Biomechanical modeling of neck flexion for deformable alignment of the salivary glands in head and neck cancer images

During head and neck (HN) cancer radiation therapy, analysis of the dose-response relationship for the parotid glands (PG) relies on the ability to accurately align soft tissue organs between longitudinal images. In order to isolate the response of the salivary glands to delivered dose, from deforma...

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Veröffentlicht in:Physics in medicine & biology 2019-09, Vol.64 (17), p.175018-175018
Hauptverfasser: McCulloch, Molly M, Anderson, Brian M, Cazoulat, Guillaume, Peterson, Christine B, Mohamed, Abdallah S R, Volpe, Stefania, Elhalawani, Hesham, Bahig, Houda, Rigaud, Bastien, King, Jason B, Ford, Alexandra C, Fuller, Clifton D, Brock, Kristy K
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container_issue 17
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container_title Physics in medicine & biology
container_volume 64
creator McCulloch, Molly M
Anderson, Brian M
Cazoulat, Guillaume
Peterson, Christine B
Mohamed, Abdallah S R
Volpe, Stefania
Elhalawani, Hesham
Bahig, Houda
Rigaud, Bastien
King, Jason B
Ford, Alexandra C
Fuller, Clifton D
Brock, Kristy K
description During head and neck (HN) cancer radiation therapy, analysis of the dose-response relationship for the parotid glands (PG) relies on the ability to accurately align soft tissue organs between longitudinal images. In order to isolate the response of the salivary glands to delivered dose, from deformation due to patient position, it is important to resolve the patient postural changes, mainly due to neck flexion. In this study we evaluate the use of a biomechanical model-based deformable image registration (DIR) algorithm to estimate the displacements and deformations of the salivary glands due to postural changes. A total of 82 pairs of CT images of HN cancer patients with varying angles of neck flexion were retrospectively obtained. The pairs of CTs of each patient were aligned using bone-based rigid registration. The images were then deformed using biomechanical model-based DIR method that focused on the mandible, C1 vertebrae, C3 vertebrae, and external contour. For comparison, an intensity-based DIR was also performed. The accuracy of the biomechanical model-based DIR was assessed using Dice similarity coefficient (DSC) for all images and for the subset of images where the PGs had a volume change within 20%. The accuracy was compared to the intensity-based DIR. The PG mean  ±  STD DSC were 0.63  ±  0.18, 0.80  ±  0.08, and 0.82  ±  0.15 for the rigid registration, biomechanical model-based DIR, and intensity based DIR, respectively, for patients with a PG volume change up to 20%. For the entire cohort of patients, where the PG volume change was up to 57%, the PG mean  ±  STD DSC were 0.60  ±  0.18, 0.78  ±  0.09, and 0.81  ±  0.14 for the rigid registration, biomechanical model-based DIR, and intensity based DIR, respectively. The difference in DSC of the intensity and biomechanical model-based DIR methods was not statistically significant when the volume change was less than 20% (two-sided paired t-test, p   =  0.12). When all volume changes were considered, there was a significant difference between the two registration approaches, although the magnitude was small. These results demonstrate that the proposed biomechanical model with boundary conditions on the bony anatomy can serve to describe the varying angles of neck flexion appearing in images during radiation treatment and to align the salivary glands for proper analysis of dose-response relationships. It also motivates the need for dose response modeling following neck flexion for cases where pa
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In order to isolate the response of the salivary glands to delivered dose, from deformation due to patient position, it is important to resolve the patient postural changes, mainly due to neck flexion. In this study we evaluate the use of a biomechanical model-based deformable image registration (DIR) algorithm to estimate the displacements and deformations of the salivary glands due to postural changes. A total of 82 pairs of CT images of HN cancer patients with varying angles of neck flexion were retrospectively obtained. The pairs of CTs of each patient were aligned using bone-based rigid registration. The images were then deformed using biomechanical model-based DIR method that focused on the mandible, C1 vertebrae, C3 vertebrae, and external contour. For comparison, an intensity-based DIR was also performed. The accuracy of the biomechanical model-based DIR was assessed using Dice similarity coefficient (DSC) for all images and for the subset of images where the PGs had a volume change within 20%. The accuracy was compared to the intensity-based DIR. The PG mean  ±  STD DSC were 0.63  ±  0.18, 0.80  ±  0.08, and 0.82  ±  0.15 for the rigid registration, biomechanical model-based DIR, and intensity based DIR, respectively, for patients with a PG volume change up to 20%. For the entire cohort of patients, where the PG volume change was up to 57%, the PG mean  ±  STD DSC were 0.60  ±  0.18, 0.78  ±  0.09, and 0.81  ±  0.14 for the rigid registration, biomechanical model-based DIR, and intensity based DIR, respectively. The difference in DSC of the intensity and biomechanical model-based DIR methods was not statistically significant when the volume change was less than 20% (two-sided paired t-test, p   =  0.12). When all volume changes were considered, there was a significant difference between the two registration approaches, although the magnitude was small. These results demonstrate that the proposed biomechanical model with boundary conditions on the bony anatomy can serve to describe the varying angles of neck flexion appearing in images during radiation treatment and to align the salivary glands for proper analysis of dose-response relationships. 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Med. Biol</addtitle><description>During head and neck (HN) cancer radiation therapy, analysis of the dose-response relationship for the parotid glands (PG) relies on the ability to accurately align soft tissue organs between longitudinal images. In order to isolate the response of the salivary glands to delivered dose, from deformation due to patient position, it is important to resolve the patient postural changes, mainly due to neck flexion. In this study we evaluate the use of a biomechanical model-based deformable image registration (DIR) algorithm to estimate the displacements and deformations of the salivary glands due to postural changes. A total of 82 pairs of CT images of HN cancer patients with varying angles of neck flexion were retrospectively obtained. The pairs of CTs of each patient were aligned using bone-based rigid registration. The images were then deformed using biomechanical model-based DIR method that focused on the mandible, C1 vertebrae, C3 vertebrae, and external contour. For comparison, an intensity-based DIR was also performed. The accuracy of the biomechanical model-based DIR was assessed using Dice similarity coefficient (DSC) for all images and for the subset of images where the PGs had a volume change within 20%. The accuracy was compared to the intensity-based DIR. The PG mean  ±  STD DSC were 0.63  ±  0.18, 0.80  ±  0.08, and 0.82  ±  0.15 for the rigid registration, biomechanical model-based DIR, and intensity based DIR, respectively, for patients with a PG volume change up to 20%. For the entire cohort of patients, where the PG volume change was up to 57%, the PG mean  ±  STD DSC were 0.60  ±  0.18, 0.78  ±  0.09, and 0.81  ±  0.14 for the rigid registration, biomechanical model-based DIR, and intensity based DIR, respectively. The difference in DSC of the intensity and biomechanical model-based DIR methods was not statistically significant when the volume change was less than 20% (two-sided paired t-test, p   =  0.12). When all volume changes were considered, there was a significant difference between the two registration approaches, although the magnitude was small. These results demonstrate that the proposed biomechanical model with boundary conditions on the bony anatomy can serve to describe the varying angles of neck flexion appearing in images during radiation treatment and to align the salivary glands for proper analysis of dose-response relationships. It also motivates the need for dose response modeling following neck flexion for cases where parotid gland response is noted.</description><subject>Algorithms</subject><subject>biomechanical modeling</subject><subject>deformable image registration</subject><subject>head and neck cancer</subject><subject>Head and Neck Neoplasms - diagnostic imaging</subject><subject>Head and Neck Neoplasms - radiotherapy</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>image registration</subject><subject>Neck - diagnostic imaging</subject><subject>Neck - physiopathology</subject><subject>Posture</subject><subject>Radiotherapy Planning, Computer-Assisted - methods</subject><subject>Range of Motion, Articular</subject><subject>Salivary Glands - diagnostic imaging</subject><subject>volumetric response</subject><issn>0031-9155</issn><issn>1361-6560</issn><issn>1361-6560</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kU1v1DAQhi0Eokvhzgn52AOh_nZyQYKKL6kSl94txxlnXRI72Juq_fd4lbICCSFZtmb8zOsZvwi9puQdJW17SbmijZKKXNqeecqfoN0p9RTtCOG06aiUZ-hFKbeEUNoy8RydccpUJ7TcofVjSDO4vY3B2QnPaYApxBEnjyO4H9hPcB9SxD5lPEDdZ9tPgO0UxjhDPBzBwx5wqZk7mx_wONk4FBwi3oMdcA02IWejg4zDbEcoL9Ezb6cCrx7Pc3Tz-dPN1dfm-vuXb1cfrhsnaHdoeC-ZACWcUtIPmmvSWcv0AMCorIMSpTvWgta0A8aFZ5KQjlrCOWjBgJ-j95vssvYzDK72m-1klly7yA8m2WD-volhb8Z0Z7QWbdvyKnDxKJDTzxXKwcyhOJjqjJDWYhiTjCkqGKso2VCXUykZ_OkZSszRLHN0xhydMZtZteTNn-2dCn67U4G3GxDSYm7TmmP9rP_pXfwDX-beKGGorksS2ppl8PwXcmisJg</recordid><startdate>20190905</startdate><enddate>20190905</enddate><creator>McCulloch, Molly M</creator><creator>Anderson, Brian M</creator><creator>Cazoulat, Guillaume</creator><creator>Peterson, Christine B</creator><creator>Mohamed, Abdallah S R</creator><creator>Volpe, Stefania</creator><creator>Elhalawani, Hesham</creator><creator>Bahig, Houda</creator><creator>Rigaud, Bastien</creator><creator>King, Jason B</creator><creator>Ford, Alexandra C</creator><creator>Fuller, Clifton D</creator><creator>Brock, Kristy K</creator><general>IOP Publishing</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><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-0038-429X</orcidid><orcidid>https://orcid.org/0000-0002-3866-7420</orcidid><orcidid>https://orcid.org/0000-0003-3316-0468</orcidid><orcidid>https://orcid.org/0000-0002-2748-1444</orcidid><orcidid>https://orcid.org/0000-0002-2692-7539</orcidid><orcidid>https://orcid.org/0000-0001-9848-2623</orcidid><orcidid>https://orcid.org/0000-0003-2064-7613</orcidid><orcidid>https://orcid.org/0000-0003-2042-7602</orcidid><orcidid>https://orcid.org/0000-0002-7531-1263</orcidid><orcidid>https://orcid.org/0000-0001-9508-0602</orcidid><orcidid>https://orcid.org/0000-0002-5264-3994</orcidid><orcidid>https://orcid.org/0000-0003-0498-2964</orcidid><orcidid>https://orcid.org/0000-0001-9364-5040</orcidid></search><sort><creationdate>20190905</creationdate><title>Biomechanical modeling of neck flexion for deformable alignment of the salivary glands in head and neck cancer images</title><author>McCulloch, Molly M ; Anderson, Brian M ; Cazoulat, Guillaume ; Peterson, Christine B ; Mohamed, Abdallah S R ; Volpe, Stefania ; Elhalawani, Hesham ; Bahig, Houda ; Rigaud, Bastien ; King, Jason B ; Ford, Alexandra C ; Fuller, Clifton D ; Brock, Kristy K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c419t-3b524e64c665fd73709aa27dee215136067928e7719e234f250091a033e742e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>biomechanical modeling</topic><topic>deformable image registration</topic><topic>head and neck cancer</topic><topic>Head and Neck Neoplasms - diagnostic imaging</topic><topic>Head and Neck Neoplasms - radiotherapy</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>image registration</topic><topic>Neck - diagnostic imaging</topic><topic>Neck - physiopathology</topic><topic>Posture</topic><topic>Radiotherapy Planning, Computer-Assisted - methods</topic><topic>Range of Motion, Articular</topic><topic>Salivary Glands - diagnostic imaging</topic><topic>volumetric response</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>McCulloch, Molly M</creatorcontrib><creatorcontrib>Anderson, Brian M</creatorcontrib><creatorcontrib>Cazoulat, Guillaume</creatorcontrib><creatorcontrib>Peterson, Christine B</creatorcontrib><creatorcontrib>Mohamed, Abdallah S R</creatorcontrib><creatorcontrib>Volpe, Stefania</creatorcontrib><creatorcontrib>Elhalawani, Hesham</creatorcontrib><creatorcontrib>Bahig, Houda</creatorcontrib><creatorcontrib>Rigaud, Bastien</creatorcontrib><creatorcontrib>King, Jason B</creatorcontrib><creatorcontrib>Ford, Alexandra C</creatorcontrib><creatorcontrib>Fuller, Clifton D</creatorcontrib><creatorcontrib>Brock, Kristy K</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><collection>PubMed Central (Full Participant titles)</collection><jtitle>Physics in medicine &amp; biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>McCulloch, Molly M</au><au>Anderson, Brian M</au><au>Cazoulat, Guillaume</au><au>Peterson, Christine B</au><au>Mohamed, Abdallah S R</au><au>Volpe, Stefania</au><au>Elhalawani, Hesham</au><au>Bahig, Houda</au><au>Rigaud, Bastien</au><au>King, Jason B</au><au>Ford, Alexandra C</au><au>Fuller, Clifton D</au><au>Brock, Kristy K</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Biomechanical modeling of neck flexion for deformable alignment of the salivary glands in head and neck cancer images</atitle><jtitle>Physics in medicine &amp; biology</jtitle><stitle>PMB</stitle><addtitle>Phys. Med. Biol</addtitle><date>2019-09-05</date><risdate>2019</risdate><volume>64</volume><issue>17</issue><spage>175018</spage><epage>175018</epage><pages>175018-175018</pages><issn>0031-9155</issn><issn>1361-6560</issn><eissn>1361-6560</eissn><coden>PHMBA7</coden><abstract>During head and neck (HN) cancer radiation therapy, analysis of the dose-response relationship for the parotid glands (PG) relies on the ability to accurately align soft tissue organs between longitudinal images. In order to isolate the response of the salivary glands to delivered dose, from deformation due to patient position, it is important to resolve the patient postural changes, mainly due to neck flexion. In this study we evaluate the use of a biomechanical model-based deformable image registration (DIR) algorithm to estimate the displacements and deformations of the salivary glands due to postural changes. A total of 82 pairs of CT images of HN cancer patients with varying angles of neck flexion were retrospectively obtained. The pairs of CTs of each patient were aligned using bone-based rigid registration. The images were then deformed using biomechanical model-based DIR method that focused on the mandible, C1 vertebrae, C3 vertebrae, and external contour. For comparison, an intensity-based DIR was also performed. The accuracy of the biomechanical model-based DIR was assessed using Dice similarity coefficient (DSC) for all images and for the subset of images where the PGs had a volume change within 20%. The accuracy was compared to the intensity-based DIR. The PG mean  ±  STD DSC were 0.63  ±  0.18, 0.80  ±  0.08, and 0.82  ±  0.15 for the rigid registration, biomechanical model-based DIR, and intensity based DIR, respectively, for patients with a PG volume change up to 20%. For the entire cohort of patients, where the PG volume change was up to 57%, the PG mean  ±  STD DSC were 0.60  ±  0.18, 0.78  ±  0.09, and 0.81  ±  0.14 for the rigid registration, biomechanical model-based DIR, and intensity based DIR, respectively. The difference in DSC of the intensity and biomechanical model-based DIR methods was not statistically significant when the volume change was less than 20% (two-sided paired t-test, p   =  0.12). When all volume changes were considered, there was a significant difference between the two registration approaches, although the magnitude was small. These results demonstrate that the proposed biomechanical model with boundary conditions on the bony anatomy can serve to describe the varying angles of neck flexion appearing in images during radiation treatment and to align the salivary glands for proper analysis of dose-response relationships. 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subjects Algorithms
biomechanical modeling
deformable image registration
head and neck cancer
Head and Neck Neoplasms - diagnostic imaging
Head and Neck Neoplasms - radiotherapy
Humans
Image Processing, Computer-Assisted - methods
image registration
Neck - diagnostic imaging
Neck - physiopathology
Posture
Radiotherapy Planning, Computer-Assisted - methods
Range of Motion, Articular
Salivary Glands - diagnostic imaging
volumetric response
title Biomechanical modeling of neck flexion for deformable alignment of the salivary glands in head and neck cancer images
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