Dosimetric and radiobiological characterizations of prostate intensity-modulated radiotherapy and volumetric-modulated arc therapy: A single-institution review of ninety cases
Bibliographic record
Abstract
This study reviewed prostate volumetric-modulated arc therapy (VMAT) plans with intensity-modulated radiotherapy (IMRT) plans after prostate IMRT technique was replaced by VMAT in an institution. Characterizations of dosimetry and radiobiological variation in prostate were determined based on treatment plans of 40 prostate IMRT patients (planning target volume = 77.8-335 cm(3)) and 50 VMAT patients (planning target volume = 120-351 cm(3)) treated before and after 2013, respectively. Both IMRT and VMAT plans used the same dose-volume criteria in the inverse planning optimization. Dose-volume histogram, mean doses of target and normal tissues (rectum, bladder and femoral heads), dose-volume points (D99% of planning target volume; D30%, D50%, V30 Gy and V35 Gy of rectum and bladder; D5%, V14 Gy, V22 Gy of femoral heads), conformity index (CI), homogeneity index (HI), gradient index (GI), prostate tumor control probability (TCP), and rectal normal tissue complication probability (NTCP) based on the Lyman-Burman-Kutcher algorithm were calculated for each IMRT and VMAT plan. From our results, VMAT plan was found better due to its higher (1.05%) CI, lower (0.83%) HI and (0.75%) GI than IMRT. Comparing doses in normal tissues between IMRT and VMAT, it was found that IMRT mostly delivered higher doses of about 1.05% to the normal tissues than VMAT. Prostate TCP and rectal NTCP were found increased (1%) for VMAT than IMRT. It is seen that VMAT technique can decrease the dose-volume evaluation criteria for the normal tissues. Based on our dosimetric and radiobiological results in treatment plans, it is concluded that our VMAT implementation could produce comparable or slightly better target coverage and normal tissue sparing with a faster treatment time in prostate radiotherapy.
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 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".