Diffusion time effects over the adult lifespan indicates persistent zone‐specific microstructural alterations in the human prostate with aging
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to investigate microstructural changes in the aging adult prostate by comparing the effects of varying diffusion times using diffusion MRI, and to provide an age-related benchmark for future prostate cancer studies. METHODS: -weighted image. Volume and mean diffusivity (MD) were measured in the peripheral (PZ) and transition zones (TZ), which were assessed versus age. RESULTS: PZ and TZ showed quadratic age trajectories for all diffusion scans, with MD decreasing from 19 years to a minimum ˜30-40 years followed by a greater increase at older ages. Short (OGSE) and medium (PGSE) diffusion time MD had similar age trajectories, whereas long diffusion time (PGSTE) MD was significantly lower, particularly in PZ (22%). MD difference (∆MD) of OGSE-PGSTE and PGSE-PGSTE showed significant positive linear correlations with age for both PZ (larger slope) and TZ, resulting in ˜3.3x (PZ) and 1.8x (TZ) greater ∆MD from 19 to 69 years. MD and ∆MD versus age relationships differed from volume, which conversely had greater proportional growth in TZ than PZ. CONCLUSION: The diffusion time effects suggest age-related microstructural changes consistent with development of persistently larger cell dimensions mainly in the prostate peripheral zone over the adult lifespan. This normative data can be used for comparison to prostate cancer factoring in age.
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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 | 0.000 |
| 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 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".