Ectopic Recurrence of Skull Base Chordoma after Proton Therapy
Bibliographic record
Abstract
BACKGROUND: Chordoma are rare tumors of the axial skeleton. The treatment gold standard is surgery, followed by particle radiotherapy. Total resection is usually not achievable in skull base chordoma (SBC) and high recurrence rates are reported. Ectopic recurrence as a first sign of treatment failure is considered rare. Favorable sites of these ectopic recurrences remain unknown. METHODS: Five out of 16 SBC patients treated with proton therapy and surgical resection developed ectopic recurrence as a first sign of treatment failure were critically analyzed regarding prior surgery, radiotherapy, and recurrences at follow-up imaging. RESULTS: Eighteen recurrences were defined in five patients. A total of 31 surgeries were performed for primary tumors and recurrences. Seventeen out of eighteen (94%) ectopic recurrences could be related to prior surgical tracts, outside the therapeutic radiation dose. Follow-up imaging showed that tumor recurrence was difficult to distinguish from radiation necrosis and anatomical changes due to surgery. CONCLUSIONS: In our cohort, we found uncommon ectopic recurrences in the surgical tract. Our theory is that these recurrences are due to microscopic tumor spill during surgery. These cells did not receive a therapeutic radiation dose. Advances in surgical possibilities and adjusted radiotherapy target volumes might improve local control and survival.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".