Impact of intraoperative MRI/TRUS fusion on dosimetric parameters in cT3a prostate cancer patients treated with high-dose-rate real-time brachytherapy
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate the impact of intraoperative MRI/TRUS fusion procedure in cT3a prostate cancer patients treated with high-dose-rate (HDR) real-time brachytherapy. MATERIAL AND METHODS: Prostate gland, dominant intraprostatic lesions (DILs), and extracapsular extension (ECE) were delineated in the pre-brachytherapy magnetic resonance images (MRI) of 9 consecutive patients. The pre-implant P-CTVUS (prostate clinical target volume) was defined as the prostate seen in the transrectal ultrasound (TRUS) images. The CTVMR includedthe prostate with the ECE image (ECE-CTV) as defined on the MRI. Two virtual treatment plans were performed based on the MRI/TRUS fusion images, the first one prescribing 100% of the dose to the P-PTVUS, and the second prescribing to the PTVMR. The implant parameters and dose-volume histogram (DVH) related parameters of the prostate, OARs, and ECE were compared between both plans. RESULTS: Mean radial distance of ECE was 3.6 mm (SD: 1.1). No significant differences were found between prostate V100, V150, V200, and OARs DVH-related parameters between the plans. Mean values of ECE V100, V150, and V200 were 85.9% (SD: 15.1), 18.2% (SD: 17.3), and 5.85% (SD: 7) when the doses were prescribed to the PTVUS, whereas ECE V100, V150, and V200 were 99.3% (SD: 1.2), 45.8% (SD: 22.4), and 19.6% (SD: 12.6) when doses were prescribed to PTVMR (p = 0.028, p = 0.002 and p = 0.004, respectively). CONCLUSIONS: TRUS/MRI fusion provides important information for prostate brachytherapy, allowing for better coverage and higher doses to extracapsular disease in patients with clinical stage T3a.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".