Evaluation of the clinical utility of maximum intensity projections of <scp>3D contrast‐enhanced</scp>, <scp>T1</scp>‐weighted imaging for the detection of brain metastases
Bibliographic record
Abstract
BACKGROUND: To visualize and assess brain metastases on magnetic resonance imaging, radiologists face an ever-increasing pressure to perform faster and more efficiently. The usage of maximum intensity projections (MIPs) of contrast-enhanced T1-weighed (T1ce) magnetization-prepared rapid acquisition with gradient echo (MP-RAGE) images proposes to increase reading efficiency by increasing lesion conspicuity while reducing in the number of images to be reviewed. AIM: To assess if MIPs save reading time and achieve the same level of diagnostic accuracy as standard 1 mm T1ce images for the detection of brain metastases. METHODS: ) images were analyzed and post-processed into 5 and 10 mm MIPs. Two readers evaluated the randomly assorted images and recorded reading time. Reading time differences were analyzed using the Wilcoxon test, and inter-reader statistics were performed using Bland-Altman plots. RESULTS: About 22.5 61.2 s/study and 43.8 ± 159.9 s/study were saved using 5 and 10 mm MIPs, respectively. Combined average sensitivity was 92.0% for 5 mm MIPs and 86.3% for 10 mm MIPs compared to standard 1 mm axial slices, with an average rate of 0.98 and 0.57 false positives per study, respectively CONCLUSION: While 5 mm and 10 mm T1ce MP-RAGE MIPs showed a clinical benefit in reducing reading times for evaluation of brain metastases, they should be used in conjunction with standard 1 mm images for best sensitivity and specificity, a practice which possibly annuls their benefit.
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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 | 0.004 | 0.010 |
| 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".