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Tsagkas C, Horvath-Huck A, Haas T, Amann M, Todea A, Altermatt A, Müller J, Cagol A, Leimbacher M, Barakovic M, Weigel M, Pezold S, Sprenger T, Kappos L, Bieri O, Granziera C, Cattin P, Parmar K. Fully Automatic Method for Reliable Spinal Cord Compartment Segmentation in Multiple Sclerosis. AJNR Am J Neuroradiol 2023; 44:218-227. [PMID: 36702504 PMCID: PMC9891337 DOI: 10.3174/ajnr.a7756] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 12/05/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND AND PURPOSE Fully automatic quantification methods of spinal cord compartments are needed to study pathologic changes of the spinal cord GM and WM in MS in vivo. We propose a novel method for automatic spinal cord compartment segmentation (SCORE) in patients with MS. MATERIALS AND METHODS The cervical spinal cords of 24 patients with MS and 24 sex- and age-matched healthy controls were scanned on a 3T MR imaging system, including an averaged magnetization inversion recovery acquisition sequence. Three experienced raters manually segmented the spinal cord GM and WM, anterior and posterior horns, gray commissure, and MS lesions. Subsequently, manual segmentations were used to train neural segmentation networks of spinal cord compartments with multidimensional gated recurrent units in a 3-fold cross-validation fashion. Total intracranial volumes were quantified using FreeSurfer. RESULTS The intra- and intersession reproducibility of SCORE was high in all spinal cord compartments (eg, mean relative SD of GM and WM: ≤ 3.50% and ≤1.47%, respectively) and was better than manual segmentations (all P < .001). The accuracy of SCORE compared with manual segmentations was excellent, both in healthy controls and in patients with MS (Dice similarity coefficients of GM and WM: ≥ 0.84 and ≥0.92, respectively). Patients with MS had lower total WM areas (P < .05), and total anterior horn areas (P < .01 respectively), as measured with SCORE. CONCLUSIONS We demonstrate a novel, reliable quantification method for spinal cord tissue segmentation in healthy controls and patients with MS and other neurologic disorders affecting the spinal cord. Patients with MS have reduced areas in specific spinal cord tissue compartments, which may be used as MS biomarkers.
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Affiliation(s)
- C Tsagkas
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
| | - A Horvath-Huck
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - T Haas
- Department of Medicine and Biomedical Engineering; Division of Radiological Physics (T.H., M.W., O.B.)
| | - M Amann
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
- Medical Image Analysis Center AG (M.A., A.A.), Basel, Switzerland
| | - A Todea
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Radiology; Department of Neuroradiology (A.T.), Clinic for Radiology & Nuclear Medicine; and Research Center for Clinical Neuroimmunology
| | - A Altermatt
- Medical Image Analysis Center AG (M.A., A.A.), Basel, Switzerland
| | - J Müller
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
| | - A Cagol
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - M Leimbacher
- Medical Faculty (M.L., P.C.), University of Basel, Basel, Switzerland
| | - M Barakovic
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - M Weigel
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Medicine and Biomedical Engineering; Division of Radiological Physics (T.H., M.W., O.B.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - S Pezold
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - T Sprenger
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Department of Neurology (T.S.), DKD Helios Klinik Wiesbaden, Wiesbaden, Germany
| | - L Kappos
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Neuroscience Basel (RC2NB) (L.K.), Departments of Medicine, Clinical Research, and Biomedical Imaging, University Hospital Basel and University of Basel, Basel, Switzerland
| | - O Bieri
- Department of Medicine and Biomedical Engineering; Division of Radiological Physics (T.H., M.W., O.B.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - C Granziera
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - P Cattin
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
- Medical Faculty (M.L., P.C.), University of Basel, Basel, Switzerland
| | - K Parmar
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Reha Rheinfelden (K.P.), Rheinfelden, Switzerland
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Bonnier G, Fischi-Gomez E, Roche A, Hilbert T, Kober T, Krueger G, Granziera C. Personalized pathology maps to quantify diffuse and focal brain damage. Neuroimage Clin 2018; 21:101607. [PMID: 30502080 PMCID: PMC6413479 DOI: 10.1016/j.nicl.2018.11.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Revised: 10/02/2018] [Accepted: 11/18/2018] [Indexed: 01/04/2023]
Abstract
Background and objectives Quantitative MRI (qMRI) permits the quantification of brain changes compatible with inflammation, degeneration and repair in multiple sclerosis (MS) patients. In this study, we propose a new method to provide personalized maps of tissue alterations and longitudinal brain changes based on different qMRI metrics, which provide complementary information about brain pathology. Methods We performed baseline and two-years follow-up on (i) 13 relapsing-remitting MS patients and (ii) four healthy controls. A group consisting of up to 65 healthy controls was used to compute the reference distribution of qMRI metrics in healthy tissue. All subjects underwent 3T MRI examinations including T1, T2, T2* relaxation and Magnetization Transfer Ratio (MTR) imaging. We used a recent partial volume estimation algorithm to estimate the concentration of different brain tissue types on T1 maps; then, we computed a deviation map (z-score map) for each contrast at both time-points. Finally, we subtracted those deviation maps only for voxels showing a significant difference with healthy tissue in one of the time points, to obtain a difference map for each subject. Results and conclusion Control subjects did not show any significant z-score deviations or longitudinal z-score changes. On the other hand, MS patients showed brain regions with cross-sectional and longitudinal concomitant increase in T1, T2, T2* z-scores and decrease of MTR z-scores, suggesting brain tissue degeneration/loss. In the lesion periphery, we observed areas with cross-sectional and longitudinal decreased T1/T2 and slight decrease in T2* most likely related to iron accumulation. Moreover, we measured longitudinal decrease in T1, T2 - and to a lesser extent in T2* - as well as a concomitant increase in MTR, suggesting remyelination/repair. In summary, we have developed a method that provides whole-brain personalized maps of cross-sectional and longitudinal changes in MS patients, which are computed in patient space. These maps may open new perspectives to complement and support radiological evaluation of brain damage for a given patient.
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Affiliation(s)
- G Bonnier
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - E Fischi-Gomez
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
| | - A Roche
- Advanced Clinical Imaging Technology (HC CEMEA SUI DI PI), Siemens Healthcare AG, Switzerland; Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - T Hilbert
- Advanced Clinical Imaging Technology (HC CEMEA SUI DI PI), Siemens Healthcare AG, Switzerland; Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - T Kober
- Advanced Clinical Imaging Technology (HC CEMEA SUI DI PI), Siemens Healthcare AG, Switzerland; Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - G Krueger
- Siemens Healthcare AG (HC CEMEA DI), Zürich, Switzerland
| | - C Granziera
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States; Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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Granziera C, Daducci A, Donati A, Bonnier G, Romascano D, Roche A, Bach Cuadra M, Schmitter D, Klöppel S, Meuli R, von Gunten A, Krueger G. A multi-contrast MRI study of microstructural brain damage in patients with mild cognitive impairment. Neuroimage Clin 2015; 8:631-9. [PMID: 26236628 PMCID: PMC4511616 DOI: 10.1016/j.nicl.2015.06.003] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2015] [Revised: 05/25/2015] [Accepted: 06/07/2015] [Indexed: 11/05/2022]
Abstract
Objectives The aim of this study was to investigate pathological mechanisms underlying brain tissue alterations in mild cognitive impairment (MCI) using multi-contrast 3 T magnetic resonance imaging (MRI). Methods Forty-two MCI patients and 77 healthy controls (HC) underwent T1/T2* relaxometry as well as Magnetization Transfer (MT) MRI. Between-groups comparisons in MRI metrics were performed using permutation-based tests. Using MRI data, a generalized linear model (GLM) was computed to predict clinical performance and a support-vector machine (SVM) classification was used to classify MCI and HC subjects. Results Multi-parametric MRI data showed microstructural brain alterations in MCI patients vs HC that might be interpreted as: (i) a broad loss of myelin/cellular proteins and tissue microstructure in the hippocampus (p ≤ 0.01) and global white matter (p < 0.05); and (ii) iron accumulation in the pallidus nucleus (p ≤ 0.05). MRI metrics accurately predicted memory and executive performances in patients (p ≤ 0.005). SVM classification reached an accuracy of 75% to separate MCI and HC, and performed best using both volumes and T1/T2*/MT metrics. Conclusion Multi-contrast MRI appears to be a promising approach to infer pathophysiological mechanisms leading to brain tissue alterations in MCI. Likewise, parametric MRI data provide powerful correlates of cognitive deficits and improve automatic disease classification based on morphometric features. Forty-two MCI patients and 77 HC underwent multi-contrast quantitative MRI. MCI patients showed T1/T2* increase and MTR decrease in the hippocampus. MCI patients exhibited T1 increase in WM and T2* decrease in the pallidus. MRI metrics accurately predicted memory and executive function in patients. SVM classified MCI patients with 75% accuracy using volumetric/parametric MRI.
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Affiliation(s)
- C Granziera
- Department of Clinical Neurosciences, CHUV, Lausanne, VD, Switzerland ; Advanced Clinical Imaging Technology, EPFL, Lausanne, VD, Switzerland
| | - A Daducci
- STI IEL LTS5, EPFL, Lausanne, VD, Switzerland
| | - A Donati
- Service of Old-Age Psychiatry, Department of Psychiatry, CHUV, Lausanne, VD, Switzerland
| | - G Bonnier
- Advanced Clinical Imaging Technology, EPFL, Lausanne, VD, Switzerland
| | - D Romascano
- Advanced Clinical Imaging Technology, EPFL, Lausanne, VD, Switzerland
| | - A Roche
- Advanced Clinical Imaging Technology, EPFL, Lausanne, VD, Switzerland
| | - M Bach Cuadra
- Department of Radiology, CHUV, Lausanne, VD, Switzerland ; Signal Processing Core, Center for Biomedical Imaging, CHUV, Lausanne, VD, Switzerland
| | - D Schmitter
- Advanced Clinical Imaging Technology, EPFL, Lausanne, VD, Switzerland
| | - S Klöppel
- Department of Psychiatry and Psychotherapy, Section of Gerontopsychiatry, Department of Neurology, University Medical Center, Freiburg, Germany
| | - R Meuli
- Department of Radiology, CHUV, Lausanne, VD, Switzerland
| | - A von Gunten
- Service of Old-Age Psychiatry, Department of Psychiatry, CHUV, Lausanne, VD, Switzerland
| | - G Krueger
- Advanced Clinical Imaging Technology, EPFL, Lausanne, VD, Switzerland ; Heathcare IM S AW, Siemens Schweiz AG, Renens, VD, Switzerland
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Granziera C, D’Arceuil H, Zai L, Magistretti P, Sorensen A, de Crespigny A. Long-term monitoring of post-stroke plasticity after transient cerebral ischemia in mice using in vivo and ex vivo diffusion tensor MRI. Open Neuroimag J 2007; 1:10-7. [PMID: 19018310 PMCID: PMC2577937 DOI: 10.2174/1874440000701010010] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2007] [Revised: 10/11/2007] [Accepted: 10/18/2007] [Indexed: 11/22/2022] Open
Abstract
WE USED A MURINE MODEL OF TRANSIENT FOCAL CEREBRAL ISCHEMIA TO STUDY: 1) in vivo DTI long-term temporal evolution of the apparent diffusion coefficient (ADC) and diffusion fractional anisotropy (FA) at days 4, 10, 15 and 21 after stroke 2) ex vivo distribution of a plasticity-related protein (GAP-43) and its relationship with the ex vivo DTI characteristics of the striato-thalamic pathway (21 days). All animals recovered motor function. In vivo ADC within the infarct was significantly increased after stroke. In the stroke group, GAP-43 expression and FA values were significantly higher in the ipsilateral (IL) striatum and contralateral (CL) hippocampus compared to the shams. DTI tractography showed fiber trajectories connecting the CL striatum to the stroke region, where increased GAP43 and FA were observed and fiber tracts from the CL striatum terminating in the IL hippocampus.Our data demonstrate that DTI changes parallel histological remodeling and recovery of function.
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Affiliation(s)
- C Granziera
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
- Department of Neurology, CHUV, Lausanne, Switzerland
| | - H D’Arceuil
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - L Zai
- Laboratories for Neuroscience Research in Neurosurgery, Children’s Hospital, Harvard Medical School, Charlestown, MA, USA
| | - P.J Magistretti
- Brain Mind Institute, Ecole Polytechnique Federale de Lausanne (EPFL) and Centre de Neurosciences Psychiatriques, Departement de Psychiatrie, CHUV, Lausanne, Switzerland
| | - A.G Sorensen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - A.J de Crespigny
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
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