Investigation of a Logistic Model for T2* Dynamic Susceptibility Contrast Magnetic Resonance Imaging (dscMRI) Perfusion Studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There are a number of T1- and T2-based dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic modeling approaches to study cancer microvasculature. Alternatively, model-free approaches offer an easy, quantitative assessment of microcirculation. In this work, we investigate a 6-parameter model-free approach applied to a T2*-weighted echo-planar imaging bolus response curve. We tested this new approach on a small cohort of patients with clinically diagnosed primary rectal carcinoma before adjuvant chemoradiotherapy and surgical excision. Comparison with healthy muscle tissue shows that logistic parameters P1/P2, P4, and P5 offer good discrimination between tumor and healthy tissue. Bolus response logistic parameters P4 and P5 have been implicated in previous T1-based works as being important in the assessment of cancer malignancy. Further comparison of T2* parameters with signal attenuation amplitude (maximum signal drop) and percentage baseline signal loss also corroborates the models' ability to quantify the microenvironment.
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.
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 | 0.001 | 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 it