Cargando…
A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data
PURPOSE: 7T time-of-flight (TOF) MRI provides high resolution for the evaluation of cerebrovascular vessels and pathologies. In combination with 4D flow fields acquired with phase-contrast (PC) MRI, hemodynamic information can be extracted to enhance the analysis by providing direct measurements in...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113302/ https://www.ncbi.nlm.nih.gov/pubmed/36662415 http://dx.doi.org/10.1007/s11548-023-02836-y |
_version_ | 1785027810354528256 |
---|---|
author | Spitz, Lena Gaidzik, Franziska Stucht, Daniel Mattern, Hendrik Preim, Bernhard Saalfeld, Sylvia |
author_facet | Spitz, Lena Gaidzik, Franziska Stucht, Daniel Mattern, Hendrik Preim, Bernhard Saalfeld, Sylvia |
author_sort | Spitz, Lena |
collection | PubMed |
description | PURPOSE: 7T time-of-flight (TOF) MRI provides high resolution for the evaluation of cerebrovascular vessels and pathologies. In combination with 4D flow fields acquired with phase-contrast (PC) MRI, hemodynamic information can be extracted to enhance the analysis by providing direct measurements in the larger arteries or patient-specific boundary conditions. Hence, a registration between both modalities is required. METHODS: To combine TOF and PC-MRI data, we developed a hybrid registration approach. Vessels and their centerlines are segmented from the TOF data. The centerline is fit to the intensity ridges of the lower resolved PC-MRI data, which provides temporal information. We used a metric that utilizes a scaled sum of weighted intensities and gradients on the normal plane. The registration is then guided by decoupled local affine transformations. It is applied hierarchically following the branching order of the vessel tree. RESULTS: A landmark validation over Monte Carlo simulations yielded an average mean squared error of 184.73 mm and an average Hausdorff distance of 15.20 mm. The hierarchical traversal that transforms child vessels with their parents registers even small vessels not detectable in the PC-MRI. CONCLUSION: The presented work combines high-resolution tomographic information from 7T TOF-MRI and measured flow data from 4D 7T PC-MRI scan for the arteries of the brain. This enables usage of patient-specific flow parameters for realistic simulations, thus supporting research in areas such as cerebral small vessel disease. Automatization and free deformations can help address the limiting error measures in the future. |
format | Online Article Text |
id | pubmed-10113302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-101133022023-04-20 A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data Spitz, Lena Gaidzik, Franziska Stucht, Daniel Mattern, Hendrik Preim, Bernhard Saalfeld, Sylvia Int J Comput Assist Radiol Surg Original Article PURPOSE: 7T time-of-flight (TOF) MRI provides high resolution for the evaluation of cerebrovascular vessels and pathologies. In combination with 4D flow fields acquired with phase-contrast (PC) MRI, hemodynamic information can be extracted to enhance the analysis by providing direct measurements in the larger arteries or patient-specific boundary conditions. Hence, a registration between both modalities is required. METHODS: To combine TOF and PC-MRI data, we developed a hybrid registration approach. Vessels and their centerlines are segmented from the TOF data. The centerline is fit to the intensity ridges of the lower resolved PC-MRI data, which provides temporal information. We used a metric that utilizes a scaled sum of weighted intensities and gradients on the normal plane. The registration is then guided by decoupled local affine transformations. It is applied hierarchically following the branching order of the vessel tree. RESULTS: A landmark validation over Monte Carlo simulations yielded an average mean squared error of 184.73 mm and an average Hausdorff distance of 15.20 mm. The hierarchical traversal that transforms child vessels with their parents registers even small vessels not detectable in the PC-MRI. CONCLUSION: The presented work combines high-resolution tomographic information from 7T TOF-MRI and measured flow data from 4D 7T PC-MRI scan for the arteries of the brain. This enables usage of patient-specific flow parameters for realistic simulations, thus supporting research in areas such as cerebral small vessel disease. Automatization and free deformations can help address the limiting error measures in the future. Springer International Publishing 2023-01-20 2023 /pmc/articles/PMC10113302/ /pubmed/36662415 http://dx.doi.org/10.1007/s11548-023-02836-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Spitz, Lena Gaidzik, Franziska Stucht, Daniel Mattern, Hendrik Preim, Bernhard Saalfeld, Sylvia A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data |
title | A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data |
title_full | A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data |
title_fullStr | A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data |
title_full_unstemmed | A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data |
title_short | A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data |
title_sort | hybrid hierarchical strategy for registration of 7t tof-mri to 7t pc-mri intracranial vessel data |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113302/ https://www.ncbi.nlm.nih.gov/pubmed/36662415 http://dx.doi.org/10.1007/s11548-023-02836-y |
work_keys_str_mv | AT spitzlena ahybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT gaidzikfranziska ahybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT stuchtdaniel ahybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT matternhendrik ahybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT preimbernhard ahybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT saalfeldsylvia ahybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT spitzlena hybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT gaidzikfranziska hybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT stuchtdaniel hybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT matternhendrik hybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT preimbernhard hybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata AT saalfeldsylvia hybridhierarchicalstrategyforregistrationof7ttofmrito7tpcmriintracranialvesseldata |