Multiparametric magnetic resonance imaging of multifocal prostate cancer to reveal intra-prostatic genomic heterogeneity and novel radio-genomic correlates: Results of the Smarter Prostate Interventions and Therapeutics (SPIRIT) study.
Bibliographic record
Abstract
20 Background: Multi-focality and heterogeneity in prostate cancer can confound the selection of appropriate clinical management. Our study aimed to explore radio-genomic correlations using multiparametric magnetic resonance imaging (mpMRI) against a histopathologic reference standard. Methods: Eight men with prostate cancer who underwent mpMRI followed by prostatectomy were selected for this pilot. Whole-mount histopathology was digitized and co-registered to corresponding MRI slices using a validated high-fidelity methodology.(1) Foci, including central/transitional and peripheral zone lesions were identified by a pathologist, and contoured on digitized histopathology specimens and these digitized maps were used to guide macrodissection of the individual foci for genomic copy-number aberration (CNA) analysis. Correlation of radiomics signatures with the histologic findings and genomic analysis was performed. Results: We found a broad range of CNAs revealing inter-patient and intra-prostatic heterogeneity. Recurrently-altered loci ( e.g., 8p21) containing genes of known significance ( e.g., NKX3-1) were observed. Only radiomic features derived from apparent diffusion coefficient (ADC) independently correlated with both Gleason grade (Rho=-0.62, p=0.003) and median CNA burden (Rho=-0.68, p<0.001). While greater CNA burden expectedly correlated with higher grade, intermediate-grade (Gleason score 3+4 or 4+3) lesions appeared more like either high-grade (Gleason scores ≥4+4) or low-grade (Gleason score 3+3) disease when clustered based on CNA and ADC metrics. Conclusions: These findings suggest ADC derived radiomic metrics may be a useful imaging biomarker across both central and peripheral zone lesion and could aid in further characterization of intra-prostatic biologic heterogeneity. These proof-of-principle data reveal novel radio-genomic correlations that could supplement histologic grading and conventional imaging, thus warranting expanded study and validation. 1) Int J Rad Oncol Biol Phys. 2016; 96(1):188-96.
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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 | 0.002 | 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 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".