Susceptibility Source Separation Unveils Paramagnetic and Diamagnetic Trajectories in Healthy Brains From 5 to 90 Years.
The 4 matches
- [1] § Methods › Susceptibility Source Separation Processing ↔ single_orientation/APART_QSM_single_ori_demo.m, lines 6–38 · score 0.83 · B0 field, B0 direction, magnitude images, brain mask, R2 map, APART QSM
- [2] § Methods › Susceptibility Source Separation Processing ↔ multi_orientation/APART_QSM_multi_ori_demo.m, lines 12–61 · score 0.83 · B0 field, B0 direction, magnitude images, brain mask, R2 map, APART QSM
- [3] § Methods › Relaxation Maps Reconstruction (R2, R2* and R2′) ↔ multi_orientation/APART_QSM_multi_ori_demo.m, lines 12–61 · score 0.52 · magnitude images, R2 maps, decay, echo
- [4] § Methods › Relaxation Maps Reconstruction (R2, R2* and R2′) ↔ single_orientation/APART_QSM_single_ori_demo.m, lines 6–38 · score 0.52 · magnitude images, R2 maps, decay, echo
Paper
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The authors' code
MATLAB · 58 lines · 2.3 KB · no license · 2 matches
- % Demo of APART-QSM using single-orientation data
- clear
- clc
- %% loading and setting
- % save path
- save_path = './results'; % please define the path to save results
- % input
- load('./single_orientation_data/mag_img.mat'); % magnitude image
- load('./single_orientation_data/phi_local_img.mat'); % local phase image
- load('./single_orientation_data/r2_img.mat'); % R2 map
- load('./single_orientation_data/chi_img.mat'); % initial STAR-QSM image
- load('./single_orientation_data/mask.mat'); % brain mask
- load('./single_orientation_data/TEs.mat'); % echo time
- % set mask
- params.mask = mask;
- % set parameters
- params.size = size(mag_img(:,:,:,1)); % matrix size
- params.voxel_size = [1, 1, 2]; % voxel size, unit: mm
- params.n_echo = length(TEs); % echo number
- params.TEs = TEs; % echo time, unit: s
- params.gamma = 42.576; % gyromagnetic ratio, unit: MHz/T
- params.B0 = 3; % B0 field, unit: T
- params.B0_dir = [0, 0, 1]; % B0 direction
- params.a = 323.5; % magnitude decay kernel unit: Hz/ppm
- % tolerance of the a-map relative change in two consecutive iterations
- params.tol_a = 0.3;
- % scaling weight
- params.lambda_r2prime = 0.1;
- params.lambda_chi = 10;
- params.lambda_TV = 1;
- %% exexcute APART-QSM
- Res_map = apart_qsm_single_ori(mag_img, phi_local_img, r2_img, chi_img, params);
- %% save results
- if ~exist(save_path,'dir')
- mkdir(save_path);
- end
- save_nii(make_nii(single(Res_map(:,:,:,1)), params.voxel_size), fullfile(save_path,'X_para.nii'));
- save_nii(make_nii(single(Res_map(:,:,:,2)), params.voxel_size), fullfile(save_path,'X_dia_abs.nii'));
- save_nii(make_nii(single(Res_map(:,:,:,3)), params.voxel_size), fullfile(save_path,'phase_res.nii'));
- save_nii(make_nii(single(Res_map(:,:,:,4)), params.voxel_size), fullfile(save_path,'a_map.nii'));
- save_nii(make_nii(single(Res_map(:,:,:,5)), params.voxel_size), fullfile(save_path,'M0.nii'));
- save_nii(make_nii(single(Res_map(:,:,:,6)), params.voxel_size), fullfile(save_path,'R2star.nii'));
- save_nii(make_nii(single(Res_map(:,:,:,7)), params.voxel_size), fullfile(save_path,'R2prime.nii'));
- save_nii(make_nii(single(Res_map(:,:,:,1) - Res_map(:,:,:,2)), params.voxel_size), fullfile(save_path,'X_composite.nii'));
APART_QSM_single_ori_demo.m at commit c49bad4, no license · at the source
Overview
- Department of Biomedical Engineering University of Alberta Edmonton Alberta Canada
- Department of Radiology and Diagnostic Imaging University of Alberta Edmonton Alberta Canada
Abstract
Susceptibility source separation (SSS) enables independent evaluation of both paramagnetic iron and diamagnetic myelin in the human brain. The aim of this work was to analyze healthy brain lifespan trajectories of paramagnetic and diamagnetic susceptibilities in deep gray matter (DGM) and white matter (WM) from a large database (339 subjects, 5 to 90 years), all acquired at 3 T on the same scanner, using χ‐separation and comparing it to two other common SSS methods (χ‐sepnet and APART‐QSM). A 3D multiple echo gradient echo sequence was used to measure phase, R2* and QSM, as well as dual echo fast spin echo to measure R2. The mean value of WM and DGM regions was calculated for SSS output maps and plotted against age to evaluate trajectories across the lifespan. With χ‐separation, most DGM regions showed an increasing trend with age in the paramagnetic map, except for thalamus, which showed an inverted‐U quadratic trajectory, and all DGM regions showed an increase in diamagnetic content with age. In WM, for the paramagnetic maps, body of corpus callosum, splenium and corticospinal tract showed an inverted quadratic trajectory, cingulum an increasing exponential, while no significant changes were seen in genu. For the diamagnetic WM maps, all regions followed a similar trajectory, increase in early life, peak around 40 to 60 years, and decrease with age. The different SSS approaches yielded different curve shapes and mean values in many instances. For example, APART‐QSM had consistently lower ppb values, χ‐sepnet had biologically unexpected results for early ages, and χ‐separation data had higher standard deviation of best‐fit residuals when compared to the other evaluated methods for all analyzed regions and maps. All SSS methods enabled depiction of independent iron and myelin trends; however, different results between methods suggest caution in choosing SSS methods and the need for further methodological advances.
Reproduced under the paper's license (CC BY), from the paper cited above.
Repositories
Its files are read in the Code ↔ Paper reader above, with 4 matches between paragraphs and lines of code.
SNU-LIST/chi-separation
29f901c39c70cf71eca4ba46cd8da2a67d16d874, 3 June 2026Availability: 1 check, the latest on 26 September 2026: the link answers
- 26 September 2026: the link answers
1 file
- README.md, Text, 45 lines
SNU-LIST/chi_sepnet
99ea6e6260b596fba2eeda42326da7129513e9de, 12 September 2025Availability: 1 check, the latest on 26 September 2026: the link answers
- 26 September 2026: the link answers
10 files
- Code/
custom_dataset.py , Python, 319 lines - Code/
logging_helper.py , Python, 95 lines - Code/
network.py , Python, 188 lines - Code/
test.py , Python, 389 lines - Code/
test_params.py , Python, 143 lines - Code/
train.py , Python, 415 lines - Code/
train_data_patch.py , Python, 341 lines - Code/
train_params.py , Python, 148 lines - Code/
utils.py , Python, 532 lines - README.md, Text, 44 lines
AMRI-Lab/APART-QSM
c49bad4301b35c430a21a29154180ed18ba94966, 31 March 2025Availability: 1 check, the latest on 26 September 2026: the link answers
- 26 September 2026: the link answers
12 files
- multi_orientation/
APART_QSM_multi_ori_demo , MATLAB, 81 lines, 2 matches.m - multi_orientation/
dipole_kernel.m , MATLAB, 89 lines - single_orientation/
@TVOP/ , MATLAB, 10 linesTVOP.m - single_orientation/
@TVOP/ , MATLAB, 4 linesctranspose.m - single_orientation/
@TVOP/ , MATLAB, 15 linesmtimes.m - single_orientation/
@TVOP/ , MATLAB, 24 linesprivate/ D.m - single_orientation/
@TVOP/ , MATLAB, 27 linesprivate/ adjD.m - single_orientation/
@TVOP/ , MATLAB, 4 linestimes.m - single_orientation/
APART_QSM_single_ori_dem , MATLAB, 58 lines, 2 matcheso.m - single_orientation/
dipole_kernel.m , MATLAB, 89 lines - single_orientation/
gradient_mask_all.m , MATLAB, 62 lines - README.md, Text, 11 lines
The paper's code and data availability statement is in the Data section.
Tracing map
Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.
What the map holds:
- 3 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
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- neither the text of the paper nor the code itself.
Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.
Data
Datasets cited
- neurovault.org/
images/ , at neurovault.org; found in the references1401
Data Availability Statement
The measurements (mean value per subject with age and sex, for all reported regions and metrics—χpara, χdia, QSM, R2′ and R2*) and analysis scripts of this study are available from the corresponding author upon request. Participant MRI images and maps are not publicly available due to ethical considerations.
Reproduced under the paper's license (CC BY), from the paper cited above.
Versions
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Version 3, 28 September 2026
- Publisher: n/a → Wiley
Version 1, 27 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 4 keywords, 16 MeSH terms, 2 funders, 47 references.
Cite
This paper
Assunção, T. B. O., Naji, N., Seres, P., Beaulieu, C., & Wilman, A. H. (2026). Susceptibility Source Separation Unveils Paramagnetic and Diamagnetic Trajectories in Healthy Brains From 5 to 90 Years. NMR in biomedicine, 39(8), e70349. https://
BibTeX
@article{assuncao2026sus
author = {Assunção, Tereza Beatriz Oliveira and Naji, Nashwan and Seres, Peter and Beaulieu, Christian and Wilman, Alan H.},
title = {{Susceptibility Source Separation Unveils Paramagnetic and Diamagnetic Trajectories in Healthy Brains From 5 to 90 Years}},
journal = {NMR in biomedicine},
year = {2026},
month = aug,
volume = {39},
number = {8},
pages = {e70349},
publisher = {Wiley},
issn = {0952-3480},
doi = {10.1002/
url = {https://
pmid = {42405451},
pmcid = {PMC13334517}
}
RIS
TY - JOUR
AU - Assunção, Tereza Beatriz Oliveira
AU - Naji, Nashwan
AU - Seres, Peter
AU - Beaulieu, Christian
AU - Wilman, Alan H.
TI - Susceptibility Source Separation Unveils Paramagnetic and Diamagnetic Trajectories in Healthy Brains From 5 to 90 Years
T2 - NMR in biomedicine
J2 - NMR Biomed
PY - 2026
DA - 2026/
VL - 39
IS - 8
SP - e70349
SN - 0952-3480
PB - Wiley
DO - 10.1002/
UR - https://
LA - en
ER -
CSL-JSON
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