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Record W4406993048 · doi:10.1161/str.56.suppl_1.50

Abstract 50: Co-localization of NCCT hypodensity and CTA spot sign to predict intracerebral hematoma expansion and severity: development and validation of the Black,-&-White sign

2025· article· en· W4406993048 on OpenAlexaffabout
Umberto Pensato, Kõji Tanaka, MacKenzie Horn, Ericka Teleg, Abdulaziz Al Sultan, Linda Kasickova Machova, Tomoyuki Ohara, Piyush Ojha, Sina Marzoughi, Ankur Banerjee, Girish Baburao Kulkarni, Bijoy K. Menon, Mayank Goyal, Michael D. Hill, Carlos A. Molina, Yolanda Silva, Jean‐Martin Boulanger, Gord Gubitz, Rohit Bhatia, M.V. Padma Srivastava, Jayanta Roy, Imanuel Dzialowski, Carlos S. Kase, Adam Kobayashi, David Rodríguez‐Luna, Richard I. Aviv, Dar Dowlatshahi, Andrew M. Demchuk

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsUniversity of TorontoUniversity of OttawaDalhousie UniversityGrand River HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineIntracerebral hemorrhageSign (mathematics)HematomaRadiologyBlack spotStroke (engine)Nuclear medicineSurgeryGlasgow Coma ScaleMathematical analysis

Abstract

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Introduction: Hematoma expansion (HE) occurs in one-fourth of patients with acute intracerebral hematoma (ICH) and is associated with worse outcomes. Existing radiological markers of HE show modest predictive accuracy. We aim to investigate a novel radiological marker that co-localizes findings from non-contrast CT (NCCT) and CT angiography (CTA) to predict HE. Methods: We analyzed 200 consecutive acute ICH patients admitted at Foothills Medical Centre in Calgary, Canada (development cohort) and analyzed 304 patients from the multicenter observational study PREDICT (validation cohort). The Black-&-White (B&W) sign was defined as any visually identified spot sign on CTA co-localized with a hypodensity sign on the corresponding NCCT ( Figure 1 ). The primary outcome was hematoma expansion (≥6mL or ≥33%). Secondary outcomes included absolute (<3mL, 3-6mL, 6-12mL, ≥12mL) and relative (0%, <25%, 25-50%, 50-75%, or >75%) hematoma growth scales. Results: In the development cohort, 22% (n=44) showed the spot sign, 34.5% (n=69) the hypodensity sign, and 7% (n=14) the B&W sign. Those with the B&W sign had higher proportions of HE (100% vs. 19.4%, p<0.001), greater absolute hematoma growth (23.37 mL [IQR=15.41-30.27] vs. 0 mL [IQR=0-2.39], p<0.001) and relative hematoma growth (120% [IQR=49-192] vs. 0% [0-15%], p<0.001) in comparison to those without. The B&W sign yielded a specificity of 100%, a PPV of 100%, and an accuracy of 82%. In the validation cohort, 25% (n=76) showed the spot sign, 39.1% (n=119) the hypodensity sign, and 9.5% (n=29) the B&W sign. Those with B&W signs had higher proportions of HE (79.3% vs. 30.2%, p<0.001), greater absolute hematoma growth (19.1 mL [IQR=6.4-40] vs. 0.8 mL [0-5.6], p<0.001), and relative hematoma growth (92% [IQR=16-151%] vs. 9% [0-34%], p<0.001) in comparison to those without. The B&W sign yielded a specificity of 97%, a PPV of 79%, and an accuracy of 71%. We found a consistent progressive improvement in predicting HE when hypodensity and spot signs are absent, individually present, both present but not co-localized, and co-localized ( Figures 2-3 ). The inter-rater agreement was excellent (k=0.84) in the development cohort, with a uniform imaging protocol of NCCT immediately followed by CTA at a single center, and moderate (k=0.54) in the validation cohort at multiple centers. Conclusion: The Black-&-White sign is a robust predictor of hematoma expansion occurrence and hematoma expansion severity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.017
GPT teacher head0.278
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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