IMRT: Improvement in treatment planning efficiency using NTCP calculation independent of the dose‐volume‐histogram
Bibliographic record
Abstract
The normal tissue complication probability (NTCP) is a predictor of radiobiological effect for organs at risk (OAR). The calculation of the NTCP is based on the dose-volume-histogram (DVH) which is generated by the treatment planning system after calculation of the 3D dose distribution. Including the NTCP in the objective function for intensity modulated radiation therapy (IMRT) plan optimization would make the planning more effective in reducing the postradiation effects. However, doing so would lengthen the total planning time. The purpose of this work is to establish a method for NTCP determination, independent of a DVH calculation, as a quality assurance check and also as a mean of improving the treatment planning efficiency. In the study, the CTs of ten randomly selected prostate patients were used. IMRT optimization was performed with a PINNACLE3 V 6.2b planning system, using planning target volume (PTV) with margins in the range of 2 to 10 mm. The DVH control points of the PTV and OAR were adapted from the prescriptions of Radiation Therapy Oncology Group protocol P-0126 for an escalated prescribed dose of 82 Gy. This paper presents a new model for the determination of the rectal NTCP (R(NTCP)). The method uses a special function, named GVN (from Gy, Volume, NTCP), which describes the R(NTCP) if 1 cm3 of the volume of intersection of the PTV and rectum (R(int)) is irradiated uniformly by a dose of 1 Gy. The function was "geometrically" normalized using a prostate-prostate ratio (PPR) of the patients' prostates. A correction of the R(NTCP) for different prescribed doses, ranging from 70 to 82 Gy, was employed in our model. The argument of the normalized function is the R(int), and parameters are the prescribed dose, prostate volume, PTV margin, and PPR. The R(NTCPs) of another group of patients were calculated by the new method and the resulting difference was < +/- 5% in comparison to the NTCP calculated by the PINNACLE3 software where Kutcher's dose-response model for NTCP calculation is adopted.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".