Intermixed Normal Tissue within Prostate Cancer: Effect on MR Imaging Measurements of Apparent Diffusion Coefficient and T2—Sparse versus Dense Cancers
Bibliographic record
Abstract
PURPOSE: To investigate differences in apparent diffusion coefficient (ADC) and T2 values between dense and sparse regions in prostate cancer. MATERIALS AND METHODS: Eighteen patients (median age, 61 years; range, 44-72 years) gave informed consent for this retrospective Research Ethics Board-approved study. Prior to radical prostatectomy, ADC (b value, 600 sec/mm(2)) and T2 maps were obtained by using 1.5-T magnetic resonance (MR) imaging. Twenty-eight peripheral zone (PZ) tumors were reviewed by using whole-mount histologic findings, and regions assessed to contain primarily (>60%) normal PZ tissue were delineated. Tumors were categorized as "sparse" if more than 50% of their cross-sectional areas were these primarily normal PZ regions and were considered "dense" otherwise. Normal PZ tissue was outlined separately on the same section. Tumor and normal tissue outlines were transferred to corresponding ADC and T2 maps, and median values were calculated. Values were compared by using multiple regression analysis. Matched-pair tumor-to-normal tissue differences and log(2)-transformed ratios were assessed by using nonparametric tests. RESULTS: Thirty-six percent (10 of 28) of tumors were sparse; 64% (18 of 28) were dense. For both overall and intrapatient comparisons, dense tumors had significantly lower ADC and T2 values than normal PZ tissue (P < .05), but no significant differences were observed between sparse tumors and normal tissue. Log(2)-transformed tumor-to-normal tissue ratios were significantly less than zero for dense tumors for both ADC and T2 (P < .01) measurements but not for sparse tumors. Both matched-pair differences and log(2)-transformed ratios were significantly different between sparse and dense tumors (P < .01). ADC and T2 values were moderately correlated (Pearson correlation coefficient range, r = 0.770-0.804). CONCLUSION: Sparse prostate tumors have similar ADC and T2 values to those of normal PZ tissue. This may limit MR imaging detection and the assessment of tumor volume of some cancers.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".