Natural history of prostatic lesions on serial multiparametric magnetic resonance imaging
Bibliographic record
Abstract
INTRODUCTION: The natural history of prostatic lesions identified on multiparametric magnetic resonance imaging (mpMRI) is largely unknown. We aimed to describe changes observed over time on serial MRI. METHODS: All patients with ≥2 MRI studies between 2008 and 2015 at our institution were identified. MRI progression was defined as an increase in Prostate Imaging Reporting and Data System (PI-RADS; version 2) or size of existing lesions, or the appearance of a new lesion PIRADS ≥4. Patients on active surveillance (AS) were analyzed for correlation of MRI progression to biopsy reclassification. RESULTS: A total of 83 patients (54 on AS and 29 for diagnostic purposes) underwent serial MRI, with a mean interval of 1.9 years between scans. At baseline, 115 lesions (66 index, 49 non-index) were identified. Index lesions were more likely than non-index lesions to increase in size ≥2 mm (36.2 vs. 7.3 %; p=0.002). Overall progression was more likely to be seen among the index cohort (34.8 vs. 7.6%; p<0.001). New lesions with PIRADS ≥4 were seen on second imaging in 13 (16.5%) men, and became the index lesion in 29 cases (34.9%). Eighteen men on AS showed evidence of MRI progression (five with new lesions, 13 with progression of a previous lesion). Biopsy reclassification was present in three men (16.7%) with and seven men without MRI progression (19.4%). CONCLUSIONS: Overall changes in size and PIRADS scores of index lesions on MRI were small. New lesions were common, but usually did not alter management.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".