P2‐021: Detection of β‐amyloid plaques in human AD brain tissue specimen using MR imaging
Bibliographic record
Abstract
There are no human in vivo magnetic resonance (MR) imaging techniques that specifically demonstrate the formation of β-amyloid plaques of Alzheimer's Disease (AD). High field strength MR studies of human specimens and in vivo AD animal model brain tissue have shown evidence that MR can detect β-amyloid plaques on the basis of iron co-localization with plaques. Here we adapt and exploit an optimized form of the highly SNR-efficient and iron-sensitive Fast Imaging Employing STeady State Acquisition (FIESTA) MR sequence for the detection of AD β-amyloid plaques, using a clinical 3T system supported by a gradient insert in order to provide the spatial resolution for high-resolution imaging of brain tissue specimens. MRI was performed on a 3T scanner (GE Signa HD) interfaced with an insertable gradient coil [peak strength: 500 mT/m, peak slew rate: 3200 T/m/s] and 3.5cm diameter solenoidal RF coil. Isotropically resolved FIESTA images of n=5 autopsy AD brain tissue sets (CERAD definite AD) were acquired in 218 minutes [(100μm); TR/TE 21/11 ms; FA 20°; BW ±8 kHz; phase cycling number/recon: 8/sum-of-squares]-. Datasets were analyzed for the presence of focal signal voids. Subsequent histological sections were stained for β-amyloid protein. High-resolution imaging revealed spherical signal voids throughout the specimen and we observed correlations between patterns found in MRI and histology. A subset of about 10% of plaques in immunohistochemistry sections stained for β-amyloid correlated to spherical signal voids throughout the brain specimen parenchyma on matched high-resolution 3DFIESTA images. However the task of β-amyloid plaque detection was complicated by a second paramagnetic intraparenchymal deposition because post-mortem formalin fixed human AD brain tissue specimens feature intravascular blood products caused by perimortal stasis. Using Minimum Intensity Projection (MinIP) spherical intra-parenchymal and tubular intravascular signal voids could be distinguished. This study provides evidence that clinical field strength MR has the ability to detect microscopic iron associated with human β-amyloid plaques although our gradient insert permits gradient amplitudes and slew rates that are presently not available for human studies with clinical MR systems. We will continue to explore this MR imaging tool for further specific cross-sectional analyses of AD brain.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".