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Vidal JP, Danet L, Péran P, Pariente J, Bach Cuadra M, Zahr NM, Barbeau EJ, Saranathan M. Robust thalamic nuclei segmentation from T1-weighted MRI using polynomial intensity transformation. Brain Struct Funct 2024; 229:1087-1101. [PMID: 38546872 PMCID: PMC11147736 DOI: 10.1007/s00429-024-02777-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 02/19/2024] [Indexed: 04/09/2024]
Abstract
Accurate segmentation of thalamic nuclei, crucial for understanding their role in healthy cognition and in pathologies, is challenging to achieve on standard T1-weighted (T1w) magnetic resonance imaging (MRI) due to poor image contrast. White-matter-nulled (WMn) MRI sequences improve intrathalamic contrast but are not part of clinical protocols or extant databases. In this study, we introduce histogram-based polynomial synthesis (HIPS), a fast preprocessing transform step that synthesizes WMn-like image contrast from standard T1w MRI using a polynomial approximation for intensity transformation. HIPS was incorporated into THalamus Optimized Multi-Atlas Segmentation (THOMAS) pipeline, a method developed and optimized for WMn MRI. HIPS-THOMAS was compared to a convolutional neural network (CNN)-based segmentation method and THOMAS modified for the use of T1w images (T1w-THOMAS). The robustness and accuracy of the three methods were tested across different image contrasts (MPRAGE, SPGR, and MP2RAGE), scanner manufacturers (PHILIPS, GE, and Siemens), and field strengths (3 T and 7 T). HIPS-transformed images improved intra-thalamic contrast and thalamic boundaries, and HIPS-THOMAS yielded significantly higher mean Dice coefficients and reduced volume errors compared to both the CNN method and T1w-THOMAS. Finally, all three methods were compared using the frequently travelling human phantom MRI dataset for inter- and intra-scanner variability, with HIPS displaying the least inter-scanner variability and performing comparably with T1w-THOMAS for intra-scanner variability. In conclusion, our findings highlight the efficacy and robustness of HIPS in enhancing thalamic nuclei segmentation from standard T1w MRI.
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Affiliation(s)
- Julie P Vidal
- CNRS, CerCo (Brain and Cognition Research Center), Paul Sabatier University, Toulouse, France
- INSERM, ToNiC (Toulouse NeuroImaging Center), Paul Sabatier University, Toulouse, France
| | - Lola Danet
- INSERM, ToNiC (Toulouse NeuroImaging Center), Paul Sabatier University, Toulouse, France
- Neurology Department, Purpan Hospital, Toulouse University Hospital Center, Toulouse, France
| | - Patrice Péran
- INSERM, ToNiC (Toulouse NeuroImaging Center), Paul Sabatier University, Toulouse, France
| | - Jérémie Pariente
- INSERM, ToNiC (Toulouse NeuroImaging Center), Paul Sabatier University, Toulouse, France
- Neurology Department, Purpan Hospital, Toulouse University Hospital Center, Toulouse, France
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Radiology Department, Lausanne University and University Hospital, Lausanne, Switzerland
| | - Natalie M Zahr
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Emmanuel J Barbeau
- CNRS, CerCo (Brain and Cognition Research Center), Paul Sabatier University, Toulouse, France
| | - Manojkumar Saranathan
- Department of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
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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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Vidal JP, Danet L, Péran P, Pariente J, Cuadra MB, Zahr NM, Barbeau EJ, Saranathan M. Robust thalamic nuclei segmentation from T1-weighted MRI using polynomial intensity transformation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.30.24301606. [PMID: 38352493 PMCID: PMC10862991 DOI: 10.1101/2024.01.30.24301606] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Accurate segmentation of thalamic nuclei, crucial for understanding their role in healthy cognition and in pathologies, is challenging to achieve on standard T1-weighted (T1w) magnetic resonance imaging (MRI) due to poor image contrast. White-matter-nulled (WMn) MRI sequences improve intrathalamic contrast but are not part of clinical protocols or extant databases. In this study, we introduce histogram-based polynomial synthesis (HIPS), a fast preprocessing transform step that synthesizes WMn-like image contrast from standard T1w MRI using a polynomial approximation for intensity transformation. HIPS was incorporated into THalamus Optimized Multi-Atlas Segmentation (THOMAS) pipeline, a method developed and optimized for WMn MRI. HIPS-THOMAS was compared to a convolutional neural network (CNN)-based segmentation method and THOMAS modified for T1w images (T1w-THOMAS). The robustness and accuracy of the three methods were tested across different image contrasts (MPRAGE, SPGR, and MP2RAGE), scanner manufacturers (PHILIPS, GE, and Siemens), and field strengths (3T and 7T). HIPS-transformed images improved intra-thalamic contrast and thalamic boundaries, and HIPS-THOMAS yielded significantly higher mean Dice coefficients and reduced volume errors compared to both the CNN method and T1w-THOMAS. Finally, all three methods were compared using the frequently travelling human phantom MRI dataset for inter- and intra-scanner variability, with HIPS displaying the least inter-scanner variability and performing comparably with T1w-THOMAS for intra-scanner variability. In conclusion, our findings highlight the efficacy and robustness of HIPS in enhancing thalamic nuclei segmentation from standard T1w MRI.
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Nicholson S, Russo AW, Brewer K, Bien H, Tobyne SM, Eloyan A, Klawiter EC. The effect of ibudilast on thalamic volume in progressive multiple sclerosis. Mult Scler 2023; 29:1819-1830. [PMID: 37947294 PMCID: PMC10841081 DOI: 10.1177/13524585231204710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
BACKGROUND Thalamic volume loss is known to be associated with clinical and cognitive disability in progressive multiple sclerosis (PMS). OBJECTIVE To investigate the treatment effect of ibudilast on thalamic atrophy more than 96 weeks in the phase 2 trial in progressive(MS Secondary and Primary Progressive Ibudilast NeuroNEXT Trial in Multiple Sclerosis [SPRINT-MS]). METHODS A total of 231 participants were randomized to either ibudilast (n = 114) or placebo (n = 117). Thalamic volume change was computed using Bayesian Sequence Adaptive Multimodal Segmentation tool (SAMseg) incorporating T1, fluid-attenuated inversion recovery (FLAIR), and fractional anisotropy maps and analyzed with a mixed-effects repeated-measures model. RESULTS There was no significant difference in thalamic volumes between treatment groups. On exploratory analysis, participants with primary progressive multiple sclerosis (PPMS) on placebo had a 0.004% greater rate of thalamic atrophy than PPMS participants on ibudilast (p = 0.058, 95% confidence interval (CI) = -0.008 to <0.001). Greater reductions in thalamic volumes at more than 96 weeks were associated with worsening multiple sclerosis functional composite (MSFC-4) scores (p = 0.002) and worsening performance on the symbol digit modality test (SDMT) (p < 0.001). CONCLUSION In a phase 2 trial evaluating ibudilast in PMS, no treatment effect was demonstrated in preventing thalamic atrophy. Participants with PPMS exhibited a treatment effect that trended toward significance. Longitudinal changes in thalamic volume were related to worsening of physical and cognitive disability, highlighting this outcome's clinical importance.
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Affiliation(s)
- Showly Nicholson
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrew W Russo
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Kristina Brewer
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Heidi Bien
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sean M Tobyne
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ani Eloyan
- Department of Biostatistics, Brown University, Providence, RI, USA
| | - Eric C Klawiter
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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5
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Tregidgo HFJ, Soskic S, Althonayan J, Maffei C, Van Leemput K, Golland P, Insausti R, Lerma-Usabiaga G, Caballero-Gaudes C, Paz-Alonso PM, Yendiki A, Alexander DC, Bocchetta M, Rohrer JD, Iglesias JE. Accurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas. Neuroimage 2023; 274:120129. [PMID: 37088323 PMCID: PMC10636587 DOI: 10.1016/j.neuroimage.2023.120129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 03/30/2023] [Accepted: 04/20/2023] [Indexed: 04/25/2023] Open
Abstract
The human thalamus is a highly connected brain structure, which is key for the control of numerous functions and is involved in several neurological disorders. Recently, neuroimaging studies have increasingly focused on the volume and connectivity of the specific nuclei comprising this structure, rather than looking at the thalamus as a whole. However, accurate identification of cytoarchitectonically designed histological nuclei on standard in vivo structural MRI is hampered by the lack of image contrast that can be used to distinguish nuclei from each other and from surrounding white matter tracts. While diffusion MRI may offer such contrast, it has lower resolution and lacks some boundaries visible in structural imaging. In this work, we present a Bayesian segmentation algorithm for the thalamus. This algorithm combines prior information from a probabilistic atlas with likelihood models for both structural and diffusion MRI, allowing segmentation of 25 thalamic labels per hemisphere informed by both modalities. We present an improved probabilistic atlas, incorporating thalamic nuclei identified from histology and 45 white matter tracts surrounding the thalamus identified in ultra-high gradient strength diffusion imaging. We present a family of likelihood models for diffusion tensor imaging, ensuring compatibility with the vast majority of neuroimaging datasets that include diffusion MRI data. The use of these diffusion likelihood models greatly improves identification of nuclear groups versus segmentation based solely on structural MRI. Dice comparison of 5 manually identifiable groups of nuclei to ground truth segmentations show improvements of up to 10 percentage points. Additionally, our chosen model shows a high degree of reliability, with median test-retest Dice scores above 0.85 for four out of five nuclei groups, whilst also offering improved detection of differential thalamic involvement in Alzheimer's disease (AUROC 81.98%). The probabilistic atlas and segmentation tool will be made publicly available as part of the neuroimaging package FreeSurfer (https://freesurfer.net/fswiki/ThalamicNucleiDTI).
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Affiliation(s)
- Henry F J Tregidgo
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, UK.
| | - Sonja Soskic
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, UK
| | - Juri Althonayan
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, UK
| | - Chiara Maffei
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, USA
| | - Koen Van Leemput
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, USA; Department of Health Technology, Technical University of Denmark, Denmark
| | - Polina Golland
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, USA
| | - Ricardo Insausti
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Spain
| | - Garikoitz Lerma-Usabiaga
- BCBL. Basque Center on Cognition, Brain and Language, Spain; Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | | | - Pedro M Paz-Alonso
- BCBL. Basque Center on Cognition, Brain and Language, Spain; Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Anastasia Yendiki
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, USA
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, UK
| | - Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, UK; Centre for Cognitive and Clinical Neuroscience, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, UK
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, UK; Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, USA
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6
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Okada T, Fujimoto K, Fushimi Y, Akasaka T, Thuy DHD, Shima A, Sawamoto N, Oishi N, Zhang Z, Funaki T, Nakamoto Y, Murai T, Miyamoto S, Takahashi R, Isa T. Neuroimaging at 7 Tesla: a pictorial narrative review. Quant Imaging Med Surg 2022; 12:3406-3435. [PMID: 35655840 PMCID: PMC9131333 DOI: 10.21037/qims-21-969] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/05/2022] [Indexed: 01/26/2024]
Abstract
Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.
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Affiliation(s)
- Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Thai Akasaka
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Dinh H. D. Thuy
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsushi Shima
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Medial Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Funaki
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Diffusion tensor magnetic resonance imaging: is it valuable in the detection of brain microstructural changes in patients having migraine without aura? Pol J Radiol 2021; 86:e548-e556. [PMID: 34820031 PMCID: PMC8607831 DOI: 10.5114/pjr.2021.110645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Accepted: 08/20/2020] [Indexed: 12/21/2022] Open
Abstract
Purpose The aim of this study is to assess the diagnostic value of diffusion tensor magnetic resonance imaging (MRI) in the detection of brain microstructural changes in patients having migraine without aura. Material and methods Our prospective study included 33 patients having migraine without aura and 15 volunteers with matched age and sex, who underwent brain MRI with diffusion tensor imaging (DTI). The fractional anisotropy (FA) and mean diffusivity (MD) of selected grey and white matter regions on both sides were measured and correlated with the neurological clinical examination. Results Significant differences were detected in MD values in the thalamus, globus pallidus, and hippocampus head on the right side of patients versus controls. Also, significant differences of the FA values were detected in the thalamus, globus pallidus, and hippocampus head on the right side of patients versus controls. Regarding the FA values of the same regions on the left side, a significant difference in the FA value was detected only in the hippocampus head. There was a statistically significant difference in the FA values on both sides of the white matter of the frontal lobes, posterior limbs of the internal capsules, and cerebellar hemispheres in patients compared to controls. There was a statistically significant difference in MD values in the white matter of both frontal lobes, posterior limb of the right internal capsule, and both cerebellar hemispheres in patients compared to controls. Conclusions DTI can detect microstructural changes of the grey and white matter in patients having migraine without aura that could not be detected by conventional MRI.
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Saranathan M, Iglehart C, Monti M, Tourdias T, Rutt B. In vivo high-resolution structural MRI-based atlas of human thalamic nuclei. Sci Data 2021; 8:275. [PMID: 34711852 PMCID: PMC8553748 DOI: 10.1038/s41597-021-01062-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 09/21/2021] [Indexed: 12/31/2022] Open
Abstract
Thalamic nuclei play critical roles in regulation of neurological functions like sleep and wakefulness. They are increasingly implicated in neurodegenerative and neurological diseases such as multiple sclerosis and essential tremor. However, segmentation of thalamic nuclei is difficult due to their poor visibility in conventional MRI scans. Sophisticated methods have been proposed which require specialized MRI acquisitions and complex post processing. There are few high spatial resolution (1 mm3 or higher) in vivo MRI thalamic atlases available currently. The goal of this work is the development of an in vivo MRI-based structural thalamic atlas at 0.7 × 0.7 × 0.5 mm resolution based on manual segmentation of 9 healthy subjects using the Morel atlas as a guide. Using data analysis from healthy subjects as well as patients with multiple-sclerosis and essential tremor and at 3T and 7T MRI, we demonstrate the utility of this atlas to provide fast and accurate segmentation of thalamic nuclei when only conventional T1 weighted images are available.
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Affiliation(s)
| | - Charles Iglehart
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA
| | - Martin Monti
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Thomas Tourdias
- Service de Neuroimagerie Diagnostique et Thérapeutique, Université de Bordeaux, Bordeaux, France
| | - Brian Rutt
- Department of Radiology, Stanford University, Palo Alto, CA, USA
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Boelens Keun JT, van Heese EM, Laansma MA, Weeland CJ, de Joode NT, van den Heuvel OA, Gool JK, Kasprzak S, Bright JK, Vriend C, van der Werf YD. Structural assessment of thalamus morphology in brain disorders: A review and recommendation of thalamic nucleus segmentation and shape analysis. Neurosci Biobehav Rev 2021; 131:466-478. [PMID: 34587501 DOI: 10.1016/j.neubiorev.2021.09.044] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 08/25/2021] [Accepted: 09/24/2021] [Indexed: 12/30/2022]
Abstract
The thalamus is a central brain structure crucially involved in cognitive, emotional, sensory, and motor functions and is often reported to be involved in the pathophysiology of neurological and psychiatric disorders. The functional subdivision of the thalamus warrants morphological investigation on the level of individual subnuclei. In addition to volumetric measures, the investigation of other morphological features may give additional insights into thalamic morphology. For instance, shape features offer a higher spatial resolution by revealing small, regional differences that are left undetected in volumetric analyses. In this review, we discuss the benefits and limitations of recent advances in neuroimaging techniques to investigate thalamic morphology in vivo, leading to our proposed methodology. This methodology consists of available pipelines for volume and shape analysis, focussing on the morphological features of volume, thickness, and surface area. We demonstrate this combined approach in a Parkinson's disease cohort to illustrate their complementarity. Considering our findings, we recommend a combined methodology as it allows for more sensitive investigation of thalamic morphology in clinical populations.
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Affiliation(s)
- Jikke T Boelens Keun
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Eva M van Heese
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Max A Laansma
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Cees J Weeland
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Niels T de Joode
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Jari K Gool
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; SEIN, Heemstede, the Netherlands; Department of Neurology, LUMC, Leiden, the Netherlands
| | - Selina Kasprzak
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Joanna K Bright
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Chris Vriend
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Ysbrand D van der Werf
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands.
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Bernstein AS, Rapcsak SZ, Hornberger M, Saranathan M. Structural Changes in Thalamic Nuclei Across Prodromal and Clinical Alzheimer's Disease. J Alzheimers Dis 2021; 82:361-371. [PMID: 34024824 DOI: 10.3233/jad-201583] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Increasing evidence suggests that thalamic nuclei may atrophy in Alzheimer's disease (AD). We hypothesized that there will be significant atrophy of limbic thalamic nuclei associated with declining memory and cognition across the AD continuum. OBJECTIVE The objective of this work was to characterize volume differences in thalamic nuclei in subjects with early and late mild cognitive impairment (MCI) as well as AD when compared to healthy control (HC) subjects using a novel MRI-based thalamic segmentation technique (THOMAS). METHODS MPRAGE data from the ADNI database were used in this study (n = 540). Healthy control (n = 125), early MCI (n = 212), late MCI (n = 114), and AD subjects (n = 89) were selected, and their MRI data were parcellated to determine the volumes of 11 thalamic nuclei for each subject. Volumes across the different clinical subgroups were compared using ANCOVA. RESULTS There were significant differences in thalamic nuclei volumes between HC, late MCI, and AD subjects. The anteroventral, mediodorsal, pulvinar, medial geniculate, and centromedian nuclei were significantly smaller in subjects with late MCI and AD when compared to HC subjects. Furthermore, the mediodorsal, pulvinar, and medial geniculate nuclei were significantly smaller in early MCI when compared to HC subjects. CONCLUSION This work highlights nucleus specific atrophy within the thalamus in subjects with early and late MCI and AD. This is consistent with the hypothesis that memory and cognitive changes in AD are mediated by damage to a large-scale integrated neural network that extends beyond the medial temporal lobes.
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Affiliation(s)
- Adam S Bernstein
- Department of Medical Imaging, University of Arizona, Tuscon, AZ, USA
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Zheng W, Tan X, Liu T, Li X, Gao J, Hong L, Zhang X, Zhao Z, Yu Y, Zhang Y, Luo B, Wu D. Individualized Thalamic Parcellation Reveals Alterations in Shape and Microstructure of Thalamic Nuclei in Patients with Disorder of Consciousness. Cereb Cortex Commun 2021; 2:tgab024. [PMID: 34296169 PMCID: PMC8152869 DOI: 10.1093/texcom/tgab024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/25/2021] [Accepted: 03/28/2021] [Indexed: 12/02/2022] Open
Abstract
The thalamus plays crucial roles in consciousness generation and information processing. Previous evidence suggests that disorder of consciousness (DOC) caused by severe brain injury, is potentially related to thalamic abnormalities. However, how the morphology and microstructure change in thalamic subfields and thalamocortical fiber pathways in patients with DOC, and the relationships between these changes and the consciousness status remain unclear. Here, we generated the individual-specific thalamic parcellation in 10 DOC patients and 10 healthy controls (HC) via a novel thalamic segmentation framework based on the fiber orientation distribution (FOD) derived from 7-Tesla diffusion MRI, and investigated the shape deformation of thalamic nuclei as well as the microstructural changes associated with thalamic nuclei and thalamocortical pathways in patients with DOC. Enlargement of dorsal posterior nucleus and atrophy of anterior nucleus in the right thalamus were observed in DOC cohort relative to the HCs, and the former was closely linked to the consciousness level of the patients. We also found significant reductions of fiber density, but not fiber bundle cross-section, within several thalamic nuclei and most of the thalamocortical fiber pathways, suggesting that loss of axons might take primary responsibility for the impaired thalamocortical connections in patients with DOC rather than the change in fiber-bundle morphology. Furthermore, the individual-specific thalamic parcellation achieved 80% accuracy in classifying patients at the minimally conscious state from the vegetative state, compared with ~60% accuracy based on group-level parcellations. Our findings provide the first evidence for the shape deformation of thalamic nuclei in DOC patients and the microstructural basis of the disrupted thalamocortical connections.
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Affiliation(s)
- Weihao Zheng
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P.R. China
| | - Xufei Tan
- Department of Clinical Medicine, School of Medicine, Zhejiang University City College, Hangzhou, 310015, P.R. China
| | - Tingting Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P.R. China
| | - Xiaoxia Li
- Department of Neurology and Brain Medical Centre, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, P.R. China
| | - Jian Gao
- Department of Rehabilitation, Hospital of Zhejiang Armed Police Corps, Hangzhou, 310051, P.R. China
| | - Lirong Hong
- Department of Rehabilitation, Hospital of Zhejiang Armed Police Corps, Hangzhou, 310051, P.R. China
| | - Xiaotong Zhang
- Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, 310029, P.R. China
| | - Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P.R. China
| | - Yamei Yu
- Department of Neurology and Brain Medical Centre, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, P.R. China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P.R. China
| | - Benyan Luo
- Department of Neurology and Brain Medical Centre, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, P.R. China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P.R. China
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12
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Honnorat N, Saranathan M, Sullivan EV, Pfefferbaum A, Pohl KM, Zahr NM. Performance ramifications of abnormal functional connectivity of ventral posterior lateral thalamus with cerebellum in abstinent individuals with Alcohol Use Disorder. Drug Alcohol Depend 2021; 220:108509. [PMID: 33453503 PMCID: PMC7889734 DOI: 10.1016/j.drugalcdep.2021.108509] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/03/2020] [Accepted: 12/07/2020] [Indexed: 01/06/2023]
Abstract
The extant literature supports the involvement of the thalamus in the cognitive and motor impairment associated with chronic alcohol consumption, but clear structure/function relationships remain elusive. Alcohol effects on specific nuclei rather than the entire thalamus may provide the basis for differential cognitive and motor decline in Alcohol Use Disorder (AUD). This functional MRI (fMRI) study was conducted in 23 abstinent individuals with AUD and 27 healthy controls to test the hypothesis that functional connectivity between anterior thalamus and hippocampus would be compromised in those with an AUD diagnosis and related to mnemonic deficits. Functional connectivity between 7 thalamic structures [5 thalamic nuclei: anterior ventral (AV), mediodorsal (MD), pulvinar (Pul), ventral lateral posterior (VLP), and ventral posterior lateral (VPL); ventral thalamus; the entire thalamus] and 14 "functional regions" was evaluated. Relative to controls, the AUD group exhibited different VPL-based functional connectivity: an anticorrelation between VPL and a bilateral middle temporal lobe region observed in controls became a positive correlation in the AUD group; an anticorrelation between the VPL and the cerebellum was stronger in the AUD than control group. AUD-associated altered connectivity between anterior thalamus and hippocampus as a substrate of memory compromise was not supported; instead, connectivity differences from controls selective to VPL and cerebellum demonstrated a relationship with impaired balance. These preliminary findings support substructure-level evaluation in future studies focused on discerning the role of the thalamus in AUD-associated cognitive and motor deficits.
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Affiliation(s)
- Nicolas Honnorat
- Neuroscience Program, SRI International, 333 Ravenswood Ave., Menlo Park, CA, 94025, USA.
| | - Manojkumar Saranathan
- Department of Medical Imaging, University of Arizona College of Medicine, 1501 N. Campbell Ave., Tucson, AZ, 85724, USA.
| | - Edith V Sullivan
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd., Stanford, CA, 94305, USA.
| | - Adolf Pfefferbaum
- Neuroscience Program, SRI International, 333 Ravenswood Ave., Menlo Park, CA, 94025, USA; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd., Stanford, CA, 94305, USA.
| | - Kilian M Pohl
- Neuroscience Program, SRI International, 333 Ravenswood Ave., Menlo Park, CA, 94025, USA; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd., Stanford, CA, 94305, USA.
| | - Natalie M Zahr
- Neuroscience Program, SRI International, 333 Ravenswood Ave., Menlo Park, CA, 94025, USA; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd., Stanford, CA, 94305, USA.
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13
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Datta R, Bacchus MK, Kumar D, Elliott MA, Rao A, Dolui S, Reddy R, Banwell BL, Saranathan M. Fast automatic segmentation of thalamic nuclei from MP2RAGE acquisition at 7 Tesla. Magn Reson Med 2020; 85:2781-2790. [PMID: 33270943 DOI: 10.1002/mrm.28608] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 09/29/2020] [Accepted: 10/30/2020] [Indexed: 12/26/2022]
Abstract
PURPOSE Thalamic nuclei are largely invisible in conventional MRI due to poor contrast. Thalamus Optimized Multi-Atlas Segmentation (THOMAS) provides automatic segmentation of 12 thalamic nuclei using white-matter-nulled (WMn) Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequence at 7T, but increases overall scan duration. Routinely acquired, bias-corrected Magnetization Prepared 2 Rapid Gradient Echo (MP2RAGE) sequence yields superior tissue contrast and quantitative T1 maps. Application of THOMAS to MP2RAGE has been investigated in this study. METHODS Eight healthy volunteers and five pediatric-onset multiple sclerosis patients were recruited at Children's Hospital of Philadelphia and scanned at Siemens 7T with WMn-MPRAGE and multi-echo-MP2RAGE (ME-MP2RAGE) sequences. White-matter-nulled contrast was synthesized (MP2-SYN) from T1 maps from ME-MP2RAGE sequence. Thalamic nuclei were segmented using THOMAS joint label fusion algorithm from WMn-MPRAGE and MP2-SYN datasets. THOMAS pipeline was modified to use majority voting to segment bias corrected T1-weighted uniform (MP2-UNI) images. Thalamic nuclei from MP2-SYN and MP2-UNI images were evaluated against corresponding nuclei obtained from WMn-MPRAGE images using dice coefficients, volume similarity indices (VSIs) and distance between centroids. RESULTS For MP2-SYN, dice > 0.85 and VSI > 0.95 was achieved for five larger nuclei and dice > 0.6 and VSI > 0.7 was achieved for seven smaller nuclei. The dice and VSI were slightly higher, whereas the distance between centroids were smaller for MP2-SYN compared to MP2-UNI, indicating improved performance using the MP2-SYN image. CONCLUSIONS THOMAS algorithm can successfully segment thalamic nuclei in MP2RAGE images with essentially equivalent quality as WMn-MPRAGE, widening its applicability in studies focused on thalamic involvement in aging and disease.
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Affiliation(s)
- Ritobrato Datta
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Micky K Bacchus
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Dushyant Kumar
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mark A Elliott
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Aditya Rao
- Biological Basis of Behavior Program, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sudipto Dolui
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ravinder Reddy
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Brenda L Banwell
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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14
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Majdi MS, Keerthivasan MB, Rutt BK, Zahr NM, Rodriguez JJ, Saranathan M. Automated thalamic nuclei segmentation using multi-planar cascaded convolutional neural networks. Magn Reson Imaging 2020; 73:45-54. [PMID: 32828985 DOI: 10.1016/j.mri.2020.08.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 07/25/2020] [Accepted: 08/17/2020] [Indexed: 12/15/2022]
Abstract
PURPOSE To develop a fast and accurate convolutional neural network based method for segmentation of thalamic nuclei. METHODS A cascaded multi-planar scheme with a modified residual U-Net architecture was used to segment thalamic nuclei on conventional and white-matter-nulled (WMn) magnetization prepared rapid gradient echo (MPRAGE) data. A single network was optimized to work with images from healthy controls and patients with multiple sclerosis (MS) and essential tremor (ET), acquired at both 3 T and 7 T field strengths. WMn-MPRAGE images were manually delineated by a trained neuroradiologist using the Morel histological atlas as a guide to generate reference ground truth labels. Dice similarity coefficient and volume similarity index (VSI) were used to evaluate performance. Clinical utility was demonstrated by applying this method to study the effect of MS on thalamic nuclei atrophy. RESULTS Segmentation of each thalamus into twelve nuclei was achieved in under a minute. For 7 T WMn-MPRAGE, the proposed method outperforms current state-of-the-art on patients with ET with statistically significant improvements in Dice for five nuclei (increase in the range of 0.05-0.18) and VSI for four nuclei (increase in the range of 0.05-0.19), while performing comparably for healthy and MS subjects. Dice and VSI achieved using 7 T WMn-MPRAGE data are comparable to those using 3 T WMn-MPRAGE data. For conventional MPRAGE, the proposed method shows a statistically significant Dice improvement in the range of 0.14-0.63 over FreeSurfer for all nuclei and disease types. Effect of noise on network performance shows robustness to images with SNR as low as half the baseline SNR. Atrophy of four thalamic nuclei and whole thalamus was observed for MS patients compared to healthy control subjects, after controlling for the effect of parallel imaging, intracranial volume, gender, and age (p < 0.004). CONCLUSION The proposed segmentation method is fast, accurate, performs well across disease types and field strengths, and shows great potential for improving our understanding of thalamic nuclei involvement in neurological diseases.
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Affiliation(s)
- Mohammad S Majdi
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States of America
| | - Mahesh B Keerthivasan
- Department of Medical Imaging, University of Arizona, Tucson, AZ, United States of America; Siemens Healthcare, Tucson, AZ, USA
| | - Brian K Rutt
- Department of Radiology, Stanford University, Stanford, CA, United States of America
| | - Natalie M Zahr
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States of America
| | - Jeffrey J Rodriguez
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States of America
| | - Manojkumar Saranathan
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States of America; Department of Medical Imaging, University of Arizona, Tucson, AZ, United States of America.
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15
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A systematic comparison of structural-, structural connectivity-, and functional connectivity-based thalamus parcellation techniques. Brain Struct Funct 2020; 225:1631-1642. [PMID: 32440784 DOI: 10.1007/s00429-020-02085-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Accepted: 05/09/2020] [Indexed: 12/14/2022]
Abstract
The thalamus consists of several histologically and functionally distinct nuclei increasingly implicated in brain pathology and important for treatment, motivating the need for development of fast and accurate thalamic parcellation. The contrast between thalamic nuclei as well as between the thalamus and surrounding tissues is poor in T1- and T2-weighted magnetic resonance imaging (MRI), inhibiting efforts to date to segment the thalamus using standard clinical MRI. Automatic parcellation techniques have been developed to leverage thalamic features better captured by advanced MRI methods, including magnetization prepared rapid acquisition gradient echo (MP-RAGE), diffusion tensor imaging (DTI), and resting-state functional MRI (fMRI). Despite operating on fundamentally different image contrasts, these methods claim a high degree of agreement with the Morel stereotactic atlas of the thalamus. However, no comparison has been undertaken to compare the results of these disparate parcellation methods. We have implemented state-of-the-art structural-, diffusion-, and functional imaging-based thalamus parcellation techniques and used them on a single set of subjects. We present the first systematic qualitative and quantitative comparison of these methods. The results show that DTI parcellation agrees more with structural parcellation in the larger thalamic nuclei, while rsfMRI parcellation agrees more with structural parcellation in the smaller nuclei. Structural parcellation is the most accurate in the delineation of small structures such as the habenular, antero-ventral, and medial geniculate nuclei.
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16
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Gravbrot N, Saranathan M, Pouratian N, Kasoff W. Advanced Imaging and Direct Targeting of the Motor Thalamus and Dentato-Rubro-Thalamic Tract for Tremor: A Systematic Review. Stereotact Funct Neurosurg 2020; 98:220-240. [DOI: 10.1159/000507030] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 02/27/2020] [Indexed: 11/19/2022]
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17
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Pagnozzi AM, Fripp J, Rose SE. Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies. Neuroimage 2019; 201:116018. [PMID: 31319182 DOI: 10.1016/j.neuroimage.2019.116018] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 07/01/2019] [Accepted: 07/12/2019] [Indexed: 12/13/2022] Open
Abstract
The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.
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Affiliation(s)
- Alex M Pagnozzi
- CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia.
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia
| | - Stephen E Rose
- CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia
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18
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Su JH, Thomas FT, Kasoff WS, Tourdias T, Choi EY, Rutt BK, Saranathan M. Thalamus Optimized Multi Atlas Segmentation (THOMAS): fast, fully automated segmentation of thalamic nuclei from structural MRI. Neuroimage 2019; 194:272-282. [PMID: 30894331 DOI: 10.1016/j.neuroimage.2019.03.021] [Citation(s) in RCA: 108] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 02/10/2019] [Accepted: 03/10/2019] [Indexed: 12/21/2022] Open
Abstract
The thalamus and its nuclei are largely indistinguishable on standard T1 or T2 weighted MRI. While diffusion tensor imaging based methods have been proposed to segment the thalamic nuclei based on the angular orientation of the principal diffusion tensor, these are based on echo planar imaging which is inherently limited in spatial resolution and suffers from distortion. We present a multi-atlas segmentation technique based on white-matter-nulled MP-RAGE imaging that segments the thalamus into 12 nuclei with computation times on the order of 10 min on a desktop PC; we call this method THOMAS (THalamus Optimized Multi Atlas Segmentation). THOMAS was rigorously evaluated on 7T MRI data acquired from healthy volunteers and patients with multiple sclerosis by comparing against manual segmentations delineated by a neuroradiologist, guided by the Morel atlas. Segmentation accuracy was very high, with uniformly high Dice indices: at least 0.85 for large nuclei like the pulvinar and mediodorsal nuclei and at least 0.7 even for small structures such as the habenular, centromedian, and lateral and medial geniculate nuclei. Volume similarity indices ranged from 0.82 for the smaller nuclei to 0.97 for the larger nuclei. Volumetry revealed that the volumes of the right anteroventral, right ventral posterior lateral, and both right and left pulvinar nuclei were significantly lower in MS patients compared to controls, after adjusting for age, sex and intracranial volume. Lastly, we evaluated the potential of this method for targeting the Vim nucleus for deep brain surgery and focused ultrasound thalamotomy by overlaying the Vim nucleus segmented from pre-operative data on post-operative data. The locations of the ablated region and active DBS contact corresponded well with the segmented Vim nucleus. Our fast, direct structural MRI based segmentation method opens the door for MRI guided intra-operative procedures like thalamotomy and asleep DBS electrode placement as well as for accurate quantification of thalamic nuclear volumes to follow progression of neurological disorders.
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Affiliation(s)
- Jason H Su
- Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Francis T Thomas
- Electrical & Computer Engineering, University of Arizona, Tucson, AZ, USA
| | - Willard S Kasoff
- Division of Neurosurgery, University of Arizona, Tucson, AZ, USA
| | - Thomas Tourdias
- Service de Neuroimagerie Diagnostique et Thérapeutique, Université de Bordeaux, Bordeaux, France
| | | | - Brian K Rutt
- Radiology, Stanford University, Stanford, CA, USA
| | - Manojkumar Saranathan
- Electrical & Computer Engineering, University of Arizona, Tucson, AZ, USA; Medical Imaging, University of Arizona, Tucson, AZ, USA.
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19
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Najdenovska E, Tuleasca C, Jorge J, Maeder P, Marques JP, Roine T, Gallichan D, Thiran JP, Levivier M, Bach Cuadra M. Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T. Sci Rep 2019; 9:1119. [PMID: 30718634 PMCID: PMC6361927 DOI: 10.1038/s41598-018-37825-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Accepted: 12/13/2018] [Indexed: 12/22/2022] Open
Abstract
The ventro-intermediate nucleus (Vim), as part of the motor thalamic nuclei, is a commonly used target in functional stereotactic neurosurgery for treatment of drug-resistant tremor. As it cannot be directly visualized on routinely used magnetic resonance imaging (MRI), its clinical targeting is performed using indirect methods. Recent literature suggests that the Vim can be directly visualized on susceptibility-weighted imaging (SWI) acquired at 7 T. Our work aims to assess the distinguishable Vim on 7 T SWI in both healthy-population and patients and, using it as a reference, to compare it with: (1) The clinical targeting, (2) The automated parcellation of thalamic subparts based on 3 T diffusion MRI (dMRI), and (3) The multi-atlas segmentation techniques. In 95.2% of the data, the manual outline was adjacent to the inferior lateral border of the dMRI-based motor-nuclei group, while in 77.8% of the involved cases, its ventral part enclosed the Guiot points. Moreover, the late MRI signature in the patients was always observed in the anterior part of the manual delineation and it overlapped with the multi-atlas outline. Overall, our study provides new insight on Vim discrimination through MRI and imply novel strategies for its automated segmentation, thereby opening new perspectives for standardizing the clinical targeting.
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Affiliation(s)
- Elena Najdenovska
- Centre d'Imagerie BioMédicale (CIBM), University of Lausanne (UNIL), Lausanne, Switzerland. .,Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
| | - Constantin Tuleasca
- Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland.,Sorbonne Université, Faculté de Médecine, Paris, France.,Assistance Publique - Hôpitaux de Paris, Hôpitaux Universitaires Paris-Sud, Hôpital Bicêtre, Service de Neurochirurgie, Le Kremlin Bicêtre, France
| | - João Jorge
- Centre d'Imagerie BioMédicale (CIBM), University of Lausanne (UNIL), Lausanne, Switzerland.,Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Philippe Maeder
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - José P Marques
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Timo Roine
- Centre d'Imagerie BioMédicale (CIBM), University of Lausanne (UNIL), Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Turku Brain and Mind Center, University of Turku, Turku, Finland
| | - Daniel Gallichan
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Marc Levivier
- Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland
| | - Meritxell Bach Cuadra
- Centre d'Imagerie BioMédicale (CIBM), University of Lausanne (UNIL), Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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20
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Iglesias JE, Insausti R, Lerma-Usabiaga G, Bocchetta M, Van Leemput K, Greve DN, van der Kouwe A, Fischl B, Caballero-Gaudes C, Paz-Alonso PM. A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology. Neuroimage 2018; 183:314-326. [PMID: 30121337 PMCID: PMC6215335 DOI: 10.1016/j.neuroimage.2018.08.012] [Citation(s) in RCA: 296] [Impact Index Per Article: 49.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 07/27/2018] [Accepted: 08/09/2018] [Indexed: 01/18/2023] Open
Abstract
The human thalamus is a brain structure that comprises numerous, highly specific nuclei. Since these nuclei are known to have different functions and to be connected to different areas of the cerebral cortex, it is of great interest for the neuroimaging community to study their volume, shape and connectivity in vivo with MRI. In this study, we present a probabilistic atlas of the thalamic nuclei built using ex vivo brain MRI scans and histological data, as well as the application of the atlas to in vivo MRI segmentation. The atlas was built using manual delineation of 26 thalamic nuclei on the serial histology of 12 whole thalami from six autopsy samples, combined with manual segmentations of the whole thalamus and surrounding structures (caudate, putamen, hippocampus, etc.) made on in vivo brain MR data from 39 subjects. The 3D structure of the histological data and corresponding manual segmentations was recovered using the ex vivo MRI as reference frame, and stacks of blockface photographs acquired during the sectioning as intermediate target. The atlas, which was encoded as an adaptive tetrahedral mesh, shows a good agreement with previous histological studies of the thalamus in terms of volumes of representative nuclei. When applied to segmentation of in vivo scans using Bayesian inference, the atlas shows excellent test-retest reliability, robustness to changes in input MRI contrast, and ability to detect differential thalamic effects in subjects with Alzheimer's disease. The probabilistic atlas and companion segmentation tool are publicly available as part of the neuroimaging package FreeSurfer.
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Affiliation(s)
- Juan Eugenio Iglesias
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom; BCBL. Basque Center on Cognition, Brain and Language, Spain.
| | - Ricardo Insausti
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Spain
| | | | - Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, Institute of Neurology, University College London, United Kingdom
| | - Koen Van Leemput
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, USA; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark
| | - Douglas N Greve
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, USA
| | - Andre van der Kouwe
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, USA
| | - Bruce Fischl
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, USA; MIT Computer Science and Artificial Intelligence Laboratory, USA
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Najdenovska E, Alemán-Gómez Y, Battistella G, Descoteaux M, Hagmann P, Jacquemont S, Maeder P, Thiran JP, Fornari E, Bach Cuadra M. In-vivo probabilistic atlas of human thalamic nuclei based on diffusion- weighted magnetic resonance imaging. Sci Data 2018; 5:180270. [PMID: 30480664 PMCID: PMC6257045 DOI: 10.1038/sdata.2018.270] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Accepted: 10/12/2018] [Indexed: 11/23/2022] Open
Abstract
The thalamic nuclei are involved in many neurodegenerative diseases and therefore, their identification is of key importance in numerous clinical treatments. Automated segmentation of thalamic subparts is currently achieved by exploring diffusion-weighted magnetic resonance imaging (DW-MRI), but in absence of such data, atlas-based segmentation can be used as an alternative. Currently, there is a limited number of available digital atlases of the thalamus. Moreover, all atlases are created using a few subjects only, thus are prone to errors due to the inter-subject variability of the thalamic morphology. In this work, we present a probabilistic atlas of anatomical subparts of the thalamus built upon a relatively large dataset where the individual thalamic parcellation was done by employing a recently proposed automatic diffusion-based clustering method. Our analyses, comparing the segmentation performance between the atlas-based and the clustering method, demonstrate the ability of the provided atlas to substitute the automated diffusion-based subdivision in the individual space when the DW-MRI is not available.
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Affiliation(s)
- Elena Najdenovska
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Centre d’Imagerie BioMédicale (CIBM), Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Yasser Alemán-Gómez
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Centre d’Imagerie BioMédicale (CIBM), Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Service of General Psychiatry, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Giovanni Battistella
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, USA
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Universite de Sherbrooke, Sherbrooke, Canada
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Sebastien Jacquemont
- Department of Pediatrics, University Hospital Center Sainte-Justine, Montreal H3T 1C5, Canada
| | - Philippe Maeder
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Eleonora Fornari
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Centre d’Imagerie BioMédicale (CIBM), Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Meritxell Bach Cuadra
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Centre d’Imagerie BioMédicale (CIBM), Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Tuleasca C, Najdenovska E, Régis J, Witjas T, Girard N, Champoudry J, Faouzi M, Thiran JP, Cuadra MB, Levivier M, Van De Ville D. Pretherapeutic Motor Thalamus Resting-State Functional Connectivity with Visual Areas Predicts Tremor Arrest After Thalamotomy for Essential Tremor: Tracing the Cerebello-thalamo-visuo-motor Network. World Neurosurg 2018; 117:e438-e449. [DOI: 10.1016/j.wneu.2018.06.049] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 06/06/2018] [Accepted: 06/08/2018] [Indexed: 11/17/2022]
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Human Motor Thalamus Reconstructed in 3D from Continuous Sagittal Sections with Identified Subcortical Afferent Territories. eNeuro 2018; 5:eN-NWR-0060-18. [PMID: 30023427 PMCID: PMC6049607 DOI: 10.1523/eneuro.0060-18.2018] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Revised: 04/02/2018] [Accepted: 05/03/2018] [Indexed: 11/21/2022] Open
Abstract
Classification and delineation of the motor-related nuclei in the human thalamus have been the focus of numerous discussions for a long time. Difficulties in finding consensus have for the most part been caused by paucity of direct experimental data on connections of individual nuclear entities. Kultas-Ilinsky et al. (2011) showed that distribution of glutamic acid decarboxylase isoform 65 (GAD65), the enzyme that synthesizes inhibitory neurotransmitter γ-aminobutyric acid, is a reliable marker that allows to delineate connectionally distinct nuclei in the human motor thalamus, namely the territories innervated by nigral, pallidal, and cerebellar afferents. We compared those immunocytochemical staining patterns with underlying cytoarchitecture and used the latter to outline the three afferent territories in a continuous series of sagittal Nissl-stained sections of the human thalamus. The 3D volume reconstructed from the outlines was placed in the Talairach stereotactic coordinate system relative to the intercommissural line and sectioned in three stereotactic planes to produce color-coded nuclear maps. This 3D coordinate-based atlas was coregistered to the Montreal Neurological Institute (MNI-152) space. The current report proposes a simplified nomenclature of the motor-related thalamic nuclei, presents images of selected histological sections and stereotactic maps illustrating topographic relationships of these nuclei as well as their relationship with adjacent somatosensory afferent region. The data are useful in different applications such as functional MRI and diffusion tractography. The 3D dataset is publicly available under an open license and can also be applicable in clinical interventions in the thalamus.
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Tuleasca C, Najdenovska E, Régis J, Witjas T, Girard N, Champoudry J, Faouzi M, Thiran JP, Cuadra MB, Levivier M, Van De Ville D. Ventrolateral Motor Thalamus Abnormal Connectivity in Essential Tremor Before and After Thalamotomy: A Resting-State Functional Magnetic Resonance Imaging Study. World Neurosurg 2018; 113:e453-e464. [DOI: 10.1016/j.wneu.2018.02.055] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 02/08/2018] [Accepted: 02/09/2018] [Indexed: 01/30/2023]
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Zhang S, Li CSR. Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis. Brain Connect 2017; 7:602-616. [PMID: 28954523 PMCID: PMC5695755 DOI: 10.1089/brain.2017.0500] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10-6, corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.
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Affiliation(s)
- Sheng Zhang
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Chiang-Shan R. Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
- Department of Neuroscience, Yale University School of Medicine, New Haven, Connecticut
- Interdepartmental Neuroscience Program, Yale University, New Haven, Connecticut
- Beijing Huilongguan Hospital, Beijing, China
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Kumar VJ, van Oort E, Scheffler K, Beckmann CF, Grodd W. Functional anatomy of the human thalamus at rest. Neuroimage 2017; 147:678-691. [DOI: 10.1016/j.neuroimage.2016.12.071] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 12/21/2016] [Accepted: 12/22/2016] [Indexed: 12/25/2022] Open
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Robust thalamic nuclei segmentation method based on local diffusion magnetic resonance properties. Brain Struct Funct 2016; 222:2203-2216. [PMID: 27888345 PMCID: PMC5504280 DOI: 10.1007/s00429-016-1336-4] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2016] [Accepted: 11/09/2016] [Indexed: 12/11/2022]
Abstract
The thalamus is an essential relay station in the cortical–subcortical connections. It is characterized by a complex anatomical architecture composed of numerous small nuclei, which mediate the involvement of the thalamus in a wide range of neurological functions. We present a novel framework for segmenting the thalamic nuclei, which explores the orientation distribution functions (ODFs) from diffusion magnetic resonance images at 3 T. The differentiation of the complex intra-thalamic microstructure is improved by using the spherical harmonic (SH) representation of the ODFs, which provides full angular characterization of the diffusion process in each voxel. The clustering was performed using the k-means algorithm initialized in a data-driven manner. The method was tested on 35 healthy volunteers and our results show a robust, reproducible and accurate segmentation of the thalamus in seven nuclei groups. Six of them closely matched the anatomy and were labeled as anterior, ventral anterior, medio-dorsal, ventral latero-ventral, ventral latero-dorsal and pulvinar, while the seventh cluster included the centro-lateral and the latero-posterior nuclei. Results were evaluated both qualitatively, by comparing the segmented nuclei to the histological atlas of Morel, and quantitatively, by measuring the clusters’ extent and the clusters’ spatial distribution across subjects and hemispheres. We also showed the robustness of our approach across different sequences and scanners, as well as intra-subject reproducibility of the segmented clusters using additional two scan–rescan datasets. We also observed an overlap between the path of the main long-connection tracts passing through the thalamus and the spatial distribution of the nuclei identified with our clustering algorithm. Our approach, based on SH representations of the ODFs, outperforms the one based on angular differences between the principle diffusion directions, which is considered so far as state-of-the-art method. Our findings show an anatomically reliable segmentation of the main groups of thalamic nuclei that could be of potential use in many clinical applications.
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Wu C, D'Haese PF, Pallavaram S, Dawant BM, Konrad P, Sharan AD. Variations in Thalamic Anatomy Affect Targeting in Deep Brain Stimulation for Epilepsy. Stereotact Funct Neurosurg 2016; 94:387-396. [PMID: 27846633 DOI: 10.1159/000449009] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Accepted: 08/08/2016] [Indexed: 11/19/2022]
Abstract
BACKGROUND Thalamic size and shape vary significantly across patients - with changes specific to the anterior thalamus occurring with age and in the setting of chronic epilepsy. Such ambiguity raises concerns regarding electrode position and potential implications for seizure outcomes. METHODS MRIs from 6 patients from a single center underwent quantitative analysis. In addition to direct measurements from postimplantation MRIs, the CRAnialVault Explorer suite was used to normalize electrode position to a common reference system. Relationships between thalamic dimensions, electrode location, and seizure outcome were analyzed. RESULTS Although this study group was too small to sufficiently power statistical analysis, general trends were identified. There was a trend towards smaller thalamic volumes in nonresponders. Electrode locations demonstrated more variation after normalization. There was a trend towards a more lateral, posterior, and inferior electrode position in nonresponders. CONCLUSIONS Variations in thalamic shape and volume necessitate direct targeting. Given that changes occur to thalamic anatomy with age and in the setting of epilepsy, improved methods for visualizing and targeting the anterior nucleus are necessary. Pronounced thalamic atrophy may preclude proper electrode placement and serve as a poor prognostic indicator. A greater understanding of thalamic anatomy and connectivity is necessary to optimize deep brain stimulation for epilepsy.
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Affiliation(s)
- Chengyuan Wu
- Division of Epilepsy and Neuromodulation Neurosurgery, Department of Neurosurgery, Thomas Jefferson University, Philadelphia, Pa., USA
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Lambert C, Simon H, Colman J, Barrick TR. Defining thalamic nuclei and topographic connectivity gradients in vivo. Neuroimage 2016; 158:466-479. [PMID: 27639355 DOI: 10.1016/j.neuroimage.2016.08.028] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2016] [Revised: 08/12/2016] [Accepted: 08/14/2016] [Indexed: 10/21/2022] Open
Abstract
The thalamus consists of multiple nuclei that have been previously defined by their chemoarchitectual and cytoarchitectual properties ex vivo. These form discrete, functionally specialized, territories with topographically arranged graduated patterns of connectivity. However, previous in vivo thalamic parcellation with MRI has been hindered by substantial inter-individual variability or discrepancies between MRI derived segmentations and histological sections. Here, we use the Euclidean distance to characterize probabilistic tractography distributions derived from diffusion MRI. We generate 12 feature maps by performing voxel-wise parameterization of the distance histograms (6 feature maps) and the distribution of three-dimensional distance transition gradients generated by applying a Sobel kernel to the distance metrics. We use these 12 feature maps to delineate individual thalamic nuclei, then extract the tractography profiles for each and calculate the voxel-wise tractography gradients. Within each thalamic nucleus, the tractography gradients were topographically arranged as distinct non-overlapping cortical networks with transitory overlapping mid-zones. This work significantly advances quantitative segmentation of the thalamus in vivo using 3T MRI. At an individual subject level, the thalamic segmentations consistently achieve a close relationship with a priori histological atlas information, and resolve in vivo topographic gradients within each thalamic nucleus for the first time. Additionally, these techniques allow individual thalamic nuclei to be closely aligned across large populations and generate measures of inter-individual variability that can be used to study both basic function and pathological processes in vivo.
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Affiliation(s)
- Christian Lambert
- Neurosciences Research Centre, Cardiac and Cell Sciences Research Institute, St George's University of London, United Kingdom.
| | - Henry Simon
- Neurosciences Research Centre, Cardiac and Cell Sciences Research Institute, St George's University of London, United Kingdom
| | - Jordan Colman
- Neurosciences Research Centre, Cardiac and Cell Sciences Research Institute, St George's University of London, United Kingdom
| | - Thomas R Barrick
- Neurosciences Research Centre, Cardiac and Cell Sciences Research Institute, St George's University of London, United Kingdom
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Disrupted Working Memory Circuitry in Schizophrenia: Disentangling fMRI Markers of Core Pathology vs Other Aspects of Impaired Performance. Neuropsychopharmacology 2016; 41:2411-20. [PMID: 27103065 PMCID: PMC4946071 DOI: 10.1038/npp.2016.55] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2015] [Revised: 03/03/2016] [Accepted: 04/07/2016] [Indexed: 11/08/2022]
Abstract
Working memory (WM) impairment, a core feature of schizophrenia, is often associated with aberrant dorsolateral prefrontal cortex (dlPFC) activation. Reduced resting-state connectivity within the frontoparietal control network (FPCN) has also been reported in schizophrenia. However, interpretation of WM-related dlPFC dysfunction has been limited by performance differences between patients and controls, and by uncertainty over the relevance of resting-state connectivity to network engagement during task. We contrasted brain activation in 40 schizophrenia patients and 40 controls during verbal WM performance, and evaluated underlying functional connectivity during rest and task. During correct trials, patients demonstrated normal FPCN activation, despite an inverse relationship between positive symptoms and activation. FPCN activation differed between the groups only during error trials (controls>patients). In contrast, controls demonstrated stronger deactivation of the ventromedial prefrontal cortex (vmPFC) during correct and error trials. Functional connectivity analysis indicated impaired resting-state FPCN connectivity in patients, but normal connectivity during task. However, patients showed abnormal connectivity among regions such as vmPFC, lateral orbitofrontal cortex, and parahippocampal gyrus (PHG) during both rest and task. During task, patients also exhibited altered thalamic connectivity to PHG and FPCN. Activation and connectivity patterns that were more characteristic of controls generally correlated with better performance. In summary, patients demonstrated normal FPCN activation when they remained on-task, and exhibited normal FPCN connectivity during WM, whereas vmPFC deactivation differences persisted regardless of WM performance. Our findings suggest that altered FPCN activation in patients reflects performance difference, and that limbic and thalamic dysfunction is critically involved in WM deficits in schizophrenia.
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Renauld E, Descoteaux M, Bernier M, Garyfallidis E, Whittingstall K. Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves. PLoS One 2016; 11:e0156436. [PMID: 27383146 PMCID: PMC4934857 DOI: 10.1371/journal.pone.0156436] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2016] [Accepted: 05/13/2016] [Indexed: 12/13/2022] Open
Abstract
At rest, healthy human brain activity is characterized by large electroencephalography (EEG) fluctuations in the 8-13 Hz range, commonly referred to as the alpha band. Although it is well known that EEG alpha activity varies across individuals, few studies have investigated how this may be related to underlying morphological variations in brain structure. Specifically, it is generally believed that the lateral geniculate nucleus (LGN) and its efferent fibres (optic radiation, OR) play a key role in alpha activity, yet it is unclear whether their shape or size variations contribute to its inter-subject variability. Given the widespread use of EEG alpha in basic and clinical research, addressing this is important, though difficult given the problems associated with reliably segmenting the LGN and OR. For this, we employed a multi-modal approach and combined diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI) and EEG in 20 healthy subjects to measure structure and function, respectively. For the former, we developed a new, semi-automated approach for segmenting the OR and LGN, from which we extracted several structural metrics such as volume, position and diffusivity. Although these measures corresponded well with known morphology based on previous post-mortem studies, we nonetheless found that their inter-subject variability was not significantly correlated to alpha power or peak frequency (p >0.05). Our results therefore suggest that alpha variability may be mediated by an alternative structural source and our proposed methodology may in general help in better understanding the influence of anatomy on function such as measured by EEG or fMRI.
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Affiliation(s)
- Emmanuelle Renauld
- Department of Nuclear Medecine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke, Sherbrooke, Qc, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Faculty of Science, University of Sherbrooke, Sherbrooke, Qc, Canada
- Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, Qc, Canada
- Centre d’Imagerie Moléculaire de Sherbrooke (CIMS), Centre de Recherche du CHUS, Sherbrooke, Qc, Canada
| | - Michaël Bernier
- Department of Nuclear Medecine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke, Sherbrooke, Qc, Canada
| | - Eleftherios Garyfallidis
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Faculty of Science, University of Sherbrooke, Sherbrooke, Qc, Canada
| | - Kevin Whittingstall
- Department of Nuclear Medecine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke, Sherbrooke, Qc, Canada
- Department of Diagnostic Radiology, Faculty of Medicine and Health Science, University of Sherbrooke, Sherbrooke, Qc, Canada
- Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, Qc, Canada
- Centre d’Imagerie Moléculaire de Sherbrooke (CIMS), Centre de Recherche du CHUS, Sherbrooke, Qc, Canada
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32
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Kumar V, Mang S, Grodd W. Direct diffusion-based parcellation of the human thalamus. Brain Struct Funct 2016; 220:1619-35. [PMID: 24659254 DOI: 10.1007/s00429-014-0748-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Accepted: 02/07/2014] [Indexed: 01/10/2023]
Abstract
To assess stable anatomical features of the human thalamus, an unbiased diffusion tensor parcellation approach was used to segment thalamic substructures with similar spatial orientation. We determined localization, size and individual variations of 21 thalamic clusters in a group of 63 healthy human subjects (32 males/31 females). The laterality differences accounted for ± 6% and gender differences for ± 4% of the thalamic volume. Consecutively, five stable clusters in the anterior, medial, lateral and posterior thalamus were selected, which were common to 90% of all subjects and contained at least 10 voxels. These clusters could be assigned to the anteroventral nucleus (AN) group, the mediodorsal (MD) nucleus, the medial pulvinar (PuM), and the lateral nuclei group. The subcortical and cortical connectivity of these clusters revealed that: (1) the oblique cranio-caudal-oriented fibers of the AN cluster mainly connect to limbic structures, (2) the numerous dorso-frontal-oriented fibers of MD mainly project to the prefrontal cortex and the medial temporal lobe, (3) the fibers of the PuM running in parallel with the x-axis project to medio-occipital and medio-temporal areas and connect visual areas with the hippocampus and amygdala and via intrathalamic pathways with medio-frontal areas, and (4) the oblique caudo-cranial fibers of the two lateral clusters located anteriorly in the motor and posteriorly in the sensory thalamus are routing sensory-motor information from the brain stem via the internal capsule to pre- and peri-central regions of the cortex.
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33
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Palesi F, Tournier JD, Calamante F, Muhlert N, Castellazzi G, Chard D, D'Angelo E, Wheeler-Kingshott CAM. Contralateral cerebello-thalamo-cortical pathways with prominent involvement of associative areas in humans in vivo. Brain Struct Funct 2015; 220:3369-84. [PMID: 25134682 PMCID: PMC4575696 DOI: 10.1007/s00429-014-0861-2] [Citation(s) in RCA: 120] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2014] [Accepted: 07/21/2014] [Indexed: 12/26/2022]
Abstract
In addition to motor functions, it has become clear that in humans the cerebellum plays a significant role in cognition too, through connections with associative areas in the cerebral cortex. Classical anatomy indicates that neo-cerebellar regions are connected with the contralateral cerebral cortex through the dentate nucleus, superior cerebellar peduncle, red nucleus and ventrolateral anterior nucleus of the thalamus. The anatomical existence of these connections has been demonstrated using virus retrograde transport techniques in monkeys and rats ex vivo. In this study, using advanced diffusion MRI tractography we show that it is possible to calculate streamlines to reconstruct the pathway connecting the cerebellar cortex with contralateral cerebral cortex in humans in vivo. Corresponding areas of the cerebellar and cerebral cortex encompassed similar proportion (about 80%) of the tract, suggesting that the majority of streamlines passing through the superior cerebellar peduncle connect the cerebellar hemispheres through the ventrolateral thalamus with contralateral associative areas. This result demonstrates that this kind of tractography is a useful tool to map connections between the cerebellum and the cerebral cortex and moreover could be used to support specific theories about the abnormal communication along these pathways in cognitive dysfunctions in pathologies ranging from dyslexia to autism.
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Affiliation(s)
- Fulvia Palesi
- Department of Physics, University of Pavia, Via Bassi 6, 27100, Pavia, Italy.
- Brain Connectivity Center, C. Mondino National Neurological Institute, Via Mondino 2, 27100, Pavia, Italy.
| | - Jacques-Donald Tournier
- The Florey Institute of Neuroscience and Mental Health, Melbourne Brain Centre, 245 Burgundy Street, Heidelberg, VIC, 3084, Australia.
- Department of Medicine, Austin Health and Northern Health, University of Melbourne, Studley Road, Heidelberg, Australia.
| | - Fernando Calamante
- The Florey Institute of Neuroscience and Mental Health, Melbourne Brain Centre, 245 Burgundy Street, Heidelberg, VIC, 3084, Australia.
- Department of Medicine, Austin Health and Northern Health, University of Melbourne, Studley Road, Heidelberg, Australia.
| | - Nils Muhlert
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK.
- Department of Psychology, Cardiff University, Cardiff, CF10 2AT, UK.
| | - Gloria Castellazzi
- Brain Connectivity Center, C. Mondino National Neurological Institute, Via Mondino 2, 27100, Pavia, Italy.
- Department of Industrial and Information Engineering, University of Pavia, Via Ferrata 1, 27100, Pavia, Italy.
| | - Declan Chard
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK.
- National Institute for Health Research, University College London Hospitals Biomedical Research Centre, 149 Tottenham Court Road, London, W1T 7DN, UK.
| | - Egidio D'Angelo
- Brain Connectivity Center, C. Mondino National Neurological Institute, Via Mondino 2, 27100, Pavia, Italy.
- Department of Brain and Behavioural Sciences, University of Pavia, Via Forlanini 6, 27100, Pavia, Italy.
| | - Claudia A M Wheeler-Kingshott
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK.
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34
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Beukema P, Yeh FC, Verstynen T. In vivo characterization of the connectivity and subcomponents of the human globus pallidus. Neuroimage 2015. [PMID: 26196668 DOI: 10.1016/j.neuroimage.2015.07.031] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Projections from the substantia nigra and striatum traverse through the pallidum on the way to their targets. To date, in vivo characterization of these pathways remains elusive. Here we used high angular resolution diffusion imaging (N=138) to study the characteristics and structural subcompartments of the human pallidum. Our central result shows that the diffusion orientation distribution functions within the pallidum are asymmetrically oriented in a dorsal to dorsolateral direction, consistent with the orientation of underlying fiber systems. We also observed systematic differences in the diffusion signal between the two pallidal segments. Compared to the outer pallidal segment, the internal segment has more peaks in the diffusion orientation distribution and stronger anisotropy in the primary fiber direction, consistent with known cellular differences between the underlying nuclei. These differences in orientation, complexity, and degree of anisotropy are sufficiently robust to automatically segment the pallidal nuclei using diffusion properties. We characterize these patterns in one data set using diffusion spectrum imaging and replicate in a separate sample of subjects imaged using multi-shell imaging, highlighting the reliability of these diffusion patterns within pallidal nuclei. Thus the gray matter diffusion signal can be useful as an in vivo measure of the collective efferent pathways running through the human pallidum.
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Affiliation(s)
- Patrick Beukema
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA 15260, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA 15213, United States
| | - Fang-Cheng Yeh
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA 15213, United States
| | - Timothy Verstynen
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA 15213, United States.
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Plantinga BR, Temel Y, Roebroeck A, Uludağ K, Ivanov D, Kuijf ML, Ter Haar Romenij BM. Ultra-high field magnetic resonance imaging of the basal ganglia and related structures. Front Hum Neurosci 2014; 8:876. [PMID: 25414656 PMCID: PMC4220687 DOI: 10.3389/fnhum.2014.00876] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2014] [Accepted: 10/10/2014] [Indexed: 12/13/2022] Open
Abstract
Deep brain stimulation is a treatment for Parkinson's disease and other related disorders, involving the surgical placement of electrodes in the deeply situated basal ganglia or thalamic structures. Good clinical outcome requires accurate targeting. However, due to limited visibility of the target structures on routine clinical MR images, direct targeting of structures can be challenging. Non-clinical MR scanners with ultra-high magnetic field (7T or higher) have the potential to improve the quality of these images. This technology report provides an overview of the current possibilities of visualizing deep brain stimulation targets and their related structures with the aid of ultra-high field MRI. Reviewed studies showed improved resolution, contrast- and signal-to-noise ratios at ultra-high field. Sequences sensitive to magnetic susceptibility such as T2* and susceptibility weighted imaging and their maps in general showed the best visualization of target structures, including a separation between the subthalamic nucleus and the substantia nigra, the lamina pallidi medialis and lamina pallidi incompleta within the globus pallidus and substructures of the thalamus, including the ventral intermediate nucleus (Vim). This shows that the visibility, identification, and even subdivision of the small deep brain stimulation targets benefit from increased field strength. Although ultra-high field MR imaging is associated with increased risk of geometrical distortions, it has been shown that these distortions can be avoided or corrected to the extent where the effects are limited. The availability of ultra-high field MR scanners for humans seems to provide opportunities for a more accurate targeting for deep brain stimulation in patients with Parkinson's disease and related disorders.
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Affiliation(s)
- Birgit R Plantinga
- Biomedical Image Analysis, Eindhoven University of Technology Eindhoven, Netherlands ; Department of Neuroscience, Maastricht University Maastricht, Netherlands
| | - Yasin Temel
- Department of Neuroscience, Maastricht University Maastricht, Netherlands ; Department of Neurology, Maastricht University Medical Center Maastricht, Netherlands
| | - Alard Roebroeck
- Department of Neurosurgery, Maastricht University Medical Center Maastricht, Netherlands
| | - Kâmil Uludağ
- Department of Neurosurgery, Maastricht University Medical Center Maastricht, Netherlands
| | - Dimo Ivanov
- Department of Neurosurgery, Maastricht University Medical Center Maastricht, Netherlands
| | - Mark L Kuijf
- Department of Cognitive Neuroscience, Maastricht University Maastricht, Netherlands
| | - Bart M Ter Haar Romenij
- Biomedical Image Analysis, Eindhoven University of Technology Eindhoven, Netherlands ; Department of Biomedical and Information Engineering, Northeastern University Shenyang, China
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Kong Y, Wang D, Shi L, Hui SCN, Chu WCW. Adaptive distance metric learning for diffusion tensor image segmentation. PLoS One 2014; 9:e92069. [PMID: 24651858 PMCID: PMC3961296 DOI: 10.1371/journal.pone.0092069] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2013] [Accepted: 02/17/2014] [Indexed: 11/23/2022] Open
Abstract
High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.
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Affiliation(s)
- Youyong Kong
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Defeng Wang
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- The Chinese University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- Department of Biomedical Engineering and Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- * E-mail: (DW); (WCWC)
| | - Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Steve C. N. Hui
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Winnie C. W. Chu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- The Chinese University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- * E-mail: (DW); (WCWC)
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Coppola G, Tinelli E, Lepre C, Iacovelli E, Di Lorenzo C, Di Lorenzo G, Serrao M, Pauri F, Fiermonte G, Bianco F, Pierelli F. Dynamic changes in thalamic microstructure of migraine without aura patients: a diffusion tensor magnetic resonance imaging study. Eur J Neurol 2013; 21:287-e13. [DOI: 10.1111/ene.12296] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2013] [Accepted: 09/23/2013] [Indexed: 12/12/2022]
Affiliation(s)
- G. Coppola
- Department of Neurophysiology of Vision and Neurophthalmology; G.B. Bietti Foundation IRCCS; Rome Italy
| | - E. Tinelli
- Neuroradiology Section; Department of Neurology and Psychiatry; ‘Sapienza’ University of Rome; Rome Italy
| | - C. Lepre
- Neurology Section; Department of Medico-Surgical Sciences and Biotechnologies; ‘Sapienza’ University of Rome; Rome Italy
| | - E. Iacovelli
- Neurology Section; Department of Medico-Surgical Sciences and Biotechnologies; ‘Sapienza’ University of Rome; Rome Italy
| | | | - G. Di Lorenzo
- Laboratory of Psychophysiology; Psychiatric Clinic; Department of Systems Medicine; University of Rome ‘Tor Vergata’; Rome Italy
| | - M. Serrao
- Department of Medico-Surgical Sciences and Biotechnologies; ‘Sapienza’ University of Rome Polo Pontino; Latina Italy
| | - F. Pauri
- Neurology Section; Department of Medico-Surgical Sciences and Biotechnologies; ‘Sapienza’ University of Rome; Rome Italy
| | - G. Fiermonte
- Neurology Section; Department of Medico-Surgical Sciences and Biotechnologies; ‘Sapienza’ University of Rome; Rome Italy
| | - F. Bianco
- Neurology Section; Department of Medico-Surgical Sciences and Biotechnologies; ‘Sapienza’ University of Rome; Rome Italy
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Tourdias T, Saranathan M, Levesque IR, Su J, Rutt BK. Visualization of intra-thalamic nuclei with optimized white-matter-nulled MPRAGE at 7T. Neuroimage 2013; 84:534-45. [PMID: 24018302 DOI: 10.1016/j.neuroimage.2013.08.069] [Citation(s) in RCA: 92] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2013] [Revised: 07/27/2013] [Accepted: 08/29/2013] [Indexed: 12/01/2022] Open
Abstract
Novel MR image acquisition strategies have been investigated to elicit contrast within the thalamus, but direct visualization of individual thalamic nuclei remains a challenge because of their small size and the low intrinsic contrast between adjacent nuclei. We present a step-by-step specific optimization of the 3D MPRAGE pulse sequence at 7T to visualize the intra-thalamic nuclei. We first measured T1 values within different sub-regions of the thalamus at 7T in 5 individuals. We used these to perform simulations and sequential experimental measurements (n=17) to tune the parameters of the MPRAGE sequence. The optimal set of parameters was used to collect high-quality data in 6 additional volunteers. Delineation of thalamic nuclei was performed twice by one rater and MR-defined nuclei were compared to the classic Morel histological atlas. T1 values within the thalamus ranged from 1400ms to 1800ms for adjacent nuclei. Using these values for theoretical evaluations combined with in vivo measurements, we showed that a short inversion time (TI) close to the white matter null regime (TI=670ms) enhanced the contrast between the thalamus and the surrounding tissues, and best revealed intra-thalamic contrast. At this particular nulling regime, lengthening the time between successive inversion pulses (TS=6000ms) increased the thalamic signal and contrast and lengthening the α pulse train time (N*TR) further increased the thalamic signal. Finally, a low flip angle during the gradient echo acquisition (α=4°) was observed to mitigate the blur induced by the evolution of the magnetization along the α pulse train. This optimized set of parameters enabled the 3D delineation of 15 substructures in all 6 individuals; these substructures corresponded well with the known anatomical structures of the thalamus based on the classic Morel atlas. The mean Euclidean distance between the centers of mass of MR- and Morel atlas-defined nuclei was 2.67mm (±1.02mm). The reproducibility of the MR-defined nuclei was excellent with intraclass correlation coefficient measured at 0.997 and a mean Euclidean distance between corresponding centers of mass found at first versus second readings of 0.69mm (±0.38mm). This 7T strategy paves the way to better identification of thalamic nuclei for neurosurgical planning and investigation of regional changes in neurological disorders.
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Affiliation(s)
- Thomas Tourdias
- Richard M. Lucas Center for Imaging, Radiology Department, Stanford University, 1201 Welch Road, Stanford, CA 94305-5488, USA.
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