(106 days)
910SGA Digital Flat Panel X-Ray Detector is indicated for digital imaging solution designed for human anatomy including head, neck, spinal column, arm, leg and peripheral (foot, hand, wrist, fingers, etc.). It is intended to replace film based radiographic diagnostic systems and provide a case diagnosis and treatment planning for physicians and other health professionals. Not to be used for mammography.
910SGA is a digital solid state X-ray detector that is based on flat-panel technology. This radiographic image detector and processing unit consists of a scintillator coupled to an a-Si TFT sensor. This device needs to be integrated with a radiographic imaging system. It can be utilized to capture and digitalize X-ray images for radiographic diagnosis The RAW files can be further processed as DICOM compatible image files by separate console SW (not part of this 510K submission) for a radiographic diagnosis and analysis.
Here's a breakdown of the acceptance criteria and study information for the 910SGA Digital Flat Panel X-ray Detector, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance:
The document doesn't explicitly state "acceptance criteria" in a quantitative, numbered list. Instead, it demonstrates substantial equivalence to a predicate device (1210SGA) through direct comparison of technical characteristics and performance metrics. The underlying acceptance is that the device must perform at least as well as, or be substantially equivalent to, the predicate device.
| Characteristic | Acceptance Criteria (Predicate Device K113630: 1210SGA) | Reported Device Performance (910SGA) | Meets Criteria? |
|---|---|---|---|
| Intended Use | Digital imaging for human anatomy (head, neck, spinal column, arm, leg, peripheral); replaces film-based systems for diagnosis and treatment planning; not for mammography. | Digital imaging for human anatomy (head, neck, spinal column, arm, leg, peripheral); replaces film-based systems for diagnosis and treatment planning; not for mammography. (Identical wording used) | Yes |
| Detector Type | Amorphous Silicon with TFT | Amorphous Silicon with TFT | Yes |
| Scintillator | Gadolinium Oxysulfide | Gadolinium Oxysulfide | Yes |
| Pixel Pitch | 127 x 127 μm | 127 x 127 μm | Yes |
| MTF (Resolution/Sharpness) | Equivalent to or better than 1210SGA | "The MTF of the 910SGA detector performed almost same with 1210SGA. Therefore the overall resolution performance and sharpness of 910SGA is almost same with 1210SGA." | Yes |
| DQE (Ability to Visualize Details) | Equivalent to or better than 1210SGA | "910GA demonstrated higher DQE performance than 1210GA at various spatial frequencies and provides almost same Signal-to Noise Ratio (SNR) transfer from the input to the output of a detector as a function of frequency. At the lowest spatial frequency, 910SGA has a DQE of 46% and that of 1210SGA is 45%." (Higher DQE is better) | Yes |
| NPS (Noise Performance) | Equivalent to or better than 1210SGA | "910SGA also exhibited NPS which has almost same performance with 1210SGA." | Yes |
| Clinical Image Quality | Substantially equivalent to 1210SGA | "Based on... the outcome of a comparative review by an expert for both devices, we can claim the substantial equivalency between 910SA and its predicate device, 1210SGA in terms of image quality." | Yes |
| Safety and Performance | Compliant with IEC 60601-1: 2005 + CORR.I(2006) + CORR(2007) and IEC 60601-1-2:2007, Class A. | "Electrical, mechanical, environmental safety and performance testing according to standard IEC 60601-1: 2005 + CORR.I(2006) + CORR(2007) (Medical electrical equipment Part 1:General requirements for basic safety and essential performance) was performed, and EMC testing were conducted in accordance with standard IEC 60601-1-2:2007, Class A. All test results were satisfactory." | Yes |
2. Sample Size and Data Provenance (Test Set):
- Sample Size: The document does not specify an exact number of images or cases used for the clinical assessment. It states, "clinical images are taken from both devices" and implies a "sample radiographs of similar age groups and anatomical structures." This suggests a comparative, rather than quantitative, sample size.
- Data Provenance: Not explicitly stated, but the submission is for a Korean company (Rayence Co., Ltd.) seeking FDA clearance, and the expert is a "licensed US radiologist." This suggests the clinical images could have been taken in the US or in Korea and reviewed by a US expert. The document does not specify if the images were retrospective or prospective.
3. Number of Experts and Qualifications (Ground Truth for Test Set):
- Number of Experts: "a licensed US radiologist" (singular).
- Qualifications: "licensed US radiologist." No specific years of experience are mentioned, but "licensed" implies significant training and qualification.
4. Adjudication Method (Test Set):
- Method: Not explicitly stated as a formal adjudication method (like 2+1 or 3+1). The text mentions a "comparative review by an expert for both devices" and an "expert opinion." This implies a single expert's assessment without a formal multi-reader adjudication process described.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- Was it done?: No, an MRMC comparative effectiveness study involving human readers with vs. without AI assistance was not explicitly stated or performed. This study focused on the performance of the new device (910SGA) compared to a predicate device (1210SGA), not on the impact of AI assistance on human readers. The device itself is a flat panel detector, not an AI algorithm for image interpretation.
6. Standalone (Algorithm Only) Performance:
- Was it done?: This is not applicable in the context of this submission. The device is a digital flat panel X-ray detector, an imaging hardware component, not an AI algorithm. The performance evaluation focuses on the detector's image acquisition capabilities (MTF, DQE, NPS, and overall image quality for diagnosis) as compared to a predicate device.
7. Type of Ground Truth Used (Test Set):
- Type: Clinical images were reviewed by an expert to render an "expert opinion" on image quality and "substantial equivalency." This falls under expert consensus/opinion rather than pathology or outcomes data. The goal was to confirm the diagnostic quality of the images produced by the device, not to diagnose specific diseases.
8. Sample Size for the Training Set:
- Sample Size: The document does not refer to a "training set" in the context of machine learning or AI. The testing described is for a hardware device (X-ray detector). The "comparison" is between the proposed device and its predicate, using physical and clinical tests.
9. How the Ground Truth for the Training Set Was Established:
- Method: Not applicable, as there is no mention of a "training set" for an AI algorithm. The testing relates to fundamental imaging performance and clinical image quality comparison of a hardware device.
§ 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.