Multimodal CT Provides Improved Performance for Lacunar Infarct Detection
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Lacunar infarcts account for approximately 25% of acute ischemic strokes. Compared with NCCT alone, the addition of CTP improves sensitivity for detection of infarcts overall. Our aim was to systematically evaluate the diagnostic benefit and interobserver reliability of an incremental CT protocol in lacunar infarction. MATERIALS AND METHODS: Institutional review board approval and patient consent were obtained. One hundred sixty-three patients presenting with a lacunar syndrome ≤4.5 hours from symptom onset were enrolled. Images were reviewed incrementally by 2 blinded readers in 3 separate sessions (NCCT only, NCCT/CTA, and NCCT/CTA/CTP). Diagnostic confidence was recorded on a 6-point scale with DWI/ADC as a reference. Logistic regression analysis calculated differences between actual and observed diagnoses, adjusted for confidence. Predictive effects of observed diagnostic accuracy and confidence score were quantified with the entropy r(2) value. Sensitivity, specificity, and confidence intervals were calculated accounting for multiple readers. Receiver operating characteristic analyses were compared among diagnostic strategies. Interobserver agreement was established with Cohen κ statistic. RESULTS: The final study cohort comprised 88 patients (50% male). DWI/ADC-confirmed lacunar infarction occurred in 59/88 (67%) with 36/59 (61%) demonstrating a concordant abnormal finding on CTP. Sensitivity for definite or probable presence of lacunar infarct increased significantly from 9.3% to 42.4% with incremental protocol use, though specificity was unchanged (range, 91.9%-95.3%). The observed diagnosis was significantly related to the actual diagnosis after adjusting for CTP confidence level (P = .04) and was 5.1 and 2.4 times more likely to confirm lacunar infarct than NCCT or CTA source images. CTP area under the curve (0.77) was significantly higher than that of CTA source images (0.68, P = .006) or NCCT (0.55, P < .001). CONCLUSIONS: CTP offers an improved diagnostic benefit over NCCT and CTA for the diagnosis of lacunar infarction.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".