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Real-time motion analytics during brain MRI improve data quality and reduce costs
Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring c...
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Published in: | NeuroImage (Orlando, Fla.) Fla.), 2017-11, Vol.161, p.80-93 |
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creator | Dosenbach, Nico U.F. Koller, Jonathan M. Earl, Eric A. Miranda-Dominguez, Oscar Klein, Rachel L. Van, Andrew N. Snyder, Abraham Z. Nagel, Bonnie J. Nigg, Joel T. Nguyen, Annie L. Wesevich, Victoria Greene, Deanna J. Fair, Damien A. |
description | Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional ‘buffer data’, an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more.
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doi_str_mv | 10.1016/j.neuroimage.2017.08.025 |
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[Display omitted]</description><identifier>ISSN: 1053-8119</identifier><identifier>EISSN: 1095-9572</identifier><identifier>DOI: 10.1016/j.neuroimage.2017.08.025</identifier><identifier>PMID: 28803940</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Accuracy ; Adolescent ; Adult ; Alcoholism - diagnostic imaging ; Attention Deficit Disorder with Hyperactivity - diagnostic imaging ; Autism Spectrum Disorder - diagnostic imaging ; Brain ; Brain - diagnostic imaging ; Child ; Cost control ; Functional magnetic resonance imaging ; Functional MRI ; Functional Neuroimaging - methods ; Functional Neuroimaging - standards ; Head motion distortion ; Head movement ; Head Movements - physiology ; Humans ; Image Processing, Computer-Assisted - methods ; Image Processing, Computer-Assisted - standards ; Magnetic Resonance Imaging - methods ; Magnetic Resonance Imaging - standards ; MRI acquisition ; MRI methods ; Neural networks ; NMR ; Nuclear magnetic resonance ; Quality ; Real-time quality control ; Resting state functional connectivity MRI ; Scanners ; Structural MRI ; Structure-function relationships ; Young Adult</subject><ispartof>NeuroImage (Orlando, Fla.), 2017-11, Vol.161, p.80-93</ispartof><rights>2017 The Authors</rights><rights>Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited Nov 1, 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c507t-13c4e845b6dad91048beb7321eb6d0436470d9b04c8531705929dbc8ac89ed7d3</citedby><cites>FETCH-LOGICAL-c507t-13c4e845b6dad91048beb7321eb6d0436470d9b04c8531705929dbc8ac89ed7d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28803940$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dosenbach, Nico U.F.</creatorcontrib><creatorcontrib>Koller, Jonathan M.</creatorcontrib><creatorcontrib>Earl, Eric A.</creatorcontrib><creatorcontrib>Miranda-Dominguez, Oscar</creatorcontrib><creatorcontrib>Klein, Rachel L.</creatorcontrib><creatorcontrib>Van, Andrew N.</creatorcontrib><creatorcontrib>Snyder, Abraham Z.</creatorcontrib><creatorcontrib>Nagel, Bonnie J.</creatorcontrib><creatorcontrib>Nigg, Joel T.</creatorcontrib><creatorcontrib>Nguyen, Annie L.</creatorcontrib><creatorcontrib>Wesevich, Victoria</creatorcontrib><creatorcontrib>Greene, Deanna J.</creatorcontrib><creatorcontrib>Fair, Damien A.</creatorcontrib><title>Real-time motion analytics during brain MRI improve data quality and reduce costs</title><title>NeuroImage (Orlando, Fla.)</title><addtitle>Neuroimage</addtitle><description>Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional ‘buffer data’, an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more.
[Display omitted]</description><subject>Accuracy</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Alcoholism - diagnostic imaging</subject><subject>Attention Deficit Disorder with Hyperactivity - diagnostic imaging</subject><subject>Autism Spectrum Disorder - diagnostic imaging</subject><subject>Brain</subject><subject>Brain - diagnostic imaging</subject><subject>Child</subject><subject>Cost control</subject><subject>Functional magnetic resonance imaging</subject><subject>Functional MRI</subject><subject>Functional Neuroimaging - methods</subject><subject>Functional Neuroimaging - standards</subject><subject>Head motion distortion</subject><subject>Head movement</subject><subject>Head Movements - physiology</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Image Processing, Computer-Assisted - standards</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Magnetic Resonance Imaging - standards</subject><subject>MRI acquisition</subject><subject>MRI methods</subject><subject>Neural networks</subject><subject>NMR</subject><subject>Nuclear magnetic resonance</subject><subject>Quality</subject><subject>Real-time quality control</subject><subject>Resting state functional connectivity MRI</subject><subject>Scanners</subject><subject>Structural MRI</subject><subject>Structure-function relationships</subject><subject>Young 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motion analytics during brain MRI improve data quality and reduce costs</title><author>Dosenbach, Nico U.F. ; Koller, Jonathan M. ; Earl, Eric A. ; Miranda-Dominguez, Oscar ; Klein, Rachel L. ; Van, Andrew N. ; Snyder, Abraham Z. ; Nagel, Bonnie J. ; Nigg, Joel T. ; Nguyen, Annie L. ; Wesevich, Victoria ; Greene, Deanna J. ; Fair, Damien A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c507t-13c4e845b6dad91048beb7321eb6d0436470d9b04c8531705929dbc8ac89ed7d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accuracy</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Alcoholism - diagnostic imaging</topic><topic>Attention Deficit Disorder with Hyperactivity - diagnostic imaging</topic><topic>Autism Spectrum Disorder - diagnostic imaging</topic><topic>Brain</topic><topic>Brain - diagnostic imaging</topic><topic>Child</topic><topic>Cost 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A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Real-time motion analytics during brain MRI improve data quality and reduce costs</atitle><jtitle>NeuroImage (Orlando, Fla.)</jtitle><addtitle>Neuroimage</addtitle><date>2017-11-01</date><risdate>2017</risdate><volume>161</volume><spage>80</spage><epage>93</epage><pages>80-93</pages><issn>1053-8119</issn><eissn>1095-9572</eissn><abstract>Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional ‘buffer data’, an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more.
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subjects | Accuracy Adolescent Adult Alcoholism - diagnostic imaging Attention Deficit Disorder with Hyperactivity - diagnostic imaging Autism Spectrum Disorder - diagnostic imaging Brain Brain - diagnostic imaging Child Cost control Functional magnetic resonance imaging Functional MRI Functional Neuroimaging - methods Functional Neuroimaging - standards Head motion distortion Head movement Head Movements - physiology Humans Image Processing, Computer-Assisted - methods Image Processing, Computer-Assisted - standards Magnetic Resonance Imaging - methods Magnetic Resonance Imaging - standards MRI acquisition MRI methods Neural networks NMR Nuclear magnetic resonance Quality Real-time quality control Resting state functional connectivity MRI Scanners Structural MRI Structure-function relationships Young Adult |
title | Real-time motion analytics during brain MRI improve data quality and reduce costs |
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