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The Definium AMX 700 X-Ray Unit is indicated for use in generating radiographic images of human anatomy. It is intended for general-purpose diagnostic procedures. It is capable of generating radiographic images on film or digitally. This device is not intended for mammographic applications.

The GE Definium AMX 700 is a mobile x-ray system that enables the capture of radiographic images via a tethered digital detector or traditional film cassettes.

The GE Definium AMX 700 is a mobile X-ray system. The information provided outlines its substantial equivalence to a predicate device rather than a study involving specific acceptance criteria for a new clinical performance claim. Therefore, much of the requested information regarding clinical studies, ground truth establishment, expert adjudication, and sample sizes is not applicable in this context.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Not Applicable. No clinical test set involving patient data was required for this 510(k) submission.

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

• Not Applicable. No clinical test set requiring expert-established ground truth was part of this submission.

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

• Not Applicable. No clinical test set requiring adjudication was part of this submission.

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 submission is for a conventional mobile X-ray system, not an AI-powered device. Therefore, no MRMC study or AI-related comparative effectiveness was conducted or reported.

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

• Not Applicable. This is a hardware device, not an algorithm.

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

• Not Applicable. No clinical ground truth was established for this submission as it relied on substantial equivalence. The "ground truth" for the device's acceptability was its conformance to safety standards and its functional equivalence to a legally marketed predicate device.

8. The sample size for the training set:

• Not Applicable. This is a hardware device, not a machine learning model, so there is no training set in the context of AI. If "training set" refers to engineering testing or design validation, the document does not specify sample sizes for those internal processes.

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

• Not Applicable. As above, there is no "training set" in the context of AI. For engineering and design validation, conformance to specifications and industry standards would be the "ground truth." The document states "The design and development processes of the manufacturer conform with 21 CFR 820, ISO 9001 and ISO 13485 quality systems," which implies internal validation against established criteria.

Summary of the Study (as described in the document):

The "studies" summarized are focused on electrical and radiation safety, confirming the device's conformance with applicable medical device safety standards. No clinical tests were required because the product is considered a combination of two already cleared devices for the US market (via 21 CFR Part 807). The substance of the submission revolves around demonstrating substantial equivalence to the predicate GE AMX-4+ Mobile X-ray System, meaning the new device has the same intended uses and fundamental scientific technology, and comparable safety and effectiveness features.

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Volume Viewer Plus is a medical diagnostic software that allows the processing, review, and communication of 3D reconstructed images and their relationship acquired images from CT, MR, X-Ray Angio and PET Scanning devices. The combination of acquired images, reconstructed images, annotations and measurements performed by the clinician are intended to provide to the referring physician clinically relevant information for diagnosis, surgery and treatment planning.

Volume Viewer Plus is a software package to be used on the GE Advantage Workstation, the GE Centricity PACS Workstation and the GE CT Operator Consoles (LightSpeed and HiSpeed). It allows the 3D processing, review and analysis of DICOM CT, MR, X-Ray Angio and PET images previously acquired, reconstructed and transferred on the corresponding workstation. This software provides Multi-Planar Reformation (MPR) views in any plane (orthogonal, oblique or curved), 3D views in any rendering mode (MIP, MinIP, Average, Volume Rendering, Fly-Through) and their correlation to originally acquired images. Its user interface provides the tools to manipulate, annotate, measure and record these views as well as output an exam report. Additional features allow for segmentation of anatomy as well as display of multi-phase and/or fused hybrid images (PET/CT, PET/MR).

This 510(k) pertains to "Volume Viewer Plus," a software package for 3D processing, review, and analysis of medical images (CT, MR, X-Ray Angio, PET). The submission focuses on demonstrating substantial equivalence to previously cleared devices, rather than a de novo clinical study with specific acceptance criteria and performance data for a novel algorithm.

Therefore, many of the requested sections (acceptance criteria, performance, sample size for test/training, expert adjudication, MRMC study, standalone performance, ground truth details) are not applicable or not provided in this 510(k) summary. The summary focuses on comparing the new device's features and potential risks to its predicates.

Here's a breakdown based on the provided document:

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

• Acceptance Criteria: Not explicitly stated as this is a substantial equivalence submission for a software upgrade/enhancement, not a de novo device with novel performance claims requiring specific thresholds. The "acceptance criteria" here is implicitly "performing as well as predicate devices" and "not introducing new safety risks."
• Reported Device Performance: No specific quantitative performance metrics (e.g., sensitivity, specificity, accuracy) are reported for Volume Viewer Plus itself. The claim is that it "performs as well as devices currently on the market" (i.e., the predicate devices).

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

• Sample Size for Test Set: Not specified. The submission does not detail a clinical test set for performance validation in the way a novel diagnostic device might.
• Data Provenance: Not specified. Given it's a software for existing imaging modalities, it would utilize DICOM images, but no specific dataset or its origin is mentioned.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.
• Reason: This information is typically required for studies demonstrating diagnostic accuracy. As this submission focuses on substantial equivalence of image processing/viewing software, such a clinical validation study with expert ground truth is not elaborated upon in the summary.

4. Adjudication method for the test set

• Not specified. (See explanation for point 3).

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

• MRMC Study: No, an MRMC comparative effectiveness study is not mentioned or implied in this 510(k) summary.
• Reason: Volume Viewer Plus is described as software for 3D processing, review, and analysis of images, providing tools for clinicians. It is not an AI-assisted diagnostic algorithm intended to improve human reader performance in the typical sense that an AI CADe or CADx device would claim. Its enhancements are in visualization, segmentation, and workflow, which are intended to provide "clinically relevant information" but not explicitly quantified as a human reader performance uplift through an MRMC study in this document.

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

• Standalone Performance: No, a standalone algorithm performance evaluation is not mentioned.
• Reason: This device is a software package for clinicians to use, not an autonomous AI algorithm that performs diagnosis independently. It's an "accessory to Computed Tomography System" and "Magnetic Resonance diagnostic device."

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

• Not specified. (See explanation for point 3).

8. The sample size for the training set

• Not applicable/Not specified. This is a software package whose development would typically involve software engineering and validation against specifications, rather than machine learning model training on a "training set" in the context of AI.

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

• Not applicable/Not specified. (See explanation for point 8).

Summary of Device and Regulatory Context:

The Volume Viewer Plus submission is a 510(k) seeking clearance for a software product that provides enhanced 3D processing, review, and analysis capabilities for various medical imaging modalities. The core of the submission relies on demonstrating substantial equivalence to existing cleared devices (Advantage Windows Volume Rendering Option K972399 and CT Colonography / Navigator2 K012313). The justification for clearance is that the new features are enhancements to existing functionalities and do not introduce new safety risks, while performing as well as the predicates. The documentation focuses on software development and risk management processes rather than a clinical performance study with specific performance metrics and gold standards.

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CT Colonography II is a CT image analysis software package which allows the visualization of 2D and 3D medical image data of the colon derived from DICOM 3.0 compliant CT scans for the purpose of screening of a colon to detect polyps, masses, cancers, and other lesions. It provides functionality for 2D/3D rendering, bookmarking of suspected lesions, synchronized viewing of the 2D, 3D and 360 dissection views, and an object oriented endoluminal display. In comparison to Colonoscopy, this tool has an advantage of depth penetration due to its 3D presentation capability. It is intended for use by Radiologists, Clinicians, and referring Physicians to process, render, review, archive, print and distribute colon image studies.

CT Colonography II is a CT image analysis software package which allows the visualization of 2D and 3D medical image data of the colon derived from DICOM 3.0 compliant CT scans for the purpose of screening of a colon to detect polyps, masses, cancers, and other lesions. It provides functionality for 2D/3D rendering, bookmarking of suspected lesions, synchronized viewing of the 2D, 3D and 360 dissection views, and an object oriented endoluminal display.

The provided text is a 510(k) summary for the GE Medical Systems CT Colonography II device. It describes the device, its indications for use, and its substantial equivalence to a predicate device. However, it does not contain any information regarding acceptance criteria or the study that proves the device meets those criteria.

Specifically, the document focuses on:

• Product Identification: Name, classification, manufacturer, distributor, and predicate device.
• Device Description: What the device is and its functions (visualization of 2D/3D medical image data of the colon, bookmarking, synchronized viewing, endoluminal display).
• Indications for Use: Screening of a colon to detect polyps, masses, cancers, and other lesions.
• Comparison with Predicate: States substantial equivalence to the CT Colonography (K023943).
• Adverse Effects on Health: Identifies potential hazards managed through software development, validation, verification processes, and adherence to standards.
• Conclusions: No new safety risks, performs as well as existing devices, equivalent to the predicate.
• FDA Clearance Letter: Official communication from the FDA confirming substantial equivalence.

Therefore, I cannot provide the requested table or additional information as the document does not contain the necessary data regarding acceptance criteria, performance studies, sample sizes, expert involvement, ground truth establishment, or comparative effectiveness details.

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CardIQ Analysis III is a CT image analysis software package, which allows the visualization of 2D and 3D medical image data of the heart derived from DICOM 3.0 compliant CT scans for the purpose of cardiovascular disease assessment. It provides functionally for 2D/3D rendering, assessment of calcified and non-calcified plaque to determine the densities of the plaque within a coronary artery, ventricular function of the heart, and measurement tools to detect coronary artery stenosis. This product can be used to aid a trained physician for to process, render, review, archive, print and visualizing cardiac anatomy and coronary vessels. CardIQ Analysis III will run on the AW workstation, scanner operator console and PACS system.

CardIO Analysis III is a post processing software option that can be used in the analysis of CT angiographic images to display structures of the heart in a MIP, reformat or volume rendering view. When the heart is displayed the software has the ability to measure the diameter of the vessel or hounsfield units within a coronary arteries to determine the size of a vessel or plaque density within a vessel. Functional parameters of the heart can also be determined when images of end systole and end diastole are present. Diarneters, densities, functional parameters and images can all be printed to reports or saved to the AW workstation. It is a software option for the GE family of LightSpeed multi-slice CT scanners.

The provided text for K041267 describes a device called CardIQ Analysis III, a post-processing software option for analyzing CT angiographic images of the heart. However, it does not include specific information regarding acceptance criteria, a dedicated study proving device performance against those criteria, or details such as sample sizes, ground truth establishment, expert qualifications, or comparative effectiveness studies.

The document primarily focuses on establishing substantial equivalence to previously cleared predicate devices (CardIQ Analysis II and CardIQ Function) based on functional features and safety. It states that "The CardIQ Analysis III does not result in any new potential safety risks and performs as well as devices currently on the market." This suggests that the primary "proof" of meeting acceptance criteria for this 510(k) submission relies on the established performance and safety of its predicate devices, rather than a new, detailed performance study with explicit acceptance criteria.

Therefore, many of the requested details cannot be extracted from the provided text.

Here's a breakdown of what can be inferred or directly stated, and what is missing:

1. Table of acceptance criteria and reported device performance:
   • Acceptance Criteria: Not explicitly stated in terms of quantitative metrics (e.g., sensitivity, specificity, accuracy, measurement error). The "acceptance criteria" here implicitly refer to demonstrating equivalence in functionality and safety to predicate devices.
   • Reported Device Performance: No quantitative performance metrics are provided for CardIQ Analysis III itself. The performance is stated to be "as well as devices currently on the market," referring to its predicates.

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

   • Sample size: Not specified.
   • Data provenance: Not specified.

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

   • Not specified.

4. Adjudication method for the test set:

   • Not specified.

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 mentioned. The document focuses on the device's standalone features as a visualization and analysis tool, not on its impact on human reader performance in an MRMC study.

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

   • The device is a standalone software package for analysis and visualization. However, no specific "standalone performance study" with quantitative metrics is described beyond the assertion that it performs "as well as" its predicates. The device's "performance" is inherently linked to its ability to process, render, and display data for a "trained physician," making the "human-in-the-loop" an integral part of its intended use.

7. The type of ground truth used:

   • Not specified. Given the nature of the device (analysis and visualization features consistent with predicates), an explicit "ground truth" for a performance study is not detailed in this submission. Its equivalence to predicates likely implies the functionality was deemed acceptable based on engineering verification and validation against specified requirements derived from the predicate devices, rather than a clinical ground truth study.

8. The sample size for the training set:

   • Not applicable as this is a 2004 510(k) for a software update to an existing product line. It details post-processing software, not a machine learning or AI algorithm that would typically require a "training set" in the modern sense. The term "training set" for AI/ML algorithms is not relevant to this historical submission for a traditional software device.

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

   • Not applicable (see point 8).

Summary of Study Information Provided:

The provided document does not describe a specific clinical or performance study for CardIQ Analysis III with defined acceptance criteria. Instead, the submission relies on demonstrating substantial equivalence to existing predicate devices (CardIQ Analysis II, K020796; and CardIQ Function, K013422). The "study" implicitly involves a comparison of the functional features and safety considerations with those of the predicate devices. The conclusion that "CardIQ Analysis III does not result in any new potential safety risks and performs as well as devices currently on the market" serves as the proof for meeting the implied "acceptance criteria" of equivalence. The underlying data and studies for the predicate devices would have established their performance, which is then extrapolated to the new device through the equivalence claim.

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The T-Wave Alternans (TWA) Algorithm Option is to be used in a hospital, doctor's office, or clinic environment by competent health care professionals for recording ST-T wave morphology fluctuations for patients who are undergoing Cardiovascular disease testing.

The T-Wave alternans analysis is intended to provide only the measurements of the fluctuations of the ST-T-waves. The T-Wave alternans measurements produced by the T-Wave Alternans analysis are intended to be used by qualified personnel in evaluating the patient in conjunction with the patients clinical history, symptoms, other diagnostic tests, as well as the professional's clinical judgment. No interpretation is generated.

T-Wave Alternans (TWA) Algorithm Option is a software algorithm that runs on GE Medical Systems Information Technologies' electrocardiographs.

The provided text describes the T-Wave Alternans (TWA) Algorithm Option, a software algorithm for electrocardiographs. However, the document (K023380) is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study report with specific acceptance criteria and performance data.

Therefore, much of the requested information regarding acceptance criteria, specific study details, sample sizes, ground truth establishment, expert qualifications, adjudication methods, and MRMC effectiveness studies is not available within this document. The document primarily focuses on regulatory compliance and the intended use of the device.

Here's an attempt to answer the questions based on the available information, with clear indications of what is not provided:

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

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

• Sample size for the test set: Not provided.
• Data provenance: Not provided. (The document mentions "Verification and Validation" but does not detail the specific datasets used for these activities.)

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)

• Number of experts: Not provided.
• Qualifications of experts: Not provided.

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

• Adjudication method: 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

• MRMC study done: Not provided. The document focuses on the algorithm's performance itself and its equivalency to a predicate device, not on its impact on human reader performance.
• Effect size of human reader improvement with AI: Not applicable, as an MRMC study is not mentioned.

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

• Standalone study done: The document implies standalone testing in that it describes the algorithm as a "software algorithm that runs on GE Medical Systems Information Technologies' electrocardiographs" and states "Verification and Validation" were performed. However, specific details of a formal standalone performance study with metrics are not explicitly provided. The comparison is often implicitly against the performance of the predicate device's existing algorithm.

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

• Type of ground truth: Not provided.

8. The sample size for the training set

• Sample size for the training set: Not provided. The document focuses on regulatory approval, not on the developmental aspects like training data for the algorithm.

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

• How ground truth for training set was established: Not provided.

Summary of available information:

The 510(k) summary (K023380) primarily indicates that the device underwent standard quality assurance measures, including:

• Risk Analysis
• Requirements Reviews
• Design Reviews
• Code inspections
• Verification and Validation

These measures were deemed sufficient to demonstrate that the T-Wave Alternans (TWA) Algorithm Option is "as safe, as effective, and performs as well as the predicate software option offered with device, CASE 8000 Exercise Testing System." The document does not disclose the detailed methodologies, datasets, or specific performance metrics from these verification and validation activities.

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The intended use of the SEER Light Compact Digital Holter Recorder is to acquire ambulatory 2 or 3 channels of ECG signal from the chest surface of pediatric or adult patients for no longer than 24 hours. The device stores this data along with patient demographic information to on board flash memory. It does not perform any analysis on the ECG data.

The SEER Light Compact Digital Holter Recorder is intended to be used under the direct supervision of a licensed healthcare practitioner, by trained operators in a hospital or medical professional's facility.

The SEER Light Compact Digital Holter Recorder is designed to acquire ambulatory 2 or 3 channels of ECG signal from the chest surface for no longer than 24 hours. The device stores the acquired ECG data in its on-board 32 megabytes of flash memory. Additionally, the SEER Light controller downloads patient demographic information into the SEER Light recorder and checks the signal quality of the ECG data at hookup time via isolated, infra-red communications. At the end of the recording the SEER Light controller is connected to the SEER Light recorder by cable and the stored ECG data is transferred to it and onto a standard compact flash memory card.

Here's an analysis of the provided text regarding the acceptance criteria and study for the SEER Light Compact Digital Holter Recorder:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly define specific numerical acceptance criteria for performance metrics. Instead, it states that the device "complies with the voluntary standards as detailed in Section 9 of this submission" (Section 9 is not provided here) and that the "results of these measurements demonstrated that the SEER Light Compact Digital Holter Recorder is as safe, as effective, and performs as well as the predicate device."

Therefore, the acceptance criteria are implicitly tied to meeting the performance of the predicate device (K001317 Aria Digital Holter Recorder®) and relevant voluntary standards. Specific quantitative performance data from comparative testing are not detailed in this summary.

Important Note: Without access to "Section 9 of this submission" and the specific test results comparing the SEER Light to the predicate device, it's impossible to provide granular numerical acceptance criteria or performance metrics specific to ECG signal quality, data storage integrity, or accuracy that would typically be expected for such a device. This summary focuses on demonstrating equivalence rather than establishing new performance benchmarks.

2. Sample Size Used for the Test Set and Data Provenance

The provided text does not specify the sample size used for any test set or provide details on data provenance (e.g., country of origin, retrospective/prospective). It only broadly mentions "software and hardware testing," "safety testing," and "environmental testing" as part of the quality assurance measures.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The provided text does not mention the use of experts or the establishment of ground truth for any test set in the context of clinical performance or diagnostic accuracy, as the device states it "does not perform any analysis on the ECG data." Its function is purely for acquisition and storage.

4. Adjudication Method

Given that no experts or clinical performance evaluations involving diagnostic interpretation are mentioned, there is no adjudication method described in the provided document.

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

No MRMC comparative effectiveness study was done or is mentioned. The device, by its stated intended use, does not perform analysis on ECG data, so a study evaluating human readers' improvement with or without AI assistance would not be applicable.

6. Standalone Performance Study

The provided text does not describe a standalone (algorithm only without human-in-the-loop performance) study in the context often associated with diagnostic AI algorithms. The device itself is a standalone recorder, but its "performance" is based on its ability to acquire and store ECG signals reliably, not on its analytical capabilities. The testing mentioned (software, hardware, safety, environmental, final validation) would fall under performance testing, but not in the context of an "algorithm only" diagnostic performance study.

7. Type of Ground Truth Used

The concept of "ground truth" as typically used for diagnostic algorithms (e.g., pathology, outcomes data, expert consensus) does not apply to this device's stated function. The device acquires ECG signals; it does not interpret them. Therefore, its "ground truth" would relate to the accuracy of the recorded signal itself (e.g., comparison to a reference ECG machine for signal fidelity, absence of artifact, proper data storage). However, the document does not elaborate on how this type of ground truth was established.

8. Sample Size for the Training Set

The provided text does not mention a training set sample size. This device is a hardware recorder, not an AI/machine learning model that typically requires a training set.

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

As this is a hardware device for ECG data acquisition and not an AI/machine learning model, the concept of a "training set" and establishing "ground truth for a training set" as typically understood in AI/ML development is not applicable. The device's "performance" is validated through engineering and functional testing against specifications and standards, not through training on data with established ground truth for diagnostic purposes.

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AccuSketch Cardiac Quantitative Analysis System w/ Advanced Analysis Components is intended for use under the direct supervision of a licensed healthcare practitioner or by personnel trained in its proper use. AccuSketch is intended to provide and document an objective quantification of coronary artery stenosis and measurement and quantification of left ventricular function. Also provided is the ability to digitize and store video images and the ability to interactively annotate and report current and post procedural patient cardiac status.

The AccuSketch Cardiac Quantitative Analysis System w/ Advanced Analysis Components is a PC based software system comprised of 4 individual programs used to view, capture/print, analyze and annotate images from cardiac catheterization procedures. AccuSketch is offered as a complete turn-key system or can be ported into other GE cardiac image devices for image analysis. The AccuSketch is a Personal Computer (PC) based software system designed to be permanently installed in a hospital in or near the cardiac catheterization laboratory. AccuSketch is comprised of four individual programs responsible for a specific function. Their purpose is to view, capture/print, analyze and annotate images from cardiac catheterization procedures. The CardioTree is an editable coronary tree tool used to electronically annotate and document the anatomy of the patient's vessels.

The provided text describes a 510(k) submission for the "AccuSketch Cardiac Quantitative Analysis System w/ Advanced Analysis Components." This submission demonstrates substantial equivalence to predicate devices rather than proving specific performance against acceptance criteria in a standalone study. Therefore, much of the requested information regarding acceptance criteria, specific performance metrics, sample sizes, expert involvement, and ground truth establishment from a dedicated performance study is not explicitly available within this document.

However, I can extract information related to the device description, intended use, and the general approach to demonstrating effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance:

As this is a 510(k) submission focused on substantial equivalence, explicit "acceptance criteria" with numerical targets and reported performance values from a dedicated performance study are not detailed in the provided text. The document states that the device "employs the same functional scientific technology as its predicate devices" and "is as safe, as effective, and performs as well as the predicate devices," implying a comparison to the established performance of those predicates rather than a new set of independent criteria.

2. Sample Size Used for the Test Set and Data Provenance:

Not explicitly mentioned. The document focuses on demonstrating equivalence to predicate devices and describes internal testing phases (unit, integration, final acceptance, performance, safety, environmental testing) but does not provide details on specific clinical test sets, their sizes, or data provenance (e.g., country of origin, retrospective/prospective).

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts:

Not explicitly mentioned. Given the nature of a 510(k) addressing substantial equivalence, a formal ground truth establishment by external experts for a test set is not detailed. The device is intended to "aid the Cardiologist or trained technician," suggesting clinical professionals are the intended users who would interpret outputs.

4. Adjudication Method for the Test Set:

Not explicitly mentioned.

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

Not explicitly mentioned. The provided text does not describe an MRMC study or any quantitative effect size of human readers improving with AI vs. without AI assistance.

6. Standalone Performance Study (Algorithm Only Without Human-in-the-Loop Performance):

Not explicitly mentioned. The document refers to "requirements reviews," "design reviews," and various forms of testing (unit, integration, final acceptance, performance, safety, environmental), which are internal development and quality assurance measures. These are not typically standalone clinical performance studies. The device's stated intended use is to "aid the Cardiologist or trained technician," suggesting a human-in-the-loop design.

7. Type of Ground Truth Used:

Not explicitly mentioned for a formal performance study. The device's function involves "objective quantification of a patient's Left Ventricular function" and "objective quantification of coronary artery stenosis." For these types of measurements in the clinical context, the "ground truth" would typically be established by expert interpretation/consensus or potentially by comparison to other established quantitative methods. However, the document doesn't detail how this was specifically handled for a ground truth in a clinical study.

8. Sample Size for the Training Set:

Not applicable or not mentioned. The document describes a traditional software system for analysis rather than a machine learning/AI model that undergoes a "training" phase with a specific dataset. The "advanced analysis components" refer to software features, not a continuously learning algorithm.

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

Not applicable (as it's not described as an AI/ML training set).

Summary of available information from the document:

• Device: AccuSketch Cardiac Quantitative Analysis System w/ Advanced Analysis Components.
• Intended Use: Aid cardiologists or trained technicians in providing and documenting objective quantification of Left Ventricular function and coronary artery stenosis, digitize/store video images, and annotate/report cardiac status.
• Demonstration of Effectiveness: By demonstrating substantial equivalence to predicate devices (CardioTrace K912829; MUSE Cardiovascular Information System with Accusketch K992937). The device employs the same functional scientific technology and is claimed to be as safe, effective, and perform as well as the predicates.
• Quality Assurance Measures (Internal Testing): Risk Analysis, Requirements Reviews, Design Reviews, Unit-level testing (Module verification), Integration testing (System verification), Final acceptance testing (Validation), Performance testing, Safety testing, Environmental testing. These are internal development and verification processes, not a formal clinical performance study demonstrating acceptance criteria.

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Indicated for use in data collection and clinical information management through networks with independent bedside devices.

The Unity Network ID is not intended for monitoring purposes, nor is the Unity Network ID intended to control any of the clinical devices (independent bedside devices/ information systems) it is connected to.

The Unity Network ID system communicates patient data from sources other than GE Medical Systems Information Technologies equipment to a clinical information system, central station, and/or GE Medical Systems Information Technologies patient monitors.

The Unity Network ID acquires digital data from eight serial ports, converts the data to Unity Network protocols, and transmits the data over the monitoring network to a Unity Network device such as a patient monitor, clinical information system or central station.

The provided documentation does not contain information about acceptance criteria, device performance metrics, or a study that evaluates the device's diagnostic performance for medical insights in the way one would typically assess an AI/ML medical device.

The GE Medical Systems Information Technologies Unity Network ID (K021454) is a data communication and management system, not a diagnostic device that generates interpretations or analyses of patient data. Its purpose is to acquire digital data from various medical devices, convert it to a common protocol, and transmit it to other systems like patient monitors, clinical information systems, or central stations.

The "Test Summary" section describes quality assurance measures applied during development, such as risk analysis, requirements reviews, design reviews, and various levels of testing (unit, integration, acceptance, performance, safety, environmental). However, these are developmental tests to ensure the system functions as designed and is safe and effective in its intended role as a data conduit, not to assess its ability to provide clinical insights or make diagnoses.

Therefore, many of the requested categories (e.g., sample size for test set, number of experts for ground truth, adjudication method, MRMC study, standalone performance, type of ground truth, training set information) are not applicable to this device and are not present in the provided submission.

Based on the provided text, here’s a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Not applicable / Not provided. The device is a data communication system. The testing described includes unit, integration, and final acceptance testing, as well as performance, safety, and environmental testing. These types of tests typically involve controlled lab environments and specific test cases designed to test system functionality, communication integrity, and adherence to power/environmental standards, rather than a "test set" of patient data in the context of diagnostic performance. There is no mention of patient data being used for device performance evaluation in this context.

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 / Not provided. Ground truth for diagnostic accuracy is not relevant for this type of device.

4. Adjudication method (e.g. 2+1, 3+1, none) 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 / Not provided. This device is not an AI/ML diagnostic tool; it's a data network interface.

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

• Not applicable / Not provided. The device's function is purely data transmission and conversion; it does not provide an "algorithm only" diagnostic output.

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

• Not applicable / Not provided. The "truth" for this device relates to whether data is accurately acquired, converted, and transmitted without corruption, and whether it functions according to its specifications and regulatory standards. There is no diagnostic ground truth.

8. The sample size for the training set

• Not applicable / Not provided. This device is not an AI/ML model that would require a "training set" of data in that sense.

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

• Not applicable / Not provided.

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The Dash 3000/4000 Patient Monitor is intended for use under the direct supervision of a licensed healthcare practitioner. The intended use of the system is to monitor physiologic parameter data on adult, pediatric and neonatal patients. The Dash is designed as a bedside, portable, and transport monitor that can operate in all professional medical facilities and medical transport modes including but not limited to: emergency department, operating room, post anesthesia recovery, critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or neonatal intensive care areas located in hospitals, outpatient clinics, freestanding surgical centers, and other alternate care facilities, intra-hospital patient transport, inter-hospital patient transport via ground vehicles (i.e., ambulance, etc.) and fixed and rotary winged aircraft, and pre-hospital emergency response.

Physiologic data includes but is not restricted to: electrocardiogram, invasive blood pressure, noninvasive blood pressure, pulse, temperature, cardiac output, respiration, pulse oximetry, carbon dioxide, oxygen, and anesthetic agents as summarized in the operator's manual.

The Dash 3000/4000 Patient Monitor is also intended to provide physiologic data over the Unity network to clinical information systems and allow the user to access hospital data at the point-of-care.

This information can be displayed, trended, stored, and printed.

The Dash 3000/4000 Patient Monitor was developed to interface with non-proprietary third party peripheral devices that support serial data outputs.

The Dash 3000/4000 Patient Monitor is a device that is designed to be used to monitor, display, and print a patient's basic physiological parameters including: electrocardiography (ECG), invasive blood pressure, non-invasive blood pressure, oxygen saturation, temperature, impedance respiration, end-tidal carbon dioxide, oxygen, nitrous oxide and anesthetic agents. Other features include arrhythmia, cardiac output, cardiac and pulmonary calculations, dose calculations, PA wedge, ST analysis, and interpretive 12 lead ECG analysis (12SL). Additionally, the network interface allows for the display and transfer of network available patient data.

The provided document refers to the K020290 submission for the GE Medical Systems Information Technologies Dash 3000/4000 Patient Monitor. This submission is a 510(k) premarket notification, which means the device is seeking substantial equivalence to a predicate device rather than presenting novel acceptance criteria or a detailed clinical study for efficacy.

Therefore, the document does NOT contain the specific information requested in the prompt regarding:

• A table of acceptance criteria and reported device performance.
• Sample sizes, data provenance, number of experts, adjudication methods, or ground truth details for a test set.
• Information on multi-reader multi-case (MRMC) comparative effectiveness studies.
• Details of a standalone algorithm performance study.
• Sample size and ground truth establishment for a training set.

Instead, the document focuses on the regulatory aspects of a 510(k) submission, confirming the device's intended use, classification, and that it "employs the same functional scientific technology as its predicate devices."

The "Test Summary" section lists quality assurance measures applied to the development, which are general engineering and quality management practices, not specific clinical performance studies with acceptance criteria as typically understood for AI/ML devices. These measures include:

• Risk Analysis
• Requirements Reviews
• Design Reviews
• Testing on unit level (Module verification)
• Integration testing (System verification)
• Final acceptance testing (Validation)
• Performance testing
• Safety testing
• Environmental testing

The conclusion states: "The results of these measurements demonstrated that the Dash 3000/4000 Patient Monitor are as safe, as effective, and perform as well as the predicate device." This is a statement of substantial equivalence, not a report of meeting specific numerical performance criteria from a clinical study.

In summary, the provided document does not contain the detailed study results and acceptance criteria as requested because it is a 510(k) summary for a patient monitor, which relies on demonstrating substantial equivalence to a predicate device rather than presenting novel clinical performance data against predefined acceptance criteria in the manner expected for an AI/ML device.

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Advantage Sim 6.0 is used to prepare geometric and anatomical data relating to a proposed external beam radiotherapy treatment prior to dosimetry planning.

Anatomical volumes can be defined in three dimensions using a set of CT images acquired with the patient in the proposed treatment position. The geometric parameters of a proposed treatment field are selected to allow non-dosimetric, interactive optimization of field coverage.

Defined anatomical structures and geometric treatments fields are displayed on transverse CT images, on reformatted sagittal, coronal or oblique images, on 3 D views created from the CT images, or on a beam eye's view display with or without the display of defined structures with or without the display of digittaly reconstructed radiograph.

Advantage Sim 6.0. is used to prepare geometric and anatomical data relating to a proposed external beam radiotherapy treatment prior to dosimetry planning.

Anatomical volumes can be defined in three dimensions using a set of CT images acquired with the patient in the proposed treatment position. The geometric parameters of a proposed treatment field are selected to allow nondosimetric, interactive optimization of field coverage.

Defined anatomical structures and geometric treatments fields are displayed on transverse CT images, on reformatted sagittal, coronal or oblique images, on 3 D views created from the CT images, or on a beam eye's view display of defined structures with or without the display of defined structures with or without the display of digittaly reconstructed radiograph.

The GE Advantage Sim 6.0 has to ensure relations with the following external systems:

Data Export: Image, volume and plan data are exported in accordance with DICOM V3.0.

RT Data Import: Image, volume and plan data can be imported in accordance with the RT objects of the DICOM Standard.

Hardcopy: Hardcopy of all displays and plan data can be made at selected magnification on paper or transparency material. Users can print DRR to film at user defined SID if equipped with an Advantage Workstation 6.0. compatible Laser camera, with the appropriate AW Laser Camera Interface. Hardcopy of beam parameters and of isocenter coordinates, using IEC standard, can be made on an optional Postscript printer.

Archiving: Advantage Sim 6.0 can save DICOM images and DICOM RT objects on single-session DICOM CD R using an optional CD ROM writer.

Configuration Requirements: Advantage Sim 6.0 can be installed only on validated Advantage Workstation with single or dual color monitor.

The provided text is a 510(k) summary for the Advantage Sim 6.0 device, a radiation therapy simulation system. It primarily focuses on demonstrating substantial equivalence to a predicate device (Advantage Sim 1.2) rather than presenting a performance study with detailed acceptance criteria and results for the new device.

Therefore, much of the requested information regarding acceptance criteria, specific performance metrics, sample sizes for test and training sets, expert qualifications, and adjudication methods for a standalone performance study are not explicitly described in this document. The document primarily relies on comparing the new device's functionality to existing, legally marketed predicate devices to establish safety and effectiveness.

Here's a breakdown of what can be extracted and what is not available from the provided text:

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

This information is not explicitly provided in the format of acceptance criteria and device performance results. The document states:

• "Advantage Sim 6.0 provides images comparable to the predicate device."
• "Both of Advantage Sim 6.0 and Advantage Sim 1.2 provides complete volume definition and geometric beam placement capability for radiotherapy. It is then able to compute a DRR for any type of patient set-up and fully replaces a classic simulator."

These statements serve as qualitative assessments of performance and equivalence rather than quantifiable acceptance criteria.

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

This information is not provided. The document makes no mention of a specific test set or data used for a performance study.

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)

This information is not provided. There is no mention of experts or ground truth establishment for a test set.

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

This information is not provided. As there's no described test set or expert review, no adjudication method is mentioned.

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

A MRMC comparative effectiveness study is not mentioned. This device is a simulation system, not an AI-assisted diagnostic or workflow tool for human readers in the context of improving their performance.

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

A standalone performance study with specific metrics is not explicitly described. The document focuses on demonstrating substantial equivalence to a predicate device, as opposed to proving novel performance against specific quantitative criteria. The statements about "comparable images" and "complete volume definition" imply functionality but not a formal standalone study with performance metrics.

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

This information is not provided. Since no specific performance study creating ground truth is described, this detail is absent.

8. The sample size for the training set

This information is not provided. There is no mention of a training set as this is not an AI/ML device that requires training data in the modern sense.

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

This information is not provided, as no training set or its ground truth establishment is mentioned.

In summary:

The provided 510(k) summary for the Advantage Sim 6.0 primarily focuses on demonstrating substantial equivalence to a predicate device (Advantage Sim 1.2) by comparing its intended use and functionality. It states that "Advantage Sim 6.0 provides images comparable to the predicate device" and details its capabilities for "complete volume definition and geometric beam placement." However, it does not contain the details of a specific performance study with quantifiable acceptance criteria, sample sizes, expert qualifications, or ground truth methods that would be typically associated with proving a device meets detailed acceptance criteria through a formalized study. The document emphasizes risk management, software development/validation, and verification plans as part of ensuring safety and effectiveness.

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