Longitudinal changes in diffusion tensor imaging in hemodialysis patients
Introduction Hemodialysis patients have increased white matter and gray matter pathology in the brain relative to controls based on MRI. Diffusion tensor imaging is useful in detecting differences between hemodialysis and controls but has not identified the expected longitudinal decline in hemodialy...
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Veröffentlicht in: | Hemodialysis international 2024-04, Vol.28 (2), p.178-187 |
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description | Introduction
Hemodialysis patients have increased white matter and gray matter pathology in the brain relative to controls based on MRI. Diffusion tensor imaging is useful in detecting differences between hemodialysis and controls but has not identified the expected longitudinal decline in hemodialysis patients. In this study we implemented specialized post‐processing techniques to reduce noise to detect longitudinal changes in diffusion tensor imaging parameters and evaluated for any association with changes in cognition.
Methods
We collected anatomical and diffusion MRIs as well as cognitive testing from in‐center hemodialysis patients at baseline and 1 year later. Gray matter thickness, white matter volume, and white matter diffusion tensor imaging parameters were measured to identify longitudinal changes. We analyzed the diffusion tensor imaging parameters by averaging the whole white matter and using a pothole analysis. Eighteen hemodialysis patients were included in the longitudinal analysis and 15 controls were used for the pothole analysis. We used the NIH Toolbox Cognition Battery to assess cognitive performance over the same time frame.
Findings
Over the course of a year on hemodialysis, we found a decrease in white matter fractional anisotropy across the entire white matter (p |
doi_str_mv | 10.1111/hdi.13133 |
format | Article |
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Hemodialysis patients have increased white matter and gray matter pathology in the brain relative to controls based on MRI. Diffusion tensor imaging is useful in detecting differences between hemodialysis and controls but has not identified the expected longitudinal decline in hemodialysis patients. In this study we implemented specialized post‐processing techniques to reduce noise to detect longitudinal changes in diffusion tensor imaging parameters and evaluated for any association with changes in cognition.
Methods
We collected anatomical and diffusion MRIs as well as cognitive testing from in‐center hemodialysis patients at baseline and 1 year later. Gray matter thickness, white matter volume, and white matter diffusion tensor imaging parameters were measured to identify longitudinal changes. We analyzed the diffusion tensor imaging parameters by averaging the whole white matter and using a pothole analysis. Eighteen hemodialysis patients were included in the longitudinal analysis and 15 controls were used for the pothole analysis. We used the NIH Toolbox Cognition Battery to assess cognitive performance over the same time frame.
Findings
Over the course of a year on hemodialysis, we found a decrease in white matter fractional anisotropy across the entire white matter (p < 0.01), and an increase in the number of white matter fractional anisotropy voxels below pothole threshold (p = 0.03). We did not find any relationship between changes in whole brain structural parameters and cognitive performance.
Discussion
By employing noise reducing techniques, we were able to detect longitudinal changes in diffusion tensor imaging parameters in hemodialysis patients. The fractional anisotropy declines over the year indicate significant decreases in white matter health. However, we did not find that declines in fractional anisotropy was associated with declines in cognitive performance.</description><identifier>ISSN: 1492-7535</identifier><identifier>ISSN: 1542-4758</identifier><identifier>EISSN: 1542-4758</identifier><identifier>DOI: 10.1111/hdi.13133</identifier><identifier>PMID: 38351365</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Brain - pathology ; diffusion tensor imaging ; Diffusion Tensor Imaging - methods ; hemodialysis ; Humans ; kidney disease ; Magnetic Resonance Imaging ; Renal Dialysis ; White Matter - diagnostic imaging ; White Matter - pathology ; white matter integrity</subject><ispartof>Hemodialysis international, 2024-04, Vol.28 (2), p.178-187</ispartof><rights>2024 International Society for Hemodialysis.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2853-8a1eca5ae88bedbb20db8ac269bca1937ba472b4c2b704063764e5e9911b97fb3</cites><orcidid>0000-0001-8194-9434</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fhdi.13133$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fhdi.13133$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38351365$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Richerson, Wesley T.</creatorcontrib><creatorcontrib>Schmit, Brian D.</creatorcontrib><creatorcontrib>Wolfgram, Dawn F.</creatorcontrib><title>Longitudinal changes in diffusion tensor imaging in hemodialysis patients</title><title>Hemodialysis international</title><addtitle>Hemodial Int</addtitle><description>Introduction
Hemodialysis patients have increased white matter and gray matter pathology in the brain relative to controls based on MRI. Diffusion tensor imaging is useful in detecting differences between hemodialysis and controls but has not identified the expected longitudinal decline in hemodialysis patients. In this study we implemented specialized post‐processing techniques to reduce noise to detect longitudinal changes in diffusion tensor imaging parameters and evaluated for any association with changes in cognition.
Methods
We collected anatomical and diffusion MRIs as well as cognitive testing from in‐center hemodialysis patients at baseline and 1 year later. Gray matter thickness, white matter volume, and white matter diffusion tensor imaging parameters were measured to identify longitudinal changes. We analyzed the diffusion tensor imaging parameters by averaging the whole white matter and using a pothole analysis. Eighteen hemodialysis patients were included in the longitudinal analysis and 15 controls were used for the pothole analysis. We used the NIH Toolbox Cognition Battery to assess cognitive performance over the same time frame.
Findings
Over the course of a year on hemodialysis, we found a decrease in white matter fractional anisotropy across the entire white matter (p < 0.01), and an increase in the number of white matter fractional anisotropy voxels below pothole threshold (p = 0.03). We did not find any relationship between changes in whole brain structural parameters and cognitive performance.
Discussion
By employing noise reducing techniques, we were able to detect longitudinal changes in diffusion tensor imaging parameters in hemodialysis patients. The fractional anisotropy declines over the year indicate significant decreases in white matter health. However, we did not find that declines in fractional anisotropy was associated with declines in cognitive performance.</description><subject>Brain - pathology</subject><subject>diffusion tensor imaging</subject><subject>Diffusion Tensor Imaging - methods</subject><subject>hemodialysis</subject><subject>Humans</subject><subject>kidney disease</subject><subject>Magnetic Resonance Imaging</subject><subject>Renal Dialysis</subject><subject>White Matter - diagnostic imaging</subject><subject>White Matter - pathology</subject><subject>white matter integrity</subject><issn>1492-7535</issn><issn>1542-4758</issn><issn>1542-4758</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kD1PwzAQQC0EoqUw8AdQRhjS-jOJR9QCrVSJBWbLdi6pUeKUOBHqvyclhQ0vZ-mennQPoVuC52R4i13u5oQRxs7QlAhOY56K7Hz4c0njVDAxQVchfGBMCcbJJZqwjAnCEjFFm23jS9f1ufO6iuxO-xJC5HyUu6Log2t81IEPTRu5WpfOl8fdDuomd7o6BBeive4c-C5co4tCVwFuTnOG3p-f3pbrePv6slk-bmNLM8HiTBOwWmjIMgO5MRTnJtOWJtJYTSRLjeYpNdxSk2KOE5YmHARISYiRaWHYDN2P3n3bfPYQOlW7YKGqtIemD4pKmggiBRcD-jCitm1CaKFQ-3Y4oz0ogtWxnBrKqZ9yA3t30vamhvyP_E01AIsR-HIVHP43qfVqMyq_AdpkeHQ</recordid><startdate>202404</startdate><enddate>202404</enddate><creator>Richerson, Wesley T.</creator><creator>Schmit, Brian D.</creator><creator>Wolfgram, Dawn F.</creator><general>John Wiley & Sons, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-8194-9434</orcidid></search><sort><creationdate>202404</creationdate><title>Longitudinal changes in diffusion tensor imaging in hemodialysis patients</title><author>Richerson, Wesley T. ; Schmit, Brian D. ; Wolfgram, Dawn F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2853-8a1eca5ae88bedbb20db8ac269bca1937ba472b4c2b704063764e5e9911b97fb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Brain - pathology</topic><topic>diffusion tensor imaging</topic><topic>Diffusion Tensor Imaging - methods</topic><topic>hemodialysis</topic><topic>Humans</topic><topic>kidney disease</topic><topic>Magnetic Resonance Imaging</topic><topic>Renal Dialysis</topic><topic>White Matter - diagnostic imaging</topic><topic>White Matter - pathology</topic><topic>white matter integrity</topic><toplevel>online_resources</toplevel><creatorcontrib>Richerson, Wesley T.</creatorcontrib><creatorcontrib>Schmit, Brian D.</creatorcontrib><creatorcontrib>Wolfgram, Dawn F.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Hemodialysis international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Richerson, Wesley T.</au><au>Schmit, Brian D.</au><au>Wolfgram, Dawn F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Longitudinal changes in diffusion tensor imaging in hemodialysis patients</atitle><jtitle>Hemodialysis international</jtitle><addtitle>Hemodial Int</addtitle><date>2024-04</date><risdate>2024</risdate><volume>28</volume><issue>2</issue><spage>178</spage><epage>187</epage><pages>178-187</pages><issn>1492-7535</issn><issn>1542-4758</issn><eissn>1542-4758</eissn><abstract>Introduction
Hemodialysis patients have increased white matter and gray matter pathology in the brain relative to controls based on MRI. Diffusion tensor imaging is useful in detecting differences between hemodialysis and controls but has not identified the expected longitudinal decline in hemodialysis patients. In this study we implemented specialized post‐processing techniques to reduce noise to detect longitudinal changes in diffusion tensor imaging parameters and evaluated for any association with changes in cognition.
Methods
We collected anatomical and diffusion MRIs as well as cognitive testing from in‐center hemodialysis patients at baseline and 1 year later. Gray matter thickness, white matter volume, and white matter diffusion tensor imaging parameters were measured to identify longitudinal changes. We analyzed the diffusion tensor imaging parameters by averaging the whole white matter and using a pothole analysis. Eighteen hemodialysis patients were included in the longitudinal analysis and 15 controls were used for the pothole analysis. We used the NIH Toolbox Cognition Battery to assess cognitive performance over the same time frame.
Findings
Over the course of a year on hemodialysis, we found a decrease in white matter fractional anisotropy across the entire white matter (p < 0.01), and an increase in the number of white matter fractional anisotropy voxels below pothole threshold (p = 0.03). We did not find any relationship between changes in whole brain structural parameters and cognitive performance.
Discussion
By employing noise reducing techniques, we were able to detect longitudinal changes in diffusion tensor imaging parameters in hemodialysis patients. The fractional anisotropy declines over the year indicate significant decreases in white matter health. However, we did not find that declines in fractional anisotropy was associated with declines in cognitive performance.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>38351365</pmid><doi>10.1111/hdi.13133</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-8194-9434</orcidid></addata></record> |
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subjects | Brain - pathology diffusion tensor imaging Diffusion Tensor Imaging - methods hemodialysis Humans kidney disease Magnetic Resonance Imaging Renal Dialysis White Matter - diagnostic imaging White Matter - pathology white matter integrity |
title | Longitudinal changes in diffusion tensor imaging in hemodialysis patients |
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