Apparent transverse relaxation () on <scp>MRI</scp> as a method to differentiate treatment effect (pseudoprogression) versus progressive disease in chemoradiation for malignant glioma
Bibliographic record
Abstract
Abstract Introduction Pseudoprogression (ps PD ) is a transient post‐treatment imaging change that is commonly seen when treating glioma with chemotherapy and radiation. The use of apparent transverse relaxation rate ( ), which is calculated from a contrast‐free multi‐echo gradient echo Magnetic Resonance Imaging ( MRI ) sequence, may allow for quantitative identification of patients with suspected ps PD . Methods We acquired a multi‐echo gradient echo sequence using a 3T‐Siemens Prisma MRI . The signal decay through the echoes was fitted to provide the coefficient. We segmented the T 1 ‐gadolinium enhancing the image to provide a contrast enhancing lesion ( CEL ) and the FLAIR hyperintensity to provide a non‐enhancing lesion ( NEL ). These regions of interest were applied to the multi‐echo gradient echo to acquire a mean within the CEL and NEL . We additionally acquired ADC data to attempt to corroborate our findings. Results We found that patients who later exhibited PD exhibited a higher within the CEL as well as a higher ratio of CEL to NEL . Our data correctly distinguished pseudoprogression from treatment effect in 9/9 patients, while ADC corrected identified 7/9 patients using an absolute ADC of 1200 × 10 −6 mm 2 /s. Conclusions Our method seems promising for the accurate identification of ps PD , and the technique is amenable to evaluation in larger, multi‐centre patient cohorts.
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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 | 0.002 |
| 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 | 0.000 | 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".