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The D Camera Controller 5522101 has been designed for high-definition video endoscopy and can be used for both, diagnostic and therapeutic interventions. The Camera Controller is used in conjunction with other video equipment and endoscopic accessories.

The D Camera Controller 5522101 has been designed for high-definition video endoscopy and can be used for both, diagnostic and therapeutic interventions. The Camera Controller is used in conjunction with other video equipment and endoscopic accessories. The subject device is used in combination with sensor endoscopes and a monitor for visualization. In this context, the D Camera Controller is the control unit, its primary performance characteristics are signal processing of the image data and image recording. No further light source is required for the intervention. The D Camera Controller supplies the distal LED of the endoscope with light. The electrical signals provided by the sensor endoscope are processed and adequately converted to render a visible image of the endoscopic scene on a connected display device for the user.

This document is a 510(k) Summary for the Richard Wolf D Camera Controller (K211332), filed with the FDA. It declares substantial equivalence to a predicate device, the LOGIC HD LITE CAMERA CONTROLLER (K200617). The core argument for equivalence primarily rests on non-clinical performance testing and software verification.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Important Note: This device, the "D Camera Controller," is a hardware component (a camera controller) for endoscopy, not an AI or imaging diagnostic device in the traditional sense. Therefore, many of the typical acceptance criteria and study types associated with AI/ML diagnostic tools (like those involving image classification, human reader performance, ground truth establishment by expert consensus, etc.) are not applicable or described in this document. The focus here is on the functional safety and effectiveness of the device as a video endoscopy component.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is not an AI/ML diagnostic device, the acceptance criteria are largely related to functional performance, electrical safety, electromagnetic compatibility, and software validation. The document describes that the device met these criteria rather than providing a quantitative table of thresholds vs. observed performance in a diagnostic context.

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

• Sample Size: The document does not specify a "test set" sample size in terms of clinical cases or patient data. The testing described is primarily bench testing (performance, electrical safety, EMC) and software testing, not a clinical study involving a dataset of medical images or patient outcomes.
• Data Provenance: Not applicable in the context of clinical image data. The testing is described as internal verification and validation of the device's engineering performance.

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

• Not applicable. The "ground truth" for this device is its adherence to engineering specifications, electrical safety standards, electromagnetic compatibility, and software functionality, as verified through standard testing procedures. It is not an AI diagnostic device where expert interpretation of clinical data constitutes "ground truth."

4. Adjudication Method for the Test Set

• Not applicable. As the performance testing is against technical specifications and standards, there is no need for expert adjudication of medical findings.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and Effect Size

• No. An MRMC study is relevant for AI image analysis tools where human reader performance (with and without AI assistance) is being evaluated. This device is a camera controller, not such an AI tool.

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

• Not applicable. This device is a hardware component with integrated software for image acquisition and processing. Its "standalone" performance is its ability to meet specified technical and functional requirements, which are detailed implicitly through the various compliance tests mentioned (EMC, electrical safety, software V&V, functional tests). It's not a standalone diagnostic algorithm that produces a finding independent of human interaction.

7. The Type of Ground Truth Used

• The "ground truth" for this device's performance is:
  • Engineering Specifications: The device must meet its design requirements for signal processing, image recording, user interface functions, etc.
  • Regulatory Standards: Compliance with electrical safety (e.g., EN/IEC 60601-1), electromagnetic compatibility (e.g., IEC 60601-1-2), and software development/validation standards (e.g., IEC 62304).
  • Predicate Device Equivalence: The ultimate "ground truth" sought by the 510(k) pathway is demonstrating that the device is "substantially equivalent" to a legally marketed predicate device in terms of safety and effectiveness. This is achieved by showing that any differences do not raise new questions of safety or effectiveness.

8. The Sample Size for the Training Set

• Not applicable. This device does not use machine learning or AI models that require a "training set" of data in the common sense. Its software performs fixed algorithms for image processing and control, not adaptively learning from data.

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

• Not applicable. (See point 8).

In Summary:

The provided document describes the regulatory submission for a medical device (a camera controller for endoscopy) that is primarily a hardware component with integrated software. The "acceptance criteria" and "study" proving it meets them are focused on engineering and regulatory compliance (e.g., electrical safety, EMC, software validation) rather than the clinical performance metrics often associated with AI/ML diagnostic tools (like sensitivity, specificity, or human reader study endpoints). The substantial equivalence claim is built on non-clinical performance testing and software verification, demonstrating that any technological differences from the predicate device do not raise new questions of safety or effectiveness. No clinical or image-based diagnostic performance studies are mentioned or required for this type of device.

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1. To relieve symptoms associated with muscle spasm, to treat temporomandibular joint (TMJ) dysfunction and associated pain
2. Muscle re-education
3. Increasing blood flow
4. Maintain or increase mandibular range of motion

This device is a current stimulation device with Therapeutic Electro Muscle Stimulator function. Power is supplied by the built-in rechargeable lithium batter. The stimulation current generated by the output circuit of the main body is supplied to the user through the electrode to realize current stimulation. The device is equipped with PAIN mode and MCR mode. Each CH can output independently and be adjusted. If it outputs in CARE mode, it can be used for both outputs at the same time.

Upon reviewing the provided document, it appears to be an FDA 510(k) clearance letter for a medical device called "D function," a powered muscle stimulator. The document primarily focuses on demonstrating the substantial equivalence of the "D function" to legally marketed predicate devices, rather than presenting a detailed study proving the device meets specific performance acceptance criteria for diagnostic accuracy or clinical effectiveness in the way one might expect for an AI/ML-based diagnostic device.

The document does not contain the following information typically found in a study proving a device meets acceptance criteria:

• A table of acceptance criteria and reported device performance related to clinical outcomes or diagnostic accuracy.
• Sample sizes used for test sets or data provenance for such studies.
• Number of experts or their qualifications for establishing ground truth.
• Adjudication methods for test sets.
• MRMC comparative effectiveness study results.
• Standalone performance results.
• Type of ground truth used (e.g., pathology, outcomes data).
• Sample size for and ground truth establishment for training sets (this device is a stimulator, not an AI/ML diagnostic).

Instead, the document focuses on:

• Regulatory information: Device classification, product codes, predicate devices.
• Device description: How the device works (current stimulation).
• Indications for Use: What the device is intended to treat (muscle spasm, TMJ dysfunction, muscle re-education, blood flow, range of motion).
• Comparison of technological characteristics: Comparing pulse width, output frequency, and output current with predicate and reference devices, highlighting differences and justifying how these differences are supported by existing devices.
• Performance Data (Non-clinical Testing): This section refers to compliance with standards (e.g., electrical safety, EMC, software life cycle processes), and verification/validation that the device meets design/software requirements. It states that "The verification results demonstrate that the proposed device complies with the standard, IEC62304:2006/ Amd.1: 2015 Medical device software - Software life cycle processes. Additionally, the proposed device meets its design requirements in accordance with the requirements of FDA's guidance for the Content of Premarket Submissions for Software." It also states "The validation results demonstrate that the software specifications conform to user needs and that the particular requiremented through the proposed device can be consistently fulfilled."

Given the nature of this document (510(k) for a powered muscle stimulator), the "acceptance criteria" and "study" are primarily focused on non-clinical performance (electrical safety, electromagnetic compatibility, software validation, and physical/electrical specifications) to ensure the new device is as safe and effective as existing legally marketed predicate devices, despite some technological differences. It is not an AI/ML device, so typical AI/ML performance metrics (accuracy, sensitivity, specificity, AUC) are not applicable or presented.

Therefore, I cannot extract the information requested in the prompt as it pertains to AI/ML diagnostic device regulatory submissions, because this document describes a traditional medical device (a stimulator).

If you can provide a document related to an AI/ML medical device, I would be happy to attempt to extract that information.

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The D R Burton® OxyPAP™ device is indicated for the treatment and prevention of atelectasis. It also has the ability to provide supplemental oxygen when used with compressed oxygen. It includes the option of a pressure manometer. The device is for patients (ages 5 years and above) who are capable of following directions for positive airway pressure (PAP) therapy.

Normal use of the D R Burton OxyPAP™ should not be more than 24 hours total combined time.

The environment of use is for hospital and clinical setting.

The OxyPAP device is a handheld respiratory therapy device that creates a positive airway pressure. The OxyPAP device is intended to be used by pediatric (ages 5 years and above) and adult patients in the hospital environment, under the supervision of a healthcare professional. The OxyPAP device is a single patient use device.

The provided text describes the D R Burton OxyPAP device, its indications for use, and a comparison to predicate and reference devices for a 510(k) submission. However, this document does not contain any information about acceptance criteria, a specific study proving the device meets these criteria, or details regarding AI/algorithm performance and ground truth establishment.

The document is a US FDA 510(k) clearance letter and summary, which focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving performance against specific quantitative acceptance criteria through a dedicated standalone study. The "Performance" and "Non-clinical Comparative Performance" sections primarily describe comparative testing to show similarity to existing devices.

Therefore, I cannot fulfill all parts of your request based on the provided text. I will explain what information is present and what is missing.

Summary of what can be extracted from the document:

• Device Name: D R Burton OxyPAP
• Device Type: Incentive Spirometer, Positive Airway Pressure (PAP) Therapy Device
• Indications for Use: Treatment and prevention of atelectasis; ability to provide supplemental oxygen when used with compressed oxygen. For patients (ages 5 years and above) capable of following directions for PAP therapy. Normal use not more than 24 hours total combined time. Environment of use: hospital and clinical setting.
• Predicate Device: K991300 – DHD Healthcare Corp. – Boeing, Positive Airway Pressure (PAP) Therapy Device
• Reference Devices: K173819 – Trudell VersaPAP™ Device; K040991 – Ambu Disposable Pressure Manometer

Missing/Not Applicable Information based on the prompt's requirements:

The document focuses on substantial equivalence for a medical device that is not an AI/ML powered device. As such, information typically associated with AI/ML device validation studies (like distinct acceptance criteria for algorithm performance, expert review for ground truth, MRMC studies, training/test set details, etc.) is not present and not applicable to this type of device submission.

Specifically, the following sections of your request cannot be answered from the provided text:

• 1. A table of acceptance criteria and the reported device performance: The document presents comparative performance data (e.g., Mean PEEP, Mean Peak Expiratory Pressure), but these are comparisons to predicate/reference devices, not explicit acceptance criteria for a standalone study performance. There are no clear quantitative acceptance criteria stated for the D R Burton OxyPAP itself beyond being "substantially equivalent" to the predicate.
• 2. Sample size used for the test set and the data provenance: Not applicable as this is a physical device, not an algorithm being tested on a data set. The "bench testing" mentioned includes performance testing and drop testing, but no "sample size" in the context of data points.
• 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 a physical device like this is established through engineering and clinical performance testing, not expert review of AI outputs.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Not applicable. This is for an AI-assisted workflow, which is not the case here.
• 6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable, as this is a physical device, not an algorithm.
• 7. The type of ground truth used: For a physical device, "ground truth" would refer to measured physical properties or clinical outcomes. The document discusses "Biocompatibility" (material certification to a legally marketed device) and "Bench Testing" (comparative performance, drop testing, effects of aging). These are the "truths" for this device.
• 8. The sample size for the training set: Not applicable. This is not an AI/ML device.
• 9. How the ground truth for the training set was established: Not applicable.

Information that is present (though not in the requested format for AI/ML devices):

• Device Performance Reported (Comparative, not against specific acceptance criteria):
  • Proposed OxyPAP:
    • Mean PEEP (cmH2O) @800 ml TV: 2.81 @ 5 Lpm, 12 @ 10 Lpm, 12.75 @ 15 Lpm
    • Mean Peak Expiratory Pressure (cmH2O) @800 ml TV: 15 Lpm / 15 cmH2O; 20 (400 TV) / 21 (800 TV)
    • Mean Inspiratory Pressure (cmH2O) @800 ml TV: -0.7 @ 5 Lpm, -4.7 @ 10 Lpm, -3.46 @ 15 Lpm
    • Mean Expiratory Pressure (cm H2O) @ 800 ml TV: 3.1 @ 5 Lpm, 12.1 @ 10 Lpm, 13 @ 15 Lpm
  • Predicate DHD EzPAP (for comparison):
    • Mean PEEP (cmH2O) @800 ml TV: 2 @ 5 Lpm, 8 @ 10 Lpm, 16 @ 15 Lpm
    • Mean Peak Expiratory Pressure (cmH2O) @800 ml TV: 15 Lpm / 15 cmH2O; 22 (400 TV) / 26 (800 TV)
    • Mean Expiratory Pressure (cm H2O) @ 800 ml TV: 5 @ 5 Lpm, 11 @ 10 Lpm, 20 @ 15 Lpm

The core conclusion of the document is that "Based upon the comparative performance testing we have demonstrated that the proposed device compared to the predicate and reference devices can be found to be substantially equivalent." This is the primary "acceptance criterion" for a 510(k) submission of this nature.

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The D 100 L001 Ph.I.S.I.O. Newborn-Hollow Fiber Membrane Oxygenator with Phosphorilcholine Coating is intended for use in infants who undergo cardiopulmonary bypass surgery requiring extracorporeal circulation with a maximum blood flow rate of 0.7 liters/minute. It provides oxygenation and carbon dioxide removal from venous or suctioned blood. The integrated heat exchanger provides blood temperature control and allows the use of hypothermia or aids in the maintenance of normothermia during surgery. The venous reservoir is intended to collect blood aspirated from the operating field during surgical procedures and the blood from patient's veins (gravity or vacuum assisted) during normal operation, to always assure the proper oxygenation capability of the device. The D 100 L001 Ph.I.S.I.O. should not be used longer than 6 hours. Contact with blood for longer periods is not advised.

The D 100 L001 Ph.I.S.I.O Newborn Hollow Fiber Oxygenator with Integrated Hardshell Cardiotomy/Venous Reservoir with phosphory/choline coating (hereafter referred to as the D 100 Ph.I.S.I.O) is a high efficiency microporous newborn hollow fiber membrane oxygenator integrated with an heat exchanger and connected to an hardshell cardiotomy/venous reservoir. The device is a modified version of the currently marketed D 901 Ph.I.S.I.O. Newborn Hollow Fiber Membrane Oxygenator with phosphoryIcholine coating unmodified device (K991737, K010478) (hereafter referred to as the D 901 Ph.I.S.I.Q.), The modification is limited to an overall reduction in the size of the device, design change to the integrated heat exchanger and hardshell cardiotomy/venous reservoir and consequent updating of product specifications in the IFUs. The reduction in size enables the device to be better suited for surgical procedures on smaller pediatric patients (newborn) where a minimal priming volume is required. Other than this change the D 100 Ph.I.S.I.O. and the D 901 Ph.I.S.I.O. are identical in intended use, materials and manufacturing processes.

The provided text describes a 510(k) summary for the Sorin Group Italia S.r.l. D 100 L001 Ph.I.S.I.O. Newborn Hollow Fiber Oxygenator. This device is a modified version of an existing oxygenator (D 901 Ph.I.S.I.O.) with changes primarily focused on reduced size and design alterations to the heat exchanger and reservoir, intended for use in smaller pediatric patients (newborns).

Here's an analysis of the acceptance criteria and study information based on the provided document:

Acceptance Criteria and Device Performance

The document does not explicitly list a table of quantifiable acceptance criteria with corresponding performance metrics for the D 100 Ph.I.S.I.O. The studies conducted were primarily comparative, aiming to demonstrate substantial equivalence to the predicate device (D 901 Ph.I.S.I.O.) rather than meeting discrete, pre-defined numerical thresholds for a novel device.

However, the text implies that the acceptance criteria are met if the device's performance is either "substantially equivalent" to the predicate, or if observed differences are explainable by the design changes and still suitable for the intended use. The "results of these tests met established specifications" is a recurring phrase, indicating that internal specifications were indeed met, although these are not detailed in the provided summary.

General implied performance areas and their qualitative results:

Study Details

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

   • The document describes in vitro testing. There is no mention of a "test set" in the context of clinical trials or patient data. Instead, the "test set" refers to the devices themselves that were subjected to various in vitro performance assessments.
   • The sample size for these in vitro tests (e.g., number of devices tested for gas transfer, pressure drop, etc.) is not specified.
   • Data provenance: All testing described is in vitro (laboratory-based) and "carried out in accordance with the requirements of 'Guidance for Cardiopulmonary Bypass Oxygenators 510(k) submissions – Final Guidance for Industry and FDA Staff' ... and ... ISO 7199 (1996)." This implies the studies were conducted by the manufacturer, Sorin Group Italia S.r.l., likely in Italy.

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

   • This question is not applicable to this type of submission. The studies described are in vitro performance tests of a medical device, not evaluations of human-interpretable data (like medical images) where expert ground truth is typically established. The "ground truth" for these tests would be the physical/chemical properties and functional performance of the device as measured by standardized laboratory methods.

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

   • This question is not applicable. Adjudication methods are relevant for resolving discrepancies among multiple human readers/reviewers of data (e.g., medical images). The studies here are objective laboratory measurements.

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI/CAD devices where human interpretation is involved. The device here is a physical medical device (oxygenator) used in cardiopulmonary bypass.

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

   • This is not applicable. This is a physical medical device, not an algorithm or AI. The tests performed are "standalone" in the sense that they assess the device's technical performance directly, independent of a human operator's skill in interpreting outputs, beyond standard laboratory procedures.

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

   • The "ground truth" for the in vitro tests is derived from objective laboratory measurements performed according to established international and FDA guidance documents (e.g., ISO 7199, FDA Guidance for Oxygenators). The "truth" is whether the device's measured performance parameters fall within pre-defined specifications or are comparable to the predicate device's performance. For biocompatibility, the ground truth relates to the absence of toxic effects as per ISO 10993.

7. The sample size for the training set:

   • This question is not applicable. This device is a physical medical device. It does not involve a "training set" in the context of machine learning.

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

   • This question is not applicable, as there is no training set for this type of device.

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The Dideco D 905 EOS Hollow Fiber Oxygenator with Integrated Hardshell Venous/Cardiotomy Reservoir is intended for use in patients who undergo cardiopulmonary bypass surgery requiring extracorporeal circulation with a maximum blood flow rate of 5 liters /minute. It provides oxygenation and carbon dioxide removal from venous blood. The integrated heat exchanger provides blood temperature control and allows the use of hypothermia or aids in the maintenance of normothermia during surgery. The venous reservoir with cardiotomy filter is intended to collect blood aspirated from the operating field during surgical procedures and the blood from patient's veins (gravity or vacuum assisted) during normal operation to assure the proper oxygenation capability of the device. The device is intended to be used for 6 hours or less.

The D 905 EOS Hollow Fiber Oxygenator With Integrated Hardshell Venous/Cardiotomy Reservoir (hereafter referred to as the D 905 EOS) is a high efficiency microporous hollow fiber membrane oxygenator integrated with an heat exchanger and connected to an hardshell venous/cardiotomy reservoir. The device is a modified version of the currently marketed D 903 Avant 2 Ph.I.S.I.O (K033323) predicate device (hereafter referred to as the Avant Ph.1.S.I.O.). The modification is limited to an overall reduction in the size of the device. The reduction in size enables the device to be better suited for the pediatric and small adult patient population.

Here's an analysis of the provided text regarding the D 905 EOS Oxygenator, extracting information relevant to acceptance criteria and the study proving it meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly list quantitative acceptance criteria in a dedicated table. Instead, it states that the test results "met established specifications" and that the device is "substantially equivalent" to predicate devices. The performance is reported in relation to these comparisons.

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

The document does not specify a distinct "test set" sample size for each performance characteristic. Instead, it refers to in-vitro testing performed on the "D 905 EOS" (the device itself) and, "for comparative purposes," on the "D 903 Avant 2 Ph.I.S.I.O." and the "Cobe Optimin predicate device."

• Sample Size: Not explicitly stated as a number of devices or data points for the in-vitro tests. It refers to testing the device and predicate devices.
• Data Provenance: Retrospective for the predicate devices as they are "legally marketed." Prospective for the D 905 EOS, as the testing was conducted to support its 510(k) submission. There is no mention of country of origin for the data collection, but the submitter is Italian (Dideco S.r.l.).

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

This information is not provided in the document. The studies described are in-vitro tests, which typically rely on standardized laboratory measurements and comparison to objective specifications and predicate device performance, rather than expert judgment for "ground truth."

4. Adjudication Method for the Test Set

Not applicable. As described above, the studies are in-vitro tests with objective measurements, not studies requiring expert adjudication.

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 device is a medical oxygenator, not an AI-based diagnostic or assistive technology that would involve "human readers" or "AI assistance" in the context of imaging or similar interpretation tasks.

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

Not applicable. The device itself is a standalone medical device. The "standalone" concept typically applies to software or AI algorithms operating independently of human intervention. Here, the device's performance was evaluated in various standalone in-vitro tests.

7. The Type of Ground Truth Used

The "ground truth" for the in-vitro performance characteristics was established by:

• Established Specifications: These would be pre-defined numerical or qualitative criteria based on regulatory guidelines, engineering principles, and clinical requirements for oxygenators.
• Predicate Device Performance: The functional parameters of the D 903 Avant 2 Ph.I.S.I.O. and Cobe Optimin served as benchmarks for demonstrating substantial equivalence.

There is no mention of pathology, outcomes data, or expert consensus (in the context of clinical interpretation) as ground truth.

8. The Sample Size for the Training Set

Not applicable. This device is a physical medical device, not a software algorithm that would require a "training set" in the context of machine learning. The term "training set" refers to data used to train an AI model.

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

Not applicable, for the same reasons as point 8.

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The Dideco D 903 Avant Adult Hollow Fiber Oxygenator with Integral Hardshell Venous Reservoir is intended for use in adults who undergo cardiopulmonary bypass surgery requiring extracorporeal circulation. It provides oxygenation and carbon dioxide removal from venous blood. The integrated on other provides blood temperature control and allows the use of hypothermia or aids in the maintenance of normothermia during surgery. The venous reservoir with cardiotomy filter is intended to collect blood aspirated from the operating field during surgical procedures and the blood from to tient's veins (gravity or vacuum assisted) during normal operation to assure the proper oxygenation capability of the device. The device is intended to be used for six hours or less.

The D 903 AVANT and D 903 AVANT 2 Ph.I.S.I.O, hereafter referred to as the AVANT, are hollow fiber membrane oxygenators with integral heat exchanger and a hardshell cardiotomy/venous reservoir. The D 903 AVANT 2 Ph.I.S.I.O. is the phosphorylcholine coated version of the same AVANT oxygenator. The change covered by this submission is limited to extending the intended use of the AVANT (uncoated and coated versions) in order to allow the use of active venous drainage with vacuum. No modifications are being made to the devices themselves except an addition to the indications for use and instructions for use.

This is a 510(k) premarket notification for a medical device, the D 903 AVANT Adult Hollow Fiber Oxygenator. These notifications are about demonstrating substantial equivalence to a predicate device, not necessarily defining or proving new acceptance criteria through a clinical study in the way an AI/ML device submission would. Therefore, many of the requested categories for AI/ML study details (like sample size for test sets, number of experts, MRMC studies, training set details) are not applicable here.

Here's a breakdown of the available information in the context of your request:

Acceptance Criteria and Device Performance

The "acceptance criteria" here are implicitly defined by the performance characteristics of the predicate devices and the relevant standards. The "reported device performance" is a demonstration of substantial equivalence to these predicate devices.

• Performance characterization
• Physical effectiveness characterization/integrity |
  | Blood Compatibility (for coated version) | "Blood compatibility characterization and stability of the coating were performed on the AVANT Ph.I.S.I.O. predicate device (K020351)." This included "hemolysis/cell depletion characterization, microembolic activity characterization, and reservoir housing integrity during active venous drainage." "The results of these tests met established specifications." |
  | Intended Use with Vacuum Drainage | The submission specifically addresses the extension of intended use to include active venous drainage with vacuum. The above tests (e.g., reservoir housing integrity during active venous drainage) would cover this. "functional tests demonstrate that the AVANT is equivalent to the predicate devices, with respect to its intended use with vacuum drainage." |
  | Equivalence to Predicate Devices | "The results of the study showed the device characteristics of the modified AVANT and predicate devices are comparable." "The results of in vitro studies demonstrate that the AVANT Adult Hollow Fiber Membrane Oxygenator performs in a manner substantially equivalent to the predicate device." |

Study Details (as applicable to a 510(k) for a non-AI/ML device)

1. Sample size used for the test set and the data provenance: Not applicable in the context of an AI/ML device. This submission focuses on in vitro and biocompatibility testing of a physical medical device. The "test set" would refer to the physical samples of the oxygenator or its materials subjected to various tests. The provenance is the manufacturer's testing facilities (Dideco S.p.A., Italy).
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical device's performance is established by standardized laboratory measurements and compliance with ISO standards, not expert consensus in the diagnostic sense.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. Adjudication methods are typically for subjective assessments or discrepancies in diagnostic interpretations, not for objective measurements of physical device performance.
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 is for a physical medical device, not an AI/ML diagnostic algorithm.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is for a physical medical device.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): The "ground truth" here is compliance with established international standards (ISO 10993-1:1995, ISO 7199 (1996)) and FDA guidance documents, as well as objective measurements of physical and chemical properties of the device and its materials.
7. The sample size for the training set: Not applicable. This is for a physical medical device, not an AI/ML device that requires a training set.
8. How the ground truth for the training set was established: Not applicable.

In summary, this 510(k) premarket notification demonstrates substantial equivalence for a physical medical device based on in vitro performance data and biocompatibility testing, not an AI/ML diagnostic product, so many of the requested AI/ML-specific details are not present.

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The Dideco D 903 Avant 2 Ph.I.S.I.O. Adult Hollow Fiber Oxygenator with Integral Hardshell Venous Reservoir is intended for use in adults who undergo cardiopulmonary bypass surgery requiring extracorporeal circulation. It provides oxygenation and carbon dioxide removal from venous blood. The integrated heat exchanger provides blood temperature control and allows the use of hypothermia or aids in the maintenance of normothermia during surgery. The venous reservoir with cardiotomy filter is intended to collect blood aspirated from the operating field during surgical procedures and the blood from patient's veins during normal operation to assure the proper oxygenation capability of the device. The device is intended to be used for six hours or less.

The D 903 AVANT Ph.I.S.I.O is a hollow fiber membrane oxygenator with integral heat exchanger and a hardshell cardiotomy venous reservoir.

Here's an analysis of the provided text regarding the acceptance criteria and study for the D 903 AVANT Ph.I.S.I.O. Adult Hollow Fiber Oxygenator:

This document is a 510(k) summary for a medical device seeking substantial equivalence to predicate devices, not a study report describing novel performance claims. Therefore, the device is not demonstrating performance against acceptance criteria in the way an AI/ML device would. Instead, it is demonstrating substantial equivalence to existing devices through a series of tests. Many of the requested categories are not directly applicable to this type of submission.

The "acceptance criteria" here are implicitly that the D 903 AVANT Ph.I.S.I.O. performs equivalently or within acceptable ranges compared to its predicate devices for relevant characteristics. The "study" proving this is a series of in vitro and biocompatibility tests.

1. Table of "Acceptance Criteria" and Reported Device Performance

The following points are mostly not applicable to this type of device submission (a traditional 510(k) for an oxygenator, not an AI/ML diagnostic system):

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

• Sample Size: Not specified in terms of number of devices or "cases." The "tests" here refer to laboratory evaluations on physical devices (e.g., a certain number of oxygenator units were subjected to gas transfer, heat exchange, etc., tests). The specific number of units isn't detailed in this summary.
• Data Provenance: The tests were conducted internally by Dideco S.p.A. (Italy) as part of their submission to the FDA. The data is prospective in the sense that the tests were specifically performed for this submission.

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

• Not Applicable. "Ground truth" in the context of expert consensus is relevant for diagnostic interpretations. For this device, "ground truth" refers to established physical and chemical measurement standards (e.g., for gas exchange, blood compatibility), which are measured by laboratory technicians according to specified protocols.

4. Adjudication method for the test set

• Not Applicable. Adjudication methods like 2+1 or 3+1 are for reconciling disagreements among human readers/experts in diagnostic tasks. This device is evaluated by objective physical and chemical tests against predefined specifications.

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-assisted diagnostic device.

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

• Not Applicable. This is a hardware medical device, not an algorithm. Performance is inherent to the device's physical function.

7. The type of ground truth used

• Physical and Chemical Measurement Standards / Predicate Device Performance: The "ground truth" is based on established engineering and biocompatibility standards (e.g., ISO 10993, ISO 7199, FDA guidance) and the performance characteristics of the legally marketed predicate devices (D 903 AVANT, D 901 Lilliput Ph.I.S.I.O., Monolyth Mimesys). The device is considered "substantially equivalent" if it meets the same functional performance levels.

8. The sample size for the training set

• Not Applicable. This is a hardware device; there is no "training set" in the context of machine learning. The design and manufacturing processes are refined through engineering, but not "trained" with data.

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

• Not Applicable. As there is no training set, this question does not apply.

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