Arterial brain calcium (ABC) volume - A novel radiological marker of atherosclerotic risk and future stroke risk on non-contrast CT
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Coronary calcium is a well-recognized marker of atherosclerotic risk. While intracranial carotid artery calcification has received some attention, calcific disease in other intracranial arteries is not well studied. In this pilot study, we sought to examine the whether the total volume of calcium in the intracranial arteries is associated with established markers of atherosclerosis and stroke risk. METHODS AND METHODS: We examined a subset of 360 consecutive cases in a population-level cohort of 7,745 patients representing all patients diagnosed with ischemic stroke/TIA in an entire Canadian province (Alberta) from 1-April-2016 to 31-March-2017. Trained readers manually segmented visible calcifications in all intracranial arteries on non-contrast CT using ITKSnap. Volumetric data for all segmentations were combined to obtain the total Arterial Brain Calcium (ABC) volume. We related this volume to the total burden of vascular risk factors, number of vessels with intracranial atherosclerotic disease, atherosclerosis burden in different territories using ordinal logistic regressions adjusted for age and sex, and to the 5-year risk of recurrent events using Poisson regressions. RESULTS: ) and was lower in females (4.22 mL, IQR:0.25-6.37 v/s 6.60 mL, IQR:0.35-8.33, p = 0.0004). ABC volume was independently associated with the burden of intracranial arterial (age/ sex-adjusted common odds-ratio [acOR] per mL increase:1.14, 95 %CI:1.04-1.26) and combined intracranial/carotid/ aortic/ coronary atherosclerosis (acOR:1.18, 95 %CI:1.10-1.27), and vascular risk factors (acOR:1.07, 95 %CI:1.01-1.13). Those with higher ABC volume had a higher risk of recurrent events (IRR:3.20, 95 % CI:1.24-8.25). CONCLUSIONS: ABC volume derived from routine non contrast CT scan may be utilised as a novel imaging marker of atherosclerotic burden and merits further validation as a predictive tool in recurrent ischemic stroke/ TIA.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".