Standardized reporting templates with mandatory reporting fields and “pick-list” options improve use of Prostate Imaging and Data Reporting System version 2 in clinical practice: A plan-do-study-act analysis
Bibliographic record
Abstract
The Prostate Imaging and Data Reporting System version 2 (PI-RADS v2) aims to simplify performance, interpretation, and reporting of prostate magnetic resonance imaging (MRI).1 PI-RADS v2 introduced probability scores (assessment categories, Table 1), which indicate the likelihood of clinically significant cancer (Gleason score ≥7)2 based upon MRI findings. PI-RADS v2 has been validated as accurate for detection of cancers and improves interobserver agreement. 3 Despite this, in our experience, use of PI-RADS v2 scores in practice is variable. This study evaluated a method to improve use of PI-RADS v2 scores by using a plan-do-study-act (PDSA) analysis. Table 1 Summary of Prostate Imaging and Data Reporting System (PI-RADS) version 2 assessment categories
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.
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 | 0.019 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".