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The AIRO® is intended to be used for X-ray computed tomography applications for anatomy that can be imaged in the 107cm aperture excluding patients weighing over 400 lbs (182 kg).

The Mobius Airo is a Mobile Intraoperative Computed Tomography (CT) System. The Airo has a large-diameter bore designed for intraoperative use; the main features include a 107cm bore, with a 51.2cm field of view (FOV). The Airo has two modes of operation; transport and scanning (both helical and axial). In its scanning mode, translation along the longitudinal axis is achieved through movement of the gantry along the length of the system base (rather than through movement of the patient support table).

The lightweight translating gantry consists of a rotating disk with a solid-state X-ray generator, solid state detector array (that includes detector modules that consist of Gadolinium Oxysulfide (GOS) and Photodiode Array). Each detector module includes a 32 x 16-pixel scintillator array that produces scintillation events responsive to irradiation by X-rays. The Airo also includes a collimator, control computer, communications link, data acquisition system, reconstruction computer, power system, brushless DC servo drive system (disk rotation), and a DC brushless servo drive system (translation).

The power system consists of batteries which provide system power while unplugged from a standard power outlet (e.g., during transport of the System and also during scanning). The base has retractable rotating caster wheels and electrical drive system can be easily moved to different locations.

In addition, the System has the necessary safety features such as emergency stop button, X-ray indicators, interlocks, patient alignment lasers, and 110 percent X-ray timer. The software helical and axial reconstruction algorithms are both based on an exact filtered-back projection.

The provided text describes a 510(k) premarket notification for the AIRO® Computed Tomography (CT) X-ray System (K180393). This submission aims to demonstrate substantial equivalence to a legally marketed predicate device (K160126) and primarily concerns the addition of pediatric scanning features/protocols and the removal of pediatric restrictions from the Indications for Use. The study conducted to meet acceptance criteria is a series of non-clinical bench tests and technical verification and validation activities rather than a clinical trial involving human subjects or AI-specific performance evaluation in a diagnostic context.

Here's an analysis of the provided information:

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

The document does not explicitly present a table of acceptance criteria for specific performance metrics alongside reported device performance. Instead, it states that the modified device's performance, particularly related to the added pediatric features and protocols, meets acceptance criteria through various testing. The comparison table (pages 5-7) primarily highlights the equivalence of technological characteristics between the proposed device and the predicate. The key differences causing the need for this submission are:

• Added pediatric scanning feature/protocols: This required the addition of 80 and 100 kV scanning capabilities and updated software to include age and height parameters.
• Modified Indications for Use Statement: Removal of pediatric restriction.

The "reported device performance" is a general statement that "the modified Airo CT System meets the acceptance criteria" based on the performed non-clinical tests. Specific numerical performance metrics (e.g., image quality scores, dose reduction percentages for pediatric protocols) are not detailed within the provided text. The only specific metric given is "Spatial Resolution for Sharpest Clinical Algorithm (Ip/cm at 2%) = 6.9," which is identical to the predicate.

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

The study described is a non-clinical bench testing and verification/validation effort. Therefore, there is no "test set" in the sense of a dataset of patient images or clinical cases. The "test set" would consist of phantoms used for image quality metrics, dose testing, and protocol validation. The text mentions:

• "Battery of bench testing with phantom images presented in Section 18." (Section 18 is not included in the provided text).
• "Image Quality Metrics and phantom images for Pediatrics."
• "Pediatrics Protocol Design & Validation (using Image Gently, ACR and AAPM guidelines)."
• "Radiation/Dose Testing."

The provenance of this phantom data would be internal testing conducted by Mobius Imaging, LLC in the USA. It is inherently "prospective" in the sense that the tests were designed and executed to validate the modified device.

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

Given that this is a non-clinical bench study focused on engineering validation and demonstrating general safety and effectiveness, there is no mention of experts establishing a "ground truth" for a test set in the diagnostic interpretation sense. The "ground truth" for performance would be derived from physical measurements on phantoms and compliance with recognized standards and guidelines (e.g., Image Gently, ACR, AAPM guidelines for pediatric protocols). While experts might have been involved in defining these standards or interpreting test results, their number and specific qualifications are not specified here.

4. Adjudication method for the test set

Not applicable, as this is a non-clinical engineering study of a CT device itself, not an AI software evaluating images, and therefore does not involve human adjudication of diagnostic interpretations.

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. This submission is for a CT X-ray system, not an AI-powered diagnostic tool. Therefore, an MRMC comparative effectiveness study to assess human reader improvement with or without AI assistance was not performed or described.

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

No. The AIRO® Computed Tomography (CT) X-ray System is a medical imaging device, not a standalone AI algorithm for image analysis. The "AI" in AIRO® is likely part of the product name and not an indicator of artificial intelligence functions for diagnosis or analysis in the context of this submission. The "software" updates mentioned are for scanner control and protocol management, not diagnostic AI.

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

For the non-clinical testing conducted, the "ground truth" primarily refers to established physical standards and metrics for CT image quality, radiation dose, and compliance with recognized regulatory and industry standards (e.g., IEC 60601 series, NEMA XR standards, Image Gently, ACR, AAPM guidelines). This "ground truth" is based on:

• Physical measurements on phantoms: To assess image quality, spatial resolution, contrast, noise, and radiation dose.
• Compliance with specified engineering and performance requirements: As defined by the company and aligned with international and national standards.

8. The sample size for the training set

Not applicable. This is a submission for a CT hardware system with software updates, not an AI model requiring a training set of data.

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

Not applicable, as there is no training set for an AI model in this submission.

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The AIRO® is intended to be used for X-ray computed tomography applications for anatomy that can be imaged in the 107cm aperture excluding pediatric patients and patients weighing over 400 lbs (182 kg).

The Mobius Airo is a Mobile Intraoperative Computed Tomography (CT) System. The Airo has a large-diameter bore designed for intraoperative use; the main features include a 107cm bore, with a 51.2cm field of view (FOV). The Airo has two modes of operation; transport and scanning (both helical and axial in patient mode). In its scanning mode, translation along the longitudinal axis is achieved through movement of the gantry along the length of the system base (rather than through movement of the patient support table).

The lightweight translating gantry consists of a rotating disk with a solid state x-ray generator, solid state detector array (that includes detector modules that consist of a layered Cadmium Tungstate (CdWO4) and Photodiode Array). Each detector module includes a 32 x 16 pixel scintillator array that produces scintillation events responsive to irradiation by X-rays. The Airo also includes a collimator, control computer, communications link, data acquisition system, reconstruction computer, power system, brushless DC servo drive system (disk rotation), and a DC brushless servo drive system (translation).

The power system consists of batteries which provide system power while unplugged from a standard power outlet (e.g., during transport of the System and also during scanning). The base has retractable rotating caster wheels and electrical drive system can be easily moved to different locations.

In addition, the System has the necessary safety features such as emergency stop button, X-ray indicators, interlocks, patient alignment lasers, and 110 percent X-ray timer. The software helical and axial reconstruction algorithms are both based on an exact filtered-back projection.

The provided text describes the Mobius Imaging AIRO® Computed Tomography (CT) X-ray System and its substantial equivalence to a predicate device (Airo Mobile CT System – K131431). However, the document does not contain explicit acceptance criteria and a detailed study proving the device meets those criteria in a format that directly addresses all the requested information categories.

Instead, it focuses on demonstrating substantial equivalence through a comparison of technological characteristics and a summary of non-clinical tests.

Here's an attempt to extract and infer the requested information based on the provided text, while also noting what is not present:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present a formal table of acceptance criteria with specific performance metrics and their corresponding reported device performance values. The closest information is the comparison table of technological characteristics to the predicate device, implying that equivalence to the predicate's performance serves as an acceptance criterion for these features.

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

The document lists "Image Phantom Data," "Historical Clinical Image Data Reconstruction Comparison," and "Offline Reconstruction Clinical Image Comparison (for NMAR feature)" as non-clinical tests. However, it does not specify the sample size for these test sets, nor the country of origin or retrospective/prospective nature of any clinical image data used.

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

The document mentions "Independent Review Analysis for Diagnostic Image Quality" but does not provide details on the number of experts, their qualifications, or how they established ground truth.

4. Adjudication method for the test set

The document does not describe any adjudication method used for establishing ground truth for the test set.

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

This document describes a CT X-ray system, not an AI-assisted diagnostic tool that would typically involve human reader improvement. Therefore, no MRMC comparative effectiveness study was done in the context of human reader improvement with AI.

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

The document specifies "Image Quality Metrics," "Image Phantom Data," and "Historical Clinical Image Data Reconstruction Comparison" as tests. These tests assess the device's technical performance and image quality, which are indicative of standalone (algorithm only) performance. However, specific metrics and results are not provided. The phrase "Offline Reconstruction Clinical Image Comparison (for NMAR feature)" also suggests standalone evaluation of the algorithm.

7. The type of ground truth used

For objective metrics like spatial resolution, phantom data likely served as ground truth. For "Historical Clinical Image Data Reconstruction Comparison" and "Offline Reconstruction Clinical Image Comparison," the ground truth would likely be the original clinical images from the predicate device (K131431) or accepted diagnostic standards derived from them, to ensure the modified device's images are comparable. The document also mentions "Independent Review Analysis for Diagnostic Image Quality," which suggests expert review/consensus was involved in parts of the evaluation.

8. The sample size for the training set

This document primarily describes the substantial equivalence of a medical imaging device (CT scanner). While it mentions reconstruction algorithms and a Metal Artifact Reduction (MAR) algorithm, it does not provide information on a "training set" as would be typical for machine learning-based AI devices. The focus is on the device's hardware and software performance characteristics in comparison to a predicate.

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

As no training set is explicitly mentioned or detailed for an AI component in the conventional sense, this information is not applicable/provided. The ground truth relevant to the device's performance evaluation would be related to its imaging capabilities, not the training of a diagnostic AI model.

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