The application of magnetic susceptibility separation for measuring cerebral oxygenation in preterm neonates
Bibliographic record
Abstract
Abstract Background Quantitative susceptibility mapping (QSM), a magnetic resonance imaging (MRI) modality sensitive to deoxyhemoglobin, is a promising method for measuring cerebral oxygenation in human neonates. Paramagnetic sources, like deoxyhemoglobin, however, can be obscured by diamagnetic sources such as water and myelin. This study evaluated whether QSM images, or isolated paramagnetic components, are more accurate for measuring oxygenation of cerebral veins of preterm neonates, and explored oxygenation differences between the major cerebral veins. Methods 19 preterm neonates were scanned on at term equivalent age on a 3T MRI using a multi-echo susceptibility-weighted imaging sequence. Susceptibility values were calculated from QSM images to determine oxygen saturation (SvO 2 ) in the superior sagittal sinus (SSS) and central cerebral veins (CCV). The paramagnetic components of QSM images were isolated, and SvO 2 values were recalculated. Results The mean SvO 2 values from QSM were 72.4% (SD, 3.4%) for the SSS and 68.7% (SD, 3.5%) for the CCV. SvO 2 values for paramagnetic components were 58.1% (SD, 7.3%) for the SSS and 57.7% (SD, 7.0%) for the CCV. Conclusion While paramagnetic component decomposition yielded SSS values closer to those found in the literature, it increased variability. No significant oxygenation differences were found between the SSS and CCV, contrasting with prior studies. Impact This study evaluated the use of QSM and its paramagnetic components to measure cerebral oxygenation in neonates. By comparing susceptibility-derived oxygen saturation (SvO 2 ) in the superior sagittal sinus (SSS) and central cerebral veins (CCV), it adds to the field of neonatal cerebral oxygenation measurement. Decomposing QSM into paramagnetic components shows potential for improving SvO 2 accuracy, particularly in the SSS, though variability remains a challenge. The results suggest no significant oxygenation difference between the SSS and CCV, contrasting with previous findings, indicating a need for further research on neonatal venous oxygenation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".