SPECT/CT bone scan fusion imaging in osteochondral lesions of the talus
Bibliographic record
Abstract
1055 Learning Objectives 1. Describe and illustrate bone scan findings of ankle activity with and without SPECT/CT. 2. Explain the benefit and advantage of SPECT/CT fusion image in localization of the talar dome lesion. 3. Review anatomy and pathophysiology of osteochondritis descans of the ankle. Summary: Osteochondritis Descans (OCD) of the ankle is a rare disease affecting mostly young people. The typical presentation is persistent ankle pain following ankle injury. Early diagnosis and treatment are important to prevent permanent ankle joint impairment. Unfortunately physical examination and radiography are not sensitive for diagnosing OCD. Bone scintigraphy is an excellent screening tool in patients presented with persistent ankle pain. Traditional bone scan with planar imaging is known to have a good sensitivity but has poor lesion localization. Although SPECT could be performed to help localize the OCD lesion to the talar dome, it is limited by poor spatial resolution, especially with complex anatomy of ankle mortise. The fusion of functional images with CT has tremendously improved localization capabilities. With low mA on CT, the effective dose of radiation exposure from the CT portion is minimal, at less than 20% of that of a bone scan. In this exhibit we present five bone SPECT/CT studies of ankles in patients with suspected OCD. SPECT/CT clearly localizes the uptake to the talar dome, medial malleolus, inferior medial talus and distal tibia on the fusion images. Since most nuclear medicine physicians are unaware of benefit of SPECT/CT of the ankle, this exhibit demonstrates that SPECT/CT provides not only a screening tool to patients with an ankle injury, but also an accurate localization of the bony lesion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".