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The FXATM software is a quantitative imaging software application. It is designed for physicians and clinical professions who are interested in the analysis of motion in medical images, particularly in musculoskeletal images. The FXA™ software permits users to review static and dynamic digital images acquired from a variety of radiographic sources for the purpose of facilitating a quantitative assessment of relative motion. Information about the motion of selected objects, such as bone structures, can be generated and presented in the form of a report containing graphics, charts, text and statistical data.

The FXA™ software is a software tool which was developed to measure static dimensions and to analyze relative motion of implants or bony structures. Basis for the analysis are medical images such as functional radiographs. The FXA™ software was developed with the aim to detect and analyze even small changes with high precision, high reproducibility and low operator variability. For this, patent-pending algorithms were developed and implemented for image-superimposition and the automatic detection of bony structures within selected areas of the image. The software may be installed on workstations with Windows® operating system according to the software requirement specification (SRS, (Attachment B01)).

Here's a detailed breakdown of the acceptance criteria and the study that proves the FXATM device meets them, based on the provided text:

Acceptance Criteria and Device Performance

Note: The document frames the acceptance criteria implicitly by comparing the FXATM's performance against its predicate device (QMA™ software by Medical Metrics Inc., K022585). The key "acceptance" is that FXATM performs as well as or better than the predicate.

Study Details

1. Sample Size used for the test set and the data provenance:

   • Test Sets: The document refers to three types of tests:
     • "Tests under 'best case' conditions" (Attachment F01) - Sample size not specified.
     • "Tests under real conditions"
       • "Through images obtained from in-vitro cadaver experiments" (Attachment I) - Sample size not specified.
       • "Through side-by-side comparison with real clinical images" (Attachment H) - Sample size not specified.
     • "Tests addressing the inter- and intra-observer variability" (Attachment F04) - Sample size not specified.
   • Data Provenance:
     • "In-vitro cadaver experiments"
     • "Real clinical images"
     • "Images obtained from" best case conditions (likely simulated or highly controlled).
     • Country of Origin: Not explicitly stated for any of the data sets. Given the submitter's location (Germany), it's plausible some data originated there, but this is not confirmed.
     • Retrospective or Prospective: Not explicitly stated for any of the data sets. "Real clinical images" could imply retrospective, but without further detail, it's unclear. Cadaver experiments are inherently experimental.

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

   • Not specified. The document mentions "inter-observer variability" tests, implying multiple observers were involved, but it does not detail how ground truth was established by experts or their qualifications.

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

   • Not specified. The document focuses on measurement error and variability rather than a diagnostic performance where adjudication methods are typically applied.

4. 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 was not an MRMC comparative effectiveness study involving human readers' performance with and without AI. The device (FXATM) is a quantitative imaging software, not an AI-assisted diagnostic tool for human readers in the traditional sense discussed in MRMC studies. The comparison is between the FXATM software itself and a predicate software (QMA™).

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

   • Yes, effectively. The performance data presented are for the "FXATM" software directly, measuring its output (e.g., measurement error, inter-observer variability when using the software). While the software is "designed for physicians and clinical professions," the reported performance metrics are intrinsic to the software's ability to measure motion accurately, rather than its impact on a human's diagnostic decision-making. The "inter-observer variability" tests assess how much different operators using the software vary in their results, which is still a measure of the software's robustness and precision in application, not necessarily a human "reading" performance improvement.

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

   • Not explicitly stated in detail. For the "best case" and "cadaver experiment" conditions, the ground truth likely involved precise physical measurements or highly controlled setups from which true motion could be derived. For "real clinical images" and inter-observer variability, the ground truth for "accuracy" would have been relative to some gold standard measurement method or perhaps a detailed manual assessment that the software aims to replicate or assist. The document implies accuracy is measured against a "true" motion, but the specific method of establishing that "true" motion isn't detailed.

7. The sample size for the training set:

   • Not specified. The document does not provide details about a training set for the algorithms. It discusses implementation of "patent-pending algorithms for image-superimposition and the automatic detection of bony structures." This implies algorithmic development, but without details on machine learning or adaptive algorithms, a distinct "training set" might not be applicable or specified in the same way it would be for modern AI/ML systems.

8. How the ground truth for the training set was established:

   • Not applicable / Not specified. As no specific "training set" is mentioned or detailed, there's no information on how its ground truth might have been established.

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