Abstract 36: The Boston Criteria V2.0 for Cerebral Amyloid Angiopathy: Updated Criteria and Multicenter MRI-Neuropathology Validation
Bibliographic record
Abstract
Introduction: The Boston criteria are used worldwide for in vivo diagnosis of cerebral amyloid angiopathy (CAA). Given substantial advances in CAA research, we aimed to update the Boston criteria and externally validate their diagnostic accuracy across the spectrum of CAA-related presentations and across international sites. Methods: As part of an International CAA Association multicenter study, we identified patients age 50 or older with potential CAA-related clinical presentations (spontaneous intracerebral hemorrhage, cognitive impairment, or transient focal neurological episodes), available brain MRI, and histopathologic assessment for the diagnosis of CAA. We derived Boston criteria v2.0 by selecting MRI features to optimize diagnostic specificity and sensitivity in a pre-specified derivation sample (Boston cases 1994 to 2012, n=159), then externally validated in pre-specified temporal (Boston cases 2012-2018, n=59) and geographical (non-Boston cases 2004-2018; n=123) validation samples and compared their diagnostic accuracy to the currently used modified Boston criteria. Results: Based on exploratory analyses in the derivation sample, we derived provisional criteria for probable CAA requiring presence of at least 2 strictly lobar hemorrhagic lesions (intracerebral hemorrhage, cerebral microbleed, or cortical superficial siderosis focus) or at least 1 strictly lobar hemorrhagic lesion and 1 white matter characteristic (severe degree of visible perivascular spaces in centrum semiovale or white matter hyperintensities multispot pattern). Sensitivity/specificity of the criteria were 74.8/84.6% in the derivation sample, 92.5/89.5% in the temporal validation sample, 80.2/81.5% in the geographic validation sample, and 74.5/95.0% in cases across all samples with autopsy as the diagnostic gold standard. The v2.0 criteria for probable CAA had superior accuracy to the currently modified Boston criteria (p<0.005) in the autopsied cases. Conclusion: The Boston criteria v.2.0 incorporate emerging MRI markers of CAA to enhance sensitivity without compromising their high specificity. Validation of the criteria across independent patient settings firmly supports their adoption into clinical practice and research.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".