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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: 5] [Impact Index Per Article: 2.5] [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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Raghu ALB, Martin SC, Parker T, Aziz TZ, Green AL. Connectivity-based thalamus parcellation and surgical targeting of somatosensory subnuclei. J Neurosurg 2022; 137:209-216. [PMID: 34798607 DOI: 10.3171/2021.7.jns211140] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 07/12/2021] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The anatomy of the posterolateral thalamus varies substantially between individuals, presenting a challenge for surgical targeting. Patient-specific, connectivity-based parcellation of the thalamus may effectively approximate the ventrocaudal nucleus (Vc). This remains to be robustly validated or assessed as a method to guide surgical targeting. The authors assessed the validity of connectivity-based parcellation for targeting the Vc and its potential for improving clinical outcomes of pain surgery. METHODS A cohort of 19 patients with regional, chronic neuropathic pain underwent preoperative structural and diffusion MRI, then progressed to deep brain stimulation targeting the Vc based on traditional atlas coordinates. Surgical thalami were retrospectively segmented and then parcellated based on tractography estimates of thalamocortical connectivity. The location of each patient's electrode array was analyzed with respect to their primary somatosensory cortex (S1) parcel and compared across patients with reference to the thalamic homunculus. RESULTS Ten patients achieved long-term pain relief. Sixty-one percent of an average array (interquartile range 42%-74%) was located in the S1 parcel. In patients who achieved long-term benefit from surgery, array location in the individually generated S1 parcels was medial for face pain, centromedial for arm pain, and centrolateral for leg pain. Patients who did not benefit from surgery did not follow this pattern. Standard stereotactic coordinates of electrode locations diverged from this pattern. CONCLUSIONS Connectivity-based parcellation of the thalamus appears to be a reliable method for segmenting the Vc. Identifying the Vc in this way, and targeting mediolaterally as appropriate for the region of pain, merits exploration in an effort to increase the yield of successful surgical procedures.
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Affiliation(s)
- Ashley L B Raghu
- 1Oxford Functional Neurosurgery, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom; and
| | - Sean C Martin
- 1Oxford Functional Neurosurgery, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom; and
- 2Department of Neurosurgery, John Radcliffe Hospital, Oxford University NHS Foundation Trust, Oxford, United Kingdom
| | - Tariq Parker
- 1Oxford Functional Neurosurgery, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom; and
| | - Tipu Z Aziz
- 1Oxford Functional Neurosurgery, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom; and
- 2Department of Neurosurgery, John Radcliffe Hospital, Oxford University NHS Foundation Trust, Oxford, United Kingdom
| | - Alexander L Green
- 1Oxford Functional Neurosurgery, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom; and
- 2Department of Neurosurgery, John Radcliffe Hospital, Oxford University NHS Foundation Trust, Oxford, United Kingdom
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Mantel T, Jochim A, Meindl T, Deppe J, Zimmer C, Li Y, Haslinger B. Thalamic structural connectivity profiles in blepharospam/Meige's syndrome. Neuroimage Clin 2022; 34:103013. [PMID: 35483134 PMCID: PMC9125780 DOI: 10.1016/j.nicl.2022.103013] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND Blepharospasm is a debilitating focal dystonia characterized by involuntary eyelid spasms that can be accompanied by oromandibular muscle involvement (Meige's syndrome). Frequently observed abnormality in functional neuroimaging hints at an important position of the thalamus, that relays involved cortico-basal ganglia-cortical and cortico-cerebello-cortical circuits, within the abnormal network in blepharospasm. OBJECTIVE To characterize abnormal cortico-thalamic structural/streamline connectivity (SC) patterns in the disease, as well as their potential co-occurrence with abnormal subcortico-thalamo-cortical projections using diffusion tractography. METHODS Diffusion imaging was obtained in 17 patients with blepharospasm (5 with mild lower facial involvement) and 17 healthy controls. Probabilistic tractography was used for quantification of SC between six cortical regions and thalamus, and voxel-level thalamic SC mapping as well as evaluation of the thalamic SC distributions' topography by center-of-gravity analysis was performed. Post-hoc, correlations of SC with clinical parameters were evaluated. Further, white matter integrity was investigated within representative segments of the dentato-thalamo-cortical and pallido-thalamo-cortical tract. RESULTS Connectivity mapping showed significant reduction of right (pre)motor- and left occipital-thalamic SC, as well as a topographic shift of the left occipital-thalamic SC distribution in patients. Significant positive correlation of occipital-thalamic SC with disease severity was found. Post-hoc analysis revealed significantly reduced mean fractional anisotropy in patients within the dentato-thalamo-cortical trajectory connecting to right (pre)motor and left occipital cortex. CONCLUSION Abnormal occipital/motor SC provides evidence for dysfunction of the thalamus-relayed visual and motor network as a key aspect in the disease. Concurrent impairment of microstructural integrity within the dentato-thalamic trajectories targeting those cortices hints at cerebellar contribution.
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Affiliation(s)
- Tobias Mantel
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Strasse 22, Munich, Germany
| | - Angela Jochim
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Strasse 22, Munich, Germany
| | - Tobias Meindl
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Strasse 22, Munich, Germany
| | - Jonas Deppe
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Strasse 22, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Strasse 22, Munich, Germany
| | - Yong Li
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Strasse 22, Munich, Germany
| | - Bernhard Haslinger
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Strasse 22, Munich, Germany.
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Milardi D, Antonio Basile G, Faskowitz J, Bertino S, Quartarone A, Anastasi G, Bramanti A, Ciurleo R, Cacciola A. Effects of diffusion signal modeling and segmentation approaches on subthalamic nucleus parcellation. Neuroimage 2022; 250:118959. [PMID: 35122971 DOI: 10.1016/j.neuroimage.2022.118959] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 11/24/2021] [Accepted: 01/31/2022] [Indexed: 12/14/2022] Open
Abstract
The subthalamic nucleus (STN) is commonly used as a surgical target for deep brain stimulation in movement disorders such as Parkinson's Disease. Tractography-derived connectivity-based parcellation (CBP) has been recently proposed as a suitable tool for non-invasive in vivo identification and pre-operative targeting of specific functional territories within the human STN. However, a well-established, accurate and reproducible protocol for STN parcellation is still lacking. The present work aims at testing the effects of different tractography-based approaches for the reconstruction of STN functional territories. We reconstructed functional territories of the STN on the high-quality dataset of 100 unrelated healthy subjects and on the test-retest dataset of the Human Connectome Project (HCP) repository. Connectivity-based parcellation was performed with a hypothesis-driven approach according to cortico-subthalamic connectivity, after dividing cortical areas into three groups: associative, limbic and sensorimotor. Four parcellation pipelines were compared, combining different signal modeling techniques (single-fiber vs multi-fiber) and different parcellation approaches (winner takes all parcellation vs fiber density thresholding). We tested these procedures on STN regions of interest obtained from three different, commonly employed, subcortical atlases. We evaluated the pipelines both in terms of between-subject similarity, assessed on the cohort of 100 unrelated healthy subjects, and of within-subject similarity, using a second cohort of 44 subjects with available test-retest data. We found that each parcellation provides converging results in terms of location of the identified parcels, but with significative variations in size and shape. All pipelines obtained very high within-subject similarity, with tensor-based approaches outperforming multi-fiber pipelines. On the other hand, higher between-subject similarity was found with multi-fiber signal modeling techniques combined with fiber density thresholding. We suggest that a fine-tuning of tractography-based parcellation may lead to higher reproducibility and aid the development of an optimized surgical targeting protocol.
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Affiliation(s)
- Demetrio Milardi
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy.
| | - Gianpaolo Antonio Basile
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Joshua Faskowitz
- Program in Neuroscience, Indiana University, Bloomington, IN, USA; Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th Street, Bloomington, IN, 47405, USA
| | - Salvatore Bertino
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Angelo Quartarone
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Giuseppe Anastasi
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Alessia Bramanti
- Department of Medicine, Surgery and Dentistry "Medical School of Salerno"- University of Salerno, Italy
| | | | - Alberto Cacciola
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy.
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Bertino S, Basile GA, Bramanti A, Ciurleo R, Tisano A, Anastasi GP, Milardi D, Cacciola A. Ventral intermediate nucleus structural connectivity-derived segmentation: anatomical reliability and variability. Neuroimage 2021; 243:118519. [PMID: 34461233 DOI: 10.1016/j.neuroimage.2021.118519] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 07/24/2021] [Accepted: 08/25/2021] [Indexed: 12/30/2022] Open
Abstract
The Ventral intermediate nucleus (Vim) of thalamus is the most targeted structure for the treatment of drug-refractory tremors. Since methodological differences across existing studies are remarkable and no gold-standard pipeline is available, in this study, we tested different parcellation pipelines for tractography-derived putative Vim identification. Thalamic parcellation was performed on a high quality, multi-shell dataset and a downsampled, clinical-like dataset using two different diffusion signal modeling techniques and two different voxel classification criteria, thus implementing a total of four parcellation pipelines. The most reliable pipeline in terms of inter-subject variability has been picked and parcels putatively corresponding to motor thalamic nuclei have been selected by calculating similarity with a histology-based mask of Vim. Then, spatial relations with optimal stimulation points for the treatment of essential tremor have been quantified. Finally, effect of data quality and parcellation pipelines on a volumetric index of connectivity clusters has been assessed. We found that the pipeline characterized by higher-order signal modeling and threshold-based voxel classification criteria was the most reliable in terms of inter-subject variability regardless data quality. The maps putatively corresponding to Vim were those derived by precentral and dentate nucleus-thalamic connectivity. However, tractography-derived functional targets showed remarkable differences in shape and sizes when compared to a ground truth model based on histochemical staining on seriate sections of human brain. Thalamic voxels connected to contralateral dentate nucleus resulted to be the closest to literature-derived stimulation points for essential tremor but at the same time showing the most remarkable inter-subject variability. Finally, the volume of connectivity parcels resulted to be significantly influenced by data quality and parcellation pipelines. Hence, caution is warranted when performing thalamic connectivity-based segmentation for stereotactic targeting.
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Affiliation(s)
- Salvatore Bertino
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Gianpaolo Antonio Basile
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | | | | | - Adriana Tisano
- Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy
| | - Giuseppe Pio Anastasi
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Demetrio Milardi
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Alberto Cacciola
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy.
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Bertino S, Basile GA, Bramanti A, Anastasi GP, Quartarone A, Milardi D, Cacciola A. Spatially coherent and topographically organized pathways of the human globus pallidus. Hum Brain Mapp 2020; 41:4641-4661. [PMID: 32757349 PMCID: PMC7555102 DOI: 10.1002/hbm.25147] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 06/29/2020] [Accepted: 07/12/2020] [Indexed: 12/18/2022] Open
Abstract
Internal and external segments of globus pallidus (GP) exert different functions in basal ganglia circuitry, despite their main connectional systems share the same topographical organization, delineating limbic, associative, and sensorimotor territories. The identification of internal GP sensorimotor territory has therapeutic implications in functional neurosurgery settings. This study is aimed at assessing the spatial coherence of striatopallidal, subthalamopallidal, and pallidothalamic pathways by using tractography‐derived connectivity‐based parcellation (CBP) on high quality diffusion MRI data of 100 unrelated healthy subjects from the Human Connectome Project. A two‐stage hypothesis‐driven CBP approach has been carried out on the internal and external GP. Dice coefficient between functionally homologous pairs of pallidal maps has been computed. In addition, reproducibility of parcellation according to different pathways of interest has been investigated, as well as spatial relations between connectivity maps and existing optimal stimulation points for dystonic patients. The spatial organization of connectivity clusters revealed anterior limbic, intermediate associative and posterior sensorimotor maps within both internal and external GP. Dice coefficients showed high degree of coherence between functionally similar maps derived from the different bundles of interest. Sensorimotor maps derived from the subthalamopallidal pathway resulted to be the nearest to known optimal pallidal stimulation sites for dystonic patients. Our findings suggest that functionally homologous afferent and efferent connections may share similar spatial territory within the GP and that subcortical pallidal connectional systems may have distinct implications in the treatment of movement disorders.
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Affiliation(s)
- Salvatore Bertino
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Gianpaolo Antonio Basile
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | | | - Giuseppe Pio Anastasi
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Angelo Quartarone
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Demetrio Milardi
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy.,IRCCS Centro Neurolesi "Bonino Pulejo", Messina, Italy
| | - Alberto Cacciola
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
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