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Dünnwald M, Krohn F, Sciarra A, Sarkar M, Schneider A, Fliessbach K, Kimmich O, Jessen F, Rostamzadeh A, Glanz W, Incesoy EI, Teipel S, Kilimann I, Goerss D, Spottke A, Brustkern J, Heneka MT, Brosseron F, Lüsebrink F, Hämmerer D, Düzel E, Tönnies K, Oeltze-Jafra S, Betts MJ. Fully Automated MRI-based Analysis of the Locus Coeruleus in Aging and Alzheimer's Disease Dementia using ELSI-Net. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.26.605356. [PMID: 39091766 PMCID: PMC11291139 DOI: 10.1101/2024.07.26.605356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
INTRODUCTION The Locus Coeruleus (LC) is linked to the development and pathophysiology of neurodegenerative diseases such as Alzheimer's Disease (AD). Magnetic Resonance Imaging based LC features have shown potential to assess LC integrity in vivo. METHODS We present a Deep Learning based LC segmentation and feature extraction method: ELSI-Net and apply it to healthy aging and AD dementia datasets. Agreement to expert raters and previously published LC atlases were assessed. We aimed to reproduce previously reported differences in LC integrity in aging and AD dementia and correlate extracted features to cerebrospinal fluid (CSF) biomarkers of AD pathology. RESULTS ELSI-Net demonstrated high agreement to expert raters and published atlases. Previously reported group differences in LC integrity were detected and correlations to CSF biomarkers were found. DISCUSSION Although we found excellent performance, further evaluations on more diverse datasets from clinical cohorts are required for a conclusive assessment of ELSI-Nets general applicability.
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Affiliation(s)
- Max Dünnwald
- Department of Neurology, Otto von Guericke University Magdeburg (OvGU), Germany
- Faculty of Computer Science, OvGU, Germany
| | - Friedrich Krohn
- Institute of Cognitive Neurology and Dementia Research, OvGU, Germany
| | - Alessandro Sciarra
- Department of Neurology, Otto von Guericke University Magdeburg (OvGU), Germany
| | - Mousumi Sarkar
- Institute of Cognitive Neurology and Dementia Research, OvGU, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Cognitive Disorders and Old Age Psychiatry, University Hospital Bonn, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Cognitive Disorders and Old Age Psychiatry, University Hospital Bonn, Germany
| | - Okka Kimmich
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry, University of Cologne, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Germany
| | | | | | - Enise I. Incesoy
- Institute of Cognitive Neurology and Dementia Research, OvGU, Germany
- DZNE, Magdeburg, Germany
- Department for Psychiatry and Psychotherapy, University Clinic Magdeburg, Germany
| | - Stefan Teipel
- DZNE, Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Germany
| | - Ingo Kilimann
- DZNE, Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Germany
| | - Doreen Goerss
- DZNE, Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Germany
| | | | - Michael T. Heneka
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | | | | | - Dorothea Hämmerer
- Institute of Cognitive Neurology and Dementia Research, OvGU, Germany
- DZNE, Magdeburg, Germany
- Department of Psychology, University of Innsbruck, Austria
- Institute of Cognitive Neuroscience, University College London, United Kingdom
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research, OvGU, Germany
- DZNE, Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, United Kingdom
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | | | - Steffen Oeltze-Jafra
- Peter L. Reichertz Institute for Medical Informatics, Hannover Medical School, Germany
| | - Matthew J. Betts
- Institute of Cognitive Neurology and Dementia Research, OvGU, Germany
- DZNE, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
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Aganj I, Mora J, Fischl B, Augustinack JC. Automatic geometry-based estimation of the locus coeruleus region on T 1-weighted magnetic resonance images. Front Neurosci 2024; 18:1375530. [PMID: 38774790 PMCID: PMC11106368 DOI: 10.3389/fnins.2024.1375530] [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: 01/24/2024] [Accepted: 04/09/2024] [Indexed: 05/24/2024] Open
Abstract
The locus coeruleus (LC) is a key brain structure implicated in cognitive function and neurodegenerative disease. Automatic segmentation of the LC is a crucial step in quantitative non-invasive analysis of the LC in large MRI cohorts. Most publicly available imaging databases for training automatic LC segmentation models take advantage of specialized contrast-enhancing (e.g., neuromelanin-sensitive) MRI. Segmentation models developed with such image contrasts, however, are not readily applicable to existing datasets with conventional MRI sequences. In this work, we evaluate the feasibility of using non-contrast neuroanatomical information to geometrically approximate the LC region from standard 3-Tesla T1-weighted images of 20 subjects from the Human Connectome Project (HCP). We employ this dataset to train and internally/externally evaluate two automatic localization methods, the Expected Label Value and the U-Net. For out-of-sample segmentation, we compare the results with atlas-based segmentation, as well as test the hypothesis that using the phase image as input can improve the robustness. We then apply our trained models to a larger subset of HCP, while exploratorily correlating LC imaging variables and structural connectivity with demographic and clinical data. This report provides an evaluation of computational methods estimating neural structure.
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Affiliation(s)
- Iman Aganj
- Radiology Department, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Radiology Department, Harvard Medical School, Boston, MA, United States
| | - Jocelyn Mora
- Radiology Department, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Bruce Fischl
- Radiology Department, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Radiology Department, Harvard Medical School, Boston, MA, United States
| | - Jean C. Augustinack
- Radiology Department, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Radiology Department, Harvard Medical School, Boston, MA, United States
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Trujillo P, Aumann MA, Claassen DO. Neuromelanin-sensitive MRI as a promising biomarker of catecholamine function. Brain 2024; 147:337-351. [PMID: 37669320 PMCID: PMC10834262 DOI: 10.1093/brain/awad300] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/17/2023] [Accepted: 08/20/2023] [Indexed: 09/07/2023] Open
Abstract
Disruptions to dopamine and noradrenergic neurotransmission are noted in several neurodegenerative and psychiatric disorders. Neuromelanin-sensitive (NM)-MRI offers a non-invasive approach to visualize and quantify the structural and functional integrity of the substantia nigra and locus coeruleus. This method may aid in the diagnosis and quantification of longitudinal changes of disease and could provide a stratification tool for predicting treatment success of pharmacological interventions targeting the dopaminergic and noradrenergic systems. Given the growing clinical interest in NM-MRI, understanding the contrast mechanisms that generate this signal is crucial for appropriate interpretation of NM-MRI outcomes and for the continued development of quantitative MRI biomarkers that assess disease severity and progression. To date, most studies associate NM-MRI measurements to the content of the neuromelanin pigment and/or density of neuromelanin-containing neurons, while recent studies suggest that the main source of the NM-MRI contrast is not the presence of neuromelanin but the high-water content in the dopaminergic and noradrenergic neurons. In this review, we consider the biological and physical basis for the NM-MRI contrast and discuss a wide range of interpretations of NM-MRI. We describe different acquisition and image processing approaches and discuss how these methods could be improved and standardized to facilitate large-scale multisite studies and translation into clinical use. We review the potential clinical applications in neurological and psychiatric disorders and the promise of NM-MRI as a biomarker of disease, and finally, we discuss the current limitations of NM-MRI that need to be addressed before this technique can be utilized as a biomarker and translated into clinical practice and offer suggestions for future research.
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Affiliation(s)
- Paula Trujillo
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Megan A Aumann
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Daniel O Claassen
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
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Aganj I, Mora J, Fischl B, Augustinack JC. Automatic Geometry-based Estimation of the Locus Coeruleus Region on T 1-Weighted Magnetic Resonance Images. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576958. [PMID: 38328208 PMCID: PMC10849695 DOI: 10.1101/2024.01.23.576958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The locus coeruleus (LC) is a key brain structure implicated in cognitive function and neurodegenerative disease. Automatic segmentation of the LC is a crucial step in quantitative non-invasive analysis of the LC in large MRI cohorts. Most publicly available imaging databases for training automatic LC segmentation models take advantage of specialized contrast-enhancing (e.g., neuromelanin-sensitive) MRI. Segmentation models developed with such image contrasts, however, are not readily applicable to existing datasets with conventional MRI sequences. In this work, we evaluate the feasibility of using non-contrast neuroanatomical information to geometrically approximate the LC region from standard 3-Tesla T1-weighted images of 20 subjects from the Human Connectome Project (HCP). We employ this dataset to train and internally/externally evaluate two automatic localization methods, the Expected Label Value and the U-Net. We also test the hypothesis that using the phase image as input can improve the robustness of out-of-sample segmentation. We then apply our trained models to a larger subset of HCP, while exploratorily correlating LC imaging variables and structural connectivity with demographic and clinical data. This report contributes and provides an evaluation of two computational methods estimating neural structure.
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Affiliation(s)
- Iman Aganj
- Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, Boston, MA 02129, USA
- Radiology Department, Harvard Medical School, Boston, MA 02115, USA
| | - Jocelyn Mora
- Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, Boston, MA 02129, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, Boston, MA 02129, USA
- Radiology Department, Harvard Medical School, Boston, MA 02115, USA
| | - Jean C. Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, Boston, MA 02129, USA
- Radiology Department, Harvard Medical School, Boston, MA 02115, USA
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Welton T, Hartono S, Shih YC, Schwarz ST, Xing Y, Tan EK, Auer DP, Harel N, Chan LL. Ultra-high-field 7T MRI in Parkinson's disease: ready for clinical use?-a narrative review. Quant Imaging Med Surg 2023; 13:7607-7620. [PMID: 37969629 PMCID: PMC10644128 DOI: 10.21037/qims-23-509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 09/15/2023] [Indexed: 11/17/2023]
Abstract
Background and Objective The maturation of ultra-high-field magnetic resonance imaging (MRI) [≥7 Tesla (7T)] has improved our capability to depict and characterise brain structures efficiently, with better signal-to-noise ratio (SNR) and spatial resolution. We evaluated whether these improvements benefit the clinical detection and management of Parkinson's disease (PD). Methods We performed a literature search in March 2023 in PubMed (MEDLINE), EMBASE and Google Scholar for articles on "7T MRI" AND "Parkinson*", written in English, published between inception and 1st March, 2023, which we synthesised in narrative form. Key Content and Findings In deep-brain stimulation (DBS) surgical planning, early studies show that 7T MRI can distinguish anatomical substructures, and that this results in reduced adverse effects. In other areas, while there is strong evidence for improved accuracy and precision of 7T MRI-based measurements for PD, there is limited evidence for meaningful clinical translation. In particular, neuromelanin-iron complex quantification and visualisation in midbrain nuclei is enhanced, enabling depiction of nigrosomes 1-5, improved morphometry and vastly improved radiological assessments; however, studies on the related clinical outcomes, diagnosis, subtyping, differentiation of atypical parkinsonisms, and monitoring of treatment response using 7T MRI are lacking. Moreover, improvements in clinical utility must be great enough to justify the additional costs. Conclusions Together, current evidence supports feasible future clinical implementation of 7T MRI for PD. Future impacts to clinical decision making for diagnosis, differentiation, and monitoring of progression or treatment response are likely; however, to achieve this, further longitudinal studies using 7T MRI are needed in prodromal, early-stage PD and parkinsonism cohorts focusing on clinical translational potential.
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Affiliation(s)
- Thomas Welton
- National Neuroscience Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Septian Hartono
- National Neuroscience Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Department of Diagnostic Radiology, Singapore General Hospital, Singapore, Singapore
| | - Yao-Chia Shih
- Duke-NUS Medical School, Singapore, Singapore
- Department of Diagnostic Radiology, Singapore General Hospital, Singapore, Singapore
- Graduate Institute of Medicine, Yuan Ze University and National Taiwan University, Taipei
| | - Stefan T. Schwarz
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
- Department of Radiology, Cardiff and Vale University Health Board, Cardiff, Wales, UK
| | - Yue Xing
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Eng-King Tan
- National Neuroscience Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Dorothee P. Auer
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Noam Harel
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Ling-Ling Chan
- National Neuroscience Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Department of Diagnostic Radiology, Singapore General Hospital, Singapore, Singapore
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Wang Z, Cao X, LaBella A, Zeng X, Biegon A, Franceschi D, Petersen E, Clayton N, Ulaner GA, Zhao W, Goldan AH. High-resolution and high-sensitivity PET for quantitative molecular imaging of the monoaminergic nuclei: A GATE simulation study. Med Phys 2022; 49:4430-4444. [PMID: 35390182 PMCID: PMC11025683 DOI: 10.1002/mp.15653] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 02/03/2022] [Accepted: 03/07/2022] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Quantitative in vivo molecular imaging of fine brain structures requires high-spatial resolution and high-sensitivity. Positron emission tomography (PET) is an attractive candidate to introduce molecular imaging into standard clinical care due to its highly targeted and versatile imaging capabilities based on the radiotracer being used. However, PET suffers from relatively poor spatial resolution compared to other clinical imaging modalities, which limits its ability to accurately quantify radiotracer uptake in brain regions and nuclei smaller than 3 mm in diameter. Here we introduce a new practical and cost-effective high-resolution and high-sensitivity brain-dedicated PET scanner, using our depth-encoding Prism-PET detector modules arranged in a conformal decagon geometry, to substantially reduce the partial volume effect and enable accurate radiotracer uptake quantification in small subcortical nuclei. METHODS Two Prism-PET brain scanner setups were proposed based on our 4-to-1 and 9-to-1 coupling of scintillators to readout pixels using1.5 × 1.5 × 20 $1.5 \times 1.5 \times 20$ mm3 and0.987 × 0.987 × 20 $0.987 \times 0.987 \times 20$ mm3 crystal columns, respectively. Monte Carlo simulations of our Prism-PET scanners, Siemens Biograph Vision, and United Imaging EXPLORER were performed using Geant4 application for tomographic emission (GATE). National Electrical Manufacturers Association (NEMA) standard was followed for the evaluation of spatial resolution, sensitivity, and count-rate performance. An ultra-micro hot spot phantom was simulated for assessing image quality. A modified Zubal brain phantom was utilized for radiotracer imaging simulations of 5-HT1A receptors, which are abundant in the raphe nuclei (RN), and norepinephrine transporters, which are highly concentrated in the bilateral locus coeruleus (LC). RESULTS The Prism-PET brain scanner with 1.5 mm crystals is superior to that with 1 mm crystals as the former offers better depth-of-interaction (DOI) resolution, which is key to realizing compact and conformal PET scanner geometries. We achieved uniform 1.3 mm full-width-at-half-maximum (FWHM) spatial resolutions across the entire transaxial field-of-view (FOV), a NEMA sensitivity of 52.1 kcps/MBq, and a peak noise equivalent count rate (NECR) of 957.8 kcps at 25.2 kBq/mL using 450-650 keV energy window. Hot spot phantom results demonstrate that our scanner can resolve regions as small as 1.35 mm in diameter at both center and 10 cm away from the center of the transaixal FOV. Both 5-HT1A receptor and norepinephrine transporter brain simulations prove that our Prism-PET scanner enables accurate quantification of radiotracer uptake in small brain regions, with a 1.8-fold and 2.6-fold improvement in the dorsal RN as well as a 3.2-fold and 4.4-fold improvement in the bilateral LC compared to the Biograph Vision and EXPLORER, respectively. CONCLUSIONS Based on our simulation results, the proposed high-resolution and high-sensitivity Prism-PET brain scanner is a promising cost-effective candidate to achieve quantitative molecular neuroimaging of small but important brain regions with PET clinically viable.
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Affiliation(s)
- Zipai Wang
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Xinjie Cao
- Department of Electrical and Computer Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Andy LaBella
- Department of Radiology, Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Xinjie Zeng
- Department of Electrical and Computer Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Anat Biegon
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
| | - Dinko Franceschi
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
| | - Eric Petersen
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Nicholas Clayton
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
| | - Gary A. Ulaner
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Molecular Imaging and Therapy, Hoag Family Cancer Institute, Newport Beach, California, USA
| | - Wei Zhao
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
| | - Amir H. Goldan
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA
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Dünnwald M, Ernst P, Düzel E, Tönnies K, Betts MJ, Oeltze-Jafra S. Fully automated deep learning-based localization and segmentation of the locus coeruleus in aging and Parkinson's disease using neuromelanin-sensitive MRI. Int J Comput Assist Radiol Surg 2021; 16:2129-2135. [PMID: 34797512 PMCID: PMC8616874 DOI: 10.1007/s11548-021-02528-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 10/21/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE Development and performance measurement of a fully automated pipeline that localizes and segments the locus coeruleus in so-called neuromelanin-sensitive magnetic resonance imaging data for the derivation of quantitative biomarkers of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. METHODS We propose a pipeline composed of several 3D-Unet-based convolutional neural networks for iterative multi-scale localization and multi-rater segmentation and non-deep learning-based components for automated biomarker extraction. We trained on the healthy aging cohort and did not carry out any adaption or fine-tuning prior to the application to Parkinson's disease subjects. RESULTS The localization and segmentation pipeline demonstrated sufficient performance as measured by Euclidean distance (on average around 1.3mm on healthy aging subjects and 2.2mm in Parkinson's disease subjects) and Dice similarity coefficient (overall around [Formula: see text] on healthy aging subjects and [Formula: see text] for subjects with Parkinson's disease) as well as promising agreement with respect to contrast ratios in terms of intraclass correlation coefficient of [Formula: see text] for healthy aging subjects compared to a manual segmentation procedure. Lower values ([Formula: see text]) for Parkinson's disease subjects indicate the need for further investigation and tests before the application to clinical samples. CONCLUSION These promising results suggest the usability of the proposed algorithm for data of healthy aging subjects and pave the way for further investigations using this approach on different clinical datasets to validate its practical usability more conclusively.
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Affiliation(s)
- Max Dünnwald
- Department of Neurology, Faculty of Medicine, Otto von Guericke University Magdeburg (OVGU), Magdeburg, Germany. .,Faculty of Computer Science, OVGU, Magdeburg, Germany.
| | - Philipp Ernst
- Faculty of Computer Science, OVGU, Magdeburg, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), Faculty of Medicine, OVGU, Magdeburg, Germany.,Institute of Cognitive Neuroscience, University College London, London, Great Britain, UK.,Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany
| | - Klaus Tönnies
- Faculty of Computer Science, OVGU, Magdeburg, Germany
| | - Matthew J Betts
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), Faculty of Medicine, OVGU, Magdeburg, Germany.,Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany
| | - Steffen Oeltze-Jafra
- Department of Neurology, Faculty of Medicine, Otto von Guericke University Magdeburg (OVGU), Magdeburg, Germany.,Faculty of Computer Science, OVGU, Magdeburg, Germany.,Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany
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Düzel E, Costagli M, Donatelli G, Speck O, Cosottini M. Studying Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis with 7-T magnetic resonance. Eur Radiol Exp 2021; 5:36. [PMID: 34435242 PMCID: PMC8387546 DOI: 10.1186/s41747-021-00221-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 04/07/2021] [Indexed: 12/18/2022] Open
Abstract
Ultra-high-field (UHF) magnetic resonance (MR) scanners, that is, equipment operating at static magnetic field of 7 tesla (7 T) and above, enable the acquisition of data with greatly improved signal-to-noise ratio with respect to conventional MR systems (e.g., scanners operating at 1.5 T and 3 T). The change in tissue relaxation times at UHF offers the opportunity to improve tissue contrast and depict features that were previously inaccessible. These potential advantages come, however, at a cost: in the majority of UHF-MR clinical protocols, potential drawbacks may include signal inhomogeneity, geometrical distortions, artifacts introduced by patient respiration, cardiac cycle, and motion. This article reviews the 7 T MR literature reporting the recent studies on the most widespread neurodegenerative diseases: Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.
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Affiliation(s)
- Emrah Düzel
- Otto-von-Guericke University Magdeburg, Magdeburg, Germany. .,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany. .,University College London, London, UK.
| | - Mauro Costagli
- IRCCS Stella Maris, Pisa, Italy.,University of Genoa, Genova, Italy
| | - Graziella Donatelli
- Fondazione Imago 7, Pisa, Italy.,Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
| | - Oliver Speck
- Otto-von-Guericke University Magdeburg, Magdeburg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Mirco Cosottini
- Azienda Ospedaliero Universitaria Pisana, Pisa, Italy.,University of Pisa, Pisa, Italy
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9
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Noradrenergic correlates of chronic cocaine craving: neuromelanin and functional brain imaging. Neuropsychopharmacology 2021; 46:851-859. [PMID: 33408330 PMCID: PMC8027452 DOI: 10.1038/s41386-020-00937-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/18/2020] [Accepted: 11/24/2020] [Indexed: 12/13/2022]
Abstract
Preclinical studies have implicated noradrenergic (NA) dysfunction in cocaine addiction. In particular, the NA system plays a central role in motivated behavior and may partake in the regulation of craving and drug use. Yet, human studies of the NA system are scarce, likely hampered by the difficulty in precisely localizing the locus coeruleus (LC). Here, we used neuromelanin imaging to localize the LC and quantified LC neuromelanin signal (NMS) intensity in 44 current cocaine users (CU; 37 men) and 59 nondrug users (NU; 44 men). We also employed fMRI to investigate cue-induced regional responses and LC functional connectivities, as quantified by generalized psychophysiological interaction (gPPI), in CU. Imaging data were processed by published routines and the findings were evaluated with a corrected threshold. We examined how these neural measures were associated with chronic cocaine craving, as assessed by the Cocaine Craving Questionnaire (CCQ). Compared to NU, CU demonstrated higher LC NMS for all probabilistic thresholds defined of 50-90% of the peak. In contrast, NMS of the ventral tegmental area/substantia nigra (VTA/SN) did not show significant group differences. Drug as compared to neutral cues elicited higher activations of many cortical and subcortical regions, none of which were significantly correlated with CCQ score. Drug vs. neutral cues also elicited "deactivation" of bilateral parahippocampal gyri (PHG) and PHG gPPI with a wide array of cortical and subcortical regions, including the ventral striatum and, with small volume correction, the LC. Less deactivation of the PHG (r = 0.40, p = 0.008) and higher PHG-LC gPPI (r = 0.44, p = 0.003) were positively correlated with the CCQ score. In contrast, PHG-VTA/SN connectivity did not correlate with the CCQ score. Together, chronic cocaine exposure may induce higher NMS intensity, suggesting neurotoxic effects on the LC. The correlation of cue-elicited PHG LC connectivity with CCQ score suggests a noradrenergic correlate of chronic cocaine craving. Potentially compensating for memory functions as in neurodegenerative conditions, cue-elicited PHG LC circuit connectivity plays an ill-adaptive role in supporting cocaine craving.
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Mäki-Marttunen V, Espeseth T. Uncovering the locus coeruleus: Comparison of localization methods for functional analysis. Neuroimage 2020; 224:117409. [PMID: 33011416 DOI: 10.1016/j.neuroimage.2020.117409] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 09/17/2020] [Accepted: 09/25/2020] [Indexed: 12/17/2022] Open
Abstract
Functional neuroimaging of small brainstem structures in humans is gaining interest due to their potential importance in aging and many clinical conditions. Researchers have used different methods to measure activity in the locus coeruleus (LC), the main noradrenergic nucleus in the brain. However, the extent to which these different LC localization methods yield similar results is unclear. In the present article, we compared four different approaches to estimate localization of the LC in a large sample (N = 98): 1) a probabilistic map from a previous study, 2) masks segmented from neuromelanin-sensitive scans, both manually and semi-automatically, 3) components from a masked-independent components analysis of the functional data, and 4) a mask from pupil regression of the functional data. The four methods have all been used previously in the imaging community to localize the LC in vivo in humans. We report several measures of similarity between the LC masks obtained from the different methods. In addition, we compare functional connectivity maps obtained from the different masks. We conclude that sample-specific masks appear more suitable than masks obtained from an independent sample, that masks based on structural versus functional methods may capture different portions of LC, and that, at the group level, the creation of a "consensus" mask using more than one approach may give a better estimate of LC localization.
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Affiliation(s)
| | - Thomas Espeseth
- Department of Psychology, University of Oslo, Postboks 1094, Blindern, 0317 Oslo, Norway; Bjørknes College, Lovisenberggata 13, 0456 Oslo, Norway
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Colzato L, Beste C. A literature review on the neurophysiological underpinnings and cognitive effects of transcutaneous vagus nerve stimulation: challenges and future directions. J Neurophysiol 2020; 123:1739-1755. [PMID: 32208895 DOI: 10.1152/jn.00057.2020] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Brain stimulation approaches are important to gain causal mechanistic insights into the relevance of functional brain regions and/or neurophysiological systems for human cognitive functions. In recent years, transcutaneous vagus nerve stimulation (tVNS) has attracted considerable popularity. It is a noninvasive brain stimulation technique based on the stimulation of the vagus nerve. The stimulation of this nerve activates subcortical nuclei, such as the locus coeruleus and the nucleus of the solitary tract, and from there, the activation propagates to the cortex. Since tVNS is a novel stimulation technique, this literature review outlines a brief historical background of tVNS, before detailing underlying neurophysiological mechanisms of action, stimulation parameters, cognitive effects of tVNS on healthy humans, and, lastly, current challenges and future directions of tVNS research in cognitive functions. Although more research is needed, we conclude that tVNS, by increasing norepineprine (NE) and gamma-aminobutyric acid (GABA) levels, affects NE- and GABA-related cognitive performance. The review provides detailed background information how to use tVNS as a neuromodulatory tool in cognitive neuroscience and outlines important future leads of research on tVNS.
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Affiliation(s)
- Lorenza Colzato
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany.,Department of Cognitive Psychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany.,Cognitive Psychology, Faculty of Psychology, Shandong Normal University, Jinan, China
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany.,Cognitive Psychology, Faculty of Psychology, Shandong Normal University, Jinan, China
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Trujillo P, Petersen KJ, Cronin MJ, Lin YC, Kang H, Donahue MJ, Smith SA, Claassen DO. Quantitative magnetization transfer imaging of the human locus coeruleus. Neuroimage 2019; 200:191-198. [PMID: 31233908 PMCID: PMC6934172 DOI: 10.1016/j.neuroimage.2019.06.049] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 06/17/2019] [Accepted: 06/19/2019] [Indexed: 12/14/2022] Open
Abstract
The locus coeruleus (LC) is the major origin of norepinephrine in the central nervous system, and is subject to age-related and neurodegenerative changes, especially in disorders such as Parkinson's disease and Alzheimer's disease. Previous studies have shown that neuromelanin (NM)-sensitive MRI can be used to visualize the LC, and it is hypothesized that magnetization transfer (MT) effects are the primary source of LC contrast. The aim of this study was to characterize the MT effects in LC imaging by applying high spatial resolution quantitative MT (qMT) imaging to create parametric maps of the macromolecular content of the LC and surrounding tissues. Healthy volunteers (n = 26; sex = 17 F/9M; age = 41.0 ± 19.1 years) underwent brain MRI on a 3.0 T scanner. qMT data were acquired using a 3D MT-prepared spoiled gradient echo sequence. A traditional NM scan consisting of a T1-weighted turbo spin echo sequence with MT preparation was also acquired. The pool-size ratio (PSR) was estimated for each voxel using a single-point qMT approach. The LC was semi-automatically segmented on the MT-weighted images. The MT-weighted images provided higher contrast-ratio between the LC and surrounding pontine tegmentum (PT) (0.215 ± 0.031) than the reference images without MT-preparation (-0.005 ± 0.026) and the traditional NM images (0.138 ± 0.044). The PSR maps showed significant differences between the LC (0.090 ± 0.009) and PT (0.188 ± 0.025). The largest difference between the PSR values in the LC and PT was observed in the central slices, which also correspond to those with the highest contrast-ratio. These results highlight the role of MT in generating NM-related contrast in the LC, and should serve as a foundation for future studies aiming to quantify pathological changes in the LC and surrounding structures in vivo.
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Affiliation(s)
- Paula Trujillo
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Kalen J Petersen
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Matthew J Cronin
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ya-Chen Lin
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Manus J Donahue
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Daniel O Claassen
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
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