Caroline H Roney, Jose Alonso Solis Lemus, Carlos Lopez Barrera, Alexander Zolotarev, Onur Ulgen, Eric Kerfoot, Laura Bevis, Semhar Misghina, Caterina Vidal Horrach, Ovais A Jaffery, Mahmoud Ehnesh, Cristobal Rodero, Dhani Dharmaprani, Gonzalo R Ríos-Muñoz, Anand Ganesan, Wilson W Good, Aurel Neic, Gernot Plank, Luuk H G A Hopman, Marco J W Götte, Shohreh Honarbakhsh, Sanjiv M Narayan, Edward Vigmond, Steven Niederer
{"title":"按比例构建双层和容积心房模型。","authors":"Caroline H Roney, Jose Alonso Solis Lemus, Carlos Lopez Barrera, Alexander Zolotarev, Onur Ulgen, Eric Kerfoot, Laura Bevis, Semhar Misghina, Caterina Vidal Horrach, Ovais A Jaffery, Mahmoud Ehnesh, Cristobal Rodero, Dhani Dharmaprani, Gonzalo R Ríos-Muñoz, Anand Ganesan, Wilson W Good, Aurel Neic, Gernot Plank, Luuk H G A Hopman, Marco J W Götte, Shohreh Honarbakhsh, Sanjiv M Narayan, Edward Vigmond, Steven Niederer","doi":"10.1098/rsfs.2023.0038","DOIUrl":null,"url":null,"abstract":"<p><p>To enable large <i>in silico</i> trials and personalized model predictions on clinical timescales, it is imperative that models can be constructed quickly and reproducibly. First, we aimed to overcome the challenges of constructing cardiac models at scale through developing a robust, open-source pipeline for bilayer and volumetric atrial models. Second, we aimed to investigate the effects of fibres, fibrosis and model representation on fibrillatory dynamics. To construct bilayer and volumetric models, we extended our previously developed coordinate system to incorporate transmurality, atrial regions and fibres (rule-based or data driven diffusion tensor magnetic resonance imaging (MRI)). We created a cohort of 1000 biatrial bilayer and volumetric models derived from computed tomography (CT) data, as well as models from MRI, and electroanatomical mapping. Fibrillatory dynamics diverged between bilayer and volumetric simulations across the CT cohort (correlation coefficient for phase singularity maps: left atrial (LA) 0.27 ± 0.19, right atrial (RA) 0.41 ± 0.14). Adding fibrotic remodelling stabilized re-entries and reduced the impact of model type (LA: 0.52 ± 0.20, RA: 0.36 ± 0.18). The choice of fibre field has a small effect on paced activation data (less than 12 ms), but a larger effect on fibrillatory dynamics. Overall, we developed an open-source user-friendly pipeline for generating atrial models from imaging or electroanatomical mapping data enabling <i>in silico</i> clinical trials at scale (https://github.com/pcmlab/atrialmtk).</p>","PeriodicalId":13795,"journal":{"name":"Interface Focus","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10722212/pdf/","citationCount":"0","resultStr":"{\"title\":\"Constructing bilayer and volumetric atrial models at scale.\",\"authors\":\"Caroline H Roney, Jose Alonso Solis Lemus, Carlos Lopez Barrera, Alexander Zolotarev, Onur Ulgen, Eric Kerfoot, Laura Bevis, Semhar Misghina, Caterina Vidal Horrach, Ovais A Jaffery, Mahmoud Ehnesh, Cristobal Rodero, Dhani Dharmaprani, Gonzalo R Ríos-Muñoz, Anand Ganesan, Wilson W Good, Aurel Neic, Gernot Plank, Luuk H G A Hopman, Marco J W Götte, Shohreh Honarbakhsh, Sanjiv M Narayan, Edward Vigmond, Steven Niederer\",\"doi\":\"10.1098/rsfs.2023.0038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>To enable large <i>in silico</i> trials and personalized model predictions on clinical timescales, it is imperative that models can be constructed quickly and reproducibly. First, we aimed to overcome the challenges of constructing cardiac models at scale through developing a robust, open-source pipeline for bilayer and volumetric atrial models. Second, we aimed to investigate the effects of fibres, fibrosis and model representation on fibrillatory dynamics. To construct bilayer and volumetric models, we extended our previously developed coordinate system to incorporate transmurality, atrial regions and fibres (rule-based or data driven diffusion tensor magnetic resonance imaging (MRI)). We created a cohort of 1000 biatrial bilayer and volumetric models derived from computed tomography (CT) data, as well as models from MRI, and electroanatomical mapping. Fibrillatory dynamics diverged between bilayer and volumetric simulations across the CT cohort (correlation coefficient for phase singularity maps: left atrial (LA) 0.27 ± 0.19, right atrial (RA) 0.41 ± 0.14). Adding fibrotic remodelling stabilized re-entries and reduced the impact of model type (LA: 0.52 ± 0.20, RA: 0.36 ± 0.18). The choice of fibre field has a small effect on paced activation data (less than 12 ms), but a larger effect on fibrillatory dynamics. Overall, we developed an open-source user-friendly pipeline for generating atrial models from imaging or electroanatomical mapping data enabling <i>in silico</i> clinical trials at scale (https://github.com/pcmlab/atrialmtk).</p>\",\"PeriodicalId\":13795,\"journal\":{\"name\":\"Interface Focus\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2023-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10722212/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Interface Focus\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1098/rsfs.2023.0038\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/12/6 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interface Focus","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1098/rsfs.2023.0038","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/12/6 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
Constructing bilayer and volumetric atrial models at scale.
To enable large in silico trials and personalized model predictions on clinical timescales, it is imperative that models can be constructed quickly and reproducibly. First, we aimed to overcome the challenges of constructing cardiac models at scale through developing a robust, open-source pipeline for bilayer and volumetric atrial models. Second, we aimed to investigate the effects of fibres, fibrosis and model representation on fibrillatory dynamics. To construct bilayer and volumetric models, we extended our previously developed coordinate system to incorporate transmurality, atrial regions and fibres (rule-based or data driven diffusion tensor magnetic resonance imaging (MRI)). We created a cohort of 1000 biatrial bilayer and volumetric models derived from computed tomography (CT) data, as well as models from MRI, and electroanatomical mapping. Fibrillatory dynamics diverged between bilayer and volumetric simulations across the CT cohort (correlation coefficient for phase singularity maps: left atrial (LA) 0.27 ± 0.19, right atrial (RA) 0.41 ± 0.14). Adding fibrotic remodelling stabilized re-entries and reduced the impact of model type (LA: 0.52 ± 0.20, RA: 0.36 ± 0.18). The choice of fibre field has a small effect on paced activation data (less than 12 ms), but a larger effect on fibrillatory dynamics. Overall, we developed an open-source user-friendly pipeline for generating atrial models from imaging or electroanatomical mapping data enabling in silico clinical trials at scale (https://github.com/pcmlab/atrialmtk).
期刊介绍:
Each Interface Focus themed issue is devoted to a particular subject at the interface of the physical and life sciences. Formed of high-quality articles, they aim to facilitate cross-disciplinary research across this traditional divide by acting as a forum accessible to all. Topics may be newly emerging areas of research or dynamic aspects of more established fields. Organisers of each Interface Focus are strongly encouraged to contextualise the journal within their chosen subject.