Evaluation of Brain Functions in Conversion Disorder with PET/MRI
Bibliographic record
Abstract
Introduction Since there is no objective criteria, unique clinical symptom or laboratory test to make the diagnosis of conversion disorder; its diagnosis and treatment is challenging which leads to a poor prognosis. Objectives The aim of this study is to investigate the brain metabolic activity of patients with conversion disorder with PET/MRI. Methods 12 conversion disorder patients were included. Somatosensory Amplification Scale, Somatoform Dissociation Scale, Patient Health Questionnaire-15, Toronto Alexithymia Scale were filled in by the participants. Neurological, mental status examinations, Wechsler Adult Intelligence Scale-Revised Form (WAIS-R) and brain F18-FDG-PET/MRI were performed. Structured Clinical Interview for DSM-5, Hamilton Depression and Anxiety Scales were administered. Results 83% of the patients were female, the mean age was 33 years and average education period was 10,2 years. WAIS-R total scores were consistent with low avarage intelligence level.Cerebral hypermetabolism was detected in the primary visual cortex. Average regional brain metabolic activity had a tendency to increase in bilateral prefrontal, right sensorimotor (SM),cingulate,right inferior parietal,occipital lateral,right temporal lateral cortices and cerebellum. Each region was metabolically correlated with the homologous contralateral regions. Significant correlations in the same direction was found between frontal and occipital lateral & primary visual cortices; cerebellum and left sensorimotor cortex; anterior cingulate cortex(ACC) and superior parietal cortex & cerebellum. No correlations were found between ACC and left SM cortex. Conclusions Findings of our study indicate that there are moderate changes in regional brain metabolic activities and inter-regional correlations in patients with conversion disorder. In order to confirm these findings, furter functional neuroimaging studies are needed. Disclosure No significant relationships.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".