31d0854ad680367bfe22dd3f3b51fd82 270280.pdf afff9522c9497fdf416528d3bfb4a70ab77765f5 270280.pdf 4bc1723fdeb9a1336a839a7507e4a222965c76a5ff3f6960827a079ea47c5e8c 270280.pdf Title: Sensitivity Analysis of In Silico Fluid Simulations to Predict Thrombus Formation after Left Atrial Appendage Occlusion Subject: Atrial fibrillation (AF) is nowadays the most common human arrhythmia and it is considered a marker of an increased risk of embolic stroke. It is known that 99% of AF-related thrombi are generated in the left atrial appendage (LAA), an anatomical structure located within the left atrium (LA). Left atrial appendage occlusion (LAAO) has become a good alternative for nonvalvular AF patients with contraindications to anticoagulants. However, there is a non-negligible number of device-related thrombus (DRT) events, created next to the device surface. In silico fluid simulations can be a powerful tool to better understand the relation between LA anatomy, haemodynamics, and the process of thrombus formation. Despite the increasing literature in LA fluid modelling, a consensus has not been reached yet in the community on the optimal modelling choices and boundary conditions for generating realistic simulations. In this line, we have performed a sensitivity analysis of several boundary conditions scenarios, varying inlet/outlet and LA wall movement configurations, using patient-specific imaging data of six LAAO patients (three of them with DRT at follow-up). Mesh and cardiac cycle convergence were also analysed. The boundary conditions scenario that better predicted DRT cases had echocardiography-based velocities at the mitral valve outlet, a generic pressure wave from an AF patient at the pulmonary vein inlets, and a dynamic mesh approach for LA wall deformation, emphasizing the need for patient-specific data for realistic simulations. The obtained promising results need to be further validated with larger cohorts, ideally with ground truth data, but they already offer unique insights on thrombogenic risk in the left atria. Keywords: sensitivity analysis; boundary conditions; computational fluid dynamics; dynamic mesh; device-related thrombus; left atrium; left atrial appendage Author: Jordi Mill, Victor Agudelo, Andy L. Olivares, Maria Isabel Pons, Etelvino Silva, Marta Nuñez-Garcia, Xabier Morales, Dabit Arzamendi, Xavier Freixa, Jérôme Noailly and Oscar Camara Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Wed Sep 22 05:10:48 2021 CEST ModDate: Wed Sep 22 05:21:07 2021 CEST Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 19 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 14122832 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- KIIOKQ+URWPalladioL-Ital Type 1 Custom yes yes no 10 0 LMZPTZ+URWPalladioL-Bold Type 1 Custom yes yes no 15 0 TGYOPM+URWPalladioL-Roma Type 1 Custom yes yes no 19 0 DVTHKG+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 27 0 MCBCCI+SourceSansRoman-Regular Type 1C Custom yes yes no 45 0 MCBCCM+SourceSansRoman.613wght Type 1C Custom yes yes no 49 0 MCBCCO+SourceSansRoman-Bold 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Velocities, and Rigid Wall Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@4d3167f4 Item: Title: Scenario 3: Patient Pressure Wave as Inlet, Imaging-Based Outlet Velocities, and Dynamic Mesh Wall Deformation Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@ed9d034 Item: Title: Scenario 4: Literature Velocity Profile as Inlet, Mitral Valve as Wall (Systole) or Constant Pressure (Diastole), and Dynamic Mesh Wall Deformation Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@6121c9d6 Item: Title: Mesh and Cardiac Cycle Convergence Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@87f383f Item: Title: In Silico Prediction of Device-Related Thrombosis Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@4eb7f003 Item: Title: Discussion Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@eafc191 Children: Item: Title: Boundary Conditions Scenarios Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@612fc6eb Item: Title: In Silico Prediction of Device-Related Thrombosis Risk Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1060b431 Item: Title: Mesh and Cardiac Cycle Convergence Analysis Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@612679d6 Item: Title: Limitations and Future Work Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@11758f2a Item: Title: Conclusions Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@e720b71 Item: Title: References Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1b26f7b2 Info: Title: Sensitivity Analysis of In Silico Fluid Simulations to Predict Thrombus Formation after Left Atrial Appendage Occlusion Author: Jordi Mill, Victor Agudelo, Andy L. Olivares, Maria Isabel Pons, Etelvino Silva, Marta Nuñez-Garcia, Xabier Morales, Dabit Arzamendi, Xavier Freixa, Jérôme Noailly and Oscar Camara Subject: Atrial fibrillation (AF) is nowadays the most common human arrhythmia and it is considered a marker of an increased risk of embolic stroke. It is known that 99% of AF-related thrombi are generated in the left atrial appendage (LAA), an anatomical structure located within the left atrium (LA). Left atrial appendage occlusion (LAAO) has become a good alternative for nonvalvular AF patients with contraindications to anticoagulants. However, there is a non-negligible number of device-related thrombus (DRT) events, created next to the device surface. In silico fluid simulations can be a powerful tool to better understand the relation between LA anatomy, haemodynamics, and the process of thrombus formation. Despite the increasing literature in LA fluid modelling, a consensus has not been reached yet in the community on the optimal modelling choices and boundary conditions for generating realistic simulations. In this line, we have performed a sensitivity analysis of several boundary conditions scenarios, varying inlet/outlet and LA wall movement configurations, using patient-specific imaging data of six LAAO patients (three of them with DRT at follow-up). Mesh and cardiac cycle convergence were also analysed. The boundary conditions scenario that better predicted DRT cases had echocardiography-based velocities at the mitral valve outlet, a generic pressure wave from an AF patient at the pulmonary vein inlets, and a dynamic mesh approach for LA wall deformation, emphasizing the need for patient-specific data for realistic simulations. The obtained promising results need to be further validated with larger cohorts, ideally with ground truth data, but they already offer unique insights on thrombogenic risk in the left atria. Keywords: sensitivity analysis; boundary conditions; computational fluid dynamics; dynamic mesh; device-related thrombus; left atrium; left atrial appendage Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Wed Sep 22 05:10:48 CEST 2021 ModDate: Wed Sep 22 05:21:07 CEST 2021 ID: 0x9c93f7dfc874d139cc8bcf65c74166ee, 0x9c93f7dfc874d139cc8bcf65c74166ee Filters: FilterPipeline: FlateDecode FilterPipeline: DCTDecode Images: Image: NisoImageMetadata: FormatName: image/jpg CompressionScheme: JPEG ImageWidth: 2796 ImageHeight: 1973 ColorSpace: RGB BitsPerSample: 8 BitsPerSampleUnit: integer Image: NisoImageMetadata: FormatName: image/png ImageWidth: 1622 ImageHeight: 2014 ColorSpace: RGB BitsPerSample: 8 BitsPerSampleUnit: integer Filter: FlateDecode Image: NisoImageMetadata: FormatName: image/png ImageWidth: 2652 ImageHeight: 1276 ColorSpace: RGB BitsPerSample: 8 BitsPerSampleUnit: integer Filter: FlateDecode Image: NisoImageMetadata: FormatName: image/png ImageWidth: 1914 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Annotation: Subtype: Link Rect: 59, 331, 97, 341 Annotation: Subtype: Link Rect: 103, 331, 139, 341 Annotation: Subtype: Link Rect: 216, 296, 254, 306 Annotation: Subtype: Link Rect: 295, 272, 332, 283 Annotation: Subtype: Link Rect: 407, 249, 445, 260 Checksum: 585098da Type: CRC32 Checksum: 31d0854ad680367bfe22dd3f3b51fd82 Type: MD5 Checksum: afff9522c9497fdf416528d3bfb4a70ab77765f5 Type: SHA-1