Direct observation of NMR transverse relaxation in nanopatterned clusters of iron oxide particles
We aim to verify predictions showing T relaxation rate of nanoparticle clusters and its dependence on spacing, size, geometry, and pulse sequence. We performed a laboratory validation study using nanopatterned arrays of iron oxide nanoparticles to precisely control cluster geometry and image diverse...
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creator | Bok, Ilhan Rauch, Beth Ashtiani, Alireza Hai, Aviad |
description | We aim to verify predictions showing T
relaxation rate of nanoparticle clusters and its dependence on spacing, size, geometry, and pulse sequence.
We performed a laboratory validation study using nanopatterned arrays of iron oxide nanoparticles to precisely control cluster geometry and image diverse samples using a 4.7T MRI scanner with a T
-weighted fast spin-echo multislice sequence. We applied denoising and normalization to regions of interest and estimated relative R
for each relevant nanoparticle array or nanocluster array. We determined significance using an unpaired two-tailed t-test or one-way analysis of variance and performed curve fitting.
We measured a density-dependent T
effect (p = 8.9976 × 10
, one-way analysis of variance) and insignificant effect of cluster anisotropy (p = 0.5924, unpaired t-test) on T
relaxation. We found negative quadratic relationships (-0.0045[log τ
]
-0.0655[log τ
]-2.7800) for single nanoparticles of varying sizes and for clusters (-0.0045[log τ
]
-0.0827[log τ
]-2.3249) for diffusional correlation time τ
= r
/D. Clusters show positive quadratic relationships for large (3.8615 × 10
[d
/r
]
-9.3853 × 10
[d
/r
]-2.0393) and exponential relationships for small (-2.0050[d
/r
]
) clusters. Calculated R
peak values also align well with in silico predictions (7.85 × 10
ms compared with 1.47 × 10
, 4.23 × 10
, and 5.02 × 10
ms for single iron oxide nanoparticles, 7.88 × 10
ms compared with 5.24 × 10
ms for nanoparticle clusters).
Our verification affirms longstanding in silico predictions and demonstrates aggregation-dependent behavior in agreement with previous Monte Carlo simulation studies. |
doi_str_mv | 10.1002/mrm.29898 |
format | Article |
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relaxation rate of nanoparticle clusters and its dependence on spacing, size, geometry, and pulse sequence.
We performed a laboratory validation study using nanopatterned arrays of iron oxide nanoparticles to precisely control cluster geometry and image diverse samples using a 4.7T MRI scanner with a T
-weighted fast spin-echo multislice sequence. We applied denoising and normalization to regions of interest and estimated relative R
for each relevant nanoparticle array or nanocluster array. We determined significance using an unpaired two-tailed t-test or one-way analysis of variance and performed curve fitting.
We measured a density-dependent T
effect (p = 8.9976 × 10
, one-way analysis of variance) and insignificant effect of cluster anisotropy (p = 0.5924, unpaired t-test) on T
relaxation. We found negative quadratic relationships (-0.0045[log τ
]
-0.0655[log τ
]-2.7800) for single nanoparticles of varying sizes and for clusters (-0.0045[log τ
]
-0.0827[log τ
]-2.3249) for diffusional correlation time τ
= r
/D. Clusters show positive quadratic relationships for large (3.8615 × 10
[d
/r
]
-9.3853 × 10
[d
/r
]-2.0393) and exponential relationships for small (-2.0050[d
/r
]
) clusters. Calculated R
peak values also align well with in silico predictions (7.85 × 10
ms compared with 1.47 × 10
, 4.23 × 10
, and 5.02 × 10
ms for single iron oxide nanoparticles, 7.88 × 10
ms compared with 5.24 × 10
ms for nanoparticle clusters).
Our verification affirms longstanding in silico predictions and demonstrates aggregation-dependent behavior in agreement with previous Monte Carlo simulation studies.</description><identifier>ISSN: 0740-3194</identifier><identifier>ISSN: 1522-2594</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.29898</identifier><identifier>PMID: 37867452</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Aggregation behavior ; Anisotropy ; Arrays ; Clusters ; Computer Simulation ; Curve fitting ; Iron oxides ; Magnetic Resonance Imaging - methods ; Magnetic Resonance Spectroscopy ; Monte Carlo Method ; Monte Carlo simulation ; Nanoclusters ; Nanoparticles ; NMR ; Nuclear magnetic resonance ; Predictions ; Variance analysis</subject><ispartof>Magnetic resonance in medicine, 2024-02, Vol.91 (2), p.687-698</ispartof><rights>2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c308t-9594c08960197490543d682a28cf15b5c514542651fcc4b404afaa77ca32f4023</cites><orcidid>0000-0002-4481-7843 ; 0000-0002-4556-3048</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37867452$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bok, Ilhan</creatorcontrib><creatorcontrib>Rauch, Beth</creatorcontrib><creatorcontrib>Ashtiani, Alireza</creatorcontrib><creatorcontrib>Hai, Aviad</creatorcontrib><title>Direct observation of NMR transverse relaxation in nanopatterned clusters of iron oxide particles</title><title>Magnetic resonance in medicine</title><addtitle>Magn Reson Med</addtitle><description>We aim to verify predictions showing T
relaxation rate of nanoparticle clusters and its dependence on spacing, size, geometry, and pulse sequence.
We performed a laboratory validation study using nanopatterned arrays of iron oxide nanoparticles to precisely control cluster geometry and image diverse samples using a 4.7T MRI scanner with a T
-weighted fast spin-echo multislice sequence. We applied denoising and normalization to regions of interest and estimated relative R
for each relevant nanoparticle array or nanocluster array. We determined significance using an unpaired two-tailed t-test or one-way analysis of variance and performed curve fitting.
We measured a density-dependent T
effect (p = 8.9976 × 10
, one-way analysis of variance) and insignificant effect of cluster anisotropy (p = 0.5924, unpaired t-test) on T
relaxation. We found negative quadratic relationships (-0.0045[log τ
]
-0.0655[log τ
]-2.7800) for single nanoparticles of varying sizes and for clusters (-0.0045[log τ
]
-0.0827[log τ
]-2.3249) for diffusional correlation time τ
= r
/D. Clusters show positive quadratic relationships for large (3.8615 × 10
[d
/r
]
-9.3853 × 10
[d
/r
]-2.0393) and exponential relationships for small (-2.0050[d
/r
]
) clusters. Calculated R
peak values also align well with in silico predictions (7.85 × 10
ms compared with 1.47 × 10
, 4.23 × 10
, and 5.02 × 10
ms for single iron oxide nanoparticles, 7.88 × 10
ms compared with 5.24 × 10
ms for nanoparticle clusters).
Our verification affirms longstanding in silico predictions and demonstrates aggregation-dependent behavior in agreement with previous Monte Carlo simulation studies.</description><subject>Aggregation behavior</subject><subject>Anisotropy</subject><subject>Arrays</subject><subject>Clusters</subject><subject>Computer Simulation</subject><subject>Curve fitting</subject><subject>Iron oxides</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Magnetic Resonance Spectroscopy</subject><subject>Monte Carlo Method</subject><subject>Monte Carlo simulation</subject><subject>Nanoclusters</subject><subject>Nanoparticles</subject><subject>NMR</subject><subject>Nuclear magnetic resonance</subject><subject>Predictions</subject><subject>Variance analysis</subject><issn>0740-3194</issn><issn>1522-2594</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkM1KxDAURoMozji68AUk4EYX1SRN2mQp4y-MCqLrkqYpZGiTmqTD-PZmnNGFq3vhnu_ycQA4xegKI0Sue99fEcEF3wNTzAjJCBN0H0xRSVGWY0En4CiEJUJIiJIegkle8qKkjEyBvDVeqwhdHbRfyWicha6FL89vMHppw0r7oKHXnVxvj8ZCK60bZIzaW91A1Y0hrWETM34TX5tGw0H6aFSnwzE4aGUX9MluzsDH_d37_DFbvD48zW8WmcoRj5lIlRXiokA4dRSI0bwpOJGEqxazmimGKaOkYLhVitYUUdlKWZZK5qSliOQzcLH9O3j3OeoQq94EpbtOWu3GUBHOESckOUjo-T906UZvU7tECSp4WQiaqMstpbwLweu2Grzppf-qMKo23qvkvfrxntiz3cex7nXzR_6Kzr8BsMt9Zg</recordid><startdate>20240201</startdate><enddate>20240201</enddate><creator>Bok, Ilhan</creator><creator>Rauch, Beth</creator><creator>Ashtiani, Alireza</creator><creator>Hai, Aviad</creator><general>Wiley Subscription Services, 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>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4481-7843</orcidid><orcidid>https://orcid.org/0000-0002-4556-3048</orcidid></search><sort><creationdate>20240201</creationdate><title>Direct observation of NMR transverse relaxation in nanopatterned clusters of iron oxide particles</title><author>Bok, Ilhan ; Rauch, Beth ; Ashtiani, Alireza ; Hai, Aviad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c308t-9594c08960197490543d682a28cf15b5c514542651fcc4b404afaa77ca32f4023</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aggregation behavior</topic><topic>Anisotropy</topic><topic>Arrays</topic><topic>Clusters</topic><topic>Computer Simulation</topic><topic>Curve fitting</topic><topic>Iron oxides</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Magnetic Resonance Spectroscopy</topic><topic>Monte Carlo Method</topic><topic>Monte Carlo simulation</topic><topic>Nanoclusters</topic><topic>Nanoparticles</topic><topic>NMR</topic><topic>Nuclear magnetic resonance</topic><topic>Predictions</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bok, Ilhan</creatorcontrib><creatorcontrib>Rauch, Beth</creatorcontrib><creatorcontrib>Ashtiani, Alireza</creatorcontrib><creatorcontrib>Hai, Aviad</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Magnetic resonance in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bok, Ilhan</au><au>Rauch, Beth</au><au>Ashtiani, Alireza</au><au>Hai, Aviad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Direct observation of NMR transverse relaxation in nanopatterned clusters of iron oxide particles</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn Reson Med</addtitle><date>2024-02-01</date><risdate>2024</risdate><volume>91</volume><issue>2</issue><spage>687</spage><epage>698</epage><pages>687-698</pages><issn>0740-3194</issn><issn>1522-2594</issn><eissn>1522-2594</eissn><abstract>We aim to verify predictions showing T
relaxation rate of nanoparticle clusters and its dependence on spacing, size, geometry, and pulse sequence.
We performed a laboratory validation study using nanopatterned arrays of iron oxide nanoparticles to precisely control cluster geometry and image diverse samples using a 4.7T MRI scanner with a T
-weighted fast spin-echo multislice sequence. We applied denoising and normalization to regions of interest and estimated relative R
for each relevant nanoparticle array or nanocluster array. We determined significance using an unpaired two-tailed t-test or one-way analysis of variance and performed curve fitting.
We measured a density-dependent T
effect (p = 8.9976 × 10
, one-way analysis of variance) and insignificant effect of cluster anisotropy (p = 0.5924, unpaired t-test) on T
relaxation. We found negative quadratic relationships (-0.0045[log τ
]
-0.0655[log τ
]-2.7800) for single nanoparticles of varying sizes and for clusters (-0.0045[log τ
]
-0.0827[log τ
]-2.3249) for diffusional correlation time τ
= r
/D. Clusters show positive quadratic relationships for large (3.8615 × 10
[d
/r
]
-9.3853 × 10
[d
/r
]-2.0393) and exponential relationships for small (-2.0050[d
/r
]
) clusters. Calculated R
peak values also align well with in silico predictions (7.85 × 10
ms compared with 1.47 × 10
, 4.23 × 10
, and 5.02 × 10
ms for single iron oxide nanoparticles, 7.88 × 10
ms compared with 5.24 × 10
ms for nanoparticle clusters).
Our verification affirms longstanding in silico predictions and demonstrates aggregation-dependent behavior in agreement with previous Monte Carlo simulation studies.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>37867452</pmid><doi>10.1002/mrm.29898</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-4481-7843</orcidid><orcidid>https://orcid.org/0000-0002-4556-3048</orcidid><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; Wiley Online Library All Journals |
subjects | Aggregation behavior Anisotropy Arrays Clusters Computer Simulation Curve fitting Iron oxides Magnetic Resonance Imaging - methods Magnetic Resonance Spectroscopy Monte Carlo Method Monte Carlo simulation Nanoclusters Nanoparticles NMR Nuclear magnetic resonance Predictions Variance analysis |
title | Direct observation of NMR transverse relaxation in nanopatterned clusters of iron oxide particles |
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