Evaluation of ganglion cysts using vastly undersampled isotropic projection reconstruction (VIPR)
Bibliographic record
Abstract
For some atypical para-articular ganglia, the presence of a joint connection is highly controversial. The proper preoperative diagnosis and identification of this joint connection for ganglion cysts is important for patient treatment and outcome. MRI is the imaging modality of choice when evaluating such lesions, but the detection of subtle joint connections remains difficult with conventional MR protocols. We investigated the utility of a steady-state free-precession acquisition with isotropic high resolution using the vastly undersampled isotropic projection reconstruction (VIPR) pulse sequence to determine if joint connections for ganglion cysts could be seen more effectively, using the knee region as a model. We evaluated four patients: two with peroneal intraneural ganglion cysts, one with adventitial cystic disease of the popliteal artery, and one patient with a more typical extraneural (intramuscular) cyst. Both conventional MR and VIPR techniques were used. In our clinical experience, we found VIPR to be superior to conventional MR techniques in detecting and depicting joint connections in typical and atypical ganglion cysts around the knee.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".