Multiparametric Magnetic Resonance Imaging of Prostate Cancer Bone Disease
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to correlate magnetic resonance imaging (MRI) of castration-resistant prostate cancer (CRPC) bone metastases with histological and molecular features of bone metastases. MATERIALS AND METHODS: Forty-three bone marrow biopsies from 33 metastatic CRPC (mCRPC) patients with multiparametric MRI and documented bone metastases were evaluated. A second cohort included 10 CRPC patients with no bone metastases. Associations of apparent diffusion coefficient (ADC), normalized b900 diffusion-weighted imaging (nDWI) signal, and signal-weighted fat fraction (swFF) with bone marrow biopsy histological parameters were evaluated using Mann-Whitney U test and Spearman correlations. Univariate and multivariate logistic regression models were analyzed. RESULTS: Median ADC and nDWI signal was significantly higher, and median swFF was significantly lower, in bone metastases than nonmetastatic bone (P < 0.001). In the metastatic cohort, 31 (72.1%) of 43 biopsies had detectable cancer cells. Median ADC and swFF were significantly lower and median nDWI signal was significantly higher in biopsies with tumor cells versus nondetectable tumor cells (898 × 10 mm/s vs 1617 × 10 mm/s; 11.5% vs 62%; 5.3 vs 2.3, respectively; P < 0.001). Tumor cellularity inversely correlated with ADC and swFF, and positively correlated with nDWI signal (P < 0.001). In serial biopsies, taken before and after treatment, changes in multiparametric MRI parameters paralleled histological changes. CONCLUSIONS: Multiparametric MRI provides valuable information about mCRPC bone metastases. These data further clinically qualify DWI as a response biomarker in mCRPC.
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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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".