New developments in the imaging of metastatic prostate cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: In the last 10 years, metastatic castration-resistant prostate cancer (mCRPC) treatment has completely changed. Several new agents have been shown to increase mCRPC patients' overall survival. The importance to define castration-resistant prostate cancer as metastatic and to enable earlier detection of cancer progression set a renewed role for prostate cancer (PCa) imaging. RECENT FINDINGS: Recently published data on molecular imaging of metastatic PCa have focused on diagnostic accuracy, clinical impact and prognostic value of newer techniques using PET and MRI. SUMMARY: Molecular imaging techniques are more sensitive and accurate than conventional imaging for the early detection of lymph node and bone metastases. New capabilities offered by PET imaging, MRI lymphography and whole-body MRI are consolidating the role of imaging in metastatic PCa management. These techniques are particularly useful for detecting metastasis, a driver for treatment initiation, especially in patients under androgen-deprivation therapy. Moreover, there is an increasing body of evidence supporting the use of metabolic PET and computed tomography as a prognostic biomarker able to predict survival in patients with metastatic PCa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".