Accuracy of transcranial brain parenchyma sonography in the diagnosis of dementia with Lewy bodies
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Transcranial sonography (TCS) of the brain parenchyma is used to visualize alterations in the substantia nigra (SN) and it is applied for early diagnosis of Parkinson's disease. Our aim was to explore specific echogenic alterations of the SN in dementia with Lewy bodies (DLB) compared to Alzheimer's disease (AD). METHODS: Seventy-one subjects underwent TCS: 22 DLB, 28 AD and 21 healthy elderly controls. Cognitive impairment, extrapyramidal signs, visual hallucinations, fluctuations and rapid eye movement sleep behaviour symptoms were investigated. TCS assessed SN hyperechogenicity and symmetry. RESULTS: Transcranial sonography revealed SN hyperechogenicity in 100% of DLB compared to 50% of AD and 30% of controls. Mean SN echogenic area (cm(2) ) was 0.22 ± 0.03 in DLB, 0.15 ± 0.03 in AD and 0.14 ± 0.03 in controls (P < 0.0001). More than 50% of DLB presented a marked hyperechogenicity (cutoff value >0.22 cm(2) ) compared to only 10% of AD (P < 0.0003). DLB had symmetrical SN enlargement, whereas AD were mostly asymmetrical (P = 0.015). A combination of SN echogenic area and asymmetry index had a sensitivity of 88.9% and a specificity of 81.2% in discriminating DLB from AD (positive predictive value 85.7%, negative predictive value 85.7%). No association was found between SN hyperechogenicity and Unified Parkinson's Disease Rating Scale part III, Mini Mental State Examination or the presence of visual hallucinations. CONCLUSIONS: Transcranial sonography may be a valid supportive tool in the diagnostic workup of neurodegenerative dementia helping clinicians to distinguish DLB from AD even at the early stages.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".