(63 days)
SDX-4343CS Digital Flat Panel X-Ray Detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy for adults and pediatric care. It is intended to replace film based radiographic diagnostic systems and provide a case diagnosis and treatment planning for physicians and other health care professionals who are licensed by the law of the State in which he or she practices to use the device. Not to be used for mammography.
SDX-4343CS digital X-ray flat panel detectors can generate radiographic images of any part of the body. Each of them consists of a scintillator directly coupled to an a-SI TFT sensor. It makes high-resolution, high-sensitive digital images. SDX-4343CS is designed specifically to be integrated with an operating PC and a X-Ray generator to digitalize x-ray images into RAW files. The RAW files can be made to DICOM compatible image files for a radiographic diagnosis and analysis by the user's designated console software which is not included in SDX-4343CS, digital flat panel X-ray detector.
The provided text is a 510(k) Special Submission for a Digital Flat Panel X-Ray Detector (SDX-4343CS). This submission focuses on establishing substantial equivalence to a predicate device and includes information on the device's description, intended use, and safety/performance testing.
However, the document does not contain the detailed acceptance criteria or a study proving the device meets those criteria, particularly in the context of advanced AI/CAD system testing. The text describes a standard medical device submission process for an imaging hardware component, not an AI-powered diagnostic tool.
Therefore, many of the requested details, such as sample sizes for test sets, data provenance, number and qualifications of experts, adjudication methods, MRMC studies, standalone algorithm performance, and training set information (which are common for AI/CAD device submissions), are not present in this document.
The document mainly focuses on proving the safety and effectiveness of the hardware and its substantial equivalence to a previously cleared predicate device based on electrical, mechanical, environmental safety, and EMC testing.
Based on the provided information, here's what can be extracted and what is missing:
1. Table of Acceptance Criteria and Reported Device Performance
Not explicitly present in the provided text. The document states that "Electrical, mechanical, environmental safety and performance testing according to standard ENVIEC 60601-1 was performed, and EMC testing was conducted in accordance with standard ENVIEC 60601-1-2(2001). All test results were satisfactory." This indicates that the device met the requirements of these general safety and performance standards for X-ray equipment, but specific numerical acceptance criteria (e.g., MTF, DQE, SNR, etc., which are common for imaging detectors) and their corresponding measured performance are not detailed in this summary.
2. Sample Size Used for the Test Set and Data Provenance
Not applicable/Not mentioned. This submission is for an X-ray detector hardware, not an AI algorithm that processes images. Therefore, 'test sets' in the context of diagnostic performance on patient data are not relevant here. The testing mentioned (EN/IEC standards) would involve engineering and performance tests on the device itself, not a clinical study on patient images.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
Not applicable/Not mentioned. As this is for hardware performance, the concept of "ground truth" established by clinical experts on patient images is not relevant to this submission summary.
4. Adjudication Method for the Test Set
Not applicable/Not mentioned.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
No. This is not an AI/CAD device. Therefore, no MRMC study of human readers with/without AI assistance was performed or reported here.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was Done
No. This is not an AI/CAD device.
7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)
Not applicable/Not mentioned. For the hardware performance tests (EN/IEC standards), ground truth would refer to quantifiable physical measurements and adherence to specified tolerances, not clinical diagnostic ground truth.
8. The Sample Size for the Training Set
Not applicable/Not mentioned. This is not an AI/CAD device; thus, there is no "training set" of data for an algorithm.
9. How the Ground Truth for the Training Set was Established
Not applicable/Not mentioned.
§ 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.