Incidentaloma Discoveries in the Course of Neuroimaging Research
Bibliographic record
Abstract
ABSTRACTAmong healthy volunteers in psychiatric brain functional magnetic resonance imaging (fMRI) research studies, the prevalence of incidentalomas can be as high as 34%, of which 10% show clinical significance. An incidentaloma is a lesion found by coincidence without clinical symptoms or suspicion. Like lesions and other types of accidental findings, it is found in healthy individuals recruited to take part in psychiatric studies. The prevalence of these accidental findings among specific psychiatric populations remains unknown. However, a precise understanding of cerebral neuroanatomy, neuroradiological expertise, and an appropriate choice of fMRI exploration sequences will increase the sensitivity of identifying these accidental findings and enable researchers to address their clinical relevance and nature. We present recommendations on how to appropriately inform patients or participants of the accidental findings. Additionally, we propose specific suggestions pertaining to the clinical research setting aimed for investigators and psychiatrists. Unlike current articles pertaining to incidentaloma, the current report provides a distinct focus on psychiatric issues and specific recommendations for studies involving psychiatric patients.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".