uDR Aurora CX 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 Description

uDR Aurora CX is a model of Digital Medical X-ray Imaging System developed and manufactured by Shanghai United Imaging Healthcare Co., Ltd(UIH). It includes X-ray Generator, X-ray Imaging System. The X-ray Generator produces controlled X-rays by high-voltage generator and X-ray tube assembly, ensuring stable energy output for human body penetration. The X-ray Imaging System converts X-ray photons into electrical signals by detectors, and generates DICOM-standard images by workstation to reflecting density variations of human body.

AI/ML Overview

This document describes the acceptance criteria and study details for two features of the uDR Aurora CX device: uVision and uAid.

1. Acceptance Criteria and Reported Device Performance

Feature	Acceptance Criteria	Reported Device Performance
uVision	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. This demonstrates that uVision can effectively assist clinical technicians in positioning tasks, specifically by aiming to reduce retake rates attributed to incorrect positioning (which studies indicate can range from 9% to 28%).	In 95% of patient positioning processes, the light field and equipment position automatically set by uVision met clinical positioning and shooting requirements for chest PA, whole-spine, and whole-lower-limb stitching exams. In the remaining 5% of cases, manual adjustments by technicians were needed.
uAid	The accuracy of non-standard image recognition (specifically, the rate of "Grade A" images recognized) should meet a 90% pass rate, aligning with industry standards derived from guidelines like those from European Radiology and ACR-AAPM-SPR Practice Parameter (which indicate Grade A image rates between 80% and 90% in public hospitals). This demonstrates that uAid can effectively assist clinical technicians in managing standardized image quality.	Overall Performance: The uAid function can correctly identify four types of results (Foreign object, Incomplete lung fields, Unexposed shoulder blades, and Centerline deviation) and classify images into Green (qualified), Yellow (secondary), or Red (waste). It meets the requirement for checking examination and positioning quality.
		Specific Metric/Quantitative Performance (from "Summary"):- Average algorithm time: 1.359 seconds (longest not exceeding 2 seconds).- Maximum memory occupation: Not more than 2G.- For foreign body, lung field integrity, and scapula opening, both sensitivity and specificity for recognition exceed 0.9.

2. Sample Size and Data Provenance for the Test Set

Feature	Sample Size for Test Set	Data Provenance
uVision	348 cases (328 Chest PA cases + 20 Full Spine or Full Lower Limb Stitching cases) collected over one week from 2024.12.17 to 2024.12.23. The device had been installed for over a year, with an average daily volume of ~80 patients, ~45 chest X-rays/day, and ~10-20 stitching cases/week.	Prospective/Retrospective Hybrid: The data was collected prospectively from a device (serial number 11XT7E0001) in clinical use after installation and commissioning over a year prior to the reported test period. It was collected from individuals of all genders and varying heights (able to stand independently). The testing was conducted in a real-world clinical setting. Country of Origin: Not explicitly stated, but the company is in Shanghai, China, suggesting the data is likely from China.
uAid	Not explicitly stated as a single total number of cases. Instead, the data distribution is provided, indicating various counts for different conditions across gender and age groups. For example, "lung field segmentation" had 465 negative and 31 positive cases. "Foreign object" had 1078 negative and 3080 positive cases. The sum of these individual counts suggests a total dataset of several thousand images.	Retrospective: Data collection for uAid started in October 2017, with a wide range of data sources, including different cooperative hospitals. The data was cleaned and stored in DICOM format. Country of Origin: Not explicitly stated, but the company is in Shanghai, China, suggesting the data is likely from China.

3. Number and Qualifications of Experts for Ground Truth (Test Set)

Feature	Number of Experts	Qualifications of Experts
uVision	Not explicitly stated. The statement says, "The results automatically set by the system are then statistically analyzed by clinical experts."	"Clinical experts." No specific qualifications (e.g., years of experience, specialty) are provided.
uAid	Not explicitly stated. The document mentions "The study was approved by the institutional review board of the hospitals," which implies expert review but does not detail the number or roles of experts in establishing the ground truth labels for the specific image characteristics tested.	Not explicitly stated for establishing ground truth labels.

4. Adjudication Method (Test Set)

Feature	Adjudication Method
uVision	Not explicitly stated. The data was "statistically analyzed by clinical experts." It does not specify if multiple experts reviewed cases or how disagreements were resolved.
uAid	Not explicitly stated. The process mentions data cleaning and sorting, and IRB approval, but not the specific adjudication method for individual image labels.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

uVision: No MRMC comparative effectiveness study was done to compare human readers with and without AI assistance. The study evaluates the AI's direct assistance in positioning, measured by compliance with clinical criteria, rather than comparing diagnostic performance of human readers.
uAid: No MRMC comparative effectiveness study was done. The study focuses on the standalone performance of the algorithm in identifying image quality issues, not on how it impacts human reader diagnostic accuracy or efficiency.

6. Standalone Performance (Algorithm Only)

uVision: Yes, a standalone performance study was done. The "95% compliance" rate refers to the algorithm's direct ability to set system position and FOV that meet clinical technician criteria without a human actively adjusting or guiding the initial AI-generated settings during the compliance evaluation. Technicians could manually adjust those settings if needed.
uAid: Yes, a standalone performance study was done. The algorithm processes images and outputs a quality classification (Green, Yellow, Red) and identifies specific issues (foreign object, incomplete lung fields, etc.). Its sensitivity and specificity metrics are standalone performance indicators.

7. Type of Ground Truth Used

uVision: Expert Consensus/Clinical Criteria: The ground truth for uVision's performance (i.e., whether the automatically set position/FOV was "compliant") was established by "clinical experts" based on "clinical technicians' criteria" for proper positioning and shooting requirements.
uAid: Expert Consensus/Manual Labeling: The ground truth for uAid's evaluation (e.g., presence of foreign objects, complete lung fields, open scapula, centerline deviation) was established through a "classification" process, implying manual labeling or consensus by experts after data collection and cleaning. The document mentions "negative" and "positive" data distributions for each criterion.

8. Sample Size for the Training Set

uVision: Not explicitly stated in the provided text. The testing data was confirmed to be "collected independently from the training dataset, with separated subjects and during different time periods."
uAid: Not explicitly stated in the provided text. The document mentions "The data collection started in October 2017, with a wide range of data sources" for training, but does not provide specific numbers for the training set size.

9. How Ground Truth for Training Set was Established

uVision: Not explicitly stated for the training set. It can be inferred that a similar process to the test set, involving expert review against clinical criteria, would have been used.
uAid: Not explicitly stated for the training set. Given that the data was collected from "different cooperative hospitals," "multiple cleaning and sorting" was performed, and the study was "approved by the institutional review board," it is highly likely that the ground truth for the training set involved manual labeling by clinical experts/radiologists, followed by a review process (potentially consensus-based or single-expert) to establish the labels for image characteristics and quality.

Summary

FDA 510(k) Clearance Letter - uDR Aurora CX

Page 1

U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov

Doc ID # 04017.08.00

September 19, 2025

Shanghai United Imaging Healthcare Co., Ltd.
℅ Xin Gao
Regulatory Affairs Manager
No.2258 Chengbei Rd. Jiading District
SHANGHAI, 201807
CHINA

Re: K251167
Trade/Device Name: uDR Aurora CX
Regulation Number: 21 CFR 892.1680
Regulation Name: Stationary X-Ray System
Regulatory Class: Class II
Product Code: KPR
Dated: April 15, 2025
Received: August 19, 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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K251167 - Xin Gao Page 2

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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K251167 - Xin Gao Page 3

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

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

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): K251167
Device Name: uDR Aurora CX

Indications for Use (Describe)

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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Shanghai United Imaging Healthcare Co., Ltd.
Tel: +86 (21) 67076888 Fax：+86 (21) 67076889
www.united-imaging.com

K251167

510 (k) SUMMARY

1. Date of Preparation:

April 15, 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 Aurora CX
Common Name: Digital Medical X-ray Imaging System
Model(s): uDR Aurora CX

Regulatory Information

Classification Name: Stationary X-Ray System
Device Classification: II
Product Code: KPR
Regulation Number: 21 CFR 892. 1680
Review Panel: Radiology

5. Identification of Predicate Device(s)

Predicate Device:

Trade Name： uDR 780i
510(k) Number: K241068
Classification Name: Stationary X-Ray System
Classification Panel: Radiology
Regulation Number: 21 CFR 892. 1680
Classification: II
Product Code: KPR

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Reference Device：

Trade Name: MULTIX Impact C
510(k) Number: K213700
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:

7. Intended Use Statement:

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8. Substantially Equivalent (SE) Comparison

A comparison between the technological characteristics of proposed and predicate devices is provided as below.

Table 1 Comparison of Technology Characteristics to predicate device

Item	Proposed Device uDR Aurora CX	Predicate Device uDR 780i (K241068)	Remark
General
Product Code	KPR	KPR	Same
Regulation No.	892.1680	896.1680	Same
Class	II	II	Same
Intended Use	uDR Aurora CX 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 780i Digital Medical X-ray system is intended for 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, and other anatomic sites. Applications can be performed with the subject sitting, standing, or lying in the prone or supine position. Not for mammography.	Note1
Specifications

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Item	Proposed Device uDR Aurora CX	Predicate Device uDR 780i (K241068)	Remark
High Voltage Generator
Max. Power/kW	65kW/80kW	65kW/80kW	Same
Max. tube Voltage(kV)	150kV	150kV	Same
Shortest exposure time	1ms	1ms	Same
X-Ray Tube Assemble
Focus Nominal Value	0.6/1.2	0.6/1.2	Same
Maximum peak voltage	150kV	150kV	Same
Anode Heat Content	65kw: ≥300kHU80kw: ≥400kHU	65kw: ≥300kHU80kw: ≥400kHU	Same
Anode Target Angle	12°	12°	Same
X-ray tube assembly Heat content	65kw: ≥1250KHU	65kw: ≥1250KHU	Same

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Item	Proposed Device uDR Aurora CX	Predicate Device uDR 780i (K241068)	Remark
	80kw: ≥1500KHU	80kw: ≥1500KHU
Flat Panel Detector-Config.1
Model	uFPD1717-100	AR-C4343W
Power	Battery or DC operated	Battery or DC operated	Same
Scintillator	Cesium iodide (CsI)	Cesium iodide (CsI)	Same
Image Matrix Size	4267x4267100 μm	3320x3408125μm	Note2
Effective radiographic size	42.67cm x 42.67cm	41.5cm x 42.6cm	Note 3
Flat Panel Detector-Config.2
Model	uFPD1417-100	AR-C4343W
Power	Battery or DC operated	Battery or DC operated	Same
Scintillator	Cesium iodide (CsI)	Cesium iodide (CsI)	Same
Image Matrix Size	3500x4300	3320x3408	Note 4

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Item	Proposed Device uDR Aurora CX	Predicate Device uDR 780i (K241068)	Remark
	100 μm	125μm
Effective Radiographic Size	35cm x 43cm	41.5cm x 42.6cm	Note 5
Collimator
Inherent filtration	1mm Al	1mm Al	Same
Copper prefilter	without filter,0.1 mm,0.2 mm,0.3 mm;	without filter,0.1 mm,0.2 mm,0.3 mm;	Same
Bulit-in camera	Live 2D Camera for patient positioning and collimation	N/A	Note 6
Elevating table
Motorized vertical travel	≥38.2cm	≥38.2cm	Same
Max. patient weight	320kg	320kg	Same

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Item	Proposed Device uDR Aurora CX	Predicate Device uDR 780i (K241068)	Remark
Detector travel range	≥90cm	≥67cm	Note 7
Auto tracking for adjusting the table height is maintained	Yes, X-ray tube follows table height adjustment; source-image distance is maintained.	Yes, X-ray tube follows table height adjustment; source-image distance is maintained.	Same
Auto tracking for longitudinal tube travel	Yes, detector follows tube movement; centering maintained.	Yes, detector follows tube movement; centering maintained.	Same
Auto tracking for tube rotation	Yes, detector follows tube movement; centering maintained.	Yes, detector follows tube movement; centering maintained.	Same
Software function
uAid	Yes	No	Note8
Stitching	Yes	Yes	Same
AEC	Yes	Yes	Same
Safety

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Item	Proposed Device uDR Aurora CX	Predicate Device uDR 780i (K241068)	Remark
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
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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Table2: Comparison of new features to predicate device

Item	Proposed Device uDR Aurora CX	Reference Device MULTIX Impact C(K213700)	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 CollimationManually 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 CollimationExam 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 9

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Justification

Note	Description
Note 1	Minor grammatical changes only.
Note 2	The larger the image matrix size, the higher the resolution, and the greater the capability to capture fine structures, which means the ability to identify smaller lesions and tissues. The difference does not introduce safety and effectiveness issues.
Note 3	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 4	The larger the image matrix size, the higher the resolution, and the greater the capability to capture fine structures, which means the ability to identify smaller lesions and tissues. The difference does not introduce safety and effectiveness issues.
Note 5	Only the different of size specification, does not affect safety and effectiveness. The 35cm x 43cm normally used in free exam mode which is different with 41.5cm x 42.6cm which used in the tray in table.
Note 6	2D camera only introduced to capture optical information and support more clinical operational possibilities., does not affect safety and effectiveness.
Note 7	Detector travel range refers to the movement range of the tray in Table. A larger travel range indicates a larger coverage on table and more operational possibilities. The difference does not introduce safety and effectiveness issues.

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Note	Description
Note 8	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, to assist standardizing the management of image quality/technologist skills. The difference does not introduce safety and effectiveness issues.
Note 9	For manually adjust collimation size and automatically planned for chest and stitching range these two functions are same with predicate device MULTIX Impact C, the difference is the description way, 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:

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:

Feature	Bench Testing Performed
uVision	Introduction

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The uVision algorithm in the digital medical X-ray imaging system (uDR Aurora CX) 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 installed 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
2024.12.17	62	3	2
2024.12.18	44	3	2
2024.12.19.	35	2	5
2024.12.20	18	1	5
2024.12.21	59	2	2
2024.12.22	47	1	1
2024.12.23	63	2	3

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| Total number of cases in a week | 328 | 14 | 20 | 0 |

Equipment and Protocols

The test data was collected, 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

Summary：

Test dataset analysis results are summarized as below:

The average time of the uAid algorithm is 1.359 seconds, and the longest does not exceed 2 seconds;
The maximum memory occupation of uAid algorithm is not more than 2G;
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 Aurora CX, 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 Aurora CX 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.

Regulation Number and Section

§ 892.1680 Stationary x-ray system.

(a)
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.(b)
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.