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510(k) Data Aggregation
(300 days)
ADX6000 Portable X-Ray System; iRayA6
The ADX6000 (also known as iRay A6) is a handheld and portable general purpose X-ray system. The device uses a variable tube current with voltage from 50-80 kVp and, therefore, is limited to taking diagnostic x-rays of extremities.
It is intended to be used by a qualified and trained clinician on both adult and pediatric patients. This device is not intended for mammography.
The ADX6000 is a portable x-ray system intended to generate and control the emission of xray energy for diagnostic procedures by exposing an x-ray image receptor to ionizing radiation, typically in a hospital or clinic environment.
The x-ray source, a tube by Toshiba (tube voltage 50-80kV with 0.8 mm focal spot) is located inside the handheld device. A flat panel detector (FPD), not part of the system, connects to the device via LAN port to enable image capture, manipulation, storage, and transmission through the user interface and device software/firmware.
The operator controls three key x-ray variables to obtain the best image at minimal exposure:
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- Exposure intensity (kV)
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- Exposure dosage (mA)
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- Exposure time setting (Sec)
The ADX6000 does not have a wireless feature for transmission of data.
This document describes a 510(k) premarket notification for the ADX6000 Portable X-Ray System (also known as iRay A6). The provided text does not contain information about a study that assesses the device's diagnostic performance against specific acceptance criteria using a test set of patient data, nor does it detail any AI-related studies. Instead, it focuses on the device's technical specifications, safety, and equivalence to predicate devices.
Therefore, many of the requested sections about acceptance criteria and study details cannot be directly answered from the provided text. I will address the points based on the information available.
1. A table of acceptance criteria and the reported device performance
Based on the provided text, the "acceptance criteria" primarily relate to safety and technical performance standards, rather than diagnostic accuracy on patient cases.
| Acceptance Criteria Category | Standard Met / Performance |
|---|---|
| Software Validation | Completed software validation; determined to be a moderate level of concern software. Risk management test performed in accordance with ISO 14971 and met all requirements. |
| Electrical Safety | Tests performed for 60601-1, 60601-1-3, 60601-2-7, and 60601-2-28 by Onetech Corp. All requirements for electrical safety were met. |
| Electromagnetic Compatibility (EMC) | Tests performed for 60601-1-2, 61000-3-2, and 61000-3-3 by Korea Testing Laboratory. All requirements for EMC were met. |
| Bench Testing (Radiation Protection) | Performance tests for radiation protection in x-ray equipment completed by Korea Testing Laboratory. The tests met the requirements. |
| Diagnostic Quality of Images | Images from the ADX6000 were evaluated by a board-certified radiologist and were "approved for diagnostic quality." (No specific quantitative metrics or acceptance criteria for this approval are provided). |
| Source-Skin Distance (SSD) | The ADX6000 has an SSD cage attached to meet FDA standards (21 CFR 1020.31) of not less than 30 cm. (Operators are instructed not to remove it and images cannot be taken closer than the cage allows). |
| Radiation Safety Guidance | The petition was prepared in compliance with "FDA Guidance on Radiation Safety Considerations for X-Ray Equipment Designed for Hand-Held Use." |
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document primarily focuses on technical safety and performance tests. For the diagnostic image quality evaluation, it states: "Images from the ADX6000 were evaluated for diagnostic quality by a board certified radiologist and were approved for diagnostic quality."
- Sample size for test set: Not specified. The number of images evaluated is not provided.
- Data provenance: Not specified. It does not mention if the images were from clinical studies, phantoms, or simulated data, nor their country of origin or whether they were retrospective or prospective.
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)
- Number of experts: One, as indicated by "a board certified radiologist."
- Qualifications of those experts: "a board certified radiologist." No further details on experience or sub-specialty are provided.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable/Not specified. Since only one radiologist evaluated the images, there was no multi-reader adjudication method employed for diagnostic image quality. The radiologist "approved" the images for diagnostic quality.
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
- MRMC study: No, an MRMC study was not described.
- Effect size with/without AI: Not applicable. The device described is a portable X-ray system, not an AI-powered diagnostic tool. The document makes no mention of AI.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is not an AI algorithm. The diagnostic performance mentioned refers to the quality of images produced by the X-ray system for human interpretation.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For the diagnostic quality evaluation, the "ground truth" was the opinion of a single board-certified radiologist who "approved" the images. This is essentially a form of expert opinion or evaluation of image quality suitability for diagnosis, rather than a definitive medical ground truth like pathology or outcomes data.
8. The sample size for the training set
Not applicable. The document describes an X-ray imaging device, not an AI model requiring a training set.
9. How the ground truth for the training set was established
Not applicable. There is no mention of an AI model or a training set.
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