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Müller J, Lu PJ, Cagol A, Ruberte E, Shin HG, Ocampo-Pineda M, Chen X, Tsagkas C, Barakovic M, Galbusera R, Weigel M, Schaedelin SA, Wang Y, Nguyen TD, Spincemaille P, Kappos L, Kuhle J, Lee J, Granziera C. Quantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions. Neurology 2024; 103:e209604. [PMID: 39213476 PMCID: PMC11362958 DOI: 10.1212/wnl.0000000000209604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 05/20/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Myelin and iron play essential roles in remyelination processes of multiple sclerosis (MS) lesions. χ-separation, a novel biophysical model applied to multiecho T2*-data and T2-data, estimates the contribution of myelin and iron to the obtained susceptibility signal. We used this method to investigate myelin and iron levels in lesion and nonlesion brain areas in patients with MS and healthy individuals. METHODS This prospective MS cohort study included patients with MS fulfilling the McDonald Criteria 2017 and healthy individuals, aged 18 years or older, with no other neurologic comorbidities. Participants underwent MRI at baseline and after 2 years, including multiecho GRE-(T2*) and FAST-(T2) sequences. Using χ-separation, we generated myelin-sensitive and iron-sensitive susceptibility maps. White matter lesions (WMLs), cortical lesions (CLs), surrounding normal-appearing white matter (NAWM), and normal-appearing gray matter were segmented on fluid-attenuated inversion recovery and magnetization-prepared 2 rapid gradient echo images, respectively. Cross-sectional group comparisons used Wilcoxon rank-sum tests, longitudinal analyses applied Wilcoxon signed-rank tests. Associations with clinical outcomes (disease phenotype, age, sex, disease duration, disability measured by Expanded Disability Status Scale [EDSS], neurofilament light chain levels, and T2-lesion number and volume) were assessed using linear regression models. RESULTS Of 168 patients with MS (median [interquartile range (IQR)] age 47.0 [21.7] years; 101 women; 6,898 WMLs, 775 CLs) and 103 healthy individuals (age 33.0 [10.5] years, 57 women), 108 and 62 were followed for a median of 2 years, respectively (IQR 0.1; 5,030 WMLs, 485 CLs). At baseline, WMLs had lower myelin (median 0.025 [IQR 0.015] parts per million [ppm]) and iron (0.017 [0.015] ppm) than the corresponding NAWM (myelin 0.030 [0.012]; iron 0.019 [0.011] ppm; both p < 0.001). After 2 years, both myelin (0.027 [0.014] ppm) and iron had increased (0.018 [0.015] ppm; both p < 0.001). Younger age (p < 0.001, b = -5.111 × 10-5), lower disability (p = 0.04, b = -2.352 × 10-5), and relapsing-remitting phenotype (RRMS, 0.003 [0.01] vs primary progressive 0.002 [IQR 0.01], p < 0.001; vs secondary progressive 0.0004 [IQR 0.01], p < 0.001) at baseline were associated with remyelination. Increment of myelin correlated with clinical improvement measured by EDSS (p = 0.015, b = -6.686 × 10-4). DISCUSSION χ-separation, a novel mathematical model applied to multiecho T2*-images and T2-images shows that young RRMS patients with low disability exhibit higher remyelination capacity, which correlated with clinical disability over a 2-year follow-up.
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Affiliation(s)
- Jannis Müller
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Po-Jui Lu
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Alessandro Cagol
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Esther Ruberte
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Hyeong-Geol Shin
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Mario Ocampo-Pineda
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Xinjie Chen
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Charidimos Tsagkas
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Muhamed Barakovic
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Riccardo Galbusera
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Matthias Weigel
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Sabine A Schaedelin
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Yi Wang
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Thanh D Nguyen
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Pascal Spincemaille
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Ludwig Kappos
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Jens Kuhle
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Jongho Lee
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Cristina Granziera
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
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Bai M, Xiong Z, Zhang Y, Wang Z, Zeng X. Associations between quantitative susceptibility mapping with male obstructive sleep apnea clinical and imaging markers. Sleep Med 2024; 124:154-161. [PMID: 39303362 DOI: 10.1016/j.sleep.2024.09.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 08/31/2024] [Accepted: 09/12/2024] [Indexed: 09/22/2024]
Abstract
PURPOSE To quantitatively measure and compare whole-brain iron deposition between OSA patients and a healthy control group, we initially utilized QSM and evaluated its correlation with PSG results and cognitive function. MATERIALS AND METHODS A total of 28 OSA patients and 22 healthy control subjects matched in age, education level, and BMI were enrolled in our study. Each participant underwent scanning with 3D T1 and multi-echo GRE sequences. Additionally, PSG results were collected from OSA patients, and they underwent simple cognitive assessments. Finally, we analyzed the relationship between iron content in different brain regions, PSG results, and cognitive ability. RESULTS In OSA patients, iron content increased in the left temporal-pole-sup and right putamen, while it decreased in the left fusiform gyrus, left middle temporal gyrus, right inferior occipital gyrus, and right superior temporal gyrus. The correlation analysis between brain iron content and PSG results/cognitive scales is as follows: left fusiform gyrus and MMSE (r = -0.416, p = 0.028); right superior temporal gyrus and MMSE (r = 0.422, p = 0.025); left middle temporal gyrus and average oxygen saturation (r = -0.418, p = 0.027); left temporal-pole-sup and REM stage (rs = 0.466, p = 0.012); the right putamen and N1 stage (rs = 0.393. p = 0.039). Moreover, both MoCA (r = 0.598, p = 0.001) and MMSE (r = 0.456, p = 0.015) show a positive correlation with average oxygen saturation. CONCLUSION This study is the first to use QSM technology to show abnormal brain iron levels in OSA. Correlations between brain iron content, PSG, and cognition in OSA may reveal neuropathological mechanisms, aiding OSA diagnosis.
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Affiliation(s)
- Mingxian Bai
- GuiZhou University Medical College, Guiyang, China; Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China
| | - Zhenliang Xiong
- Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China; College of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Yan Zhang
- Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China; College of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Zhongxin Wang
- Department of Pulmonary and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang, China
| | - Xianchun Zeng
- GuiZhou University Medical College, Guiyang, China; Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China.
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Williams T, John N, Calvi A, Bianchi A, De Angelis F, Doshi A, Wright S, Shatila M, Yiannakas MC, Chowdhury F, Stutters J, Ricciardi A, Prados F, MacManus D, Grussu F, Karsa A, Samson B, Battiston M, Gandini Wheeler-Kingshott CAM, Shmueli K, Ciccarelli O, Barkhof F, Chataway J. Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial. NEUROIMAGE. REPORTS 2024; 4:100216. [PMID: 39328985 PMCID: PMC11422291 DOI: 10.1016/j.ynirp.2024.100216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 08/02/2024] [Accepted: 08/22/2024] [Indexed: 09/28/2024]
Abstract
Background Deep grey matter pathology is a key driver of disability worsening in people with multiple sclerosis. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique which quantifies local magnetic susceptibility from variations in phase produced by changes in the local magnetic field. In the deep grey matter, susceptibility has previously been validated against tissue iron concentration. However, it currently remains unknown whether susceptibility is abnormal in older progressive MS cohorts, and whether it correlates with disability. Objectives To investigate differences in mean regional susceptibility in deep grey matter between people with secondary progressive multiple sclerosis (SPMS) and healthy controls; to examine in patients the relationships between deep grey matter susceptibility and clinical and imaging measures of disease severity. Methods Baseline data from a subgroup of the MS-STAT2 trial (simvastatin vs. placebo in SPMS, NCT03387670) were included. The subgroup underwent clinical assessments and an advanced MRI protocol at 3T. A cohort of age-matched healthy controls underwent the same MRI protocol. Susceptibility maps were reconstructed using a robust QSM pipeline from multi-echo 3D gradient-echo sequence. Regions of interest (ROIs) in the thalamus, globus pallidus and putamen were segmented from 3D T1-weighted images, and lesions segmented from 3D fluid-attenuated inversion recovery images. Linear regression was used to compare susceptibility from ROIs between patients and controls, adjusting for age and sex. Where significant differences were found, we further examined the associations between ROI susceptibility and clinical and imaging measures of MS severity. Results 149 SPMS (77% female; mean age: 53 yrs; median Expanded Disability Status Scale (EDSS): 6.0 [interquartile range 4.5-6.0]) and 33 controls (52% female, mean age: 57) were included.Thalamic susceptibility was significantly lower in SPMS compared to controls: mean (SD) 28.6 (12.8) parts per billion (ppb) in SPMS vs. 39.2 (12.7) ppb in controls; regression coefficient: -12.0 [95% confidence interval: -17.0 to -7.1], p < 0.001. In contrast, globus pallidus and putamen susceptibility were similar between both groups.In SPMS, a 10 ppb lower thalamic susceptibility was associated with a +0.13 [+0.01 to +0.24] point higher EDSS (p < 0.05), a -2.4 [-3.8 to -1.0] point lower symbol digit modality test (SDMT, p = 0.001), and a -2.4 [-3.7 to -1.1] point lower Sloan low contrast acuity, 2.5% (p < 0.01).Lower thalamic susceptibility was also strongly associated with a higher T2 lesion volume (T2LV, p < 0.001) and lower normalised whole brain, deep grey matter and thalamic volumes (all p < 0.001). Conclusions The reduced thalamic susceptibility found in SPMS compared to controls suggests that thalamic iron concentrations are lower at this advanced stage of the disease. The observed relationships between lower thalamic susceptibility and more severe physical, cognitive and visual disability suggests that reductions in thalamic iron may correlate with important mechanisms of clinical disease progression. Such mechanisms appear to intimately link reductions in thalamic iron with higher T2LV and the development of thalamic atrophy, encouraging further research into QSM-derived thalamic susceptibility as a biomarker of disease severity in SPMS.
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Affiliation(s)
- Thomas Williams
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Nevin John
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- Monash University, Department of Medicine, School of Clinical Sciences, Clayton, Australia
| | - Alberto Calvi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Alessia Bianchi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Floriana De Angelis
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Anisha Doshi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Sarah Wright
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Madiha Shatila
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Marios C Yiannakas
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Fatima Chowdhury
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Jon Stutters
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Antonio Ricciardi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
- Universitat Oberta de Catalunya, Barcelona, Spain
| | - David MacManus
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Francesco Grussu
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Anita Karsa
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Becky Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Marco Battiston
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, United Kingdom
| | - Frederik Barkhof
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
- National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, United Kingdom
- Vrije Universiteit Amsterdam, Department of Radiology & Nuclear Medicine, VU University Medical Centre, Amsterdam, Netherlands
| | - Jeremy Chataway
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- Medical Research Council Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, United Kingdom
- National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, United Kingdom
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4
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Yan S, Lu J, Duan B, Zhu H, Liu D, Li L, Qin Y, Li Y, Zhu W. Quantitative susceptibility mapping of multiple system atrophy and Parkinson's disease correlates with neurotransmitter reference maps. Neurobiol Dis 2024; 198:106549. [PMID: 38830476 DOI: 10.1016/j.nbd.2024.106549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 05/29/2024] [Accepted: 05/31/2024] [Indexed: 06/05/2024] Open
Abstract
BACKGROUND Multiple system atrophy (MSA) and Parkinson's disease (PD) are neurodegenerative disorders characterized by α-synuclein pathology, disrupted iron homeostasis and impaired neurochemical transmission. Considering the critical role of iron in neurotransmitter synthesis and transport, our study aims to identify distinct patterns of whole-brain iron accumulation in MSA and PD, and to elucidate the corresponding neurochemical substrates. METHODS A total of 122 PD patients, 58 MSA patients and 78 age-, sex-matched health controls underwent multi-echo gradient echo sequences and neurological evaluations. We conducted voxel-wise and regional analyses using quantitative susceptibility mapping to explore MSA or PD-specific alterations in cortical and subcortical iron concentrations. Spatial correlation approaches were employed to examine the topographical alignment of cortical iron accumulation patterns with normative atlases of neurotransmitter receptor and transporter densities. Furthermore, we assessed the associations between the colocalization strength of neurochemical systems and disease severity. RESULTS MSA patients exhibited increased susceptibility in the striatal, midbrain, cerebellar nuclei, as well as the frontal, temporal, occipital lobes, and anterior cingulate gyrus. In contrast, PD patients displayed elevated iron levels in the left inferior occipital gyrus, precentral gyrus, and substantia nigra. The excessive iron accumulation in MSA or PD correlated with the spatial distribution of cholinergic, noradrenaline, glutamate, serotonin, cannabinoids, and opioid neurotransmitters, and the degree of this alignment was related to motor deficits. CONCLUSIONS Our findings provide evidence of the interaction between iron accumulation and non-dopamine neurotransmitters in the pathogenesis of MSA and PD, which inspires research on potential targets for pharmacotherapy.
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Affiliation(s)
- Su Yan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun Lu
- Department of CT & MRI, The First Affiliated Hospital, College of Medicine, Shihezi University, 107 North Second Road, Shihezi, China
| | - Bingfang Duan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongquan Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dong Liu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Li Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuanyuan Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuanhao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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5
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Xiong Z, Gao Y, Liu Y, Fazlollahi A, Nestor P, Liu F, Sun H. Quantitative susceptibility mapping through model-based deep image prior (MoDIP). Neuroimage 2024; 291:120583. [PMID: 38554781 DOI: 10.1016/j.neuroimage.2024.120583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 03/17/2024] [Accepted: 03/21/2024] [Indexed: 04/02/2024] Open
Abstract
The data-driven approach of supervised learning methods has limited applicability in solving dipole inversion in Quantitative Susceptibility Mapping (QSM) with varying scan parameters across different objects. To address this generalization issue in supervised QSM methods, we propose a novel training-free model-based unsupervised method called MoDIP (Model-based Deep Image Prior). MoDIP comprises a small, untrained network and a Data Fidelity Optimization (DFO) module. The network converges to an interim state, acting as an implicit prior for image regularization, while the optimization process enforces the physical model of QSM dipole inversion. Experimental results demonstrate MoDIP's excellent generalizability in solving QSM dipole inversion across different scan parameters. It exhibits robustness against pathological brain QSM, achieving over 32 % accuracy improvement than supervised deep learning methods. It is also 33 % more computationally efficient and runs 4 times faster than conventional DIP-based approaches, enabling 3D high-resolution image reconstruction in under 4.5 min.
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Affiliation(s)
- Zhuang Xiong
- School of Electrical Engineering and Computer Science, University of Queensland, Brisbane, Australia
| | - Yang Gao
- School of Computer Science and Engineering, Central South University, Changsha, China
| | - Yin Liu
- Department of Radiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Amir Fazlollahi
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Peter Nestor
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Feng Liu
- School of Electrical Engineering and Computer Science, University of Queensland, Brisbane, Australia
| | - Hongfu Sun
- School of Electrical Engineering and Computer Science, University of Queensland, Brisbane, Australia; School of Engineering, University of Newcastle, Newcastle, Australia.
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6
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Niehaus P, Gonzalez de Vega R, Haindl MT, Birkl C, Leoni M, Birkl-Toeglhofer AM, Haybaeck J, Ropele S, Seeba M, Goessler W, Karst U, Langkammer C, Clases D. Multimodal analytical tools for the molecular and elemental characterisation of lesions in brain tissue of multiple sclerosis patients. Talanta 2024; 270:125518. [PMID: 38128277 DOI: 10.1016/j.talanta.2023.125518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 12/01/2023] [Accepted: 12/03/2023] [Indexed: 12/23/2023]
Abstract
Multiple sclerosis (MS) is a prevalent immune-mediated inflammatory disease of the central nervous system inducing a widespread degradation of myelin and resulting in neurological deficits. Recent advances in molecular and atomic imaging provide the means to probe the microenvironment in affected brain tissues at an unprecedented level of detail and may provide new insights. This study showcases state-of-the-art spectroscopic and mass spectrometric techniques to compare distributions of molecular and atomic entities in MS lesions and surrounding brain tissues. MS brains underwent post-mortem magnetic resonance imaging (MRI) to locate and subsequently dissect MS lesions and surrounding white matter. Digests of lesions and unaffected white matter were analysed via ICP-MS/MS revealing significant differences in concentrations of Li, Mg, P, K, Mn, V, Rb, Ag, Gd and Bi. Micro x-ray fluorescence spectroscopy (μXRF) and laser ablation - inductively coupled plasma - time of flight - mass spectrometry (LA-ICP-ToF-MS) were used as micro-analytical imaging techniques to study distributions of both endogenous and xenobiotic elements. The essential trace elements Fe, Cu and Zn were subsequently calibrated using in-house manufactured gelatine standards. Lipid distributions were studied using IR-micro spectroscopy and matrix assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI). MALDI-MSI was complemented with high-resolution tandem mass spectrometry and trapped ion mobility spectroscopy for the annotation of specified phospho- and sphingolipids, revealing specific lipid species decreased in MS lesions compared to surrounding white matter. This explorative study demonstrated that modern molecular and atomic mapping techniques provide high-resolution imaging for relevant bio-indicative entities which may complement our current understanding of the underlying pathophysiological processes.
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Affiliation(s)
- Peter Niehaus
- Institute of Inorganic and Analytical Chemistry, University of Münster, Germany
| | | | | | - Christoph Birkl
- Department of Radiology, Medical University of Innsbruck, Austria
| | - Marlene Leoni
- Diagnostic and Research Center for Molecular Biomedicine, Institute of Pathology, Medical University of Graz, Austria
| | - Anna Maria Birkl-Toeglhofer
- Diagnostic and Research Center for Molecular Biomedicine, Institute of Pathology, Medical University of Graz, Austria; Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Austria
| | - Johannes Haybaeck
- Diagnostic and Research Center for Molecular Biomedicine, Institute of Pathology, Medical University of Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Austria
| | | | | | - Uwe Karst
- Institute of Inorganic and Analytical Chemistry, University of Münster, Germany
| | | | - David Clases
- Institute of Chemistry, University of Graz, Austria.
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7
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Guan X, Lancione M, Ayton S, Dusek P, Langkammer C, Zhang M. Neuroimaging of Parkinson's disease by quantitative susceptibility mapping. Neuroimage 2024; 289:120547. [PMID: 38373677 DOI: 10.1016/j.neuroimage.2024.120547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 02/02/2024] [Accepted: 02/17/2024] [Indexed: 02/21/2024] Open
Abstract
Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.
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Affiliation(s)
- Xiaojun Guan
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Joint Laboratory of Clinical Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 31009, China
| | - Marta Lancione
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Scott Ayton
- Florey Institute, The University of Melbourne, Australia
| | - Petr Dusek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czechia; Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Auenbruggerplatz 22, Prague 8036, Czechia
| | | | - Minming Zhang
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Joint Laboratory of Clinical Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 31009, China.
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8
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Voon CC, Wiltgen T, Wiestler B, Schlaeger S, Mühlau M. Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis. Neuroimage Clin 2024; 42:103598. [PMID: 38582068 PMCID: PMC11002889 DOI: 10.1016/j.nicl.2024.103598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/07/2024] [Accepted: 03/24/2024] [Indexed: 04/08/2024]
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) is a quantitative measure based on magnetic resonance imaging sensitive to iron and myelin content. This makes QSM a promising non-invasive tool for multiple sclerosis (MS) in research and clinical practice. OBJECTIVE We performed a systematic review and meta-analysis on the use of QSM in MS. METHODS Our review was prospectively registered on PROSPERO (CRD42022309563). We searched five databases for studies published between inception and 30th April 2023. We identified 83 English peer-reviewed studies that applied QSM images on MS cohorts. Fifty-five included studies had at least one of the following outcome measures: deep grey matter QSM values in MS, either compared to healthy controls (HC) (k = 13) or correlated with the score on the Expanded Disability Status Scale (EDSS) (k = 7), QSM lesion characteristics (k = 22) and their clinical correlates (k = 17), longitudinal correlates (k = 11), histological correlates (k = 7), or correlates with other imaging techniques (k = 12). Two meta-analyses on deep grey matter (DGM) susceptibility data were performed, while the remaining findings could only be analyzed descriptively. RESULTS After outlier removal, meta-analyses demonstrated a significant increase in the basal ganglia susceptibility (QSM values) in MS compared to HC, caudate (k = 9, standardized mean difference (SDM) = 0.54, 95 % CI = 0.39-0.70, I2 = 46 %), putamen (k = 9, SDM = 0.38, 95 % CI = 0.19-0.57, I2 = 59 %), and globus pallidus (k = 9, SDM = 0.48, 95 % CI = 0.28-0.67, I2 = 60 %), whereas thalamic QSM values exhibited a significant reduction (k = 12, SDM = -0.39, 95 % CI = -0.66--0.12, I2 = 84 %); these susceptibility differences in MS were independent of age. Further, putamen QSM values positively correlated with EDSS (k = 4, r = 0.36, 95 % CI = 0.16-0.53, I2 = 0 %). Regarding rim lesions, four out of seven studies, representing 73 % of all patients, reported rim lesions to be associated with more severe disability. Moreover, lesion development from initial detection to the inactive stage is paralleled by increasing, plateauing (after about two years), and gradually decreasing QSM values, respectively. Only one longitudinal study provided clinical outcome measures and found no association. Histological data suggest iron content to be the primary source of QSM values in DGM and at the edges of rim lesions; further, when also considering data from myelin water imaging, the decrease of myelin is likely to drive the increase of QSM values within WM lesions. CONCLUSIONS We could provide meta-analytic evidence for DGM susceptibility changes in MS compared to HC; basal ganglia susceptibility is increased and, in the putamen, associated with disability, while thalamic susceptibility is decreased. Beyond these findings, further investigations are necessary to establish the role of QSM in MS for research or even clinical routine.
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Affiliation(s)
- Cui Ci Voon
- Dept. of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany; TUM-Neuroimaging Center, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Tun Wiltgen
- Dept. of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany; TUM-Neuroimaging Center, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- Dept. of Neuroradiology, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Sarah Schlaeger
- Dept. of Neuroradiology, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Mark Mühlau
- Dept. of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany; TUM-Neuroimaging Center, School of Medicine and Health, Technical University of Munich, Munich, Germany.
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9
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Voltin J, Nunn LM, Watson Z, Brasher ZE, Adisetiyo V, Hanlon CA, Nietert PJ, McRae-Clark AL, Jensen JH. Comparison of three magnetic resonance imaging measures of brain iron in healthy and cocaine use disorder participants. NMR IN BIOMEDICINE 2024; 37:e5072. [PMID: 38009303 PMCID: PMC10922943 DOI: 10.1002/nbm.5072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/28/2023] [Accepted: 10/23/2023] [Indexed: 11/28/2023]
Abstract
Several magnetic resonance imaging (MRI) measures for quantifying endogenous nonheme brain iron have been proposed. These correspond to distinct physical properties with varying sensitivities and specificities to iron. Moreover, they may depend not only on tissue iron concentration, but also on the intravoxel spatial pattern of iron deposition, which is complex in many brain regions. Here, the three MRI brain iron measures of R 2 * , magnetic field correlation (MFC), and magnetic susceptibility are compared in several deep gray matter regions for both healthy participants (HPs) and individuals with cocaine use disorder (CUD). Their concordance is assessed from their correlations with each other and their relative dependencies on age. In addition, associations between the iron measures and microstructure in adjacent white matter regions are investigated by calculating their correlations with diffusion MRI measures from the internal capsule, and associations with cognition are determined by using results from a battery of standardized tests relevant to CUD. It is found that all three iron measures are strongly correlated with each other for the considered gray matter regions, but with correlation coefficients substantially less than one indicating important differences. The age dependencies of all three measures are qualitatively similar in most regions, except for the red nucleus, where the susceptibility has a significantly stronger correlation with age than R 2 * . Weak to moderate correlations are seen for the iron measures with several of the diffusion and cognitive measures, with the strongest correlations being obtained for R 2 * . The iron measures differ little between the HP and CUD groups, although susceptibility is significantly lower in the red nucleus for the CUD group. For the comparisons made, the iron measures behave similarly in most respects, but with notable quantitative differences. It is suggested that these differences may be, in part, attributable to a higher sensitivity to the spatial pattern of iron deposition for R 2 * and MFC than for susceptibility. This is supported most strongly by a sharp contrast between the values of the iron measures in the globus pallidus relative to those in the red nucleus. The observed correlations of the iron measures with diffusion and cognitive scores point to possible connections between gray matter iron, white matter microstructure, and cognition.
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Affiliation(s)
- Joshua Voltin
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina
- Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina
| | - Lisa M. Nunn
- Department of Psychiatry and Behavioral Science, Medical University of South Carolina, Charleston, South Carolina
| | - Zoe Watson
- Department of Psychiatry and Behavioral Science, Medical University of South Carolina, Charleston, South Carolina
| | - Zoe E. Brasher
- Department of Behavioral Science and Neuroscience, Duke University Medical Center, Durham, North Carolina
| | - Vitria Adisetiyo
- Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina
| | - Colleen A. Hanlon
- Department of Psychiatry and Behavioral Science, Medical University of South Carolina, Charleston, South Carolina
| | - Paul J. Nietert
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina
| | - Aimee L. McRae-Clark
- Department of Psychiatry and Behavioral Science, Medical University of South Carolina, Charleston, South Carolina
| | - Jens H. Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina
- Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
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10
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Celardo G, Scaffei E, Buchignani B, Donatelli G, Costagli M, Cristofani P, Canapicchi R, Pasquariello R, Tosetti M, Battini R, Biagi L. Case report: Exploring chemoradiotherapy-induced leukoencephalopathy with 7T imaging and quantitative susceptibility mapping. Front Neurol 2024; 15:1362704. [PMID: 38419703 PMCID: PMC10899325 DOI: 10.3389/fneur.2024.1362704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 01/29/2024] [Indexed: 03/02/2024] Open
Abstract
Chemotherapy and radiotherapy are widely used in the treatment of central nervous system tumors and acute lymphocytic leukemia even in the pediatric population. However, such treatments run the risk of a broad spectrum of cognitive and neurological deficits. Even though the correlation with cognitive decline is still not clear, neuroradiological defects linked to white matter injury and vasculopathies may be identified. Thanks to the use of 7T MRI it is possible to better define the vascular pattern of the brain lesions with the added advantage of identifying their characteristics and anatomical localization, which, however, are not evident with a conventional brain scan. Moreover, the use of Quantitative Susceptibility Mapping (QSM) makes it possible to discriminate between calcium deposits on vessels (chemo-radiation-induced) and hemoglobin deposition in radio-induced cavernomas, speculating, as a result, about the pathophysiology of iatrogenic brain damage. We describe the case of a 9 year-old boy with a T-type acute lymphoid leukemia who had previously been treated with polychemotherapy and high-dose RT. To better define the child's neuroradiological pattern, 7T MRI and QSM were performed in addition to conventional imaging examinations. Our case report suggests the potential usefulness of a QSM study to distinguish radio-induced vascular malformations from mineralizing microangiopathy.
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Affiliation(s)
- Gaetano Celardo
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Elena Scaffei
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Bianca Buchignani
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Translational Research and of New Surgical and Medical Technologies Pisa University, Pisa, Italy
| | - Graziella Donatelli
- Department of Translational Research and of New Surgical and Medical Technologies Pisa University, Pisa, Italy
- Imago 7 Research Foundation, Pisa, Italy
| | - Mauro Costagli
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Paola Cristofani
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Raffaello Canapicchi
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Rosa Pasquariello
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Michela Tosetti
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Roberta Battini
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Laura Biagi
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
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11
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Domínguez D JF, Stewart A, Burmester A, Akhlaghi H, O'Brien K, Bollmann S, Caeyenberghs K. Improving quantitative susceptibility mapping for the identification of traumatic brain injury neurodegeneration at the individual level. Z Med Phys 2024:S0939-3889(24)00001-1. [PMID: 38336583 DOI: 10.1016/j.zemedi.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 12/19/2023] [Accepted: 01/07/2024] [Indexed: 02/12/2024]
Abstract
BACKGROUND Emerging evidence suggests that traumatic brain injury (TBI) is a major risk factor for developing neurodegenerative disease later in life. Quantitative susceptibility mapping (QSM) has been used by an increasing number of studies in investigations of pathophysiological changes in TBI. However, generating artefact-free quantitative susceptibility maps in brains with large focal lesions, as in the case of moderate-to-severe TBI (ms-TBI), is particularly challenging. To address this issue, we utilized a novel two-pass masking technique and reconstruction procedure (two-pass QSM) to generate quantitative susceptibility maps (QSMxT; Stewart et al., 2022, Magn Reson Med.) in combination with the recently developed virtual brain grafting (VBG) procedure for brain repair (Radwan et al., 2021, NeuroImage) to improve automated delineation of brain areas. We used QSMxT and VBG to generate personalised QSM profiles of individual patients with reference to a sample of healthy controls. METHODS Chronic ms-TBI patients (N = 8) and healthy controls (N = 12) underwent (multi-echo) GRE, and anatomical MRI (MPRAGE) on a 3T Siemens PRISMA scanner. We reconstructed the magnetic susceptibility maps using two-pass QSM from QSMxT. We then extracted values of magnetic susceptibility in grey matter (GM) regions (following brain repair via VBG) across the whole brain and determined if they deviate from a reference healthy control group [Z-score < -3.43 or > 3.43, relative to the control mean], with the aim of obtaining personalised QSM profiles. RESULTS Using two-pass QSM, we achieved susceptibility maps with a substantial increase in quality and reduction in artefacts irrespective of the presence of large focal lesions, compared to single-pass QSM. In addition, VBG minimised the loss of GM regions and exclusion of patients due to failures in the region delineation step. Our findings revealed deviations in magnetic susceptibility measures from the HC group that differed across individual TBI patients. These changes included both increases and decreases in magnetic susceptibility values in multiple GM regions across the brain. CONCLUSIONS We illustrate how to obtain magnetic susceptibility values at the individual level and to build personalised QSM profiles in ms-TBI patients. Our approach opens the door for QSM investigations in more severely injured patients. Such profiles are also critical to overcome the inherent heterogeneity of clinical populations, such as ms-TBI, and to characterize the underlying mechanisms of neurodegeneration at the individual level more precisely. Moreover, this new personalised QSM profiling could in the future assist clinicians in assessing recovery and formulating a neuroscience-guided integrative rehabilitation program tailored to individual TBI patients.
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Affiliation(s)
- Juan F Domínguez D
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
| | - Ashley Stewart
- School of Information Technology and Electrical Engineering, Faculty of Engineering, Architecture, and Information Technology, The University of Queensland, Brisbane, Australia
| | - Alex Burmester
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - Hamed Akhlaghi
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Department of Emergency Medicine, St. Vincent's Hospital, Melbourne, Australia
| | - Kieran O'Brien
- Siemens Healthcare Pty Ltd, Brisbane, Queensland, Australia
| | - Steffen Bollmann
- School of Information Technology and Electrical Engineering, Faculty of Engineering, Architecture, and Information Technology, The University of Queensland, Brisbane, Australia; Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
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12
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Theis H, Pavese N, Rektorová I, van Eimeren T. Imaging Biomarkers in Prodromal and Earliest Phases of Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2024:JPD230385. [PMID: 38339941 DOI: 10.3233/jpd-230385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2024]
Abstract
Assessing imaging biomarker in the prodromal and early phases of Parkinson's disease (PD) is of great importance to ensure an early and safe diagnosis. In the last decades, imaging modalities advanced and are now able to assess many different aspects of neurodegeneration in PD. MRI sequences can measure iron content or neuromelanin. Apart from SPECT imaging with Ioflupane, more specific PET tracers to assess degeneration of the dopaminergic system are available. Furthermore, metabolic PET patterns can be used to anticipate a phenoconversion from prodromal PD to manifest PD. In this regard, it is worth mentioning that PET imaging of inflammation will gain significance. Molecular imaging of neurotransmitters like serotonin, noradrenaline and acetylcholine shed more light on non-motor symptoms. Outside of the brain, molecular imaging of the heart and gut is used to measure PD-related degeneration of the autonomous nervous system. Moreover, optical coherence tomography can noninvasively detect degeneration of retinal fibers as a potential biomarker in PD. In this review, we describe these state-of-the-art imaging modalities in early and prodromal PD and point out in how far these techniques can and will be used in the future to pave the way towards a biomarker-based staging of PD.
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Affiliation(s)
- Hendrik Theis
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany
| | - Nicola Pavese
- Aarhus University, Institute of Clinical Medicine, Department of Nuclear Medicine & PET, Aarhus N, Denmark
- Newcastle University, Translational and Clinical Research Institute, Newcastle upon Tyne, United Kingdom
| | - Irena Rektorová
- Masaryk University, Faculty of Medicine and St. Anne's University Hospital, International Clinical Research Center, ICRC, Brno, Czech Republic
- Masaryk University, Faculty of Medicine and St. Anne's University Hospital, First Department of Neurology, Brno, Czech Republic
- Masaryk University, Applied Neuroscience Research Group, Central European Institute of Technology - CEITEC, Brno, Czech Republic
| | - Thilo van Eimeren
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany
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13
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Satoh R, Ali F, Botha H, Lowe VJ, Josephs KA, Whitwell JL. Direct comparison between 18F-Flortaucipir tau PET and quantitative susceptibility mapping in progressive supranuclear palsy. Neuroimage 2024; 286:120509. [PMID: 38184157 PMCID: PMC10868646 DOI: 10.1016/j.neuroimage.2024.120509] [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: 09/11/2023] [Revised: 12/22/2023] [Accepted: 01/03/2024] [Indexed: 01/08/2024] Open
Abstract
PURPOSE The pattern of flortaucipir tau PET uptake is topographically similar to the pattern of magnetic susceptibility in progressive supranuclear palsy (PSP); both with increased signal in subcortical structures such as the basal ganglia and midbrain, suggesting that they may be closely related. However, their relationship remains unknown since no studies have directly compared these two modalities in the same PSP cohort. We hypothesized that some flortaucipir uptake in PSP is associated with magnetic susceptibility, and hence iron deposition. The aim of this study was to evaluate the regional relationship between flortaucipir uptake and magnetic susceptibility and to examine the effects of susceptibility on flortaucipir uptake in PSP. METHODS Fifty PSP patients and 67 cognitively normal controls were prospectively recruited and underwent three Tesla MRI and flortaucipir tau PET scans. Quantitative susceptibility maps were reconstructed from multi-echo gradient-echo MRI images. Region of interest (ROI) analysis was performed to obtain flortaucipir and susceptibility values in the subcortical regions. Relationships between flortaucipir and susceptibility signals were evaluated using partial correlation analysis in the subcortical ROIs and voxel-based analysis in the whole brain. The effects of susceptibility on flortaucipir uptake were examined by using the framework of mediation analysis. RESULTS Both flortaucipir and susceptibility were greater in PSP compared to controls in the putamen, pallidum, subthalamic nucleus, red nucleus, and cerebellar dentate (p<0.05). The ROI-based and voxel-based analyses showed that these two signals were positively correlated in these five regions (r = 0.36-0.59, p<0.05). Mediation analysis showed that greater flortaucipir uptake was partially explained by susceptibility in the putamen, pallidum, subthalamic nucleus, and red nucleus, and fully explained in the cerebellar dentate. CONCLUSIONS These results suggest that some of the flortaucipir uptake in subcortical regions in PSP is related to iron deposition. These findings will contribute to our understanding of the mechanisms underlying flortaucipir tau PET findings in PSP and other neurodegenerative diseases.
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Affiliation(s)
- Ryota Satoh
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Farwa Ali
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, 200 1st St SW, 55905, Rochester, MN, USA
| | | | - Jennifer L Whitwell
- Department of Radiology, Mayo Clinic, 200 1st St SW, 55905, Rochester, MN, USA.
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14
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Savoie FA, Arpin DJ, Vaillancourt DE. Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here? Curr Neuropharmacol 2024; 22:1583-1605. [PMID: 37533246 PMCID: PMC11284713 DOI: 10.2174/1570159x21666230801140648] [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: 08/10/2022] [Revised: 01/11/2023] [Accepted: 01/13/2023] [Indexed: 08/04/2023] Open
Abstract
Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.
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Affiliation(s)
- Félix-Antoine Savoie
- Department of Applied Physiology and Kinesiology, Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
| | - David J. Arpin
- Department of Applied Physiology and Kinesiology, Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
| | - David E. Vaillancourt
- Department of Applied Physiology and Kinesiology, Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
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15
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Satoh R, Weigand SD, Pham T, Ali F, Arani A, Senjem ML, Jack CR, Whitwell JL, Josephs KA. Magnetic Susceptibility in Progressive Supranuclear Palsy Variants, Parkinson's Disease, and Corticobasal Syndrome. Mov Disord 2023; 38:2282-2290. [PMID: 37772771 PMCID: PMC10840892 DOI: 10.1002/mds.29613] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 09/11/2023] [Indexed: 09/30/2023] Open
Abstract
BACKGROUND Previous studies have shown that magnetic susceptibility is increased in several subcortical regions in progressive supranuclear palsy (PSP). However, it is still unclear how subcortical and cortical susceptibilities vary across different PSP variants, Parkinson's disease (PD), and corticobasal syndrome (CBS). OBJECTIVE This study aims to clarify the susceptibility profiles in the subcortical and cortical regions in different PSP variants, PD, and CBS. METHODS Sixty-four patients, 20 PSP-Richardson syndrome (PSP-RS), 9 PSP-parkinsonism (PSP-P), 7 PSP-progressive gait freezing, 4 PSP-postural instability, 11 PD, and 13 CBS, and 20 cognitively normal control subjects underwent a 3-Tesla magnetic resonance imaging scan to reconstruct quantitative susceptibility maps. Region-of-interest analysis was performed to obtain susceptibility in several subcortical and cortical regions. Bayesian linear mixed effect models were used to estimate susceptibility within group and differences between groups. RESULTS In the subcortical regions, patients with PSP-RS and PSP-P showed greater susceptibility than control subjects in the pallidum, substantia nigra, red nucleus, and cerebellar dentate (P < 0.05). Patients with PSP-RS also showed greater susceptibility than patients with PSP-progressive gait freezing, PD, and CBS in the red nucleus and cerebellar dentate, and patients with PSP-P showed greater susceptibility than PD in the red nucleus. Patients with PSP-postural instability and CBS showed greater susceptibility than control subjects in the pallidum and substantia nigra. No significant differences were observed in any cortical region. CONCLUSIONS The PSP variants and CBS had different patterns of magnetic susceptibility in the subcortical regions. The findings will contribute to our understanding about iron profiles and pathophysiology of PSP and may provide a potential biomarker to differentiate PSP variants, PD, and CBS. © 2023 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Ryota Satoh
- Department of Neurology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Stephen D Weigand
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA
| | - Thu Pham
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Farwa Ali
- Department of Neurology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Arvin Arani
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Matthew L. Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
- Department of Information Technology, Mayo Clinic, Rochester, MN, 55905, USA
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16
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Zhu X, Gao Y, Liu F, Crozier S, Sun H. BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources. Z Med Phys 2023; 33:578-590. [PMID: 36064695 PMCID: PMC10751722 DOI: 10.1016/j.zemedi.2022.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 07/20/2022] [Accepted: 08/10/2022] [Indexed: 11/30/2022]
Abstract
INTRODUCTION Background field removal (BFR) is a critical step required for successful quantitative susceptibility mapping (QSM). However, eliminating the background field in brains containing significant susceptibility sources, such as intracranial hemorrhages, is challenging due to the relatively large scale of the field induced by these pathological susceptibility sources. METHOD This study proposes a new deep learning-based method, BFRnet, to remove the background field in healthy and hemorrhagic subjects. The network is built with the dual-frequency octave convolutions on the U-net architecture, trained with synthetic field maps containing significant susceptibility sources. The BFRnet method is compared with three conventional BFR methods and one previous deep learning method using simulated and in vivo brains from 4 healthy and 2 hemorrhagic subjects. Robustness against acquisition field-of-view (FOV) orientation and brain masking are also investigated. RESULTS For both simulation and in vivo experiments, BFRnet led to the best visually appealing results in the local field and QSM results with the minimum contrast loss and the most accurate hemorrhage susceptibility measurements among all five methods. In addition, BFRnet produced the most consistent local field and susceptibility maps between different sizes of brain masks, while conventional methods depend drastically on precise brain extraction and further brain edge erosions. It is also observed that BFRnet performed the best among all BFR methods for acquisition FOVs oblique to the main magnetic field. CONCLUSION The proposed BFRnet improved the accuracy of local field reconstruction in the hemorrhagic subjects compared with conventional BFR algorithms. The BFRnet method was effective for acquisitions of tilted orientations and retained whole brains without edge erosion as often required by traditional BFR methods.
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Affiliation(s)
- Xuanyu Zhu
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Yang Gao
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Feng Liu
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Stuart Crozier
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Hongfu Sun
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia.
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17
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Nathoo N, Gee M, Nelles K, Burt J, Sun H, Seres P, Wilman AH, Beaulieu C, Ba F, Camicioli R. Quantitative Susceptibility Mapping Changes Relate to Gait Issues in Parkinson's Disease. Can J Neurol Sci 2023; 50:853-860. [PMID: 36351571 DOI: 10.1017/cjn.2022.316] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) demonstrates elevated iron content in Parkinson's disease (PD) patients within the basal ganglia, though it has infrequently been studied in relation to gait difficulties including freezing of gait (FOG). Our purpose was to relate QSM of basal ganglia and extra-basal ganglia structures with qualitative and quantitative gait measures in PD. METHODS This case-control study included PD and cognitively unimpaired (CU) participants from the Comprehensive Assessment of Neurodegeneration and Dementia study. Whole brain QSM was acquired at 3T. Region of interests (ROIs) were drawn blinded manually in the caudate nucleus, putamen, globus pallidus, pulvinar nucleus of the thalamus, red nucleus, substantia nigra, and dentate nucleus. Susceptibilities of ROIs were compared between PD and CU. Items from the FOG questionnaire and quantitative gait measures from PD participants were compared to susceptibilities. RESULTS Twenty-nine participants with PD and 27 CU participants were included. There was no difference in susceptibility values in any ROI when comparing CU versus PD (p > 0.05 for all). PD participants with gait impairment (n = 23) had significantly higher susceptibility in the putamen (p = 0.008), red nucleus (p = 0.01), and caudate nucleus (p = 0.03) compared to those without gait impairment (n = 6). PD participants with FOG (n = 12) had significantly higher susceptibility in the globus pallidus (p = 0.03) compared to those without FOG (n = 17). Among quantitative gait measures, only stride time variability was significantly different between those with and without FOG (p = 0.04). CONCLUSION Susceptibilities in basal ganglia and extra-basal ganglia structures are related to qualitative measures of gait impairment and FOG in PD.
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Affiliation(s)
- Nabeela Nathoo
- Department of Medicine (Neurology), University of Alberta, Edmonton, Alberta, Canada
| | - Myrlene Gee
- Department of Medicine (Neurology), University of Alberta, Edmonton, Alberta, Canada
| | - Krista Nelles
- Department of Medicine (Neurology), University of Alberta, Edmonton, Alberta, Canada
| | - Jacqueline Burt
- Department of Medicine (Neurology), University of Alberta, Edmonton, Alberta, Canada
| | - Hongfu Sun
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Peter Seres
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Fang Ba
- Department of Medicine (Neurology), University of Alberta, Edmonton, Alberta, Canada
| | - Richard Camicioli
- Department of Medicine (Neurology), University of Alberta, Edmonton, Alberta, Canada
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18
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De Lury AD, Bisulca JA, Lee JS, Altaf MD, Coyle PK, Duong TQ. Magnetic resonance imaging detection of deep gray matter iron deposition in multiple sclerosis: A systematic review. J Neurol Sci 2023; 453:120816. [PMID: 37827008 DOI: 10.1016/j.jns.2023.120816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023]
Abstract
Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease involving immune-mediated damage. Iron deposition in deep gray matter (DGM) structures like the thalamus and basal ganglia have been suggested to play a role in MS pathogenesis. Magnetic Resonance Imaging (MRI) imaging methods like T2 and T2* imaging, susceptibility-weighted imaging, and quantitative susceptibility mapping can track iron deposition storage in the brain primarily from ferritin and hemosiderin (paramagnetic iron storage proteins) with varying levels of tissue contrast and sensitivity. In this systematic review, we evaluated the role of DGM iron deposition as detected by MRI techniques in relation to MS-related neuroinflammation and its potential as a novel therapeutic target. We searched through PubMed, Embase, and Web of Science databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, against predetermined inclusion and exclusion criteria. We included 89 articles (n = 6630 patients), and then grouped them into different categories: i) methodological techniques to measure DGM iron, ii) cross-sectional and group comparison of DGM iron content, iii) longitudinal comparisons of DGM iron, iv) associations between DGM iron and other imaging and neurobiological markers, v) associations with disability, and vi) associations with cognitive impairment. The review revealed that iron deposition in DGM is independent yet concurrent with demyelination, and that these iron deposits contribute to MS-related cognitive impairment and disability. Variability in iron distributions appears to rely on a positive feedback loop between inflammation, and release of iron by oligodendrocytes. DGM iron seems to be a promising prognostic biomarker for MS pathophysiology.
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Affiliation(s)
- Amy D De Lury
- Department of Radiology, Albert Einstein College of Medicine and Montefiore Medical Center, 111 East 210(th) Street, Bronx, NY, USA.
| | - Joseph A Bisulca
- Department of Radiology, Albert Einstein College of Medicine and Montefiore Medical Center, 111 East 210(th) Street, Bronx, NY, USA.
| | - Jimmy S Lee
- Department of Radiology, Albert Einstein College of Medicine and Montefiore Medical Center, 111 East 210(th) Street, Bronx, NY, USA.
| | - Muhammad D Altaf
- Department of Radiology, Albert Einstein College of Medicine and Montefiore Medical Center, 111 East 210(th) Street, Bronx, NY, USA.
| | - Patricia K Coyle
- Department of Neurology, Stony Brook University Medical Center, Stony Brook, NY, USA.
| | - Tim Q Duong
- Department of Radiology, Albert Einstein College of Medicine and Montefiore Medical Center, 111 East 210(th) Street, Bronx, NY, USA.
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Yin F, Yan Z, Li Y, Ding S, Wang X, Shi Z, Feng J, Du S, Tan Z, Zeng C. Multimodal Investigation of Deep Gray Matter Nucleus in Patients with Multiple Sclerosis and Their Clinical Correlations: A Multivariate Pattern Analysis Study. J Pers Med 2023; 13:1488. [PMID: 37888099 PMCID: PMC10608176 DOI: 10.3390/jpm13101488] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 09/28/2023] [Accepted: 09/30/2023] [Indexed: 10/28/2023] Open
Abstract
Deep gray matter (DGM) nucleus are involved in patients with multiple sclerosis (MS) and are strongly associated with clinical symptoms. We used machine learning approach to further explore microstructural alterations in DGM of MS patients. One hundred and fifteen MS patients and seventy-one healthy controls (HC) underwent brain MRI. The fractional anisotropy (FA), mean diffusivity (MD), quantitative susceptibility value (QSV) and volumes of the caudate nucleus (CN), putamen (PT), globus pallidus (GP), and thalamus (TH) were measured. Multivariate pattern analysis, based on a machine-learning algorithm, was applied to investigate the most damaged regions. Partial correlation analysis was used to investigate the correlation between MRI quantitative metrics and clinical neurological scores. The area under the curve of FA-based classification model was 0.83, while they were 0.93 for MD and 0.81 for QSV. The Montreal cognitive assessment scores were correlated with the volume of the DGM and the expanded disability status scale scores were correlated with the MD of the GP and PT. The study results indicated that MS patients had involvement of DGM with the CN being the most affected. The atrophy of DGM in MS patients mainly affected cognitive function and the microstructural damage of DGM was mainly correlated with clinical disability.
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Affiliation(s)
- Feiyue Yin
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (F.Y.); (Z.Y.); (Y.L.); (X.W.); (Z.S.); (S.D.); (Z.T.)
| | - Zichun Yan
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (F.Y.); (Z.Y.); (Y.L.); (X.W.); (Z.S.); (S.D.); (Z.T.)
| | - Yongmei Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (F.Y.); (Z.Y.); (Y.L.); (X.W.); (Z.S.); (S.D.); (Z.T.)
| | - Shuang Ding
- Department of Radiology, The Childrens’ Hospital of Chongqing Medical University, Chongqing 400015, China;
| | - Xiaohua Wang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (F.Y.); (Z.Y.); (Y.L.); (X.W.); (Z.S.); (S.D.); (Z.T.)
| | - Zhuowei Shi
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (F.Y.); (Z.Y.); (Y.L.); (X.W.); (Z.S.); (S.D.); (Z.T.)
| | - Jinzhou Feng
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China;
| | - Silin Du
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (F.Y.); (Z.Y.); (Y.L.); (X.W.); (Z.S.); (S.D.); (Z.T.)
| | - Zeyun Tan
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (F.Y.); (Z.Y.); (Y.L.); (X.W.); (Z.S.); (S.D.); (Z.T.)
| | - Chun Zeng
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; (F.Y.); (Z.Y.); (Y.L.); (X.W.); (Z.S.); (S.D.); (Z.T.)
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20
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Alkemade A, Großmann R, Bazin PL, Forstmann BU. Mixed methodology in human brain research: integrating MRI and histology. Brain Struct Funct 2023; 228:1399-1410. [PMID: 37365411 PMCID: PMC10335951 DOI: 10.1007/s00429-023-02675-2] [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: 04/26/2023] [Accepted: 06/20/2023] [Indexed: 06/28/2023]
Abstract
Postmortem magnetic resonance imaging (MRI) can provide a bridge between histological observations and the in vivo anatomy of the human brain. Approaches aimed at the co-registration of data derived from the two techniques are gaining interest. Optimal integration of the two research fields requires detailed knowledge of the tissue property requirements for individual research techniques, as well as a detailed understanding of the consequences of tissue fixation steps on the imaging quality outcomes for both MRI and histology. Here, we provide an overview of existing studies that bridge between state-of-the-art imaging modalities, and discuss the background knowledge incorporated into the design, execution and interpretation of postmortem studies. A subset of the discussed challenges transfer to animal studies as well. This insight can contribute to furthering our understanding of the normal and diseased human brain, and to facilitate discussions between researchers from the individual disciplines.
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Affiliation(s)
- Anneke Alkemade
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
| | - Rosa Großmann
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Birte U Forstmann
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
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21
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Shinkawa N, Takahashi N, Yano K, Sawaguchi A, Sonoda A, Kakizaki E, Yukawa N. A Suggested Mechanism for Green Discoloration of the Postmortem Brain. Am J Forensic Med Pathol 2023; 44:132-135. [PMID: 36943704 DOI: 10.1097/paf.0000000000000822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
ABSTRACT In the putrefied brain, the cortex and basal ganglia show dark-grayish to green discoloration due to sulfhemoglobin formed from hydrogen sulfide (H 2 S) produced by endogenous bacteria and hemoglobin. In this study, we propose and demonstrate another mechanism of green discoloration in the brain. The formalin-fixed brain of a cadaver donated for medical education with no putrefaction was used. Half of the brain was immersed in sodium hydrosulfide solution, to imitate the H 2 S produced by bacteria. This half showed greenish discoloration, mainly in the basal ganglia and cortex. The other half showed positive Perls' Prussian blue staining, mainly in the basal ganglia and cortex. The area of greenish discoloration due to H 2 S and the region positive for Perls' Prussian blue staining coincided. Tissue treatment with strong oxidizing agents is required to liberate heme iron. The positive Perls' Prussian blue staining in this study thus does not reflect heme iron. In conclusion, we considered that non-heme iron compounds physiologically present in the brain and H 2 S represent sources of putrefactive greenish discoloration in the brain.
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Affiliation(s)
| | - Nobuyasu Takahashi
- Division of Ultrastructural Cell Biology, Department of Anatomy, Faculty of Medicine, University of Miyazaki, Miyazaki, Japan
| | - Kiyoko Yano
- From the Section of Legal Medicine, Department of Social Medicine, Faculty of Medicine, University of Miyazaki
| | - Akira Sawaguchi
- Division of Ultrastructural Cell Biology, Department of Anatomy, Faculty of Medicine, University of Miyazaki, Miyazaki, Japan
| | - Ai Sonoda
- From the Section of Legal Medicine, Department of Social Medicine, Faculty of Medicine, University of Miyazaki
| | - Eiji Kakizaki
- From the Section of Legal Medicine, Department of Social Medicine, Faculty of Medicine, University of Miyazaki
| | - Nobuhiro Yukawa
- From the Section of Legal Medicine, Department of Social Medicine, Faculty of Medicine, University of Miyazaki
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22
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Li J, Guan X, Wu Q, He C, Zhang W, Lin X, Liu C, Wei H, Xu X, Zhang Y. Direct localization and delineation of human pedunculopontine nucleus based on a self-supervised magnetic resonance image super-resolution method. Hum Brain Mapp 2023; 44:3781-3794. [PMID: 37186095 DOI: 10.1002/hbm.26311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/24/2023] [Accepted: 03/30/2023] [Indexed: 05/17/2023] Open
Abstract
The pedunculopontine nucleus (PPN) is a small brainstem structure and has attracted attention as a potentially effective deep brain stimulation (DBS) target for the treatment of Parkinson's disease (PD). However, the in vivo location of PPN remains poorly described and barely visible on conventional structural magnetic resonance (MR) images due to a lack of high spatial resolution and tissue contrast. This study aims to delineate the PPN on a high-resolution (HR) atlas and investigate the visibility of the PPN in individual quantitative susceptibility mapping (QSM) images. We combine a recently constructed Montreal Neurological Institute (MNI) space unbiased QSM atlas (MuSus-100), with an implicit representation-based self-supervised image super-resolution (SR) technique to achieve an atlas with improved spatial resolution. Then guided by a myelin staining histology human brain atlas, we localize and delineate PPN on the atlas with improved resolution. Furthermore, we examine the feasibility of directly identifying the approximate PPN location on the 3.0-T individual QSM MR images. The proposed SR network produces atlas images with four times the higher spatial resolution (from 1 to 0.25 mm isotropic) without a training dataset. The SR process also reduces artifacts and keeps superb image contrast for further delineating small deep brain nuclei, such as PPN. Using the myelin staining histological atlas as guidance, we first identify and annotate the location of PPN on the T1-weighted (T1w)-QSM hybrid MR atlas with improved resolution in the MNI space. Then, we relocate and validate that the optimal targeting site for PPN-DBS is at the middle-to-caudal part of PPN on our atlas. Furthermore, we confirm that the PPN region can be identified in a set of individual QSM images of 10 patients with PD and 10 healthy young adults. The contrast ratios of the PPN to its adjacent structure, namely the medial lemniscus, on images of different modalities indicate that QSM substantially improves the visibility of the PPN both in the atlas and individual images. Our findings indicate that the proposed SR network is an efficient tool for small-size brain nucleus identification. HR QSM is promising for improving the visibility of the PPN. The PPN can be directly identified on the individual QSM images acquired at the 3.0-T MR scanners, facilitating a direct targeting of PPN for DBS surgery.
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Affiliation(s)
- Jun Li
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qing Wu
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Chenyu He
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Weimin Zhang
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Xiyue Lin
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, California, USA
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, California, USA
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuyao Zhang
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
- Ihuman Institute, ShanghaiTech University, Shanghai, China
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23
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Satoh R, Arani A, Senjem ML, Duffy JR, Clark HM, Utianski RL, Botha H, Machulda MM, Jack CR, Whitwell JL, Josephs KA. Spatial patterns of elevated magnetic susceptibility in progressive apraxia of speech. Neuroimage Clin 2023; 38:103394. [PMID: 37003130 PMCID: PMC10102559 DOI: 10.1016/j.nicl.2023.103394] [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: 01/19/2023] [Revised: 03/23/2023] [Accepted: 03/27/2023] [Indexed: 03/30/2023]
Abstract
PURPOSE Progressive apraxia of speech (PAOS) is a neurodegenerative disorder affecting the planning or programming of speech. Little is known about its magnetic susceptibility profiles indicative of biological processes such as iron deposition and demyelination. This study aims to clarify (1) the pattern of susceptibility in PAOS patients, (2) the susceptibility differences between the phonetic (characterized by predominance of distorted sound substitutions and additions) and prosodic (characterized by predominance of slow speech rate and segmentation) subtypes of PAOS, and (3) the relationships between susceptibility and symptom severity. METHODS Twenty patients with PAOS (nine phonetic and eleven prosodic subtypes) were prospectively recruited and underwent a 3 Tesla MRI scan. They also underwent detailed speech, language, and neurological evaluations. Quantitative susceptibility maps (QSM) were reconstructed from multi-echo gradient echo MRI images. Region of interest analysis was conducted to estimate susceptibility coefficients in several subcortical and frontal regions. We compared susceptibility values between PAOS and an age-matched control group and performed a correlation analysis between susceptibilities and an apraxia of speech rating scale (ASRS) phonetic and prosodic feature ratings. RESULTS The magnetic susceptibility of PAOS was statistically greater than that of controls in subcortical regions (left putamen, left red nucleus, and right dentate nucleus) (p < 0.01, also survived FDR correction) and in the left white-matter precentral gyrus (p < 0.05, but not survived FDR correction). The prosodic patients showed greater susceptibilities than controls in these subcortical and precentral regions. The susceptibility in the left red nucleus and in the left precentral gyrus correlated with the prosodic sub-score of the ASRS. CONCLUSION Magnetic susceptibility in PAOS patients was greater than controls mainly in the subcortical regions. While larger samples are needed before QSM is considered ready for clinical differential diagnosis, the present study contributes to our understanding of magnetic susceptibility changes and the pathophysiology of PAOS.
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Affiliation(s)
- Ryota Satoh
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Arvin Arani
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA; Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Joseph R Duffy
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
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24
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Marxreiter F, Lambrecht V, Mennecke A, Hanspach J, Jukic J, Regensburger M, Herrler J, German A, Kassubek J, Grön G, Müller HP, Laun FB, Dörfler A, Winkler J, Schmidt MA. Parkinson's disease or multiple system atrophy: potential separation by quantitative susceptibility mapping. Ther Adv Neurol Disord 2023; 16:17562864221143834. [PMID: 36846471 PMCID: PMC9950607 DOI: 10.1177/17562864221143834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 11/08/2022] [Indexed: 02/24/2023] Open
Abstract
Background Due to the absence of robust biomarkers, and the low sensitivity and specificity of routine imaging techniques, the differential diagnosis between Parkinson's disease (PD) and multiple system atrophy (MSA) is challenging. High-field magnetic resonance imaging (MRI) opened up new possibilities regarding the analysis of pathological alterations associated with neurodegenerative processes. Recently, we have shown that quantitative susceptibility mapping (QSM) enables visualization and quantification of two major histopathologic hallmarks observed in MSA: reduced myelin density and iron accumulation in the basal ganglia of a transgenic murine model of MSA. It is therefore emerging as a promising imaging modality on the differential diagnosis of Parkinsonian syndromes. Objectives To assess QSM on high-field MRI for the differential diagnosis of PD and MSA. Methods We assessed 23 patients (nine PDs and 14 MSAs) and nine controls using QSM on 3T and 7T MRI scanners at two academic centers. Results We observed increased susceptibility in MSA at 3T in prototypical subcortical and brainstem regions. Susceptibility measures of putamen, pallidum, and substantia nigra reached excellent diagnostic accuracy to separate both synucleinopathies. Increase toward 100% sensitivity and specificity was achieved using 7T MRI in a subset of patients. Magnetic susceptibility correlated with age in all groups, but not with disease duration in MSA. Sensitivity and specificity were particularly high for possible MSA, and reached 100% in the putamen. Conclusion Putaminal susceptibility measures, in particular on ultra-high-field MRI, may distinguish MSA patients from both, PD and controls, allowing an early and sensitive diagnosis of MSA.
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Affiliation(s)
| | | | - Angelika Mennecke
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany
| | - Jannis Hanspach
- Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Jelena Jukic
- Department of Molecular Neurology, University
Hospital Erlangen, Erlangen, Germany
| | - Martin Regensburger
- Department of Molecular Neurology, University
Hospital Erlangen, Erlangen, Germany,Center for Rare Diseases, University Hospital
Erlangen, Erlangen, Germany
| | - Juergen Herrler
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany,Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Alexander German
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany,Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Jan Kassubek
- Department of Neurology, Ulm University, Ulm,
Germany
| | - Georg Grön
- Department of Psychiatry and Psychotherapy
III, Ulm University, Ulm, Germany
| | | | - Frederik B. Laun
- Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Arnd Dörfler
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany
| | - Juergen Winkler
- Department of Molecular Neurology, University
Hospital Erlangen, Erlangen, Germany,Center for Rare Diseases, University Hospital
Erlangen, Erlangen, Germany
| | - Manuel A. Schmidt
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany
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25
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Hu R, Gao B, Tian S, Liu Y, Jiang Y, Li W, Li Y, Song Q, Wang W, Miao Y. Regional high iron deposition on quantitative susceptibility mapping correlates with cognitive decline in type 2 diabetes mellitus. Front Neurosci 2023; 17:1061156. [PMID: 36793541 PMCID: PMC9922715 DOI: 10.3389/fnins.2023.1061156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 01/10/2023] [Indexed: 01/31/2023] Open
Abstract
Objective To quantitatively evaluate the iron deposition and volume changes in deep gray nuclei according to threshold-method of quantitative susceptibility mapping (QSM) acquired by strategically acquired gradient echo (STAGE) sequence, and to analyze the correlation between the magnetic susceptibility values (MSV) and cognitive scores in type 2 diabetes mellitus (T2DM) patients. Methods Twenty-nine patients with T2DM and 24 healthy controls (HC) matched by age and gender were recruited in this prospective study. QSM images were used to evaluate whole-structural volumes (Vwh), regional magnetic susceptibility values (MSVRII), and volumes (VRII) in high-iron regions in nine gray nuclei. All QSM data were compared between groups. Receiver operating characteristic (ROC) analysis was used to assess the discriminating ability between groups. The predictive model from single and combined QSM parameters was also established using logistic regression analysis. The correlation between MSVRII and cognitive scores was further analyzed. Multiple comparisons of all statistical values were corrected by false discovery rate (FDR). A statistically significant P-value was set at 0.05. Results Compared with HC group, the MSVRII of all gray matter nuclei in T2DM were increased by 5.1-14.8%, with significant differences found in bilateral head of caudate nucleus (HCN), right putamen (PUT), right globus pallidus (GP), and left dentate nucleus (DN) (P < 0.05). The Vwh of most gray nucleus in T2DM group were decreased by 1.5-16.9% except bilateral subthalamic nucleus (STN). Significant differences were found in bilateral HCN, bilateral red nucleus (RN), and bilateral substantia nigra (SN) (P < 0.05). VRII was increased in bilateral GP, bilateral PUT (P < 0.05). VRII/Vwh was also increased in bilateral GP, bilateral PUT, bilateral SN, left HCN and right STN (P < 0.05). Compared with the single QSM parameter, the combined parameter showed the largest area under curve (AUC) of 0.86, with a sensitivity of 87.5% and specificity of 75.9%. The MSVRII in the right GP was strongly associated with List A Long-delay free recall (List A LDFR) scores (r = -0.590, P = 0.009). Conclusion In T2DM patients, excessive and heterogeneous iron deposition as well as volume loss occurs in deep gray nuclei. The MSV in high iron regions can better evaluate the distribution of iron, which is related to the decline of cognitive function.
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26
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Association between Beta Oscillations from Subthalamic Nucleus and Quantitative Susceptibility Mapping in Deep Gray Matter Structures in Parkinson's Disease. Brain Sci 2023; 13:brainsci13010081. [PMID: 36672062 PMCID: PMC9857066 DOI: 10.3390/brainsci13010081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/15/2022] [Accepted: 12/27/2022] [Indexed: 01/03/2023] Open
Abstract
This study aimed to investigate the association between beta oscillations and brain iron deposition. Beta oscillations were filtered from the microelectrode recordings of local field potentials (LFP) in the subthalamic nucleus (STN), and the ratio of the power spectral density of beta oscillations (PSDXb) to that of the LFP signals was calculated. Iron deposition in the deep gray matter (DGM) structures was indirectly assessed using quantitative susceptibility mapping (QSM). The Unified Parkinson's Disease Rating Scale (UPDRS), part III, was used to assess the severity of symptoms. Spearman correlation coefficients were applied to assess the associations of PSDXb with QSM values in the DGM structures and the severity of symptoms. PSDXb showed a significant positive correlation with the average QSM values in DGM structures, including caudate and substantia nigra (SN) (p = 0.008 and 0.044). Similarly, the PSDXb showed significant negative correlations with the severity of symptoms, including axial symptoms and the gait in the medicine-off state (p = 0.006 for both). The abnormal iron metabolism in the SN and striatum pathways may be one of the underlying mechanisms for the occurrence of abnormal beta oscillations in the STN, and beta oscillations may serve as important pathophysiological biomarkers of PD.
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27
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Spence H, McNeil CJ, Waiter GD. Cognition and brain iron deposition in whole grey matter regions and hippocampal subfields. Eur J Neurosci 2022; 56:6039-6054. [PMID: 36215153 PMCID: PMC10092357 DOI: 10.1111/ejn.15838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/26/2022] [Accepted: 10/03/2022] [Indexed: 12/29/2022]
Abstract
Regional brain iron accumulation is observed in many neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease, and is associated with cognitive decline. We explored associations between age, cognition and iron content in grey matter regions and hippocampal subfields in 380 participants of the Aberdeen children of the 1950s cohort and their first-generation relatives (aged 26-72 years). Participants underwent cognitive assessment at the time of MRI scanning. Quantitative susceptibility mapping of these MRI data was used to assess iron content in grey matter regions and in hippocampal subfields. Principle component analysis was performed on cognitive test scores to create a general cognition score. Spline analysis was used with the Akaike information criterion to determine if order 1, 2 or 3 natural splines were optimal for assessing non-linear relationships between regional iron and age. Multivariate linear models were used to assess associations between regional iron and cognition. Higher iron correlated with older age in the left putamen across all ages and in the right putamen of only participants over 58. Whereas a decrease in iron with older age was observed in the right thalamus and left pallidum across all ages. Right amygdala iron levels were associated with poorer general cognition scores and poorer immediate recall scores. Iron was not associated with any measures of cognitive performance in other regions of interest. Our results suggest that, whilst iron in some regions was associated with cognitive performance, there is an overall lack of association between regional iron content and cognitive ability in cognitively healthy individuals.
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Affiliation(s)
- Holly Spence
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Chris J McNeil
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Gordon D Waiter
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
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28
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Naji N, Lauzon ML, Seres P, Stolz E, Frayne R, Lebel C, Beaulieu C, Wilman AH. Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads. NMR IN BIOMEDICINE 2022; 35:e4788. [PMID: 35704837 DOI: 10.1002/nbm.4788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/28/2022] [Accepted: 06/05/2022] [Indexed: 06/15/2023]
Abstract
Iron concentration in the human brain plays a crucial role in several neurodegenerative diseases and can be monitored noninvasively using quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R2 *) mapping from multiecho T2 *-weighted images. Large population studies enable better understanding of pathologies and can benefit from pooling multisite data. However, reproducibility may be compromised between sites and studies using different hardware and sequence protocols. This work investigates QSM and R2 * reproducibility at 3 T using locally optimized sequences from three centers and two vendors, and investigates possible reduction of cross-site variability through postprocessing approaches. Twenty-four healthy subjects traveled between three sites and were scanned twice at each site. Scan-rescan measurements from seven deep gray matter regions were used for assessing within-site and cross-site reproducibility using intraclass correlation coefficient (ICC) and within-subject standard deviation (SDw) measures. In addition, multiple QSM and R2 * postprocessing options were investigated with the aim to minimize cross-site sequence-related variations, including: mask generation approach, echo-timing selection, harmonizing spatial resolution, field map estimation, susceptibility inversion method, and linear field correction for magnitude images. The same-subject cross-site region of interest measurements for QSM and R2 * were highly correlated (R2 ≥ 0.94) and reproducible (mean ICC of 0.89 and 0.82 for QSM and R2 *, respectively). The mean cross-site SDw was 4.16 parts per billion (ppb) for QSM and 1.27 s-1 for R2 *. For within-site measurements of QSM and R2 *, the mean ICC was 0.97 and 0.87 and mean SDw was 2.36 ppb and 0.97 s-1 , respectively. The precision level is regionally dependent and is reduced in the frontal lobe, near brain edges, and in white matter regions. Cross-site QSM variability (mean SDw) was reduced up to 46% through postprocessing approaches, such as masking out less reliable regions, matching available echo timings and spatial resolution, avoiding the use of the nonconsistent magnitude contrast between scans in field estimation, and minimizing streaking artifacts.
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Affiliation(s)
- Nashwan Naji
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - M Louis Lauzon
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Peter Seres
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Emily Stolz
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Richard Frayne
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Catherine Lebel
- Department of Radiology, Alberta Children's Hospital Research Institute and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
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29
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Ravanfar P, Syeda WT, Jayaram M, Rushmore RJ, Moffat B, Lin AP, Lyall AE, Merritt AH, Yaghmaie N, Laskaris L, Luza S, Opazo CM, Liberg B, Chakravarty MM, Devenyi GA, Desmond P, Cropley VL, Makris N, Shenton ME, Bush AI, Velakoulis D, Pantelis C. In Vivo 7-Tesla MRI Investigation of Brain Iron and Its Metabolic Correlates in Chronic Schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:86. [PMID: 36289238 PMCID: PMC9605948 DOI: 10.1038/s41537-022-00293-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 09/30/2022] [Indexed: 06/16/2023]
Abstract
Brain iron is central to dopaminergic neurotransmission, a key component in schizophrenia pathology. Iron can also generate oxidative stress, which is one proposed mechanism for gray matter volume reduction in schizophrenia. The role of brain iron in schizophrenia and its potential link to oxidative stress has not been previously examined. In this study, we used 7-Tesla MRI quantitative susceptibility mapping (QSM), magnetic resonance spectroscopy (MRS), and structural T1 imaging in 12 individuals with chronic schizophrenia and 14 healthy age-matched controls. In schizophrenia, there were higher QSM values in bilateral putamen and higher concentrations of phosphocreatine and lactate in caudal anterior cingulate cortex (caCC). Network-based correlation analysis of QSM across corticostriatal pathways as well as the correlation between QSM, MRS, and volume, showed distinct patterns between groups. This study introduces increased iron in the putamen in schizophrenia in addition to network-wide disturbances of iron and metabolic status.
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Affiliation(s)
- Parsa Ravanfar
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Warda T Syeda
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Mahesh Jayaram
- Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, Australia
| | - R Jarrett Rushmore
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Morphometric Analysis (CMA), Massachusetts General Hospital, Charlestown, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Bradford Moffat
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC, Australia
| | - Alexander P Lin
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Amanda E Lyall
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Antonia H Merritt
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Negin Yaghmaie
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC, Australia
- Department of Biomedical Engineering, The University of Melbourne, Parkville, VIC, Australia
| | - Liliana Laskaris
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Sandra Luza
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience & Mental Health, and The University of Melbourne, Parkville, VIC, Australia
| | - Carlos M Opazo
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience & Mental Health, and The University of Melbourne, Parkville, VIC, Australia
| | - Benny Liberg
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - M Mallar Chakravarty
- Cerebral Imaging Center, Douglas Research Centre, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Gabriel A Devenyi
- Cerebral Imaging Center, Douglas Research Centre, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Patricia Desmond
- Department of Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Vanessa L Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Nikos Makris
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Morphometric Analysis (CMA), Massachusetts General Hospital, Charlestown, MA, USA
| | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ashley I Bush
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience & Mental Health, and The University of Melbourne, Parkville, VIC, Australia
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia.
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30
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Mao Z, Yu Y. Diagnostic Performance of Putaminal Hypointensity on Susceptibility MRI in Distinguishing Parkinson Disease from Progressive Supranuclear Palsy: A Meta-Analysis. Mov Disord Clin Pract 2022; 10:168-174. [PMID: 36825057 PMCID: PMC9941919 DOI: 10.1002/mdc3.13573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 08/21/2022] [Accepted: 08/31/2022] [Indexed: 11/11/2022] Open
Abstract
Background Idiopathic Parkinson's disease (IPD) and progressive supranuclear palsy (PSP) have similar clinical signs and symptoms, making accurate clinical diagnosis difficult. T2* gradient echo (T2* GRE), susceptibility-weighted imaging (SWI), and quantitative susceptibility mapping (QSM) are susceptibility MR imaging sequences that provide more information about brain iron levels than other conventional MR imaging. Objective This study aimed to evaluate the diagnostic power of putaminal hypointensity on T2* GRE, SWI, and QSM in distinguishing PSP from IPD. Methods Eligible studies were identified via systematic searches of PubMed and Clarivate Analytics® Web of Science® Core Collection. Studies that satisfied the inclusion and exclusion criteria were reviewed. A meta-analysis was conducted using the hierarchical summary receiver operating characteristic curve approach. Results Our literature search of the two databases yielded 562 primary articles, 10 of which were deemed relevant and only six were eligible for further analyses. We performed a meta-analysis of putaminal hypointensity measurements: 438 patients with IPD and 109 patients with PSP were enrolled in the quantitative synthesis. The meta-analysis of six studies with 547 patients revealed a sensitivity of 69% (95% confidence interval (CI): 33%-90%) and specificity of 91% (95% CI: 80%-96%) for putaminal hypointensity on T2* GRE, SWI, or QSM distinguishing PSP from IPD. Conclusions Putaminal hypointensity on T2* GRE, SWI, or QSM is able to distinguish patients with PSP from those with IPD with high specificity. Further multicenter prospective studies on patients are needed to verify our results.
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Affiliation(s)
- Zhijuan Mao
- Department of NeurologyTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
| | - Ying Yu
- Department of NeurologyTongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
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31
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Nakhid D, McMorris C, Sun H, Gibbard WB, Tortorelli C, Lebel C. Brain volume and magnetic susceptibility differences in children and adolescents with prenatal alcohol exposure. Alcohol Clin Exp Res 2022; 46:1797-1807. [PMID: 36016464 DOI: 10.1111/acer.14928] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 08/09/2022] [Accepted: 08/18/2022] [Indexed: 02/01/2023]
Abstract
BACKGROUND Prenatal alcohol exposure (PAE) can negatively affect brain development thereby increasing the risk of cognitive deficits, behavioral challenges, and mental health problems. Brain iron is important for a number of physiological processes for healthy brain development. Animal studies show that PAE reduced brain iron; however, this has not been investigated in human children with PAE. METHODS We studied 20 children and adolescents with PAE and 44 unexposed children and adolescents aged 7.5 to 15 years. All children underwent quantitative susceptibility mapping and T1-weighted magnetic resonance imaging scans. Susceptibility and volume measurements of the caudate, putamen, pallidum, thalamus, amygdala, hippocampus, and nucleus accumbens were extracted using FreeSurfer. ANCOVAs were used to compare volume and susceptibility between groups for each region of interest, controlling for age and gender. For structures where susceptibility differed by group, we also tested for an association between intelligence quotient (IQ) and susceptibility. RESULTS There were no significant group differences in susceptibility after multiple comparison correction, though the PAE group had higher susceptibility in the thalamus compared to unexposed participants before correction (p = 0.032, q = 0.230). There was no association between IQ and thalamus susceptibility. The PAE group had significantly lower volume in the bilateral caudate, bilateral pallidum, and left putamen. CONCLUSIONS These findings suggest susceptibility may be altered in children and adolescents with PAE, though more research is needed. Volume reductions are consistent with previous literature and likely underlie cognitive and behavioral deficits associated with PAE.
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Affiliation(s)
- Daphne Nakhid
- Department of Neuroscience, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute (ACHRI), University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Carly McMorris
- Alberta Children's Hospital Research Institute (ACHRI), University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,School and Applied Child Psychology, Werklund School of Education, University of Calgary, Calgary, Alberta, Canada.,Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Hongfu Sun
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Queensland, Australia
| | - William Benton Gibbard
- Alberta Children's Hospital Research Institute (ACHRI), University of Calgary, Calgary, Alberta, Canada.,Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Christina Tortorelli
- Department of Child Studies and Social Work, Mount Royal University, Calgary, Alberta, Canada
| | - Catherine Lebel
- Alberta Children's Hospital Research Institute (ACHRI), University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Department of Radiology, University of Calgary, Calgary, Alberta, Canada
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32
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Zachariou V, Bauer CE, Pappas C, Gold BT. High cortical iron is associated with the disruption of white matter tracts supporting cognitive function in healthy older adults. Cereb Cortex 2022; 33:4815-4828. [PMID: 36182267 PMCID: PMC10110441 DOI: 10.1093/cercor/bhac382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/29/2022] [Accepted: 08/30/2022] [Indexed: 01/25/2023] Open
Abstract
Aging is associated with brain iron accumulation, which has been linked to cognitive decline. However, how brain iron affects the structure and function of cognitive brain networks remains unclear. Here, we explored the possibility that iron load in gray matter is associated with disruption of white matter (WM) microstructure within a network supporting cognitive function, in a cohort of 95 cognitively normal older adults (age range: 60-86). Functional magnetic resonance imaging was used to localize a set of brain regions involved in working memory and diffusion tensor imaging based probabilistic tractography was used to identify a network of WM tracts connecting the functionally defined regions. Brain iron concentration within these regions was evaluated using quantitative susceptibility mapping and microstructural properties were assessed within the identified tracts using neurite orientation dispersion and density imaging. Results indicated that high brain iron concentration was associated with low neurite density (ND) within the task-relevant WM network. Further, regional associations were observed such that brain iron in cortical regions was linked with lower ND in neighboring but not distant WM tracts. Our results provide novel evidence suggesting that age-related increases in brain iron concentration are associated with the disruption of WM tracts supporting cognitive function in normal aging.
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Affiliation(s)
- Valentinos Zachariou
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States
| | - Christopher E Bauer
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States
| | - Colleen Pappas
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States
| | - Brian T Gold
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States.,Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40536-0298, United States.,Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, KY 40536-0298, United States
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Iron Deposition in Brain: Does Aging Matter? Int J Mol Sci 2022; 23:ijms231710018. [PMID: 36077413 PMCID: PMC9456423 DOI: 10.3390/ijms231710018] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/30/2022] [Accepted: 08/30/2022] [Indexed: 11/17/2022] Open
Abstract
The alteration of iron homeostasis related to the aging process is responsible for increased iron levels, potentially leading to oxidative cellular damage. Iron is modulated in the Central Nervous System in a very sensitive manner and an abnormal accumulation of iron in the brain has been proposed as a biomarker of neurodegeneration. However, contrasting results have been presented regarding brain iron accumulation and the potential link with other factors during aging and neurodegeneration. Such uncertainties partly depend on the fact that different techniques can be used to estimate the distribution of iron in the brain, e.g., indirect (e.g., MRI) or direct (post-mortem estimation) approaches. Furthermore, recent evidence suggests that the propensity of brain cells to accumulate excessive iron as a function of aging largely depends on their anatomical location. This review aims to collect the available data on the association between iron concentration in the brain and aging, shedding light on potential mechanisms that may be helpful in the detection of physiological neurodegeneration processes and neurodegenerative diseases such as Alzheimer's disease.
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Distinct brain iron profiles associated with logopenic progressive aphasia and posterior cortical atrophy. Neuroimage Clin 2022; 36:103161. [PMID: 36029670 PMCID: PMC9428862 DOI: 10.1016/j.nicl.2022.103161] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 08/05/2022] [Accepted: 08/18/2022] [Indexed: 12/14/2022]
Abstract
Quantitative susceptibility mapping (QSM) can detect iron distribution in the brain by estimating local tissue magnetic susceptibility properties at every voxel. Iron deposition patterns are well studied in typical Alzheimer's disease (tAD), but little is known about these patterns in atypical clinical presentations of AD such as logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA). Seventeen PCA patients and eight LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent MRI that included a five-echo gradient echo sequence for calculation of QSM. Mean QSM signal was extracted from gray and white matter for regions-of-interest across the brain using the Mayo Clinic Adult Lifespan Template. Bayesian hierarchical models were fit per-region and per-hemisphere to compare PCA, LPA, 63 healthy controls, and 20 tAD patients. Strong evidence (posterior probability > 0.99) was observed for greater susceptibility in the middle occipital gyrus and amygdala in both LPA and PCA, and in the right inferior parietal, inferior temporal, and angular gyri in PCA and the caudate and substantia nigra in LPA compared to controls. Moderate evidence for greater susceptibility (posterior probability > 0.90) was also observed in the inferior occipital gyrus, precuneus, putamen and entorhinal cortex in both LPA and PCA, along with superior frontal gyrus in PCA and inferior temporal gyri, insula and basal ganglia in LPA, when compared to controls. Between phenotypic comparisons, LPA had greater susceptibility in the caudate, hippocampus, and posterior cingulate compared to PCA, while PCA showed greater susceptibility in the right superior frontal and middle temporal gyri compared to LPA. Both LPA and PCA showed moderate and strong evidence for greater susceptibility than tAD, particularly in medial and lateral parietal regions, while tAD showed greater susceptibility in the hippocampus and basal ganglia. This study proposes the possibility of unique iron profiles existing between LPA and PCA within cortical and subcortical structures. These changes match well with the disease-related changes of the clinical phenotypes, suggesting that QSM could be an informative candidate marker to study iron deposition in these patients.
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Lancione M, Donatelli G, Del Prete E, Campese N, Frosini D, Cencini M, Costagli M, Biagi L, Lucchi G, Tosetti M, Godani M, Arnaldi D, Terzaghi M, Provini F, Pacchetti C, Cortelli P, Bonanni E, Ceravolo R, Cosottini M. Evaluation of iron overload in nigrosome 1 via quantitative susceptibility mapping as a progression biomarker in prodromal stages of synucleinopathies. Neuroimage 2022; 260:119454. [PMID: 35810938 DOI: 10.1016/j.neuroimage.2022.119454] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 06/17/2022] [Accepted: 07/05/2022] [Indexed: 10/17/2022] Open
Abstract
Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies, such as Parkinson's disease (PD), which are characterized by the loss of dopaminergic neurons in substantia nigra, associated with abnormal iron load. The assessment of presymptomatic biomarkers predicting the onset of neurodegenerative disorders is critical for monitoring early signs, screening patients for neuroprotective clinical trials and understanding the causal relationship between iron accumulation processes and disease development. Here, we used Quantitative Susceptibility Mapping (QSM) and 7T MRI to quantify iron deposition in Nigrosome 1 (N1) in early PD (ePD) patients, iRBD patients and healthy controls and investigated group differences and correlation with disease progression. We evaluated the radiological appearance of N1 and analyzed its iron content in 35 ePD, 30 iRBD patients and 14 healthy controls via T2*-weighted sequences and susceptibility (χ) maps. N1 regions of interest (ROIs) were manually drawn on control subjects and warped onto a study-specific template to obtain probabilistic N1 ROIs. For each subject the N1 with the highest mean χ was considered for statistical analysis. The appearance of N1 was rated pathological in 45% of iRBD patients. ePD patients showed increased N1 χ compared to iRBD patients and HC but no correlation with disease duration, indicating that iron load remains stable during the early stages of disease progression. Although no difference was reported in iron content between iRBD and HC, N1 χ in the iRBD group increases as the disease evolves. QSM can reveal temporal changes in N1 iron content and its quantification may represent a valuable presymptomatic biomarker to assess neurodegeneration in the prodromal stages of PD.
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Affiliation(s)
- Marta Lancione
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy; Imago7 Research Foundation, Pisa, Italy
| | - Graziella Donatelli
- Imago7 Research Foundation, Pisa, Italy; Neuroradiology Unit, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy.
| | - Eleonora Del Prete
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Nicole Campese
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Daniela Frosini
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Matteo Cencini
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy; Imago7 Research Foundation, Pisa, Italy
| | - Mauro Costagli
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy
| | - Laura Biagi
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy; Imago7 Research Foundation, Pisa, Italy
| | - Giacomo Lucchi
- Neuroradiology Unit, Department of Translational Research on New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Michela Tosetti
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy; Imago7 Research Foundation, Pisa, Italy
| | | | - Dario Arnaldi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Michele Terzaghi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy; IRCCS Mondino Foundation, Pavia, Italy
| | - Federica Provini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Clinica Neurologica Rete Metropolitana, Bologna, Italy; Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
| | - Claudio Pacchetti
- Parkinson's Disease and Movement Disorders Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Pietro Cortelli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Clinica Neurologica Rete Metropolitana, Bologna, Italy; Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
| | - Enrica Bonanni
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Roberto Ceravolo
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Mirco Cosottini
- Neuroradiology Unit, Department of Translational Research on New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
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Kim H, Jang J, Kang J, Jang S, Nam Y, Choi Y, Shin NY, Ahn KJ, Kim BS. Clinical Implications of Focal Mineral Deposition in the Globus Pallidus on CT and Quantitative Susceptibility Mapping of MRI. Korean J Radiol 2022; 23:742-751. [PMID: 35695315 PMCID: PMC9240299 DOI: 10.3348/kjr.2022.0003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To assess focal mineral deposition in the globus pallidus (GP) by CT and quantitative susceptibility mapping (QSM) of MRI scans and evaluate its clinical significance, particularly cerebrovascular degeneration. MATERIALS AND METHODS This study included 105 patients (66.1 ± 13.7 years; 40 male and 65 female) who underwent both CT and MRI with available QSM data between January 2017 and December 2019. The presence of focal mineral deposition in the GP on QSM (GPQSM) and CT (GPCT) was assessed visually using a three-point scale. Cerebrovascular risk factors and small vessel disease (SVD) imaging markers were also assessed. The clinical and radiological findings were compared between the different grades of GPQSM and GPCT. The relationship between GP grades and cerebrovascular risk factors and SVD imaging markers was assessed using univariable and multivariable linear regression analyses. RESULTS GPCT and GPQSM were significantly associated (p < 0.001) but were not identical. Higher GPCT and GPQSM grades showed smaller gray matter (p = 0.030 and p = 0.025, respectively) and white matter (p = 0.013 and p = 0.019, respectively) volumes, as well as larger GP volumes (p < 0.001 for both). Among SVD markers, white matter hyperintensity was significantly associated with GPCT (p = 0.006) and brain atrophy was significantly associated with GPQSM (p = 0.032) in at univariable analysis. In multivariable analysis, the normalized volume of the GP was independently positively associated with GPCT (p < 0.001) and GPQSM (p = 0.002), while the normalized volume of the GM was independently negatively associated with GPCT (p = 0.040) and GPQSM (p = 0.035). CONCLUSION Focal mineral deposition in the GP on CT and QSM might be a potential imaging marker of cerebral vascular degeneration. Both were associated with increased GP volume.
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Affiliation(s)
- Hyojin Kim
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jinhee Jang
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
| | - Junghwa Kang
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Korea
| | - Seungun Jang
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Korea
| | - Yoonho Nam
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Korea
| | - Yangsean Choi
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Na-Young Shin
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Kook-Jin Ahn
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Bum-Soo Kim
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
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Brain Iron and Mental Health Symptoms in Youth with and without Prenatal Alcohol Exposure. Nutrients 2022; 14:nu14112213. [PMID: 35684012 PMCID: PMC9183007 DOI: 10.3390/nu14112213] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 05/18/2022] [Accepted: 05/19/2022] [Indexed: 12/18/2022] Open
Abstract
Prenatal alcohol exposure (PAE) negatively affects brain development and increases the risk of poor mental health. We investigated if brain volumes or magnetic susceptibility, an indirect measure of brain iron, were associated with internalizing or externalizing symptoms in youth with and without PAE. T1-weighted and quantitative susceptibility mapping (QSM) MRI scans were collected for 19 PAE and 40 unexposed participants aged 7.5–15 years. Magnetic susceptibility and volume of basal ganglia and limbic structures were extracted using FreeSurfer. Internalizing and Externalizing Problems were assessed using the Behavioural Assessment System for Children (BASC-2-PRS). Susceptibility in the nucleus accumbens was negatively associated with Internalizing Problems, while amygdala susceptibility was positively associated with Internalizing Problems across groups. PAE moderated the relationship between thalamus susceptibility and internalizing symptoms as well as the relationship between putamen susceptibility and externalizing symptoms. Brain volume was not related to internalizing or externalizing symptoms. These findings highlight that brain iron is related to internalizing and externalizing symptoms differently in some brain regions for youth with and without PAE. Atypical iron levels (high or low) may indicate mental health issues across individuals, and iron in the thalamus may be particularly important for behavior in individuals with PAE.
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Rao IY, Hanson LR, Johnson JC, Rosenbloom MH, Frey WH. Brain Glucose Hypometabolism and Iron Accumulation in Different Brain Regions in Alzheimer's and Parkinson's Diseases. Pharmaceuticals (Basel) 2022; 15:551. [PMID: 35631378 PMCID: PMC9143620 DOI: 10.3390/ph15050551] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 04/17/2022] [Accepted: 04/27/2022] [Indexed: 02/01/2023] Open
Abstract
The aim of this study was to examine the relationship between the presence of glucose hypometabolism (GHM) and brain iron accumulation (BIA), two potential pathological mechanisms in neurodegenerative disease, in different regions of the brain in people with late-onset Alzheimer's disease (AD) or Parkinson's disease (PD). Studies that conducted fluorodeoxyglucose positron emission tomography (FDG-PET) to map GHM or quantitative susceptibility mapping-magnetic resonance imaging (QSM-MRI) to map BIA in the brains of patients with AD or PD were reviewed. Regions of the brain where GHM or BIA were reported in each disease were compared. In AD, both GHM and BIA were reported in the hippocampus, temporal, and parietal lobes. GHM alone was reported in the cingulate gyrus, precuneus and occipital lobe. BIA alone was reported in the caudate nucleus, putamen and globus pallidus. In PD, both GHM and BIA were reported in thalamus, globus pallidus, putamen, hippocampus, and temporal and frontal lobes. GHM alone was reported in cingulate gyrus, caudate nucleus, cerebellum, and parietal and occipital lobes. BIA alone was reported in the substantia nigra and red nucleus. GHM and BIA are observed independent of one another in various brain regions in both AD and PD. This suggests that GHM is not always necessary or sufficient to cause BIA and vice versa. Hypothesis-driven FDG-PET and QSM-MRI imaging studies, where both are conducted on individuals with AD or PD, are needed to confirm or disprove the observations presented here about the potential relationship or lack thereof between GHM and BIA in AD and PD.
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Affiliation(s)
- Indira Y. Rao
- HealthPartners Center for Memory and Aging, 295 Phalen Boulevard, St. Paul, MN 55130, USA; (I.Y.R.); (L.R.H.); (M.H.R.)
| | - Leah R. Hanson
- HealthPartners Center for Memory and Aging, 295 Phalen Boulevard, St. Paul, MN 55130, USA; (I.Y.R.); (L.R.H.); (M.H.R.)
- HealthPartners Institute, Bloomington, MN 55425, USA
| | - Julia C. Johnson
- HealthPartners Struthers Parkinson’s Center, Minneapolis, MN 55427, USA;
| | - Michael H. Rosenbloom
- HealthPartners Center for Memory and Aging, 295 Phalen Boulevard, St. Paul, MN 55130, USA; (I.Y.R.); (L.R.H.); (M.H.R.)
| | - William H. Frey
- HealthPartners Center for Memory and Aging, 295 Phalen Boulevard, St. Paul, MN 55130, USA; (I.Y.R.); (L.R.H.); (M.H.R.)
- HealthPartners Institute, Bloomington, MN 55425, USA
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Gustavsson J, Papenberg G, Falahati F, Laukka EJ, Kalpouzos G. Contributions of the Catechol-O-Methyltransferase Val158Met Polymorphism to Changes in Brain Iron Across Adulthood and Their Relationships to Working Memory. Front Hum Neurosci 2022; 16:838228. [PMID: 35571998 PMCID: PMC9091601 DOI: 10.3389/fnhum.2022.838228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 03/16/2022] [Indexed: 11/13/2022] Open
Abstract
Ageing is associated with excessive free brain iron, which may induce oxidative stress and neuroinflammation, likely causing cognitive deficits. Lack of dopamine may be a factor behind the increase of iron with advancing age, as it has an important role in cellular iron homoeostasis. We investigated the effect of COMT Val 158 Met (rs4680), a polymorphism crucial for dopamine degradation and proxy for endogenous dopamine, on iron accumulation and working memory in a longitudinal lifespan sample (n = 208, age 20–79 at baseline, mean follow-up time = 2.75 years) using structural equation modelling. Approximation of iron content was assessed using quantitative susceptibility mapping in striatum and dorsolateral prefrontal cortex (DLPFC). Iron accumulated in both striatum and DLPFC during the follow-up period. Greater iron accumulation in DLPFC was associated with more deleterious change in working memory. Older (age 50–79) Val homozygotes (with presumably lower endogenous dopamine) accumulated more iron than older Met carriers in both striatum and DLPFC, no such differences were observed among younger adults (age 20–49). In conclusion, individual differences in genetic predisposition related to low dopamine levels increase iron accumulation, which in turn may trigger deleterious change in working memory. Future studies are needed to better understand how dopamine may modulate iron accumulation across the human lifespan.
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Affiliation(s)
- Jonatan Gustavsson
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- *Correspondence: Jonatan Gustavsson,
| | - Goran Papenberg
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Farshad Falahati
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Erika J. Laukka
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Stockholm Gerontology Research Center, Stockholm, Sweden
| | - Grégoria Kalpouzos
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Grégoria Kalpouzos,
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Mao H, Dou W, Chen K, Wang X, Wang X, Guo Y, Zhang C. Evaluating iron deposition in gray matter nuclei of patients with unilateral middle cerebral artery stenosis using quantitative susceptibility mapping. Neuroimage Clin 2022; 34:103021. [PMID: 35500369 PMCID: PMC9065429 DOI: 10.1016/j.nicl.2022.103021] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 03/17/2022] [Accepted: 04/23/2022] [Indexed: 11/18/2022]
Abstract
Iron mediated oxidative stress is involved in the process of brain injury after long-term ischemia. While increased iron deposition in the affected brain regions was observed in animal models of ischemic stroke, potential changes in the brain iron content in clinical patients with cerebral ischemia remain unclear. Quantitative susceptibility mapping (QSM), a non-invasive magnetic resonance imaging technique, can be used to evaluate iron content in the gray matter (GM) nuclei reliably. In this study, we aimed to quantitatively evaluate iron content changes in GM nuclei of patients with long-term unilateral middle cerebral artery (MCA) stenosis/occlusion-related cerebral ischemia using QSM. Forty-six unilateral MCA stenosis/occlusion patients and 38 age-, sex- and education-matched healthy controls underwent QSM. Clinical variables of history of hypertension, diabetes, hyperlipidemia, hyperhomocysteinemia, smoking, and drinking in all patients were evaluated. The iron-related susceptibility of GM nucleus subregions, including the bilateral caudate nucleus (CN), putamen (PU), globus pallidus (GP), thalamus, substantia nigra (SN), red nucleus, and dentate nucleus, was assessed. Susceptibility was compared between the bilateral GM nuclei in patients and controls. Receiver operating characteristic curve analysis was used to evaluate the efficacy of QSM susceptibility in distinguishing patients with unilateral MCA stenosis/occlusion from healthy controls. Multiple linear regression analysis was used to evaluate the relationship between ipsilateral susceptibility levels and clinical variables. Except for the CN, the susceptibility in most bilateral GM nucleus subregions was comparable in healthy controls, whereas for patients with unilateral MCA stenosis/occlusion, the ipsilateral PU, GP, and SN exhibited significantly higher susceptibility than the contralateral side (all P < 0.05). Compared with controls, susceptibility of the ipsilateral PU, GP, and SN and of contralateral PU in patients were significantly increased (all P < 0.05). The area under the curve (AUC) was greater for the ipsilateral PU than for the GP and SN (AUC = 0.773, 0.662 and 0.681; all P < 0.05). Multiple linear regression analysis showed that the increased susceptibility of the ipsilateral PU was significantly associated with hypertension, of the ipsilateral GP associated with smoking, and of the ipsilateral SN associated with diabetes (all P < 0.05). Our findings provide support for abnormal iron accumulation in the GM nuclei after chronic MCA stenosis/occlusion and its correlation with some cerebrovascular disease risk factors. Therefore, iron deposition in the GM nuclei, as measured by QSM, may be a potential biomarker for long-term cerebral ischemia.
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Affiliation(s)
- Huimin Mao
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Weiqiang Dou
- MR Research, GE Healthcare, Beijing 10076, China
| | - Kunjian Chen
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Xinyu Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Xinyi Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China.
| | - Yu Guo
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Chao Zhang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China
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Nikparast F, Ganji Z, Danesh Doust M, Faraji R, Zare H. Brain pathological changes during neurodegenerative diseases and their identification methods: How does QSM perform in detecting this process? Insights Imaging 2022; 13:74. [PMID: 35416533 PMCID: PMC9008086 DOI: 10.1186/s13244-022-01207-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 03/13/2022] [Indexed: 12/14/2022] Open
Abstract
The presence of iron is essential for many biological processes in the body. But sometimes, for various reasons, the amount of iron deposition in different areas of the brain increases, which leads to problems related to the nervous system. Quantitative susceptibility mapping (QSM) is one of the newest magnetic resonance imaging (MRI)-based methods for assessing iron accumulation in target areas. This Narrative Review article aims to evaluate the performance of QSM compared to other methods of assessing iron deposition in the clinical field. Based on the results, we introduced related basic definitions, some neurodegenerative diseases, methods of examining iron deposition in these diseases, and their advantages and disadvantages. This article states that the QSM method can be introduced as a new, reliable, and non-invasive technique for clinical evaluations.
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Affiliation(s)
- Farzaneh Nikparast
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Zohreh Ganji
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mohammad Danesh Doust
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Reyhane Faraji
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hoda Zare
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. .,Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
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Lewis MM, Albertson RM, Du G, Kong L, Foy A, Huang X. Parkinson’s Disease Progression and Statins: Hydrophobicity Matters. JOURNAL OF PARKINSON'S DISEASE 2022; 12:821-830. [PMID: 34958045 PMCID: PMC10141621 DOI: 10.3233/jpd-212819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Recent randomized clinical trials using hydrophobic statins reported no influence on Parkinson’s disease (PD) clinical progression. Hydrophobicity is a key determinant for blood-brain barrier penetrance. Objective: Investigate a potential effect of statins on PD progression. Methods: Statin use was determined at baseline and subtyped according to hydrophobicity in 125 PD patients participating in the PD Biomarker Program (PDBP, 2012–2015) at our site. Clinical (N = 125) and susceptibility MRI (N = 86) data were obtained at baseline and 18-months. Movement Disorders Society-Unified PD Rating Scales were used to track progression of non-motor (MDS-UPDRS-I) and motor (MDS-UPDRS-II) symptoms, and rater-based scores (MDS-UPDRS-III) of patients in the “on” drug state. R2* values were used to capture pathological progression in the substantia nigra. Associations between statin use, its subtypes, and PD progression were evaluated with linear mixed effect regressions. Results: Compared to statin non-users, overall statin or lipophilic statin use did not significantly influence PD clinical or imaging progression. Hydrophilic statin users, however, demonstrated faster clinical progression of non-motor symptoms [MDS-UPDRS-I (β= 4.8, p = 0.010)] and nigral R2* (β= 3.7, p = 0.043). A similar trend was found for MDS-UPDRS-II (β= 3.9, p = 0.10), but an opposite trend was observed for rater-based MDS-UPDRS-III (β= –7.3, p = 0.10). Compared to lipophilic statin users, hydrophilic statin users also showed significantly faster clinical progression of non-motor symptoms [MDS-UPDRS-I (β= 5.0, p = 0.020)], but R2* did not reach statistical significance (β= 2.5, p = 0.24). Conclusion: This study suggests that hydrophilic, but not lipophilic, statins may be associated with faster PD progression. Future studies may have clinical and scientific implications.
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Affiliation(s)
- Mechelle M. Lewis
- Department of Neurology, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Pharmacology, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Richard M. Albertson
- Department of Neurology, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Guangwei Du
- Department of Neurology, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Lan Kong
- Department of Public Health Sciences, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Andrew Foy
- Department of Public Health Sciences, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Medicine, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Xuemei Huang
- Department of Neurology, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Pharmacology, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Radiology, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Neurosurgery, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Kinesiology, Pennsylvania State University Milton S. Hershey Medical Center, Hershey, PA, USA
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Howard CM, Jain S, Cook AD, Packard LE, Mullin HA, Chen N, Liu C, Song AW, Madden DJ. Cortical iron mediates age-related decline in fluid cognition. Hum Brain Mapp 2022; 43:1047-1060. [PMID: 34854172 PMCID: PMC8764476 DOI: 10.1002/hbm.25706] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/20/2021] [Accepted: 10/21/2021] [Indexed: 01/19/2023] Open
Abstract
Brain iron dyshomeostasis disrupts various critical cellular functions, and age-related iron accumulation may contribute to deficient neurotransmission and cell death. While recent studies have linked excessive brain iron to cognitive function in the context of neurodegenerative disease, little is known regarding the role of brain iron accumulation in cognitive aging in healthy adults. Further, previous studies have focused primarily on deep gray matter regions, where the level of iron deposition is highest. However, recent evidence suggests that cortical iron may also contribute to cognitive deficit and neurodegenerative disease. Here, we used quantitative susceptibility mapping (QSM) to measure brain iron in 67 healthy participants 18-78 years of age. Speed-dependent (fluid) cognition was assessed from a battery of 12 psychometric and computer-based tests. From voxelwise QSM analyses, we found that QSM susceptibility values were negatively associated with fluid cognition in the right inferior temporal gyrus, bilateral putamen, posterior cingulate gyrus, motor, and premotor cortices. Mediation analysis indicated that susceptibility in the right inferior temporal gyrus was a significant mediator of the relation between age and fluid cognition, and similar effects were evident for the left inferior temporal gyrus at a lower statistical threshold. Additionally, age and right inferior temporal gyrus susceptibility interacted to predict fluid cognition, such that brain iron was negatively associated with a cognitive decline for adults over 45 years of age. These findings suggest that iron may have a mediating role in cognitive decline and may be an early biomarker of neurodegenerative disease.
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Affiliation(s)
- Cortney M. Howard
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Shivangi Jain
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Psychological and Brain SciencesUniversity of IowaIowa CityIowaUSA
| | - Angela D. Cook
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Lauren E. Packard
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Hollie A. Mullin
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Nan‐kuei Chen
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Biomedical EngineeringUniversity of ArizonaTucsonArizonaUSA
| | - Chunlei Liu
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Electrical Engineering and Computer SciencesUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Allen W. Song
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - David J. Madden
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Department of Psychiatry and Behavioral SciencesDuke University Medical CenterDurhamNorth CarolinaUSA
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Sato R, Kudo K, Udo N, Matsushima M, Yabe I, Yamaguchi A, Tha KK, Sasaki M, Harada M, Matsukawa N, Amemiya T, Kawata Y, Bito Y, Ochi H, Shirai T. A diagnostic index based on quantitative susceptibility mapping and voxel-based morphometry may improve early diagnosis of Alzheimer's disease. Eur Radiol 2022; 32:4479-4488. [PMID: 35137303 DOI: 10.1007/s00330-022-08547-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/25/2021] [Accepted: 12/14/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Voxel-based morphometry (VBM) is widely used to quantify the progression of Alzheimer's disease (AD), but improvement is still needed for accurate early diagnosis. We evaluated the feasibility of a novel diagnosis index for early diagnosis of AD based on quantitative susceptibility mapping (QSM) and VBM. METHODS Thirty-seven patients with AD, 24 patients with mild cognitive impairment (MCI) due to AD, and 36 cognitively normal (NC) subjects from four centers were included. A hybrid sequence was performed by using 3-T MRI with a 3D multi-echo GRE sequence to obtain both a T1-weighted image for VBM and phase images for QSM. The index was calculated from specific voxels in QSM and VBM images by using a linear support vector machine. The method of voxel extraction was optimized to maximize diagnostic accuracy, and the optimized index was compared with the conventional VBM-based index using receiver operating characteristic analysis. RESULTS The index was optimal when voxels were extracted as increased susceptibility (AD > NC) in the parietal lobe and decreased gray matter volume (AD < NC) in the limbic system. The optimized proposed index showed excellent performance for discrimination between AD and NC (AUC = 0.94, p = 1.1 × 10-10) and good performance for MCI and NC (AUC = 0.87, p = 1.8 × 10-6), but poor performance for AD and MCI (AUC = 0.68, p = 0.018). Compared with the conventional index, AUCs were improved for all cases, especially for MCI and NC (p < 0.05). CONCLUSIONS In this preliminary study, the proposed index based on QSM and VBM improved the diagnostic performance between MCI and NC groups compared with the VBM-based index. KEY POINTS • We developed a novel diagnostic index for Alzheimer's disease based on quantitative susceptibility mapping (QSM) and voxel-based morphometry (VBM). • QSM and VBM images can be acquired simultaneously in a single sequence with little increasing scan time. • In this preliminary study, the proposed diagnostic index improved the discriminative performance between mild cognitive impairment and normal control groups compared with the conventional VBM-based index.
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Affiliation(s)
- Ryota Sato
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan.
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan.
| | - Kohsuke Kudo
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Niki Udo
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Masaaki Matsushima
- Department of Neurology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Ichiro Yabe
- Department of Neurology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Akinori Yamaguchi
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Khin Khin Tha
- Global Center for Biomedical Science and Engineering, Hokkaido University Faculty of Medicine, Sapporo, Hokkaido, Japan
| | - Makoto Sasaki
- Institute for Biomedical Sciences, Iwate Medical University, Morioka, Iwate, Japan
| | - Masafumi Harada
- Department of Radiology, Tokushima University, Tokushima, Japan
| | | | - Tomoki Amemiya
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Yasuo Kawata
- Radiation Diagnostic Systems Division, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Yoshitaka Bito
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
- Radiation Diagnostic Systems Division, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Hisaaki Ochi
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Toru Shirai
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
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Mao H, Dou W, Wang X, Chen K, Wang X, Guo Y, Zhang C. Iron Deposition in Gray Matter Nuclei of Patients With Intracranial Artery Stenosis: A Quantitative Susceptibility Mapping Study. Front Neurol 2022; 12:785822. [PMID: 35069414 PMCID: PMC8766754 DOI: 10.3389/fneur.2021.785822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 12/14/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: This study aimed to use quantitative susceptibility mapping (QSM) to systematically investigate the changes of iron content in gray matter (GM) nuclei in patients with long-term anterior circulation artery stenosis (ACAS) and posterior circulation artery stenosis (PCAS). Methods: Twenty-five ACAS patients, 25 PCAS patients, and 25 age- and sex-matched healthy controls underwent QSM examination. Patients were scored using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) to assess the degree of neural function deficiency. On QSM images, iron related susceptibility of GM nuclei, including bilateral caudate nucleus, putamen (PU), globus pallidus (GP), thalamus (TH), substantia nigra (SN), red nucleus, and dentate nucleus (DN), were assessed. Susceptibility was compared between bilateral GM nuclei in healthy controls, ACAS patients, and PCAS patients. Partial correlation analysis, with age as a covariate, was separately performed to assess the relationships of susceptibility with NIHSS and mRS scores. Results: There were no significant differences between the susceptibilities for left and right hemispheres in all seven GM nucleus subregions for healthy controls, ACAS patients, and PCAS patients. Compared with healthy controls, mean susceptibility of bilateral PU, GP, and SN in ACAS patients and of bilateral PU, GP, SN, and DN in PCAS patients were significantly increased (all P < 0.05). In addition, mean susceptibility of bilateral TH and SN in PCAS patients was significantly higher than in ACAS patients (both P < 0.05). With partial correlation analysis, mean susceptibility at bilateral PU of ACAS patients was significantly correlated with mRS score (r = 0.415, P < 0.05), and at bilateral PU in PCAS patients was correlated with NIHSS score (r = 0.424, P < 0.05). Conclusion: Our findings indicated that abnormal iron metabolism may present in different subregions of GM nuclei after long-term ACAS and PCAS. In addition, iron content of PU in patients with ACAS and PCAS was correlated with neurological deficit scores. Therefore, iron quantification measured by QSM susceptibility may provide a new insight to understand the pathological mechanism of ischemic stroke caused by ACAS and PCAS.
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Affiliation(s)
- Huimin Mao
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | | | - Xinyi Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - Kunjian Chen
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | - Xinyu Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | - Yu Guo
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | - Chao Zhang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
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Donatelli G, Costagli M, Cecchi P, Migaleddu G, Bianchi F, Frumento P, Siciliano G, Cosottini M. Motor cortical patterns of upper motor neuron pathology in amyotrophic lateral sclerosis: A 3 T MRI study with iron-sensitive sequences. NEUROIMAGE: CLINICAL 2022; 35:103138. [PMID: 36002961 PMCID: PMC9421531 DOI: 10.1016/j.nicl.2022.103138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/05/2022] [Accepted: 07/27/2022] [Indexed: 11/11/2022] Open
Abstract
M1 regions associated with the body site of onset are frequently affected at MRI. The simultaneous involvement of both homologous M1 regions is frequent. The T2* hypointensity in non-contiguous M1 regions seems rare.
Background Patterns of initiation and propagation of disease in Amyotrophic Lateral Sclerosis (ALS) are still partly unknown. Single or multiple foci of neurodegeneration followed by disease diffusion to contiguous or connected regions have been proposed as mechanisms underlying symptom occurrence. Here, we investigated cortical patterns of upper motor neuron (UMN) pathology in ALS using iron-sensitive MR imaging. Methods Signal intensity and magnetic susceptibility of the primary motor cortex (M1), which are associated with clinical UMN burden and neuroinflammation, were assessed in 78 ALS patients using respectively T2*-weighted images and Quantitative Susceptibility Maps. The signal intensity of the whole M1 and each of its functional regions was rated as normal or reduced, and the magnetic susceptibility of each M1 region was measured. Results The highest frequencies of T2* hypointensity were found in M1 regions associated with the body sites of symptom onset. Homologous M1 regions were both hypointense in 80–93 % of patients with cortical abnormalities, and magnetic susceptibility values measured in homologous M1 regions were strongly correlated with each other (ρ = 0.88; p < 0.0001). In some cases, the T2* hypointensity was detectable in two non-contiguous M1 regions but spared the cortex in between. Conclusions M1 regions associated with the body site of onset are frequently affected at imaging. The simultaneous involvement of both homologous M1 regions is frequent, followed by that of adjacent regions; the affection of non-contiguous regions, instead, seems rare. This type of cortical involvement suggests the interhemispheric connections as one of the preferential paths for the UMN pathology diffusion in ALS.
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Jellen LC, Lewis MM, Du G, Wang X, Galvis MLE, Krzyzanowski S, Capan CD, Snyder AM, Connor JR, Kong L, Mailman RB, Brundin P, Brundin L, Huang X. Low plasma serotonin linked to higher nigral iron in Parkinson's disease. Sci Rep 2021; 11:24384. [PMID: 34934078 PMCID: PMC8692322 DOI: 10.1038/s41598-021-03700-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 11/18/2021] [Indexed: 12/30/2022] Open
Abstract
A growing body of evidence suggests nigral iron accumulation plays an important role in the pathophysiology of Parkinson's disease (PD), contributing to dopaminergic neuron loss in the substantia nigra pars compacta (SNc). Converging evidence suggests this accumulation might be related to, or increased by, serotonergic dysfunction, a common, often early feature of the disease. We investigated whether lower plasma serotonin in PD is associated with higher nigral iron. We obtained plasma samples from 97 PD patients and 89 controls and MRI scans from a sub-cohort (62 PD, 70 controls). We measured serotonin concentrations using ultra-high performance liquid chromatography and regional iron content using MRI-based quantitative susceptibility mapping. PD patients had lower plasma serotonin (p < 0.0001) and higher nigral iron content (SNc: p < 0.001) overall. Exclusively in PD, lower plasma serotonin was correlated with higher nigral iron (SNc: r(58) = - 0.501, p < 0.001). This correlation was significant even in patients newly diagnosed (< 1 year) and stronger in the SNc than any other region examined. This study reveals an early, linear association between low serotonin and higher nigral iron in PD patients, which is absent in controls. This is consistent with a serotonin-iron relationship in the disease process, warranting further studies to determine its cause and directionality.
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Affiliation(s)
- Leslie C Jellen
- Department of Neurology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Mechelle M Lewis
- Department of Neurology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Pharmacology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Guangwei Du
- Department of Neurology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Xi Wang
- Public Health Sciences, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Martha L Escobar Galvis
- Parkinson's Disease Center, Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave NE, Grand Rapids, MI, 49503, USA
| | - Stanislaw Krzyzanowski
- Parkinson's Disease Center, Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave NE, Grand Rapids, MI, 49503, USA
| | - Colt D Capan
- Parkinson's Disease Center, Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave NE, Grand Rapids, MI, 49503, USA
| | - Amanda M Snyder
- Department of Neurology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - James R Connor
- Department of Neurology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Lan Kong
- Public Health Sciences, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Richard B Mailman
- Department of Neurology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Pharmacology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Patrik Brundin
- Parkinson's Disease Center, Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave NE, Grand Rapids, MI, 49503, USA
| | - Lena Brundin
- Parkinson's Disease Center, Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave NE, Grand Rapids, MI, 49503, USA.
- Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI, USA.
| | - Xuemei Huang
- Department of Neurology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA.
- Department of Pharmacology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA.
- Departments of Neurosurgery and Radiology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA.
- Department of Kinesiology, Penn State University-Milton S. Hershey Medical Center, Hershey, PA, USA.
- Translational Brain Research Center, Penn State University-Hershey Medical Center, 500 University Dr., Mail Code H037, Hershey, PA, 17033, USA.
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Zachariou V, Bauer CE, Powell DK, Gold BT. Ironsmith: An Automated Pipeline for QSM-based Data Analyses. Neuroimage 2021; 249:118835. [PMID: 34936923 PMCID: PMC8935985 DOI: 10.1016/j.neuroimage.2021.118835] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 11/27/2021] [Accepted: 12/17/2021] [Indexed: 12/13/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) is an MRI-based, computational method for anatomically localizing and measuring concentrations of specific biomarkers in tissue such as iron. Growing research suggests QSM is a viable method for evaluating the impact of iron overload in neurological disorders and on cognitive performance in aging. Several software toolboxes are currently available to reconstruct QSM maps from 3D GRE MR Images. However, few if any software packages currently exist that offer fully automated pipelines for QSM-based data analyses: from DICOM images to region-of-interest (ROI) based QSM values. Even less QSM-based software exist that offer quality control measures for evaluating the QSM output. Here, we address these gaps in the field by introducing and demonstrating the reliability and external validity of Ironsmith; an open-source, fully automated pipeline for creating and processing QSM maps, extracting QSM values from subcortical and cortical brain regions (89 ROIs) and evaluating the quality of QSM data using SNR measures and assessment of outlier regions on phase images. Ironsmith also features automatic filtering of QSM outlier values and precise CSF-only QSM reference masks that minimize partial volume effects. Testing of Ironsmith revealed excellent intra- and inter-rater reliability. Finally, external validity of Ironsmith was demonstrated via an anatomically selective relationship between motor performance and Ironsmith-derived QSM values in motor cortex. In sum, Ironsmith provides a freely-available, reliable, turn-key pipeline for QSM-based data analyses to support research on the impact of brain iron in aging and neurodegenerative disease.
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Affiliation(s)
- Valentinos Zachariou
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY 40536-0298 United States.
| | - Christopher E Bauer
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY 40536-0298 United States
| | - David K Powell
- Department of Neuroscience, Magnetic Resonance Imaging and Spectroscopy Center, College of Medicine, University of Kentucky, Lexington, KY 40536-0298 United States
| | - Brian T Gold
- Department of Neuroscience, Sanders-Brown Center on Aging, Magnetic Resonance Imaging and Spectroscopy Center, College of Medicine, University of Kentucky, Lexington, KY 40536-0298 United States.
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49
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Lazari A, Salvan P, Cottaar M, Papp D, Jens van der Werf O, Johnstone A, Sanders ZB, Sampaio-Baptista C, Eichert N, Miyamoto K, Winkler A, Callaghan MF, Nichols TE, Stagg CJ, Rushworth MFS, Verhagen L, Johansen-Berg H. Reassessing associations between white matter and behaviour with multimodal microstructural imaging. Cortex 2021; 145:187-200. [PMID: 34742100 PMCID: PMC8940642 DOI: 10.1016/j.cortex.2021.08.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 06/21/2021] [Accepted: 08/27/2021] [Indexed: 12/15/2022]
Abstract
Several studies have established specific relationships between White Matter (WM) and behaviour. However, these studies have typically focussed on fractional anisotropy (FA), a neuroimaging metric that is sensitive to multiple tissue properties, making it difficult to identify what biological aspects of WM may drive such relationships. Here, we carry out a pre-registered assessment of WM-behaviour relationships in 50 healthy individuals across multiple behavioural and anatomical domains, and complementing FA with myelin-sensitive quantitative MR modalities (MT, R1, R2∗). Surprisingly, we only find support for predicted relationships between FA and behaviour in one of three pre-registered tests. For one behavioural domain, where we failed to detect an FA-behaviour correlation, we instead find evidence for a correlation between behaviour and R1. This hints that multimodal approaches are able to identify a wider range of WM-behaviour relationships than focusing on FA alone. To test whether a common biological substrate such as myelin underlies WM-behaviour relationships, we then ran joint multimodal analyses, combining across all MRI parameters considered. No significant multimodal signatures were found and power analyses suggested that sample sizes of 40–200 may be required to detect such joint multimodal effects, depending on the task being considered. These results demonstrate that FA-behaviour relationships from the literature can be replicated, but may not be easily generalisable across domains. Instead, multimodal microstructural imaging may be best placed to detect a wider range of WM-behaviour relationships, as different MRI modalities provide distinct biological sensitivities. Our findings highlight a broad heterogeneity in WM's relationship with behaviour, suggesting that variable biological effects may be shaping their interaction.
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Affiliation(s)
- Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK.
| | - Piergiorgio Salvan
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Michiel Cottaar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Daniel Papp
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Olof Jens van der Werf
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, the Netherlands
| | - Ainslie Johnstone
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK; Department of Clinical and Movement Neuroscience, Institute of Neurology, University College London, UK
| | - Zeena-Britt Sanders
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Cassandra Sampaio-Baptista
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Nicole Eichert
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK
| | - Kentaro Miyamoto
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, UK
| | - Anderson Winkler
- National Institute of Mental Health, National of Health, Bethesda, MD, USA
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Thomas E Nichols
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nu_eld Department of Population Health, University of Oxford, UK
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK; MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, UK
| | - Lennart Verhagen
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, UK; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nu_eld Department of Clinical Neurosciences, University of Oxford, UK.
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50
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Yu B, Li L, Guan X, Xu X, Liu X, Yang Q, Wei H, Zuo C, Zhang Y. HybraPD atlas: Towards precise subcortical nuclei segmentation using multimodality medical images in patients with Parkinson disease. Hum Brain Mapp 2021; 42:4399-4421. [PMID: 34101297 PMCID: PMC8357000 DOI: 10.1002/hbm.25556] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 05/27/2021] [Accepted: 05/30/2021] [Indexed: 12/29/2022] Open
Abstract
Human brain atlases are essential for research and surgical treatment of Parkinson's disease (PD). For example, deep brain stimulation for PD often requires human brain atlases for brain structure identification. However, few atlases can provide disease-specific subcortical structures for PD, and most of them are based on T1w and T2w images. In this work, we construct a HybraPD atlas using fused quantitative susceptibility mapping (QSM) and T1w images from 87 patients with PD. The constructed HybraPD atlas provides a series of templates, that is, T1w, GRE magnitude, QSM, R2*, and brain tissue probabilistic maps. Then, we manually delineate a parcellation map with 12 bilateral subcortical nuclei, which are highly related to PD pathology, such as sub-regions in globus pallidus and substantia nigra. Furthermore, we build a whole-brain parcellation map by combining existing cortical parcellation and white-matter segmentation with the proposed subcortical nuclei map. Considering the multimodality of the HybraPD atlas, the segmentation accuracy of each nucleus is evaluated using T1w and QSM templates, respectively. The results show that the HybraPD atlas provides more accurate segmentation than existing atlases. Moreover, we analyze the metabolic difference in subcortical nuclei between PD patients and healthy control subjects by applying the HybraPD atlas to calculate uptake values of contrast agents on positron emission tomography (PET) images. The atlas-based analysis generates accurate disease-related brain nuclei segmentation on PET images. The newly developed HybraPD atlas could serve as an efficient template to study brain pathological alterations in subcortical regions for PD research.
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Affiliation(s)
- Boliang Yu
- School of Information Science and TechnologyShanghaiTech UniversityShanghaiChina
| | - Ling Li
- PET Center, Huashan HospitalFudan UniversityShanghaiChina
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Xueling Liu
- Department of Radiology, Huashan HospitalFudan UniversityShanghaiChina
| | - Qing Yang
- Institute of Brain‐Intelligence Technology, Zhangjiang LaboratoryShanghaiChina
| | - Hongjiang Wei
- Institute for Medicine Imaging Technology, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina
| | - Chuantao Zuo
- PET Center, Huashan HospitalFudan UniversityShanghaiChina
| | - Yuyao Zhang
- School of Information Science and TechnologyShanghaiTech UniversityShanghaiChina
- Shanghai Engineering Research Center of Intelligent Vision and ImagingShanghaiTech UniversityShanghaiChina
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