On Optimization of Mixed Photon Energies in Volumetric Modulated Arc Therapy
Bibliographic record
Abstract
This dissertation investigates the dosimetric influence of mixed photon beams in volumetric modulated arc therapy (VMAT) for prostate cancer and presents new algorithmic frameworks for simultaneous optimization of mixed photon beams in VMAT. The potential scope of using mixed photon VMAT for prostate cancer was first studied by using a clinical treatment planning software. A significant reduction in doses to bladder (P < 0.05) and rectum (P < 0.05), and similar target dose conformity was achieved by mixed photon (6&15 MV) VMAT compared to single energy (6 or 15 MV) VMAT. Radiobiological effectiveness was evaluated through tumor control probability (TCP) and normal tissue complication probability (NTCP). Across four different parameter sets for grade ≥ 2 rectal bleeding, mixed energy reduced NTCP by 1.3%, 4.1%, 0.1% and 2.6%, respectively, compared to single energy (P < 0.05). For bladder, mixed energy reduced mean equivalent uniform dose by 2 Gy (P < 0.05). In this study, however, each energy plan had to be optimized separately followed by their summation in order to generate a mixed photon VMAT plan. From optimization standpoint, this approach limits the solution search space. With the aim of furthering current optimization approach, a comprehensive algorithmic framework was presented for simultaneous optimization of mixed photon beams (6 & 18 MV) in VMAT (MP-VMAT). This was solved heuristically in two steps, accounting for dosimetric and mechanical constraints. This novel proof of concept was tested for its practicality and dosimetric outcome on two prostate cancer cases. In both cases, the proposed approach was able to reduce doses to rectum and bladder while maintaining the target dose coverage. Overall results suggested the viability and dosimetric benefits of the proposed concept, compared to single energy approach, in VMAT planning. Next, the concept of MP-VMAT was expanded for a single-arc treatment, consisting of energy dependent partial arcs. To this end, the first formalism was presented to optimize mixed photon energy (6 & 18 MV) fluences along with corresponding arc locations and lengths over a full 360o gantry rotation. The radiobiological and dosimetric effectiveness of this framework was tested on prostate cases with varying body types. The proposed technique was able to reduce bladder and rectum complication by 14% and 7%, respectively, in large size patients compared to single energy VMAT. The novel concept of simultaneous optimization of multi-energy introduced in this dissertation can also be employed in learning based approach for beam angle optimization in intensity modulated radiation therapy treatments as well as in optimization of mixed modality treatments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".