P1‐134: Magnetic Resonance Spectroscopy (MRS) analysis in Alzheimer's disease ‐ a novel approach for integrating metabolite spectra, tissue segmentation and perfusion data
Bibliographic record
Abstract
Magnetic Resonance Spectroscopy (MRS) is frequently used for in-vivo study of brain health and pathology, which can allow inferences about local metabolic tissue changes1. Integration with other modalities such as T1/PD/T2 segmentation and perfusion (SPECT, MR, or CT) can further inform our understanding of MRS. Scans were acquired comparing 20 probable AD subjects with varying degrees of white-matter-hyperintensities (WMH) with 21 normal controls (mean ages 69.7 and 71.3 respectively). Standard T1-weighted, interleaved proton-density and T2-weighted, and single voxel MRS were acquired on a GE 1.5T Signa scanner. MRS prescriptions were placed on confluent WMH when visible. SPECT perfusion data was also acquired on a Phillips triple-head gamma camera. T1 tissue segmentation was performed using a previously published method2. WMH volumes were separately obtained using the program Lesion Explorer©3. Spectral profiles were obtained with the program LCmodel, with concentrations measured relative to creatine4. All images and series were coregistered to T1 space using AIR 5.05. AD subjects showed a negative correlation between relative gray matter volume (GM) and glycerophosphocholine+phosphocholine/creatine (GPC+PCh/Cr) (r=-0.587, p=0.005) and a positive correlation between GM and glutamate+glutamine/creatine (Glu+Gln/Cr) (r=0.538, p=0.012). NC's showed a positive correlations between normal-appearing-white-matter (NAWM) and both N-acetyl-aspartate/creatine (NAA/Cr) (r=0.423, p=0.035) and GPC+PCh/Cr (r=0.417, p=0.038). Additionally, SPECT perfusion negatively correlated with relative WMH volume within the MRS sampling voxels (r=-0.585, p=0.007). The presence of a positive relationship between NAA and NAWM in NC's and the lack thereof in the AD subjects may indicate the comparative health of brain tissues in these groups with the AD group showing greater axonal comprise. The positive relationship between GM volume and Glu+Gln/Cr in the AD group may reflect neurodegenerative glutamate toxicity. The perfusion correlation shows that the greater the volume of WMH, the greater the decrease in tissue perfusion. MRS can be useful for gaining valuable insight in to metabolic changes taking place in AD and the aging brain. This technique is being extended to a larger sample, and will incorporate diffusion tensor data within the MRS voxels to further understand the disease processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".