1
|
Welton T, Hartono S, Lee W, Teh PY, Hou W, Chen RC, Chen C, Lim EW, Prakash KM, Tan LCS, Tan EK, Chan LL. Classification of Parkinson's disease by deep learning on midbrain MRI. Front Aging Neurosci 2024; 16:1425095. [PMID: 39228827 PMCID: PMC11369979 DOI: 10.3389/fnagi.2024.1425095] [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: 04/29/2024] [Accepted: 08/01/2024] [Indexed: 09/05/2024] Open
Abstract
Purpose Susceptibility map weighted imaging (SMWI), based on quantitative susceptibility mapping (QSM), allows accurate nigrosome-1 (N1) evaluation and has been used to develop Parkinson's disease (PD) deep learning (DL) classification algorithms. Neuromelanin-sensitive (NMS) MRI could improve automated quantitative N1 analysis by revealing neuromelanin content. This study aimed to compare classification performance of four approaches to PD diagnosis: (1) N1 quantitative "QSM-NMS" composite marker, (2) DL model for N1 morphological abnormality using SMWI ("Heuron IPD"), (3) DL model for N1 volume using SMWI ("Heuron NI"), and (4) N1 SMWI neuroradiological evaluation. Method PD patients (n = 82; aged 65 ± 9 years; 68% male) and healthy-controls (n = 107; 66 ± 7 years; 48% male) underwent 3 T midbrain MRI with T2*-SWI multi-echo-GRE (for QSM and SMWI), and NMS-MRI. AUC was used to compare diagnostic performance. We tested for correlation of each imaging measure with clinical parameters (severity, duration and levodopa dosing) by Spearman-Rho or Kendall-Tao-Beta correlation. Results Classification performance was excellent for the QSM-NMS composite marker (AUC = 0.94), N1 SMWI abnormality (AUC = 0.92), N1 SMWI volume (AUC = 0.90), and neuroradiologist (AUC = 0.98). Reasons for misclassification were right-left asymmetry, through-plane re-slicing, pulsation artefacts, and thin N1. In the two DL models, all 18/189 (9.5%) cases misclassified by Heuron IPD were controls with normal N1 volumes. We found significant correlation of the SN QSM-NMS composite measure with levodopa dosing (rho = -0.303, p = 0.006). Conclusion Our data demonstrate excellent performance of a quantitative QSM-NMS marker and automated DL PD classification algorithms based on midbrain MRI, while suggesting potential further improvements. Clinical utility is supported but requires validation in earlier stage PD cohorts.
Collapse
Affiliation(s)
- Thomas Welton
- National Neuroscience Institute (NNI), Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Septian Hartono
- National Neuroscience Institute (NNI), Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Weiling Lee
- Singapore General Hospital, Singapore, Singapore
| | - Peik Yen Teh
- Singapore General Hospital, Singapore, Singapore
| | - Wenlu Hou
- Singapore General Hospital, Singapore, Singapore
| | - Robert Chun Chen
- National Neuroscience Institute (NNI), Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Singapore General Hospital, Singapore, Singapore
| | - Celeste Chen
- Singapore General Hospital, Singapore, Singapore
| | - Ee Wei Lim
- National Neuroscience Institute (NNI), Singapore, Singapore
| | | | - Louis C. S. Tan
- National Neuroscience Institute (NNI), Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Eng King Tan
- National Neuroscience Institute (NNI), Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Ling Ling Chan
- National Neuroscience Institute (NNI), Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Singapore General Hospital, Singapore, Singapore
| |
Collapse
|
2
|
Tedeschi R, Platano D, Donati D, Giorgi F. Harnessing Mirror Neurons: A New Frontier in Parkinson's Disease Rehabilitation-A Scoping Review of the Literature. J Clin Med 2024; 13:4539. [PMID: 39124805 PMCID: PMC11313649 DOI: 10.3390/jcm13154539] [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: 07/14/2024] [Revised: 07/25/2024] [Accepted: 08/01/2024] [Indexed: 08/12/2024] Open
Abstract
Background: Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor symptoms such as tremors, rigidity, and bradykinesia. Rehabilitation utilizing mirror neurons leverages the brain's capacity for action observation (AO) and motor imagery (MI) to enhance motor function. This approach involves patients imitating movements observed in therapists or videos, aiming to improve gait, coordination, and overall quality of life. Mirror neuron activation facilitates motor learning and may decelerate disease progression, thus enhancing patient mobility and independence. Methods: This scoping review aimed to map current evidence on PD therapies employing mirror neuron-based rehabilitation. Databases searched included PubMed, PEDro, and Cochrane. The review included randomized controlled trials (RCTs) and systematic reviews that examined the effects of AO and MI in PD rehabilitation. Results: Five studies met the inclusion criteria, encompassing various rehabilitation techniques focusing on AO and MI. These studies consistently demonstrated positive outcomes, such as reduced disease severity and improved quality of life, gait, and balance in PD patients. The activation of mirror neurons through AO and MI was shown to facilitate motor learning and contribute to improved functional mobility. Conclusions: Although the included studies support the beneficial impact of AO and MI techniques in PD rehabilitation, numerous questions remain unresolved. Further research is necessary to evaluate the potential integration of these techniques into standard physiotherapy routines for PD patients. This review highlights the promise of AO and MI in enhancing motor rehabilitation for PD, suggesting the need for more comprehensive studies to validate and refine these therapeutic approaches.
Collapse
Affiliation(s)
- Roberto Tedeschi
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum, University of Bologna, 40125 Bologna, Italy;
| | - Daniela Platano
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum, University of Bologna, 40125 Bologna, Italy;
- Physical Medicine and Rehabilitation Unit, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy
| | - Danilo Donati
- Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, 41124 Modena, Italy;
- Physical Therapy and Rehabilitation Unit, Policlinico di Modena, 41125 Modena, Italy
| | - Federica Giorgi
- IRCCS Institute of Neurological Sciences, UOC Child Rehabilitation Medicine, 40138 Bologna, Italy;
| |
Collapse
|
3
|
Reyes SC, Shahraki T, Soman S. Editorial for "Automatic Segmentation and Quantification of Nigrosome-1 Neuromelanin and Iron in MRI: A Candidate Biomarker for Parkinson's Disease". J Magn Reson Imaging 2024; 60:548-549. [PMID: 37915261 DOI: 10.1002/jmri.29076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 11/03/2023] Open
Affiliation(s)
- Susana Creagh Reyes
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Tamkin Shahraki
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Salil Soman
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|
4
|
Ariz M, Martínez M, Alvarez I, Fernández-Seara MA, Castellanos G, Pastor P, Pastor MA, Ortiz de Solórzano C. Automatic Segmentation and Quantification of Nigrosome-1 Neuromelanin and Iron in MRI: A Candidate Biomarker for Parkinson's Disease. J Magn Reson Imaging 2024; 60:534-547. [PMID: 37915245 DOI: 10.1002/jmri.29073] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 11/03/2023] Open
Abstract
BACKGROUND There is a lack of automated tools for the segmentation and quantification of neuromelanin (NM) and iron in the nigrosome-1 (N1). Existing tools evaluate the N1 sign, i.e., the presence or absence of the "swallow-tail" in iron-sensitive MRI, or globally analyze the MRI signal in an area containing the N1, without providing a volumetric delineation. PURPOSE Present an automated method to segment the N1 and quantify differences in N1's NM and iron content between Parkinson's disease (PD) patients and healthy controls (HCs). Study whether N1 degeneration is clinically related to PD and could be used as a biomarker of the disease. STUDY TYPE Prospective. SUBJECTS Seventy-one PD (65.3 ± 10.3 years old, 34 female/37 male); 30 HC (62.7 ± 7.8 years old, 17 female/13 male). FIELD STRENGTH/SEQUENCE 3 T Anatomical T1-weighted MPRAGE, NM-MRI T1-weighted gradient with magnetization transfer, susceptibility-weighted imaging (SWI). ASSESSMENT N1 was automatically segmented in SWI images using a multi-image atlas, populated with healthy N1 structures manually annotated by a neurologist. Relative NM and iron content were quantified and their diagnostic performance assessed and compared with the substantia nigra pars compacta (SNc). The association between image parameters and clinically relevant variables was studied. STATISTICAL TESTS Nonparametric tests were used (Mann-Whitney's U, chi-square, and Friedman tests) at P = 0.05. RESULTS N1's relative NM content decreased and relative iron content increased in PD patients compared with HCs (NM-CRHC = 22.55 ± 1.49; NM-CRPD = 19.79 ± 1.92; NM-nVolHC = 2.69 × 10-5 ± 1.02 × 10-5; NM-nVolPD = 1.18 × 10-5 ± 0.96 × 10-5; Iron-CRHC = 10.51 ± 2.64; Iron-CRPD = 19.35 ± 7.88; Iron-nVolHC = 0.72 × 10-5 ± 0.81 × 10-5; Iron-nVolPD = 2.82 × 10-5 ± 2.04 × 10-5). Binary logistic regression analyses combining N1 and SNc image parameters yielded a top AUC = 0.955. Significant correlation was found between most N1 parameters and both disease duration (ρNM-CR = -0.31; ρiron-CR = 0.43; ρiron-nVol = 0.46) and the motor status (ρNM-nVol = -0.27; ρiron-CR = 0.33; ρiron-nVol = 0.28), suggesting NM reduction along with iron accumulation in N1 as the disease progresses. DATA CONCLUSION This method provides a fully automatic N1 segmentation, and the analyses performed reveal that N1 relative NM and iron quantification improves diagnostic performance and suggest a relative NM reduction along with a relative iron accumulation in N1 as the disease progresses. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 1.
Collapse
Affiliation(s)
- Mikel Ariz
- Ciberonc and Biomedical Engineering Program, CIMA University of Navarra, Pamplona, Spain
- Department of Electrical, Electronic and Communications Engineering, Public University of Navarre, Pamplona, Spain
| | - Martín Martínez
- Neuroimaging Laboratory, University of Navarra, School of Medicine, Pamplona, Spain
| | - Ignacio Alvarez
- Movement Disorders Unit, Neurology, University Hospital Mútua de Terrassa, Terrassa, Barcelona, Spain
| | - Maria A Fernández-Seara
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
- IdiSNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain
| | - Gabriel Castellanos
- Department of Physiological Sciences, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Pau Pastor
- Unit of Neurodegenerative Diseases, Department of Neurology, University Hospital Germans Trias i Pujol, and Germans Trias i Pujol Research Institute (IGTP), Badalona, Barcelona, Spain
| | - Maria A Pastor
- Neuroimaging Laboratory, University of Navarra, School of Medicine, Pamplona, Spain
- Movement Disorders Unit, Neurology, University of Navarra, Pamplona, Spain
| | - Carlos Ortiz de Solórzano
- Ciberonc and Biomedical Engineering Program, CIMA University of Navarra, Pamplona, Spain
- IdiSNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain
| |
Collapse
|
5
|
Jin J, Su D, Zhang J, Lam JST, Zhou J, Feng T. Iron deposition in subcortical nuclei of Parkinson's disease: A meta-analysis of quantitative iron-sensitive magnetic resonance imaging studies. Chin Med J (Engl) 2024:00029330-990000000-01086. [PMID: 38809051 DOI: 10.1097/cm9.0000000000003167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Iron deposition plays a crucial role in the pathophysiology of Parkinson's disease (PD), yet the distribution pattern of iron deposition in the subcortical nuclei has been inconsistent across previous studies. We aimed to assess the difference patterns of iron deposition detected by quantitative iron-sensitive magnetic resonance imaging (MRI) between patients with PD and patients with atypical parkinsonian syndromes (APSs), and between patients with PD and healthy controls (HCs). METHODS A systematic literature search was conducted on PubMed, Embase, and Web of Science databases to identify studies investigating the iron content in PD patients using the iron-sensitive MRI techniques (R2* and quantitative susceptibility mapping [QSM]), up until May 1, 2023. The quality assessment of case-control and cohort studies was performed using the Newcastle-Ottawa Scale, whereas diagnostic studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. Standardized mean differences and summary estimates of sensitivity, specificity, and area under the curve (AUC) were calculated for iron content, using a random effects model. We also conducted the subgroup-analysis based on the MRI sequence and meta-regression. RESULTS Seventy-seven studies with 3192 PD, 209 multiple system atrophy (MSA), 174 progressive supranuclear palsy (PSP), and 2447 HCs were included. Elevated iron content in substantia nigra (SN) pars reticulata (P <0.001) and compacta (P <0.001), SN (P <0.001), red nucleus (RN, P <0.001), globus pallidus (P <0.001), putamen (PUT, P = 0.009), and thalamus (P = 0.046) were found in PD patients compared with HCs. PD patients showed lower iron content in PUT (P <0.001), RN (P = 0.003), SN (P = 0.017), and caudate nucleus (P = 0.027) than MSA patients, and lower iron content in RN (P = 0.001), PUT (P <0.001), globus pallidus (P = 0.004), SN (P = 0.015), and caudate nucleus (P = 0.001) than PSP patients. The highest diagnostic accuracy distinguishing PD from HCs was observed in SN (AUC: 0.85), and that distinguishing PD from MSA was found in PUT (AUC: 0.90). In addition, the best diagnostic performance was achieved in the RN for distinguishing PD from PSP (AUC: 0.84). CONCLUSION Quantitative iron-sensitive MRI could quantitatively detect the iron content of subcortical nuclei in PD and APSs, while it may be insufficient to accurately diagnose PD. Future studies are needed to explore the role of multimodal MRI in the diagnosis of PD. REGISTRISION PROSPERO; CRD42022344413.
Collapse
Affiliation(s)
- Jianing Jin
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Dongning Su
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Junjiao Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Joyce S T Lam
- Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Junhong Zhou
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Roslindale, MA 02131, United States
- Harvard Medical School, Boston, MA 02210, United States
| | - Tao Feng
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| |
Collapse
|
6
|
Liu P, Wang X, Zhang Y, Huang P, Jin Z, Cheng Z, Chen Y, Xu Q, Ghassaban K, Liu Y, Chen S, He N, Yan F, Haacke EM. PENCIL imaging: A novel approach for neuromelanin sensitive MRI in Parkinson's disease. Neuroimage 2024; 291:120588. [PMID: 38537765 DOI: 10.1016/j.neuroimage.2024.120588] [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: 08/31/2023] [Revised: 03/11/2024] [Accepted: 03/25/2024] [Indexed: 04/01/2024] Open
Abstract
BACKGROUND Parkinson's disease (PD) is associated with the loss of neuromelanin (NM) and increased iron in the substantia nigra (SN). Magnetization transfer contrast (MTC) is widely used for NM visualization but has limitations in brain coverage and scan time. This study aimed to develop a new approach called Proton-density Enhanced Neuromelanin Contrast in Low flip angle gradient echo (PENCIL) imaging to visualize NM in the SN. METHODS This study included 30 PD subjects and 50 healthy controls (HCs) scanned at 3T. PENCIL and MTC images were acquired. NM volume in the SN pars compacta (SNpc), normalized image contrast (Cnorm), and contrast-to-noise ratio (CNR) were calculated. The change of NM volume in the SNpc with age was analyzed using the HC data. A group analysis compared differences between PD subjects and HCs. Receiver operating characteristic (ROC) analysis and area under the curve (AUC) calculations were used to evaluate the diagnostic performance of NM volume and CNR in the SNpc. RESULTS PENCIL provided similar visualization and structural information of NM compared to MTC. In HCs, PENCIL showed higher NM volume in the SNpc than MTC, but this difference was not observed in PD subjects. PENCIL had higher CNR, while MTC had higher Cnorm. Both methods revealed a similar pattern of NM volume in SNpc changes with age. There were no significant differences in AUCs between NM volume in SNpc measured by PENCIL and MTC. Both methods exhibited comparable diagnostic performance in this regard. CONCLUSIONS PENCIL imaging provided improved CNR compared to MTC and showed similar diagnostic performance for differentiating PD subjects from HCs. The major advantage is PENCIL has rapid whole-brain coverage and, when using STAGE imaging, offers a one-stop quantitative assessment of tissue properties.
Collapse
Affiliation(s)
- Peng Liu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China
| | - Xinhui Wang
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China
| | - Youmin Zhang
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China
| | - Pei Huang
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China
| | - Zhijia Jin
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China
| | - Zenghui Cheng
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China
| | - Yongsheng Chen
- Department of Neurology, Wayne State University School of Medicine, 4201St. Antoine, Detroit, MI 48201, USA
| | - Qiuyun Xu
- SpinTech MRI, Bingham Farms, MI 48025, USA
| | | | - Yu Liu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China
| | - Shengdi Chen
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China
| | - Naying He
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China.
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China; Faculty of Medical Imaging Technology, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
| | - E Mark Haacke
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China; Department of Neurology, Wayne State University School of Medicine, 4201St. Antoine, Detroit, MI 48201, USA; Department of Radiology, Wayne State University School of Medicine, 3990 John R Street, MRI Concourse, Detroit, MI 48201, USA.
| |
Collapse
|
7
|
Alushaj E, Handfield-Jones N, Kuurstra A, Morava A, Menon RS, Owen AM, Sharma M, Khan AR, MacDonald PA. Increased iron in the substantia nigra pars compacta identifies patients with early Parkinson'sdisease: A 3T and 7T MRI study. Neuroimage Clin 2024; 41:103577. [PMID: 38377722 PMCID: PMC10944193 DOI: 10.1016/j.nicl.2024.103577] [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: 08/07/2023] [Revised: 12/19/2023] [Accepted: 02/07/2024] [Indexed: 02/22/2024]
Abstract
Degeneration in the substantia nigra (SN) pars compacta (SNc) underlies motor symptoms in Parkinson's disease (PD). Currently, there are no neuroimaging biomarkers that are sufficiently sensitive, specific, reproducible, and accessible for routine diagnosis or staging of PD. Although iron is essential for cellular processes, it also mediates neurodegeneration. MRI can localize and quantify brain iron using magnetic susceptibility, which could potentially provide biomarkers of PD. We measured iron in the SNc, SN pars reticulata (SNr), total SN, and ventral tegmental area (VTA), using quantitative susceptibility mapping (QSM) and R2* relaxometry, in PD patients and age-matched healthy controls (HCs). PD patients, diagnosed within five years of participation and HCs were scanned at 3T (22 PD and 23 HCs) and 7T (17 PD and 21 HCs) MRI. Midbrain nuclei were segmented using a probabilistic subcortical atlas. QSM and R2* values were measured in midbrain subregions. For each measure, groups were contrasted, with Age and Sex as covariates, and receiver operating characteristic (ROC) curve analyses were performed with repeated k-fold cross-validation to test the potential of our measures to classify PD patients and HCs. Statistical differences of area under the curves (AUCs) were compared using the Hanley-MacNeil method (QSM versus R2*; 3T versus 7T MRI). PD patients had higher QSM values in the SNc at both 3T (padj = 0.001) and 7T (padj = 0.01), but not in SNr, total SN, or VTA, at either field strength. No significant group differences were revealed using R2* in any midbrain region at 3T, though increased R2* values in SNc at 7T MRI were marginally significant in PDs compared to HCs (padj = 0.052). ROC curve analyses showed that SNc iron measured with QSM, distinguished early PD patients from HCs at the single-subject level with good diagnostic accuracy, using 3T (mean AUC = 0.83, 95 % CI = 0.82-0.84) and 7T (mean AUC = 0.80, 95 % CI = 0.79-0.81) MRI. Mean AUCs reported here are from averages of tests in the hold-out fold of cross-validated samples. The Hanley-MacNeil method demonstrated that QSM outperforms R2* in discriminating PD patients from HCs at 3T, but not 7T. There were no significant differences between 3T and 7T in diagnostic accuracy of QSM values in SNc. This study highlights the importance of segmenting midbrain subregions, performed here using a standardized atlas, and demonstrates high accuracy of SNc iron measured with QSM at 3T MRI in identifying early PD patients. QSM measures of SNc show potential for inclusion in neuroimaging diagnostic biomarkers of early PD. An MRI diagnostic biomarker of PD would represent a significant clinical advance.
Collapse
Affiliation(s)
- Erind Alushaj
- Department of Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada; Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
| | - Nicholas Handfield-Jones
- Department of Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada; Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
| | - Alan Kuurstra
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada; Department of Medical Biophysics, Western University, London, Ontario N6A 3K7, Canada
| | - Anisa Morava
- School of Kinesiology, Faculty of Health Sciences, Western University, London, Ontario N6A 3K7, Canada
| | - Ravi S Menon
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada; Department of Medical Biophysics, Western University, London, Ontario N6A 3K7, Canada
| | - Adrian M Owen
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada; Department of Physiology and Pharmacology, Western University, London, Ontario N6A 3K7, Canada
| | - Manas Sharma
- Department of Radiology, Western University, London, Ontario N6A 3K7, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario N6A 3K7, Canada
| | - Ali R Khan
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada; Department of Medical Biophysics, Western University, London, Ontario N6A 3K7, Canada
| | - Penny A MacDonald
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario N6A 3K7, Canada.
| |
Collapse
|
8
|
Lee MD. Editorial for "Enhancing Nigrosome-1 Sign Identification via Interpretable AI Using True Susceptibility Weighted Imaging". J Magn Reson Imaging 2024. [PMID: 38270224 DOI: 10.1002/jmri.29260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 12/28/2023] [Indexed: 01/26/2024] Open
Affiliation(s)
- Matthew D Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, New York, USA
| |
Collapse
|
9
|
Long H, Zhu W, Wei L, Zhao J. Iron homeostasis imbalance and ferroptosis in brain diseases. MedComm (Beijing) 2023; 4:e298. [PMID: 37377861 PMCID: PMC10292684 DOI: 10.1002/mco2.298] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 06/29/2023] Open
Abstract
Brain iron homeostasis is maintained through the normal function of blood-brain barrier and iron regulation at the systemic and cellular levels, which is fundamental to normal brain function. Excess iron can catalyze the generation of free radicals through Fenton reactions due to its dual redox state, thus causing oxidative stress. Numerous evidence has indicated brain diseases, especially stroke and neurodegenerative diseases, are closely related to the mechanism of iron homeostasis imbalance in the brain. For one thing, brain diseases promote brain iron accumulation. For another, iron accumulation amplifies damage to the nervous system and exacerbates patients' outcomes. In addition, iron accumulation triggers ferroptosis, a newly discovered iron-dependent type of programmed cell death, which is closely related to neurodegeneration and has received wide attention in recent years. In this context, we outline the mechanism of a normal brain iron metabolism and focus on the current mechanism of the iron homeostasis imbalance in stroke, Alzheimer's disease, and Parkinson's disease. Meanwhile, we also discuss the mechanism of ferroptosis and simultaneously enumerate the newly discovered drugs for iron chelators and ferroptosis inhibitors.
Collapse
Affiliation(s)
- Haining Long
- Department of Diagnostic and Interventional RadiologyShanghai Sixth People’s Hospital Afliated to Shanghai Jiao Tong University School
of MedicineShanghaiChina
| | - Wangshu Zhu
- Department of Diagnostic and Interventional RadiologyShanghai Sixth People’s Hospital Afliated to Shanghai Jiao Tong University School
of MedicineShanghaiChina
| | - Liming Wei
- Department of Diagnostic and Interventional RadiologyShanghai Sixth People’s Hospital Afliated to Shanghai Jiao Tong University School
of MedicineShanghaiChina
| | - Jungong Zhao
- Department of Diagnostic and Interventional RadiologyShanghai Sixth People’s Hospital Afliated to Shanghai Jiao Tong University School
of MedicineShanghaiChina
| |
Collapse
|
10
|
Wang X, Huang P, Haacke EM, Liu Y, Zhang Y, Jin Z, Li Y, Xu Q, Liu P, Chen S, He N, Yan F. Locus coeruleus and substantia nigra neuromelanin magnetic resonance imaging differentiates Parkinson's disease and essential tremor. Neuroimage Clin 2023; 38:103420. [PMID: 37141646 PMCID: PMC10176060 DOI: 10.1016/j.nicl.2023.103420] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 04/04/2023] [Accepted: 04/23/2023] [Indexed: 05/06/2023]
Abstract
BACKGROUND Differential diagnosis of essential tremor (ET) and Parkinson's disease (PD) can still be a challenge in clinical practice. These two tremor disorders may have different pathogenesis related to the substantia nigra (SN) and locus coeruleus (LC). Characterizing neuromelanin (NM) in these structures may help improve the differential diagnosis. METHODS Forty-three subjects with tremor-dominant PD (PDTD), 31 subjects with ET, and 30 age- and sex-matched healthy controls were included. All subjects were scanned with NM magnetic resonance imaging (NM-MRI). NM volume and contrast measures for the SN and contrast for the LC were evaluated. Logistic regression was used to calculate predicted probabilities by using the combination of SN and LC NM measures. The discriminative power of the NM measures in detecting subjects with PDTD from ET was assessed with a receiver operative characteristic curve, and the area under the curve (AUC) was calculated. RESULTS The NM contrast-to-noise ratio (CNR) of the LC, the NM volume, and CNR of the SN on the right and left sides were significantly lower in PDTD subjects than in ET subjects or healthy controls (all P < 0.05). Furthermore, when combining the best model constructed from the NM measures, the AUC reached 0.92 in differentiating PDTD from ET. CONCLUSION The NM volume and contrast measures of the SN and contrast for the LC provided a new perspective on the differential diagnosis of PDTD and ET, and the investigation of the underlying pathophysiology.
Collapse
Affiliation(s)
- Xinhui Wang
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Pei Huang
- From the Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Ewart Mark Haacke
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China; Department of Biomedical Engineering, Wayne State University, 3990 John R, Detroit, MI, USA; Department of Radiology, Wayne State University, 3990 John R, Detroit, MI, USA; Department of Neurology, Wayne State University, 3990 John R, Detroit, MI, USA
| | - Yu Liu
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Youmin Zhang
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Zhijia Jin
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Yan Li
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Qiuyun Xu
- Department of Biomedical Engineering, Wayne State University, 3990 John R, Detroit, MI, USA
| | - Peng Liu
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Shengdi Chen
- From the Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China.
| | - Naying He
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China.
| | - Fuhua Yan
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China.
| |
Collapse
|