Multi‐parametric (mp) MRI of prostatic ductal adenocarcinoma
Bibliographic record
Abstract
BACKGROUND: Prostatic ductal adenocarcinoma (DCa) is an aggressive variant of conventional adenocarcinoma (CCa) with mixed DCa and CCa tumors comprising up to 5% of all prostate cancers. DCa may be underestimated on T2-weighted (T2W) MRI. This study assessed the mp-MRI appearance of DCa as compared with CCa. METHODS: With research ethics board approval, we identified 38 patients who underwent mp-MRI (T2W, DWI, and DCE) and radical prostatectomy (RP) between 2012 and 2014. Eight DCa in 8 patients and 39 CCa tumor foci in 30 consecutive patients were identified. Tumor volume, apparent diffusion coefficient (ADC;10(-3) mm(2) /s), and time-signal intensity (SI) curves were calculated. Parametric data were compared using the Kruskal-Wallis test and univariate regression. Time-SI curves were compared using the chi-square test. RESULTS: Tumor volumes were: 1.62(±1.02) for DCa, 1.03(±0.54) for Gleason 9, 0.88(±0.93) for Gleason 7/8, and 0.26(±0.14) mL for Gleason 6. There was no difference in size between DCa and Gleason 9 (P = 0.22); however, DCa were larger than Gleason 7/8 (P = 0.03) and Gleason 6 (P = 0.003) tumors. ADC values were: 0.789(±0.22) for DCa, 1.01(±0.19) for Gleason 9, 0.992(±0.23) for Gleason 7/8 and 1.389(±0.41) 10(-3) mm(2) /s for Gleason 6 tumors. There was no difference in ADC between DCa and Gleason 9 (P = 0.14) or Gleason 7/8 (P = 0.055) tumors. There was a difference in ADC for DCa and Gleason ≥7 CCa compared to Gleason 6 tumors, (P < 0.001 and P = 0.012). All DCa demonstrated type III time-SI curves. Gleason ≥ 7 tumors demonstrated type II/III curves. Gleason 6 tumors demonstrated Type I/II time-SI curves. There was no difference in curve type between groups, (P = 0.18). CONCLUSION: Although DCa mimics Gleason score 3 + 3 = 6 tumor at T2W MRI; DCa resembles Gleason ≥7 CCa on mp-MRI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".