Hyperoxygenation Differentiates Vascular Lesions From Parenchymal Lesions Using Susceptibility Weighted MRI In Mice With Experimental Autoimmune Encephalomyelitis (P1.166)
Bibliographic record
Abstract
OBJECTIVE: To determine whether using hyperoxygenation can differentiate between vascular lesions and parenchymal white matter lesions in the experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis (MS) with susceptibility weighted imaging (SWI). BACKGROUND: SWI detects lesions in MS patients not seen with conventional magnetic resonance imaging (MRI) methods. Previously in the EAE model (Nathoo et al., Multiple Sclerosis J 19:721, 2013), we observed two types of lesions using SWI: 1) vascular lesions, due to deoxyhemoglobin and 2) parenchymal white matter lesions, due to iron deposition and demyelination. We aimed to determine if these two lesion types could be differentiated by increasing the inspired oxygen, hypothesizing that vascular lesions would alter in appearance with high oxygen in SWI, whereas parenchymal lesions would not. DESIGN/METHODS: Lumbar spinal cords of control and EAE mice were imaged at 9.4T for SWI with 30% O2/70% N2 then 100% O2. A subset of mice were imaged with these gases and then after perfusion (to remove blood). Lesions (hypointensities, or dark spots) were counted and compared between control and EAE mice, and the number of hypointensities seen with 30% O2 was compared with the number unchanged with 100% O2. RESULTS: Most hypointensities seen with 30% O2 (control: 8.6±0.8, peak EAE: 13.4±1.3; mean±SEM) altered in appearance with 100% O2 (control: 7.1±0.9, p<0.001; EAE: 8±1.7, p<0.01). Hypointensities changing in appearance with 100% O2 disappeared after perfusion, supporting that they are due to deoxyhemoglobin. Parenchymal lesions did not change in appearance with hyperoxygenation. CONCLUSIONS: Using hyperoxygenation with SWI differentiates between vascular and parenchymal lesions in EAE in vivo. This method can be applied in MS, paving the way to investigate the pathophysiology of venous hypoxia and iron deposition in MS. Study Supported by: CIHR, NSERC, Alberta Innovates - Health Solutions, MS Society of Canada, and the Alberta endMS Regional Research and Training Centre of the endMS Research and Training Network.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".