@article{nokeyc,

title = {Verification Study of In Silico Computed Intracardiac Blood Flow With 4D Flow MRI},

author = {Lukas Obermeier and M. Wiegand and F. Hellmeier and C. Manini and Titus Kuehne and Leonid Goubergrits},

editor = {IEEE},

url = {https://ieeexplore.ieee.org/document/10478556},

doi = {10.1109/TBME.2024.3381212},

year  = {2024},

date = {2024-03-25},

urldate = {2024-03-25},

journal = {IEEE Transactions on Biomedical Engineering},

volume = {71},

issue = {9},

pages = {2568 - 2579},

abstract = {Objective: Major challenges for clinical applications of in silico medicine are limitations in time and computational resources. Computational approaches should therefore be tailored to specific applications with relatively low complexity and must be verified and validated against clinical gold standards. Methods: This study performed computational fluid dynamics simulations of left ventricular hemodynamics of different complexity based on shape reconstruction from steady state gradient echo magnetic resonance imaging (MRI) data. Computed flow results of a rigid wall model (RWM) and a prescribed motion fluid-structure interaction (PM-FSI) model were compared against phase-contrast MRI measurements for three healthy subjects. Results: Extracted boundary conditions from the steady state MRI sequences as well as computed metrics, such as flow rate, valve velocities, and kinetic energy show good agreement with in vivo flow measurements. Regional flow analysis reveals larger differences. Conclusion: Basic flow structures are well captured with RWM and PM-FSI. For the computation of further biomarkers like washout or flow efficiency, usage of PM-FSI is required. Regarding boundary-near flow, more accurate anatomical models are inevitable. Significance: These results delineate areas of application of both methods and lay a foundation for larger validation studies and sensitivity analysis for healthy and diseased cases, being an essential step upon clinical translations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokeyg,

title = {Inter-model and inter-modality analysis of left ventricular hemodynamics: comparative study of two CFD approaches based on TTE and MRI},

author = {Lukas Obermeier and Jana Korte and Katharina Vellguth and Fabian Barbieri and Florian Hellmeier and Philipp Berg and Leonid Goubergrits},

url = {https://onlinelibrary.wiley.com/doi/full/10.1002/gamm.202370004},

doi = {10.1002/gamm.202370004},

year  = {2024},

date = {2024-01-23},

urldate = {2024-01-23},

journal = {GAMM-Mitteilungen},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1136/bmjopen-2022-063051,

title = {Geometric uncertainty in intracranial aneurysm rupture status discrimination: a two-site retrospective study},

author = {Florian Hellmeier and Jan Bruening and Philipp Berg and Sylvia Saalfeld and Andreas Spuler and Erol I. Sandalcioglu and Oliver Beuing and Naomi Larsen and Jens Schaller and Leonid Goubergrits},

editor = {BMJ Open},

url = {https://pubmed.ncbi.nlm.nih.gov/36351732/},

doi = {10.1136/bmjopen-2022-063051},

year  = {2022},

date = {2022-11-08},

urldate = {2022-11-08},

journal = {BMJ Open},

volume = {12},

issue = {11},

abstract = {Assessing the risk associated with unruptured intracranial aneurysms (IAs) is essential in clinical decision making. Several geometric risk parameters have been proposed for this purpose. However, performance of these parameters has been inconsistent. This study evaluates the performance and robustness of geometric risk parameters on two datasets and compare it to the uncertainty inherent in assessing these parameters and quantifies interparameter correlations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.3389/fcvm.2022.901902,

title = {CT-Based Analysis of Left Ventricular Hemodynamics Using Statistical Shape Modeling and Computational Fluid Dynamics},

author = {Leonid Goubergrits and Katharina Vellguth and Lukas Obermeier and Adriano Schlief and Lennart Tautz and Jan Bruening and Hans Lamecker and Angelika Szengel and Olena Nemchyna and Christoph Knosalla and Titus Kuehne and Natalia Solowjowa},

editor = {Frontiers Cardiovascular Medicine},

url = {https://www.frontiersin.org/articles/10.3389/fcvm.2022.901902/full},

doi = {10.3389/fcvm.2022.901902“},

year  = {2022},

date = {2022-07-05},

urldate = {2022-07-05},

journal = {Front. Cardiovasc. Med., 05 July 2022},

volume = {Sec. Cardiovascular Imaging},

issue = {Volume 9 - 2022},

pages = {901902},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Obermeier2022,

title = {CT-Based Simulation of Left Ventricular Hemodynamics: A Pilot Study in Mitral Regurgitation and Left Ventricle Aneurysm Patients},

author = {Lukas Obermeier and Katharina Vellguth and Adriano Schlief and Lennart Tautz and Jan Bruening and Christoph Knosalla and Titus Kuehne and Natalia Solowjowa and Leonid Goubergrits},

doi = {10.3389/fcvm.2022.828556},

issn = {2297-055X},

year  = {2022},

date = {2022-03-22},

urldate = {2022-03-22},

journal = {Frontiers in Cardiovascular Medicine},

issue = {9/2022},

abstract = {Background: Cardiac CT (CCT) is well suited for a detailed analysis of heart structures due to its high spatial resolution, but in contrast to MRI and echocardiography, CCT does not allow an assessment of intracardiac flow. Computational fluid dynamics (CFD) can complement this shortcoming. It enables the computation of hemodynamics at a high spatio-temporal resolution based on medical images. The aim of this proposed study is to establish a CCT-based CFD methodology for the analysis of left ventricle (LV) hemodynamics and to assess the usability of the computational framework for clinical practice. 

Materials and methods: The methodology is demonstrated by means of four cases selected from a cohort of 125 multiphase CCT examinations of heart failure patients. These cases represent subcohorts of patients with and without LV aneurysm and with severe and no mitral regurgitation (MR). All selected LVs are dilated and characterized by a reduced ejection fraction (EF). End-diastolic and end-systolic image data was used to reconstruct LV geometries with 2D valves as well as the ventricular movement. The intraventricular hemodynamics were computed with a prescribed-motion CFD approach and evaluated in terms of large-scale flow patterns, energetic behavior, and intraventricular washout. 

Results: In the MR patients, a disrupted E-wave jet, a fragmentary diastolic vortex formation and an increased specific energy dissipation in systole are observed. In all cases, regions with an impaired washout are visible. The results furthermore indicate that considering several cycles might provide a more detailed view of the washout process. The pre-processing times and computational expenses are in reach of clinical feasibility. 

Conclusion: The proposed CCT-based CFD method allows to compute patient-specific intraventricular hemodynamics and thus complements the informative value of CCT. The method can be applied to any CCT data of common quality and represents a fair balance between model accuracy and overall expenses. With further model enhancements, the computational framework has the potential to be embedded in clinical routine workflows, to support clinical decision making and treatment planning. 

Keywords: cardiac computed tomography; computational fluid dynamics; fluid-structure interaction; image-based modeling; intraventricular hemodynamics; left ventricle aneurysm; mitral regurgitation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}