Automatic Segmentation and Quantification of Nigrosome‐1 Neuromelanin and Iron in MRI: A Candidate Biomarker for Parkinson's Disease
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 c...
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| Published in | Journal of magnetic resonance imaging Vol. 60; no. 2; pp. 534 - 547 |
|---|---|
| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Hoboken, USA
John Wiley & Sons, Inc
01.08.2024
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1053-1807 1522-2586 1522-2586 |
| DOI | 10.1002/jmri.29073 |
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| 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 |
|---|---|
| AbstractList | 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.BACKGROUNDThere 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.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.PURPOSEPresent 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.Prospective.STUDY TYPEProspective.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).SUBJECTSSeventy-one PD (65.3 ± 10.3 years old, 34 female/37 male); 30 HC (62.7 ± 7.8 years old, 17 female/13 male).3 T Anatomical T1-weighted MPRAGE, NM-MRI T1-weighted gradient with magnetization transfer, susceptibility-weighted imaging (SWI).FIELD STRENGTH/SEQUENCE3 T Anatomical T1-weighted MPRAGE, NM-MRI T1-weighted gradient with magnetization transfer, susceptibility-weighted imaging (SWI).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.ASSESSMENTN1 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.Nonparametric tests were used (Mann-Whitney's U, chi-square, and Friedman tests) at P = 0.05.STATISTICAL TESTSNonparametric tests were used (Mann-Whitney's U, chi-square, and Friedman tests) at P = 0.05.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.RESULTSN1'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.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.DATA CONCLUSIONThis 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.1 TECHNICAL EFFICACY: Stage 1.EVIDENCE LEVEL1 TECHNICAL EFFICACY: Stage 1. 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. 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. Prospective. 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). 3 T Anatomical T1-weighted MPRAGE, NM-MRI T1-weighted gradient with magnetization transfer, susceptibility-weighted imaging (SWI). 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. Nonparametric tests were used (Mann-Whitney's U, chi-square, and Friedman tests) at P = 0.05. N1's relative NM content decreased and relative iron content increased in PD patients compared with HCs (NM-CR = 22.55 ± 1.49; NM-CR = 19.79 ± 1.92; NM-nVol = 2.69 × 10 ± 1.02 × 10 ; NM-nVol = 1.18 × 10 ± 0.96 × 10 ; Iron-CR = 10.51 ± 2.64; Iron-CR = 19.35 ± 7.88; Iron-nVol = 0.72 × 10 ± 0.81 × 10 ; Iron-nVol = 2.82 × 10 ± 2.04 × 10 ). 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 (ρ = -0.31; ρ = 0.43; ρ = 0.46) and the motor status (ρ = -0.27; ρ = 0.33; ρ = 0.28), suggesting NM reduction along with iron accumulation in N1 as the disease progresses. 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. 1 TECHNICAL EFFICACY: Stage 1. 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 BackgroundThere 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.PurposePresent 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 TypeProspective.SubjectsSeventy‐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/Sequence3 T Anatomical T1‐weighted MPRAGE, NM‐MRI T1‐weighted gradient with magnetization transfer, susceptibility‐weighted imaging (SWI).AssessmentN1 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 TestsNonparametric tests were used (Mann–Whitney's U, chi‐square, and Friedman tests) at P = 0.05.ResultsN1'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 ConclusionThis 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 Level1Technical EfficacyStage 1 |
| Author | Ariz, Mikel Pastor, Pau Martínez, Martín Castellanos, Gabriel Pastor, Maria A. Ortiz de Solórzano, Carlos Fernández‐Seara, Maria A. Alvarez, Ignacio |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37915245$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1002_jmri_29076 crossref_primary_10_3390_jcm13154539 crossref_primary_10_1002_jmri_29260 |
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| ContentType | Journal Article |
| Copyright | 2023 Fundación para la Investigación Médica Aplicada. published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. 2023 Fundación para la Investigación Médica Aplicada. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. 2023. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| CorporateAuthor | The Catalonian Neuroimaging Parkinson's Disease Consortium Catalonian Neuroimaging Parkinson's Disease Consortium |
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| Keywords | nigrosome‐1 iron Parkinson's disease automatic segmentation susceptibility weighted imaging neuromelanin |
| Language | English |
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| Notes | Mikel Ariz, Martín Martínez, Pau Pastor, Maria A. Pastor, Carlos Ortiz de Solórzano contributed equally to this work. Members of The Catalonian Neuroimaging Parkinson's Disease Consortium are listed in Appendix 1 . ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
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There is a lack of automated tools for the segmentation and quantification of neuromelanin (NM) and iron in the nigrosome‐1 (N1). Existing tools... 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... BackgroundThere is a lack of automated tools for the segmentation and quantification of neuromelanin (NM) and iron in the nigrosome‐1 (N1). Existing tools... |
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| SubjectTerms | Accumulation Aged automatic segmentation Automation Biomarkers Biomarkers - metabolism Degeneration Disease control Female Females Field strength Humans Image processing Image Processing, Computer-Assisted - methods Image segmentation Iron Iron - metabolism Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Males Medical imaging Melanins - metabolism Middle Aged Movement disorders Neurodegenerative diseases neuromelanin nigrosome‐1 Parameters Parkinson Disease - diagnostic imaging Parkinson Disease - metabolism Parkinson's disease Prospective Studies Regression analysis Segmentation Statistical analysis Statistical tests Substantia nigra Substantia Nigra - diagnostic imaging Substantia Nigra - metabolism susceptibility weighted imaging |
| Title | Automatic Segmentation and Quantification of Nigrosome‐1 Neuromelanin and Iron in MRI: A Candidate Biomarker for Parkinson's Disease |
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