Cross-Scanner Harmonization of Neuromelanin-Sensitive MRI for Multisite Studies

被引:12
|
作者
Wengler, Kenneth [1 ]
Cassidy, Clifford [2 ]
van Der Pluijm, Marieke [3 ,4 ]
Weinstein, Jodi J. [1 ,5 ]
Abi-Dargham, Anissa [5 ]
van de Giessen, Elsmarieke [3 ]
Horga, Guillermo [1 ]
机构
[1] Columbia Univ, Dept Psychiat, New York State Psychiat Inst, New York, NY USA
[2] Univ Ottawa, Mental Hlth Res Inst, Ottawa, ON, Canada
[3] Univ Amsterdam, Dept Radiol & Nucl Med, Amsterdam UMC, Amsterdam, Netherlands
[4] Univ Amsterdam, Dept Psychiat, Amsterdam UMC, Amsterdam, Netherlands
[5] SUNY Stony Brook, Dept Psychiat, New York, NY USA
关键词
neuromelanin; harmonization; ComBat; neuromelanin‐ sensitive magnetic resonance imaging; dopamine; neurodegeneration; SUBSTANTIA-NIGRA; CORTICAL THICKNESS; LOCUS-COERULEUS; HUMAN BRAIN; BIOMARKERS; ACCUMULATE; IRON;
D O I
10.1002/jmri.27679
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background Neuromelanin-sensitive magnetic resonance imaging (NM-MRI) is a validated measure of neuromelanin concentration in the substantia nigra-ventral tegmental area (SN-VTA) complex and is a proxy measure of dopaminergic function with potential as a noninvasive biomarker. The development of generalizable biomarkers requires large-scale samples necessitating harmonization approaches to combine data collected across sites. Purpose To develop a method to harmonize NM-MRI across scanners and sites. Study Type Prospective. Population A total of 128 healthy subjects (18-73 years old; 45% female) from three sites and five MRI scanners. Field Strength/Sequence 3.0 T; NM-MRI two-dimensional gradient-recalled echo with magnetization-transfer pulse and three-dimensional T1-weighted images. Assessment NM-MRI contrast (contrast-to-noise ratio [CNR]) maps were calculated and CNR values within the SN-VTA (defined previously by manual tracing on a standardized NM-MRI template) were determined before harmonization (raw CNR) and after ComBat harmonization (harmonized CNR). Scanner differences were assessed by calculating the classification accuracy of a support vector machine (SVM). To assess the effect of harmonization on biological variability, support vector regression (SVR) was used to predict age and the difference in goodness-of-fit (Delta r) was calculated as the correlation (between actual and predicted ages) for the harmonized CNR minus the correlation for the raw CNR. Statistical Tests Permutation tests were used to determine if SVM classification accuracy was above chance level and if SVR Delta r was significant. A P-value In the raw CNR, SVM MRI scanner classification was above chance level (accuracy = 86.5%). In the harmonized CNR, the accuracy of the SVM was at chance level (accuracy = 29.5%; P = 0.8542). There was no significant difference in age prediction using the raw or harmonized CNR (Delta r = -0.06; P = 0.7304). Data Conclusion ComBat harmonization removes differences in SN-VTA CNR across scanners while preserving biologically meaningful variability associated with age. Level of Evidence 2 Technical Efficacy 1
引用
收藏
页码:1189 / 1199
页数:11
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