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The (X-Coated) Capiox® SX25 and SX18 Hollow Fiber Oxygenators with/without Detachable Hardshell Reservoirs are used to exchange gases between blood and a gaseous environment to satisfy the gas exchange needs of a patient during cardiopulmonary bypass surgery for periods up to 6 hours.

The integral heat exchanger is used to warm or cool blood or perfusion fluid as it flows through the device.

The (detachable) hardshell reservoir is used to store blood during extracorporeal circulation from both the venous line and the cardiotomy line. The reservoir contains a venous section that is comprised of a filter and defoamer to facilitate air bubble removal. The cardiotomy section of the reservoir contains a filter to remove particulate matter and a defoamer to facilitate air bubble removal.

The Hardshell Reservoir is also used for post-operative chest drainage and autotransfusion procedures to aseptically return the blood to the patient for blood volume replacement.

The Hardshell Reservoir is also used with the vacuum-assisted venous return technique during cardiopulmonary bypass.

(The X-Coating™ is a polymer coating that is applied to blood contacting surfaces of the oxygenator to reduce the adhesion of platelets to the surfaces of the device.)

The modified and predicate Capiox® SX18/25 Oxygenator utilizes porous fiber technology to facilitate the transfer of gases between a blood-phase environment and a gas-phase environment for the intent of satisfying the gas exchange needs of a patient during cardiopulmonary bypass surgery. A fiber bundle offers the porous membrane surface to sufficiently permit the movement of gases through the walls of the hollow fibers via diffusion.

The modified and predicate Capiox® SX18/25 Oxygenator has an integrated heat exchanger that is comprised of stainless steel encased in a polycarbonate housing. The stainless steel acts as a heat transfer material that permits heat that is generated from a temperature controlled external water bath to transverse across the walls of the stainless steel to effect the necessary temperature change upon circulating blood.

With respect to the filtration of blood, the modified and predicate Capiox® Hardshell Reservoir relies upon mechanical entrapment of particulates and emboli within the filter mesh as a means to remove those particulates from the blood.

The subject of this Special 510(k) is a modification being made to the Hardshell Reservoir. The reservoir component remains identical to the design of the original reservoir that was cleared by FDA with (K130359) - except the modified device will include PVC tubing (with TOTM plasticizer) for a flared venous inlet drop tube, auxiliary tube, sampling manifold tubing, and purge line tubing.

This document describes a Special 510(k) submission for modifications to the Terumo Capiox® SX18/25 Hollow Fiber Oxygenator with detachable Hardshell Reservoir. The submission aims to demonstrate substantial equivalence to the previously cleared predicate device (K130359).

1. Acceptance Criteria and Reported Device Performance

The application does not include specific numerical acceptance criteria for the modified device's performance compared to the predicate device. Instead, it states that performance evaluations were conducted to demonstrate "functional equivalence." The changes made were related to the design and material of the venous inlet drop tube, auxiliary tube, sampling manifold tubing, and purge line tubing within the hardshell reservoir. The primary changes are:

• Venous Inlet Drop Tube: Changed from Non-Flared (DEHP plasticizer) to Flared (TOTM plasticizer).
• Auxiliary Drop Tube, Sampling Manifold Tubing, Purge line Tubing: Changed from DEHP plasticizer to TOTM plasticizer.

The performance evaluations listed are:

• Hemolysis Testing
• Air Handling
• Reservoir Pressure Drop
• Venous Defoaming

The document explicitly states that the oxygenator design is unaffected, and the modifications to the hardshell reservoir are primarily to improve flow dynamics (flared venous drop tube) and adjust to pending regulatory requirements (TOTM plasticizer). The conclusion is that "the differences between the modified device and the predicate device do not affect the intended use of the device nor do they affect safety and effectiveness of the device when used as labeled."

Since the purpose of this submission is to demonstrate equivalence rather than a specific performance threshold against a clinical endpoint for a novel device, the acceptance criteria would implicitly be that the modified device's performance in these listed tests is comparable to or better than the predicate, and crucially, does not introduce new safety or effectiveness concerns. The document broadly concludes that the modified device "is substantially equivalent" and "does not raise new issues of patient/user safety or product effectiveness," implying these equivalency tests were met.

Due to the nature of the device (cardiopulmonary bypass oxygenator and associated reservoir) and the type of modification (material and minor design changes to tubing), the performance evaluation revolves around specific in-vitro tests relevant to blood compatibility and fluid dynamics within the device.

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

The document does not specify the sample sizes used for the in-vitro performance evaluations (Hemolysis Testing, Air Handling, Reservoir Pressure Drop, Venous Defoaming). It also does not explicitly state the data provenance (e.g., country of origin, retrospective or prospective), but given these are in-vitro tests for device performance, they would typically be conducted in a laboratory setting.

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

Not applicable. This device is a cardiopulmonary bypass oxygenator and reservoir system. The "ground truth" for its performance is established through controlled physical and chemical in-vitro tests, not through expert interpretation of medical images or clinical data. Therefore, there is no mention of experts establishing ground truth in the context of medical image interpretation.

4. Adjudication method for the test set

Not applicable. As noted in point 3, the evaluation of this device relies on in-vitro performance testing, not on expert adjudication of diagnostic outcomes.

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 device used in cardiopulmonary bypass surgery, not an AI-assisted diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant.

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

Not applicable. This device is a physical medical device, not a software algorithm.

7. The type of ground truth used

The "ground truth" for evaluating this device's performance is based on objective measurements derived from the specified in-vitro tests (Hemolysis Testing, Air Handling, Reservoir Pressure Drop, Venous Defoaming). These tests measure physical and biocompatibility parameters that are critical for the safe and effective functioning of a cardiopulmonary bypass system. The ground truth is established by comparing the results of these tests for the modified device against established standards, regulatory requirements, and the performance characteristics of the predicate device.

8. The sample size for the training set

Not applicable. This device is a physical medical device, not a machine learning model that requires a training set.

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

Not applicable. As noted in point 8, this device is a physical medical device, not a machine learning model.

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The CDI System 500 provides continuous, on-line monitoring of the extracorporeal partial pressure of oxygen and carbon dioxide, pH, potassium, oxygen saturation, hematocrit, hemoglobin and temperature. In addition, calculated values of base excess, bicarbonate, oxygen saturation, and oxygen consumption may also be provided. These parameters are displayed at either actual temperature or adjusted to 37°C. For documentation purposes, the system 500's integral printer provides a hard copy of displayed parameters.

The CDI™ System 500 is an AC-powered (battery back-up) microprocessor-based device used with the following components/accessories:

• CDI™ 500 Monitor .
• Arterial and/or Venous Blood Parameter Modules (BPM) .
• CDI™ H/S Probe .
• CDI™ 540 Gas Calibrator and Calibration Gases (A and B) .
• CDI™ 510H Shunt Sensor .
• Shunt Bypass Line .
• CDI™ H/S Cuvette with or without extension tubing .
• Monitor Mounting Hardware (Pole Clamp and Cable Head Bracket) .
• . Printer Paper
  The CDI™ System 500 measures blood parameters in real time by utilizing a microprocessor based monitor, electro-optics modules (i.e., BPM and H/S probe), fluorescence chemistry technology, and optical reflectance technology. The electrooptics modules connect the monitor to the disposables (i.e., shunt sensor or cuvette) which are inserted into the extracorporeal circuit. Light is emitted from the modules, and the optical responses from the blood via the sensor(s) are measured by the monitor. The blood parameters are measured or calculated by the CDI™ 500 Monitor in real time, and displayed to the user via a graphical LCD display.

The provided text describes a 510(k) summary for the CDI™ Blood Parameter Monitoring System 500, a device for continuous, on-line monitoring of various blood parameters during cardiopulmonary bypass. The submission is for "Modifications to previously cleared system" and aims to demonstrate substantial equivalence to predicate devices K123039 and K972962.

Here's an analysis of the acceptance criteria and study information:

Acceptance Criteria and Reported Device Performance

The document states that the performance testing was conducted to "verify/validate the changes to the CDI™ System 500". The conclusion section further states that the modified device has "substantially equivalent performance specifications as compared to the predicate device." However, no specific quantitative acceptance criteria or detailed results of device performance metrics (e.g., accuracy, precision for each parameter like pH, pO2, pCO2, etc.) are provided in this summary. The document only broadly mentions "System verification testing in a blood loop to simulate clinical use."

Since specific acceptance criteria and detailed device performance are not explicitly stated in the provided text, the table below will reflect the information that is present:

Study Information

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

   • Sample Size: Not explicitly stated. The document mentions "System verification testing in a blood loop to simulate clinical use," but does not specify the number of blood samples, runs, or test conditions.
   • Data Provenance: Not explicitly stated, though the testing was described as "in a blood loop," implying an in-vitro or ex-vivo setting rather than live human subjects. This suggests controlled laboratory conditions. The country of origin for the data is not mentioned. It is a retrospective summary of testing performed for the 510(k) submission.

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

   • Not applicable/Not mentioned. The testing described is "System verification testing in a blood loop to simulate clinical use." This typically involves comparing the device's measurements against a reference method or standard in the blood loop, not against expert interpretation of data generated by the device itself. Therefore, ground truth would likely be established by precise laboratory reference measurements rather than expert consensus on device output.

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

   • Not applicable/Not mentioned. Adjudication methods are typically used in studies involving human interpretation (e.g., image reading) to resolve discrepancies. This study focuses on the technical performance of a monitoring device against reference values in a lab setting, where disagreement on "ground truth" (e.g., from a calibrated reference sensor) is not resolved by adjudication.

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 is not relevant to this device. This device is a blood parameter monitoring system, not an AI-assisted diagnostic imaging or interpretation tool that assists human readers.

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

   • Since this is a monitoring device, its primary function is standalone performance (i.e., the accuracy of its measurements). The "System verification testing" would have assessed the standalone performance of the device in measuring blood parameters in a simulated environment. While not explicitly called "standalone performance," this is the nature of the testing described for such a device.

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

   • Based on the description "System verification testing in a blood loop to simulate clinical use," the ground truth would most likely be established by reference laboratory methods or highly accurate and calibrated reference sensors/analyzers used to measure the blood parameters (pH, pO2, pCO2, K+, SO2, Hct, Hgb, Temperature) in the blood loop. This ensures an objective and reliable comparison against the device's readings.

7. The sample size for the training set:

   • Not applicable/Not mentioned. This is a monitoring device based on electro-optics modules, fluorescence chemistry, and optical reflectance technology, incorporating a microprocessor for calculations. It's not described as a machine learning or AI-driven algorithm that requires a "training set" in the conventional sense (i.e., for supervised learning). While its internal algorithms and calibrations are developed, this typically involves engineering and validation against physical and chemical principles and reference standards, not a "training set" of patient data.

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

   • Not applicable for the reason given in point 7. For algorithms within such a device, "ground truth" during development would be established through meticulous engineering, physical modeling, chemical principles, and calibration against known standards and reference measurements.

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The Terumo® Advanced Perfusion System 1 is indicated for use for up to 6 hours in the extracorporeal circulation of blood for arterial perfusion, regional perfusion, and cardiopulmonary bypass procedures, when used by a qualified medical professional who is experienced in the operation of this or similar equipment. The centrifugal pump is indicated for use in cardiopulmonary bypass procedures only.

The Advanced Perfusion System 1 is a configurable heart-lung system with a distributed network architecture that allows the user to customize the number and types of system components, which can then be configured, displayed, and controlled from a central monitor. The system is designed to enable users to choose from the TCVS supplied components to define and configure a heart-lung system to meet individual institution requirements.

The provided text describes a 510(k) summary for a medical device called the "Advanced Perfusion System 1" from Terumo Cardiovascular Systems Corporation. This document concerns modifications made to a previously cleared heart-lung machine, primarily for compliance with electromagnetic compatibility standards (IEC 60601-1-2) and software updates. It does not present a study with specific acceptance criteria and reported device performance metrics in the format requested, such as sensitivity, specificity, or AUC.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device (the Advanced Perfusion System 1 K022947) through performance testing related to safety and functionality, rather than a clinical efficacy study with quantitative performance measures.

Therefore, many of the requested fields cannot be directly extracted from the provided text. I will fill in the available information and indicate where information is not present.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample size for test set: Not specified. The document refers to "third party testing," "software verification and validation testing," and "functionality testing" but does not quantify the number of units or test cases used.
• Data provenance: Not explicitly stated as retrospective or prospective data from a specific country, as this was a device modification and testing performed for regulatory submission, likely in a controlled lab environment by Terumo and a third-party testing facility.

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

• This information is not provided in the document. The testing described appears to be technical in nature (electromagnetic compatibility, software, functionality) rather than clinical validation requiring expert ground truth in the context of diagnostic interpretation.

4. Adjudication method for the test set

• This information is not provided in the document, as it's not applicable to the type of technical performance testing 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, an MRMC comparative effectiveness study was not done. This submission is for modifications to a heart-lung machine, not an AI-powered diagnostic device, so this type of study is not relevant here.

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

• This question is not applicable as the device is a heart-lung machine, an active medical device, not a diagnostic algorithm. Performance is assessed through compliance with standards and functional testing, inherently involving the device's operational capabilities.

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

• The "ground truth" for the performance testing described would be defined by the technical specifications and standards (e.g., IEC 60601-1-2 for electromagnetic compatibility, and internal design specifications for software and functionality). It is not clinical ground truth established by medical experts or pathology in the typical sense for an AI/diagnostic device.

8. The sample size for the training set

• This concept is not applicable to the type of device described. A heart-lung machine does not typically involve training sets in the context of machine learning or AI algorithm development.

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

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

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The Sarns™ Soft-Flow Aortic Cannula is indicated for perfusion of the ascending aorta during cardiopulmonary bypass surgery for up to 6 hours of use.

The design of the Sams™ Soft-Flow Aortic Cannula allows patient blood to re-enter the body after the blood has routed through an extracorporeal circuit for blood oxygenation. The design of the cannula is simple in that it consists of a tubular conduit with a tip that can be positioned into the patient's anatomy (ascending aorta) to allow the blood to re-enter the vascular blood stream.

The provided text describes the 510(k) summary for the Sarns™ Soft-Flow® Aortic Cannula, which is a medical device. The document does not describe a study involving an AI device or algorithm, but rather a conventional medical device (an aortic cannula).

Therefore, I cannot provide an answer that includes details about AI-specific acceptance criteria, sample sizes for test/training sets, expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance, as these concepts are not addressed in the provided document.

The document discusses performance evaluations for the physical device through bench studies.

Here's the information about the acceptance criteria and the "study" (bench studies) for the Sarns™ Soft-Flow® Aortic Cannula based on the provided text:

Acceptance Criteria and Reported Device Performance

Explanation: The document states that "Terumo Cardiovascular has conducted performance studies with the modified devices to ensure that they all continue to satisfy appropriate device performance specifications and to ensure that they satisfy customer needs. There are no appreciable differences between the subject devices and the predicate devices." While specific numerical acceptance thresholds are not provided, the general statement indicates compliance with established specifications for each evaluation type.

Study Details (Bench Studies for a Conventional Medical Device)

1. Sample size used for the test set and the data provenance: Not explicitly stated. The studies were "bench studies," meaning they were conducted in a laboratory setting, not with patient data.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Bench studies for physical device performance typically rely on engineering specifications and measurement standards, not expert interpretations of data like in AI studies.
3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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 not an AI algorithm.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This device is not an AI algorithm.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Engineering specifications and physical measurements.
7. The sample size for the training set: Not applicable. Bench studies for physical device performance typically do not have a "training set" in the context of machine learning.
8. How the ground truth for the training set was established: Not applicable.

Additional Notes from the Document:

• Clinical studies involving patients were deemed "not necessary to demonstrate the safety and effectiveness of the subject devices."
• The purpose of the submission was due to cumulative non-significant changes to the device design since its original clearance. The performance evaluations were conducted to ensure the modified device still met specifications and was substantially equivalent to the predicate devices.

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The Sarns™ High-Flow Aortic Arch Cannula is indicated for perfusion of the ascending aorta during cardiopulmonary bypass surgery for up to 6 hours of use.

The design of the Sams™ High-Flow Aortic Arch Cannula allows patient blood to re-enter the body after the blood has routed through an extracorporeal circuit for blood oxygenation. The design of the cannula is simple in that it consists of a tubular conduit with a tip that can be positioned into the patient's anatomy (ascending aorta) to allow the blood to re-enter the vascular blood stream.

The provided text describes a 510(k) submission for the Sarns™ High-Flow Aortic Arch Cannula, which is a modification of a previously cleared device. The submission asserts substantial equivalence to predicate devices and does not involve an AI device. Therefore, many of the requested details related to AI performance studies are not applicable.

Here's an attempt to extract relevant information and explain why other sections are not applicable:

Acceptance Criteria and Device Performance for Sarns™ High-Flow Aortic Arch Cannula (K133151)

This 510(k) submission is for a medical device (aortic cannula) and not an AI/ML-based diagnostic or therapeutic device. Therefore, many of the requested criteria related to AI performance, such as sample sizes for test sets, expert ground truth, adjudication methods, MRMC studies, and standalone performance, are not applicable.

The submission focuses on demonstrating substantial equivalence to existing predicate devices through bench testing and comparison of design, materials, and intended use.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a quantitative table format for the modifications. Instead, it lists "Performance Evaluations" conducted to ensure the modified devices "continue to satisfy appropriate device performance specifications and to ensure that they satisfy customer needs." The implicit acceptance criterion is that the modified device performs comparably to the predicate device and retains its safety and effectiveness.

Note: The document states that "Terumo Cardiovascular has conducted performance studies with the modified devices to ensure that they all continue to satisfy appropriate device performance specifications and to ensure that they satisfy customer needs. There are no appreciable differences between the subject devices and the predicate devices." This implies that the modified device met the performance standards established for the predicate device across these evaluations.

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

Not applicable in the context of an AI device. For this medical device, the "test set" would refer to the samples of the Sarns™ High-Flow Aortic Arch Cannula that underwent the bench performance evaluations. The document does not specify the exact number of cannulas tested for each evaluation. The provenance of the data is from Terumo Cardiovascular Systems Corporation's internal bench testing activities. These studies are prospective from the perspective of evaluating the modified device.

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

Not applicable. Ground truth for the performance evaluations of a physical medical device (like an aortic cannula) is established through laboratory measurements and engineering specifications, not expert interpretation of outputs.

4. Adjudication Method for the Test Set

Not applicable. Adjudication methods are typically relevant for human interpretation or consensus in diagnostic or prognostic studies, not for the direct measurement of device performance characteristics.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for evaluating the performance of AI algorithms in diagnostic tasks, often comparing human readers with and without AI assistance. This submission pertains to a physical medical device.

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

Not applicable. This is not an AI algorithm. The performance evaluations listed ("force at break," "liquid and air leak," etc.) measure the physical properties and function of the device itself.

7. The Type of Ground Truth Used

For the performance evaluations, the "ground truth" would be the engineered specifications and performance characteristics of the predicate device, against which the modified device's performance was compared. This is based on engineering specifications and direct physical measurements rather than expert consensus, pathology, or outcomes data in the typical sense of AI/clinical studies.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable. There is no training set for this type of medical device submission.

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The (X-Coated) Capiox® SX25 and SX18 Hollow Fiber Oxygenators with/without Detachable Hardshell Reservoirs are used to exchange gases between blood and a gaseous environment to satisfy the gas exchange needs of a patient during cardiopulmonary bypass surgery for periods up to 6 hours. The integral heat exchanger is used to warm or cool blood or perfusion fluid as it flows through the device. The (detachable) hardshell reservoir is used to store blood during extracorporeal circulation from both the venous line and the cardiotomy line. The reservoir contains a venous section that is comprised of a filter and defoamer to facilitate air bubble removal. The cardiotomy section of the reservoir contains a filter to remove particulate matter and a defoamer to facilitate air bubble removal. The Hardshell Reservoir is also used for post-operative chest drainage and autotransfusion procedures to aseptically return the blood to the patient for blood volume replacement. The Hardshell Reservoir is also used with the vacuum-assisted venous return technique during cardiopulmonary bypass. (The X-Coating™ is a polymer coating that is applied to blood contacting surfaces of the oxygenator to reduce the adhesion of platelets to the surfaces of the device.)

The Capiox® Hardshell Reservoir is a hardshell reservoir used to store blood during extracorporeal circulation from both the venous line. And the cardiotomy line. The reservoir contains filters to remove particulate matter and defoamers to facilitate air bubble removal. The Hardshell Reservoir is also used for post-operative chest drainage and autotransfusion procedures to aseptically return blood to the patient for blood volume replacement. The Hardshell Reservoir is also used with the vacuum-assisted venous return technique during cardiopulmonary bypass. The Hardshell Reservoir contains X-Coating, which is intended to reduce platelet adhesion on the surfaces of the device. The device may be used for procedures lasting up to 6 hours.

The modified and predicate Capiox SX Oxygenator utilizes porous fiber technology to facilitate the transfer of gases between a blood-phase environment and a gas-phase environment for the intent of satisfying the gas exchange needs of a patient during cardiopulmonary bypass. A fiber bundle offers the porous membrane surface to sufficiently permit the movement of gases through the walls of the hollow fibers via diffusion. The modified and predicate Capiox SX Oxygenator has an integrated heat exchanger that is comprised of stainless steel encased in a polycarbonate housing. The stainless steel acts as heat transfer material that permits heat that is generated from a temperature controlled external water bath to transverse across the walls of the stainless steel to effect the necessary temperature change upon circulating blood. With respect to the filtration of blood, the modified and predicate Capiox Hardshell Reservoir relies upon mechanical entrapment of particulates and emboli within the filter media as a means to remove those particulates from the blood. The design of the modified Capiox SX oxygenator device is unaffected by the changes being incorporated at this time. The subject of this Special 510(k) is a modification being made to the Hardshell Reservoir. The design of the Hardshell Reservoir component remains identical to the design of the original reservoir that was cleared by FDA with (K961000, K962667, K993772, and K013526) except that a positive pressure relief valve will be included in the lid of the reservoir. The intent of the relief valve is to eliminate excessive pressure that could accumulate in a reservoir during bypass procedures. The materials that are used in the construction of the CAPIOX® SX Oxygenator/Hardshell Reservoir may include, but are not limited to, nylon, polycarbonate, stainless steel, polyvinyl chloride, polyurethane, polyester, polypropylene, polyethylene, and X-Coating™.

The provided text describes a 510(k) summary for a modified medical device, the Capiox® SX Oxygenator and Hardshell Reservoir. The document focuses on demonstrating substantial equivalence to predicate devices rather than proving the device's efficacy through extensive clinical studies against specific performance criteria.

Therefore, many of the requested categories for acceptance criteria and studies (like sample sizes for test/training sets, expert qualifications, ground truth establishment, MRMC studies, or standalone algorithm performance) are not applicable or not provided in this type of regulatory submission. This document describes in-vitro performance evaluations for substantial equivalence, not a study to establish clinical efficacy or AI performance.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a table with explicit acceptance criteria and corresponding reported performance metrics in the format of a typical efficacy study. Instead, it lists performance evaluations conducted to demonstrate substantial equivalence to predicate devices. The "reported device performance" is implied to meet the expectations established by the predicate devices.

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

• Sample Size: Not specified. The evaluations mentioned are primarily in-vitro tests and assessments, not typically described with "test set" sample sizes in the context of clinical data or AI model evaluation.
• Data Provenance: In-vitro performance evaluations. No information on country of origin or whether it's retrospective/prospective in a clinical sense. These are laboratory-based engineering tests.

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

• Not Applicable. This is a 510(k) submission for a modified medical device, not a study evaluating an AI algorithm's diagnostic performance requiring expert-established ground truth. The "ground truth" here is the expected physical and functional performance of the device based on engineering principles and comparison to predicate devices.

4. Adjudication Method for the Test Set

• Not Applicable. No human adjudication method described, as this is not a study requiring expert consensus on clinical findings or AI outputs.

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

• No. An MRMC study is relevant for evaluating the impact of AI assistance on human reader performance for diagnostic tasks. This document describes the substantial equivalence of a physical medical device (oxygenator/reservoir), not a diagnostic AI system.

6. Standalone (Algorithm Only) Performance

• No. This is not an AI algorithm. It's a physical medical device.

7. Type of Ground Truth Used

• Engineering Specifications and Predicate Device Performance. The "ground truth" for these performance evaluations is the established engineering design specifications for the modified device and the known, acceptable performance characteristics of the predicate devices. The goal is to show the modified device performs equivalently or within acceptable parameters.

8. Sample Size for the Training Set

• Not Applicable. There is no "training set" in the context of AI for this type of device modification. The device design and materials are based on existing engineering knowledge and the predicate device's design.

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

• Not Applicable. As there is no training set mentioned in an AI context, there's no ground truth established for it. The design of the modified device is based on internal engineering processes, regulatory requirements, and the characteristics of the predicate devices.

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The CAPIOX® RX Hollow Fiber Oxygenators with/without Hardshell Reservoir are intended to be used to exchange gases between blood and a gaseous environment to satisfy the gas exchange needs of a patient during cardiopulmonary bypass surgery.

The integral heat exchanger is used to warm or cool blood and/or perfusion fluid as it flows through the device.

The (detachable) hardshell reservoir(s) is (are) used to store blood during extra-corporeal circulation from both venous line and the cardiotomy line (via gravity or vacuum assisted venous drainage procedures). The reservoir contains a venous section that is comprised of a filter and defoamer to facilitate air bubble removal. The cardiotomy section of the reservoir contains a filter to remove particulate matter and a defoamer to facilitate air bubble removal. The reservoir may also be used for Post Operative Chest Drainage Procedures.

The CAPIOX® RX Oxygenators with/without Hardshell Reservoirs can be used in procedures lasting up to 6 hours.

The CAPIOX® RX15 is for use with patients when the required blood flow rate will not exceed 5.0 L/min when used with a 4 Liter Reservoir; and when the required blood flow rate will not exceed 4.0 L/min when used with a 3 Liter Reservoir).

The CAPIOX® RX25 is for use with patients when the required blood flow rate will not exceed 7.0 L/min.

The modified and predicate Capiox RX Oxygenator utilize a porous fiber technology to facilitate the transfer of gases between a blood-phase environment and a gas-phase environment for the intent of satisfying the gas exchange needs of a patient during cardiopulmonary bypass surgery. A wound fiber bundle offers the porous membrane surface to sufficiently permit the movement of gases through the walls of the hollow fibers via diffusion.

The modified and predicate Capiox RX device have an integrated heat exchanger that is comprised of stainless steel encased in a polycarbonate housing. The stainless steel acts as a heat transfer material that permits heat that is generated from a temperature controlled external water bath to transverse across the walls of the stainless steel to effect the necessary temperature change upon circulating blood.

With respect to the filtration of blood, the modified Capiox RX Reservoir relies upon mechanical entrapment of particulates and emboli within the filter mesh as a means to remove those particulates from the blood.

The subject of this Special 510(k) is a modification being made to the Hardshell Reservoir. The design of the Hardshell Reservoir component remains identical to the design of the original reservoir that was cleared by FDA with (K062381) - except that a positive pressure relief valve will be included on the lid of the reservoir. The intent of the relief valve is to eliminate excessive pressure that could accumulate in a reservoir during bypass procedures.

The provided text describes a 510(k) summary for the modified Capiox® RX Oxygenator/Reservoir. This is a medical device submission focused on demonstrating substantial equivalence to a predicate device, rather than a clinical study evaluating the performance of an AI algorithm or a diagnostic device.

Therefore, many of the requested categories for AI/diagnostic device studies (such as sample size for test/training sets, experts for ground truth, adjudication methods, MRMC studies, standalone performance, and data provenance) are not applicable to this type of submission.

However, I can extract information related to the performance evaluations conducted for the device.

Here's a summary based on the provided text:

Acceptance Criteria and Device Performance for Modified Capiox® RX Oxygenator/Reservoir

The submission is for a modified version of an existing device (CAPIOX® RX Hollow Fiber Oxygenator with/without Hardshell Reservoir, K062381). The modification is a change to the Hardshell Reservoir to include a positive pressure relief valve. As such, the performance evaluations are focused on demonstrating that this modification does not affect the substantial equivalence of the device and maintains its safety and effectiveness. The acceptance criteria generally revolve around maintaining the performance characteristics of the predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

Additional Information (as applicable to this type of submission):

2. Sample size used for the test set and the data provenance: This information is not provided in the summary. The studies were described as "in-vitro performance evaluations," meaning they were conducted in a laboratory setting, not with human patients. Thus, data provenance in terms of country of origin or retrospective/prospective is not applicable in the typical sense for clinical data. The exact number of units tested per evaluation is also not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: This information is not applicable. The evaluations are in-vitro physical and functional tests of a medical device, not diagnostic interpretations requiring expert consensus.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: This information is not applicable. There's no interpretive task requiring 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: This information is not applicable. This submission is for a cardiopulmonary bypass oxygenator, not an AI-powered diagnostic device.

6. If a standalone (i.e. algorithm only, without human-in-the-loop performance) was done: This information is not applicable. This is not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The "ground truth" for these in-vitro tests would be established engineering specifications, performance standards, and the known performance characteristics of the predicate device. The goal was to demonstrate that the modified device's performance aligns with these objective criteria and is "substantially equivalent."

8. The sample size for the training set: This information is not applicable. This is a physical medical device, not a machine learning model, so there is no "training set."

9. How the ground truth for the training set was established: This information is not applicable for the same reason as above.

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The CDI System 500 provides continuous, on-line monitoring of the extracorporeal partial pressure of oxygen and carbon dioxide, pH, potassium, oxygen saturation, hematocrit, hemoglobin and temperature. In addition, calculated values of base excess, bicarbonate, oxygen saturation, and oxygen consumption may also be provided. These parameters are displayed at either actual temperature or adjusted to 37°C. For documentation purposes, the system 500's integral printer provides a hard copy of displayed parameters.

The CDI™ System 500 is an AC-powered (battery back-up) microprocessor-based device used with the following components/accessories:

• CDI™ 500 Monitor
• Arterial and/or Venous Blood Parameter Modules (BPM)
• CDI™ Hematocrit/Saturation (H/S) Probe
• CDI™ 540 Gas Calibrator and Calibration Gases (A and B)
• CDI™ 510H Shunt Sensor
• Shunt Bypass Line
• CDI™ H/S Cuvette with or without extension tubing
• Monitor Mounting Hardware (Pole Clamp and Cable Head Bracket)
• Printer Paper

The CDI™ System 500 measures blood parameters in real time by utilizing a microprocessor based monitor, electro-optics modules (i.e., BPM and H/S probe), fluorescence chemistry technology, and optical reflectance technology. The electrooptics modules connect the monitor to the disposables (i.e., shunt sensor or cuvette) which are inserted into the extracorporeal circuit. Light is emitted from the modules, and the optical responses from the blood via the sensor(s) are measured by the monitor. The blood parameters are measured or calculated by the CDI™ 500 Monitor in real time, and displayed to the user via a graphical LCD display.

Here's an analysis of the provided text regarding acceptance criteria and the supporting study:

The provided document describes a 510(k) submission for a modification to the Terumo CDI™ System 500, a blood parameter monitoring system. The core of this submission is to demonstrate substantial equivalence to a predicate device, specifically focusing on a design change to improve the robustness of the Blood Parameter Module (BPM) Probe Cable-Head against moisture ingress.

Therefore, the acceptance criteria and the study primarily revolve around verifying the effectiveness and safety of this specific design change, rather than proving performance metrics for all blood parameters. The document explicitly states: "This design change did not alter the device indication for use or performance specifications."

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: The document does not explicitly state the sample size used for the verification testing. It only generally refers to "Design control activities identified the requirements for the design change, which drove the design change verification activities."
• Data Provenance: Not specified. There is no mention of country of origin, or whether the study was retrospective or prospective. Given the nature of a design change verification, it would likely be prospective testing conducted in a controlled environment.

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

• The document does not mention the use of experts to establish ground truth for this specific verification testing. The testing appears to be objective engineering verification rather than a clinical study requiring expert interpretation of results.

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

• There is no mention of an adjudication method. This type of method is typically used in clinical trials where there's subjectivity in interpreting results and multiple readers are involved. For engineering verification of moisture ingress and function, such a method would not be applicable.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and 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 device is a blood parameter monitor; it does not involve AI or human interpretation of images or complex data in a way that would necessitate an MRMC study. The verification focuses on the hardware's robustness.

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

• This question is not applicable as the device is a measurement system, not an algorithm-based diagnostic or AI-driven tool. The "standalone performance" here refers to the device's ability to measure parameters, which is the inherent function it performs without human interpretation in the loop. The verification covered the robustness of a particular component.

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

• The ground truth for this design modification verification would be objective engineering measurements and functional tests. For example:
  • Functional performance: The device successfully provides accurate blood parameter readings after exposure to high humidity (ground truth derived from reference methods for blood gas analysis).
  • Safety: Absence of electrical malfunction or other hazards after moisture exposure (ground truth defined by safety standards and direct observation).
  • Expected life: The component continues to perform functionally for a defined duration under simulated conditions (ground truth against design durability specifications).
  • The document implies that the "predefined acceptance criteria" themselves represent the ground truth for success in these tests.

8. The sample size for the training set:

• This question is not applicable as the device is not an AI/ML model that requires a training set. The "design change" refers to a hardware modification, not a software algorithm that learns from data.

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

• This question is not applicable for the same reasons as #8.

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The TLink™ DMS is an electronic clinical record keeping and reporting system indicated for use in collecting, displaying, storing and managing data from external medical devices. The system facilitates the creation of electronic patient records and enables post-procedural case reviews. Data and records can be viewed on local workstations or transferred to a central computer or hospital network for storage and post-case analysis/reporting.

The TLink™ DMS consists of the TLink™ software and hardware accessories including computers meeting minimum requirements, data entry devices (barcode laser scanner, touch screen stylus, keyboard), mounting trays and brackets, and serial converters. The system can interface with a variety of external medical devices including, but not limited to, heart-lung machines, blood parameter monitoring systems, centrifugal systems, blood gas devices, patient monitors and anesthesia monitors. Case data can be entered manually by the user or collected automatically from independent medical devices. Screen layouts are customizable to meet hospital and user requirements for patient/case records. Physiological data can be graphed at user defined time intervals for event recording. Certain calculations routinely performed by the clinician during surgery can be performed by the TLink™ DMS, e.g., Body Surface Area (based on patient height and weight data) and Fluid Balance (based on fluid input and output data). Case templates and administrative information are developed on a central computer and transferred to the satellite computer(s) connected to the external medical device(s) in the procedure rooms. Case records are then transferred back to the central computer or hospital information system for central storage and post-case analysis/reporting. All transfers between satellite and central computers are via network and/or removable media. A variety of post-procedure reports are available including case report, clinical activity, case checklist, quality assurance, audit summary report, and audit detail report.

Here's a breakdown of the acceptance criteria and study information for the TLink™ Data Management System (DMS) based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The provided documentation is a summary for a 510(k) submission, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance metrics like sensitivity/specificity for a diagnostic AI system. The acceptance criteria here are functional and validation-based, typical for a software system that manages and displays data.

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

The provided 510(k) summary does not specify a "test set" in the context of clinical data for algorithmic performance. The tests described are System & Software Design Verification Testing and System & Software Design Validation Testing. These are engineering and usability tests, not clinical performance studies involving patient data.

• Sample Size for Test Set: Not applicable in the context of clinical data. The tests refer to the comprehensive evaluation of the software and hardware system.
• Data Provenance: Not applicable. The tests are focused on the system's design and functionality, not analysis of patient data from specific origins.

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

Not applicable. As noted above, the tests are functional and validation-based, not reliant on expert-established ground truth from clinical cases.

4. Adjudication Method for the Test Set

Not applicable. No clinical test set requiring adjudication (e.g., of expert interpretations) is described.

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

No MRMC comparative effectiveness study is mentioned. This device is a data management system, not a diagnostic AI system intended to improve human reader performance in interpreting medical images or data.

6. Standalone (Algorithm Only) Performance

Yes, the studies described (System & Software Design Verification Testing and System & Software Design Validation Testing) are essentially "standalone" in the sense that they evaluate the device's functionality and adherence to design specifications and user needs. There is no human-in-the-loop performance described for these specific tests, as the device itself is designed to collect, display, store, and manage data, not to interpret it in a diagnostic manner that would typically involve a "human-in-the-loop" interaction for algorithmic decision-making.

7. Type of Ground Truth Used

The "ground truth" for the verification and validation tests described would be the design inputs and user requirements themselves. For example:

• Design Verification: The ground truth is whether the system's outputs match the specified design requirements.
• Design Validation: The ground truth is whether the system effectively meets the intended user needs under simulated use conditions.

This is not clinical ground truth (like pathology, expert consensus on imaging, or patient outcomes data) because the device's function is data management, not diagnostic interpretation.

8. Sample Size for the Training Set

Not applicable. The TLink™ DMS is a clinical information management system, not an AI or machine learning model that requires a training set of data. Its functionality is based on programmed logic and user configuration.

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

Not applicable. As there is no training set for an AI/ML model, there is no ground truth established for such a set.

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The Large (6") Roller Pump for the Terumo® Advanced Perfusion System 1 is indicated for use for up to 6 hours in the extracorporeal circulation of blood for arterial perfusion, regional perfusion, and cardiopulmonary bypass procedures, when used by a qualified medical professional who is experienced in the operation of this or similar equipment.

The image shows a device description and indications for use of the APS 1 Large (6") Roller Pump. The device is a peristaltic pump with a 6 inch diameter race that can be mounted on the base of the Advanced Perfusion System 1 (APS1) console or positioned in an optimal location in the perfusion circuit by mounting on the pole. The large roller pump can accommodate applications requiring flow rates up to 10 L/min.

Here's a breakdown of the acceptance criteria and study 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 does not explicitly state the numerical sample size used for the test set in the performance studies. It mentions "new and aged parts" but no specific quantity.

The data provenance is not explicitly stated in terms of country of origin or whether it was retrospective or prospective. Given the nature of a 510(k) submission for a design change, the testing would generally be prospective, conducted in a laboratory setting by the manufacturer.

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

This information is not provided in the document. The performance tests appear to be engineering-based (strength, reliability/durability) rather than requiring expert clinical interpretation for ground truth.

4. Adjudication Method for the Test Set

This information is not provided. Given the nature of the tests (Pass/Fail based on engineering criteria), formal adjudication by clinical experts is unlikely.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This device is a mechanical pump, not an AI-powered diagnostic or interpretive tool that would involve human readers.

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

Yes, the performance tests described (Strength, Reliability/Durability) are standalone tests of the device's mechanical integrity and function. The device itself (a roller pump) is a standalone piece of equipment. The assessment of its performance did not involve a "human-in-the-loop" component for interpretation of results, but rather its mechanical operation and ability to withstand stress.

7. Type of Ground Truth Used

The ground truth used for these performance tests appears to be engineering specifications and pre-defined acceptance criteria. For "Strength," the ground truth is defined by the "Knob/Cam Follower Impact Strength Verification" protocol. For "Reliability/Durability," the ground truth is established by "Simulated use testing... under worst-case conditions." The "Pass" result indicates that the device met these engineering and design validation targets.

8. Sample Size for the Training Set

This information is not applicable and therefore not provided. The device is a mechanical pump, not an AI/ML-based system that requires a "training set" in the context of machine learning. The design and manufacturing process would involve internal testing and validation, but not a "training set" in the computational sense.

9. How Ground Truth for the Training Set Was Established

This information is not applicable as there is no "training set" for this type of medical device.

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