Helical tomotherapy in the radiotherapy treatment of Hodgkin's disease ‐ a feasibility study
Bibliographic record
Abstract
Radiation therapy for advanced Hodgkin's disease often requires large fields and may result in significant exposure of normal tissues to ionizing radiation. In long-term survivors, this may increase the risk for late toxicity including secondary malignancies. 3DCRT has been successfully used to treat this disease but treatment delivery is often complex requiring matching of photon with electron beams, utilization of field-in-field techniques and of partial transmission blocks. HT is an arc-rotational intensity modulated radiation therapy technique proven to achieve superior target dose conformality and sharp dose gradients around critical normal tissues. HT however, has also been associated with higher volumes of low dose regions in normal tissues and therefore, higher integral dose. The present study was undertaken to compare the dosimetry of 3DCRT to HT in a pediatric patient with advanced HD. Clinical target volume (CTV) included bilateral lower cervical and supraclavicular areas, mediastinum, bilateral hili, left axilla and bilateral diaphragmatic lymph nodes. The planning target volume (PTV) was derived by circumferentially expanding the CTV by 1 cm. Whole lung and heart irradiation was also planned due to bilateral pleural and pericardial effusions. The prescribed radiation dose was 21 Gy to the PTV and 10.5 Gy to the whole lung and heart. Target coverage was comparable for both plans. The minimum, maximum and mean PTV doses were 18.61 Gy, 22.45 Gy and 21.52 Gy with 3DCRT and 19.85 Gy, 22.36 Gy and 21.39 Gy with HT, respectively. HT decreased mean normal tissue dose by 21.6% and 20.07% for right and left breast, 20.40% for lung, 30.78% for heart and 22.74% for the thyroid gland. Integral dose also decreased with HT by 46.50%. HT results in significant dosimetric gain related to normal tissue sparing compared to 3DCRT. Further studies are warranted to evaluate clinical applications of HT in patients with HD.
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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) | 0.000 | 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".