ArticleWorld neurosurgery2023
Automated Quantification of Compartmental Blood Volumes Enables Prediction of Delayed Cerebral Ischemia and Outcomes After Aneurysmal Subarachnoid Hemorrhage.
Article in World neurosurgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Machine Learning for the Early Prediction of Delayed Cerebral Ischemia in Patients With Subarachnoid Hemorrhage: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Association of Impaired Hematoma Clearance After Aneurysmal Subarachnoid Hemorrhage with Delayed Cerebral Ischemia, Hydrocephalus, and Long-Term Outcomes.Neurocritical care · 2026Article
- Cerebral Vasospasm Detection and Delayed Cerebral Ischemia Prediction after Aneurysmal Subarachnoid Hemorrhage: A Scoping Review.Neurocritical care · 2026Article
- Prognostic Value of Admission D-dimer Levels and Total Bleeding Volume in Aneurysmal Subarachnoid Hemorrhage: A Retrospective Cohort Study with Machine Learning-Based Modeling.Neurocritical care · 2026Article
- A Longitudinal Imaging and Clinical Data Workflow Identifies Potential Time-Dependent Risk Factors for Post-Subarachnoid Hemorrhage Epilepsy.Neurocritical care · 2026Article
- A Platform for Automatic Extraction of Imaging Biomarkers in CT Scans from Ischemic and Hemorrhagic Stroke Patients.Journal of imaging informatics in medicine · 2026Article
- Associations Between Delayed Cerebral Ischemia in Spontaneous Subarachnoid Hemorrhage and Dysfunction of Autonomic Cardiovascular Modulation Compared to Transcranial Doppler Ultrasound Findings.Diagnostics (Basel, Switzerland) · 2026Article
- External multicenter validation of the eSAH score for predicting outcomes after subarachnoid hemorrhage.Scientific reports · 2025Article
- Volumetric blood cutoff for outcome prediction in aneurysmal subarachnoid hemorrhage using semiautomated quantification.European journal of medical research · 2025Article
- Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage.BMC medical imaging · 2025Article
- SAHVAI-3D and 4D: Automated AI Volumetric Measurement of Subarachnoid Hemorrhage on Noncontrast Head CT.Stroke (Hoboken, N.J.) · 2025Article
- Semiautomated Hemorrhage Volume Quantification in Aneurysmal Subarachnoid Hemorrhage.Neurocritical care · 2025Article
- Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT.AJNR. American journal of neuroradiology · 2024Article
- Deep learning-based multiclass segmentation in aneurysmal subarachnoid hemorrhage.Frontiers in neurology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
objectiveThe role of hemorrhage volume in risk of vasospasm, delayed cerebral ischemia (DCI), and poor outcomes after aneurysmal subarachnoid hemorrhage (SAH) is well established. However, the relative contribution of blood within individual compartments is unclear. We present an automated technique for measuring not only total but also volumes of blood in each major compartment after SAH.
methodsWe trained convolutional neural networks to identify compartmental blood (cisterns, sulci, and ventricles) from baseline computed tomography scans of patients with SAH. We compared automated blood volumes against traditional markers of bleeding (modified Fisher score [mFS], Hijdra sum score [HSS]) in 190 SAH patients for prediction of vasospasm, DCI, and functional status (modified Rankin Scale) at hospital discharge.
resultsCombined cisternal and sulcal volume was better correlated with mFS and HSS than cisternal volume alone (ρ = 0.63 vs. 0.58 and 0.75 vs. 0.70, P < 0.001). Only blood volume in combined cisternal plus sulcal compartments was independently associated with DCI (OR 1.023 per mL, 95% CI 1.002-1.048), after adjusting for clinical factors while ventricular blood volume was not. Total and specifically sulcal blood volume was strongly associated with poor outcome (OR 1.03 per mL, 1.01-1.06, P = 0.006 and OR 1.04, 1.00-1.08 for sulcal) as was HSS (OR 1.06 per point, 1.00-1.12, P = 0.04), while mFS was not (P = 0.24).
conclusionsAn automated imaging algorithm can measure the volume of bleeding after SAH within individual compartments, demonstrating cisternal plus sulcal (and not ventricular) blood contributes to risk of DCI/vasospasm. Automated blood volume was independently associated with outcome, while qualitative grading was not.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.