The Initial Step Towards Establishing a Quantitative, Magnetic Resonance Imaging-Based Framework for Response Assessment of Spinal Metastases After Stereotactic Body Radiation Therapy
Bibliographic record
Abstract
BACKGROUND: There are no established threshold values regarding the degree of growth on imaging when assessing response of spinal metastases treated with stereotactic body radiation therapy (SBRT). OBJECTIVE: To determine a magnetic resonance imaging-based minimum detectable difference (MDD) in gross tumor volume (GTV) and its association with 1-yr radiation site-specific (RSS) progression-free survival (PFS). METHODS: GTVs at baseline and first 2 post-SBRT scans (Post1 and Post2, respectively) for 142 spinal segments were contoured, and percentage volume change between scans calculated. One-year RSS PFS was acquired from medical records. The MDD was determined. The MDD was compared against optimal thresholds of GTV changes associated with 1-yr RSS PFS using Youden's J index, and receiver operating characteristic curves between timepoints compared to determine which timeframe had the best association. RESULTS: A total of 17 of the 142 segments demonstrated progression. The MDD was 10.9%. Baseline-Post2 demonstrated the best performance (area under the curve [AUC] 0.90). Only Baseline-Post2 had an optimal threshold > MDD at 14.7%. Due to large distribution of GTVs, volumes were split into tertiles. Small tumors (GTV < 2 cc) had optimal thresholds of 42.0%, 71.3%, and 37.2% at Baseline-Post1 (AUC 0.81), Baseline-Post2 (AUC 0.89), and Post1-Post2 (AUC 0.77), respectively. Medium tumors (2 ≤ GTV ≤ 8.3 cc) all demonstrated optimal thresholds < MDD, with AUCs ranging from 0.65 to 0.84. Large tumors (GTV > 8.3 cc) had 2 timepoints where optimal thresholds > MDD: Baseline-Post2 (13.3%; AUC 0.97) and Post1-Post2 (11.8%; AUC 0.66). Baseline-Post2 had the best association with RSS PFS for all tertiles. CONCLUSION: Given a MDD of 10.9%, for small GTVs, larger (>37%) changes were required before local failure could be determined, compared to 11% to 13% for medium/large tumors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| 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) | 0.000 | 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 teacher head, 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".