A Case of Radiation-Associated Vertebral Compression Fracture Mimicking Solitary Bone Metastasis of Lung Cancer
Bibliographic record
Abstract
Radiation therapy plays an important role in the treatment of lung cancer. Although adverse effects of radiation are well known, they are sometimes difficult to be diagnosed. We report a case of a radiation-associated vertebral compression fracture which mimicked bone metastasis of lung cancer. The patient was a 57-year-old man diagnosed with lung squamous cell carcinoma (cT1aN2M0, c-stage IIIA). He received concurrent chemoradiotherapy (CRT) in combination with 6 weeks of weekly carboplatin plus paclitaxel and thoracic radiation of 60 Gy/30 fractions, followed by bi-weekly durvalumab for 12 months. On the last day of the 12-month durvalumab regimen, he complained of backache. Magnetic resonance imaging showed compression fracture of the seventh thoracic vertebra with the spinal cord compressed, and fluorine-18 fluorodeoxyglucose positron emission tomography and computed tomography demonstrated weak focal uptake only at the seventh thoracic vertebra. Although the fracture had been suspected to be bone metastasis, surgical biopsy revealed no evidence of malignancy. Since the seventh thoracic vertebra was included in the irradiation area, the patient was diagnosed with a radiation-associated fracture. Dual-energy X-ray absorptiometry of the lumbar vertebrae (L2 - 4) after the surgery revealed osteopenia. In conclusion, we successfully diagnosed the radiation-associated vertebral fracture caused by radical CRT. The fracture mimicked bone metastasis in preoperative imaging tests. Thus, surgical biopsy was useful for diagnosis.
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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".