Simultaneous R<sub>2<sup>*</sup></sub>and quantitative susceptibility mapping measurement enables differentiation of thrombus hematocrit and age: an in vitro study at 3 T
Bibliographic record
Abstract
Background The efficacy of acute ischemic stroke treatment is affected by thrombus composition and age, yet no diagnostic method capable of quantitative thrombus characterization currently exists. This in vitro study evaluates the use of R 2 * , quantitative susceptibility mapping (QSM), and proton density fat fraction (FF) maps derived from a single gradient echo (GRE) MRI acquisition for characterizing clot of various hematocrit, as well as added calcified and lipidic components, throughout aging. Methods Two thrombus phantoms containing porcine clots (10–60% hematocrit, one with added calcium or lard) were scanned serially throughout 6 days of aging. Three-dimensional multi-echo GRE imaging was used to generate R 2 * , QSM, and FF maps, from which mean values for all clots at every time point were obtained. Receiver operating characteristic analysis was used to derive thresholds differentiating acute from chronic clot, and measured R 2 * and QSM were tested for their ability to estimate clot hematocrit. Results R 2 * and QSM varied minimally over the first 6 hours of aging (acute), and QSM was found to linearly relate to clot hematocrit. Beyond 6 hours (chronic), R 2 * and QSM increased considerably over time and hematocrit could be estimated from the R 2 * /QSM ratio. R 2 * and QSM thresholds of 22 s -1 and 0.165 ppm differentiated acute from chronic clots with a sensitivity/specificity of 100%/100% and 85%/92%, respectively. QSM and FF maps definitively distinguished calcium and lipid, respectively, from clots of any hematocrit and age. Conclusions R 2 * , QSM, and FF from a single multi-echo GRE scan discriminated hematocrit and age, and distinguished calcification and lipid withinin vitro clot.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 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 teacher head, 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".