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510(k) Data Aggregation
(384 days)
The X Twin is intended to be used as a digital multifunctional x-ray system, suitable for all radiographic exams, including specialist areas like trauma or pediatric work, excluding mammography.
X Twin shall only be operated by qualified, trained professionals. The patient can be in sitting, lying or standing position.
The device is a permanently installed device and is intended to be operated in medical rooms with appropriate radiation protection only. It is not intended to be used with flammable anesthetic agents or in potentially explosive atmospheres.
The X Twin is a digital multifunctional x-ray system, in which an X Twin stand holds the xray image receptor, the collimator and the x-ray tube including the x-ray tube housing assembly. The generator, x-ray tube, beam limiting device, image receptor, including the workstation for image processing plus imaging software and the optional mobile x-ray table are known components. The geometry of the X Twin contains two guide frames, two support arms, an x-ray tube column and an image receptor column. The movements of the columns and the arms as well as the SID adjustment are motorized. The x-ray tube support arm as well as the image receptor support arm is provided with an integrated control unit, located at the front of the support arms. These units allow an adjustment of angle, height and distance of the image receptor and x-ray in relation to the patient. Simultaneously an integrated electronic control system provides automatic focusing of the image receptor and x-ray tube. Additionally an integrated touch display for indication of current values and additional control options is implemented in the tube support arm. The device receives its power from the x-ray generator.
The provided document is a 510(k) premarket notification for a medical device called the "X Twin System," which is a digital multifunctional x-ray system. The document focuses on demonstrating substantial equivalence to a predicate device and includes summaries of non-clinical and clinical performance testing. However, it does not explicitly define acceptance criteria in terms of specific performance metrics or provide a detailed study that proves the device meets such criteria for diagnostic accuracy.
The document states that the X Twin system itself did not undergo clinical testing but refers to clinical performance testing performed for the integrated Image Detector DFP4343C7 by its manufacturer, NIPK Electron (with 510(k) release number K122589). Without the full 510(k) submission for the DFP4343C7 detector, it is not possible to provide all details requested regarding acceptance criteria and its supporting study.
Based on the available information:
1. A table of acceptance criteria and the reported device performance:
The document does not explicitly state quantitative acceptance criteria for diagnostic performance (e.g., sensitivity, specificity for detecting specific conditions) for the X Twin System. Instead, the acceptance criteria are implicitly tied to demonstrating safety, efficacy, and substantial equivalence to the predicate device (Essenta DR, K070528) and the previously cleared Image Detector DFP4343C7.
Acceptance Criteria (Implicit) | Reported Device Performance |
---|---|
Safety and Efficacy (General) | The X Twin system is deemed substantially equivalent to the predicate device Essenta DR (K070528). |
Compliance with Electrical Safety Standards (IEC 60601-1) | The device complies with IEC 60601-1. |
Compliance with X-ray Specific Standards (IEC 60601-1-2, IEC 60601-1-3, IEC 60601-2-54) | The device underwent testing for half-value layer, focal spot to image receptor distance, and leakage radiation as per relevant test clauses. All test results were satisfactory. |
Biocompatibility (ISO 10993) | No evidence was found that the surfaces of the X Twin system cause skin irritations or similar negative effects on the patient. The observed surface coatings have a 10-year history of safe use on similar medical devices. |
Software Level of Concern (per FDA Guidance for Software in Medical Devices) | The X Twin Control Software and the Imaging Software DXRS were classified as "Moderate" Level of Concern. The documentation and testing were performed in accordance with the guidance. The DXRS software was part of the 510(k) Premarket Notification No. K122589 (for the Image Detector DFP4343C7). |
Image Detector DFP4343C7 Performance (Non-Clinical) (per Guidance for the Submission of 510(k)'s for Solid State X-ray Imaging Devices) | Non-clinical performance testing was performed by NIPK Electron (as 510(k) Applicant for K122589). All test results were satisfactory. (Specific metrics for image quality, resolution, DQE, MTF, etc., are not provided in this document but would be in K122589). |
Image Detector DFP4343C7 Performance (Clinical) (per Guidance for the Submission of 510(k)'s for Solid State X-ray Imaging Devices) | Clinical Performance Testing was performed by NIPK Electron (as 510(k) Applicant for K122589). All test results were satisfactory. (Specific outcomes, diagnostic equivalence, or performance metrics are not detailed in this document but would be in K122589). The X Twin system itself did not perform clinical testing, relying on the clearance of its integrated detector. |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
- For the X Twin System (as a whole): The document states, "Roesys GmbH did not perform any clinical testing for the X Twin." Therefore, there is no test set sample size or data provenance provided for the X Twin system directly.
- For the Image Detector DFP4343C7: Clinical performance testing was performed by NIPK Electron. This document does not provide the sample size, data provenance (country, retrospective/prospective), or study design details for that specific testing. This information would be found in the K122589 submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):
- This information is not provided in the document for the X Twin System, as no direct clinical testing was performed by Roesys GmbH.
- For the Image Detector DFP4343C7's clinical study (K122589), these details would be available in its specific submission, but are not present here.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not applicable for the X Twin System's submission as presented here, as no direct clinical test set was used by Roesys GmbH for diagnostic performance.
- The adjudication method for the DFP4343C7's clinical study is not detailed in this document.
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 MRMC comparative effectiveness study is mentioned or implied for the X Twin System. The device is a conventional X-ray system, not an AI-based diagnostic tool.
- The document does not indicate the presence of AI assistance within the X Twin control software or the DXRS imaging software that would involve human readers improving with AI. The software functions described are for control of the X-ray system and image processing/viewing, not AI-powered diagnostic interpretations.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
- Not applicable. The X Twin System is an X-ray imaging device; its software controls the device and processes images for human interpretation, it is not a standalone diagnostic algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Since no clinical diagnostic performance study for the X Twin system is presented by Roesys GmbH, the type of ground truth is not specified for this submission.
- For the clinical performance testing for the Image Detector DFP4343C7 (K122589), this information would be within that specific submission.
8. The sample size for the training set:
- Not applicable, as this device does not involve machine learning or AI models with training sets for diagnostic purposes. The software controls mechanical movements and image display/processing.
9. How the ground truth for the training set was established:
- Not applicable, as this device does not involve machine learning or AI models with training sets.
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