a2z-Unified-Triage

K252366

A2z Radiology Ai, Inc. · cleared 2025-11-24 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.4)

“a2z-Unified-Triage is a radiological computer-aided triage and notification software indicated for use in the analysis of abdominal/pelvic CT images in adults aged 22 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communicating suspected positive cases of the 7 specified abdominopelvic findings: Acute Cholecystitis, Acute Pancreatitis, Unruptured Abdominal Aortic Aneurysm, Acute Diverticulitis, Free Air, Hydronephrosis, and Small Bowel Obstruction. These findings are intended to be used together as one device. The device supports both cloud-based and on-premises deployment, with integration either directly with healthcare facility systems or through third-party healthcare technology platforms.”

Algorithmartificial intelligence algorithms implement deep learning models that analyze CT studies and return binary outputs indicating the presence or absence of each of the 7 target abdominopelvic findings

source quote (p.6)

“Algorithm Architecture: The artificial intelligence algorithms implement deep learning models that analyze CT studies and return binary outputs indicating the presence or absence of each of the 7 target abdominopelvic findings.”

Adaptive (vs locked)No

source quote (p.13)

“The PCCP does not include provisions for implementation of adaptive algorithms that will continuously learn in the field. All algorithm modifications will be trained, validated, and locked prior to release of the software to the field.”

PCCPYes

source quote (p.1)

“FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP). Under section 515C(b)(1) of the Act, a new premarket notification is not required for a change to a device cleared under section 510(k) of the Act, if such change is consistent with an established PCCP granted pursuant to section 515C(b)(2) of the Act.”

Cybersecurity addressedNo

Validation studies (1)

Retrospective clinical

n=675 cases · 12 site(s)

endpoints: Acute Cholecystitis; Acute Pancreatitis; Unruptured AAA; Acute Diverticulitis; Free Air; Hydronephrosis; Small Bowel Obstruction

Reported performance (45 observations)

aurocas written: “Acute Cholecystitis (QFM) AUC”0.985CI 0.972-0.998

source quote (p.12)

“Acute Cholecystitis (QFM) Total N=675, Positive=77 AUC: 0.985 [0.972-0.998]”

sensitivityas written: “Acute Cholecystitis (QFM) High Sensitivity Sensitivity”0.961CI 89.2-98.7%

source quote (p.12)

“High Sensitivity: Se 96.1% [89.2-98.7%], Sp 89.3% [86.6-91.5%]”

sensitivityas written: “Acute Cholecystitis (QFM) High Sensitivity Specificity”0.893CI 86.6-91.5%

source quote (p.12)

“High Sensitivity: Se 96.1% [89.2-98.7%], Sp 89.3% [86.6-91.5%]”

sensitivityas written: “Acute Cholecystitis (QFM) Sensitivity Biased Sensitivity”0.922CI 84.0-96.4%

source quote (p.12)

“Sensitivity Biased: Se 92.2% [84.0-96.4%], Sp 95.8% [93.9-97.2%]”

sensitivityas written: “Acute Cholecystitis (QFM) Sensitivity Biased Specificity”0.958CI 93.9-97.2%

source quote (p.12)

“Sensitivity Biased: Se 92.2% [84.0-96.4%], Sp 95.8% [93.9-97.2%]”

sensitivityas written: “Acute Cholecystitis (QFM) Balanced Sensitivity”0.922CI 84.0-96.4%

source quote (p.12)

“Balanced: Se 92.2% [84.0-96.4%], Sp 95.8% [93.9-97.2%]”

specificityas written: “Acute Cholecystitis (QFM) Balanced Specificity”0.958CI 93.9-97.2%

source quote (p.12)

“Balanced: Se 92.2% [84.0-96.4%], Sp 95.8% [93.9-97.2%]”

aurocas written: “Acute Pancreatitis (QFM) AUC”0.994CI 0.985-1.000

source quote (p.12)

“Acute Pancreatitis (QFM) Total N=675, Positive=99 AUC: 0.994 [0.985-1.000]”

sensitivityas written: “Acute Pancreatitis (QFM) High Sensitivity Sensitivity”0.98CI 92.9-99.4%

source quote (p.12)

“High Sensitivity: Se 98.0% [92.9-99.4%], Sp 87.8% [84.9-90.3%]”

sensitivityas written: “Acute Pancreatitis (QFM) High Sensitivity Specificity”0.878CI 84.9-90.3%

source quote (p.12)

“High Sensitivity: Se 98.0% [92.9-99.4%], Sp 87.8% [84.9-90.3%]”

sensitivityas written: “Acute Pancreatitis (QFM) Sensitivity Biased Sensitivity”0.98CI 92.9-99.4%

source quote (p.12)

“Sensitivity Biased: Se 98.0% [92.9-99.4%], Sp 97.0% [95.3-98.1%]”

sensitivityas written: “Acute Pancreatitis (QFM) Sensitivity Biased Specificity”0.97CI 95.3-98.1%

source quote (p.12)

“Sensitivity Biased: Se 98.0% [92.9-99.4%], Sp 97.0% [95.3-98.1%]”

sensitivityas written: “Acute Pancreatitis (QFM) Balanced Sensitivity”0.98CI 92.9-99.4%

source quote (p.12)

“Balanced: Se 98.0% [92.9-99.4%], Sp 97.0% [95.3-98.1%]”

specificityas written: “Acute Pancreatitis (QFM) Balanced Specificity”0.97CI 95.3-98.1%

source quote (p.12)

“Balanced: Se 98.0% [92.9-99.4%], Sp 97.0% [95.3-98.1%]”

sensitivityas written: “Acute Pancreatitis (QFM) High Specificity Sensitivity”0.929CI 86.1-96.5%

source quote (p.12)

“High Specificity: Se 92.9% [86.1-96.5%], Sp 99.8% [99.0-100.0%]”

specificityas written: “Acute Pancreatitis (QFM) High Specificity Specificity”0.998CI 99.0-100.0%

source quote (p.12)

“High Specificity: Se 92.9% [86.1-96.5%], Sp 99.8% [99.0-100.0%]”

aurocas written: “Acute Diverticulitis (QFM) AUC”0.995CI 0.990-1.000

source quote (p.12)

“Acute Diverticulitis (QFM) Total N=675, Positive=76 AUC: 0.995 [0.990-1.000]”

sensitivityas written: “Acute Diverticulitis (QFM) High Sensitivity Sensitivity”0.987CI 92.9-99.8%

source quote (p.12)

“High Sensitivity: Se 98.7% [92.9-99.8%], Sp 89.3% [86.6-91.5%]”

sensitivityas written: “Acute Diverticulitis (QFM) High Sensitivity Specificity”0.893CI 86.6-91.5%

source quote (p.12)

“High Sensitivity: Se 98.7% [92.9-99.8%], Sp 89.3% [86.6-91.5%]”

sensitivityas written: “Acute Diverticulitis (QFM) Sensitivity Biased Sensitivity”0.974CI 90.9-99.3%

source quote (p.12)

“Sensitivity Biased: Se 97.4% [90.9-99.3%], Sp 96.8% [95.1-98.0%]”

sensitivityas written: “Acute Diverticulitis (QFM) Sensitivity Biased Specificity”0.968CI 95.1-98.0%

source quote (p.12)

“Sensitivity Biased: Se 97.4% [90.9-99.3%], Sp 96.8% [95.1-98.0%]”

sensitivityas written: “Acute Diverticulitis (QFM) Balanced Sensitivity”0.974CI 90.9-99.3%

source quote (p.12)

“Balanced: Se 97.4% [90.9-99.3%], Sp 96.8% [95.1-98.0%]”

specificityas written: “Acute Diverticulitis (QFM) Balanced Specificity”0.968CI 95.1-98.0%

source quote (p.12)

“Balanced: Se 97.4% [90.9-99.3%], Sp 96.8% [95.1-98.0%]”

sensitivityas written: “Acute Diverticulitis (QFM) High Specificity Sensitivity”0.947CI 87.2-97.9%

source quote (p.12)

“High Specificity: Se 94.7% [87.2-97.9%], Sp 98.7% [97.4-99.3%]”

specificityas written: “Acute Diverticulitis (QFM) High Specificity Specificity”0.987CI 97.4-99.3%

source quote (p.12)

“High Specificity: Se 94.7% [87.2-97.9%], Sp 98.7% [97.4-99.3%]”

aurocas written: “Unruptured AAA (QFM) AUC”0.995CI 0.991-0.999

source quote (p.12)

“Unruptured AAA (QFM) Total N=675, Positive=76 AUC: 0.995 [0.991-0.999]”

sensitivityas written: “Unruptured AAA (QFM) High Sensitivity Sensitivity”1CI 95.2-100.0%

source quote (p.12)

“High Sensitivity: Se 100.0% [95.2-100.0%], Sp 86.3% [83.3-88.8%]”

sensitivityas written: “Unruptured AAA (QFM) High Sensitivity Specificity”0.863CI 83.3-88.8%

source quote (p.12)

“High Sensitivity: Se 100.0% [95.2-100.0%], Sp 86.3% [83.3-88.8%]”

sensitivityas written: “Unruptured AAA (QFM) Sensitivity Biased Sensitivity”0.974CI 90.9-99.3%

source quote (p.12)

“Sensitivity Biased: Se 97.4% [90.9-99.3%], Sp 95.8% [93.9-97.2%]”

sensitivityas written: “Unruptured AAA (QFM) Sensitivity Biased Specificity”0.958CI 93.9-97.2%

source quote (p.12)

“Sensitivity Biased: Se 97.4% [90.9-99.3%], Sp 95.8% [93.9-97.2%]”

sensitivityas written: “Unruptured AAA (QFM) Balanced Sensitivity”0.974CI 90.9-99.3%

source quote (p.12)

“Balanced: Se 97.4% [90.9-99.3%], Sp 97.5% [95.9-98.5%]”

specificityas written: “Unruptured AAA (QFM) Balanced Specificity”0.975CI 95.9-98.5%

source quote (p.12)

“Balanced: Se 97.4% [90.9-99.3%], Sp 97.5% [95.9-98.5%]”

aurocas written: “Hydronephrosis (QFM) AUC”0.976CI 0.960-0.991

source quote (p.12)

“Hydronephrosis (QFM) Total N=675, Positive=97 AUC: 0.976 [0.960-0.991]”

sensitivityas written: “Hydronephrosis (QFM) High Sensitivity Sensitivity”0.897CI 82.1-94.3%

source quote (p.12)

“High Sensitivity: Se 89.7% [82.1-94.3%], Sp 92.9% [90.5-94.7%]”

sensitivityas written: “Hydronephrosis (QFM) High Sensitivity Specificity”0.929CI 90.5-94.7%

source quote (p.12)

“High Sensitivity: Se 89.7% [82.1-94.3%], Sp 92.9% [90.5-94.7%]”

sensitivityas written: “Small Bowel Obstruction (QAS) High Sensitivity Sensitivity”0.949CI 88.7-97.8%

source quote (p.13)

“High Sensitivity: Se 94.9% [88.7-97.8%], Sp 91.7% [89.1-93.7%]”

sensitivityas written: “Small Bowel Obstruction (QAS) High Sensitivity Specificity”0.917CI 89.1-93.7%

source quote (p.13)

“High Sensitivity: Se 94.9% [88.7-97.8%], Sp 91.7% [89.1-93.7%]”

sensitivityas written: “Small Bowel Obstruction (QAS) Sensitivity Biased Sensitivity”0.919CI 84.9-95.8%

source quote (p.13)

“Sensitivity Biased: Se 91.9% [84.9-95.8%], Sp 96.0% [94.1-97.3%]”

sensitivityas written: “Small Bowel Obstruction (QAS) Sensitivity Biased Specificity”0.96CI 94.1-97.3%

source quote (p.13)

“Sensitivity Biased: Se 91.9% [84.9-95.8%], Sp 96.0% [94.1-97.3%]”

sensitivityas written: “Small Bowel Obstruction (QAS) Balanced Sensitivity”0.889CI 81.2-93.7%

source quote (p.13)

“Balanced: Se 88.9% [81.2-93.7%], Sp 98.1% [96.6-98.9%]”

specificityas written: “Small Bowel Obstruction (QAS) Balanced Specificity”0.981CI 96.6-98.9%

source quote (p.13)

“Balanced: Se 88.9% [81.2-93.7%], Sp 98.1% [96.6-98.9%]”

sensitivityas written: “Free Air (QAS) Balanced Sensitivity”0.893CI 82.2-93.8%

source quote (p.13)

“Balanced: Se 89.3% [82.2-93.8%], Sp 88.6% [85.7-91.0%]”

specificityas written: “Free Air (QAS) Balanced Specificity”0.886CI 85.7-91.0%

source quote (p.13)

“Balanced: Se 89.3% [82.2-93.8%], Sp 88.6% [85.7-91.0%]”

sensitivityas written: “Free Air (QAS) High Specificity Sensitivity”0.884CI 81.1-93.1%

source quote (p.13)

“High Specificity: Se 88.4% [81.1-93.1%], Sp 90.8% [88.1-92.9%]”

specificityas written: “Free Air (QAS) High Specificity Specificity”0.908CI 88.1-92.9%

source quote (p.13)

“High Specificity: Se 88.4% [81.1-93.1%], Sp 90.8% [88.1-92.9%]”

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

recalls in product code, 24mo

MAUDE reports in code, 12mo

—

vs code's own 3-yr baseline

drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. 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).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Radiology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Final guidanceRadiology-specific2022-09
Computer-Assisted Detection Devices Applied to Radiology Images and Radiology Device Data - Premarket Notification [510(k)] Submissions
Radiology CADe/CADx · Software premarket content
Original July 2012; current database date reflects a Sept 2022 reissue. Governs CADe device 510(k) content.
Final guidanceRadiology-specific2022-09
Clinical Performance Assessment: Considerations for Computer-Assisted Detection Devices Applied to Radiology Images and Radiology Device Data in Premarket Notification (510(k)) Submissions
Radiology CADe/CADx
Original July 2012, revised 2020; current database date Sept 2022. Covers standalone and reader-study performance assessment for CADe.
Final guidanceRadiology-specific2022-06
Technical Performance Assessment of Quantitative Imaging in Radiological Device Premarket Submissions
Quantitative imaging · Radiology CADe/CADx
Final (June 2022). Relevant to devices outputting quantitative imaging measurements.
Final guidance2026-01
Clinical Decision Support Software
Clinical decision support · SaMD (general)
New final guidance issued Jan 2026, superseding the Sept 2022 version; narrows the device-CDS scope. Applies to software that informs clinical management.
Final guidance2026-01
General Wellness: Policy for Low Risk Devices
SaMD (general) · Clinical decision support
Revised final (Jan 2026); now addresses noninvasive products estimating physiologic parameters (SpO2, BP, glucose). Reshapes the device / non-device line for AI wellness features.
Final guidance2025-09
Computer Software Assurance for Production and Quality Management System Software
SaMD (general) · Postmarket
Final (Sept 2025). Covers software used in production/QMS (incl. ML development-pipeline tooling), superseding Section 6 of the 2002 GPSV — not device software functions themselves.
Final guidance2025-06
Cybersecurity in Medical Devices: Quality Management System Considerations and Content of Premarket Submissions
Cybersecurity · Software premarket content
Reissued June 2025 (retitled 'Quality Management System', was Sept 2023 'Quality System'); adds coverage of FD&C Act §524B cyber devices.
Final guidance2024-12
Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence-Enabled Device Software Functions
Predetermined Change Control Plan · AI/ML lifecycle · Software premarket content
Final (Dec 2024). Supersedes the April 2023 AI/ML PCCP draft.
Final guidance2023-10
Electronic Submission Template for Medical Device 510(k) Submissions
Software premarket content
eSTAR has been mandatory for 510(k)s since Oct 2023 — operationally unavoidable, though not AI-specific.
Final guidance2023-08
Off-The-Shelf Software Use in Medical Devices
Software premarket content · SaMD (general)
Final (Aug 2023). Applies when a device incorporates off-the-shelf software components (common in ML stacks).
Final guidance2023-06
Content of Premarket Submissions for Device Software Functions
Software premarket content · SaMD (general)
Final (June 2023); replaced the May 2005 'Software Contained in Medical Devices' guidance. Documentation level drives the software content of the submission.
Final guidance2022-09
Policy for Device Software Functions and Mobile Medical Applications
SaMD (general) · Clinical decision support
Current version Sept 2022. Frames which software functions FDA regulates as devices.
Final guidance2021-10
De Novo Classification Process (Evaluation of Automatic Class III Designation)
De Novo pathway
Final (Oct 2021), issued with the De Novo final rule. Most relevant to first-of-a-kind devices without a predicate (DEN-numbered clearances).
Final guidance2016-12
Postmarket Management of Cybersecurity in Medical Devices
Cybersecurity · Postmarket
Final guidance2002-01
General Principles of Software Validation
SaMD (general) · Software premarket content
Still active except Section 6 (superseded Sept 2025 by the Computer Software Assurance final guidance).
Draft guidance2025-01
Artificial Intelligence-Enabled Device Software Functions: Lifecycle Management and Marketing Submission Recommendations
AI/ML lifecycle · Software premarket content · Transparency
Draft as of July 2026 (published Jan 2025); finalization is on CDRH's FY2026 agenda but not yet published. Treat as FDA's stated direction, not a binding expectation.
Draft guidance2024-08
Predetermined Change Control Plans for Medical Devices
Predetermined Change Control Plan · Postmarket
Draft (Aug 2024) extending PCCPs beyond AI to all devices under FD&C §515C; not final as of July 2026.
Guiding principles2024-06
Transparency for Machine Learning-Enabled Medical Devices: Guiding Principles
Transparency · AI/ML lifecycle
Guiding principles2023-10
Predetermined Change Control Plans for Machine Learning-Enabled Medical Devices: Guiding Principles
Predetermined Change Control Plan · AI/ML lifecycle
FDA/Health Canada/MHRA joint principles (Oct 2023); companion to the GMLP and Transparency principles.
Guiding principles2021-10
Good Machine Learning Practice for Medical Device Development: Guiding Principles
AI/ML lifecycle · SaMD (general)
FDA/Health Canada/MHRA joint principles (Oct 2021). Foundational, not a binding guidance; IMDRF issued a related GMLP document Jan 2025.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.