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510(k) Data Aggregation
(24 days)
EVS 4343W / EVS 4343WG / EVS 4343WP / EVS 3643W / EVS 3643WG / EVS 3643WP
The EVS 4343W / EVS 4343WG / EVS 3643W / EVS 3643WG / EVS 3643WP Digital X-ray detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. This device is intended to replace film or screen based radiographic systems in all general purpose diagnostic procedures. This device is not intended for mammography applications.
The EVS 4343W / EVS 4343WG / EVS 4343WP / EVS 3643W / EVS 3643WG / EVS 3643WP Detector is an indirect conversion device in the form of a square plate in which converts the incoming X-rays into visible light. This visible light is then collected by an optical sensor, which generates an electric charges representation of the spatial distribution of the incoming X-ray quanta. The charges are converted to a modulated electrical signal thin film transistors. The amplified signal is converted to a voltage signal and is then converted from an analog to digital signal which can be transmitted to a viewed image print out, transmitted to remote viewing or stored as an electronic data file for later viewing.
Here's a breakdown of the acceptance criteria and the study details for the DRTECH EVS detectors, based on the provided FDA 510(k) summary:
1. Acceptance Criteria and Reported Device Performance
The acceptance criteria for the new devices (EVS 4343WP, EVS 3643WP) were primarily to demonstrate equivalent diagnostic capability to the predicate device (EVS 3643). This was assessed through clinical image evaluation, comparing image performance scores. For other device models and parameters (DQE, MTF), the acceptance typically involved being "basically equal or [better] than the predicate device."
Here's a table summarizing the comparison for key performance metrics:
Parameter | Acceptance Criteria (relative to Predicate EVS 3643/EVS 3643G) | Reported Device Performance (Subject Devices) | Predicate Device Performance (EVS 3643/EVS 3643G) |
---|---|---|---|
DQE (CsI models) | Equal or better at 1.0 lp/mm | EVS 4343W: 52.8% | |
EVS 3643W: 53.3% | |||
EVS 4343WP: 50.0% | |||
EVS 3643WP: 53.1% | EVS 3643: 55.3% | ||
DQE (GOS models) | Equal or better at 1.0 lp/mm | EVS 4343WG: 25.1% | |
EVS 3643WG: 25.9% | EVS 3643G: 23.6% | ||
MTF (CsI models) | Equal or better at 2.0 lp/mm | EVS 4343W: 50.0% | |
EVS 3643W: 42.5% | |||
EVS 4343WP: 48.4% | |||
EVS 3643WP: 42.9% | EVS 3643: 37.8% | ||
MTF (GOS models) | Equal or better at 2.0 lp/mm | EVS 4343WG: 50.1% | |
EVS 3643WG: 47.8% | EVS 3643G: 34% | ||
Resolution | 3.5 lp/mm (matching predicate) | 3.5 lp/mm | 3.5 lp/mm |
Clinical Image Performance (for IGZO TFT models) | No significant difference in image performance compared to predicate. | Difference in score within one standard deviation. | (EVS 3643 as predicate for comparison) |
Note: For DQE and MTF, the acceptance criterion implicitly means that the values should be close to or exceed the predicate's performance, indicating comparable or improved image quality metrics. The document states "basically equal or [better] than the predicate device." In some cases (e.g., EVS 4343W/EVS 3643W DQE vs. EVS 3643), the subject device values are slightly lower than the predicate, but this is presented within the context of "basically equal or [better] than" and ultimately deemed acceptable for substantial equivalence. For the GOS models, the subject devices showed improvement in DQE and MTF.
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: The document mentions "8 positions of body parts (Chest PA, Cspine AP, C-spine LAT, L-spine LAT, Shoulder AP, Shoulder LAT, Extremities)" were selected for the clinical image evaluation. It does not explicitly state the number of images per body part or the total number of images in the test set. It also doesn't specify if these were real patient cases or phantoms.
- Data Provenance: Not explicitly stated. The manufacturer is based in the Republic of Korea, so the data could originate from there, but this is not confirmed. The study is described as a "clinical image evaluation." It's not specified if it's retrospective or prospective.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified.
4. Adjudication Method for the Test Set
- Adjudication Method: Described as a "single blind clinical image evaluation." This implies that the readers were blind to which device produced the image (subject vs. predicate). However, the specific method of consensus or individual scoring (e.g., 2+1, 3+1, none) among multiple readers is not detailed.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- MRMC Study: The document describes a "single blind clinical image evaluation" to compare image performance. This sounds like a MRMC study, as it compares the image performance of multiple devices (subject vs. predicate) using human readers.
- Effect Size of Human Reader Improvement: The document states that "it is indicated that there is no significant difference of image performance between EVS 4343WP, EVS 3643WP and EVS 3643 as difference in the score is within one standard deviation." This implies equivalence rather than an improvement with AI vs. without AI assistance, as this is a comparison of X-ray detectors themselves, not an AI software. The study's focus was on the diagnostic capability of the new hardware, not an AI's impact on human performance. Thus, no effect size of human improvement with AI is provided.
6. Standalone Performance (Algorithm Only)
- This section does not involve an algorithm with standalone performance, as the device is a digital X-ray detector (hardware). The software (Econsolel) is mentioned and being the same as the predicate's, but the evaluation focuses on the hardware's image acquisition performance.
7. Type of Ground Truth Used
- Ground Truth: For the clinical image evaluation, the "ground truth" was established by comparing the "image performance" scores between the subject device's images and the predicate device's images. This is an expert consensus or subjective evaluation of image quality and diagnostic capability, rather than an objective pathology or outcomes data.
8. Sample Size for the Training Set
- Training Set Sample Size: Not applicable. This document describes the evaluation of an X-ray detector, which is hardware, not an AI algorithm that would typically require a training set.
9. How the Ground Truth for the Training Set Was Established
- Ground Truth for Training Set: Not applicable, as there is no mention of an AI algorithm training set.
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