(136 days)
ADD (Digital Flat Panel X-Ray Detector) is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy targeting both adult and children. It is intended to replace film based radiographic diagnostic systems. Not to be used for mammography.
The ADD are wired or wireless digital flat panel detectors that have been designed for faster, more streamlined approach to digital radiography systems. The ADD detector utilize a combination of propriety TFT glass and scintillators(CsI), and those and electronics are housed in one package. The detectors support an auto-trigger signal sensing technology that allows the detectors to be used without generator integration. The flat panel sensors of the ADD are fabricated using thin film technology based on amorphous silicon technology. Electronically, the sensors are much like conventional photodiode arrays. Each pixel in the array consists of a light-sensing photodiode and a switching Thin Film Transistor (TFT) in the same electronic circuit. Amorphous silicon photodiodes are sensitive to visible light, with a response curve roughly comparable to human vision. The sensitivity of amorphous silicon photodiodes peaks in green wavelengths, well matched to scintillators such as CsI. The response has the excellent linearity of a charge-integrating-biased photodiode. SDK-MCW is the software of Detector that performs image acquisition, image correction, and preprocessing.
Acceptance Criteria and Study for ADD Digital Flat Panel X-Ray Detector
This document describes the acceptance criteria and the study performed to demonstrate the substantial equivalence of the ADD Digital Flat Panel X-Ray Detector (K203188) to predicate devices.
1. Table of Acceptance Criteria and Reported Device Performance
The provided document does not explicitly present a table of "acceptance criteria" for clinical performance in the typical sense of a target metric to be achieved (e.g., sensitivity, specificity). Instead, the substantial equivalence is primarily based on technological characteristics and non-clinical performance tests, with clinical images provided as supportive evidence.
The relevant performance metrics and comparisons to predicate devices (Predicate Device#1: K181631, Predicate Device#2: K102349, Predicate Device#3: K140771) are summarized below from the provided text:
| Metric | Acceptance Criteria (Implied by Predicate Performance) | Reported Device Performance (ADD) |
|---|---|---|
| Scintillator | CsI | CsI |
| Effective Pixel Area | ~345 x 425 mm to 426.3 x 432.0 mm | 345.24 x 425.6 mm |
| Total Pixel Number | ~1,994 x 2,430 pixels to 2,981 x 3,021 pixels | 2,560 x 3,072 pixels |
| Pixel Pitch | ~140 um to 175 um | 140 um |
| High Contrast Limiting Resolution (LP/mm) | >= 3.5 (from Predicate Device#1) | Max. 3.5 |
| DQE (0.1lp/mm, min.) | Typ. 40% to 70% | 50% |
| MTF (0.1lp/mm, min.) | Typ. 95% to 97% | 97% |
| Communication | Wired/Wireless | Wired/Wireless |
| Exposure Mode | Normal Mode (Manual) / AED Mode (Auto Exposure Detection) | Normal Mode (Manual), AED Mode (Auto Exposure Detection) |
| Wireless | IEEE 802.11a/b/g/n (from Predicate Device#1 & #2) | IEEE 802.11a/b/g/n |
The submission states, "subject device shows similar or better DQE," and generally, the "inherent technical characteristics and performance are comparable to the predicate devices."
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify a distinct "test set" with a quantifiable sample size in the context of a prospective clinical trial. The "clinical images" were provided as supportive evidence, but the primary basis for substantial equivalence was non-clinical testing and technological comparison.
- Sample Size for Clinical Images: Not specified. The document only mentions "Clinical images were provided."
- Data Provenance: Not specified. However, the manufacturer is H&abyz Co., Ltd. from the Republic of Korea. It is common for such supportive clinical images to be collected retrospectively or prospectively within a clinical setting, but this is not detailed. The document explicitly states: "Clinical images were provided; these images were not necessary to establish substantial equivalence based on the differences from the predicate (note TFT technology with CsI scintillator that is identical to the predicate image plate) but they provide further evidence in addition to the laboratory performance data to show that the subject digital detector works as intended." This suggests the clinical images were not the primary means of demonstrating equivalence.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
The document does not describe an expert-based ground truth establishment process for the clinical images. Given that the images were "not necessary to establish substantial equivalence" and were "further evidence... to show that the subject digital detector works as intended," it's highly improbable that a formal expert ground truth establishment for a test set was conducted as would be typical for an AI-enabled diagnostic device.
4. Adjudication Method for the Test Set
Since a formal expert-based ground truth establishment for a clinical test set is not described, there is no mention of an adjudication method (e.g., 2+1, 3+1).
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not done or reported. The device is an X-ray detector, not an AI software for diagnostic interpretation. The submission is focused on demonstrating the detector's image quality and technical equivalence.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
Not applicable. The ADD is an X-ray detector, a hardware device for image acquisition, not a standalone algorithm. The software (SDK-MCW) performs image acquisition, correction, and preprocessing, but its performance is judged within the context of the detector's output, not as a standalone diagnostic algorithm.
7. Type of Ground Truth Used
For the non-clinical performance tests (DQE, MTF, resolution), the ground truth is established by physical measurements and standardized testing protocols as defined by IEC 62220-1.
For the supporting "clinical images," no specific ground truth (expert consensus, pathology, outcomes data) is mentioned or implied. The purpose of these images was to "show that the subject digital detector works as intended" in a real-world context, rather than to validate diagnostic accuracy against a definitive ground truth.
8. Sample Size for the Training Set
The document does not describe a training set in the context of machine learning. The ADD is a digital X-ray detector, and its software (SDK-MCW) performs image acquisition, correction, and preprocessing. While such software is developed and refined, the submission focuses on its validation rather than a "training set" for an AI model.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no mention of a training set for an AI model in this submission. The software validation followed a software development process.
§ 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.