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Sretavan K, Braun H, Liu Z, Bullock D, Palnitkar T, Patriat R, Chandrasekaran J, Brenny S, Johnson MD, Widge AS, Harel N, Heilbronner SR. A reproducible pipeline for parcellation of the anterior limb of the internal capsule. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00196-4. [PMID: 39053578 DOI: 10.1016/j.bpsc.2024.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 07/11/2024] [Accepted: 07/11/2024] [Indexed: 07/27/2024]
Abstract
BACKGROUND The anterior limb of the internal capsule (ALIC) is a white matter structure connecting the prefrontal cortex (PFC) to the brainstem, thalamus, and subthalamic nucleus. It is a target for deep brain stimulation (DBS) for obsessive-compulsive disorder. There is strong interest in improving DBS targeting by using diffusion tractography to reconstruct and target specific ALIC fiber pathways, but this methodology is susceptible to errors and lacks validation. To address these limitations, we developed a novel diffusion tractography pipeline that generates reliable and biologically validated ALIC white matter reconstructions. METHODS Following algorithm development and refinement, we analyzed 43 control subjects each with 2 sets of 3T MRI data and a subset of 5 controls with 7T data from the Human Connectome Project. We generated 22 segmented ALIC fiber bundles (11 per hemisphere) based on prefrontal PFC regions of interest, and we analyzed the relationships among bundles. RESULTS We successfully reproduced the topographies established by prior anatomical work using images acquired at both 3T and 7T. Quantitative assessment demonstrated significantly smaller intra-subject variability relative to inter-subject variability for both test and retest groups across all but one PFC region. We examined the overlap between fibers from different PFC regions and a response tract for obsessive-compulsive disorder deep brain stimulation, and we reconstructed the PFC hyperdirect pathway using a modified version of our pipeline. DISCUSSION Our dMRI algorithm reliably generates biologically validated ALIC white matter reconstructions, allowing for more precise modelling of fibers for neuromodulation therapies.
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Affiliation(s)
- Karianne Sretavan
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, Minnesota; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Henry Braun
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Zoe Liu
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota
| | - Daniel Bullock
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota
| | - Tara Palnitkar
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Remi Patriat
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Jayashree Chandrasekaran
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Samuel Brenny
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Matthew D Johnson
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota
| | - Alik S Widge
- Department of Psychiatry, University of Minnesota, Minneapolis, Minnesota
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota; Department of Neurosurgery, University of Minnesota, Minneapolis, Minnesota
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Patriat R, Palnitkar T, Chandrasekaran J, Sretavan K, Braun H, Yacoub E, McGovern RA, Aman J, Cooper SE, Vitek JL, Harel N. DiMANI: diffusion MRI for anatomical nuclei imaging-Application for the direct visualization of thalamic subnuclei. Front Hum Neurosci 2024; 18:1324710. [PMID: 38439939 PMCID: PMC10910100 DOI: 10.3389/fnhum.2024.1324710] [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: 10/20/2023] [Accepted: 02/05/2024] [Indexed: 03/06/2024] Open
Abstract
The thalamus is a centrally located and heterogeneous brain structure that plays a critical role in various sensory, motor, and cognitive processes. However, visualizing the individual subnuclei of the thalamus using conventional MRI techniques is challenging. This difficulty has posed obstacles in targeting specific subnuclei for clinical interventions such as deep brain stimulation (DBS). In this paper, we present DiMANI, a novel method for directly visualizing the thalamic subnuclei using diffusion MRI (dMRI). The DiMANI contrast is computed by averaging, voxelwise, diffusion-weighted volumes enabling the direct distinction of thalamic subnuclei in individuals. We evaluated the reproducibility of DiMANI through multiple approaches. First, we utilized a unique dataset comprising 8 scans of a single participant collected over a 3-year period. Secondly, we quantitatively assessed manual segmentations of thalamic subnuclei for both intra-rater and inter-rater reliability. Thirdly, we qualitatively correlated DiMANI imaging data from several patients with Essential Tremor with the localization of implanted DBS electrodes and clinical observations. Lastly, we demonstrated that DiMANI can provide similar features at 3T and 7T MRI, using varying numbers of diffusion directions. Our results establish that DiMANI is a reproducible and clinically relevant method to directly visualize thalamic subnuclei. This has significant implications for the development of new DBS targets and the optimization of DBS therapy.
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Affiliation(s)
- Rémi Patriat
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
| | - Tara Palnitkar
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
| | - Jayashree Chandrasekaran
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
| | - Karianne Sretavan
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN, United States
| | - Henry Braun
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
| | - Robert A. McGovern
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, United States
| | - Joshua Aman
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Scott E. Cooper
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Jerrold L. Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, United States
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3
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de Zwart JA, van Gelderen P, Wang Y, Duyn JH. Accelerated multislice MRI with patterned excitation. Magn Reson Med 2024; 91:252-265. [PMID: 37769229 DOI: 10.1002/mrm.29850] [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: 04/27/2023] [Revised: 08/14/2023] [Accepted: 08/15/2023] [Indexed: 09/30/2023]
Abstract
PURPOSE Accelerate multislice 2D MRI by using RF pulses that simultaneously act on different slices to combine contrast preparation and image acquisition. THEORY AND METHODS MRI applications often require the use of multiple RF pulses to generate desired contrast and prepare the signal for readout. Examples are the use of inversion prepulses to generate T1 contrast, or the use of spin-echo preparations to generate T2 or diffusion contrast. In multislice MRI, this separation of contrast preparation and readout can render scans time-inefficient and lengthy. We introduce a class of pulse sequences that overcomes this inefficiency by combining contrast preparation and signal readout. This is accomplished by using RF pulses that manipulate the magnetization of multiple slices simultaneously and a gradient crusher scheme that selects a target slice for readout. RESULTS Feasibility of the method was demonstrated for spin echo-based measurement of water diffusion and tissue pulsation in human brain at 3 T. Increases in time-efficiency and reductions in scan time were highly dependent on specific implementation and reached as high as 25% and 53%, respectively. CONCLUSION A novel approach to multislice MRI is demonstrated that reduces scan time for specific applications.
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Affiliation(s)
- Jacco A de Zwart
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, Bethesda, USA
| | - Peter van Gelderen
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, Bethesda, USA
| | - Yicun Wang
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, Bethesda, USA
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, Bethesda, USA
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Manzano-Patron JP, Moeller S, Andersson JLR, Ugurbil K, Yacoub E, Sotiropoulos SN. DENOISING DIFFUSION MRI: CONSIDERATIONS AND IMPLICATIONS FOR ANALYSIS. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.24.550348. [PMID: 37546835 PMCID: PMC10402048 DOI: 10.1101/2023.07.24.550348] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Development of diffusion MRI (dMRI) denoising approaches has experienced considerable growth over the last years. As noise can inherently reduce accuracy and precision in measurements, its effects have been well characterised both in terms of uncertainty increase in dMRI-derived features and in terms of biases caused by the noise floor, the smallest measurable signal given the noise level. However, gaps in our knowledge still exist in objectively characterising dMRI denoising approaches in terms of both of these effects and assessing their efficacy. In this work, we reconsider what a denoising method should and should not do and we accordingly define criteria to characterise the performance. We propose a comprehensive set of evaluations, including i) benefits in improving signal quality and reducing noise variance, ii) gains in reducing biases and the noise floor and improving, iii) preservation of spatial resolution, iv) agreement of denoised data against a gold standard, v) gains in downstream parameter estimation (precision and accuracy), vi) efficacy in enabling noise-prone applications, such as ultra-high-resolution imaging. We further provide newly acquired complex datasets (magnitude and phase) with multiple repeats that sample different SNR regimes to highlight performance differences under different scenarios. Without loss of generality, we subsequently apply a number of exemplar patch-based denoising algorithms to these datasets, including Non-Local Means, Marchenko-Pastur PCA (MPPCA) in the magnitude and complex domain and NORDIC, and compare them with respect to the above criteria and against a gold standard complex average of multiple repeats. We demonstrate that all tested denoising approaches reduce noise-related variance, but not always biases from the elevated noise floor. They all induce a spatial resolution penalty, but its extent can vary depending on the method and the implementation. Some denoising approaches agree with the gold standard more than others and we demonstrate challenges in even defining such a standard. Overall, we show that dMRI denoising performed in the complex domain is advantageous to magnitude domain denoising with respect to all the above criteria.
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Affiliation(s)
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, USA
| | | | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, USA
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
- Nottingham Biomedical Research Centre, Queen's Medical Centre, University of Nottingham, UK
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Valcourt Caron A, Shmuel A, Hao Z, Descoteaux M. versaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database. Front Neuroinform 2023; 17:1191200. [PMID: 37637471 PMCID: PMC10449583 DOI: 10.3389/fninf.2023.1191200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/27/2023] [Indexed: 08/29/2023] Open
Abstract
The lack of "gold standards" in Diffusion Weighted Imaging (DWI) makes validation cumbersome. To tackle this task, studies use translational analysis where results in humans are benchmarked against findings in other species. Non-Human Primates (NHP) are particularly interesting for this, as their cytoarchitecture is closely related to humans. However, tools used for processing and analysis must be adapted and finely tuned to work well on NHP images. Here, we propose versaFlow, a modular pipeline implemented in Nextflow, designed for robustness and scalability. The pipeline is tailored to in vivo NHP DWI at any spatial resolution; it allows for maintainability and customization. Processes and workflows are implemented using cutting-edge and state-of-the-art Magnetic Resonance Imaging (MRI) processing technologies and diffusion modeling algorithms, namely Diffusion Tensor Imaging (DTI), Constrained Spherical Deconvolution (CSD), and DIstribution of Anisotropic MicrOstructural eNvironments in Diffusion-compartment imaging (DIAMOND). Using versaFlow, we provide an in-depth study of the variability of diffusion metrics computed on 32 subjects from 3 sites of the Primate Data Exchange (PRIME-DE), which contains anatomical T1-weighted (T1w) and T2-weighted (T2w) images, functional MRI (fMRI), and DWI of NHP brains. This dataset includes images acquired over a range of resolutions, using single and multi-shell gradient samplings, on multiple scanner vendors. We perform a reproducibility study of the processing of versaFlow using the Aix-Marseilles site's data, to ensure that our implementation has minimal impact on the variability observed in subsequent analyses. We report very high reproducibility for the majority of metrics; only gamma distribution parameters of DIAMOND display less reproducible behaviors, due to the absence of a mechanism to enforce a random number seed in the software we used. This should be taken into consideration when future applications are performed. We show that the PRIME-DE diffusion data exhibits a great level of variability, similar or greater than results obtained in human studies. Its usage should be done carefully to prevent instilling uncertainty in statistical analyses. This hints at a need for sufficient harmonization in acquisition protocols and for the development of robust algorithms capable of managing the variability induced in imaging due to differences in scanner models and/or vendors.
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Affiliation(s)
- Alex Valcourt Caron
- Sherbrooke Connectivity Imaging Laboratory, Computer Science Department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Amir Shmuel
- Brain Imaging Signals Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Ziqi Hao
- Brain Imaging Signals Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory, Computer Science Department, Université de Sherbrooke, Sherbrooke, QC, Canada
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6
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Demirel ÖB, Weingärtner S, Moeller S, Akçakaya M. Improved Simultaneous Multi-slice imaging with Composition of k-space Interpolations (SMS-COOKIE) for myocardial T1 mapping. PLoS One 2023; 18:e0283972. [PMID: 37478080 PMCID: PMC10361528 DOI: 10.1371/journal.pone.0283972] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 03/21/2023] [Indexed: 07/23/2023] Open
Abstract
The aim of this study is to develop and evaluate a regularized Simultaneous Multi-Slice (SMS) reconstruction method for improved Cardiac Magnetic Resonance Imaging (CMR). The proposed reconstruction method, SMS with COmpOsition of k-space IntErpolations (SMS-COOKIE) combines the advantages of Iterative Self-consistent Parallel Imaging Reconstruction (SPIRiT) and split slice-Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA), while allowing regularization for further noise reduction. The proposed SMS-COOKIE was implemented with and without regularization, and validated using a Saturation Pulse-Prepared Heart rate Independent inversion REcovery (SAPPHIRE) myocardial T1 mapping sequence. The performance of the proposed reconstruction method was compared to ReadOut (RO)-SENSE-GRAPPA and split slice-GRAPPA, on both retrospectively and prospectively three-fold SMS-accelerated data with an additional two-fold in-plane acceleration. All SMS reconstruction methods yielded similar T1 values compared to single band imaging. SMS-COOKIE showed lower spatial variability in myocardial T1 with significant improvement over RO-SENSE-GRAPPA and split slice-GRAPPA (P < 10-4). The proposed method with additional locally low rank (LLR) regularization reduced the spatial variability, again with significant improvement over RO-SENSE-GRAPPA and split slice-GRAPPA (P < 10-4). In conclusion, improved reconstruction quality was achieved with the proposed SMS-COOKIE, which also provided lower spatial variability with significant improvement over split slice-GRAPPA.
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Affiliation(s)
- Ömer Burak Demirel
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Sebastian Weingärtner
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Mehmet Akçakaya
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, United States of America
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7
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Kornaropoulos EN, Winzeck S, Rumetshofer T, Wikstrom A, Knutsson L, Correia MM, Sundgren PC, Nilsson M. Sensitivity of Diffusion MRI to White Matter Pathology: Influence of Diffusion Protocol, Magnetic Field Strength, and Processing Pipeline in Systemic Lupus Erythematosus. Front Neurol 2022; 13:837385. [PMID: 35557624 PMCID: PMC9087851 DOI: 10.3389/fneur.2022.837385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 03/16/2022] [Indexed: 11/13/2022] Open
Abstract
There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's d for group comparison. Results showed that the choice of diffusion protocol had the largest impact on the effect size. The effect size in fractional anisotropy (FA) across all WM tracts was 0.26 higher when derived by DTI than by DKI and 0.20 higher in 3T compared with 7T. The difference due to the diffusion protocol was larger than the difference due to magnetic field strength for the majority of diffusion parameters. In contrast, the difference between including or excluding different processing steps was near negligible, except for the correction of distortions from eddy currents and motion which had a clearly positive impact. For example, effect sizes increased on average by 0.07 by including motion and eddy correction for FA derived from 3T-DTI. Effect sizes were slightly reduced by the incorporation of denoising and Gibbs-ringing removal (on average by 0.011 and 0.005, respectively). Smoothing prior to diffusion model fitting generally reduced effect sizes. In summary, 3T-DTI in combination with eddy current and motion correction yielded the highest sensitivity to WM pathology in patients with SLE. However, our results also indicated that the 3T-DKI and 7T-DTI protocols used here may be adjusted to increase effect sizes.
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Affiliation(s)
- Evgenios N. Kornaropoulos
- Clinical Sciences, Diagnostic Radiology, Lund University, Lund, Sweden
- Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom
| | - Stefan Winzeck
- Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom
- BioMedIA Group, Department of Computing, Imperial College London, London, United Kingdom
| | | | - Anna Wikstrom
- Clinical Sciences, Diagnostic Radiology, Lund University, Lund, Sweden
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Marta M. Correia
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Pia C. Sundgren
- Clinical Sciences, Diagnostic Radiology, Lund University, Lund, Sweden
- Lund University BioImaging Center, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Markus Nilsson
- Clinical Sciences, Diagnostic Radiology, Lund University, Lund, Sweden
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Sitek KR, Calabrese E, Johnson GA, Ghosh SS, Chandrasekaran B. Structural Connectivity of Human Inferior Colliculus Subdivisions Using in vivo and post mortem Diffusion MRI Tractography. Front Neurosci 2022; 16:751595. [PMID: 35392412 PMCID: PMC8981148 DOI: 10.3389/fnins.2022.751595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 01/27/2022] [Indexed: 12/05/2022] Open
Abstract
Inferior colliculus (IC) is an obligatory station along the ascending auditory pathway that also has a high degree of top-down convergence via efferent pathways, making it a major computational hub. Animal models have attributed critical roles for the IC in in mediating auditory plasticity, egocentric selection, and noise exclusion. IC contains multiple functionally distinct subdivisions. These include a central nucleus that predominantly receives ascending inputs and external and dorsal nuclei that receive more heterogeneous inputs, including descending and multisensory connections. Subdivisions of human IC have been challenging to identify and quantify using standard brain imaging techniques such as MRI, and the connectivity of each of these subnuclei has not been identified in the human brain. In this study, we estimated the connectivity of human IC subdivisions with diffusion MRI (dMRI) tractography, using both anatomical-based seed analysis as well as unsupervised k-means clustering. We demonstrate sensitivity of tractography to overall IC connections in both high resolution post mortem and in vivo datasets. k-Means clustering of the IC streamlines in both the post mortem and in vivo datasets generally segregated streamlines based on their terminus beyond IC, such as brainstem, thalamus, or contralateral IC. Using fine-grained anatomical segmentations of the major IC subdivisions, the post mortem dataset exhibited unique connectivity patterns from each subdivision, including commissural connections through dorsal IC and lateral lemniscal connections to central and external IC. The subdivisions were less distinct in the context of in vivo connectivity, although lateral lemniscal connections were again highest to central and external IC. Overall, the unsupervised and anatomically driven methods provide converging evidence for distinct connectivity profiles for each of the IC subdivisions in both post mortem and in vivo datasets, suggesting that dMRI tractography with high quality data is sensitive to neural pathways involved in auditory processing as well as top-down control of incoming auditory information.
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Affiliation(s)
- Kevin R. Sitek
- SoundBrain Lab, Brain and Auditory Sciences Research Initiative, Department of Communication and Science Disorders, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Kevin R. Sitek,
| | - Evan Calabrese
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - G. Allan Johnson
- Center for In Vivo Microscopy, Duke University, Durham, NC, United States
| | - Satrajit S. Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
- Department of Otolaryngology – Head and Neck Surgery, Harvard Medical School, Boston, MA, United States
| | - Bharath Chandrasekaran
- SoundBrain Lab, Brain and Auditory Sciences Research Initiative, Department of Communication and Science Disorders, University of Pittsburgh, Pittsburgh, PA, United States
- Bharath Chandrasekaran,
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Song M, Yang Z, Jiang T. Multimodal Brain Imaging Fusion for the White-Matter Fiber Architecture in the Human Brain. Neurosci Bull 2022; 38:561-564. [PMID: 35099675 PMCID: PMC9106764 DOI: 10.1007/s12264-022-00822-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 12/12/2021] [Indexed: 12/22/2022] Open
Affiliation(s)
- Ming Song
- National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China
- Brainnetome Center, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China
- University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhengyi Yang
- National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China
- Brainnetome Center, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China
- University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Tianzi Jiang
- National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China.
- Brainnetome Center, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China.
- University of the Chinese Academy of Sciences, Beijing, 100049, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, 100190, China.
- Key Laboratory for Neuroinformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 625014, China.
- The Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia.
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Christiansen L, Siebner HR. Tools to explore neuroplasticity in humans: Combining interventional neurophysiology with functional and structural magnetic resonance imaging and spectroscopy. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:105-119. [PMID: 35034728 DOI: 10.1016/b978-0-12-819410-2.00032-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
This chapter summarizes how brain imaging can be used in combination with non-invasive transcranial stimulation to probe and induce neuroplasticity in the human brain. We aim to give a conceptual account and highlight exemplary studies. We showcase the scientific and clinical potentials of studies focusing on the combination of transcranial magnetic stimulation (TMS) with Magnetic Resonance Imaging (MRI) or Magnetic Resonance Spectroscopy (MRS). MRI and MRS can be used before brain stimulation to identify target networks and loci but also to inform individual dosing. After a brain stimulation session, MRI and MRS can be used to pinpoint how the stimulation protocol alters brain function, structure, or metabolism and relate these after-effects to behavioral and clinical outcomes. Complementing these "offline" approaches, TMS can also be applied "online" during MRI or MRS to delineate how stimulation acutely engages the stimulated brain regions and networks. In this case, it is critical to account for confounds introduced by off-target stimulation of peripheral structures of the nervous system that may not only confound MR-based readouts but also induce neuroplastic phenomena.
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Affiliation(s)
- Lasse Christiansen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
| | - Hartwig Roman Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark.
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Aja-Fernández S, Pieciak T, Martín-Martín C, Planchuelo-Gómez Á, de Luis-García R, Tristán-Vega A. Moment-based representation of the diffusion inside the brain from reduced DMRI acquisitions: generalized AMURA. Med Image Anal 2022; 77:102356. [DOI: 10.1016/j.media.2022.102356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 12/13/2021] [Accepted: 01/06/2022] [Indexed: 01/18/2023]
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12
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Shim JH, Baek HM. White Matter Connectivity between Structures of the Basal Ganglia using 3T and 7T. Neuroscience 2021; 483:32-39. [PMID: 34974113 DOI: 10.1016/j.neuroscience.2021.12.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 12/21/2021] [Accepted: 12/24/2021] [Indexed: 11/30/2022]
Abstract
Analysis of the basal ganglia has been important in investigating the effects of Parkinson's disease as well as treatments for Parkinson's disease. One method of analysis has been using MRI for non-invasively segmenting the basal ganglia, then investigating significant parameters that involve the basal ganglia, such as fiber orientations and positional markers for deep brain stimulation (DBS). Following enhancements to optimizations and improvements to 3T and 7T MRI acquisitions, we utilized Lead-DBS on human connectome project data to automatically segment the basal ganglia of 49 human connectome project subjects, reducing the reliance on manual segmentation for more consistency. We generated probabilistic tractography streamlines between each segmentation pair using 3T and 7T human connectome diffusion data to observe any major differences in tractography streamline patterns that can arise due to tradeoffs from different field strengths and acquisitions. Tractography streamlines generated between basal ganglia structures using 3T images showed less standard deviation in streamline count than using 7T images. Mean tractography streamline counts generated using 3T diffusion images were all higher in count than streamlines generated using 7T diffusion images. We illustrate a potential method for analyzing the structural connectivity between basal ganglia structures, as well as visualize possible differences in probabilistic tractography that can arise from different acquisition protocols.
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Affiliation(s)
- Jae-Hyuk Shim
- Department of Health Sciences and Technology, GAIHST, Gachon University, Incheon 21999, Republic of Korea
| | - Hyeon-Man Baek
- Department of Health Sciences and Technology, GAIHST, Gachon University, Incheon 21999, Republic of Korea.
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13
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Vizioli L, Moeller S, Dowdle L, Akçakaya M, De Martino F, Yacoub E, Uğurbil K. Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging. Nat Commun 2021; 12:5181. [PMID: 34462435 PMCID: PMC8405721 DOI: 10.1038/s41467-021-25431-8] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 08/05/2021] [Indexed: 01/05/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) has become an indispensable tool for investigating the human brain. However, the inherently poor signal-to-noise-ratio (SNR) of the fMRI measurement represents a major barrier to expanding its spatiotemporal scale as well as its utility and ultimate impact. Here we introduce a denoising technique that selectively suppresses the thermal noise contribution to the fMRI experiment. Using 7-Tesla, high-resolution human brain data, we demonstrate improvements in key metrics of functional mapping (temporal-SNR, the detection and reproducibility of stimulus-induced signal changes, and accuracy of functional maps) while leaving the amplitude of the stimulus-induced signal changes, spatial precision, and functional point-spread-function unaltered. We demonstrate that the method enables the acquisition of ultrahigh resolution (0.5 mm isotropic) functional maps but is also equally beneficial for a large variety of fMRI applications, including supra-millimeter resolution 3- and 7-Tesla data obtained over different cortical regions with different stimulation/task paradigms and acquisition strategies. The signal-to-noise ratio is a key consideration when selecting a magnetic resonance imaging protocol. Thermal noise is major issue, especially in high resolution functional images. Here the authors introduce a method to suppress thermal noise in functional images without losses in spatial precision, increasing the signal-to-noise ratio.
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Affiliation(s)
- Luca Vizioli
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA. .,Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA.
| | - Steen Moeller
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Logan Dowdle
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA.,Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA
| | - Mehmet Akçakaya
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA.,Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Federico De Martino
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA.,Faculty of Psychology and Neuroscience, Department of Cognitive Neurosciences, Maastricht University, Maastricht, the Netherlands
| | - Essa Yacoub
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Kamil Uğurbil
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA.
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Demirel OB, Weingärtner S, Moeller S, Akçakaya M. Improved simultaneous multislice cardiac MRI using readout concatenated k-space SPIRiT (ROCK-SPIRiT). Magn Reson Med 2021; 85:3036-3048. [PMID: 33566378 DOI: 10.1002/mrm.28680] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 12/21/2020] [Accepted: 12/22/2020] [Indexed: 01/31/2023]
Abstract
PURPOSE To develop and evaluate a simultaneous multislice (SMS) reconstruction technique that provides noise reduction and leakage blocking for highly accelerated cardiac MRI. METHODS ReadOut Concatenated k-space SPIRiT (ROCK-SPIRiT) uses the concept of readout concatenation in image domain to represent SMS encoding, and performs coil self-consistency as in SPIRiT-type reconstruction in an extended k-space, while allowing regularization for further denoising. The proposed method is implemented with and without regularization, and validated on retrospectively SMS-accelerated cine imaging with three-fold SMS and two-fold in-plane acceleration. ROCK-SPIRiT is compared with two leakage-blocking SMS reconstruction methods: readout-SENSE-GRAPPA and split slice-GRAPPA. Further evaluation and comparisons are performed using prospectively SMS-accelerated cine imaging. RESULTS Results on retrospectively three-fold SMS and two-fold in-plane accelerated cine imaging show that ROCK-SPIRiT without regularization significantly improves on existing methods in terms of PSNR (readout-SENSE-GRAPPA: 33.5 ± 3.2, split slice-GRAPPA: 34.1 ± 3.8, ROCK-SPIRiT: 35.0 ± 3.3) and SSIM (readout-SENSE-GRAPPA: 84.4 ± 8.9, split slice-GRAPPA: 85.0 ± 8.9, ROCK-SPIRiT: 88.2 ± 6.6 [in percentage]). Regularized ROCK-SPIRiT significantly outperforms all methods, as characterized by these quantitative metrics (PSNR: 37.6 ± 3.8, SSIM: 94.2 ± 4.1 [in percentage]). The prospectively five-fold SMS and two-fold in-plane accelerated data show that ROCK-SPIRiT and regularized ROCK-SPIRiT have visually improved image quality compared with existing methods. CONCLUSION The proposed ROCK-SPIRiT technique reduces noise and interslice leakage in accelerated SMS cardiac cine MRI, improving on existing methods both quantitatively and qualitatively.
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Affiliation(s)
- Omer Burak Demirel
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Sebastian Weingärtner
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA.,Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Mehmet Akçakaya
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
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NOise reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing. Neuroimage 2020; 226:117539. [PMID: 33186723 PMCID: PMC7881933 DOI: 10.1016/j.neuroimage.2020.117539] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Revised: 10/15/2020] [Accepted: 10/28/2020] [Indexed: 01/04/2023] Open
Abstract
Diffusion-weighted magnetic resonance imaging (dMRI) has found great utility for a wide range of neuroscientific and clinical applications. However, high-resolution dMRI, which is required for improved delineation of fine brain structures and connectomics, is hampered by its low signal-to-noise ratio (SNR). Since dMRI relies on the acquisition of multiple different diffusion weighted images of the same anatomy, it is well-suited for denoising methods that utilize correlations across the image series to improve the apparent SNR and the subsequent data analysis. In this work, we introduce and quantitatively evaluate a comprehensive framework, NOise Reduction with DIstribution Corrected (NORDIC) PCA method for processing dMRI. NORDIC uses low-rank modeling of g-factor-corrected complex dMRI reconstruction and non-asymptotic random matrix distributions to remove signal components which cannot be distinguished from thermal noise. The utility of the proposed framework for denoising dMRI is demonstrated on both simulations and experimental data obtained at 3 Tesla with different resolutions using human connectome project style acquisitions. The proposed framework leads to substantially enhanced quantitative performance for estimating diffusion tractography related measures and for resolving crossing fibers as compared to a conventional/state-of-the-art dMRI denoising method.
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