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The Smith & Nephew Tablet Application is indicated for use to provide wireless control of Smith & Nephew compatible surgical and endoscopic devices within the operating room including camera/camera control unit, patient information system, mechanical resection system, fluid management system and RF coblation system. These controls consist of adjusting parameter settings only.

The Smith & Nephew Tablet Application is a software application that provides a Wi-Fi connection between compatible medical devices. Once connected the Tablet Application has the ability to provide limited remote control to the connected devices.

The provided document is a 510(k) premarket notification for the Smith & Nephew Tablet Application, which is a software application for wireless control of surgical and endoscopic devices. However, it does not contain specific acceptance criteria, performance data, or details about a study proving the device meets those criteria. The document focuses on demonstrating substantial equivalence to a predicate device (K192876) based on technological characteristics and intended use.

Therefore, I cannot provide the requested information from the given text.

Here's why and what information is missing:

1. Table of acceptance criteria and reported device performance: The document states that "Testing demonstrated that the Smith & Nephew Tablet Application has met the performance specifications" (Page 5, Section H). However, it does not list what those specific "performance specifications" (acceptance criteria) are, nor does it provide the reported device performance against those criteria (e.g., specific accuracy, latency, reliability metrics).
2. Sample size and data provenance: There is no mention of a test set, its sample size, or its provenance (e.g., country of origin, retrospective/prospective).
3. Number/qualifications of experts for ground truth: Since there's no mention of a clinical study or performance evaluation involving human interpretation of data where ground truth would be established by experts, this information is absent.
4. Adjudication method: Similarly, no adjudication method is described because no expert-based ground truth establishment is detailed.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: The document does not describe any study involving human readers or AI assistance for human readers. The device's function is to control surgical parameters, not to assist in image interpretation or diagnosis.
6. Standalone performance: While the software itself performs wirelessly, the concept of "standalone performance" in the context of an AI device (i.e., algorithm only without human-in-the-loop performance) is not applicable here, as its function is control, not interpretation or diagnosis. No specific performance metrics like sensitivity, specificity, or AUC for a diagnostic task are provided.
7. Type of ground truth: No ground truth is described because the device's function is control, not diagnosis or interpretation that would require a ground truth for evaluation. The "performance specifications" it met would likely relate to functional requirements, responsiveness, and connectivity, not diagnostic accuracy.
8. Sample size for the training set: There is no mention of a training set as this is not an AI/ML diagnostic or predictive algorithm.
9. How ground truth for the training set was established: Not applicable, as there's no training set mentioned.

In summary, the provided document is a 510(k) summary for a device that controls surgical equipment wirelessly, not an AI/ML diagnostic or interpretative device. Therefore, the types of studies and performance metrics typically associated with AI/ML devices (like those requiring ground truth, expert readers, MRMC studies, etc.) are not present in this submission. The "performance data" mentioned (Page 5, Section H) refers to "Software validations" and "Cybersecurity testing," which are distinct from the type of performance data requested in the prompt for AI/ML devices.

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CARESTREAM Image Suite is an image management system whose intended use is to receive, process. review. display, print and archive images and data from all imaging modalities,

Tablet Viewer Software for Image Suite is used for patient management by clinicians in order to access and display patient data. medical reports, and medical images for different modalities including CR. DR. CT. MR, and US.

Tablet Viewer Software for Image Suite provides wireless and portable images for remote reading or referral purposes from web browsers including usage with validated mobile device is not intended to replace the full Mini-PACS and should be used only when there is no access to the full Mini-PACS Web Viewer.

This excludes mammography applications in the United States.

CARESTREAM Tablet Viewer Software for Image Suite is an optional feature for Image Suite Mini-PACS users. The software technology uses HTML5 which allows a browserenabled mobile device to run the software application. The user is able to access patient images and study reports from an iPad 2 mobile device anywhere through a wireless network. Tablet Viewer Software for Image Suite has a simple GUI for viewing and includes some fundamental tools such as zoom, pan, windowing, basic measurements, cine, etc. Tablet Viewer Software for Image Suite functions as an extension to Image Suite.

CARESTREAM Image Suite is a stand-alone, self-contained radiographic imaging system designed to provide a low-cost platform to manage medical images, reports, patient/exam information and workflow in small clinics. The system performs capture, processing, review, archive, and printing of radiographic images as well as report writing and printing and is designed to run on a PC workstation. CARESTREAM Image Suite is designed to be simple and intuitive to both use and service.

CARESTREAM Image Suite connects with hardware including multiple radiographic image capture devices (CR and / or DR detectors) attached to a PC workstation with either a standard or a high-resolution monitor. CARESTREAM Image Suite is designed as a hardware-independent system and may be interfaced with verified and validated imaging modalities from both Carestream Health and 3rd party vendors, as well as Carestream Health PACS systems, and other 3rd party PACS systems. The Image Suite system can directly acquire an image from Carestream Health acquisition devices and is PC and monitor independent.

This document describes the Carestream Tablet Viewer Software for Image Suite. However, it does not contain a study with detailed acceptance criteria and reported device performance in the format requested. The provided text notes that a "Clinical Assessment of Tablet Viewer Software for Image Suite on the Apple iPad 2" was performed, along with bench testing and functional QA testing, but it does not present the results of these assessments in a structured acceptance criteria table or provide the specific details of a clinical study as requested.

Therefore, many of the requested fields cannot be filled.

Here's what can be extracted and what cannot:

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

The document mentions several types of testing but does not provide a formal table of acceptance criteria with corresponding performance metrics.

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: Not specified for the "Clinical Assessment." The bench testing would likely not involve a case sample size.
• Data Provenance: Not specified.
• Retrospective/Prospective: Not specified.

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 specified.
• Qualifications of Experts: Not specified.

4. Adjudication method (e.g. 2+1, 3+1, none) 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 specified. The assessment described does not appear to be an MRMC comparative effectiveness study involving AI assistance for human readers. This device is a viewer, not an AI diagnostic tool.

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

• Not applicable in the typical sense as this is a viewing software, not an AI algorithm performing diagnostic tasks. The "standalone" performance here would relate to its functionality as a viewer, which was generally described as "tested" or "demonstrated suitability."

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

• Not specified in detail. The "Clinical Assessment" likely involved expert review of the displayed images, but the method for establishing ground truth (e.g., comparison to full PACS, original diagnostic reports) is not elaborated upon.

8. The sample size for the training set:

• Not applicable. This device is viewing software, not an AI algorithm that undergoes training.

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

• Not applicable, as there is no training set for this viewing software.

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Table is a software application used for the display and 3D visualization of medical image files from scanning devices such as CT and MRI. It is intended for use by radiologists, clinicians, referring physicians and other qualified individuals to retrieve, process, render, review, and assist in diagnosis, utilizing standard PC hardware.

This device is not indicated for mammography use.

Table is a volumetric imaging software designed specifically for clinicians, doctors, physicians, and other qualified medical professionals. The software runs in Windows operating systems and visualizes medical imaging data on the computer screen. Users are able to examine anatomy on a computer screen and use software tools to move and manipulate images by turning, zooming, flipping, adjusting contrast and brightness, cutting, and slicing using either touch control or a mouse. The software also has the ability to perform measurements of angle and length. There are multiple tools to annotate and otherwise mark areas of interest on the images. Additionally, Table has the ability to demonstrate pathology examples of patient data for educational purposes.

The provided 510(k) summary (K140093) describes the Anatomage Table as a volumetric imaging software for 3D visualization of medical image files (CT, MRI) for diagnosis assistance.

No specific quantitative acceptance criteria are explicitly stated in the provided document. The device's performance is primarily established through a qualitative comparison to a predicate device and general confirmation of stability and designed operation.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document states "Bench testing of the software with predicate software was performed by evaluation of images rendered by Table and predicate software." However, it does not specify the sample size (number of images or cases) used for this test set nor the data provenance (e.g., country of origin, retrospective or prospective nature of the data).

3. Number of Experts and their Qualifications for Ground Truth

The testing and evaluation of the bench test were performed by "an expert in the field of radiology." Only one expert is mentioned. The document does not provide further specific qualifications (e.g., years of experience) for this expert.

4. Adjudication Method for the Test Set

The document mentions evaluation by "an expert." This suggests a single-expert assessment rather than a multi-expert adjudication method (like 2+1 or 3+1). Therefore, the adjudication method appears to be "none" in the sense of multiple experts resolving discrepancies.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The evaluation described is a bench test comparing the software's output to a predicate, assessed by a single expert. There is no mention of human readers improving with AI assistance or without.

6. Standalone Performance Study

Yes, a standalone performance study was done in the sense that the "Table" software's performance was evaluated independently in a "bench testing" scenario, comparing its outputs (rendered images and measurements) with those of a predicate software. This evaluation focused on the algorithm's capabilities without explicit human-in-the-loop performance measurement.

7. Type of Ground Truth Used

The ground truth for the test set was implicitly established through comparison to the predicate software's output and evaluation by a single radiology expert. This leans towards an expert-based assessment of accuracy and equivalence rather than pathology or outcomes data.

8. Sample Size for the Training Set

The document does not provide any information regarding a training set sample size. This suggests that if machine learning was used (which is not explicitly clear for this type of software described), the details of its training are not included in this summary. Given the description, it appears to be more of a deterministic image processing and visualization software rather than an AI/ML-driven diagnostic algorithm.

9. How Ground Truth for the Training Set Was Established

As no training set is mentioned or detailed, the document does not describe how ground truth for a training set was established.

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The Tablet Commander device is for use by patients to collect and transmit general health information, physiological measurements and other data between themselves and a caregiver.

The Tablet Commander makes no diagnosis. Clinical judgment and experience are required to check and interpret the information transmitted. The Tablet Commander is not intended as a substitute for medical care.

The Tablet Commander is a software application. Once installed on a commercially-available device, the Tablet Commander software uses standard communication protocols to exchange information with other medical devices (peripherals). Data collected from the medical devices is transmitted back to a database for review by a caregiver. The Tablet Commander software has a user interface which allows the patient and caregiver to communicate using methods which include questions and answers.

The provided text describes a 510(k) premarket notification for the "Tablet Commander" device, a software application for remote patient monitoring. The application focuses on functional and safety analysis rather than diagnostic accuracy. As such, acceptance criteria and performance metrics related to diagnostic accuracy (like sensitivity, specificity, or AUC) are not applicable or provided in this document.

Here's an analysis based on the information provided:

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

The document does not explicitly state quantitative acceptance criteria in terms of performance metrics like sensitivity, specificity, accuracy, or similar diagnostic measures. Instead, the acceptance is based on the device functioning according to its requirements and specifications, and demonstrating substantial equivalence to predicate devices in terms of intended use, technology, materials, and principles of operation, without introducing new hazards.

The key performance criterion is that the device "functioned according to its requirements and specifications." The validation activities supporting this are described as:

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 does not mention a specific "test set" in the context of clinical data or diagnostic performance. The validation appears to be primarily focused on software functionality and engineering verification and validation (V&V) activities. Therefore, details about the sample size for a test set, data provenance, or whether it was retrospective or prospective are not provided.

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)

Since there is no mention of a "test set" requiring ground truth establishment through expert review for diagnostic purposes, this information is not applicable and not provided in the document.

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

Similarly, as there is no diagnostic "test set" needing ground truth establishment, no adjudication method is described.

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 MRMC comparative effectiveness study was conducted or is mentioned, as the device is a remote patient monitoring system and not an AI-assisted diagnostic tool.

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

The Tablet Commander is described as a "software application" that collects and transmits data for review by a caregiver. It explicitly states, "The Tablet Commander makes no diagnosis," and "Clinical judgment and experience are required to check and interpret the information transmitted." This indicates that the device is not intended for standalone diagnostic performance; it functions as a data collection and transmission tool within a human-in-the-loop system. Therefore, a standalone algorithm-only performance study (in a diagnostic sense) was not done, and would not be relevant to its intended use.

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

For the software validation, the "ground truth" implicitly refers to the device's functional requirements and specifications. The V&V testing confirms that the software behaves as designed and meets these predefined requirements, rather than validating against clinical ground truth like pathology or expert consensus on a diagnosis.

8. The sample size for the training set

The document does not describe the use of machine learning or AI models that would require a "training set" for diagnostic algorithm development. The device is a software application for data management and communication.

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

As there is no mention of a training set for machine learning, this information is not applicable and not provided.

Summary of the study and its purpose:

The study described is not a performance study in the typical sense of evaluating diagnostic accuracy using clinical data. Instead, it is a verification and validation (V&V) study of a software application for remote patient monitoring, conducted as part of a 510(k) premarket notification. The purpose was to demonstrate that the "Tablet Commander" software functions according to its requirements and specifications and that it is substantially equivalent to legally marketed predicate devices without raising new questions of safety or effectiveness.

The key study type conducted was risk-based verification and validation testing of the software, following FDA guidances ("Guidance for the Content of Premarket Submissions for software Contained in Medical Devices" and "General Principles of Software Validation") and using IEC 62304 as a model for software development. This type of study focuses on ensuring the software is correctly built (verification) and that it meets specified user needs (validation) within its intended technical scope, rather than clinical efficacy or diagnostic performance. No clinical tests were conducted because the device was considered to present no new hazards to safety or effectiveness compared to predicate devices.

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Use of the Talley TableGard Pressure Relieving Patient Warming Mattress is indicated for use for patients that may be benefited by the application of heat during surgical procedures to help maintain normothermia. It is intended for use in the operating rooms, recovery rooms, intensive care departments, emergency rooms in hospitals and outpatient clinics to assist patients to maintain normal body temperature. The TableGard mattress also includes alternating air support to relieve pressure against soft tissues during prolonged periods of immobilization.

The TableGard Pressure Relieving Patient Warming Mattress system consists of an alternating air mattress (patient support surface) with air pump, and a connectable and thermally regulated warm air blower unit. The air mattress is enclosed in a vinyl and polyurethane cover, which is in turn fitted with air inlet and outlet ports to receive and recirculate warmed air within the air mattress cover under the patient. The patient is warmed by conduction of heat (regulated between 34° and 40° C) thru the polyurethane cover. The air pump and air blower unit operate on 110V, but there is no electrical contact between the control devices and the patient support mattress. The air pump alternately cycles pressures between sections of the mattress to relieve interface pressure against the patient's soft tissues.

The provided text describes the TableGard Pressure Relieving Patient Warming Mattress (K080763). It focuses on the device's functional and safety testing to support its substantial equivalence to predicate devices, rather than a clinical study evaluating its performance against specific acceptance criteria in a human population.

Therefore, much of the requested information (like sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC study details, training set information, and specific effect sizes) is not applicable or not available in the provided 510(k) summary.

However, I can extract the acceptance criteria related to the device's functional performance and how it was tested.

Acceptance Criteria and Reported Device Performance

This 510(k) summary focuses on functional and safety testing, establishing that the device's performance is acceptable and does not introduce new safety or effectiveness concerns compared to predicate devices. The "acceptance criteria" here are implicitly related to the prevention of thermal injury and effective pressure relief, ensuring the device operates within safe and intended parameters.

Study Details (Based on available information):

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

   • Test Set Sample Size: Not specified. The testing described is "functional and safety testing" and "simulated skin temperatures," implying laboratory or engineering tests, not a clinical study with a patient cohort.
   • Data Provenance: Not explicitly stated, but the nature of the tests suggests they were internal laboratory tests conducted by the manufacturer, Talley Medical/Jaxports. These are not human subject data (retrospective or prospective).

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The "ground truth" for the functional tests would be the physical measurements taken by instruments according to engineering specifications and safety standards, not expert consensus on clinical outcomes.

3. Adjudication method for the test set: Not applicable. This concept is for clinical studies involving human interpretation or outcomes, not functional device testing.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, if so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable. This device is a patient warming mattress, not an imaging or diagnostic AI device.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. This is a medical device, not an algorithm. The device's performance (temperature regulation, pressure relief) is "standalone" in the sense that it operates according to its design parameters.

6. The type of ground truth used: For temperature testing, the "ground truth" was established by measurements of "simulated skin temperatures" against predetermined safety limits (likely based on established thresholds for thermal injury). For pressure relief, the "ground truth" was the physical measurement of "interface pressure" by instruments, demonstrating cyclical and consistent relief according to the device's design.

7. The sample size for the training set: Not applicable. This is a hardware device, not a machine learning algorithm that requires a training set.

8. How the ground truth for the training set was established: Not applicable. See point 7.

Summary of the study:

The study described is a series of functional and safety tests performed on the TableGard Pressure Relieving Patient Warming Mattress system. These were engineering/laboratory tests, not clinical studies involving human subjects.

• The tests evaluated:
  • Thermal Regulation: Achieved surface temperatures were measured under normal operating conditions and in conditions of possible single-fault failures. The goal was to confirm that the warming system would not cause thermal injury.
  • Pressure Relief: Interface pressure between the patient support surface and the patient was measured to confirm that it was fully relieved on a cyclical and consistent basis.

The conclusion drawn from these tests was that the device met its functional and safety requirements, demonstrating substantial equivalence to predicate devices and not introducing new safety or effectiveness issues.

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The Table Tilt Device is an additional device for treatment tables used for radiation treatment. It enables a motorized table tilt around the lateral and longitudinal axis to compensate for patient rotation. In this fashion misalignments and shift of the patient can be precisely compensated.

The Table Tilt Device is a device used to compensate rotational patient misalignment (roll and pitch) in a linear accelerator environment for stereotactic radiosurgery or radiotherapy procedures.

The Table Tilt Device is a powered patient support assembly for use in radiotherapy and radiosurgery treatments. It allows the user to undertake motorized tilt adjustment of a patient misalignment to eliminate the need to manually move the patient on the table.

The provided text is a 510(k) summary for a "Table Tilt Device." This document focuses on demonstrating substantial equivalence to a predicate device for regulatory approval, rather than presenting a detailed study proving performance against specific acceptance criteria. Therefore, most of the requested information regarding detailed study design, sample sizes, ground truth establishment, expert qualifications, and specific performance metrics is not available in the provided text.

Here's what can be extracted and what is missing:

Acceptance Criteria and Device Performance (Limited Information)

The document primarily focuses on demonstrating "substantial equivalence" rather than specific numerical acceptance criteria. The "Intended Use" and "Device Description" sections implicitly define the functional requirements.

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

As mentioned above, the provided text does not present explicit, quantifiable acceptance criteria with corresponding reported performance metrics. The core statement is: "The validation proves the safety and effectiveness of the system."

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

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified. The document states "The Table Tilt Device will be verified and validated according to BrainLAB's procedures for product design and development." This implies internal testing.

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

Not applicable/Not specified. The validation described is for a mechanical device; "ground truth" in the context of expert consensus on medical images or diagnoses is not relevant here. The validation would likely involve engineering tests against specifications.

4. Adjudication method for the test set

Not applicable/Not specified. As it's a mechanical device, adjudication in the sense of resolving discrepancies in expert interpretations is not relevant.

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 is not an AI/imaging device, and no MRMC study is mentioned.

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

A standalone performance evaluation would be inherent in the "verification and validation" mentioned, but details of how this was done (e.g., specific test protocols, performance metrics) are not provided. The device itself is a standalone mechanical component that assists in patient positioning.

7. The type of ground truth used

For a mechanical device like a table tilt mechanism, "ground truth" would typically refer to engineering specifications and measurements (e.g., accuracy of tilt, range of motion, load bearing capacity, stability). This would likely involve:

• Engineering drawings and design specifications.
• Physical measurements using calibrated instruments.
• Stress tests and durability tests.

However, the specific methods are not detailed in this summary.

8. The sample size for the training set

Not applicable. This device is not described as involving machine learning or AI, so there is no "training set."

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

Not applicable. There is no training set for this device.

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