Assessment of quantitative susceptibility mapping (QSM) and oxygen extraction fraction (OEF) in the spectrum of Alzheimer’s disease clinical presentations
Bibliographic record
Abstract
Abstract Background Different methods have been proposed to assess vascular dysfunction in Alzheimer’s disease (AD), mild cognitive impairment (MCI), and cognitively unimpaired (CU) subjects including quantitative susceptibility mapping (QSM), and recently oxygen extraction fraction (OEF). QSM is sensitive to the presence of iron and is a non‐invasive MR approach to measure local tissue susceptibility with high spatial resolution. OEF is a measure of the percentage of oxygen taken from the brain’s blood supply and relates directly to brain oxygen metabolism. Here, we aimed to examine QSM (Figure1) and OEF (Figure1) potential in differentiating AD, MCI, and CU. Method A cohort of 310 subjects with AD (n = 48), MCI (n = 80), and CU (n = 182) were recruited. All the patients received 3D gradient‐recalled echo sequence MRI. All QSM images were constructed by MEDI+0 and OEF images were constructed by QSM+qBOLD model with CCTV (Temporal clustering, tissue composition, and total variation). Eighty‐two various brain regions of interest (ROI) and 6 Braak ROI were investigated in the current study. ANOVA and Posthoc least significant difference (LSD) tests were implemented for each ROI over AD, MCI, and CU. Result Over Braak ROI analysis, the ANOVA test showed that the average susceptibility of QSM with Braak 4 ROI is significantly different (p<0.001). LSD test showed that Braak 4 ROI of QSM is significantly different between AD vs. MCI and AD vs. CU (p<0.001). Braak 2 ROI of OEF was significantly different between AD vs. MCI and AD vs. CU (p = 0.21 and p = 0.32, respectively). Over brain ROI, the ANOVA test showed QSM right and left posterior cingulate and right Caudate were significantly different (p<0.001). Besides, these ROIs were significantly different between AD vs. MCI and AD vs. CU, according to the LSD test. Over brain ROI, OEF right Caudate was significantly different (p<0.001) followed by left Caudate and Right transverse temporal with p = 0.002 based on the ANOVA test. However, right and left Caudate were just significantly different between AD vs. CU (p<0.001) based on the LSD test (Table 1 and 2). Conclusion QSM and OEF are affordable non‐invasive MR approaches to assess vascular dysfunction in the spectrum of clinical presentations of AD.
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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 | 0.002 |
| 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) | 0.001 | 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".