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The System is intended for use in Radiographic / Fluoroscopic applications including general radiographic / fluoroscopic diagnostic, and interventional X-Ray imaging for General and Pediatric Populations.

The Soteria E-View system is classified as an interventional fluoroscopic X-ray system. The fundamental performance characteristics of the Soteria E-View interventional fluoroscopic X-ray system consists of:

• The patient table and C- arm with X-ray source on one side and the flat panel detector on the opposite side. The C-arm can be angulated in both planes, and the flat panel detector can be lifted vertically. The tabletop can be shifted from side to side and move forward/backward by an operator.
• Real-time image visualization of patient anatomy during procedures.
• Imaging techniques and tools to assist interventional procedures.
• . Post-processing functions after interventional procedures.
• Storage of reference/control images for patient records.
• Compatibility to images of other modalities via DICOM.
• . Built-in radiation safety controls-with the already FDA cleared CA-100S /FluoroShield (K182834).
  This array of functions provides the physician with the imaging information required to achieve minimally invasive interventional procedures.
  The Soteria E-View system is available as a Model GI-100 configuration. It is similar to the currently marketed predicate Soteria.Al consisting of an X-ray generator, image processor, collimator, X-ray Tube, Positioner, and patient table with CA-100S / FluoroShield Accessory, (K212336).

This document describes the Omega Medical Imaging, LLC Soteria E-View (K242488) system, which is a fluoroscopic/radiographic X-ray system. The submission aims to demonstrate substantial equivalence to its predicate device, the Soteria.AI (K212336).

The provided text details the device's technical specifications and comparisons to the predicate, as well as adherence to various safety standards and guidance documents. However, it does not contain information regarding specific acceptance criteria, corresponding device performance data, or detailed study results (including sample sizes, data provenance, ground truth establishment, expert qualifications, adjudication methods, MRMC studies, or standalone performance studies).

The document primarily focuses on demonstrating substantial equivalence through:

• Indications for Use: The Soteria E-View has similar indications, but with cardiac and vascular applications removed and gastrointestinal/ERCP applications added.
• Technological Characteristics: Changes include an updated flat panel detector (Varex Azure 3131Z CXP Detector with IGZO technology) with improved specifications like resolution and MTF, a different X-ray generator, positioner configuration, power supplies, control buttons, actuators, table size, and power unit.
• Non-Clinical Performance: States that non-clinical and "Sample clinical images" were used to validate image performance and demonstrate conformance to intended use, claims, user, and service needs. It also mentions software verification testing for functional requirements, performance, reliability, and safety.
• Safety and Effectiveness: Asserts that the differences do not raise new safety or effectiveness concerns, and the device complies with relevant 21 CFR regulations and international safety standards.

Therefore, many of the requested details about acceptance criteria and the study proving adherence cannot be extracted from this document.

Based on the provided text, here is what can be inferred or explicitly stated:

1. Table of Acceptance Criteria and Reported Device Performance

Specific, quantifiable "acceptance criteria" and direct "reported device performance" against those criteria are not explicitly laid out in a table format in the provided text. The document focuses on demonstrating substantial equivalence to a predicate device, meaning the new device performs at least as well as the predicate and does not raise new safety or effectiveness concerns.

However, some performance characteristics are compared to the predicate, implying they meet or exceed the predicate's performance, which can be seen as an indirect form of demonstrating acceptance.

Note: The table above extracts direct comparisons from Section "PRODUCT OVERVIEW" within the 510(k) summary. For other aspects like software performance, safety, and functional requirements, the document only states that "Results demonstrated that the executed verification test was passed" without providing specific criteria or data.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

The document states: "Non-clinical and Sample clinical images were used to validate image performance." It also mentions: "Non- clinical and Sample clinical images were used for validation testing of the Soteria E-View system to demonstrate conformance to the intended use, claims, user, and service needs..."
However, no specific sample size for the test set (number of images, number of cases, number of patients) is provided.
The data provenance (country of origin, retrospective/prospective) is not mentioned.

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

This information is not provided in the document.

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

This information is not provided in the document.

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

The document does not mention an MRMC study or any AI components for human reader assistance. The device is an X-ray system, and while the predicate device is named "Soteria.AI", the specific AI functionality (automatic region of interest to reduce exposure) is a built-in feature of the system and not framed as an AI-assistance tool for human readers in the context of comparative effectiveness for diagnosis. The focus is on the device's technical performance and safety.

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

This information is not provided in the document, as the device is a complete X-ray system, not a standalone algorithm. The "FluoroShield / CA-100S device to provide an automated Region of interest that reduces exposure to the patient and operator" is described as an integrated hardware/software component of the system.

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

This information is not provided in the document. The text only mentions "Sample clinical images" were used for validation testing, but how their "ground truth" was established is not detailed.

8. The sample size for the training set

The document primarily discusses validation and substantial equivalence, not the development of a specific algorithm requiring a "training set." Therefore, no information on a training set size is provided.

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

As no training set is described, this information is not applicable/provided.

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The Omega Medical Imaging, LLC Nyquist.IQ Image Processor is intended for use in Radiographic/fluoroscopic applications including cardiac, general radiographic/fluoroscopic diagnostic, and interventional x-ray imaging. The Nyquist.IQ is intended solely to be integrated only with Omega Medical Imaging CS-series-FP Systems.

Nyquist.IQ is a dynamic digital image processing system. The system application is based on a PC Windows operating system functioning on a PC based CPU. The object-oriented software performs real-time image processing and full procedure storage. The DICOM compliant connectivity provides the tools to transmit patient demographics, examination, and image data digitally.

Nyquist.IQ is not a standalone device, but functions as a component for FDA cleared Omega CS-series-FP platform. Nyquist IQ is an image processor that interfaces, with to acquire and digitize x-ray exposure from the Omega medical CS-series-FP.

The Nyquist.IQ operates in connection with the Varex's 3030 or the Teledyne 3030 flat panel detectors. This is demonstrated in the substantial equivalence section of the Nyquist.IQ is intended for the Omega CS-series-FP with Optional Accessory Device CA-100S / FluoroShield platform.

The Nyquist.IQ is intended solely to be integrated only with Omega Medical Imaging CS-series-FP systems.

The Nyquist.IQ image processor. The fundamental performance characteristics of the Nyquist.IQ interventional fluoroscopic imaging Processor system consists of:

• ) Real-time image visualization of patient anatomy during procedures

• Imaging techniques and tools to assist interventional procedures.

• 2 Post-processing functions after interventional procedures.
• 2 Storage of reference/control images for patient records.
• Σ Compatibility to images of other modalities via DICOM
• 2 Compatibility with the already FDA cleared CA-100S / FluoroShield AI Exposure Reduction Technology. (K182834)

This array of functions provides the physician the imaging information required to achieve minimally invasive interventional procedures.

The Nyquist.IQ image processor is available as a Model IPS-100 configuration and is similar to the currently marketed and predicate image processor MX-200 in CS-series-FP with optional CA-100S / FluoroShield Device.

This document is an FDA 510(k) clearance letter for the Omega Medical Imaging, LLC Nyquist.IQ Image Processor. It is a declaration of substantial equivalence to a predicate device, not a detailed study report with acceptance criteria and performance metrics for an AI/ML-driven device.

Therefore, this document does not contain the specific information required to answer your request regarding acceptance criteria and a study proving a device meets those criteria for an AI/ML product.

The information provided in the input primarily focuses on regulatory classification, indications for use, technological characteristics, and a comparison to predicate devices for a traditional medical imaging processor. It explicitly states:

• "The Nyquist.IQ did not require clinical study data since substantial equivalence to the currently marketed predicate device Omega CS-series-FP with Optional Accessory Device CA-100S / FluoroShield was demonstrated with the following attributes:
  • ∑ Indication for use.
  • A Technological characteristics.
  • ) Non-clinical performance testing; and
  • ∑ Safety and effectiveness." (Page 6)
• It also mentions a "FluoroShield AI Exposure Reduction Technology" associated with a predicate device (K182834), but it does not describe a performance study for the Nyquist.IQ as an AI/ML device itself. The Nyquist.IQ appears to be an image processor that interfaces with this existing technology, rather than being the AI/ML device itself.

To answer your specific questions, I would need a document that details a performance study, including acceptance criteria, for a software component with AI/ML functionality. This document does not provide such details.

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The System is intended for use in Radiographic/fluoroscopic applications including cardiac, general radiographic/fluoroscopic diagnostic and interventional x-ray imaging for General and Pediations

The Soteria.Al system is classified as an interventional fluoroscopic X-ray system. The fundamental performance characteristics of the Soteria.AI Interventional fluoroscopic X-ray system consists of:

• The patient table and c- arm with X-ray source on one side and the flat panel detector on the opposite side. The c-arm can be angulated in both planes, lifted vertically, shifted to the side, and moved forward/backward by an operator.
• Real-time image visualization of patient anatomy during procedures
• Imaging techniques and tools to assist interventional procedures.
• Post-processing functions after interventional procedures.
• Storage of reference/control images for patient records.
• Compatibility to images of other modalities via DICOM
• Built-in radiation safety controls-with the already FDA-cleared CA-100S / FluoroShield (K182834)

This array of functions provides the physician the imaging information required to achieve minimally invasive interventional procedures.

The Soteria.Al system is available as a Model Al-100 configuration. It is similar to the currently marketed predicate consisting of an X-ray generator, Image processor, collimator, x-ray Tube, Positioner, and patient table with CA-100S / FluoroShield Accessory, (K182834).

Additionally, Soteria.Al can be equipped with an optional X-ray VVA (Vessel and Ventricular Analysis) image analysis (FDA-Cleared) software, (K112807).

The provided text is a 510(k) summary for the Omega Medical Imaging Soteria.AI system. It states that a clinical study was NOT required because substantial equivalence to a predicate device (Omega CS-series-FP with optional CA-100S) was demonstrated through indications for use, technological characteristics, non-clinical performance testing, and safety and effectiveness.

Therefore, the document does not contain information about acceptance criteria or a study proving the device meets acceptance criteria in the context of a clinical performance study. The 510(k) submission primarily relies on non-clinical performance testing and comparison to a predicate device.

However, I can extract information regarding non-clinical performance testing and the grounds for substantial equivalence.

Here's an analysis of the provided information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of direct acceptance criteria coupled with reported device performance in the way one might expect from a clinical study for a new algorithm. Instead, it states that non-clinical performance testing was performed to demonstrate compliance with standards and guidelines, which serve as the implicit "acceptance criteria" for the device's technical and safety characteristics.

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

• Sample Size for Test Set: Not applicable in the context of a clinical efficacy test. This submission relies on non-clinical performance and safety testing.
• Data Provenance: Not applicable for clinical data. The validation and verification are based on engineering and software testing.

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

Not applicable for a clinical ground truth. The "ground truth" for the non-clinical testing is compliance with established engineering and regulatory standards.

4. Adjudication method for the test set

Not applicable for a clinical test set. The "adjudication" is determined by whether the device adequately passes the defined non-clinical tests and meets specified standards.

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 conducted. The document explicitly states: "The Soteria.AI did not require clinical study data since substantial equivalence to the currently marketed predicate device Omega CS-series-FP was demonstrated..." This device is a fluoroscopic X-ray system, and the AI component (FluoroShield / CA-100S) deals with automated region of interest to reduce exposure, not necessarily an AI for diagnostic interpretation by human readers.

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

The "FluoroShield / CA-100S (K182834)" component, which is an "automated Region of interest that reduces exposure to the patient and operator," functions in a standalone capacity within the X-ray system to manage radiation exposure. The submission states that its software was revised and integrated. However, no specific performance metrics for this AI component in a "standalone" fashion as a diagnostic algorithm are provided, as its role is a safety and optimization feature within the overall imaging system. The submission focuses on its integration and compliance rather than its standalone diagnostic performance.

7. The type of ground truth used

For the non-clinical performance and safety testing, the "ground truth" is defined by:

• Established international and FDA-approved consensus standards (e.g., IEC 62304, ISO 14971, IEC 60601 series).
• FDA guidance documents.
• System requirements specifications (functional, non-functional, safety, privacy, security).
• User and service needs.

8. The sample size for the training set

Not applicable. This document is a 510(k) submission focusing on substantial equivalence through non-clinical testing and updates to an existing system, not a de novo AI algorithm requiring a training set for model development.

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

Not applicable. As no training set was used or described for a new AI algorithm, no ground truth establishment for such a set is detailed.

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The Omega Medical Imaging, LLC CS-series-FP (SSXI) systems with optional accessory device CA-100S as a modification device to provide an automated Region of interest that reduces exposure to the patient and operator. The system is intended for use in Radiographic/fluoroscopic applications including cardiac, vascular, general radiographic/fluoroscopic diagnostic, and interventional x-ray imaging for General Populations. At no time will the CA-100S be considered as a replacement for the primary collimator shall always be used, in accordance with good medical practice, to define a Region of Interest

This 510(k) submission is for the addition of an optional secondary fast collimator system (Model: CA-100S / FluoroShield™ K182834 cleared 02/18/19). The CA-100S/ FluoroShield™ will be used with the following FDA cleared device: Omega's CS-series-FP ( K100102) which utilizes a Varex 2020 Flat Panel Detector. (Note: the only difference between this submission and the predicate is the size of the FPD. The predicate device utilizes a Varex 3030 Flat Panel Detector)

The-CA-100S/ FluoroShield™ system is composed of a Shutter, a ROI Electronics Unit, an Auto-ROI Processor, two ROI Control Panels and a Monitor.

The CA-100S / FluoroShield™ is a secondary collimator that can only be used in conjunction with the primary collimator. When using the CA-100S / FluoroShield™, the primary collimator shall be used to manually define a region of interest. Once this ROI has been established by the primary collimator, the CA-100S / FluoroShield™ can be used to further reduce the size of the ROI beyond the ROI initially established with the primary collimator.

I am sorry, but based on the provided text, there is no information about specific acceptance criteria and detailed study that proves the device meets those criteria for the CS-series-FP Radiographic / Fluoroscopic Systems with Optional CA-100S / FluoroShield™ mentioned in the document.

The document is a 510(k) premarket notification and primarily focuses on demonstrating substantial equivalence to a predicate device and outlining the device's description, function, and safety compliance. While it mentions that "Additional testing for this submission was performed utilizing a DAP meter to demonstrate the dose reduction results utilizing the CA-100S / FluoroShield™ accessory" and "A clinical study was conducted sampling 100 patients as well to demonstrate the dose reduction to patients and staff," it does not provide the specific acceptance criteria for these tests or detailed results in a table format.

Here's what can be extracted regarding some of your questions, but it's not a complete answer to all:

• Study Objective: The clinical study aimed to compare and measure radiation exposure to patients using Dose Area Product (DAP) and scatter radiation to endoscopy personnel using Landauer Luxel personal dosimetry badges.
• Performance Claim (from clinical study conclusion): "When using FluoroShield, unnecessary radiation can be reduced up to 61.8% in patients and 59.4% to the staff."
• Sample size for test set: 100 patients for the clinical study.
• Data provenance: The clinical study was a "prospective study of 100 consecutive patients who underwent fluoroscopy-guided endoscopic procedure." It doesn't specify the country of origin.
• Training set: No information available about a training set. The descriptions of "segmentation model" and "motion detection module" being updated or based on trained images from the 2020 system imply a training process, but details on sample size or ground truth establishment for this training are not provided.
• Ground truth: For the clinical study, the ground truth appears to be measured radiation exposure (DAP for patients, dosimetry badges for staff).
• Other details: Questions 1 (table of acceptance criteria), 3 (experts), 4 (adjudication), 5 (MRMC study), and 6 (standalone performance) are not addressed in the provided text.

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The Omega Medical Imaging, LLC CS-series-FP (SSXI) systems with optional accessory device CA-100S as a modification device to provide an automated Region of interest that manages exposure to the patient and operator. The system is intended for use in Radiographic applications including cardiac, vascular, general radiographic/ fluoroscopic diagnostic, and interventional x-ray imaging for General Populations.

At no time will the CA-100S be considered as a replacement for the primary collimator shall always be used, in accordance with good medical practice, to define a Region of Interest

This 510(k) submission is for the addition of an optional secondary fast collimator system (Model: CA-100S). The CA-100S will only be used with the following FDA cleared device: Omega's CSseries-FP ( K121293). The-CA-100S system is composed of a Shutter, a ROI Electronics Unit, an Auto-ROI Processor, two ROI Control Panels and a Monitor.

Omega's (CA-100S) allows for auto collimation while maintaining a perspective of surrounding anatomy. The blended image incorporates a lower frequency refresh of the peripheral image area. This combined image (live fluoroscopy of ROI + background refreshed at a rate of once or twice per second) increases the quality of information presented during interventional procedures.

The CA-100S secondary collimator may be used to additionally shield anatomy that is not the primary focus of the physician but is required to maintain peripheral imaging. The CA-100S ROI image processing combines the live ROI with the legacy image of the full field of view (defined by the primary collimator). This allows for the collimation of the ROI without impacting the doctors normal work flow, visualisation, orientation and navigation.

The Product is permanently incorporated in the host fluoroscopy system (Omega's CS-series-FP) and its clinical environment. The system is intended to be installed by trained technicians and operated by professionals trained in its use and the associated medical interventional procedures. The CA-100S Product functions in ON Mode, OFF Mode or Bypass Mode.

The Product consists of a Shutter, a ROI Electronics Unit, an Auto-ROI Processor with Status / Reduction Monitor and two ROI Control Panels.

The Omega Medical Imaging, LLC CS-series-FP with Optional Accessory Device CA-100S, a secondary fast collimator system, was designed to reduce patient and operator exposure to X-ray radiation during fluoroscopic procedures by dynamically defining a Region of Interest (ROI).

Here's an analysis of its acceptance criteria and the study that demonstrates compliance:

1. Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state quantitative acceptance criteria in a tabular format with corresponding reported device performance values. Instead, it describes the device's functional aims and summarizes the regulatory and safety compliance. The primary 'acceptance criterion' implicitly defined is the reduction in Dose Area Product (DAP) to patients and medical staff by reducing the area of exposure, while maintaining or improving image quality and clinical utility.

Since no specific quantitative acceptance criteria and reported performance with numerical values are given in the provided text, a table can be constructed based on the stated benefits and intended function.

2. Sample Size and Data Provenance for the Test Set

The document mentions "Bench performance testing" and "detailed data comparing performance with the existing Omega Medical Imaging CS-series-FP system utilizing the CA-100S integrated into an existing system." It further states that "The tests that were performed utilized commercially available Phantoms such as the Phillips Phantom, and including a fabricated Moving Catheter to exercise the auto ROI functionality."

• Sample Size for Test Set: Not explicitly stated, but implies multiple tests on phantoms. No human subject data (patients or operators) appears to have been used for this specific phase of testing as described.
• Data Provenance: The testing was conducted in a laboratory/bench setting, likely at Omega Medical Imaging, LLC. The data is thus prospective in terms of being generated specifically for this regulatory submission via bench tests. No country of origin for clinical data is mentioned as clinical data is not explicitly described for this testing.

3. Number of Experts and Qualifications for Ground Truth

The document does not detail the use of human experts to establish ground truth for the bench testing described beyond the general statement that the system is intended for use by "professionals trained in its use and the associated medical interventional procedures." The "fabricated Moving Catheter" and "Phillips Phantom" test the physical and automated tracking performance, implying objective, measurable outcomes rather than expert-derived ground truth.

4. Adjudication Method for the Test Set

Not applicable, as the testing described is primarily technical performance evaluation using phantoms, rather than subjective clinical interpretation requiring expert adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study is mentioned in the provided text regarding the effect size of human readers' improvement with AI vs. without AI assistance. The CA-100S is a hardware and image processing modification to an existing fluoroscopy system, focusing on dose reduction and maintaining visualization through dynamic collimation, not on AI-assisted diagnostic reads or interpretations.

6. Standalone Performance Study

The document describes the device's standalone operation modes (ON, OFF, BYPASS) and its functionality in managing exposure and image blending. The "Bench performance testing" utilizing phantoms focuses on the device's intrinsic capabilities, which can be considered a standalone (algorithm only without human-in-the-loop) performance evaluation in terms of its technical function (e.g., ROI tracking, dose reduction effectiveness with phantoms, image blending). The results of these tests (e.g., dose reduction, image quality improvement, auto-tracking of the moving catheter) represent the device's performance when operating independently as intended.

7. Type of Ground Truth Used

The ground truth for the described bench testing appears to be objective physical measurements and simulated scenarios using phantoms. For instance, the "fabricated Moving Catheter to exercise the auto ROI functionality" implies a known, controlled movement that the device's auto-ROI feature is expected to track. Dose reduction would be verified against dosimetric measurements.

8. Sample Size for the Training Set

The document does not provide information on a training set sample size. The CA-100S is described as a "secondary fast collimator system" that implements "image processing software" and an "Auto-ROI Processor." While this implies algorithms, the text focuses on its physical and operational integration rather than a machine learning model that would require a distinct training set. If machine learning is involved in the "Auto-ROI Processor," details about its training are not provided.

9. How the Ground Truth for the Training Set Was Established

As no training set is explicitly mentioned or detailed for a machine learning component, information on how its ground truth was established is not available in the provided text. The "Auto-ROI Processor" is described as calculating "the ROI settings that provide the most useful image," suggesting rule-based or conventional image processing algorithms rather than deep learning that heavily relies on labeled training data and ground truth.

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The Omega Medical Imaging, LLC CS-series-FP (SSXI) Systems are intended for use in Radiographic/fluroscopic applications including cardiac, vascular, general radiographic/fluroscopic diagnostic, and Interventional x-ray imaging.

The Omega Medical Imaging, LLC, CS-series-FP systems currently incorporate a 19.8cm x 19.8cm or 29.8cm x 29.8cm solid-state flat-panel detector (FPD). This 510(k) submission adds a slightly larger 21.7cm x 21.7cm and 30.3cm x 30.3cm solid-state CMOS flat-panel detector as an additional option. The CS-series-FP fluoroscopy single and dual plane x-ray imaging systems are configured with a floor mounted c-arm and patient table. The dual plane systems incorporate a ceiling suspended C-arm into the system. The MX CFP 3131 flat-panel image detector utilizes a cesium iodide scintillator coupled to an amorphous silicon TFT panel. The captured digital image is processed by the acquisition system (separate from the Flat Panel Detector) which includes image processing, viewing functions, local storage, and DICOM compatibility. The Image Processor does not have the capability to connect to the internet as there is no browser.

Subject Device Flat Panel Detectors MX CFP 2222 / 3131 are to be used only with the Omega CSseries-FP Fluoroscopic Systems

The document provided is a 510(k) premarket notification for a medical imaging device, specifically an X-ray system. It focuses on demonstrating substantial equivalence to a previously cleared predicate device, rather than proving the device meets specific clinical performance acceptance criteria against a ground truth in the way a diagnostic algorithm would.

Therefore, many of the requested categories (e.g., sample size for test set, number of experts for ground truth, MRMC study, training set information) are not applicable to this type of submission.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

For this type of device (an X-ray system, specifically an optional detector component), the "acceptance criteria" are related to technical performance benchmarks and compliance with safety standards, rather than clinical diagnostic accuracy. The reported "performance" is the technical testing done to show equivalence.

• 21 CFR 1020.30, 21 CFR 1020.31, and 21 CFR 1020.32 (Parts related to electronic product radiation control).
• IEC 60601-1-2, IEC 60601-2-7, IEC 60601-2-28, IEC 60601-2-32, and IEC 60601-2-43 (International safety standards).
• UL 60601-1 and CAN/USA C22.2 No.601.1-M90 (Specific safety standards). |
  | Equivalence in Technology | The MX CFP 2222 and 3131 option utilizes the same technology (Cesium Iodide scintillator coupled to a CMOS-light sensitive imaging component) as the predicate device. |
  | No new indications for use | The modified device does not introduce any new indications for use. |
  | No new potential hazards | The modified device does not result in any new potential hazards. |

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

• Sample Size: Not applicable. The "test set" in this context refers to commercially available test objects designed to evaluate technical imaging characteristics, not a clinical dataset of patient images.
• Data Provenance: Not applicable, as it's technical bench testing, not clinical data.

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

• Not applicable. Ground truth for technical performance tests is established by the specifications of the test objects themselves and physical measurements, not by expert consensus on clinical images.

4. Adjudication method for the test set:

• Not applicable. Technical measurements do not typically involve adjudication in the way clinical diagnostic performance studies do.

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 is an X-ray system (hardware component), not an AI algorithm. Therefore, an MRMC study and AI-related effectiveness are not relevant.

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

• Not applicable. This is an X-ray system (hardware component), not a standalone algorithm.

7. The type of ground truth used:

• Technical performance benchmarks established by the design of commercially available test objects (e.g., phantoms for low-contrast, spatial resolution, temporal resolution, dynamic range) and compliance with international and national safety standards.

8. The sample size for the training set:

• Not applicable. This is an X-ray system; there is no "training set" in the context of machine learning.

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

• Not applicable.

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The Omega Medical Imaging, LLC CS-series-FP with 3030+ Option systems are intended for use in radiographic/fluoroscopic application including cardiac, vascular, general radiographic/fluoroscopic diagnostic, and interventional x-ray imaging.

The Omega Medical Imaging, LLC. CS-series-FP systems currently incorporate a 19.8cm x 19.8cm solid-state flat-panel detector (FPD) as an option. This 510(k) submission adds a larger format (29.8cm x 29.8cm) flat-panel detector as an additional option. The CS-series-FP fluoroscopy single and dual plane x-ray imaging systems are configured with a floor mounted C-arm and a patient table. The dual plane systems incorporate a ceiling suspended C-arm into the system. The flat-panel image detector utilizes a cesium iodide scintillator coupled to an amorphous silicon TFT panel. The captured digital image is processed by the acquisition system which includes image processing, viewing functions, local storage, and DICOM compatibility.

The provided text is a 510(k) summary for the Omega Medical Imaging, LLC CS-series-FP with 3030+ Option radiographic/fluoroscopy system. This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a traditional clinical study with defined acceptance criteria and performance metrics against a gold standard in the way an AI/ML device might.

Therefore, the requested information elements related to acceptance criteria, ground truth, expert review, and statistical analyses of clinical performance are largely not applicable in this context. The "study" described is a non-clinical performance testing to show the new device meets the same performance standards as its predicate.

Here's an attempt to interpret and answer your questions based on the provided text, highlighting where the information is not available or not relevant for this type of submission:

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

Explanation of "Acceptance Criteria" in this context: For a 510(k) submission, the primary acceptance criterion is substantial equivalence to a predicate device. This means demonstrating that the new device is as safe and effective as a legally marketed device. The "acceptance criteria" here are therefore the performance characteristics of the predicate device, which the new device aims to match or exceed.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size for Test Set: Not applicable in the traditional sense of patient data. The "test set" consisted of "commercially available Test Objects" (phantoms). The number and specific types of these test objects are not detailed, but they are not human or animal subjects.
• Data Provenance: Not applicable. The "data" comes from non-clinical performance testing using phantoms, not patient data from a specific country or collected retrospectively/prospectively.

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)

• Not applicable. Ground truth as typically understood for clinical studies involving expert interpretation of images or diagnoses is not relevant here. The "ground truth" for non-clinical performance testing is inherent in the design specifications of the test objects themselves (e.g., a known number of low-contrast objects, a specific spatial resolution pattern). Performance is measured objectively by the system.

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

• Not applicable. There was no human adjudication of results for the non-clinical performance tests. Measurements are objective and quantitative (e.g., measuring line pairs per millimeter, contrast-to-noise ratio).

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 study was not performed. This submission is for an imaging system (hardware), not an AI/ML diagnostic tool. There is no AI component or human-in-the-loop performance measurement described.

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

• No. This is an imaging system, not an algorithm, so "standalone (algorithm only)" is not applicable. The performance tests evaluate the physical and technical capabilities of the X-ray system and its detector.

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

• The "ground truth" for the non-clinical testing was based on the known characteristics and specifications of the commercially available test objects (phantoms). These phantoms are designed to have specific, measurable properties (e.g., specific sizes of low-contrast objects, known spatial frequencies).

8. The sample size for the training set

• Not applicable. As this is not an AI/ML device, there is no "training set" in the machine learning sense. The device is a conventional X-ray imaging system.

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

• Not applicable, as there is no training set for an AI/ML algorithm.

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