Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts
Diffusion MRI and tractography hold great potential for surgery planning, especially to preserve eloquent white matter during resections. However, fiber tract reconstruction requires an expert with detailed understanding of neuroanatomy. Several automated approaches have been proposed, using differe...
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-01-01
|
| Series: | NeuroImage: Clinical |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213158219302335 |
| _version_ | 1828387814706774016 |
|---|---|
| author | Matteo Mancini Sjoerd B. Vos Vejay N. Vakharia Aidan G. O'Keeffe Karin Trimmel Frederik Barkhof Christian Dorfer Salil Soman Gavin P. Winston Chengyuan Wu John S. Duncan Rachel Sparks Sebastien Ourselin |
| author_facet | Matteo Mancini Sjoerd B. Vos Vejay N. Vakharia Aidan G. O'Keeffe Karin Trimmel Frederik Barkhof Christian Dorfer Salil Soman Gavin P. Winston Chengyuan Wu John S. Duncan Rachel Sparks Sebastien Ourselin |
| author_sort | Matteo Mancini |
| collection | DOAJ |
| description | Diffusion MRI and tractography hold great potential for surgery planning, especially to preserve eloquent white matter during resections. However, fiber tract reconstruction requires an expert with detailed understanding of neuroanatomy. Several automated approaches have been proposed, using different strategies to reconstruct the white matter tracts in a supervised fashion. However, validation is often limited to comparison with manual delineation by overlap-based measures, which is limited in characterizing morphological and topological differences.In this work, we set up a fully automated pipeline based on anatomical criteria that does not require manual intervention, taking advantage of atlas-based criteria and advanced acquisition protocols available on clinical-grade MRI scanners. Then, we extensively validated it on epilepsy patients with specific focus on language-related bundles. The validation procedure encompasses different approaches, including simple overlap with manual segmentations from two experts, feasibility ratings from external multiple clinical raters and relation with task-based functional MRI.Overall, our results demonstrate good quantitative agreement between automated and manual segmentation, in most cases better performances of the proposed method in qualitative terms, and meaningful relationships with task-based fMRI. In addition, we observed significant differences between experts in terms of both manual segmentation and external ratings. These results offer important insights on how different levels of validation complement each other, supporting the idea that overlap-based measures, although quantitative, do not offer a full perspective on the similarities and differences between automated and manual methods. |
| first_indexed | 2024-12-10T06:00:24Z |
| format | Article |
| id | doaj.art-3d70faebc62f4c11ade2400d92dda706 |
| institution | Directory Open Access Journal |
| issn | 2213-1582 |
| language | English |
| last_indexed | 2024-12-10T06:00:24Z |
| publishDate | 2019-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage: Clinical |
| spelling | doaj.art-3d70faebc62f4c11ade2400d92dda7062022-12-22T01:59:49ZengElsevierNeuroImage: Clinical2213-15822019-01-0123Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tractsMatteo Mancini0Sjoerd B. Vos1Vejay N. Vakharia2Aidan G. O'Keeffe3Karin Trimmel4Frederik Barkhof5Christian Dorfer6Salil Soman7Gavin P. Winston8Chengyuan Wu9John S. Duncan10Rachel Sparks11Sebastien Ourselin12Centre for Medical Image Computing, University College London, London, United Kingdom; Corresponding author at: Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, 2 Malet Pl, Camden Town, London WC1E 7JE, United Kingdom.Centre for Medical Image Computing, University College London, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont St Peter, United KingdomDepartment of Clinical and Experimental Epilepsy, University College London, London, United Kingdom; National Hospital for Neurology and Neurosurgery, Queen Square, London, UKDepartment of Statistical Science, University College London, London, UKEpilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom; National Hospital for Neurology and Neurosurgery, Queen Square, London, UK; Department of Neurology, Medical University of Vienna, Vienna, AustriaCentre for Medical Image Computing, University College London, London, United Kingdom; Brain Repair and Rehabilitation, University College London, London, UK; Radiology & Nuclear Medicine, VU University Medical Centre, Amsterdam, NetherlandsDepartment of Neurosurgery, Vienna General Hospital, Medical University of Vienna, Vienna, AustriaHarvard Medical School, Beth Israel Deaconess Medical Center, Department of Radiology, Boston, MA 00215, United States.Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom; Department of Medicine, Division of Neurology, Queen's University, Kingston, Ontario, CanadaDepartment of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, USAEpilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom; National Hospital for Neurology and Neurosurgery, Queen Square, London, UKSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UKSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UKDiffusion MRI and tractography hold great potential for surgery planning, especially to preserve eloquent white matter during resections. However, fiber tract reconstruction requires an expert with detailed understanding of neuroanatomy. Several automated approaches have been proposed, using different strategies to reconstruct the white matter tracts in a supervised fashion. However, validation is often limited to comparison with manual delineation by overlap-based measures, which is limited in characterizing morphological and topological differences.In this work, we set up a fully automated pipeline based on anatomical criteria that does not require manual intervention, taking advantage of atlas-based criteria and advanced acquisition protocols available on clinical-grade MRI scanners. Then, we extensively validated it on epilepsy patients with specific focus on language-related bundles. The validation procedure encompasses different approaches, including simple overlap with manual segmentations from two experts, feasibility ratings from external multiple clinical raters and relation with task-based functional MRI.Overall, our results demonstrate good quantitative agreement between automated and manual segmentation, in most cases better performances of the proposed method in qualitative terms, and meaningful relationships with task-based fMRI. In addition, we observed significant differences between experts in terms of both manual segmentation and external ratings. These results offer important insights on how different levels of validation complement each other, supporting the idea that overlap-based measures, although quantitative, do not offer a full perspective on the similarities and differences between automated and manual methods.http://www.sciencedirect.com/science/article/pii/S2213158219302335 |
| spellingShingle | Matteo Mancini Sjoerd B. Vos Vejay N. Vakharia Aidan G. O'Keeffe Karin Trimmel Frederik Barkhof Christian Dorfer Salil Soman Gavin P. Winston Chengyuan Wu John S. Duncan Rachel Sparks Sebastien Ourselin Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts NeuroImage: Clinical |
| title | Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts |
| title_full | Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts |
| title_fullStr | Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts |
| title_full_unstemmed | Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts |
| title_short | Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts |
| title_sort | automated fiber tract reconstruction for surgery planning extensive validation in language related white matter tracts |
| url | http://www.sciencedirect.com/science/article/pii/S2213158219302335 |
| work_keys_str_mv | AT matteomancini automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT sjoerdbvos automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT vejaynvakharia automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT aidangokeeffe automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT karintrimmel automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT frederikbarkhof automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT christiandorfer automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT salilsoman automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT gavinpwinston automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT chengyuanwu automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT johnsduncan automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT rachelsparks automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts AT sebastienourselin automatedfibertractreconstructionforsurgeryplanningextensivevalidationinlanguagerelatedwhitemattertracts |