{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105005"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105005","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Cerebrospinal fluid flow quantification in the brain using magnetic resonance imaging","abstract":"Hydrocephalus is a severe brain condition in which cerebrospinal fluid (CSF) cannot properly drain into the spinal cord, resulting in a buildup of pressure. To relieve this pressure, a shunt is placed in the brain that drains the CSF. However, the failure rate of these shunts is high, requiring additional surgeries to check functionality or for replacement. As this is costly and invasive, a way to quantitatively measure the shunt flow without surgery would be valuable. In this work, we modify a previously successful technique that quantified blood flow in the brain to quantify CSF flow. This technique, called flow enhanced signal intensity (FENSI), uses magnetic resonance (MR) to gain a quick and accurate measurement. By adjusting imaging parameters from quantitative FENSI (qFENSI), we can optimize this sequence to be sensitive to CSF flow. We demonstrate the sensitivity of our technique down to 0.1 ml/min and up to 0.4 ml/min. Additionally, taking into account the T1 relaxation rate, we can fit a curve to the data points using simulations to predict the flow rate of the measured signal.","abstract_html":"Hydrocephalus is a severe brain condition in which cerebrospinal fluid (CSF) cannot properly drain into the spinal cord, resulting in a buildup of pressure. To relieve this pressure, a shunt is placed in the brain that drains the CSF. However, the failure rate of these shunts is high, requiring additional surgeries to check functionality or for replacement. As this is costly and invasive, a way to quantitatively measure the shunt flow without surgery would be valuable. In this work, we modify a previously successful technique that quantified blood flow in the brain to quantify CSF flow. This technique, called flow enhanced signal intensity (FENSI), uses magnetic resonance (MR) to gain a quick and accurate measurement. By adjusting imaging parameters from quantitative FENSI (qFENSI), we can optimize this sequence to be sensitive to CSF flow. We demonstrate the sensitivity of our technique down to 0.1 ml/min and up to 0.4 ml/min. Additionally, taking into account the T1 relaxation rate, we can fit a curve to the data points using simulations to predict the flow rate of the measured signal.","abstract_has_math":false,"creators":["Aw, Natalie Wai-Yee"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Sutton, Brad","Liang, Zhi-Pei"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-08-23T20:35:50Z","date_published":"2019-08-23T20:35:50Z","updated_at":"2026-07-22T22:24:44Z","subjects":["Magnetic resonance imaging","MRI","FENSI","CSF shunt flow"],"languages":["en"],"rights":["Copyright 2019 Natalie W. 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By adjusting imaging parameters from quantitative FENSI (qFENSI), we can optimize this sequence to be sensitive to CSF flow. We demonstrate the sensitivity of our technique down to 0.1 ml/min and up to 0.4 ml/min. Additionally, taking into account the T1 relaxation rate, we can fit a curve to the data points using simulations to predict the flow rate of the measured signal.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-05-01","The student, Natalie Aw, accepted the attached license on 2019-04-11 at 12:55.","The student, Natalie Aw, submitted this Thesis for approval on 2019-04-12 at 12:21.","This Thesis was approved for publication on 2019-04-12 at 13:59.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13565 on 2019-08-22 at 15:05:53","Made available in DSpace on 2019-08-23T20:35:50Z (GMT). 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To relieve this pressure, a shunt is placed in the brain that drains the CSF. However, the failure rate of these shunts is high, requiring additional surgeries to check functionality or for replacement. As this is costly and invasive, a way to quantitatively measure the shunt flow without surgery would be valuable. In this work, we modify a previously successful technique that quantified blood flow in the brain to quantify CSF flow. This technique, called flow enhanced signal intensity (FENSI), uses magnetic resonance (MR) to gain a quick and accurate measurement. By adjusting imaging parameters from quantitative FENSI (qFENSI), we can optimize this sequence to be sensitive to CSF flow. We demonstrate the sensitivity of our technique down to 0.1 ml/min and up to 0.4 ml/min. Additionally, taking into account the T1 relaxation rate, we can fit a curve to the data points using simulations to predict the flow rate of the measured signal.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-05-01","The student, Natalie Aw, accepted the attached license on 2019-04-11 at 12:55.","The student, Natalie Aw, submitted this Thesis for approval on 2019-04-12 at 12:21.","This Thesis was approved for publication on 2019-04-12 at 13:59.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13565 on 2019-08-22 at 15:05:53","Made available in DSpace on 2019-08-23T20:35:50Z (GMT). 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