A Metabolic Imaging Severity Rating Scale for the Assessment of Cognitive Impairment
Bibliographic record
Abstract
PURPOSE: This study was designed to validate a simple scoring system for evaluating fluorodeoxyglucose (FDG) positron emission tomographic (PET) scans that can be used routinely in patients undergoing the clinical assessment of cognitive impairment. METHODS: The FDG-PET scans of 106 patients with cognitive impairment (65 with Alzheimer disease, 16 with frontal lobe dementia, and 25 atypical cases) were acquired using the PENN-PET scanner 40 minutes after the intravenous administration of 8 mCi FDG. Metabolic activity in various anatomic structures of the brain was scored using the following qualitative scale: 4 = normal; 3 = mildly decreased; 2 = moderately decreased; 1 = severely decreased; and 0 = no activity. Regions of interest were also placed over these regions to obtain a quantitative value. Two distinct scores were obtained. Values for visual and sensorimotor cortices, thalami, basal ganglia, and cerebellum comprised score I. Score II consisted of the values for the frontal, temporal, and parietal cortices. The qualitative metabolic imaging severity rating scale (MISRS) was compared with a quantitative MISRS (obtained from the region-of-interest analysis of the same structures). The MISRS was then compared with the results from the Mini-Mental Status Examination (MMSE) and the Dementia Severity Rating Score (DSRS). RESULTS: In all patients, the qualitative MISRS scores correlated significantly with the quantitative MISRS (r = 0.73, P < 0.0001). In all patients with cognitive impairment, the qualitative and quantitative MISRS scores correlated significantly with the DSRS and the MMSE (P < 0.001). In patients with Alzheimer disease, the qualitative and quantitative MISRS significantly correlated with the DSRS and MMSE. CONCLUSION: A simple and practical rating scale can be used to assess the severity of cognitive impairment in patients with different types of dementing illnesses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".