Motion Detection and Correction for Frame-Based Stereotactic Localization
Frame-based stereotactic localization is an important step for targeting during a surgical procedure. The motion may cause artifacts in this step reducing the accuracy of surgical targeting. While modeling of motion in real-life scenarios may be difficult, herein we analyzed the case where motion wa...
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creator | Sedrak, Mark Pezeshkian, Patrick Purger, David Srivastava, Siddharth Anderson, Ross Yecies, Derek W Call, Elena Khandhar, Suketu Balster, Keegan Bernstein, Ivan Bruce, Diana M Alaminos-Bouza, Armando L |
description | Frame-based stereotactic localization is an important step for targeting during a surgical procedure. The motion may cause artifacts in this step reducing the accuracy of surgical targeting. While modeling of motion in real-life scenarios may be difficult, herein we analyzed the case where motion was suspected to impact the localization step. In this case, a scan with and without motion was performed with a 3N localizer, allowing for a thorough analysis. Pseudo-bending of straight rods was seen when analyzing the data. This pseudo-bending appears to occur because head-frame motion during imaging acquisition decreases the accuracy of the subsequent reconstruction, which depends on Digital Imaging and Communications in Medicine (DICOM) metadata to specify the slice-to-slice location that assumes embedded object stability. Comparison of single-slice and multi-slice stereotactic localization allowed for comparative errors for each slice in a volume. This comparative error demonstrated low error when the patient was under general anesthesia and presumed not to have moved, whereas a higher error was present during the scan with motion. Pseudo-bending can be corrected by using only localizer fiducial-based information to reorient the pixels in the volume, thus creating a reoriented localizer scan. Finally, targeting demonstrated a low error of 0.1 mm (+/- 0.1 mm) using this reoriented localizer scan, signifying that this method could be used to improve or recover from motion problems. Finally, it is concluded that stability and elimination of motion for all images utilized for stereotactic surgery are critical to ensure the best possible accuracy for the procedure. |
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The motion may cause artifacts in this step reducing the accuracy of surgical targeting. While modeling of motion in real-life scenarios may be difficult, herein we analyzed the case where motion was suspected to impact the localization step. In this case, a scan with and without motion was performed with a 3N localizer, allowing for a thorough analysis. Pseudo-bending of straight rods was seen when analyzing the data. This pseudo-bending appears to occur because head-frame motion during imaging acquisition decreases the accuracy of the subsequent reconstruction, which depends on Digital Imaging and Communications in Medicine (DICOM) metadata to specify the slice-to-slice location that assumes embedded object stability. Comparison of single-slice and multi-slice stereotactic localization allowed for comparative errors for each slice in a volume. This comparative error demonstrated low error when the patient was under general anesthesia and presumed not to have moved, whereas a higher error was present during the scan with motion. Pseudo-bending can be corrected by using only localizer fiducial-based information to reorient the pixels in the volume, thus creating a reoriented localizer scan. Finally, targeting demonstrated a low error of 0.1 mm (+/- 0.1 mm) using this reoriented localizer scan, signifying that this method could be used to improve or recover from motion problems. Finally, it is concluded that stability and elimination of motion for all images utilized for stereotactic surgery are critical to ensure the best possible accuracy for the procedure.</description><identifier>ISSN: 2168-8184</identifier><identifier>EISSN: 2168-8184</identifier><identifier>DOI: 10.7759/cureus.28387</identifier><language>eng</language><publisher>Palo Alto: Cureus Inc</publisher><subject>Accuracy ; Case reports ; Digital imaging ; Localization ; Magnetic resonance imaging ; Medical imaging ; Medical Physics ; Medical Simulation ; Metadata ; Neurosurgery ; Software ; Tomography</subject><ispartof>Curēus (Palo Alto, CA), 2022-08, Vol.14 (8)</ispartof><rights>Copyright © 2022, Sedrak et al. This work is published under https://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Copyright © 2022, Sedrak et al. 2022 Sedrak et al.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c243t-d506407adc58e69f3bdd90de54ddf42e8e71b7767d8b018c2db5adfccfad63243</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510889/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510889/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids></links><search><creatorcontrib>Sedrak, Mark</creatorcontrib><creatorcontrib>Pezeshkian, Patrick</creatorcontrib><creatorcontrib>Purger, David</creatorcontrib><creatorcontrib>Srivastava, Siddharth</creatorcontrib><creatorcontrib>Anderson, Ross</creatorcontrib><creatorcontrib>Yecies, Derek W</creatorcontrib><creatorcontrib>Call, Elena</creatorcontrib><creatorcontrib>Khandhar, Suketu</creatorcontrib><creatorcontrib>Balster, Keegan</creatorcontrib><creatorcontrib>Bernstein, Ivan</creatorcontrib><creatorcontrib>Bruce, Diana M</creatorcontrib><creatorcontrib>Alaminos-Bouza, Armando L</creatorcontrib><title>Motion Detection and Correction for Frame-Based Stereotactic Localization</title><title>Curēus (Palo Alto, CA)</title><description>Frame-based stereotactic localization is an important step for targeting during a surgical procedure. The motion may cause artifacts in this step reducing the accuracy of surgical targeting. While modeling of motion in real-life scenarios may be difficult, herein we analyzed the case where motion was suspected to impact the localization step. In this case, a scan with and without motion was performed with a 3N localizer, allowing for a thorough analysis. Pseudo-bending of straight rods was seen when analyzing the data. This pseudo-bending appears to occur because head-frame motion during imaging acquisition decreases the accuracy of the subsequent reconstruction, which depends on Digital Imaging and Communications in Medicine (DICOM) metadata to specify the slice-to-slice location that assumes embedded object stability. Comparison of single-slice and multi-slice stereotactic localization allowed for comparative errors for each slice in a volume. This comparative error demonstrated low error when the patient was under general anesthesia and presumed not to have moved, whereas a higher error was present during the scan with motion. Pseudo-bending can be corrected by using only localizer fiducial-based information to reorient the pixels in the volume, thus creating a reoriented localizer scan. Finally, targeting demonstrated a low error of 0.1 mm (+/- 0.1 mm) using this reoriented localizer scan, signifying that this method could be used to improve or recover from motion problems. Finally, it is concluded that stability and elimination of motion for all images utilized for stereotactic surgery are critical to ensure the best possible accuracy for the procedure.</description><subject>Accuracy</subject><subject>Case reports</subject><subject>Digital imaging</subject><subject>Localization</subject><subject>Magnetic resonance imaging</subject><subject>Medical imaging</subject><subject>Medical Physics</subject><subject>Medical Simulation</subject><subject>Metadata</subject><subject>Neurosurgery</subject><subject>Software</subject><subject>Tomography</subject><issn>2168-8184</issn><issn>2168-8184</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpVkE9LAzEQxYMoWGpvfoAFr25NsrtJ9iJobbVQ8aCeQzYzq1vaTU2ygn56t38QPc0b3uM3wyPknNGxlEV5ZTuPXRhzlSl5RAacCZUqpvLjP_qUjEJYUkoZlZxKOiDzRxcb1yZ3GNHulGkhmTjvD2vtfDLzZo3prQkIyXNEjy6a3rXJwlmzar7NNnlGTmqzCjg6zCF5nU1fJg_p4ul-PrlZpJbnWUyhoCKn0oAtFIqyziqAkgIWOUCdc1QoWSWlkKAqypTlUBUGamtrAyLrEUNyveduumqNYLGN3qz0xjdr47-0M43-77TNu35zn7osGFWq7AEXB4B3Hx2GqJeu823_s-aSlUIokbM-dblPWe9C8Fj_XmBUbwvX-8L1rvDsBwJgd0Y</recordid><startdate>20220825</startdate><enddate>20220825</enddate><creator>Sedrak, Mark</creator><creator>Pezeshkian, Patrick</creator><creator>Purger, David</creator><creator>Srivastava, Siddharth</creator><creator>Anderson, Ross</creator><creator>Yecies, Derek W</creator><creator>Call, Elena</creator><creator>Khandhar, Suketu</creator><creator>Balster, Keegan</creator><creator>Bernstein, Ivan</creator><creator>Bruce, Diana M</creator><creator>Alaminos-Bouza, Armando L</creator><general>Cureus Inc</general><general>Cureus</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope></search><sort><creationdate>20220825</creationdate><title>Motion Detection and Correction for Frame-Based Stereotactic Localization</title><author>Sedrak, Mark ; Pezeshkian, Patrick ; Purger, David ; Srivastava, Siddharth ; Anderson, Ross ; Yecies, Derek W ; Call, Elena ; Khandhar, Suketu ; Balster, Keegan ; Bernstein, Ivan ; Bruce, Diana M ; Alaminos-Bouza, Armando L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c243t-d506407adc58e69f3bdd90de54ddf42e8e71b7767d8b018c2db5adfccfad63243</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Accuracy</topic><topic>Case reports</topic><topic>Digital imaging</topic><topic>Localization</topic><topic>Magnetic resonance imaging</topic><topic>Medical imaging</topic><topic>Medical Physics</topic><topic>Medical Simulation</topic><topic>Metadata</topic><topic>Neurosurgery</topic><topic>Software</topic><topic>Tomography</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sedrak, Mark</creatorcontrib><creatorcontrib>Pezeshkian, Patrick</creatorcontrib><creatorcontrib>Purger, David</creatorcontrib><creatorcontrib>Srivastava, Siddharth</creatorcontrib><creatorcontrib>Anderson, Ross</creatorcontrib><creatorcontrib>Yecies, Derek W</creatorcontrib><creatorcontrib>Call, Elena</creatorcontrib><creatorcontrib>Khandhar, Suketu</creatorcontrib><creatorcontrib>Balster, Keegan</creatorcontrib><creatorcontrib>Bernstein, Ivan</creatorcontrib><creatorcontrib>Bruce, Diana M</creatorcontrib><creatorcontrib>Alaminos-Bouza, Armando L</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Curēus (Palo Alto, CA)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sedrak, Mark</au><au>Pezeshkian, Patrick</au><au>Purger, David</au><au>Srivastava, Siddharth</au><au>Anderson, Ross</au><au>Yecies, Derek W</au><au>Call, Elena</au><au>Khandhar, Suketu</au><au>Balster, Keegan</au><au>Bernstein, Ivan</au><au>Bruce, Diana M</au><au>Alaminos-Bouza, Armando L</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Motion Detection and Correction for Frame-Based Stereotactic Localization</atitle><jtitle>Curēus (Palo Alto, CA)</jtitle><date>2022-08-25</date><risdate>2022</risdate><volume>14</volume><issue>8</issue><issn>2168-8184</issn><eissn>2168-8184</eissn><abstract>Frame-based stereotactic localization is an important step for targeting during a surgical procedure. The motion may cause artifacts in this step reducing the accuracy of surgical targeting. While modeling of motion in real-life scenarios may be difficult, herein we analyzed the case where motion was suspected to impact the localization step. In this case, a scan with and without motion was performed with a 3N localizer, allowing for a thorough analysis. Pseudo-bending of straight rods was seen when analyzing the data. This pseudo-bending appears to occur because head-frame motion during imaging acquisition decreases the accuracy of the subsequent reconstruction, which depends on Digital Imaging and Communications in Medicine (DICOM) metadata to specify the slice-to-slice location that assumes embedded object stability. Comparison of single-slice and multi-slice stereotactic localization allowed for comparative errors for each slice in a volume. This comparative error demonstrated low error when the patient was under general anesthesia and presumed not to have moved, whereas a higher error was present during the scan with motion. Pseudo-bending can be corrected by using only localizer fiducial-based information to reorient the pixels in the volume, thus creating a reoriented localizer scan. Finally, targeting demonstrated a low error of 0.1 mm (+/- 0.1 mm) using this reoriented localizer scan, signifying that this method could be used to improve or recover from motion problems. Finally, it is concluded that stability and elimination of motion for all images utilized for stereotactic surgery are critical to ensure the best possible accuracy for the procedure.</abstract><cop>Palo Alto</cop><pub>Cureus Inc</pub><doi>10.7759/cureus.28387</doi><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Case reports Digital imaging Localization Magnetic resonance imaging Medical imaging Medical Physics Medical Simulation Metadata Neurosurgery Software Tomography |
title | Motion Detection and Correction for Frame-Based Stereotactic Localization |
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