icobrain-ctp
Icometrix NV • Radiology • 02/28/2020
Device Purpose
icobrain ctp is an image processing software designed to quantify cerebral perfusion deficits from CT brain scans by automatically calculating key parameters such as Tmax and CBF abnormalities through algorithmic analysis of DICOM images. Its methodology involves generating quantitative reports and perfusion parameter maps, with its accuracy and reproducibility validated using both simulated digital phantoms and clinical data from stroke patients.
Summary
icobrain ctp is an image processing software package for trained professionals to analyze computed tomography (CT) perfusion scans of the brain, aiding in the assessment of cerebral hemodynamics. The software processes DICOM CT perfusion data to calculate parameters related to tissue flow and blood volume, specifically identifying and quantifying Tmax abnormality (tissue with delayed arrival) and CBF abnormality (tissue with delayed arrival and critically decreased cerebral blood flow) using algorithmic image processing. Key outputs include volumes of these abnormalities, their mismatch volume and ratio, arterial input/venous output function time series, and perfusion parameter maps (Tmax, CBF, CBV, MTT), all exportable in DICOM format. Performance validation was conducted on simulated digital phantoms and clinical CT scans from stroke patients, assessing accuracy against ground truth (simulated values, manually delineated DWI, reference device) and reproducibility under simulated patient motion. All validation tests met pre-established acceptance criteria, with perfusion parameter correlations exceeding 0.90 in digital phantom studies, demonstrating its capability for quantitative analysis.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. How does the algorithm for defining and segmenting Tmax and CBF abnormalities in icobrain ctp compare to other established methods, particularly in challenging cases like low signal-to-noise ratio or motion artifacts not fully mitigated by pre-processing?; What is the specific range of 'clinically relevant values of perfusion parameters' used in the digital phantom validation, and how does the software's accuracy vary across this range, especially at extreme physiological or pathological values?; The performance testing mentions comparison to 'manually delineated DWI images' for CBF abnormality validation; what was the inter-rater and intra-rater variability for these manual delineations, and how does this variability compare to the software's performance metrics?; Given that the default thresholds for Tmax abnormality (Tmax > 6s) and CBF abnormality (CBF < 30%) are not user-adjustable, what is the evidence supporting these specific fixed thresholds across diverse patient populations, CT scanner manufacturers, and acquisition protocols?; How does icobrain ctp handle CTP scans with significant motion artifacts or incomplete contrast bolus administration, and what are the specific criteria or thresholds used by the software to determine when to exclude time points or image volumes due to artifacts, as mentioned in its output report capabilities?
Risk Classification
ESL AnalysisFDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Authorized before §524B enforcement
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Powered by SBOMator™Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.
Supply Chain BOM Evidence
Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.
Analysis:
• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.
• Evidence of SBOM, ML-BOM detected in AI-generated device summary.
• This device was authorized before §524B took effect. Cybersecurity evidence requirements were less prescriptive at the time.
• Postmarket cybersecurity monitoring plan not clearly documented in AI-generated device summary.
• Not detected in AI-generated device summary: SaaSBOM, HBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.
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