Fully Automated Valve Segmentation for Blood Flow Assessment From 4D Flow MRI Including Automated Cardiac Valve Tracking and Transvalvular Velocity Mapping
Background Automated 4D flow MRI valvular flow quantification without time‐consuming manual segmentation might improve workflow. Purpose Compare automated valve segmentation (AS) to manual (MS), and manually corrected automated segmentation (AMS), in corrected atrioventricular septum defect (c‐AVSD)...
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| Veröffentlicht in: | Journal of magnetic resonance imaging 2025-01, Vol.61 (1), p.198-208 |
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| creator | Braekt, Thomas Aben, Jean‐Paul Maussen, Marc Bosch, Harrie C.M. Houthuizen, Patrick Roest, Arno A.W. Boogaard, Pieter J. Lamb, Hildo J. Westenberg, Jos J.M. |
| description | Background
Automated 4D flow MRI valvular flow quantification without time‐consuming manual segmentation might improve workflow.
Purpose
Compare automated valve segmentation (AS) to manual (MS), and manually corrected automated segmentation (AMS), in corrected atrioventricular septum defect (c‐AVSD) patients and healthy volunteers, for assessing net forward volume (NFV) and regurgitation fraction (RF).
Study Type
Retrospective.
Population
27 c‐AVSD patients (median, 23 years; interquartile range, 16–31 years) and 24 healthy volunteers (25 years; 12.5–36.5 years).
Field strength/Sequence
Whole‐heart 4D flow MRI and cine steady‐state free precession at 3T.
Assessment
After automatic valve tracking, valve annuli were segmented on time‐resolved reformatted trans‐valvular velocity images by AS, MS, and AMS. NFV was calculated for all valves, and RF for right and left atrioventricular valves (RAVV and LAVV). NFV variation (standard deviation divided by mean NFV) and NFV differences (NFV difference of a valve vs. mean NFV of other valves) expressed internal NFV consistency.
Statistical Tests
Comparisons between methods were assessed by Wilcoxon signed‐rank tests, and intra/interobserver variability by intraclass correlation coefficients (ICCs). P |
| doi_str_mv | 10.1002/jmri.29370 |
| format | Article |
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Automated 4D flow MRI valvular flow quantification without time‐consuming manual segmentation might improve workflow.
Purpose
Compare automated valve segmentation (AS) to manual (MS), and manually corrected automated segmentation (AMS), in corrected atrioventricular septum defect (c‐AVSD) patients and healthy volunteers, for assessing net forward volume (NFV) and regurgitation fraction (RF).
Study Type
Retrospective.
Population
27 c‐AVSD patients (median, 23 years; interquartile range, 16–31 years) and 24 healthy volunteers (25 years; 12.5–36.5 years).
Field strength/Sequence
Whole‐heart 4D flow MRI and cine steady‐state free precession at 3T.
Assessment
After automatic valve tracking, valve annuli were segmented on time‐resolved reformatted trans‐valvular velocity images by AS, MS, and AMS. NFV was calculated for all valves, and RF for right and left atrioventricular valves (RAVV and LAVV). NFV variation (standard deviation divided by mean NFV) and NFV differences (NFV difference of a valve vs. mean NFV of other valves) expressed internal NFV consistency.
Statistical Tests
Comparisons between methods were assessed by Wilcoxon signed‐rank tests, and intra/interobserver variability by intraclass correlation coefficients (ICCs). P < 0.05 was considered statistically significant, with multiple testing correction.
Results
AMS mean analysis time was significantly shorter compared with MS (5.3 ± 1.6 minutes vs. 9.1 ± 2.5 minutes). MS NFV variation (6.0%) was significantly smaller compared with AMS (6.3%), and AS (8.2%). Median NFV difference of RAVV, LAVV, PV, and AoV between segmentation methods ranged from −0.7–1.0 mL, −0.5–2.8 mL, −1.1–3.6 mL, and − 3.1–‐2.1 mL, respectively. Median RAVV and LAVV RF, between 7.1%–7.5% and 3.8%–4.3%, respectively, were not significantly different between methods. Intraobserver/interobserver agreement for AMS and MS was strong‐to‐excellent for NFV and RF (ICC ≥0.88).
Data Conclusion
MS demonstrates strongest internal consistency, followed closely by AMS, and AS. Automated segmentation, with or without manual correction, can be considered for 4D flow MRI valvular flow quantification.
Level of Evidence
3
Technical Efficacy
Stage 3</description><identifier>ISSN: 1053-1807</identifier><identifier>ISSN: 1522-2586</identifier><identifier>EISSN: 1522-2586</identifier><identifier>DOI: 10.1002/jmri.29370</identifier><identifier>PMID: 38558490</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>4D flow MRI ; Adolescent ; Adult ; automated valve segmentation ; Automation ; Blood flow ; Blood Flow Velocity - physiology ; Child ; Consistency ; Correlation coefficient ; Correlation coefficients ; Female ; Field strength ; Flow mapping ; Heart valves ; Heart Valves - diagnostic imaging ; Humans ; Image Interpretation, Computer-Assisted - methods ; Image processing ; Image Processing, Computer-Assisted - methods ; Image segmentation ; Imaging, Three-Dimensional - methods ; Magnetic resonance imaging ; Magnetic Resonance Imaging - methods ; Magnetic Resonance Imaging, Cine - methods ; Male ; Mean ; Median (statistics) ; net flow volume ; Population studies ; postprocessing analysis time ; Rank tests ; Regurgitation ; regurgitation fraction ; Reproducibility of Results ; Retrospective Studies ; Segmentation ; Statistical analysis ; Statistical methods ; Statistical tests ; Tracking ; Velocity ; Workflow ; Young Adult</subject><ispartof>Journal of magnetic resonance imaging, 2025-01, Vol.61 (1), p.198-208</ispartof><rights>2024 The Authors. published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.</rights><rights>2024 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.</rights><rights>2024. This article is published under http://creativecommons.org/licenses/by-nc/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-c4620-4506e03ee18ccb8e3240a7efe7177cc48ba23caad2dbe609e052b4df206309983</cites><orcidid>0000-0001-7945-3421 ; 0000-0003-1946-1715 ; 0000-0002-6969-2418</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjmri.29370$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjmri.29370$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,777,781,882,1412,27905,27906,45555,45556</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38558490$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Braekt, Thomas</creatorcontrib><creatorcontrib>Aben, Jean‐Paul</creatorcontrib><creatorcontrib>Maussen, Marc</creatorcontrib><creatorcontrib>Bosch, Harrie C.M.</creatorcontrib><creatorcontrib>Houthuizen, Patrick</creatorcontrib><creatorcontrib>Roest, Arno A.W.</creatorcontrib><creatorcontrib>Boogaard, Pieter J.</creatorcontrib><creatorcontrib>Lamb, Hildo J.</creatorcontrib><creatorcontrib>Westenberg, Jos J.M.</creatorcontrib><title>Fully Automated Valve Segmentation for Blood Flow Assessment From 4D Flow MRI Including Automated Cardiac Valve Tracking and Transvalvular Velocity Mapping</title><title>Journal of magnetic resonance imaging</title><addtitle>J Magn Reson Imaging</addtitle><description>Background
Automated 4D flow MRI valvular flow quantification without time‐consuming manual segmentation might improve workflow.
Purpose
Compare automated valve segmentation (AS) to manual (MS), and manually corrected automated segmentation (AMS), in corrected atrioventricular septum defect (c‐AVSD) patients and healthy volunteers, for assessing net forward volume (NFV) and regurgitation fraction (RF).
Study Type
Retrospective.
Population
27 c‐AVSD patients (median, 23 years; interquartile range, 16–31 years) and 24 healthy volunteers (25 years; 12.5–36.5 years).
Field strength/Sequence
Whole‐heart 4D flow MRI and cine steady‐state free precession at 3T.
Assessment
After automatic valve tracking, valve annuli were segmented on time‐resolved reformatted trans‐valvular velocity images by AS, MS, and AMS. NFV was calculated for all valves, and RF for right and left atrioventricular valves (RAVV and LAVV). NFV variation (standard deviation divided by mean NFV) and NFV differences (NFV difference of a valve vs. mean NFV of other valves) expressed internal NFV consistency.
Statistical Tests
Comparisons between methods were assessed by Wilcoxon signed‐rank tests, and intra/interobserver variability by intraclass correlation coefficients (ICCs). P < 0.05 was considered statistically significant, with multiple testing correction.
Results
AMS mean analysis time was significantly shorter compared with MS (5.3 ± 1.6 minutes vs. 9.1 ± 2.5 minutes). MS NFV variation (6.0%) was significantly smaller compared with AMS (6.3%), and AS (8.2%). Median NFV difference of RAVV, LAVV, PV, and AoV between segmentation methods ranged from −0.7–1.0 mL, −0.5–2.8 mL, −1.1–3.6 mL, and − 3.1–‐2.1 mL, respectively. Median RAVV and LAVV RF, between 7.1%–7.5% and 3.8%–4.3%, respectively, were not significantly different between methods. Intraobserver/interobserver agreement for AMS and MS was strong‐to‐excellent for NFV and RF (ICC ≥0.88).
Data Conclusion
MS demonstrates strongest internal consistency, followed closely by AMS, and AS. Automated segmentation, with or without manual correction, can be considered for 4D flow MRI valvular flow quantification.
Level of Evidence
3
Technical Efficacy
Stage 3</description><subject>4D flow MRI</subject><subject>Adolescent</subject><subject>Adult</subject><subject>automated valve segmentation</subject><subject>Automation</subject><subject>Blood flow</subject><subject>Blood Flow Velocity - physiology</subject><subject>Child</subject><subject>Consistency</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Female</subject><subject>Field strength</subject><subject>Flow mapping</subject><subject>Heart valves</subject><subject>Heart Valves - diagnostic imaging</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image processing</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Image segmentation</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Magnetic resonance imaging</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Magnetic Resonance Imaging, Cine - methods</subject><subject>Male</subject><subject>Mean</subject><subject>Median (statistics)</subject><subject>net flow volume</subject><subject>Population studies</subject><subject>postprocessing analysis time</subject><subject>Rank tests</subject><subject>Regurgitation</subject><subject>regurgitation fraction</subject><subject>Reproducibility of Results</subject><subject>Retrospective Studies</subject><subject>Segmentation</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Statistical tests</subject><subject>Tracking</subject><subject>Velocity</subject><subject>Workflow</subject><subject>Young Adult</subject><issn>1053-1807</issn><issn>1522-2586</issn><issn>1522-2586</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp9kU1v1DAQhiMEoqVw4QcgS1wQUsr4I18ntCwsLGqFBKVXy3EmixcnXuxkq_0t_FkcslSFAyfbM48ezfhNkqcUzikAe7XtvDlnFS_gXnJKM8ZSlpX5_XiHjKe0hOIkeRTCFgCqSmQPkxNeZlkpKjhNfq5Gaw9kMQ6uUwM25FrZPZIvuOmwH9RgXE9a58kb61xDVtbdkEUIGMLUJivvOiLezvXLz2uy7rUdG9Nv7hiXyjdG6aP5yiv9fQJU30yPPuxjfbTKk2u0TpvhQC7VbheRx8mDVtmAT47nWfJ19e5q-SG9-PR-vVxcpFrkDFKRQY7AEWmpdV0iZwJUgS0WtCi0FmWtGNdKNaypMYcKIWO1aFoGOY8fUvKz5PXs3Y11h42Om3ll5c6bTvmDdMrIvzu9-SY3bi8pzUUmKhoNL44G736MGAbZmaDRWtWjG4PkwCnlXDAe0ef_oFs3-j7uJzkVgkGZVRCplzOlvQvBY3s7DQU5hS6n0OXv0CP87O78t-iflCNAZ-DGWDz8RyU_xhBn6S8xr7nU</recordid><startdate>202501</startdate><enddate>202501</enddate><creator>Braekt, Thomas</creator><creator>Aben, Jean‐Paul</creator><creator>Maussen, Marc</creator><creator>Bosch, Harrie C.M.</creator><creator>Houthuizen, Patrick</creator><creator>Roest, Arno A.W.</creator><creator>Boogaard, Pieter J.</creator><creator>Lamb, Hildo J.</creator><creator>Westenberg, Jos J.M.</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><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>7QO</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-7945-3421</orcidid><orcidid>https://orcid.org/0000-0003-1946-1715</orcidid><orcidid>https://orcid.org/0000-0002-6969-2418</orcidid></search><sort><creationdate>202501</creationdate><title>Fully Automated Valve Segmentation for Blood Flow Assessment From 4D Flow MRI Including Automated Cardiac Valve Tracking and Transvalvular Velocity Mapping</title><author>Braekt, Thomas ; Aben, Jean‐Paul ; Maussen, Marc ; Bosch, Harrie C.M. ; Houthuizen, Patrick ; Roest, Arno A.W. ; Boogaard, Pieter J. ; Lamb, Hildo J. ; Westenberg, Jos J.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4620-4506e03ee18ccb8e3240a7efe7177cc48ba23caad2dbe609e052b4df206309983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>4D flow MRI</topic><topic>Adolescent</topic><topic>Adult</topic><topic>automated valve segmentation</topic><topic>Automation</topic><topic>Blood flow</topic><topic>Blood Flow Velocity - physiology</topic><topic>Child</topic><topic>Consistency</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Female</topic><topic>Field strength</topic><topic>Flow mapping</topic><topic>Heart valves</topic><topic>Heart Valves - diagnostic imaging</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Image processing</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Image segmentation</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Magnetic resonance imaging</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Magnetic Resonance Imaging, Cine - methods</topic><topic>Male</topic><topic>Mean</topic><topic>Median (statistics)</topic><topic>net flow volume</topic><topic>Population studies</topic><topic>postprocessing analysis time</topic><topic>Rank tests</topic><topic>Regurgitation</topic><topic>regurgitation fraction</topic><topic>Reproducibility of Results</topic><topic>Retrospective Studies</topic><topic>Segmentation</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Statistical tests</topic><topic>Tracking</topic><topic>Velocity</topic><topic>Workflow</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Braekt, Thomas</creatorcontrib><creatorcontrib>Aben, Jean‐Paul</creatorcontrib><creatorcontrib>Maussen, Marc</creatorcontrib><creatorcontrib>Bosch, Harrie C.M.</creatorcontrib><creatorcontrib>Houthuizen, Patrick</creatorcontrib><creatorcontrib>Roest, Arno A.W.</creatorcontrib><creatorcontrib>Boogaard, Pieter J.</creatorcontrib><creatorcontrib>Lamb, Hildo J.</creatorcontrib><creatorcontrib>Westenberg, Jos J.M.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of magnetic resonance imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Braekt, Thomas</au><au>Aben, Jean‐Paul</au><au>Maussen, Marc</au><au>Bosch, Harrie C.M.</au><au>Houthuizen, Patrick</au><au>Roest, Arno A.W.</au><au>Boogaard, Pieter J.</au><au>Lamb, Hildo J.</au><au>Westenberg, Jos J.M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fully Automated Valve Segmentation for Blood Flow Assessment From 4D Flow MRI Including Automated Cardiac Valve Tracking and Transvalvular Velocity Mapping</atitle><jtitle>Journal of magnetic resonance imaging</jtitle><addtitle>J Magn Reson Imaging</addtitle><date>2025-01</date><risdate>2025</risdate><volume>61</volume><issue>1</issue><spage>198</spage><epage>208</epage><pages>198-208</pages><issn>1053-1807</issn><issn>1522-2586</issn><eissn>1522-2586</eissn><abstract>Background
Automated 4D flow MRI valvular flow quantification without time‐consuming manual segmentation might improve workflow.
Purpose
Compare automated valve segmentation (AS) to manual (MS), and manually corrected automated segmentation (AMS), in corrected atrioventricular septum defect (c‐AVSD) patients and healthy volunteers, for assessing net forward volume (NFV) and regurgitation fraction (RF).
Study Type
Retrospective.
Population
27 c‐AVSD patients (median, 23 years; interquartile range, 16–31 years) and 24 healthy volunteers (25 years; 12.5–36.5 years).
Field strength/Sequence
Whole‐heart 4D flow MRI and cine steady‐state free precession at 3T.
Assessment
After automatic valve tracking, valve annuli were segmented on time‐resolved reformatted trans‐valvular velocity images by AS, MS, and AMS. NFV was calculated for all valves, and RF for right and left atrioventricular valves (RAVV and LAVV). NFV variation (standard deviation divided by mean NFV) and NFV differences (NFV difference of a valve vs. mean NFV of other valves) expressed internal NFV consistency.
Statistical Tests
Comparisons between methods were assessed by Wilcoxon signed‐rank tests, and intra/interobserver variability by intraclass correlation coefficients (ICCs). P < 0.05 was considered statistically significant, with multiple testing correction.
Results
AMS mean analysis time was significantly shorter compared with MS (5.3 ± 1.6 minutes vs. 9.1 ± 2.5 minutes). MS NFV variation (6.0%) was significantly smaller compared with AMS (6.3%), and AS (8.2%). Median NFV difference of RAVV, LAVV, PV, and AoV between segmentation methods ranged from −0.7–1.0 mL, −0.5–2.8 mL, −1.1–3.6 mL, and − 3.1–‐2.1 mL, respectively. Median RAVV and LAVV RF, between 7.1%–7.5% and 3.8%–4.3%, respectively, were not significantly different between methods. Intraobserver/interobserver agreement for AMS and MS was strong‐to‐excellent for NFV and RF (ICC ≥0.88).
Data Conclusion
MS demonstrates strongest internal consistency, followed closely by AMS, and AS. Automated segmentation, with or without manual correction, can be considered for 4D flow MRI valvular flow quantification.
Level of Evidence
3
Technical Efficacy
Stage 3</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>38558490</pmid><doi>10.1002/jmri.29370</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-7945-3421</orcidid><orcidid>https://orcid.org/0000-0003-1946-1715</orcidid><orcidid>https://orcid.org/0000-0002-6969-2418</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of magnetic resonance imaging, 2025-01, Vol.61 (1), p.198-208 |
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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | 4D flow MRI Adolescent Adult automated valve segmentation Automation Blood flow Blood Flow Velocity - physiology Child Consistency Correlation coefficient Correlation coefficients Female Field strength Flow mapping Heart valves Heart Valves - diagnostic imaging Humans Image Interpretation, Computer-Assisted - methods Image processing Image Processing, Computer-Assisted - methods Image segmentation Imaging, Three-Dimensional - methods Magnetic resonance imaging Magnetic Resonance Imaging - methods Magnetic Resonance Imaging, Cine - methods Male Mean Median (statistics) net flow volume Population studies postprocessing analysis time Rank tests Regurgitation regurgitation fraction Reproducibility of Results Retrospective Studies Segmentation Statistical analysis Statistical methods Statistical tests Tracking Velocity Workflow Young Adult |
| title | Fully Automated Valve Segmentation for Blood Flow Assessment From 4D Flow MRI Including Automated Cardiac Valve Tracking and Transvalvular Velocity Mapping |
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