Prospective comparison of whole-body bone SPECT and sodium 18F-fluoride PET in the detection of bone metastases from breast cancer
Bibliographic record
Abstract
OBJECTIVE: The superiority of sodium F-fluoride PET (F-PET)/computed tomography (CT) over planar and single field-of-view single-photon emission computed tomography (SPECT) bone scintigraphy with Tc-methylene diphosphonate in bone metastases detection has been established. The present study prospectively compares whole-body Tc-methylene diphosphonate SPECT (WB-SPECT) and F-PET performance indices for the detection of bone metastases in breast cancer. METHODS: A total of 41 pairs of studies in female breast cancer patients (average age 58 years, range 30-75) were included. Half-time WB-SPECT and F-PET/CT were performed at a 4-day average interval (range 0-36 days), with subsequent fusion of CT to WB-SPECT. Two readers independently interpreted the studies, with differences resolved by consensus. Composite gold standard included the CT component of the F-PET/CT study with follow-up CT, MRI, F-fluoro-deoxyglucose-PET/CT, and bone scans. RESULTS: On patient-based analysis, metastases were diagnosed in 21 patients, with 19 patients detected by WB-SPECT and 21 with F-PET, the latter being the only modality to detect a single metastasis in two patients. The sensitivity of WB-SPECT and F-PET was 90 and 100% (P=NS), and the specificity were 95 and 85%, respectively (P=NS). On lesion-based analysis, 284 total sites of increased uptake were found. WB-SPECT detected 171/284 (60%) and F-PET 268/284 (94%) lesions, with good interobserver agreement for WB-SPECT (κ=0.679) and excellent agreement for F-PET (κ=0.798). The final analysis classified 204 lesions as benign and 80 as metastases. WB-SPECT identified 121 benign and 50 malignant sites compared with 192 and 76, respectively, for F-PET. WB-SPECT and F-PET had a sensitivity of 63 vs. 95%, P-value of less than 0.001, and a specificity of 97 vs. 96% (P=NS), respectively, on lesion-based analysis. CONCLUSION: F-PET had higher sensitivity for the diagnosis of bone metastases from breast cancer compared with WB-SPECT, showing a statistically significant 32% increase on lesion-based analysis.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".