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- Creator:
- Murguia, Amaya, Swanson, Scott D., Scheven, Ulrich, Jacobson, Andrea, Nielsen, Jon-Fredrik, Fessler, Jeffrey A., and Seraji-Bozorgzad, Navid
- Description:
- Validation of quantitative MRI (qMRI) parameters with histology is often done with ex vivo fixed tissue samples. Freezing is another common form of tissue preservation, but the effects of freezing and thawing tissue on myelin-sensitive qMRI parameters and their correlation with histology require further analysis. To study the effects of freezing vs. fixing tissue on myelin-sensitive parameters, we conducted myelin water imaging, off-resonance RF saturation magnetization transfer (MT), and selective inversion recovery MT MRI experiments on 14 fresh, thawed, and fixed sheep brain tissue samples to calculate various surrogate measures of myelin content. These measures were compared with luxol fast blue (LFB) histological stain results. 14 sheep brain tissue samples were scanned fresh. Half were frozen and subsequently thawed and scanned again. The second half were fixed and scanned again. Then all samples were fixed and sent for histological processing. This folder contains the MR and histology images collected for this study. All data are stored as mat files. The top level folder sheep_data_paper has subfolders: fresh_thawed: holds the data for the samples scanned fresh and thawed (S1-S7) fresh_fixed: holds the data for the samples scanned fresh and fresh_fixed (S8-S14) Each structure variable (data.mat) holds data for a specific sample and a specific tissue preparation (fresh, thawed, or fixed). The data variable has the following fields: gre: gradient echo scan data (128 x 128 x 5) fse: fast spin echo scan data (256 x 256 x 5) mese: multi-echo spin echo scan data for MWF mapping (128 x 128 x 5 x 104) b0data: gradient echo scan data for B0 mapping (128 x 128 x 5 x 4) b1data: EPI scan data for B1 mapping (32 x 32 x 5 x 9) t1data: EPI inversion recovery data for T1 mapping (64 x 64 x 5 x 21) mtdata: gradient echo data for quantitative MT analysis (128 x 128 x 4 x nf) hist: Luxol fast blue stain / Cresyl violet counterstain (LFB) histology image
- Keyword:
- myelin, magnetic resonance imaging, histology, quantitative MRI, ex vivo tissue, myelin water imaging, magnetization transfer, and luxol fast blue
- Citation to related publication:
- Murguia, A., Swanson, S. D., Scheven, U., Jacobson, A., Nielsen, J. F., Fessler, J. A., & Seraji-Bozorgzad, N. (2025). Impact of Tissue Sample Preparation Methods on Myelin-Sensitive Quantitative MR Imaging. bioRxiv, 2025-05.
- Discipline:
- Health Sciences and Engineering
-
- Creator:
- Whitaker, Steven T., Nataraj, Gopal, Nielsen, Jon-Fredrik, and Fessler, Jeffrey A.
- Description:
- File: P,jf06Sep2019,mese.7 The multi-echo spin echo (MESE) data was acquired using a 3D acquisition with an initial 90 degree excitation pulse followed by 32 refocusing (180 degree) pulses, resulting in 32 echoes with echo spacing of 10 ms. The repetition time of the sequence was 1200 ms. Each refocusing pulse was flanked by crusher gradients to impart 14 cycles of phase across the imaging volume. The initial excitation pulse had time-bandwidth product of 6, duration of 3 ms, and slab thickness of 0.9 cm, and each refocusing pulse had time-bandwidth product of 2, duration of 2 ms, and slab thickness of 2.1 cm. The scan took 36 min 11 s and covered a field of view (FOV) of 22 x 22 x 0.99 cm^3 with matrix size 200 x 200 x 9., File: P,jf06Sep2019,b1.7 The Bloch-Siegert (BS) scans were acquired using a 3D acquisition. The excitation pulse of these scans had time-bandwidth product of 8 and duration of 1 ms. The pair of scans used +/-4 kHz off-resonant Fermi pulses between excitation and readout. The BS scans took 2 min 40 s in total and covered a FOV of 22 x 22 x 0.99 cm^3 with matrix size 200 x 50 x 9., File: P,jf06Sep2019,mwf.7 The small-tip fast recovery (STFR) scans were acquired using a 3D acquisition. The first two and last two scans were pairs of spoiled gradient-recalled echo (SPGR) scans with echo time difference of 2.3 ms. (In the related paper, only the first set was used, i.e., only 11 of the 13 scans were used.) The remaining scans used scan parameters that were optimized to minimize the Cramer-Rao Lower Bound (CRLB) of estimates of myelin water fraction (MWF). The RF pulses had time-bandwidth product of 8 and duration of 1 ms. Each pair of SPGR scans took 58 s and the nine STFR scans took 3 min 36 s for a total scan time of 5 min 32 s (4 min 34 s if one pair of SPGR scans is ignored). The scans covered a field of view (FOV) of 22 x 22 x 0.99 cm^3 with matrix size 200 x 200 x 9., File: meseslice5.mat Contains the 32 echoes of the MESE image data for the middle slice of the imaging volume. Saved using Mathworks MATLAB R2019a., File: b1slice5.mat Contains the transmit field inhomogeneity map for the middle slice of the imaging volume., File: recon.jld Key "img" contains the 11 STFR images for the middle slice of the imaging volume. Key "b0map" contains a field map estimated from the two SPGR scans. Key "mask" contains a mask of the voxels for which to estimate MWF. Key "T1img" contains a T1-weighted image for anatomical reference., File: headmask.mat Contains a mask for visualizing just the brain (ignores the skull) for the middle slice of the imaging volume., File: rois.mat Contains masks for various regions of interest (ROIs), used for computing statistics. Keys "mtopleft", "mtopright", "mbottomleft", and "mbottomright" refer to the corresponding locations on the anatomical reference image (see related paper). Key "mic" refers to the internal capsules, and key "mgm" refers to a gray matter ROI., The raw data files (P-files) can be read into the Julia programming language using the Julia version of the Michigan Image Reconstruction Toolbox ( https://github.com/JeffFessler/MIRT.jl) or into MATLAB using TOPPE ( https://github.com/toppeMRI/toppe). The reconstructed slices used in the related paper are provided for convenience, and are stored in .mat files that can be loaded into Julia (using the package MAT.jl) or MATLAB, and a .jld file that can be loaded into Julia (using the package JLD.jl). The Julia code for processing the data to create MWF maps is hosted publicly on GitHub at https://github.com/StevenWhitaker/STFR-MWF., and Files: toppe-master.zip and MIRT.jl-master.zip are archived versions of the TOPPE and Michigan Image Reconstruction Toolbox code sets from GitHub as of 2/28/2020.
- Keyword:
- myelin, machine learning, kernel learning, magnetic resonance imaging, and scan design
- Citation to related publication:
- Whitaker, S. T., Nataraj, G., Nielsen, J.-F., & Fessler, J. A. (2020). Myelin water fraction estimation using small-tip fast recovery MRI. Magnetic Resonance in Medicine, 84(4), 1977–1990. https://doi.org/10.1002/mrm.28259
- Discipline:
- Health Sciences and Engineering