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The Micro C Medical Imaging System, M01 is a handheld and portable general purpose X-ray system that is indicated for use by qualified/trained clinicians on adult and pediatric patients for taking diagnostic static and serial radiographic exposures of extremities. The device is not intended to replace a radiographic system that has both variable tube current and voltages (kVp) in the range that may be required for full optimization of image quality and radiation exposure for different exam types.

The Micro C Medical Imaging System, M01 (subject device) is a handheld X-ray system designed to aid clinicians with point of care visualization through diagnostic X-rays of distal extremities. The device allows a clinician to select desired technique factors best suited for their patient anatomy. The Micro C Medical Imaging System, M01 consists of three major subsystems: The Emitter, Cassette, and Control Unit. The System is intended to interface an external Monitor (touchscreen or non-touchscreen display), keyboard and a mouse, and can provide a remote operator interface over the network to a laptop. The Micro C Medical Imaging System, M01 utilizes a computer vision positioning system to allow the emitter to be positioned above the patient anatomy and aligned to the cassette by the operator. The device is used in a clinical environment.

The provided document describes the Micro C Medical Imaging System, M01, and updates to its software to include AiLARA (Artificial Intelligence-based Algorithm for Radiography) modes. The primary focus of the document regarding acceptance criteria and performance relates to the validation of this new software feature.

Here's a breakdown of the requested information:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria for the AiLARA algorithm's performance in terms of image quality or diagnostic accuracy using specific metrics like sensitivity, specificity, or AUC. Instead, the acceptance criteria seem to be qualitative and focused on the algorithm's learning trend, software requirement fulfillment, diagnostic relevance of images, and radiation dose limits.

2. Sample size used for the test set and the data provenance

• Test Set Sample Size: The AiLARA algorithm's full development dataset was split, with 20% of the data used as the testing set for algorithm verification.
• Data Provenance: The document does not specify the country of origin. The data used for algorithm verification was part of the "full development dataset" of AiLARA. For the "Image Quality Validation Study," the validation set was collected after the algorithm was frozen and transferred to the device, using phantoms at different emitter orientations and angles. The phantom types included ankle, elbow, hand, foot, knee, toe, and wrist. The study appears to be prospective in the sense that images were collected specifically for validation after the algorithm's finalization.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• For the Image Quality Validation Study, images were reviewed and rated by board certified radiologists and an orthopedic surgeon. The exact number of experts is not specified. Their qualifications are stated as "board certified" in their respective fields.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• The document does not describe a specific adjudication method (like 2+1 or 3+1) for establishing the ground truth or evaluating the test set images. It states that experts "reviewed and rated" the images.

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 was done to evaluate human readers' improvement with AI assistance. The studies performed were primarily focused on the standalone performance and safety of the AiLARA algorithm and the updated device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Yes, a standalone evaluation of the AiLARA algorithm was performed. The "AiLARA Algorithm Verification" specifically describes training the model and then sending the full testing set into the model to predict its performance on unseen data, which is a standalone assessment. The "Image Quality Validation Study" and "Radiation Dose Testing" also evaluate the device's output (images and dose) when using the AiLARA modes, which operate without human input on technique factors during image acquisition (the algorithm "determines and recommends a power setting and an exposure time for the X-ray without user input").

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• For the "AiLARA Algorithm Verification," the ground truth was referred to as the "truth" which the model was trained to learn the trend of. Given the context of determining optimal technique factors, this "truth" likely relates to ideal exposure parameters for specific anatomies and views.
• For the "Image Quality Validation Study," the ground truth for evaluating image quality was the assessment by board-certified radiologists and an orthopedic surgeon that images were "diagnostically and clinically relevant." This can be considered a form of expert consensus or subjective expert assessment of image utility.

8. The sample size for the training set

• 80% of AiLARA's full development dataset was used for the training set. The total size of the "full development dataset" is not specified.

9. How the ground truth for the training set was established

• The document states that the AiLARA model was trained to "learn the trend of the training dataset (truth)." It implies that the ground truth for the training set consisted of the correct or desired power settings and exposure times for various phantom anatomies and orientations. The specific methodology for establishing this "truth" (e.g., manual expert selection, physical measurements, reference images) for the training data is not detailed but is implicitly linked to generating "a clinically relevant image" while "reduc[ing] overexposures."

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The Micro C Medical Imaging System, M01 is a handheld and portable general purpose X-ray system that is indicated for use by qualified/trained clinicians on adult and pediatric patients for taking diagnostic static and serial radiographic exposures of extremities. The device is not intended to replace a radiographic system that has both variable tube current and voltages (kVp) in the range that may be required for full optimization of image quality and radiation exposure for different exam types.

The Micro C Medical Imaging System, M01 (subject device) is a handheld X-ray system designed to aid clinicians with point of care visualization through diagnostic X-rays of distal extremities. The device allows a clinician to select desired technique factors best suited for their patient anatomy. The Micro C Medical Imaging System, M01 consists of three major subsystems: The Emitter, Cassette, and Control Unit. The System is intended to interface an external Monitor (touchscreen or non-touchscreen display), keyboard and a mouse, and can provide a remote operator interface over the network to a laptop. The Micro C Medical Imaging System, M01 utilizes a computer vision positioning system to allow the emitter to be positioned above the patient anatomy and aligned to the cassette by the operator. The device is used in a clinical environment.

The provided text describes a 510(k) premarket notification for the OXOS Medical Micro C Medical Imaging System, M01. This submission aims to expand the indications for use to include pediatric patients and surgical settings. The document heavily relies on the substantial equivalence to a previously cleared predicate device (also Micro C Medical Imaging System, M01, K203658).

However, the document does not include detailed acceptance criteria or a study that rigorously proves the device meets specific performance criteria in a way that would be typical for an AI/CADe device. The focus is on demonstrating that the expanded indications (pediatric use and surgical use) do not raise new questions of safety or effectiveness compared to the predicate device. The information provided is primarily a comparison between the subject device and its predicate, highlighting that the core technological characteristics are identical.

Therefore, many of the requested details about acceptance criteria, specific performance metrics, sample sizes, expert ground truth establishment, adjudication methods, MRMC studies, and standalone AI performance are not present in the provided text, as this is a submission for an imaging device, not an AI/CADe device.

Based on the provided text, here's the information that can be extracted or inferred:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria or detailed performance metrics in the way one would expect for an AI/CADe device (e.g., sensitivity, specificity, AUC). Instead, the "performance" discussed relates to the device's fundamental imaging capabilities and its intended use, established by its substantial equivalence to the predicate. The crucial aspect from the document is the claim that the updated indication for pediatric use and surgical use is acceptable as demonstrated by "performance data" that does not raise different questions of safety and effectiveness.

2. Sample size used for the test set and the data provenance

Not provided in the document. The filing is for an X-ray imaging device, not an AI/CADe system. The "performance data" for pediatric and surgical use is not detailed with sample sizes or data provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable/Not provided. This relates to AI/CADe studies, not the 510(k) for an X-ray imaging system.

4. Adjudication method for the test set

Not applicable/Not provided.

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

Not applicable. This is not an AI-assisted device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Not applicable. This is not an AI-enabled device.

7. The type of ground truth used

Not applicable. The "performance data" for pediatric and surgical use is not specified in terms of clinical "ground truth" used for evaluation. It likely refers to technical performance evaluations and usability rather than diagnostic accuracy against a clinical gold standard for disease detection.

8. The sample size for the training set

Not applicable. This is not an AI-enabled device.

9. How the ground truth for the training set was established

Not applicable. This is not an AI-enabled device.

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The Micro C Medical Imaging System, M01 is a handheld and portable general purpose X-ray system that is indicated for use by qualified/trained clinicians on adult patients for taking diagnostic static and serial radiographic exposures of extremities. The device is not intended to replace a radiographic system that has both variable tube current and voltages (kVp) in the range that may be required for full optimization of image quality and radiation exposure for different exam types.

The Micro C Medical Imaging System, M01 (subject device) is a handheld X-ray system designed to aid clinicians with point of care visualization through diagnostic X-rays of distal extremities. The device allows a clinician to select desired technique factors best suited for their patient anatomy. The Micro C Medical Imaging System, M01 consists of three major subsystems: The Emitter, Cassette, and Control Unit. The System is interface an external Monitor (touchscreen or non-touchscreen display), keyboard and a mouse, and can provide a remote operator interface over the network to a laptop. The Micro C Medical Imaging System, M01 utilizes a computer vision positioning system to allow the emitter to be positioned above the patient anatomy and aligned to the cassette by the operator. The device is used in a clinical environment.

This looks like a 510(k) summary for a medical device called "Micro C Medical Imaging System, M01". The summary primarily focuses on establishing substantial equivalence to a predicate device and discussing technical characteristics and compliance with various standards.

There is no information provided regarding acceptance criteria nor a typical clinical study with patient data that would involve the following:

• A table of acceptance criteria and the reported device performance: This document does not specify quantitative acceptance criteria for image quality or diagnostic performance, nor does it report device performance against such metrics.
• Sample size used for the test set and the data provenance: There is no mention of a test set with patient data.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: As there's no clinical test set, there's no mention of experts or ground truth establishment.
• Adjudication method for the test set: Not applicable as there's no patient test set.
• If a multi reader multi case (MRMC) comparative effectiveness study was done: Not applicable as there's no patient test set or reader study mentioned.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The document describes an X-ray imaging system, not an AI algorithm. Therefore, this is not applicable.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable as there's no clinical test set.
• The sample size for the training set: Not applicable as there's no AI algorithm with a training set discussed.
• How the ground truth for the training set was established: Not applicable as there's no AI algorithm with a training set discussed.

What the document does provide:

The document focuses on demonstrating substantial equivalence to predicate devices based on:

1. Technological Characteristics Comparison (Table 5-2 and 5-3): This table compares the subject device (Micro C Medical Imaging System, M01) with a predicate mobile X-ray system (Nomad MD 75kV Handheld X-Ray System, K140723) and reference devices (KDR™ AU-DDR System, K193225 and Faxitron VisionCT, K173309). It details various technical specifications like product code, regulation, classification, indication for use, age of device use, principle of operation, image type, detector characteristics (for the detector incorporated), collimator, weight, dimensions, triggering mechanism, SSD, SID, light field, energy source, exposure time, mA, kVp, ingress protection, image processing, connectivity options, DICOM compliance, and device package contents.
2. Non-Clinical Performance Data: The document states that testing was performed successfully according to a list of international standards (e.g., ISO, IEC) and FDA regulations. These standards cover aspects like risk management, diagnostic X-ray system requirements, electrical safety, electromagnetic compatibility, usability, X-ray tube assemblies, software product lifecycle, biocompatibility, labeling, and laser safety.
3. Additional Non-Clinical Performance Testing: This includes Functional Testing, an Image Quality Study, Usability Testing, and a Cleaning Study. However, no specific details, criteria, or results from these studies are provided in this summary.

Conclusion from the document:
The summary concludes that the Micro C Medical Imaging System, M01 is similar to the legally marketed predicate device (Nomad MD 75kV Handheld X-Ray System) in intended use, similar technologies, and performance data, and therefore does not raise different questions of safety and effectiveness, thus supporting its substantial equivalence claim.

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