1
|
Jellema PEJ, Mannsdörfer LM, Visser F, De Luca A, Smit CLE, Hoving EW, van Baarsen KM, Lindner T, Mutsaerts HJMM, Dankbaar JW, Lequin MH, Wijnen JP. Improving advanced intraoperative MRI methods during pediatric neurosurgery. NMR IN BIOMEDICINE 2024; 37:e5124. [PMID: 38403798 DOI: 10.1002/nbm.5124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 02/27/2024]
Abstract
Advanced intraoperative MR images (ioMRI) acquired during the resection of pediatric brain tumors could offer additional physiological information to preserve healthy tissue. With this work, we aimed to develop a protocol for ioMRI with increased sensitivity for arterial spin labeling (ASL) and diffusion MRI (dMRI), optimized for patient positioning regularly used in the pediatric neurosurgery setting. For ethical reasons, ASL images were acquired in healthy adult subjects that were imaged in the prone and supine position. After this, the ASL cerebral blood flow (CBF) was quantified and compared between both positions. To evaluate the impact of the RF coils setups on image quality, we compared different setups (two vs. four RF coils) by looking at T1-weighted (T1w) signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), as well as undertaking a qualitative evaluation of T1w, T2w, ASL, and dMR images. Mean ASL CBF did not differ between the surgical prone and supine positions in any of the investigated regions of interest or the whole brain. T1w SNR (gray matter: p = 0.016, 34% increase; white matter: p = 0.016, 32% increase) and CNR were higher (p = 0.016) in the four versus two RF coils setups (18.0 ± 1.8 vs. 13.9 ± 1.8). Qualitative evaluation of T1w, T2w, ASL, and dMR images resulted in acceptable to good image quality and did not differ statistically significantly between setups. Only the nonweighted diffusion image maps and corticospinal tract reconstructions yielded higher image quality and reduced susceptibility artifacts with four RF coils. Advanced ioMRI metrics were more precise with four RF coils as the standard deviation decreased. Taken together, we have investigated the practical use of advanced ioMRI during pediatric neurosurgery. We conclude that ASL CBF quantification in the surgical prone position is valid and that ASL and dMRI acquisition with two RF coils can be performed adequately for clinical use. With four versus two RF coils, the SNR of the images increases, and the sensitivity to artifacts reduces.
Collapse
Affiliation(s)
- Pien E J Jellema
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Lilli M Mannsdörfer
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
| | - Fredy Visser
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
- Philips HealthCare, Best, The Netherlands
| | - Alberto De Luca
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
- Department of Neurology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cynthia L E Smit
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
| | - Eelco W Hoving
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Kirsten M van Baarsen
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Thomas Lindner
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Henk-Jan M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Jan Willem Dankbaar
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Maarten H Lequin
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Jannie P Wijnen
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
| |
Collapse
|
2
|
Newman BT, Patrie JT, Druzgal TJ. An intracellular isotropic diffusion signal is positively associated with pubertal development in white matter. Dev Cogn Neurosci 2023; 63:101301. [PMID: 37717292 PMCID: PMC10511341 DOI: 10.1016/j.dcn.2023.101301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 08/14/2023] [Accepted: 09/13/2023] [Indexed: 09/19/2023] Open
Abstract
Puberty is a key event in adolescent development that involves significant, hormone-driven changes to many aspects of physiology including the brain. Understanding how the brain responds during this time period is important for evaluating neuronal developments that affect mental health throughout adolescence and the adult lifespan. This study examines diffusion MRI scans from the cross-sectional ABCD Study baseline cohort, a large multi-site study containing thousands of participants, to describe the relationship between pubertal development and brain microstructure. Using advanced, 3-tissue constrained spherical deconvolution methods, this study is able to describe multiple tissue compartments beyond only white matter (WM) axonal qualities. After controlling for age, sex, brain volume, subject handedness, scanning site, and sibling relationships, we observe a positive relationship between an isotropic, intracellular diffusion signal fraction and pubertal development across a majority of regions of interest (ROIs) in the WM skeleton. We also observe regional effects from an intracellular anisotropic signal fraction compartment and extracellular isotropic free water-like compartment in several ROIs. This cross-sectional work suggests that changes in pubertal status are associated with a complex response from brain tissue that cannot be completely described by traditional methods focusing only on WM axonal properties.
Collapse
Affiliation(s)
- Benjamin T Newman
- Department of Radiology and Medical Imaging, School of Medicine, University of Virginia, USA.
| | - James T Patrie
- Department of Public Health Sciences, School of Medicine, University of Virginia, USA
| | - T Jason Druzgal
- Department of Radiology and Medical Imaging, School of Medicine, University of Virginia, USA
| |
Collapse
|
3
|
Orset T, Royo J, Santin MD, Pouget P, Thiebaut de Schotten M. A new open, high-resolution, multishell, diffusion-weighted imaging dataset of the living squirrel monkey. Sci Data 2023; 10:224. [PMID: 37081025 PMCID: PMC10119165 DOI: 10.1038/s41597-023-02126-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 03/31/2023] [Indexed: 04/22/2023] Open
Abstract
Although very well adapted to brain study, Magnetic Resonance Imaging (MRI) remains limited by the facilities and capabilities required to acquire data, especially for non-human primates. Addressing the data gaps resulting from these limitations requires making data more accessible and open. In contempt of the regular use of Saimiri sciureus in neuroscience research, in vivo diffusion has yet to be openly available for this species. Here we built and made openly available a unique new resource consisting of a high-resolution, multishell diffusion-weighted dataset in the anesthetized Saimiri sciureus. The data were acquired on 11 individuals with an 11.7 T MRI scanner (isotropic resolution of 400 µm3). This paper presents an overview of our dataset and illustrates some of its possible use through example analyses. To assess the quality of our data, we analyzed long-range connections (whole-brain tractography), microstructure (Neurite Orientation Dispersion and Density Imaging), and axon diameter in the corpus callosum (ActiveAx). Constituting an essential new resource for primate evolution studies, all data are openly available.
Collapse
Affiliation(s)
- Thomas Orset
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France.
- Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, ICM, Movement Investigation and Therapeutics Team, Paris, France.
| | - Julie Royo
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France
- Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, ICM, Movement Investigation and Therapeutics Team, Paris, France
| | | | - Pierre Pouget
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France
- Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, ICM, Movement Investigation and Therapeutics Team, Paris, France
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne University, Paris, France
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| |
Collapse
|
4
|
Capizzi M, Martín-Signes M, Coull JT, Chica AB, Charras P. A transcranial magnetic stimulation study on the role of the left intraparietal sulcus in temporal orienting of attention. Neuropsychologia 2023; 184:108561. [PMID: 37031951 DOI: 10.1016/j.neuropsychologia.2023.108561] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 02/21/2023] [Accepted: 04/05/2023] [Indexed: 04/11/2023]
Abstract
Adaptive behavior requires the ability to orient attention to the moment in time at which a relevant event is likely to occur. Temporal orienting of attention has been consistently associated with activation of the left intraparietal sulcus (IPS) in prior fMRI studies. However, a direct test of its causal involvement in temporal orienting is still lacking. The present study tackled this issue by transiently perturbing left IPS activity with either online (Experiment 1) or offline (Experiment 2) transcranial magnetic stimulation (TMS). In both experiments, participants performed a temporal orienting task, alternating between blocks in which a temporal cue predicted when a subsequent target would appear and blocks in which a neutral cue provided no information about target timing. In Experiment 1 we used an online TMS protocol, aiming to interfere specifically with cue-related temporal processes, whereas in Experiment 2 we employed an offline protocol whereby participants performed the temporal orienting task before and after receiving TMS. The right IPS and/or the vertex were stimulated as active control regions. While results replicated the canonical pattern of temporal orienting effects on reaction time, with faster responses for temporal than neutral trials, these effects were not modulated by TMS over the left IPS (as compared to the right IPS and/or vertex regions) regardless of the online or offline protocol used. Overall, these findings challenge the causal role of the left IPS in temporal orienting of attention inviting further research on its underlying neural substrates.
Collapse
Affiliation(s)
- Mariagrazia Capizzi
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Department of Experimental Psychology, University of Granada, Spain.
| | - Mar Martín-Signes
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Department of Experimental Psychology, University of Granada, Spain
| | - Jennifer T Coull
- Laboratoire de Neurosciences Cognitives UMR 7291, Aix-Marseille University, CNRS, Marseille, France
| | - Ana B Chica
- Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Department of Experimental Psychology, University of Granada, Spain
| | - Pom Charras
- Univ Paul Valéry Montpellier 3, EPSYLON EA 4556, F34000, Montpellier, France
| |
Collapse
|
5
|
Zhylka A, Leemans A, Pluim JPW, De Luca A. Anatomically informed multi-level fiber tractography for targeted virtual dissection. MAGMA (NEW YORK, N.Y.) 2023; 36:79-93. [PMID: 35904612 PMCID: PMC9992235 DOI: 10.1007/s10334-022-01033-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 06/30/2022] [Accepted: 07/15/2022] [Indexed: 12/01/2022]
Abstract
OBJECTIVES Diffusion-weighted MRI can assist preoperative planning by reconstructing the trajectory of eloquent fiber pathways, such as the corticospinal tract (CST). However, accurate reconstruction of the full extent of the CST remains challenging with existing tractography methods. We suggest a novel tractography algorithm exploiting unused fiber orientations to produce more complete and reliable results. METHODS Our novel approach, referred to as multi-level fiber tractography (MLFT), reconstructs fiber pathways by progressively considering previously unused fiber orientations at multiple levels of tract propagation. Anatomical priors are used to minimize the number of false-positive pathways. The MLFT method was evaluated on synthetic data and in vivo data by reconstructing the CST while compared to conventional tractography approaches. RESULTS The radial extent of MLFT reconstructions is comparable to that of probabilistic reconstruction: [Formula: see text] for the left and [Formula: see text] for the right hemisphere according to Wilcoxon test, while achieving significantly higher topography preservation compared to probabilistic tractography: [Formula: see text]. DISCUSSION MLFT provides a novel way to reconstruct fiber pathways by adding the capability of including branching pathways in fiber tractography. Thanks to its robustness, feasible reconstruction extent and topography preservation, our approach may assist in clinical practice as well as in virtual dissection studies.
Collapse
Affiliation(s)
- Andrey Zhylka
- Biomedical Engineering, Eindhoven University of Technology, Rondom 70, 5612 AP, Eindhoven, The Netherlands.
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Josien P W Pluim
- Biomedical Engineering, Eindhoven University of Technology, Rondom 70, 5612 AP, Eindhoven, The Netherlands
| | - Alberto De Luca
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.,Neurology Department, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| |
Collapse
|
6
|
Jellema PEJ, Wijnen JP, De Luca A, Mutsaerts HJMM, Obdeijn IV, van Baarsen KM, Lequin MH, Hoving EW. Advanced intraoperative MRI in pediatric brain tumor surgery. Front Physiol 2023; 14:1098959. [PMID: 37123260 PMCID: PMC10134397 DOI: 10.3389/fphys.2023.1098959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 03/29/2023] [Indexed: 05/02/2023] Open
Abstract
Introduction: In the pediatric brain tumor surgery setting, intraoperative MRI (ioMRI) provides "real-time" imaging, allowing for evaluation of the extent of resection and detection of complications. The use of advanced MRI sequences could potentially provide additional physiological information that may aid in the preservation of healthy brain regions. This review aims to determine the added value of advanced imaging in ioMRI for pediatric brain tumor surgery compared to conventional imaging. Methods: Our systematic literature search identified relevant articles on PubMed using keywords associated with pediatrics, ioMRI, and brain tumors. The literature search was extended using the snowball technique to gather more information on advanced MRI techniques, their technical background, their use in adult ioMRI, and their use in routine pediatric brain tumor care. Results: The available literature was sparse and demonstrated that advanced sequences were used to reconstruct fibers to prevent damage to important structures, provide information on relative cerebral blood flow or abnormal metabolites, or to indicate the onset of hemorrhage or ischemic infarcts. The explorative literature search revealed developments within each advanced MRI field, such as multi-shell diffusion MRI, arterial spin labeling, and amide-proton transfer-weighted imaging, that have been studied in adult ioMRI but have not yet been applied in pediatrics. These techniques could have the potential to provide more accurate fiber tractography, information on intraoperative cerebral perfusion, and to match gadolinium-based T1w images without using a contrast agent. Conclusion: The potential added value of advanced MRI in the intraoperative setting for pediatric brain tumors is to prevent damage to important structures, to provide additional physiological or metabolic information, or to indicate the onset of postoperative changes. Current developments within various advanced ioMRI sequences are promising with regard to providing in-depth tissue information.
Collapse
Affiliation(s)
- Pien E. J. Jellema
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, Netherlands
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, Netherlands
- *Correspondence: Pien E. J. Jellema,
| | - Jannie P. Wijnen
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Alberto De Luca
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, Netherlands
- Department of Neurology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Henk J. M. M. Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Iris V. Obdeijn
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Kirsten M. van Baarsen
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Maarten H. Lequin
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, Netherlands
- Department of Radiology, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Eelco W. Hoving
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, Netherlands
| |
Collapse
|
7
|
Multimodal tract-based MRI metrics outperform whole brain markers in determining cognitive impact of small vessel disease-related brain injury. Brain Struct Funct 2022; 227:2553-2567. [PMID: 35994115 PMCID: PMC9418106 DOI: 10.1007/s00429-022-02546-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 07/27/2022] [Indexed: 01/04/2023]
Abstract
In cerebral small vessel disease (cSVD), whole brain MRI markers of cSVD-related brain injury explain limited variance to support individualized prediction. Here, we investigate whether considering abnormalities in brain tracts by integrating multimodal metrics from diffusion MRI (dMRI) and structural MRI (sMRI), can better capture cognitive performance in cSVD patients than established approaches based on whole brain markers. We selected 102 patients (73.7 ± 10.2 years old, 59 males) with MRI-visible SVD lesions and both sMRI and dMRI. Conventional linear models using demographics and established whole brain markers were used as benchmark of predicting individual cognitive scores. Multi-modal metrics of 73 major brain tracts were derived from dMRI and sMRI, and used together with established markers as input of a feed-forward artificial neural network (ANN) to predict individual cognitive scores. A feature selection strategy was implemented to reduce the risk of overfitting. Prediction was performed with leave-one-out cross-validation and evaluated with the R2 of the correlation between measured and predicted cognitive scores. Linear models predicted memory and processing speed with R2 = 0.26 and R2 = 0.38, respectively. With ANN, feature selection resulted in 13 tract-specific metrics and 5 whole brain markers for predicting processing speed, and 28 tract-specific metrics and 4 whole brain markers for predicting memory. Leave-one-out ANN prediction with the selected features achieved R2 = 0.49 and R2 = 0.40 for processing speed and memory, respectively. Our results show proof-of-concept that combining tract-specific multimodal MRI metrics can improve the prediction of cognitive performance in cSVD by leveraging tract-specific multi-modal metrics.
Collapse
|
8
|
De Luca A, Karayumak SC, Leemans A, Rathi Y, Swinnen S, Gooijers J, Clauwaert A, Bahr R, Sandmo SB, Sochen N, Kaufmann D, Muehlmann M, Biessels GJ, Koerte I, Pasternak O. Cross-site harmonization of multi-shell diffusion MRI measures based on rotational invariant spherical harmonics (RISH). Neuroimage 2022; 259:119439. [PMID: 35788044 DOI: 10.1016/j.neuroimage.2022.119439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 06/23/2022] [Accepted: 06/30/2022] [Indexed: 11/25/2022] Open
Abstract
Quantification methods based on the acquisition of diffusion magnetic resonance imaging (dMRI) with multiple diffusion weightings (e.g., multi-shell) are becoming increasingly applied to study the in-vivo brain. Compared to single-shell data for diffusion tensor imaging (DTI), multi-shell data allows to apply more complex models such as diffusion kurtosis imaging (DKI), which attempts to capture both diffusion hindrance and restriction effects, or biophysical models such as NODDI, which attempt to increase specificity by separating biophysical components. Because of the strong dependence of the dMRI signal on the measurement hardware, DKI and NODDI metrics show scanner and site differences, much like other dMRI metrics. These effects limit the implementation of multi-shell approaches in multicenter studies, which are needed to collect large sample sizes for robust analyses. Recently, a post-processing technique based on rotation invariant spherical harmonics (RISH) features was introduced to mitigate cross-scanner differences in DTI metrics. Unlike statistical harmonization methods, which require repeated application to every dMRI metric of choice, RISH harmonization is applied once on the raw data, and can be followed by any analysis. RISH features harmonization has been tested on DTI features but not its generalizability to harmonize multi-shell dMRI. In this work, we investigated whether performing the RISH features harmonization of multi-shell dMRI data removes cross-site differences in DKI and NODDI metrics while retaining longitudinal effects. To this end, 46 subjects underwent a longitudinal (up to 3 time points) two-shell dMRI protocol at 3 imaging sites. DKI and NODDI metrics were derived before and after harmonization and compared both at the whole brain level and at the voxel level. Then, the harmonization effects on cross-sectional and on longitudinal group differences were evaluated. RISH features averaged for each of the 3 sites exhibited prominent between-site differences in the frontal and posterior part of the brain. Statistically significant differences in fractional anisotropy, mean diffusivity and mean kurtosis were observed both at the whole brain and voxel level between all the acquisition sites before harmonization, but not after. The RISH method also proved effective to harmonize NODDI metrics, particularly in white matter. The RISH based harmonization maintained the magnitude and variance of longitudinal changes as compared to the non-harmonized data of all considered metrics. In conclusion, the application of RISH feature based harmonization to multi-shell dMRI data can be used to remove cross-site differences in DKI metrics and NODDI analyses, while retaining inherent relations between longitudinal acquisitions.
Collapse
Affiliation(s)
- Alberto De Luca
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands; PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands; Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia.
| | | | - Alexander Leemans
- PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Yogesh Rathi
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Stephan Swinnen
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium; KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Jolien Gooijers
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium; KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Amanda Clauwaert
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium; KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Roald Bahr
- Oslo Sports Trauma Research Center, Norwegian School of Sport Sciences, Oslo, Norway
| | - Stian Bahr Sandmo
- Oslo Sports Trauma Research Center, Norwegian School of Sport Sciences, Oslo, Norway
| | - Nir Sochen
- Department of Applied Mathematics, Tel Aviv University, Tel Aviv, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - David Kaufmann
- Radiology Department, Charite University Hospital, Berlin, Germany
| | - Marc Muehlmann
- Department of Radiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Geert-Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Inga Koerte
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; cBRAIN, Department of Child and Adolescent Psychiatry, Ludwig-Maximilians-Universität, Munich, Germany
| | - Ofer Pasternak
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|
9
|
Guo F, Tax CMW, De Luca A, Viergever MA, Heemskerk A, Leemans A. Fiber orientation distribution from diffusion MRI: Effects of inaccurate response function calibration. J Neuroimaging 2021; 31:1082-1098. [PMID: 34128556 PMCID: PMC9290593 DOI: 10.1111/jon.12901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 05/24/2021] [Accepted: 06/02/2021] [Indexed: 11/27/2022] Open
Abstract
Background and Purpose Diffusion MRI of the brain enables to quantify white matter fiber orientations noninvasively. Several approaches have been proposed to estimate such characteristics from diffusion MRI data with spherical deconvolution being one of the most widely used methods. Spherical deconvolution requires to define––or derive from the data––a response function, which is used to compute the fiber orientation distribution (FOD). Different characteristics of the response function are expected to affect the FOD computation and the subsequent fiber tracking. Methods In this work, we explored the effects of inaccuracies in the shape factors of the response function on the FOD characteristics. Results With simulations, we show that the apparent fiber density could be doubled in the presence of underestimated shape factors in the response functions, whereas the overestimation of the shape factor will cause more spurious peaks in the FOD, especially when the signal‐to‐noise ratio is below 15. Moreover, crossing fiber populations with a separation angle smaller than 60° were more sensitive to inaccuracies in the response function than fiber populations with more orthogonal separation angles. Results with in vivo data demonstrate angular deviations in the FODs and spurious peaks as a result of modified shape factors of the response function, while the reconstruction of the main parts of fiber bundles is well preserved. Conclusions This work sheds light on how specific aspects of the response function shape can affect the estimated FODs, and highlights the importance of a proper calibration/definition of the response function.
Collapse
Affiliation(s)
- Fenghua Guo
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Chantal M W Tax
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
| | - Alberto De Luca
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Max A Viergever
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Anneriet Heemskerk
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| |
Collapse
|
10
|
Guo F, de Luca A, Parker G, Jones DK, Viergever MA, Leemans A, Tax CMW. The effect of gradient nonlinearities on fiber orientation estimates from spherical deconvolution of diffusion magnetic resonance imaging data. Hum Brain Mapp 2021; 42:367-383. [PMID: 33035372 PMCID: PMC7776002 DOI: 10.1002/hbm.25228] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 09/22/2020] [Accepted: 09/24/2020] [Indexed: 12/12/2022] Open
Abstract
Gradient nonlinearities in magnetic resonance imaging (MRI) cause spatially varying mismatches between the imposed and the effective gradients and can cause significant biases in rotationally invariant diffusion MRI measures derived from, for example, diffusion tensor imaging. The estimation of the orientational organization of fibrous tissue, which is nowadays frequently performed with spherical deconvolution techniques ideally using higher diffusion weightings, can likewise be biased by gradient nonlinearities. We explore the sensitivity of two established spherical deconvolution approaches to gradient nonlinearities, namely constrained spherical deconvolution (CSD) and damped Richardson-Lucy (dRL). Additionally, we propose an extension of dRL to take into account gradient imperfections, without the need of data interpolation. Simulations show that using the effective b-matrix can improve dRL fiber orientation estimation and reduces angular deviations, while CSD can be more robust to gradient nonlinearity depending on the implementation. Angular errors depend on a complex interplay of many factors, including the direction and magnitude of gradient deviations, underlying microstructure, SNR, anisotropy of the effective response function, and diffusion weighting. Notably, angular deviations can also be observed at lower b-values in contrast to the perhaps common assumption that only high b-value data are affected. In in vivo Human Connectome Project data and acquisitions from an ultrastrong gradient (300 mT/m) scanner, angular differences are observed between applying and not applying the effective gradients in dRL estimation. As even small angular differences can lead to error propagation during tractography and as such impact connectivity analyses, incorporating gradient deviations into the estimation of fiber orientations should make such analyses more reliable.
Collapse
Affiliation(s)
- Fenghua Guo
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Alberto de Luca
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Greg Parker
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
| | - Max A. Viergever
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Alexander Leemans
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Chantal M. W. Tax
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
| |
Collapse
|
11
|
Morez J, Sijbers J, Vanhevel F, Jeurissen B. Constrained spherical deconvolution of nonspherically sampled diffusion MRI data. Hum Brain Mapp 2020; 42:521-538. [PMID: 33169880 PMCID: PMC7776001 DOI: 10.1002/hbm.25241] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2020] [Revised: 08/30/2020] [Accepted: 09/29/2020] [Indexed: 12/18/2022] Open
Abstract
Constrained spherical deconvolution (CSD) of diffusion-weighted MRI (DW-MRI) is a popular analysis method that extracts the full white matter (WM) fiber orientation density function (fODF) in the living human brain, noninvasively. It assumes that the DW-MRI signal on the sphere can be represented as the spherical convolution of a single-fiber response function (RF) and the fODF, and recovers the fODF through the inverse operation. CSD approaches typically require that the DW-MRI data is sampled shell-wise, and estimate the RF in a purely spherical manner using spherical basis functions, such as spherical harmonics (SH), disregarding any radial dependencies. This precludes analysis of data acquired with nonspherical sampling schemes, for example, Cartesian sampling. Additionally, nonspherical sampling can also arise due to technical issues, for example, gradient nonlinearities, resulting in a spatially dependent bias of the apparent tissue densities and connectivity information. Here, we adopt a compact model for the RFs that also describes their radial dependency. We demonstrate that the proposed model can accurately predict the tissue response for a wide range of b-values. On shell-wise data, our approach provides fODFs and tissue densities indistinguishable from those estimated using SH. On Cartesian data, fODF estimates and apparent tissue densities are on par with those obtained from shell-wise data, significantly broadening the range of data sets that can be analyzed using CSD. In addition, gradient nonlinearities can be accounted for using the proposed model, resulting in much more accurate apparent tissue densities and connectivity metrics.
Collapse
Affiliation(s)
- Jan Morez
- Imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
| | - Jan Sijbers
- Imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
| | - Floris Vanhevel
- Department of Radiology, University Hospital Antwerp, Antwerp, Belgium
| | - Ben Jeurissen
- Imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
| |
Collapse
|
12
|
De Luca A, Guo F, Froeling M, Leemans A. Spherical deconvolution with tissue-specific response functions and multi-shell diffusion MRI to estimate multiple fiber orientation distributions (mFODs). Neuroimage 2020; 222:117206. [DOI: 10.1016/j.neuroimage.2020.117206] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Revised: 07/20/2020] [Accepted: 07/23/2020] [Indexed: 12/18/2022] Open
|