uCT ATLAS Astound with uWS-CT-Dual Energy Analysis; uCT ATLAS with uWS-CT-Dual Energy Analysis
K243617Shanghai United Imaging Healthcare Co.,Ltd. · cleared 2025-05-16 · product code JAK · Radiology
Premarket evidence — what FDA accepted
source quote (p.4)
“uCT ATLAS Astound is a computed tomography x-ray system, which is intended to produce cross-sectional images of the whole body by computer reconstruction of x-ray transmission data taken at different angles and planes. uWS-CT-Dual Energy Analysis is a post-processing software package that accepts UIH CT images acquired using different tube voltages and/or tube currents of the same anatomical location. It is an image reconstruction method for cardiac scanning based on deep learning technology.”
source quote (p.9)
“It is an image reconstruction method for cardiac scanning based on deep learning technology. It is an image reconstruction method that combines a modal-based iterative reconstruction and deep learning technology. It can recommend the optimal phase for cardiac reconstruction, which is based on deep learning technology. It is an intelligent function based on deep learning to reduce the artifacts caused by head motion. It can extend reconstruction FOV to bore size using deep learning technique. It is a motion correction function for cardiac scanning to reduce coronary motion artifact, which is based on deep learning technology.”
Validation studies (10)
Bench
sample size not stated
endpoints: IQ Performance (CT HU number, thickness section); Low Contrast Detectability (LCD); High Contrast Spatial Resolution; Noise
standards: IEC 61223-3-5, CTIQ White Paper, AAPM's report
Bench
sample size not stated
endpoints: IQ Performance (CT HU number, thickness section); Low Contrast Detectability (LCD); High Contrast Spatial Resolution; Noise
standards: IEC 61223-3-5, CTIQ White Paper, AAPM's report
Bench
sample size not stated
endpoints: Extraction accuracy of AI module in heart and coronary artery structure; Dice Similarity Coefficient (DICE); Precision; Recall
Bench
sample size not stated
endpoints: Effectiveness on reducing head motion artifacts
Bench
sample size not stated
endpoints: Effectiveness on improving CT value accuracy; Improving CT number when scanned object exceeds FOV
Reader study (MRMC)
sample size not stated
endpoints: Image quality aspects (noise level, structure fidelity, image quality, clinical features)
Reader study (MRMC)
sample size not stated
endpoints: Image quality aspects (noise level, streaking artifact reduction, image structure fidelity)
Reader study (MRMC)
sample size not stated
endpoints: Image quality aspects (artifact correction effect, clinical diagnostic benefit)
Reader study (MRMC)
sample size not stated
endpoints: Image quality aspects (image artifacts, homogeneity of same tissue); Accuracy of image CT numbers
Reader study (MRMC)
sample size not stated
endpoints: Contours clear and continuous; Motion artifacts of coronary arteries tolerable; Number of diagnostic coronaries reaches at least 50% of the total number of coronary artery segments
Reported performance (1 observation)
source quote (p.13)
“The results confirm that the images with Ultra EFOV can improve the accuracy of image CT numbers, in cases where the scanned object exceeds the CT field of view.”
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
- re_clearance
The FDA AI/ML device list shows a newer 510(k) K253173 (decision 2026-01-20) from Shanghai United Imaging Healthcare Co., Ltd. for a matching device line ("uCT 780 with uWS-CT-Dual Energy Analysis") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K253173
- recall_reason_pattern
Software/algorithm-related recall in product code JAK (GE Medical Systems, LLC, initiated 2026-03-26): "GE HealthCare has become aware of a potential security vulnerability impacting AW Server deployed via Edison Health Link (EHL) based CT Smart Subscription used in conjunction with " Recalling firm is another firm in the same product code.
first seen 2026-07-08 · recall res_event_number:98738
- recall_reason_pattern
Software/algorithm-related recall in product code JAK (PHILIPS MEDICAL SYSTEMS, initiated 2026-03-07): "Philips has identified three software issues: 1. During a continuous CT (CCT) scan, there is the potential that the Gantry could remain at the current scan position after pressing" Recalling firm is another firm in the same product code.
first seen 2026-07-08 · recall res_event_number:98588
- recall_reason_pattern
Software/algorithm-related recall in product code JAK (Siemens Medical Solutions USA, Inc, initiated 2025-12-19): "To remove the software applications from certain CT systems as the applications have not received FDA 510(k) clearance." Recalling firm is another firm in the same product code.
first seen 2026-07-08 · recall res_event_number:98206
- recall_reason_pattern
Software/algorithm-related recall in product code JAK (PHILIPS MEDICAL SYSTEMS, initiated 2025-09-25): "Issue 1: The potential for unintentional continued gantry/couch movement when a specific button series is used requiring use of manual stop. Issue 2. When performing a helical/Axia" Recalling firm is another firm in the same product code.
first seen 2026-07-08 · recall res_event_number:97699
- recall_reason_pattern
Software/algorithm-related recall in product code JAK (Philips North America Llc, initiated 2025-05-29): "Devices with affected software may experience two unintended motion issues that may lead to contact between the Gantry or table with the operator or patient, along with additional " Recalling firm is another firm in the same product code.
first seen 2026-07-08 · recall res_event_number:97010
- …and 4 more.
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-specific2022-09Computer-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-specific2022-09Clinical 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-specific2022-06Technical 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 guidance2026-01Clinical 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 guidance2026-01General 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 guidance2025-09Computer 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 guidance2025-06Cybersecurity 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 guidance2024-12Marketing 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 guidance2023-10Electronic 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 guidance2023-08Off-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 guidance2023-06Content 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 guidance2022-09Policy 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 guidance2021-10De 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 guidance2016-12Postmarket Management of Cybersecurity in Medical Devices
Cybersecurity · Postmarket
- Final guidance2002-01General 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 guidance2025-01Artificial 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 guidance2024-08Predetermined 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 principles2024-06Transparency for Machine Learning-Enabled Medical Devices: Guiding Principles
Transparency · AI/ML lifecycle
- Guiding principles2023-10Predetermined 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 principles2021-10Good 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.