Histomorphometric and microarchitectural analyses using the 2 mm bone marrow trephine in metastatic breast cancer patients–preliminary results
Bibliographic record
Abstract
BACKGROUND: Bone-targeted agents are widely used for the treatment of osteoporosis, the prevention of cancer-therapy induced bone loss, and for reducing the risk of skeletal related events in patients with metastatic disease. Despite widespread use, relatively little is known about the in vivo effect of these agents on bone homeostasis, bone quality, and bone architecture in humans. Traditionally bone quality has been assessed using a transiliac bone biopsy with a 7 mm "Bordier" core needle. We examined the possibility of using a 2 mm "Jamshidi" core needle as a more practical and less invasive method to assess bone turnover and potentially other tumor effects. METHODS: A pilot study on the feasibility of assessing bone quality and microarchitecture and tumor invasion using a 2 mm bone marrow trephine was conducted. Patients underwent a posterior trans-iliac trephine biopsy and bone marrow aspirate. Samples were analyzed for bone microarchitecture, bone density, and histomorphometry. The study plan was to accrue three patients with advanced breast cancer to assess the feasibility of the study before enrolling more patients. RESULTS: The procedure was well tolerated. The sample quality was excellent to analyze bone trabecular microarchitecture using both microCT and histomorphometry. Intense osteoclastic activity was observed in a patient with extensive tumor burden in bone despite intravenous bisphosphonate therapy. DISCUSSION: Given the success of this study for assessing bone microarchitecture, bone density, and histomorphometry assessment using a 2 mm needle the study will be expanded beyond these initial three patients for longitudinal assessment of bone-targeted therapy.
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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) | 0.001 | 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".