1
|
A methodological scoping review of the integration of fMRI to guide dMRI tractography. What has been done and what can be improved: A 20-year perspective. J Neurosci Methods 2022; 367:109435. [PMID: 34915047 DOI: 10.1016/j.jneumeth.2021.109435] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 11/30/2021] [Accepted: 12/02/2021] [Indexed: 11/23/2022]
Abstract
Combining MRI modalities is a growing trend in neurosciences. It provides opportunities to investigate the brain architecture supporting cognitive functions. Integrating fMRI activation to guide dMRI tractography offers potential advantages over standard tractography methods. A quick glimpse of the literature on this topic reveals that this technique is challenging, and no consensus or "best practices" currently exist, at least not within a single document. We present the first attempt to systematically analyze and summarize the literature of 80 studies that integrated task-based fMRI results to guide tractography, over the last two decades. We report 19 findings that cover challenges related to sample size, microstructure modelling, seeding methods, multimodal space registration, false negatives/positives, specificity/validity, gray/white matter interface and more. These findings will help the scientific community (1) understand the strengths and limitations of the approaches, (2) design studies using this integrative framework, and (3) motivate researchers to fill the gaps identified. We provide references toward best practices, in order to improve the overall result's replicability, sensitivity, specificity, and validity.
Collapse
|
2
|
Jaatela J, Aydogan DB, Nurmi T, Vallinoja J, Piitulainen H. Identification of Proprioceptive Thalamocortical Tracts in Children: Comparison of fMRI, MEG, and Manual Seeding of Probabilistic Tractography. Cereb Cortex 2022; 32:3736-3751. [PMID: 35040948 PMCID: PMC9433422 DOI: 10.1093/cercor/bhab444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 11/05/2021] [Accepted: 11/06/2021] [Indexed: 11/16/2022] Open
Abstract
Studying white matter connections with tractography is a promising approach to understand the development of different brain processes, such as proprioception. An emerging method is to use functional brain imaging to select the cortical seed points for tractography, which is considered to improve the functional relevance and validity of the studied connections. However, it is unknown whether different functional seeding methods affect the spatial and microstructural properties of the given white matter connection. Here, we compared functional magnetic resonance imaging, magnetoencephalography, and manual seeding of thalamocortical proprioceptive tracts for finger and ankle joints separately. We showed that all three seeding approaches resulted in robust thalamocortical tracts, even though there were significant differences in localization of the respective proprioceptive seed areas in the sensorimotor cortex, and in the microstructural properties of the obtained tracts. Our study shows that the selected functional or manual seeding approach might cause systematic biases to the studied thalamocortical tracts. This result may indicate that the obtained tracts represent different portions and features of the somatosensory system. Our findings highlight the challenges of studying proprioception in the developing brain and illustrate the need for using multimodal imaging to obtain a comprehensive view of the studied brain process.
Collapse
Affiliation(s)
- Julia Jaatela
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo FI-02150, Finland
| | - Dogu Baran Aydogan
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo FI-02150, Finland
- Department of Psychiatry, Helsinki University Hospital, Helsinki FI-00029, Finland
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio FI-70211, Finland
| | - Timo Nurmi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo FI-02150, Finland
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä FI-40014, Finland
| | - Jaakko Vallinoja
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo FI-02150, Finland
| | - Harri Piitulainen
- Address correspondence to Harri Piitulainen, associate professor, Harri Piitulainen, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. BOX 35, FI-40014, Finland.
| |
Collapse
|
3
|
Petrovic BD, Burman D, Chowdhry S, Bailes JE, Meyer J. Pictorial essay: How co-registered BOLD fMRI and DTI data can improve diffusion tensor tractography. INTERDISCIPLINARY NEUROSURGERY 2021. [DOI: 10.1016/j.inat.2021.101258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
|
4
|
Niu C, Cohen AD, Wen X, Chen Z, Lin P, Liu X, Menze BH, Wiestler B, Wang Y, Zhang M. Modeling motor task activation from resting-state fMRI using machine learning in individual subjects. Brain Imaging Behav 2021; 15:122-132. [PMID: 31903530 DOI: 10.1007/s11682-019-00239-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Resting-state functional MRI (rs-fMRI) has provided important insights into brain physiology. It has become an increasingly popular method for presurgical mapping, as an alternative to task-based functional MRI wherein the subject performs a task while being scanned. However, there is no commonly acknowledged gold standard approach for detecting eloquent brain areas using rs-fMRI data in clinical settings. In this study, a general linear model-based machine learning (GLM-ML) approach was tested to predict individual motor task activation based on rs-fMRI data. Its accuracy was then compared to a conventional independent component analysis (ICA) approach. 47 healthy subjects were scanned using resting state, active and passive motor task fMRI experiments using a clinically applicable low-resolution fMRI protocol. The model was trained to associate rs-fMRI network maps with that of hand movement task fMRI, then used to predict task activation maps for unseen subjects solely based on their rs-fMRI data. Our results showed that the GLM-ML approach can accurately predict individual differences in task activation using rs-fMRI data and outperform conventional ICA to detect task activation in the primary sensorimotor region. Furthermore, the predicted activation maps using the GLM -ML model matched well with the activation of passive hand movement fMRI on an individual basis. These results suggest that GLM-ML approach can robustly predict individual differences of task activation based on conventional low-resolution rs-fMRI data and has important implications for future clinical applications.
Collapse
Affiliation(s)
- Chen Niu
- Department of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, No. 277 West Yanta Road, Xi'an, 710061, Shaanxi Province, China
- Institute for Biomedical Engineering, Technical University of Munich, Munich, Germany
| | - Alexander D Cohen
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Xin Wen
- Department of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, No. 277 West Yanta Road, Xi'an, 710061, Shaanxi Province, China
| | - Ziyi Chen
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Pan Lin
- Department of Psychology and Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, China
| | - Xin Liu
- Institute for Biomedical Engineering, Technical University of Munich, Munich, Germany
| | - Bjoern H Menze
- Institute for Biomedical Engineering, Technical University of Munich, Munich, Germany
- Department of Computer Science, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, Klinikum rechts der Isar, TU München, Munich, Germany
| | - Yang Wang
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
| | - Ming Zhang
- Department of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, No. 277 West Yanta Road, Xi'an, 710061, Shaanxi Province, China.
| |
Collapse
|
5
|
Lin C, Chen L. The role of blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) combined with diffusion tensor imaging (DTI) in surgery for tumors involving motor pathways. BRAIN SCIENCE ADVANCES 2019. [DOI: 10.26599/bsa.2019.9050007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
|
6
|
Gong S, Zhang F, Norton I, Essayed WI, Unadkat P, Rigolo L, Pasternak O, Rathi Y, Hou L, Golby AJ, O’Donnell LJ. Free water modeling of peritumoral edema using multi-fiber tractography: Application to tracking the arcuate fasciculus for neurosurgical planning. PLoS One 2018; 13:e0197056. [PMID: 29746544 PMCID: PMC5944935 DOI: 10.1371/journal.pone.0197056] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Accepted: 04/25/2018] [Indexed: 12/13/2022] Open
Abstract
Purpose Peritumoral edema impedes the full delineation of fiber tracts due to partial volume effects in image voxels that contain a mixture of cerebral parenchyma and extracellular water. The purpose of this study is to investigate the effect of incorporating a free water (FW) model of edema for white matter tractography in the presence of edema. Materials and methods We retrospectively evaluated 26 consecutive brain tumor patients with diffusion MRI and T2-weighted images acquired presurgically. Tractography of the arcuate fasciculus (AF) was performed using the two-tensor unscented Kalman filter tractography (UKFt) method, the UKFt method with a reduced fiber tracking stopping fractional anisotropy (FA) threshold (UKFt+rFA), and the UKFt method with the addition of a FW compartment (UKFt+FW). An automated white matter fiber tract identification approach was applied to delineate the AF. Quantitative measurements included tract volume, edema volume, and mean FW fraction. Visual comparisons were performed by three experts to evaluate the quality of the detected AF tracts. Results The AF volume in edematous brain hemispheres was significantly larger using the UKFt+FW method (p<0.0001) compared to UKFt, but not significantly larger (p = 0.0996) in hemispheres without edema. The AF size increase depended on the volume of edema: a significant correlation was found between AF volume affected by (intersecting) edema and AF volume change with the FW model (Pearson r = 0.806, p<0.0001). The mean FW fraction was significantly larger in tracts intersecting edema (p = 0.0271). Compared to the UKFt+rFA method, there was a significant increase of the volume of the AF tract that intersected the edema using the UKFt+FW method, while the whole AF volumes were similar. Expert judgment results, based on the five patients with the smallest AF volumes, indicated that the expert readers generally preferred the AF tract obtained by using the FW model, according to their anatomical knowledge and considering the potential influence of the final results on the surgical route. Conclusion Our results indicate that incorporating biophysical models of edema can increase the sensitivity of tractography in regions of peritumoral edema, allowing better tract visualization in patients with high grade gliomas and metastases.
Collapse
Affiliation(s)
- Shun Gong
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Neurosurgery, Shanghai Institute of Neurosurgery, Shanghai Changzheng Hospital, Shanghai, China
| | - Fan Zhang
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Isaiah Norton
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Walid I. Essayed
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Prashin Unadkat
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Laura Rigolo
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ofer Pasternak
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yogesh Rathi
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lijun Hou
- Department of Neurosurgery, Shanghai Institute of Neurosurgery, Shanghai Changzheng Hospital, Shanghai, China
| | - Alexandra J. Golby
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lauren J. O’Donnell
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- * E-mail:
| |
Collapse
|
7
|
Liao R, Ning L, Chen Z, Rigolo L, Gong S, Pasternak O, Golby AJ, Rathi Y, O'Donnell LJ. Performance of unscented Kalman filter tractography in edema: Analysis of the two-tensor model. NEUROIMAGE-CLINICAL 2017; 15:819-831. [PMID: 28725549 PMCID: PMC5506885 DOI: 10.1016/j.nicl.2017.06.027] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 06/01/2017] [Accepted: 06/19/2017] [Indexed: 11/30/2022]
Abstract
Diffusion MRI tractography is increasingly used in pre-operative neurosurgical planning to visualize critical fiber tracts. However, a major challenge for conventional tractography, especially in patients with brain tumors, is tracing fiber tracts that are affected by vasogenic edema, which increases water content in the tissue and lowers diffusion anisotropy. One strategy for improving fiber tracking is to use a tractography method that is more sensitive than the traditional single-tensor streamline tractography. We performed experiments to assess the performance of two-tensor unscented Kalman filter (UKF) tractography in edema. UKF tractography fits a diffusion model to the data during fiber tracking, taking advantage of prior information from the previous step along the fiber. We studied UKF performance in a synthetic diffusion MRI digital phantom with simulated edema and in retrospective data from two neurosurgical patients with edema affecting the arcuate fasciculus and corticospinal tracts. We compared the performance of several tractography methods including traditional streamline, UKF single-tensor, and UKF two-tensor. To provide practical guidance on how the UKF method could be employed, we evaluated the impact of using various seed regions both inside and outside the edematous regions, as well as the impact of parameter settings on the tractography sensitivity. We quantified the sensitivity of different methods by measuring the percentage of the patient-specific fMRI activation that was reached by the tractography. We expected that diffusion anisotropy threshold parameters, as well as the inclusion of a free water model, would significantly influence the reconstruction of edematous WM fiber tracts, because edema increases water content in the tissue and lowers anisotropy. Contrary to our initial expectations, varying the fractional anisotropy threshold and including a free water model did not affect the UKF two-tensor tractography output appreciably in these two patient datasets. The most effective parameter for increasing tracking sensitivity was the generalized anisotropy (GA) threshold, which increased the length of tracked fibers when reduced to 0.075. In addition, the most effective seeding strategy was seeding in the whole brain or in a large region outside of the edema. Overall, the main contribution of this study is to provide insight into how UKF tractography can work, using a two-tensor model, to begin to address the challenge of fiber tract reconstruction in edematous regions near brain tumors. Reconstruction of edematous white matter from diffusion MRI is investigated. The performance of two–tensor unscented Kalman filter (UKF) tractography is assessed. The two–tensor model in UKF is analyzed in phantom and patient data experiments. Practical guidance on employing the UKF method in neurosurgical patients is provided
Collapse
Affiliation(s)
- Ruizhi Liao
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Lipeng Ning
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Zhenrui Chen
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Laura Rigolo
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Shun Gong
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Shanghai Changzheng Hospital, Shanghai, China
| | - Ofer Pasternak
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alexandra J Golby
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | |
Collapse
|
8
|
Essayed WI, Zhang F, Unadkat P, Cosgrove GR, Golby AJ, O'Donnell LJ. White matter tractography for neurosurgical planning: A topography-based review of the current state of the art. Neuroimage Clin 2017; 15:659-672. [PMID: 28664037 PMCID: PMC5480983 DOI: 10.1016/j.nicl.2017.06.011] [Citation(s) in RCA: 133] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 04/17/2017] [Accepted: 06/08/2017] [Indexed: 12/13/2022]
Abstract
We perform a review of the literature in the field of white matter tractography for neurosurgical planning, focusing on those works where tractography was correlated with clinical information such as patient outcome, clinical functional testing, or electro-cortical stimulation. We organize the review by anatomical location in the brain and by surgical procedure, including both supratentorial and infratentorial pathologies, and excluding spinal cord applications. Where possible, we discuss implications of tractography for clinical care, as well as clinically relevant technical considerations regarding the tractography methods. We find that tractography is a valuable tool in variable situations in modern neurosurgery. Our survey of recent reports demonstrates multiple potentially successful applications of white matter tractography in neurosurgery, with progress towards overcoming clinical challenges of standardization and interpretation.
Collapse
Affiliation(s)
- Walid I Essayed
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Fan Zhang
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Prashin Unadkat
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - G Rees Cosgrove
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alexandra J Golby
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Lauren J O'Donnell
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| |
Collapse
|