Effect on therapeutic ratio of planning a boosted radiotherapy dose to the dominant intraprostatic tumour lesion within the prostate based on multifunctional MR parameters
Bibliographic record
Abstract
OBJECTIVE: To demonstrate the feasibility of an 8-Gy focal radiation boost to a dominant intraprostatic lesion (DIL), identified using multiparametric MRI (mpMRI), and to assess the potential outcome compared with a uniform 74-Gy prostate dose. METHODS: The DIL location was predicted in 23 patients using a histopathologically verified model combining diffusion-weighted imaging, dynamic contrast-enhanced imaging, T2 maps and three-dimensional MR spectroscopic imaging. The DIL defined prior to neoadjuvant hormone downregulation was firstly registered to MRI-acquired post-hormone therapy and subsequently to CT radiotherapy scans. Intensity-modulated radiotherapy (IMRT) treatment was planned for an 8-Gy focal boost with 74-Gy dose to the remaining prostate. Areas under the dose-volume histograms (DVHs) for prostate, bladder and rectum, the tumour control probability (TCP) and normal tissue complication probabilities (NTCPs) were compared with those of the uniform 74-Gy IMRT plan. RESULTS: Deliverable IMRT plans were feasible for all patients with identifiable DILs (20/23). Areas under the DVHs were increased for the prostate (75.1 ± 0.6 vs 72.7 ± 0.3 Gy; p < 0.001) and decreased for the rectum (38.2 ± 2.5 vs 43.5 ± 2.5 Gy; p < 0.001) and the bladder (29.1 ± 9.0 vs 36.9 ± 9.3 Gy; p < 0.001) for the boosted plan. The prostate TCP was increased (80.1 ± 1.3 vs 75.3 ± 0.9 Gy; p < 0.001) and rectal NTCP lowered (3.84 ± 3.65 vs 9.70 ± 5.68 Gy; p = 0.04) in the boosted plan. The bladder NTCP was negligible for both plans. CONCLUSION: Delivery of a focal boost to an mpMRI-defined DIL is feasible, and significant increases in TCP and therapeutic ratio were found. ADVANCES IN KNOWLEDGE: The delivery of a focal boost to an mpMRI-defined DIL demonstrates statistically significant increases in TCP and therapeutic ratio.
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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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".