K252000 · Shanghai United Imaging Healthcare Co., Ltd. · KPR · Nov 26, 2025 · Radiology
Device Facts
Record ID
K252000
Device Name
uDR Arria & uDR Aris
Applicant
Shanghai United Imaging Healthcare Co., Ltd.
Product Code
KPR · Radiology
Decision Date
Nov 26, 2025
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.1680
Device Class
Class 2
Attributes
AI/ML, Pediatric
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Automatic patient positioning and field of view setting
Deep learning-based patient positioning recognition technology
95% compliance with clinical technicians' criteria
95% compliance
—
—
Clinical observation study: 328 chest cases, 14 full spine cases, 20 full lower limb cases
>1 (clinical experts)
Chest X-ray image quality assessment
Deep learning-based image quality classification
90% pass rate for Grade A clinical images
Sensitivity and specificity > 0.9 for all four criteria
Data collected from October 2017 on uDR 780i; includes 3,080 positive foreign object cases, 31 positive lung field segmentation cases, 68 positive spinal centerline segmentation cases, and 1,089 positive shoulder blades segmentation cases.
—
Independent test dataset collected from cooperative hospitals
—
Indications for Use
Digital Medical X-ray Imaging System is intended to acquire X-ray images of the human body by a qualified technician, examples include acquiring two-dimensional X-ray images of the skull, spinal column, chest, abdomen, extremities, limbs and trunk. The visualization of such anatomical structures provide visual evidence to radiologists and clinicians in making diagnostic decisions. This device is not intended for mammography.
Device Story
uDR Arria and uDR Aris are stationary digital X-ray systems for general radiography. Systems consist of high-voltage generator, X-ray tube, collimator, flat-panel detector, and patient table. Operated by qualified technicians in clinical settings to acquire 2D images. Features include optional uVision (camera-based patient positioning/collimation planning) and uAid (deep learning-based image quality assessment for chest X-rays). Output images are reviewed by radiologists/clinicians for diagnostic decision-making. Benefits include optimized workflow, reduced retake rates via automated positioning, and standardized image quality management. uDR Aris supports 40kW generator; uDR Arria supports 65kW/80kW. Both utilize motorized/manual collimation and AEC.
Clinical Evidence
Bench testing only. Clinical image evaluation performed by a board-certified radiologist confirmed image quality is sufficient for diagnosis. uVision performance evaluated over 5 months (328 chest cases, 20 stitching cases) showing 95% compliance with clinical positioning requirements. uAid performance evaluated on independent dataset (n=~5,000+); sensitivity/specificity >0.9 for foreign body detection, lung field integrity, scapula positioning, and spine centering.
Technological Characteristics
Stationary X-ray system; 150kV max voltage; 65kW/80kW (Arria) or 40kW (Aris) generators. Detectors: CsI scintillator, 100μm pixel size. Connectivity: DICOM 3.0. Safety: ANSI/AAMI ES 60601-1, IEC 60601-1-2, IEC 60601-2-54. Biocompatibility: ISO 10993-5/10. Software: Deep learning-based positioning (uVision) and image quality assessment (uAid).
Indications for Use
Indicated for adult and pediatric patients requiring diagnostic radiographic exposures of the skull, spinal column, chest, abdomen, extremities, limbs, and trunk. Not indicated for mammography.
Regulatory Classification
Identification
A stationary x-ray system is a permanently installed diagnostic system intended to generate and control x-rays for examination of various anatomical regions. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.
Special Controls
*Classification.* Class II (special controls). A radiographic contrast tray or radiology diagnostic kit intended for use with a stationary x-ray system only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.
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FDA U.S. FOOD & DRUG ADMINISTRATION
November 26, 2025
Shanghai United Imaging Healthcare Co., Ltd.
% Xin Gao
Regulatory Affairs Manager
No.2258 Chengbei Rd. Jiading District
SHANGHAI, 201807
CHINA
Re: K252000
Trade/Device Name: uDR Arria & uDR Aris
Regulation Number: 21 CFR 892.1680
Regulation Name: Stationary X-Ray System
Regulatory Class: Class II
Product Code: KPR
Dated: October 24, 2025
Received: October 24, 2025
Dear Xin Gao:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
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K252000 - Xin Gao
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Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-
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K252000 - Xin Gao
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assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,

Lu Jiang, Ph.D.
Assistant Director
Diagnostic X-Ray Systems Team
DHT8B: Division of Radiologic Imaging Devices and Electronic Products
OHT8: Office of Radiological Health
Office of Product Evaluation and Quality
Center for Devices and Radiological Health
Enclosure
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FORM FDA 3881 (8/23)
Page 1 of 1
PSC Publishing Services (301) 443-6740
EF
| DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration Indications for Use | Form Approved: OMB No. 0910-0120 Expiration Date: 07/31/2026 See PRA Statement below. |
| --- | --- |
| 510(k) Number (if known) K252000 | |
| Device Name uDR Arria & uDR Aris | |
| Indications for Use (Describe) Digital Medical X-ray Imaging System is intended to acquire X-ray images of the human body by a qualified technician, examples include acquiring two dimensional X-ray images of the skull, spinal column, chest, abdomen, extremities, limbs and trunk. The visualization of such anatomical structures provide visual evidence to radiologists and clinicians in making diagnostic decisions. This device is not intended for mammography. | |
| Type of Use (Select one or both, as applicable) ☑ Prescription Use (Part 21 CFR 801 Subpart D) ☐ Over-The-Counter Use (21 CFR 801 Subpart C) | |
| CONTINUE ON A SEPARATE PAGE IF NEEDED. | |
| This section applies only to requirements of the Paperwork Reduction Act of 1995. *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.* | |
| The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to: Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.gov | |
| "An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number." | |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED IMAGING
510 (k) SUMMARY
1. Date of Preparation:
June 30, 2025
2. Sponsor Identification
Shanghai United Imaging Healthcare Co., Ltd.
No.2258 Chengbei Rd. Jiading District, 201807, Shanghai, China
Establishment Registration Number: 3011015597
3. Contact Person
Name: Xin Gao
Tel: +86-021-67076888-5386
Fax: +86-021-67076889
Email: xin.gao@united-imaging.com
4. Subject Device Name and Classification
Trade Name: uDR Arria & uDR Aris
Common Name: Digital Medical X-ray Imaging System
Model(s): uDR Arria, uDR Aris
Regulatory Information
Classification Name: Stationary X-Ray System
Device Classification: II
Product Code: KPR
Regulation Number: 21 CFR 892.1680
Review Panel: Radiology
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED IMAGING
5. Identification of Predicate/Reference Device(s)
## Predicate Device:
Trade Name: uDR 596i
510(k) Number: K192293
Classification Name: Stationary X-Ray System
Classification Panel: Radiology
Regulation Number: 21 CFR 892.1680
Classification: II
Product Code: KPR
## Reference Device:
Trade Name: MULTIX Impact E
510(k) Number: K233532
Classification Name: Stationary X-Ray System
Classification Panel: Radiology
Classification Regulation: 21 CFR §892.1680
Device Class: Class II
Product Code: KPR
## 6. Device Description:
uDR Arria and uDR Aris are two models of Digital Medical X-ray Imaging System developed and manufactured by Shanghai United Imaging Healthcare Co., Ltd(UIH). The system is equipped with imaging chain components and utilizes enhanced processing technology, so it can offer radiographic images with high image quality. The intuitive user interface and easy-to-use functions provide clinical users with a experience during patient examination and image processing.
The system is intended to acquire X-ray images of the human body by a qualified technician, examples include acquiring two-dimensional X-ray images of the skull, spinal column, chest, abdomen, extremities, limbs and trunk. The visualization of such anatomical structures provide visual evidence to radiologists and clinicians in making diagnostic decisions. This device is not intended for mammography.
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
UNITED
IMAGING
www.united-imaging.com
This proposed device includes two models: uDR Arria, uDR Aris. The main differences between the two models are as follows:
| Main Component | uDR Arria | uDR Aris |
| --- | --- | --- |
| **High Voltage Generator** | | |
| Generator with key performance: -Max. 40kW output power | / | ✓ |
| Generator with key performance: -Max. 65kW output power | ✓ | / |
| Generator with key performance: -Max. 80kW output power | ✓ | / |
| **X-ray Tube Assembly** | | |
| Tube with key performance: - Anode Heat Content 230kHU | / | ✓ |
| Tube with key performance: - Anode Heat Content 300kHU | ✓ | / |
| Tube with key performance: - Anode Heat Content 400kHU | ✓ | / |
| **Collimator** | | |
| Manual | ✓ | ✓ |
| Motorized | ✓ | / |
| **Flat Panel** | | |
| uFPD 1717-100 | ✓ | ✓ |
| uFPD 1417-100 | ✓ | ✓ |
| **Patient Table** | | |
| Elevating Table | ✓ | ✓ |
| **Optional Software function** | | |
| uAid | ✓ | / |
| uVision | ✓ | / |
The main difference between the two models is that only the uDR Aris supports the 40kW output power High Voltage Generator configuration. Other components are all available for uDR Arria.
7. Intended Use Statement:
The following statement applies to uDR Arria and uDR Aris:
Digital Medical X-ray Imaging System is intended to acquire X-ray images of the human body by a qualified technician, examples include acquiring two-dimensional
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
UNITED IMAGING
www.united-imaging.com
X-ray images of the skull, spinal column, chest, abdomen, extremities, limbs and trunk. The visualization of such anatomical structures provide visual evidence to radiologists and clinicians in making diagnostic decisions. This device is not intended for mammography.
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED IMAGING
8. Substantially Equivalent (SE) Comparison
A comparison between the technological characteristics of proposed and predicate devices is provided as below.
Table 1 Comparison of uDR Arria's Technology Characteristics to predicate device
| Item | Proposed Device uDR Arria | Predicate Device uDR 596i (K192293) | Remark |
| --- | --- | --- | --- |
| General | | | |
| Product Code | KPR | KPR | Same |
| Regulation No. | 892.1680 | 896.1680 | Same |
| Class | II | II | Same |
| Intended Use | Digital Medical X-ray Imaging System is intended to acquire X-ray images of the human body by a qualified technician, examples include acquiring two-dimensional X-ray images of the skull, spinal column, chest, abdomen, extremities, limbs and trunk. The visualization of such anatomical structures provide visual evidence to radiologists and clinicians in making diagnostic decisions. This device is not intended for mammography. | The uDR 596i Radiographic system is intended to use by a qualified/trained doctor or technician on both adult and pediatric subjects for taking diagnostic radiographic exposures of the skull, spinal column, chest, abdomen, extremities, limbs and trunk. Not for mammography. | Note 1 |
| Specifications | | | |
| High Voltage Generator | | | |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED
IMAGING
6
| Item | Proposed Device
uDR Arria | Predicate Device
uDR 596i
(K192293) | Remark |
| --- | --- | --- | --- |
| Max. Power/kW | 65kW/80kW | 65kW/80kW | Same |
| Max. tube Voltage(kV) | 150kV | 150kV | Same |
| Shortest exposure time | 1ms | 1ms | Same |
| X-Ray Tube Assembly | | | |
| Focus Nominal Value | 0.6/1.2 | 0.6/1.2 | Same |
| Maximum peak voltage | 150kV | 150kV | Same |
| Anode Heat Content | 65kw: ≥300kHU
80kw: ≥400kHU | 65kw: ≥300kHU
80kw: ≥400kHU | Same |
| Anode Target Angle | 12° | 12° | Same |
| X-ray tube Heat content | 65kw: ≥1250KHU
80kw: ≥1339KHU | 65kw: ≥1250KHU
80kw: ≥1500KHU | Note 2 |
| Flat Panel Detector-Config.1 | | | |
| Model | uFPD1717-100 | Mars1717XU-VSI | |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED
IMAGING
8 of 24
| Item | Proposed Device
uDR Arria | Predicate Device
uDR 596i
(K192293) | Remark |
| --- | --- | --- | --- |
| Scintillator | Cesium iodide (CsI) | Cesium iodide (CsI) | Same |
| Image Matrix Size | 4267x4267
100 μm | 3072×3072
139 μm | Note 3 |
| Effective radiographic size | 42.7cm x 42.7cm | 42.7cm x 42.7cm | Same |
| Flat Panel Detector-Config.2 | | | |
| Model | uFPD1417-100 | Mars1717XU-VSI | |
| Scintillator | Cesium iodide (CsI) | Cesium iodide (CsI) | Same |
| Image Matrix Size | 3500x4300
100 μm | 3072×3072
139 μm | Note 4 |
| Effective Radiographic Size | 35cm x 43cm | 42.7cm x 42.7cm | Note 5 |
| Collimator Config.1(Manual) | | | |
| Inherent filtration | 1.0 mmAl@75 kV | 1.0 mmAl@75kV | Same |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED
IMAGING
| Item | Proposed Device
uDR Arria | Predicate Device
uDR 596i
(K192293) | Remark |
| --- | --- | --- | --- |
| Copper prefilter | without filter,
0.1mm,
0.2mm,
0.3mm; | without filter,
0.1mm,
0.2mm | Note 6 |
| Motorized Field of View Control | No | No | Same |
| Automatic SID Adjusted Collimation | No | No | Same |
| Collimator Config.2 (Motorized) | | | |
| Inherent filtration | 1mm Al @75 kV | 1mm Al @75 kV | Same |
| Copper prefilter | without filter,
0.1 mm,
0.2 mm,
0.3 mm; | without filter,
0.1 mm,
0.2 mm | Note 7 |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED
IMAGING
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| Item | Proposed Device
uDR Arria | Predicate Device
uDR 596i
(K192293) | Remark |
| --- | --- | --- | --- |
| Motorized Field of View Control | Yes | No | Note 8 |
| Automatic SID Adjusted Collimation | Yes | No | Note 9 |
| Bulit-in camera | Live 2D Camera for patient positioning and collimation | N.A. | Note 10 |
| **Software function** | | | |
| Stitching | Yes | Yes | Same |
| Automatic exposure control (AEC) | Yes | Yes | Same |
| **Safety** | | | |
| Electrical Safety | ANSI/AAMI ES 60601-1:2005 & A1:2012 & A2:2021 Medical electrical equipment - Part 1: General requirements for basic safety and essential performance | ANSI/AAMI ES 60601-1:2005 & A1:2012 & A2:2021 Medical electrical equipment - Part 1: General requirements for basic safety and essential performance | Same |
| EMC | Comply with IEC 60601-1-2:2014+A1:2020 | Comply with IEC60601-1-2 | Same |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED
IMAGING
| Item | Proposed Device
uDR Arria | Predicate Device
uDR 596i
(K192293) | Remark |
| --- | --- | --- | --- |
| Biocompatibility | Patient Contact Materials were tested and demonstrated no cytotoxicity (ISO 10993-5), no evidence for irritation and sensitization (ISO 10993-10). | Patient Contact Materials were tested and demonstrated no cytotoxicity (ISO 10993-5), no evidence for irritation and sensitization (ISO 10993-10). | Same |
| Clinical Image Evaluation | Clinical Image Evaluation for the proposed device are provided in Section 11.5 Clinical Image Evaluation. | | |
| Standards | | | |
| DICOM | DICOM3 | DICOM3 | Same |
| Power Source | AC Line, Various voltages available | AC Line, Various voltages available | Same |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED IMAGING
Table 2 Comparison of uDR Aris's Technology Characteristics to predicate device
| Item | Proposed Device uDR Aris | Reference Device Multix Impact E (VB10) (K233532) | Remark |
| --- | --- | --- | --- |
| General | | | |
| Product Code | KPR | KPR | Same |
| Regulation No. | 892.1680 | 896.1680 | Same |
| Class | II | II | Same |
| Intended Use | Digital Medical X-ray Imaging System is intended to acquire X-ray images of the human body by a qualified technician, examples include acquiring two-dimensional X-ray images of the skull, spinal column, chest, abdomen, extremities, limbs and trunk. The visualization of such anatomical structures provide visual evidence to radiologists and clinicians in making diagnostic decisions. This device is not intended for mammography. | MULTIX Impact E is a radiographic system used in hospitals, clinics, and medical practices. MULTIX Impact E enables radiographic exposures of the whole body including: skull, chest, abdomen, and extremities and may be used on pediatric, adult and obese patients. Exposures may be taken with the patient sitting, standing, or in the prone position. MULTIX Impact E uses digital detectors for generating diagnostic images by converting X- rays into image signals. MULTIX Impact E is also designed to be used with conventional film/screen or | Note 11 |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED
IMAGING
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| Item | Proposed Device
uDR Aris | Reference Device
Multix Impact E (VB10)
(K233532) | Remark |
| --- | --- | --- | --- |
| | | Computed Radiography (CR) cassettes.
MULTIX Impact E is not intended for
mammography. | |
| Specifications | | | |
| High Voltage Generator | | | |
| Max. Power/kW | 40kW | 40kW | Same |
| Max. tube Voltage(kV) | 150kV | 150kV | Same |
| Shortest exposure time | 1ms | 1ms | Same |
| X-Ray Tube | | | |
| Focus Nominal Value | 0.6/1.2 | 0.6/1.2 | Same |
| Maximum peak voltage | 150kV | 150kV | Same |
| Anode Heat Content | 230KHU | 230KHU | Same |
| Anode Target Angle | 12° | 12° | Same |
{16}
K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED
IMAGING
| Item | Proposed Device
uDR Aris | Reference Device
Multix Impact E (VB10)
(K233532) | Remark |
| --- | --- | --- | --- |
| X-ray tube Heat content | 1250KHU | 1350KHU | Note 12 |
| Automatic exposure control (AEC) | Yes | Yes | Same |
| Patient Table | | | |
| Elevating Table | Yes | Yes | Same |
| Patient Weight | 320kg | 300kg | Note 13 |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED IMAGING
Table 3 Comparison of uDR Arria's new features to reference device
| Item | Proposed Device uDR Arria | Reference Device Multix Impact E (VB10) (K233532) | Remark |
| --- | --- | --- | --- |
| uVision Function (optional) | Users can manually adjust FOV and stitching range on the workstation. To assist the users with setting the FOV and stitching range, exam range is automatically planned for chest and stitching range is automatically planned for WholeSpine & WholeLowerExtremity. | - Virtual Collimation Manually adjust collimation size on imaging system by 3D camera - Smart Virtual Ortho: Ortho range set by 2D camera in the image system manually - Auto Thorax Collimation Exam range automatically planned for Thorax by 3D camera with manual adjustment - Auto Full-Spine& Long-Leg Collimation: Ortho range automatically planned for Full-Spine &Long-Leg by 2D camera with manual adjustment | Note 14 |
| uAid | Yes | No | Note 15 |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
www.united-imaging.com
UNITED IMAGING
#
| Patient Table | | | |
| --- | --- | --- | --- |
| Elevating Table | Yes | Yes | Same |
| Patient Weight | 320kg | 300kg | Note 16 |
| Justification | |
| --- | --- |
| Note 1 | Rephrase the sentence only, the meaning remains the same. |
| Note 2 | X-ray tube heat content represents the maximum amount of heat fusion in the limiting state of the tube. The system is configured with corresponding heat dissipation design and power optimisation, so that the tube will not reach its limiting state during clinical use. The difference does not introduce safety and effectiveness issues. |
| Note 3 | The larger image matrix size, and smaller pixel size. The difference does not introduce safety and effectiveness issues. |
| Note 4 | The larger image matrix size, and smaller pixel size. The difference does not introduce safety and effectiveness issues. |
| Note 5 | Effective Radiographic Size refers to the actual area size of the detector panel that can be utilized in practical imaging. A larger Effective Radiographic Size indicates that the detector can cover a larger range of anatomical areas in practical use. The difference does not introduce safety and effectiveness issues. |
| Note 6 | Copper filtration removes lower energy X-ray photons, which do not enhance image quality but would otherwise contribute to patient radiation dose. Compared to the predicate device, the proposed device provides |
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K252000
Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888
Fax: +86 (21) 67076889
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| | an additional 0.3mm copper prefilter option, which not only reduces the radiation dose, but also meets more clinical requirements. The difference does not introduce safety and effectiveness issues. |
| --- | --- |
| Note 7 | Copper filtration removes lower energy X-ray photons, which do not enhance image quality but would otherwise contribute to patient radiation dose. Compared to the predicate device, the proposed device provides an additional 0.3mm copper prefilter option, which not only reduces the radiation dose, but also meets more clinical requirements. The difference does not introduce safety and effectiveness issues. |
| Note 8 | The motorized collimator supports automatically FOV setting via the preset value in organ program, offering users better usability compared to the predicate device. The difference does not introduce safety and effectiveness issues. |
| Note 9 | Under different SID, with the motorized collimator, the lead leaves of the collimator on the proposed device can automatically adjust the aperture size to maintain the FOV the same. The difference does not introduce safety and effectiveness issues. |
| Note 10 | 2D camera only introduced to capture optical information and support more clinical operational possibilities., does not affect safety and effectiveness. |
| Note 11 | Rephrase the sentence only, the meaning remains the same. |
| Note 12 | X-ray tube heat content represents the maximum amount of heat fusion in the limiting state of the tube. The system is configured with corresponding heat dissipation design and power optimisation, so that the tube will not reach its limiting state during clinical use. The difference does not introduce safety and effectiveness issues. |
| Note 13 | Compared to the predicate device, the patient weight has been increased, enabling the system more flexibility and a broader range of patient. The difference does not introduce safety and effectiveness issues. |
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| Note 14 | For manually adjust collimation size and automatically planned for chest and stitching range these two functions are same with predicate device MULTIX Impact E, the difference is the description, the difference does not introduce safety and effectiveness issues. |
| --- | --- |
| Note 15 | uAid evaluates the positioning quality of chest images with deep learning methods. It efficiently and objectively categorizes images into three levels according to four criteria, assist technologist for image acquisition. The difference does not introduce safety and effectiveness issues. |
| Note 16 | Compared to the predicate device, the patient weight has been increased, enabling the system more flexibility and a broader range of patient. The difference does not introduce safety and effectiveness issues. |
# 9. Non-Clinical Test Conclusion
# 9.1 Performance Evaluation
Non clinical tests were conducted to verify that the proposed device met all design specifications as it is Substantially Equivalent (SE) to the predicate device. The test results demonstrated that the proposed device complies with the following standards:
$\succ$ ANSI/AAMI ES 60601-1:2005 & A1:2012 & A2:2021 Medical electrical equipment - Part 1: General requirements for basic safety and essential performance.
IEC 60601-1-2:2014+A1:2020 Medical electrical equipment - Part 1-2: General requirements for basic safety and essential performance - Collateral standard: Electromagnetic disturbances - Requirements and tests.
IEC 60601-1-3:2008+A1:2013+A2:2021 Medical electrical equipment - Part 1-3: General requirements for basic safety and essential performance - Collateral standard: Radiation protection in diagnostic X-ray equipment.
IEC 60601-2-54:2022 Medical electrical equipment - Part 2-54: Particular requirements for the basic safety and essential performance of X-ray equipment for radiography and radioscopy.
IEC 60601-2-28:2017 Medical electrical equipment - Part 2-28: Particular requirements for the basic safety and essential performance of X-ray tube assemblies for medical diagnosis
Additional non-clinical tests are conducted for key features to ensure safe and effectiveness when integrated into the system:
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| Feature | Bench Testing Performed |
| --- | --- |
| uVision | Introduction The uVision algorithm in the digital medical X-ray imaging system (uDR Arria) aims to optimize the radiographic scanning workflow through patient positioning recognition technology. This algorithm utilizes cameras to capture natural images of the human body, achieving multi-modal real-time automatic localization of key anatomical points, body modeling, and pose estimation for patients. It provides the system with scanning positions, ranges, and generates motion trajectory plans for DR racks. Acceptance Criteria As an auxiliary function designed to enhance clinical workflow efficiency, uVision is expected to assist users in completing pre-exposure positioning tasks. In the context of chest X-ray imaging, the retake rate due to incorrect positioning is a critical quality control metric. According to relevant studies and literature, incorrect positioning is one of the primary causes of retakes. By a 5-month-long observation experiment, positioning error results in approximately 9% rejection in DR. Furthermore, some literature indicates that positioning errors contribute to 28% of rejections. The specific figures may vary depending on the healthcare institution, equipment type, and technician experience. Considering the impact of camera specifications and gantry control accuracy on the application of uAI vision algorithm to DR equipment, we expect that when users employ the uVision function for automatic positioning, the automatically set system position and field size will meet clinical technicians' criteria with 95% compliance, thereby demonstrating that uVision can effectively assist clinical technicians in positioning tasks. Testing Data Information The device with uVision function has been tested, with equipment serial number 11XT7E0001. Since the installation and commissioning over a year ago, the average daily imaging volume on the device has been around 80 patients, with approximately 45 chest X-rays per day and about 10 to 20 stitching cases per week. After receiving specialized training prior to use, the technicians operating this equipment utilize the uVision function to set the FOV and system position when conducting chest PA, whole-spine, and whole-lower-limb stitching exams. |
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The results automatically set by the system are then statistically analyzed by clinical experts .
Testing data includes individuals of all genders and varying heights (capable of standing independently)
| Height (m) | ≤1.25 | 1.25~1.5 | 1.5~1.75 | ≥1.75 |
| --- | --- | --- | --- | --- |
| Percentage | 3% | 7% | 58% | 32% |
Table presents the evaluation results of the imaging positioning sampled randomly over a period since the equipment was put into use.
Table . The evaluation results of uVision automatically system positioning and FOV setting for chest PA、WholeSpine and WholeLowerExtremity
| Date | Chest/case | Case of Non-Compliant Cases in System-Automatically Set Results | Full Spine or Full Lower Limb Stitching/case | Case of Non-Compliant Cases in System-Automatically Set Results |
| --- | --- | --- | --- | --- |
| 2024.12.17 | 62 | 3 | 2 | 0 |
| 2024.12.18 | 44 | 3 | 2 | 0 |
| 2024.12.19. | 35 | 2 | 5 | 0 |
| 2024.12.20 | 18 | 1 | 5 | 0 |
| 2024.12.21 | 59 | 2 | 2 | 0 |
| 2024.12.22 | 47 | 1 | 1 | 0 |
| 2024.12.23 | 63 | 2 | 3 | 0 |
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| | Total number of cases in a week | 328 | 14 | 20 | 0 | |
| --- | --- | --- | --- | --- | --- | --- |
| | Equipment and Protocols The test data was collected from hospital, and the testing protocol included chest, Whole-spine stitching, Whole-Lower-extremity stitching. Clinical Subgroups No clinical subgroups and confounders have been defined for the datasets. Testing & Training Data Independence The testing dataset was collected independently from the training dataset, with separated subjects and during different time periods. Therefore, the testing data is entirely independent and does not share any overlap with the training data. Summary According to the results of the current equipment statistics, in 95% of patient positioning processes, the light field and equipment position automatically set by uVision can meet the clinical positioning and shooting requirements. In the remaining 5% of cases, based on the light field and system position automatically set by the equipment, technicians still need to make manual adjustments | | | | | |
| uAid | Introduction uAid is used for checking the quality of examination and positioning. The results can help to assist with departmental management functions. uAid is triggered after the acquisition of chest X-ray images in patients aged over 20 years, which automatically evaluates image characteristics against four criteria, namely whether there is a foreign object, whether the lung field is complete, whether the scapula is open, and whether the spine is located on the center line, categorizing images into one of three quality levels. The outcome of the evaluation is instantly accessible to radiologic technologists, reminding them to verify that the image meets the image quality control. It bears emphasis that the result of image quality control is for reference only and cannot be used as the basis for clinical diagnosis. Acceptance Criteria uAid is designed to provide an objective image evaluation method, offering hospitals a unified assessment tool to manage images/technicians. The accuracy of non-standard image | | | | | |
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recognition is a key quality control metric. According to relevant research and literature, the rate of Grade A clinical images is typically influenced by factors such as the technician's operational standardization, equipment performance, and quality control processes, with variations observed across different levels of medical institutions and equipment types. Mature industry guidelines and standards, such as those from European Radiology and the ACR-AAPM-SPR Practice Parameter, indicate that the Grade A image rate in public hospitals generally ranges between 80% and 90%. To ensure uAid's functionality meets clinical requirements, we referenced these guidelines and set a 90% pass rate, aligning with industry standards. This demonstrates that uAid can effectively assist clinical technicians in managing standardized image quality.
# Testing Data Information
The data collection started in October 2017, with a wide range of data sources. Some of the data come from different cooperative hospitals. After multiple cleaning and sorting, the data is stored in DICOM format. The study was approved by the institutional review board of the hospitals.
It does not include data on DR-sensitive groups such as infants and young children, and is only applicable to frontal chest images.
Age and gender distribution of data sets for uAid:
| Age | Male | Female |
| --- | --- | --- |
| 20-29 | 310 | 698 |
| 30-39 | 308 | 744 |
| 40-49 | 298 | 798 |
| 50-59 | 385 | 801 |
| 60-69 | 320 | 799 |
| 70-79 | 200 | 472 |
| 80-89 | 97 | 210 |
| 90-99 | 21 | 46 |
| No Age | 97 | 187 |
| No Age, No Gender | 45 | |
Distribution of negative and positive data for uAid:
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| | Negative | Positive |
| --- | --- | --- |
| lung field segmentation | 465 | 31 |
| Spinal centerline segmentation | 815 | 68 |
| Shoulder blades segmentation | 210 | 1089 |
| Foreign object | 1078 | 3080 |
**Equipment and Protocols:**
The data collection started in October 2017 on the uDR 780i, with a wide range of data sources. Some of the data come from different cooperative hospitals.
**Clinical Subgroups:**
No clinical subgroups and confounders have been defined for the datasets.
**Testing & Training Data Independence**
The testing dataset was collected independently from the training dataset, with separated subjects and during different time periods. Therefore, the testing data is entirely independent and does not share any overlap with the training data.
**Summary:**
Test dataset analysis results are summarized as below:
1. The average time of the uAid algorithm is 1.359 seconds, and the longest does not exceed 2 seconds;
2. The maximum memory occupation of uAid algorithm is not more than 2G;
3. For uAid, the sensitivity and specificity of whether there is a foreign body, whether the lung field is intact, and whether the scapula is open all exceed 0.9;
The uAid function can correctly identify four types of results: Foreign object, Incomplete lung fields, Unexposed shoulder blades, and Centerline deviation and make classification after the exposure image is generated: Green (qualified image), yellow (secondary image), red (waste image).
uAid can meet the requirement which is used for checking the quality of examination and position for institutions. The results can assist the image quality assessment with departmental management functions.
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## 9.2 Clinical Image Evaluation
The clinical image evaluation was performed under the proposed device. Sample images of chest, abdomen, spine, pelvis, upper extremity and lower extremity were provided with a board certified radiologist to evaluate the image quality in this submission. Each image was reviewed with a statement indicating that image quality is sufficient for clinical diagnosis.
## 10. Substantially Equivalent (SE) Conclusion
Based on the comparison and analysis above, the technology characteristics of the modified uDR Arria, uDR Aris reflected in this 510(k) submission, do not alter the scientific technology of the devices and are substantially equivalent to those of the predicate devices.
In accordance with the Federal Food, Drug and Cosmetic Act, 21 CFR Part 807 and based on the information provided in this premarket notification, we conclude that the uDR Arria, uDR Aris Stationary X-Ray Systems are substantially equivalent to the predicate devices. It does not introduce new indications for use, and has the same technological characteristics and does not introduce new potential hazards or safety risks.
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Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.