(179 days)
The Wireless and Wired Yushan X-Ray Flat Panel Detector is intended to capture for display radiographic images of human anatomy. It is intended for use in general projection radiographic applications wherever conventional film/screen or CR systems may be used. The Yushan X-Ray Flat Panel Detector is not intended for mammography, fluoroscopy, tomography, and angiography applications. The use of this product is not recommended for pregnant women and the risk of radioactivity must be evaluated by a physician.
The Subject Device Yushan X-Ray Flat Panel Detector is static digital x-ray detector, model V14C PLUS, F14C PLUS, V17C PLUS are portable (wireless/ wired) detectors, while V17Ce PLUS is a non-portable (wired) detector. The Subject Device is equivalent to it's predicate device K243171, K201528, K210988, and K220510.
The Subject Device is designed to be used in any environment that would typically use a radiographic cassette for examinations. Detectors can be placed in a wall bucky for upright exams, a table bucky for recumbent exams, or removed from the bucky for non-grid or free cassette exams. The Subject Device has memory exposure mode, and extended image readout feature. Additionally, rounded-edge design for easy handling, image compression algorithm for faster image transfer, LED design for easy detector identification, extra protection against ingress of water.The Detector is currently indicated for general projection radiographic applications and the scintillator material is cesium iodide (CsI).
The Subject Device can automatically collect x-ray images from an x-ray source. It collects x-rays and digitizes the images for their transfer and display to a computer. The x-ray generator (an integral part of a fully-functional diagnostic system) is not part of the device. The sensor includes a flat panel for x-ray acquisition and digitization and a computer (including proprietary processing software) for processing, annotating and storing x-ray images.
The Subject Device is working by using DROC (Digital Radiography Operating Console), Xresta or DR console, which are unchanged from the predicate device, cleared under K201528 for DROC and K243171 for Xresta and DR console. The DROC or Xresta is a software running on a Windows PC/Laptop as a user interface for radiologist to perform a general radiography exam. The function includes:
- Detector status update
- Xray exposure workflow
- Image viewer and measurement
- Post image process and DICOM file I/O
- Image database: DROC or Xresta supports the necessary DICOM Services to allow a smooth integration into the clinical network
The DR Console is a software/app-based device, which is a software itself. When this app is operating the OTS can be considered as the iOS system (iOS 16 or above), the safety and effectiveness of this OTS has been assessed and evaluated through the software testing (compatibility) action and also the usability test (summative evaluation). All the functions operate normally and successfully under this OTS framework. The function includes:
- Imaging procedure review
- Worklist settings
- Detector connection settings
- Calibration
- Image processing
The software level of concern for the Yushan X-Ray Flat Panel Detector with DROC, Xresta, or DR Console has been determined to be basic based on the "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices"; and the cybersecurity risks of the Yushan X-Ray Flat Panel Detector with DROC, Xresta, or DR Console have also been addressed to assure that no new or increased cybersecurity risks were introduced as a part of device risk analysis. These risks are defined as sequence of events leading to a hazardous situation, and the controls for these risks were treated and implemented as proposed in the risk analysis (e.g., requirements, verification).
Acceptance Criteria and Study for Yushan X-Ray Flat Panel Detector (K250211)
This documentation describes the acceptance criteria and the study conducted for the Yushan X-Ray Flat Panel Detector (models V14C PLUS, F14C PLUS, V17C PLUS, V17Ce PLUS). The device has received 510(k) clearance (K250211) based on substantial equivalence to predicate devices (K243171, K201528, K210988, K220510).
The primary change in the subject device compared to its predicates is an increase in the CsI scintillator thickness from 400µm (in some predicate CsI models) to 600µm. This change impacts image quality metrics but, according to the manufacturer, does not introduce new safety or effectiveness concerns.
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria for this device are implicitly tied to demonstrating that the changes in scintillator thickness do not negatively impact safety or effectiveness, and ideally, improve image quality. The primary performance metrics affected by the scintillator change are DQE, MTF, and Sensitivity.
| Performance Metric | Acceptance Criteria (Implicit: No degradation in clinical utility compared to predicate, ideally improvement) | Reported Device Performance (Subject Device - 600µm CsI) | Predicate Device (CsI Models - 400µm CsI) Performance |
|---|---|---|---|
| DQE (Detective Quantum Efficiency) @ 1 lp/mm, RQA5 | Maintain or improve upon predicate's CsI DQE value. | 0.60 (Typical) | 0.48 - 0.50 |
| DQE (Detective Quantum Efficiency) @ 2 lp/mm | (Not explicitly stated for acceptance, but shown for performance) | 0.45 (Typical) | Not explicitly listed for predicate |
| MTF (Modulation Transfer Function) @ 1 lp/mm, RQA5 | Maintain comparable MTF to predicate's CsI MTF (acknowledging potential trade-offs for improved DQE). | 0.64 (Typical) | 0.63 - 0.69 |
| MTF (Modulation Transfer Function) @ 2 lp/mm | (Not explicitly stated for acceptance, but shown for performance) | 0.34 (Typical) | Not explicitly listed for predicate |
| Sensitivity | (Not explicitly stated for acceptance, but shown for performance) | 715 lsb/uGy | Not explicitly listed for predicate |
| Noise Performance | Superior noise performance compared to predicate. | Superior noise performance | Inferior to subject device |
| Image Smoothness | Smoother image quality compared to predicate. | Smoother image quality | Inferior to subject device |
| Compliance with Standards | Conformance to relevant safety and performance standards (e.g., IEC 60601 series, ISO 10993). | All specified standards met. | All specified standards met. |
| Basic Software Level of Concern | Maintained as basic. | Level of concern remains basic. | Level of concern remains basic. |
| Cybersecurity Risks | No new or increased cybersecurity risks introduced. | Risks addressed, no new or increased risks. | Risks addressed. |
| Load-Bearing Characteristics | Pass specified tests. | Passed. | Passed. |
| Protection against ingress of water | Pass specified tests. | Passed. | Passed. |
| Biocompatibility | Demonstrated through ISO 10993 series. | Demonstrated. | Demonstrated. |
Summary of Device Performance vs. Acceptance:
The subject device demonstrates improved DQE, superior noise performance, and smoother images compared to the predicate device (specifically, CsI models), while maintaining comparable MTF and meeting all other safety and performance standards. The slight reduction in MTF compared to the highest performing predicate CsI model (0.69 vs 0.64 at 1 lp/mm) is likely considered an acceptable trade-off given the improvements in DQE and noise, and it is still significantly higher than GOS models.
2. Sample Size Used for the Test Set and Data Provenance
The document does not explicitly state the numerical sample size for the test set used for the performance evaluation of the image quality metrics (DQE, MTF, Sensitivity, noise, smoothness). These metrics are typically derived from physical measurements on a controlled test setup rather than a clinical image dataset.
Data Provenance: Not explicitly stated regarding country of origin or retrospective/prospective nature. However, the evaluation results for image quality metrics, noise, and smoothness are generated internally by the manufacturer during design verification and validation activities.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
Not applicable. The ground truth for DQE, MTF, and Sensitivity measurements is established through standardized physical phantom measurements (e.g., using RQA5 beam quality) rather than expert consensus on clinical images. These are quantifiable engineering parameters.
4. Adjudication Method for the Test Set
Not applicable. The evaluation of DQE, MTF, and Sensitivity is based on objective instrumental measurements, not on reader interpretations or consensus methods.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or performed as part of this 510(k) submission. The submission focuses on demonstrating substantial equivalence based on technical specifications and physical performance measurements rather than a clinical trial assessing reader performance.
6. Standalone Performance Study
Yes, a standalone performance evaluation was conducted for the device. The reported DQE, MTF, and Sensitivity values, as well as the assessments of noise performance and image smoothness, are measures of the algorithm's (and the underlying detector hardware's) intrinsic performance without human-in-the-loop assistance. The comparison of these metrics between the subject device and the predicate device forms the basis of the standalone performance study.
7. Type of Ground Truth Used
The ground truth used for the performance evaluations (DQE, MTF, Sensitivity, noise, smoothness) is based on objective physical measurements and standardized phantom evaluations. These are quantitative technical specifications derived under controlled laboratory conditions, not expert consensus on pathology, clinical outcomes, or interpretations of patient images.
8. Sample Size for the Training Set
Not applicable. This device is an X-ray flat panel detector, a hardware component that captures images. While it includes embedded software (firmware, image processing algorithms), the document does not indicate that these algorithms rely on a "training set" in the context of machine learning. The image processing algorithms are likely deterministic or parameter-tuned, not learned from a large dataset like an AI model for diagnosis.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no indication of a machine learning "training set" as described in the context of AI models. The ground truth for the development and validation of the detector's physical performance characteristics is established through established metrology and engineering testing protocols.
§ 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.