Tyler C Diorio, Vidhya Vijayakrishnan Nair, Neal M Patel, Lauren E Hedges, Vitaliy L Rayz, Yunjie Tong
{"title":"利用fMRI流入效应估计体内脑脊液流速","authors":"Tyler C Diorio, Vidhya Vijayakrishnan Nair, Neal M Patel, Lauren E Hedges, Vitaliy L Rayz, Yunjie Tong","doi":"10.1101/2023.08.14.553250","DOIUrl":null,"url":null,"abstract":"<p><p><i>In vivo</i> estimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory gated approaches, such as 4D flow MRI, cannot capture CSF movement in real time due to limited temporal resolution and in addition deteriorate in accuracy at low fluid velocities. Other techniques like real-time PC-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability even in research settings. This study aims to quantify the inflow effect of dynamic CSF motion on functional magnetic resonance imaging (fMRI) for <i>in vivo</i>, real-time measurement of CSF flow velocity. We considered linear and nonlinear models of velocity waveforms and empirically fit them to fMRI data from a controlled flow experiment. To assess the utility of this methodology in human data, CSF flow velocities were computed from fMRI data acquired in eight healthy volunteers. Breath holding regimens were used to amplify CSF flow oscillations. Our experimental flow study revealed that CSF velocity is nonlinearly related to inflow effect-mediated signal increase and well estimated using an extension of a previous nonlinear framework. Using this relationship, we recovered velocity from <i>in vivo</i> fMRI signal, demonstrating the potential of our approach for estimating CSF flow velocity in the human brain. This novel method could serve as an alternative approach to quantifying slow flow velocities in real time, such as CSF flow in the ventricular system, thereby providing valuable insights into the glymphatic system's function and its implications for neurological disorders.</p>","PeriodicalId":7054,"journal":{"name":"Accounting and Business Research","volume":"30 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2023-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634978/pdf/","citationCount":"0","resultStr":"{\"title\":\"Real-time Quantification of in vivo cerebrospinal fluid velocity using fMRI inflow effect.\",\"authors\":\"Tyler C Diorio, Vidhya Vijayakrishnan Nair, Neal M Patel, Lauren E Hedges, Vitaliy L Rayz, Yunjie Tong\",\"doi\":\"10.1101/2023.08.14.553250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><i>In vivo</i> estimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory gated approaches, such as 4D flow MRI, cannot capture CSF movement in real time due to limited temporal resolution and in addition deteriorate in accuracy at low fluid velocities. Other techniques like real-time PC-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability even in research settings. This study aims to quantify the inflow effect of dynamic CSF motion on functional magnetic resonance imaging (fMRI) for <i>in vivo</i>, real-time measurement of CSF flow velocity. We considered linear and nonlinear models of velocity waveforms and empirically fit them to fMRI data from a controlled flow experiment. To assess the utility of this methodology in human data, CSF flow velocities were computed from fMRI data acquired in eight healthy volunteers. Breath holding regimens were used to amplify CSF flow oscillations. Our experimental flow study revealed that CSF velocity is nonlinearly related to inflow effect-mediated signal increase and well estimated using an extension of a previous nonlinear framework. Using this relationship, we recovered velocity from <i>in vivo</i> fMRI signal, demonstrating the potential of our approach for estimating CSF flow velocity in the human brain. This novel method could serve as an alternative approach to quantifying slow flow velocities in real time, such as CSF flow in the ventricular system, thereby providing valuable insights into the glymphatic system's function and its implications for neurological disorders.</p>\",\"PeriodicalId\":7054,\"journal\":{\"name\":\"Accounting and Business Research\",\"volume\":\"30 1\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2023-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634978/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounting and Business Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2023.08.14.553250\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounting and Business Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2023.08.14.553250","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Real-time Quantification of in vivo cerebrospinal fluid velocity using fMRI inflow effect.
In vivo estimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory gated approaches, such as 4D flow MRI, cannot capture CSF movement in real time due to limited temporal resolution and in addition deteriorate in accuracy at low fluid velocities. Other techniques like real-time PC-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability even in research settings. This study aims to quantify the inflow effect of dynamic CSF motion on functional magnetic resonance imaging (fMRI) for in vivo, real-time measurement of CSF flow velocity. We considered linear and nonlinear models of velocity waveforms and empirically fit them to fMRI data from a controlled flow experiment. To assess the utility of this methodology in human data, CSF flow velocities were computed from fMRI data acquired in eight healthy volunteers. Breath holding regimens were used to amplify CSF flow oscillations. Our experimental flow study revealed that CSF velocity is nonlinearly related to inflow effect-mediated signal increase and well estimated using an extension of a previous nonlinear framework. Using this relationship, we recovered velocity from in vivo fMRI signal, demonstrating the potential of our approach for estimating CSF flow velocity in the human brain. This novel method could serve as an alternative approach to quantifying slow flow velocities in real time, such as CSF flow in the ventricular system, thereby providing valuable insights into the glymphatic system's function and its implications for neurological disorders.
期刊介绍:
Accounting and Business Research publishes papers containing a substantial and original contribution to knowledge. Papers may cover any area of accounting, broadly defined and including corporate governance, auditing and taxation. However the focus must be accounting, rather than (corporate) finance or general management. Authors may take a theoretical or an empirical approach, using either quantitative or qualitative methods. They may aim to contribute to developing and understanding the role of accounting in business. Papers should be rigorous but also written in a way that makes them intelligible to a wide range of academics and, where appropriate, practitioners.