(99 days)
1417PCA Digital Flat Panel X-Ray Detector is indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to replace film or screen based radiographic systems in all general purpose diagnostic procedures. Not to be used for mammography.
1417PCA is a portable digital X-ray flat panel detector that can generate images of any part of the body. This X-ray imaging system consists of a scintillator directly coupled to an a-Si TFT sensor. It makes high-resolution, high-sensitive digital images. 1417PCA 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 console SW.
The provided 510(k) summary describes the Rayence Co., Ltd. 1417PCA Digital Flat Panel X-ray Detector and its substantial equivalence to a predicate device. The information below is extracted and organized as requested.
Acceptance Criteria and Device Performance
The acceptance criteria for the 1417PCA device are established through comparison with the predicate device, SDX-4336CP, primarily focusing on superior or equivalent performance in key imaging metrics.
Table 1: Acceptance Criteria and Reported Device Performance
| Performance Metric | Acceptance Criteria (Relative to Predicate SDX-4336CP) | Reported Device Performance (1417PCA) |
|---|---|---|
| MTF (Modulation Transfer Function) | Better than SDX-4336CP | Performed better than SDX-4336CP |
| DQE (Detective Quantum Efficiency) | Better than SDX-4336CP | Demonstrated better DQE performance (e.g., 55% at lowest spatial frequency vs. 52% for SDX-4336CP) |
| NPS (Noise Power Spectrum) | Lower performance (implies reduced noise) | Exhibited NPS with lower performance (implies reduced noise) |
| Image Quality (Overall) | Equivalent or better diagnostic image quality | Claimed equivalent or better diagnostic image quality |
Study Information
2. Sample Size Used for the Test Set and Data Provenance:
The document states that "clinical images are taken from both devices." However, it does not specify the sample size for the test set (number of images or patients).
The data provenance is not explicitly stated regarding country of origin or whether it was retrospective or prospective.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:
The test set images were "reviewed by a licensed US radiologist to render an expert opinion." This indicates that one licensed US radiologist was used. The specific qualifications (e.g., years of experience, subspecialty) are not provided beyond being a "licensed US radiologist."
4. Adjudication Method for the Test Set:
The document mentions a single "licensed US radiologist" reviewing images and rendering an "expert opinion." This implies no formal adjudication method (e.g., 2+1, 3+1) was used, as it appears to be a solitary review.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
The document does not describe an MRMC comparative effectiveness study involving multiple readers and comparing performance with and without AI assistance to quantify an effect size. The clinical evaluation involved one radiologist comparing images from the proposed and predicate devices.
6. Standalone (Algorithm Only) Performance:
The device is a digital X-ray flat panel detector, not an AI algorithm. The performance evaluation is for the hardware's ability to acquire images. Therefore, the concept of "standalone (algorithm only without human-in-the-loop performance)" is not applicable in the context of this device. The performance metrics like MTF, DQE, and NPS are intrinsic to the detector hardware.
7. Type of Ground Truth Used:
The ground truth for the clinical comparison was established by the expert opinion of a licensed US radiologist after reviewing clinical images from both devices. The images were evaluated based on age group and anatomical structures according to a diagnostic radiography evaluation procedure.
8. Sample Size for the Training Set:
The device described is a digital X-ray detector, which is hardware for image acquisition. It does not involve a "training set" in the context of machine learning algorithms. The performance evaluation focuses on the physical characteristics and image quality of the detector itself.
9. How the Ground Truth for the Training Set Was Established:
As there is no "training set" for this hardware device, this question is not applicable.
§ 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.