scholarly journals Brain virtual histology with X-rayphase-contrast tomographyPart I: whole-brain myelin mapping in white-matter injury models

2021 ◽  
Author(s):  
Matthieu Chourrout ◽  
Hugo Rositi ◽  
Elodie Ong ◽  
Violaine Hubert ◽  
Alexandre Paccalet ◽  
...  
2021 ◽  
Author(s):  
Matthieu Chourrout ◽  
Hugo Rositi ◽  
Elodie Ong ◽  
Violaine Hubert ◽  
Alexandre Paccalet ◽  
...  

AbstractWhite-matter injury leads to severe functional loss in many neurological diseases. Myelin staining on histological samples is the most common technique to investigate white-matter fibers. However, tissue processing and sectioning may affect the reliability of 3D volumetric assessments. The purpose of this study was to propose an approach that enables myelin fibers to be mapped in the whole rodent brain with microscopic resolution and without the need for strenuous staining. With this aim, we coupled in-line (propagation-based) X-ray phase-contrast tomography (XPCT) to ethanol-induced brain sample dehydration. We here provide the proof-of-concept that this approach enhances myelinated axons in rodent and human brain tissue. In addition, we demonstrated that white-matter injuries could be detected and quantified with this approach, using three animal models: ischemic stroke, premature birth and multiple sclerosis. Furthermore, in analogy to diffusion tensor imaging (DTI), we retrieved fiber directions and DTI-like diffusion metrics from our XPCT data to quantitatively characterize white-matter microstructure. Finally, we showed that this non-destructive approach was compatible with subsequent complementary brain sample analysis by conventional histology. In-line XPCT might thus become a novel gold-standard for investigating white-matter injury in the intact brain. This is Part I of a series of two articles reporting the value of in-line XPCT for virtual histology of the brain; Part II shows how in-line XPCT enables the whole-brain 3D morphometric analysis of amyloid-β (Aβ) plaques.HighlightsX-ray phase-contrast tomography (XPCT) enables myelin mapping of the whole brainXPCT detects and quantifies white-matter injuries in a range of diseasesFiber directions and anisotropy metrics can be retrieved from XPCT dataXPCT is compatible with subsequent conventional histology of brain samplesXPCT is a powerful virtual histology tool that requires minimal sample preparationGraphical Abstract


2013 ◽  
Vol 1495 ◽  
pp. 11-17 ◽  
Author(s):  
Yingzhu Chen ◽  
Qiong Yi ◽  
Gang Liu ◽  
Xue Shen ◽  
Lihui Xuan ◽  
...  

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e100451 ◽  
Author(s):  
Xuetao Mu ◽  
Binbin Nie ◽  
Hong Wang ◽  
Shaofeng Duan ◽  
Zan Zhang ◽  
...  

2016 ◽  
Vol 33 (20) ◽  
pp. 1834-1847 ◽  
Author(s):  
Wei Zhao ◽  
James C. Ford ◽  
Laura A. Flashman ◽  
Thomas W. McAllister ◽  
Songbai Ji

2019 ◽  
Author(s):  
A Brosius Lutz ◽  
P Renz ◽  
M Spinelli ◽  
V Haesler ◽  
S Liddelow ◽  
...  

Author(s):  
Thomaz R. Mostardeiro ◽  
Ananya Panda ◽  
Robert J. Witte ◽  
Norbert G. Campeau ◽  
Kiaran P. McGee ◽  
...  

Abstract Purpose MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma. Materials and methods A whole-brain 3D isotropic 1mm3 acquisition under a 3.0T field strength was used to obtain MRF T1 and T2-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included the meningioma, caudate head, centrum semiovale, contralateral white matter and thalamus. For both phantom and subjects, mean values of both T1 and T2 estimates were obtained. Statistical significance of differences in mean values between the meningioma and other brain structures was tested using a Friedman’s ANOVA test. Results MR fingerprinting phantom data demonstrated a linear relationship between measured and reference relaxometry estimates for both T1 (r2 = 0.99) and T2 (r2 = 0.97). MRF T1 relaxation times were longer in meningioma (mean ± SD 1429 ± 202 ms) compared to thalamus (mean ± SD 1054 ± 58 ms; p = 0.004), centrum semiovale (mean ± SD 825 ± 42 ms; p < 0.001) and contralateral white matter (mean ± SD 799 ± 40 ms; p < 0.001). MRF T2 relaxation times were longer for meningioma (mean ± SD 69 ± 27 ms) as compared to thalamus (mean ± SD 27 ± 3 ms; p < 0.001), caudate head (mean ± SD 39 ± 5 ms; p < 0.001) and contralateral white matter (mean ± SD 35 ± 4 ms; p < 0.001) Conclusions Phantom measurements indicate that the proposed 3D-MRF sequence relaxometry estimations are valid and reproducible. For in vivo, entire brain coverage was obtained in clinically feasible time and allows quantitative assessment of meningioma in clinical practice.


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