fluid dynamics markers to stratify aneurysm progression risk. Eight Marfan syndrome (MFS) patients, four with stable and four with dilating aneurysms of the proximal aorta, and four healthy controls were studied. FSI and CFD simulations were performed with MRI-derived geometry, inlet velocity field and Young's modulus. Flow displacement, jet angle and maximum velocity evaluated from FSI and CFD simulations were compared to 4D flow MRI data. A dimensionless parameter, the shear stress ratio (SSR), was evaluated from FSI and CFD simulations and assessed as potential correlate of aneurysm progression. FSI simulations successfully matched MRI data regarding descending to ascending aorta flow rates (R 2 = 0.92) and pulse wave velocity (R 2 = 0.99). Compared to CFD, FSI simulations showed significantly lower percentage errors in ascending and descending aorta in flow displacement (-46% ascending, -41% descending), jet angle (-28% ascending, -50% descending) and maximum velocity (-37% ascending, -34% descending) with respect to 4D flow MRI. FSI- but not CFD-derived SSR differentiated between stable and dilating MFS patients. Fluid dynamic simulations of the thoracic aorta require fluid-solid interaction to properly reproduce complex haemodynamics. FSI- but not CFD-derived SSR could help stratifying MFS patients.

Virtual endovascular treatment of intracranial aneurysms: models and uncertainty

Virtual endovascular treatment models (VETMs) have been developed with the view to aid interventional neuroradiologists and neurosurgeons to pre-operatively analyze the comparative efficacy and safety of endovascular treatments for intracranial aneurysms. Based on the current state of VETMs in aneurysm rupture risk stratification and in patient-specific prediction of treatment outcomes, we argue there is a need to go beyond personalized biomechanical flow modeling assuming deterministic parameters and error-free measurements. The mechanobiological effects associated with blood clot formation are important factors in therapeutic decision making and models of post-treatment intra-aneurysmal biology and biochemistry should be linked to the purely hemodynamic models to improve the predictive power of current VETMs. The influence of model and parameter uncertainties associated to each component of a VETM is, where feasible, quantified via a random-effects meta-analysis of the literature. This allows estimating the pooled effect size of these uncertainties on aneurysmal wall shear stress. From such meta-analyses, two main sources of uncertainty emerge where research efforts have so far been limited: (1) vascular wall distensibility, and (2) intra/intersubject systemic flow variations. In the future, we suggest that current deterministic computational simulations need to be extended with strategies for uncertainty mitigation, uncertainty exploration, and sensitivity reduction techniques. WIREs Syst Biol Med 2017, 9:e1385. doi: 10.1002/wsbm.1385 For further resources related to this article, please visit the WIREs website.

Precision Imaging: more descriptive, predictive and integrative imaging

Medical image analysis has grown into a matured field challenged by progress made across all medical imaging technologies and more recent breakthroughs in biological imaging. The cross-fertilisation between medical image analysis, biomedical imaging physics and technology, and domain knowledge from medicine and biology has spurred a truly interdisciplinary effort that stretched outside the original boundaries of the disciplines that gave birth to this field and created stimulating and enriching synergies. Consideration on how the field has evolved and the experience of the work carried out over the last 15 years in our centre, has led us to envision a future emphasis of medical imaging in Precision Imaging. Precision Imaging is not a new discipline but rather a distinct emphasis in medical imaging borne at the cross-roads between, and unifying the efforts behind mechanistic and phenomenological model-based imaging. It captures three main directions in the effort to deal with the information deluge in imaging sciences, and thus achieve wisdom from data, information, and knowledge. Precision Imaging is finally characterised by being descriptive, predictive and integrative about the imaged object. This paper provides a brief and personal perspective on how the field has evolved, summarises and formalises our vision of Precision Imaging for Precision Medicine, and highlights some connections with past research and current trends in the field.

Resting myocardial blood flow quantification using contrast-enhanced magnetic resonance imaging in the presence of stenosis: A computational fluid dynamics study

PURPOSE

The extent to which atherosclerotic plaques affect contrast agent (CA) transport in the coronary arteries and, hence, quantification of myocardial blood flow (MBF) using magnetic resonance imaging (MRI) is unclear. The purpose of this work was to evaluate the influence of plaque induced stenosis both on CA transport and on the accuracy of MBF quantification.

METHODS

Computational fluid dynamics simulations in a high-detailed realistic vascular model were employed to investigate CA bolus transport in the coronary arteries. The impact of atherosclerosis was analyzed by inserting various medium- to high-grade stenoses in the vascular model. The influence of stenosis morphology was examined by varying the stenosis shapes but keeping the area reduction constant. Errors due to CA bolus transport were analyzed using the tracer-kinetic model MMID4.

RESULTS

Dispersion of the CA bolus was found in all models and for all outlets, but with a varying magnitude. The impact of stenosis was complex: while high-grade stenoses amplified dispersion, mild stenoses reduced the effect. Morphology was found to have a marked influence on dispersion for a small number of outlets in the post-stenotic region. Despite this marked influence on the concentration-time curves, MBF errors were less affected by stenosis. In total, MBF was underestimated by -7.9% to -44.9%.

CONCLUSIONS

The presented results reveal that local hemodynamics in the coronary vasculature appears to have a direct impact on CA bolus dispersion. Inclusion of atherosclerotic plaques resulted in a complex alteration of this effect, with both degree of area reduction and stenosis morphology affecting the amount of dispersion. This strong influence of vascular transport effects impairs the accuracy of MRI-based MBF quantification techniques and, potentially, other bolus-based perfusion measurement techniques like computed tomography perfusion imaging.

Aligning 3D time-of-flight MRA datasets for quantitative longitudinal studies: evaluation of rigid registration techniques

OBJECTIVE

3D Time-of-flight (TOF) magnetic resonance angiography is commonly used for vascular analyses. A quantification of longitudinal morphological changes usually requires the registration of TOF image sequences acquired at different time points. The aim of this study was to evaluate the precision of different 3D rigid registration setups such that an optimal quantification of morphological changes can be achieved.

METHODS

Eight different rigid registration techniques were implemented and evaluated in this study using the target registration error (TRE) calculated based on 554 landmarks defined in twenty TOF datasets. The registration techniques differed in integration of brain and vessel segmentation masks and usage of a multi-resolution framework. Furthermore, the benefit of a prior volume-of-interest definition for registration accuracy was evaluated.

RESULTS

The results revealed that the highest registration accuracies can be achieved using a multi-resolution framework and a cerebrovascular segmentation as mask. Numerically, a mean TRE of 1.1mm was calculated. If applicable, a prior definition of a volume-of-interest allows a reduction of the TRE to only 0.6mm.

CONCLUSION

TOF datasets should be registered using vessel segmentations as mask, multi-resolution framework and previous volume-of-interest definition if possible to obtain the highest registration precision. This is especially the case for longitudinal datasets that are separated by several months while the registration technique seems less important for datasets that are only separated by a few days.

Choice of boundary condition for lattice-Boltzmann simulation of moderate-Reynolds-number flow in complex domains

Modeling blood flow in larger vessels using lattice-Boltzmann methods comes with a challenging set of constraints: a complex geometry with walls and inlets and outlets at arbitrary orientations with respect to the lattice, intermediate Reynolds (Re) number, and unsteady flow. Simple bounce-back is one of the most commonly used, simplest, and most computationally efficient boundary conditions, but many others have been proposed. We implement three other methods applicable to complex geometries [Guo, Zheng, and Shi, Phys. Fluids 14, 2007 (2002); Bouzidi, Firdaouss, and Lallemand, Phys. Fluids 13, 3452 (2001); Junk and Yang, Phys. Rev. E 72, 066701 (2005)] in our open-source application hemelb. We use these to simulate Poiseuille and Womersley flows in a cylindrical pipe with an arbitrary orientation at physiologically relevant Re number (1-300) and Womersley (4-12) numbers and steady flow in a curved pipe at relevant Dean number (100-200) and compare the accuracy to analytical solutions. We find that both the Bouzidi-Firdaouss-Lallemand (BFL) and Guo-Zheng-Shi (GZS) methods give second-order convergence in space while simple bounce-back degrades to first order. The BFL method appears to perform better than GZS in unsteady flows and is significantly less computationally expensive. The Junk-Yang method shows poor stability at larger Re number and so cannot be recommended here. The choice of collision operator (lattice Bhatnagar-Gross-Krook vs multiple relaxation time) and velocity set (D3Q15 vs D3Q19 vs D3Q27) does not significantly affect the accuracy in the problems studied.

RADStation3G: a platform for cardiovascular image analysis integrating PACS, 3D+t visualization and grid computing

RADStation3G is a software platform for cardiovascular image analysis and surgery planning. It provides image visualization and management in 2D, 3D and 3D+t; data storage (images or operational results) in a PACS (using DICOM); and exploitation of patients' data such as images and pathologies. Further, it provides support for computationally expensive processes with grid technology. In this article we first introduce the platform and present a comparison with existing systems, according to the platform's modules (for cardiology, angiology, PACS archived enriched searching and grid computing), and then RADStation3G is described in detail.

AngioLab--a software tool for morphological analysis and endovascular treatment planning of intracranial aneurysms

Determining whether and how an intracranial aneurysm should be treated is a tough decision that clinicians face everyday. Emerging computational tools could help clinicians analyze clinical data and make these decisions. AngioLab is a single graphical user interface, developed on top of the open source framework GIMIAS, that integrates some of the latest image analysis and computational modeling tools for intracranial aneurysms. Two workflows are available: Advanced Morphological Analysis (AMA) and Endovascular Treatment Planning (ETP). AngioLab has been evaluated by a total of 62 clinicians, who considered the information provided by AngioLab relevant and meaningful. They acknowledged the emerging need of these type of tools and the potential impact they might have on the clinical decision-making process.

Simple measurement of aneurysm residual after treatment: the SMART scale for evaluation of intracranial aneurysms treated with flow diverters

BACKGROUND

Primary endovascular reconstruction with flow diversion represents a fundamental paradigm shift in the technique of endovascular aneurysm treatment. Unlike coil embolization, often there remains residual post-procedural filling within the aneurysm with flow diverters, the curative reconstruction presumably occurring over a period of weeks. Thus, conventional grading scales for post-procedural aneurysm occlusion and recanalization are inadequate. The aim of this paper is to propose a new angiographic grading scale that addresses this fundamentally new treatment option.

METHOD

A five-point grading scale describes the location of residual flow within the aneurysm in the venous phase [grade 1: patent aneurysm with diffuse inflow; grade 2: residual filling of the aneurysm dome (saccular) or wall (fusiform); grade 3: only residual neck (saccular) or only intra-aneurysmal filling with former boundaries covered (fusiform); grade 4: complete occlusion].

FINDINGS

Grade 0 represents any aneurysm, regardless of occlusion rate with early phase, coherent inflow jet. Intra-aneurysmal flow stagnation is categorized into: (a) none, (b) capillary phase, and (c) venous phase. Prevailing parent vessel hemodynamics with in-stent stenosis (ISS) are divided into none (ISS0), mild (ISS1), moderate (ISS2), severe (ISS3), and total (ISS4) occlusion. The proposed grading scales allow assessment of the hemodynamic consequences of stent placement on endosaccular in-flow, stasis, and location of stasis as well as parent vessel hemodynamics.

CONCLUSIONS

Further studies need to show the applicability and possible predictive value of this new grading scale on the efficacy of the stent in promoting intra-aneurysmal flow stagnation, thus creating the potential to harmonize the results of future papers. This may help to optimize treatment and future device design.

@neurIST complex information processing toolchain for the integrated management of cerebral aneurysms

Cerebral aneurysms are a multi-factorial disease with severe consequences. A core part of the European project @neurIST was the physical characterization of aneurysms to find candidate risk factors associated with aneurysm rupture. The project investigated measures based on morphological, haemodynamic and aneurysm wall structure analyses for more than 300 cases of ruptured and unruptured aneurysms, extracting descriptors suitable for statistical studies. This paper deals with the unique challenges associated with this task, and the implemented solutions. The consistency of results required by the subsequent statistical analyses, given the heterogeneous image data sources and multiple human operators, was met by a highly automated toolchain combined with training. A testimonial of the successful automation is the positive evaluation of the toolchain by over 260 clinicians during various hands-on workshops. The specification of the analyses required thorough investigations of modelling and processing choices, discussed in a detailed analysis protocol. Finally, an abstract data model governing the management of the simulation-related data provides a framework for data provenance and supports future use of data and toolchain. This is achieved by enabling the easy modification of the modelling approaches and solution details through abstract problem descriptions, removing the need of repetition of manual processing work.

Influence of different computational approaches for stent deployment on cerebral aneurysm haemodynamics

Cerebral aneurysms are abnormal focal dilatations of artery walls. The interest in virtual tools to help clinicians to value the effectiveness of different procedures for cerebral aneurysm treatment is constantly growing. This study is focused on the analysis of the influence of different stent deployment approaches on intra-aneurysmal haemodynamics using computational fluid dynamics (CFD). A self-expanding stent was deployed in an idealized aneurysmatic cerebral vessel in two initial positions. Different cases characterized by a progression of simplifications on stent modelling (geometry and material) and vessel material properties were set up, using finite element and fast virtual stenting methods. Then, CFD analysis was performed for untreated and stented vessels. Haemodynamic parameters were analysed qualitatively and quantitatively, comparing the cases and the two initial positions. All the cases predicted a reduction of average wall shear stress and average velocity of almost 50 per cent after stent deployment for both initial positions. Results highlighted that, although some differences in calculated parameters existed across the cases based on the modelling simplifications, all the approaches described the most important effects on intra-aneurysmal haemodynamics. Hence, simpler and faster modelling approaches could be included in clinical workflow and, despite the adopted simplifications, support clinicians in the treatment planning.

Automated segmentation of cerebral vasculature with aneurysms in 3DRA and TOF-MRA using geodesic active regions: an evaluation study

PURPOSE

To evaluate the suitability of an improved version of an automatic segmentation method based on geodesic active regions (GAR) for segmenting cerebral vasculature with aneurysms from 3D x-ray reconstruction angiography (3DRA) and time of flight magnetic resonance angiography (TOF-MRA) images available in the clinical routine.

METHODS

Three aspects of the GAR method have been improved: execution time, robustness to variability in imaging protocols, and robustness to variability in image spatial resolutions. The improved GAR was retrospectively evaluated on images from patients containing intracranial aneurysms in the area of the Circle of Willis and imaged with two modalities: 3DRA and TOF-MRA. Images were obtained from two clinical centers, each using different imaging equipment. Evaluation included qualitative and quantitative analyses of the segmentation results on 20 images from 10 patients. The gold standard was built from 660 cross-sections (33 per image) of vessels and aneurysms, manually measured by interventional neuroradiologists. GAR has also been compared to an interactive segmentation method: isointensity surface extraction (ISE). In addition, since patients had been imaged with the two modalities, we performed an intermodality agreement analysis with respect to both the manual measurements and each of the two segmentation methods.

RESULTS

Both GAR and ISE differed from the gold standard within acceptable limits compared to the imaging resolution. GAR (ISE) had an average accuracy of 0.20 (0.24) mm for 3DRA and 0.27 (0.30) mm for TOF-MRA, and had a repeatability of 0.05 (0.20) mm. Compared to ISE, GAR had a lower qualitative error in the vessel region and a lower quantitative error in the aneurysm region. The repeatability of GAR was superior to manual measurements and ISE. The intermodality agreement was similar between GAR and the manual measurements.

CONCLUSIONS

The improved GAR method outperformed ISE qualitatively as well as quantitatively and is suitable for segmenting 3DRA and TOF-MRA images from clinical routine.

Morphological descriptors as rupture indicators in middle cerebral artery aneurysms

The rupture of intracranial aneurysms is associated to significant morbidity and mortality rates. Although the mechanisms triggering this event are still unclear, morphology is among the factors considered by interventional neuroradiologists to decide treatment. The aim of this work is to explore the potential of morphological descriptors as rupture risk predictors in middle cerebral artery aneurysms (MCA) and to provide the subset showing the best predictive capabilities. The set of evaluated descriptors include basic shape descriptors related to the aneurysm size, and most sophisticated ones such as the Zernike Moment Invariants. The population analyzed included 71 patients harboring 86 MCA aneurysms (64 unruptured vs. 22 ruptured). An existing image-based processing pipeline was used to extract such descriptors from Three-Dimensional Rotational Angiography (3DRA) images routinely acquired during standard clinical practice. Univariate and multivariate statistical analyses have shown that among the evaluated descriptors, Zernike moment invariants computed on the aneurysm and a small portion of the surrounding vessels, together with the non-sphericity index, provide the best predictive capabilities of aneurysm rupture.

AngioLab: integrated technology for patient-specific management of intracranial aneurysms

AngioLab is a software tool developed within the GIMIAS framework and is part of a more ambitious pipeline for the integrated management of cerebral aneurysms. AngioLab currently includes three plug-ins: angio segmentation, angio morphology and stenting, as well as supports advanced rendering techniques for the visualization of virtual angiographies. In December 2009, 23 clinicians completed an evaluation questionnaire about AngioLab. This activity was part of a teaching course held during the 2(nd) European Society for Minimally Invasive Neurovascular Treatment (ESMINT) Teaching Course held at the Universitat Pompeu Fabra, Barcelona, Spain. The Automated Morphological Analysis (angio morphology plug-in) and the Endovascular Treatment Planning (stenting plug-in) were evaluated. In general, the results provided by these tools were considered as relevant and as an emerging need in their clinical field.