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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

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Combined Near-infrared Fluorescent Imaging and Micro-computed Tomography for Directly Visualizing Cerebral Thromboemboli

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One scan, two answers: RAPID vs Brainomix agreement in thrombectomy patients.

Paul McHugh¹, Eimear Boylan², Seamus Looby^3,4

¹Diagnostic and Interventional Neuroradiology Department, Beaumont Hospital, Dublin, Ireland paulmchugh2@beaumont.ie.

Journal of Neurointerventional Surgery

|June 11, 2026

Summary

Automated CT perfusion software outputs from RAPID and Brainomix correlate but are not interchangeable for large-vessel occlusion stroke selection. Different CTP software can impact endovascular thrombectomy eligibility, necessitating cautious application of thresholds.

Keywords:

CT perfusion Stroke Thrombectomy

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Published on: November 26, 2013

Area of Science:

Neurology
Medical Imaging
Interventional Radiology

Background:

Automated CT perfusion (CTP) software is crucial for selecting large-vessel occlusion (LVO) stroke patients for endovascular thrombectomy (EVT).
Current practice often assumes interchangeability of CTP outputs from different software platforms, potentially affecting treatment decisions.

Purpose of the Study:

To compare the outputs of RAPID and Brainomix CTP software within the same cohort of patients undergoing EVT for LVO stroke.
To assess the agreement and potential discrepancies between these two widely used CTP analysis platforms.

Main Methods:

A retrospective observational study analyzed paired volumetric CTP data from 328 EVT patients using both RAPID and Brainomix algorithms.
Inter-platform agreement was evaluated using intraclass correlation coefficients (ICC), Pearson correlation (r), and Bland-Altman analysis.
A simplified reclassification assessed volumetric core thresholds from DEFUSE-3 and DAWN trials.

Main Results:

Median core volumes differed significantly (RAPID: 4 mL vs. Brainomix: 10 mL), with good but not perfect agreement (r=0.82, ICC=0.81) and systematic bias.
Penumbra volumes also showed lower agreement (r=0.77, ICC=0.74) with substantial bias and wide limits of agreement.
Clinically significant core discrepancies occurred in 20.1% of patients, and threshold-based reclassification was discordant in 3.4% to 7.0% of cases.

Conclusions:

While RAPID and Brainomix CTP software show overall correlation, their outputs are not interchangeable due to systematic biases and wide limits of agreement.
These discrepancies can influence mismatch-based eligibility for EVT.
Rigid application of CTP thresholds for EVT selection requires caution and integration with comprehensive clinical evaluation.