EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100)
K241923Ever Fortune.AI, Co., Ltd. · cleared 2024-12-06 · product code QAS · Radiology
Premarket evidence — what FDA accepted
source quote (p.6)
“EFAI NEUROSUITE CT MIDLINE SHIFT ASSESSMENT SYSTEM (EFAI MLSCT) is a radiological computer-assisted triage and notification software system.”
source quote (p.4)
“EFAI NEUROSUITE CT MIDLINE SHIFT ASSESSMENT SYSTEM (EFAI MLSCT) is a software workflow tool designed to aid in prioritizing the clinical assessment of non-contrast head CT cases with features suggestive of midline shift (MLS) in individuals aged 18 years and above. EFAI MLSCT analyzes cases using deep learning algorithms to identify suspected MLS findings.”
source quote (p.8)
“Additionally, the software validation activities were performed in accordance with ... the FDA Guidance documents, “Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions."”
Validation studies (1)
Retrospective clinical
n=300 cases
endpoints: evaluate the performance of the EFAI MLSCT in identifying midline shift (MLS); system processing time per study
standards: IEC 62304:2006/A1:2016 - Medical device software – Software life cycle processes, FDA Guidance documents, “Content of Premarket Submissions for Device Software Functions”, FDA Guidance documents, “Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions."
Reported performance (3 observations)
source quote (p.9)
“The EFAI MLSCT was able to demonstrate sensitivity and specificity of 0.961 (95% CI=0.903-0.985) and 0.955 (95% CI=0.916-0.973) respectively, along with an AUROC of 0.983 (95% CI=0.967-0.996), which is substantially equivalent to the predicate device (qER, K200921).”
source quote (p.9)
“The EFAI MLSCT was able to demonstrate sensitivity and specificity of 0.961 (95% CI=0.903-0.985) and 0.955 (95% CI=0.916-0.973) respectively, along with an AUROC of 0.983 (95% CI=0.967-0.996), which is substantially equivalent to the predicate device (qER, K200921).”
source quote (p.9)
“The EFAI MLSCT was able to demonstrate sensitivity and specificity of 0.961 (95% CI=0.903-0.985) and 0.955 (95% CI=0.916-0.973) respectively, along with an AUROC of 0.983 (95% CI=0.967-0.996), which is substantially equivalent to the predicate device (qER, K200921).”
Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.
Predicate network
Postmarket — what happened after clearance
Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device). Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.
Reimbursement — how devices like this got paid
Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).