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This software is intended to generate digital radiographic images of the skull, spinal column, extremities, and other body parts in patients of all ages. Applications can be performed with the patient sitting, or lying in the prone or supine position and is intended for use in all routine radiography exams. The product is not intended for mammographic applications.

This software is not meant for mammography, fluoroscopy, or angiography.

The I-Q View is a software package to be used with FDA cleared solid-state imaging receptors. It functions as a diagnostic x-ray image acquisition platform and allows these images to be transferred to hard copy, softcopy, and archive devices via DICOM protocol. The flat panel detector is not part of this submission. In the I-Q View software, the Digital Radiography Operator Console (DROC) software allows the following functions:

• 1. Add new patients to the system; enter information about the patient and physician that will be associated with the digital radiographic images.
• 2. Edit existing patient information.
• 3. Emergency registration and edit Emergency settings.
• 4. Pick from a selection of procedures, which defines the series of images to be acquired.
• 5. Adiust technique settings before capturing the x-ray image.
• 6. Preview the image, accept or reject the image entering comments or rejection reasons to the image. Accepted images will be sent to the selected output destinations.
• 7. Save an incomplete procedure, for which the rest of the exposures will be made at a later time.
• 8. Close a procedure when all images have been captured.
• 9. Review History images, resend and reprint images.
• 10. Re-exam a completed patient.
• 11. Protect patient records from being deleted by the system.
• 12. Delete an examined Study with all images being captured.
• 13. Edit User accounts.
• 14. Check statistical information.
• 15. Image QC.
• 16. Image stitching.
• 17. Provides electronic transfer of medical image data between medical devices.

The provided document is a 510(k) summary for the I-Q View software. It focuses on demonstrating substantial equivalence to a predicate device through bench testing and comparison of technical characteristics. It explicitly states that clinical testing was not required or performed.

Therefore, I cannot provide details on clinical acceptance criteria or a study proving the device meets them, as such a study was not conducted for this submission. The document relies on bench testing and comparison to a predicate device to establish substantial equivalence.

Here's a breakdown of what can be extracted from the provided text regarding acceptance criteria and the "study" (bench testing) that supports the device:

1. Table of Acceptance Criteria and Reported Device Performance

Since no clinical acceptance criteria or performance metrics are provided, this table will reflect the general statements made about the device performing to specifications.

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

• Test Set Sample Size: Not applicable/not reported. The document describes bench testing, not a test set of patient data.
• Data Provenance: Not applicable. Bench testing generally involves internal testing environments rather than patient data from specific countries or retrospective/prospective studies.

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

• Not applicable. As no clinical test set was used, no experts were needed to establish ground truth for patient data. Bench testing typically relies on engineering specifications and verification.

4. Adjudication method for the test set

• Not applicable. No clinical test set or human interpretation was involved.

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, an MRMC comparative effectiveness study was not done. The document explicitly states: "Clinical Testing: The bench testing is significant enough to demonstrate that the I-Q View software is as good as the predicate software. All features and functionality have been tested and all specifications have been met. Therefore, it is our conclusion that clinical testing is not required to show substantial equivalence." The device is software for image acquisition, not an AI-assisted diagnostic tool.

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

• Yes, in a sense. The "study" described is bench testing of the software's functionality and its integration with solid-state detectors. This is an evaluation of the algorithm/software itself.

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

• For bench testing, the "ground truth" would be the engineering specifications and expected functional behavior of the software and its interaction with hardware components. It's about verifying that the software performs according to its design requirements.

8. The sample size for the training set

• Not applicable. The I-Q View is described as an image acquisition and processing software, not an AI/machine learning model that typically requires a training set of data.

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

• Not applicable, as there is no mention of a training set or AI/machine learning component.

Summary of the "Study" (Bench Testing) for K203703:

The "study" conducted for the I-Q View software was bench testing. This involved:

• Verification and validation of the software.
• Demonstrating the intended functions and relative performance of the software.
• Integration testing to verify that compatible solid-state detectors performed within specification as intended when used with the I-Q View software.

The conclusion drawn from this bench testing was that the software performs to specification and is "as safe and as functionally effective as the predicate software." This was deemed sufficient to demonstrate substantial equivalence, and clinical testing was explicitly stated as not required.

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The purpose of Acuity is to acquire, store, communicate, display and process medical X-ray images. These radiographic systems are intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography, angiography, interventional, or fluoroscopy use.

RadmediX Acuity combines components into a complete stationary x-ray system, including software, tube stands, tube heads, collimators, generators, tables, and digital radiography panels.

Here's a breakdown of the acceptance criteria and the study information based on the provided text:

Acceptance Criteria and Device Performance:

The document describes the Acuity SDR Standard, Acuity SDR Plus, and Acuity FDR Standard as stationary x-ray systems. The core claim for substantial equivalence is that the device performs the same functions using the same technological methods as the predicate device (Visaris Vision®) to produce diagnostic x-ray images.

Study Information:

1. Sample Size and Data Provenance:

   • Test Set Sample Size: Not explicitly stated as a numerical sample size of clinical cases for a formal clinical trial. Instead, the non-clinical testing involved acquiring DICOM images from "all major body structures" using one AcuitySDR system configuration.
   • Data Provenance: The document does not specify the country of origin for the image acquisition or whether it was retrospective or prospective. It was a "field tested" system, implying real-world or simulated real-world scenarios.

2. Number of Experts and Qualifications (for Ground Truth):

   • Number of Experts: Not specified.
   • Qualifications of Experts: Not specified, beyond the statement that images were generated for "diagnostic x-rays" and assessed as "clinically acceptable." This implies evaluation by trained personnel (e.g., radiologic technologists, radiologists), but their specific qualifications or number are not detailed.

3. Adjudication Method:

   • No formal adjudication method is described. The assessment of image quality was based on whether images were "of high quality and contrast and clinically acceptable."

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No MRMC comparative effectiveness study was performed or described. The submission focuses on demonstrating substantial equivalence through technical characteristics and non-clinical image quality assessment, not on human reader performance improvement with or without AI assistance.

5. Standalone Performance Study (Algorithm Only):

   • Yes, a standalone study (non-clinical testing) was performed. The algorithm (software) alongside the hardware components was tested to acquire and process images. The output (DICOM images) was then evaluated for inherent quality and acceptability. The assessment "all images were of high quality and contrast and clinically acceptable" refers to the output of the integrated system.

6. Type of Ground Truth Used:

   • Expert Consensus / Clinical Acceptability: The ground truth for image quality was established through subjective expert assessment of "high quality and contrast and clinically acceptable." It does not mention pathology or outcomes data.

7. Training Set Sample Size:

   • Not applicable. This device is an X-ray system, not an AI/ML algorithm that requires a training set in the typical sense for image interpretation or diagnosis. The "software" components mentioned (AccuVueMED, AccuVue) are image acquisition and processing software, which are generally deterministic and not "trained" on data in the way a diagnostic AI would be. They are "previously cleared software supplied with the system."

8. How Ground Truth for Training Set Was Established:

   • Not applicable, as there is no specific "training set" for an AI/ML algorithm in this submission. The software components were previously cleared by the FDA, implying their performance was established through other means at the time of their original clearance (K152172 and K141440).

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