Validation of structural brain connectivity networks: The impact of scanning parameters
Evaluation of the structural connectivity (SC) of the brain based on tractography has mainly focused on the choice of diffusion model, tractography algorithm, and their respective parameter settings. Here, we systematically validate SC derived from a post mortem monkey brain, while varying key acqui...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2020-01-01
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| Series: | NeuroImage |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811919307980 |
| _version_ | 1818457413335908352 |
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| author | Karen S. Ambrosen Simon F. Eskildsen Max Hinne Kristine Krug Henrik Lundell Mikkel N. Schmidt Marcel A.J. van Gerven Morten Mørup Tim B. Dyrby |
| author_facet | Karen S. Ambrosen Simon F. Eskildsen Max Hinne Kristine Krug Henrik Lundell Mikkel N. Schmidt Marcel A.J. van Gerven Morten Mørup Tim B. Dyrby |
| author_sort | Karen S. Ambrosen |
| collection | DOAJ |
| description | Evaluation of the structural connectivity (SC) of the brain based on tractography has mainly focused on the choice of diffusion model, tractography algorithm, and their respective parameter settings. Here, we systematically validate SC derived from a post mortem monkey brain, while varying key acquisition parameters such as the b-value, gradient angular resolution and image resolution. As gold standard we use the connectivity matrix obtained invasively with histological tracers by Markov et al. (2014). As performance metric, we use cross entropy as a measure that enables comparison of the relative tracer labeled neuron counts to the streamline counts from tractography. We find that high angular resolution and high signal-to-noise ratio are important to estimate SC, and that SC derived from low image resolution (1.03 mm3) are in better agreement with the tracer network, than those derived from high image resolution (0.53 mm3) or at an even lower image resolution (2.03 mm3). In contradiction, sensitivity and specificity analyses suggest that if the angular resolution is sufficient, the balanced compromise in which sensitivity and specificity are identical remains 60–64% regardless of the other scanning parameters. Interestingly, the tracer graph is assumed to be the gold standard but by thresholding, the balanced compromise increases to 70–75%. Hence, by using performance metrics based on binarized tracer graphs, one risks losing important information, changing the performance of SC graphs derived by tractography and their dependence of different scanning parameters. |
| first_indexed | 2024-12-14T22:42:10Z |
| format | Article |
| id | doaj.art-a82a5831f2984cf28780758e535ce8d8 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-14T22:42:10Z |
| publishDate | 2020-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-a82a5831f2984cf28780758e535ce8d82022-12-21T22:44:57ZengElsevierNeuroImage1095-95722020-01-01204116207Validation of structural brain connectivity networks: The impact of scanning parametersKaren S. Ambrosen0Simon F. Eskildsen1Max Hinne2Kristine Krug3Henrik Lundell4Mikkel N. Schmidt5Marcel A.J. van Gerven6Morten Mørup7Tim B. Dyrby8Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark; Danish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, DenmarkCenter of Functionally Integrative Neuroscience (CFIN), Department of Clinical Medicine, Aarhus University, Aarhus, DenmarkDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the NetherlandsDepartment of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK; Institute of Biology, Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany; Leibniz-Insitute for Neurobiology, Magdeburg, GermanyDanish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, DenmarkDepartment of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, DenmarkDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the NetherlandsDepartment of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, DenmarkDanish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark; Corresponding author. Danish Research Centre for Magnetic Resonance, section 714, Copenhagen University Hospital Hvidovre, Kettegaard Alle 30, 4623, Hvidovre, Denmark.Evaluation of the structural connectivity (SC) of the brain based on tractography has mainly focused on the choice of diffusion model, tractography algorithm, and their respective parameter settings. Here, we systematically validate SC derived from a post mortem monkey brain, while varying key acquisition parameters such as the b-value, gradient angular resolution and image resolution. As gold standard we use the connectivity matrix obtained invasively with histological tracers by Markov et al. (2014). As performance metric, we use cross entropy as a measure that enables comparison of the relative tracer labeled neuron counts to the streamline counts from tractography. We find that high angular resolution and high signal-to-noise ratio are important to estimate SC, and that SC derived from low image resolution (1.03 mm3) are in better agreement with the tracer network, than those derived from high image resolution (0.53 mm3) or at an even lower image resolution (2.03 mm3). In contradiction, sensitivity and specificity analyses suggest that if the angular resolution is sufficient, the balanced compromise in which sensitivity and specificity are identical remains 60–64% regardless of the other scanning parameters. Interestingly, the tracer graph is assumed to be the gold standard but by thresholding, the balanced compromise increases to 70–75%. Hence, by using performance metrics based on binarized tracer graphs, one risks losing important information, changing the performance of SC graphs derived by tractography and their dependence of different scanning parameters.http://www.sciencedirect.com/science/article/pii/S1053811919307980 |
| spellingShingle | Karen S. Ambrosen Simon F. Eskildsen Max Hinne Kristine Krug Henrik Lundell Mikkel N. Schmidt Marcel A.J. van Gerven Morten Mørup Tim B. Dyrby Validation of structural brain connectivity networks: The impact of scanning parameters NeuroImage |
| title | Validation of structural brain connectivity networks: The impact of scanning parameters |
| title_full | Validation of structural brain connectivity networks: The impact of scanning parameters |
| title_fullStr | Validation of structural brain connectivity networks: The impact of scanning parameters |
| title_full_unstemmed | Validation of structural brain connectivity networks: The impact of scanning parameters |
| title_short | Validation of structural brain connectivity networks: The impact of scanning parameters |
| title_sort | validation of structural brain connectivity networks the impact of scanning parameters |
| url | http://www.sciencedirect.com/science/article/pii/S1053811919307980 |
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