Essenz HLM is intended to be used during cardiopulmonary bypass for procedures lasting six (6) hours or less.

Essenz ILBM is indicated for supplementary, in-line monitoring of the extracorporeal arterial oxygen partial pressure, venous oxygen saturation, venous hematocrit/hemoglobin, and arterial and venous temperature during cardiopulmonary bypass procedures up to six (6) hours.

Essenz HLM is a modular heart-lung machine. The device consists of a central console base for support, positioning mobility and power supply, roller and centrifugal pumps, user interface displays, controls, clamps and sensors for the monitoring of extracorporeal perfusion.

The Essenz HLM is configurable to user needs with different system components. The main configurable and optional system components consist of: Console, Cockpit, Control Units/ Console Control Units, Pumps, Bubble sensor, Level sensor, Temperature sensor, Pressure sensor, Flow Sensor, Manual Venous Occluder, Venous Clamp, Arterial Clamp, EP-Pack/ Power Pack, Cabinet (Enclosure), Mast.

Essenz ILBM is used for in-line continuous monitoring of patient's blood parameters during procedures requiring extracorporeal circulation when used with a compatible heart-lung machine.

Provided in-line measured parameters of Essenz ILBM are: In the Venous line: Haematocrit / Haemoqlobin (Hct/Hb), Venous blood oxygen saturation (sO2), Venous blood temperature (venT). In the Arterial line: Arterial blood oxygen partial pressure (pO2), Arterial blood temperature (artT).

The duration of application is limited to 6 hours of continuous use.

Essenz ILBM consists of the following components / disposables: B-Capta Venous and Arterial Sensors, Essenz ILBM Sensor Module, B-Capta Venous and Arterial Reference Element Holders, B-Capta disposable Venous and Arterial Cuvettes.

The B-Capta venous sensor is an optical sensor which measures hematocrit/hemoglobin and oxygen saturation using an optical reflectance technology when connected to its dedicated disposable cuvette. Infrared technology is used to measure the temperature of the venous blood.

The B-Capta arterial sensor is an optical sensor which measures, partial pressure of oxygen using an optical fluorescence technology when connected to its dedicated disposable cuvette. Infrared technology is used to measure the temperature of the arterial blood.

Both sensors are functionally connected to the compatible heart-lung machine. Data are displayed on the graphical user interface of the compatible heart-lung machine.

The provided document is a 510(k) premarket notification for two devices, Essenz HLM and Essenz ILBM, and focuses on demonstrating their substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria through a clinical study.

Therefore, the document does not contain the detailed information to answer most of your questions regarding acceptance criteria, study design, sample sizes, expert qualifications, or ground truth establishment as it would for a device undergoing de novo review or requiring clinical trials for efficacy.

Here's a breakdown of what can be answered based on the provided text, and what cannot:

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

• Cannot be provided. The document states "No clinical testing was conducted in support of the Essenz HLM and Essenz ILBM as the technological characteristics and indications for use are equivalent to those of the predicate devices." Instead, the submission relies on non-clinical testing (electrical safety, EMC, performance testing, software verification and validation) to demonstrate substantial equivalence to the predicate devices, implying that their performance is similar to already cleared devices. No specific performance metrics or acceptance criteria are detailed in this summary.

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

• Cannot be provided. No clinical test set data is described. The non-clinical testing does not typically refer to "sample size" in the same way a clinical study would (e.g., number of patients or cases).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Cannot be provided. Since no clinical test set requiring expert ground truth establishment was conducted, this information is not available.

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

• Cannot be provided. No clinical test set requiring adjudication is described.

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

• Cannot be provided. The devices (Heart-Lung Machine and Extracorporeal Blood-Gas Monitor) are not AI-assisted devices that would involve human readers or MRMC studies.

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

• Partially applicable, but for different device types. The devices described (Essenz HLM and Essenz ILBM) are medical devices, not AI algorithms. Their "standalone performance" is assessed through the non-clinical testing mentioned (electrical safety, EMC, performance testing, software V&V) rather than solely as an algorithm. The document explicitly states "No clinical testing was conducted."

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

• Cannot be provided. As no clinical studies demanding ground truth were performed, this information is not present. For non-clinical tests, "ground truth" would be defined by engineering specifications, reference measurements, and standard testing methodologies.

8. The sample size for the training set

• Cannot be provided. These are not machine learning/AI devices where a "training set" would be applicable in the context of clinical data.

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

• Cannot be provided. See answer to #8.

In summary, the provided FDA 510(k) summary focuses on demonstrating substantial equivalence through non-clinical testing (electrical safety, EMC, performance testing, software verification and validation) rather than presenting results from a clinical study with detailed acceptance criteria and ground truth validation.

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The Terumo® Advanced Perfusion System 1 is indicated for use for up to six 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 Terumo® Advanced Perfusion System 1 (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 Terumo CVS supplied components to define and configure a heart-lung system to meet individual institution requirements.

The System 1 components are listed below.

• . System 1 Base:
  • Chassis platform Provides operating power and back up battery power for all system O components (100/120V or 220/240V)
  • Central Control Monitor (CCM) A display used for configuration and control of o system components
  • Two roller pump hand cranks and hand crank bracket O
• Pump(s) and pump mounting hardware Up to eight pumps can be used with System 1, ● including the following:
  • 0 6" Roller Pump
  • 0 4" Roller Pump
  • O Centrifugal Control Unit with Centrifugal Drive Motor (up to 2)
• Pods
  • Air Bubble Detection Pod Used to detect air bubbles in the extracorporeal circuit, in O conjunction with the air sensor
  • Level Detection Pod Used to monitor liquid levels within a hard shell reservoir. O
  • O Pressure Pod - Used to monitor the pressure in the extracorporeal circuit
  • Temperature Pod Used to monitor the temperature in the extracorporeal circuit and / O or the patient
  • Flowmeter Pod Used to monitor flow volume and generate an alarm if backflow is O detected
  • Venous Line Occluder Pod Used with the Occluder Head to provide a computer O controlled tube clamping mechanism to regulate flow in the venous line
  • Interface Pods to enable data transfer between cardiac monitoring and data display o systems (i.e., Terumo CDI™ 500 Monitor, and TLink™ Data Management System)
• Electronic Patient Gas System (EPGS) Provides control and monitoring of the gas output to . the oxygenator
• Flexible Lamps (15 inch or 33 inch) for local illumination .
• . Mounting hardware (e.g., center poles, crossbars, and brackets)

This document refers to the Terumo® Advanced Perfusion System 1, a cardiopulmonary bypass heart-lung machine console (K221895). The submission is a 510(k) for a modified device, claiming substantial equivalence to a predicate device (K172220). The modifications primarily involve updating the Central Control Monitor (CCM) hardware and associated software due to component obsolescence. As such, the study does not involve evaluating the primary clinical performance of the heart-lung machine in a traditional sense, but rather the performance of the updated components to ensure they meet the existing safety and effectiveness standards.

Given the nature of the device (a heart-lung machine console) and the modifications being for component obsolescence, the "device performance" in relation to acceptance criteria primarily revolves around technical and functional verification rather than clinical metrics like sensitivity or specificity.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for the Test Set and Data Provenance

Due to the nature of the device modification (component obsolescence and software updates for an existing heart-lung machine console), the "tests" described are primarily engineering verification and validation activities rather than clinical trials with patient data.

• Test Set Sample Size: Not explicitly stated in terms of patient data or typical "test set" in an AI/imaging context. The testing involved various units of the device (or components thereof) for hardware and software verification. For usability validation, it involved "external perfusionists" as "usability testers," but the number of such testers is not specified.
• Data Provenance: Not applicable in the context of patient data for clinical performance. The data provenance described is from internal and external engineering testing, demonstration, inspection, and analysis by the manufacturer (Terumo Cardiovascular Systems Corporation) and external testing facilities for specific standards (e.g., electrical safety, EMC).

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

• Number of Experts: For the hardware validation (usability testing), "external perfusionists" were used as "usability testers." The specific number of these experts is not defined.
• Qualifications of Experts: They are described as "external perfusionists," implying they are qualified medical professionals experienced in operating such equipment, as per the device's indications for use.

4. Adjudication Method for the Test Set

Not applicable. The reported tests are primarily engineering and functional verification, and usability testing by qualified professionals, rather than diagnostic interpretation requiring adjudication of results.

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 typically performed to evaluate the diagnostic performance of an AI-powered system, often in comparison to human readers, and the current submission is for a hardware/software update of an existing mechanical device, not an AI diagnostic tool.

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

The device is a heart-lung machine console, which by its nature requires human operators (qualified medical professionals). Therefore, "standalone" performance in the context of an AI algorithm is not directly applicable. The device's software performance was validated through various engineering tests (system-level testing, boundary tests, code reviews, integration testing), but always in the context of its function within the complete system operated by a human.

7. The Type of Ground Truth Used

The "ground truth" here is defined by:

• Engineering Specifications and Requirements: For all hardware and software verification tests.
• Industry Standards: For electrical safety (IEC 60601-1), EMC (IEC 60601-1-2), shipping and vibration (ISTA-3A, MIL-STD-810G).
• User Needs and Risk Mitigations: For the hardware validation/usability testing.

8. The Sample Size for the Training Set

Not applicable. This submission is for a hardware/software update to an existing medical device, not an AI/machine learning algorithm requiring a "training set" of data in the conventional sense. The "software updates" mentioned are traditional programming changes to address component obsolescence and improve existing functionalities.

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

Not applicable, as there is no "training set" in the context of an AI algorithm.

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Essenz HLM is intended to be used during cardiopulmonary bypass for procedures lasting six (6) hours or less.

Essenz HLM is a modular heart-lung machine like its primary predicate Stöckert S5 System. The device consists of a central console base for support, positioning mobility and power supply, roller and centrifuqal pumps, user interface displays, controls, clamps and sensors for the monitoring of extracorporeal perfusion. The Essenz HLM is configurable to user needs with different system components. The main configurable and optional system components consist of: Console, Cockpit, Control Units/ Console Control Units, Pumps, Bubble sensor, Level sensor, Temperature sensor, Pressure sensor, Flow Sensor, Manual Venous Occluder, Electrical venous occluder (EVO), Arterial Clamp/ Electric Remote Control, EP-Pack/ Power Pack, Cabinet (Enclosure), Mast.

This FDA 510(k) summary for the Essenz HLM heart-lung machine does not contain information on acceptance criteria for device performance or a study proving that the device meets those criteria. In fact, it explicitly states "CLINICAL TESTING: None required" and "ANIMAL TESTING: None required."

The document details non-clinical testing for verification and validation, but these tests are against recognized standards for electrical safety, EMC, software, human factors, and mechanical performance, rather than specific, quantified device performance acceptance criteria.

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

Here's why the document doesn't contain the requested information in the typical format for AI/ML device evaluations:

• Device Type: The Essenz HLM is a hardware medical device (a heart-lung machine console) used for cardiopulmonary bypass. The questions you've asked (acceptance criteria, study design, sample size, ground truth, expert consensus, MRMC studies, standalone performance) are highly relevant to AI/Machine Learning (AI/ML) driven medical devices, especially those involved in diagnostic or predictive tasks where performance metrics like sensitivity, specificity, or AUC are critical and need to be validated against expert ground truth.
• Regulatory Pathway: This is a 510(k) submission, which demonstrates substantial equivalence to a predicate device. For hardware devices like this, substantial equivalence is often established through detailed comparisons of technological characteristics, materials, and non-clinical performance (electrical safety, EMC, mechanical testing, software verification) against recognized standards, rather than clinical efficacy studies on patient outcomes or AI model performance.
• Focus of the Document: The document focuses on demonstrating that the Essenz HLM is as safe and effective as its predicate through engineering verification and validation testing, not through a study evaluating its diagnostic accuracy or predictive capability.

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The Stöckert SS System is intended to be used during cardiopulmonary bypass for procedures lasting six (6) hours or less.

The S5 System is configurable to user needs with different system components. The main configurable and optional system components consist of: Console, System Panel, Pumps, Bubble detector, Level control, Temperature monitor, Pressure control, Cardioplegia Control, Electronic gas blender, Serial Data interface, Venous line clamps (manual), Electrical venous occlude (EVO).

The provided text is a 510(k) summary for the Stöckert S5 System, a Class II medical device (Heart-Lung Machine). It describes the device, its intended use, and the non-clinical testing performed to demonstrate substantial equivalence to a predicate device.

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

No specific acceptance criteria (numerical thresholds for performance metrics) or a study proving that the device meets those criteria is explicitly provided in the typical format one would expect for an AI/ML device.

The document is a 510(k) Pre-market Notification, which focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving a device meets specific performance acceptance criteria against a clinical endpoint with defined sensitivity/specificity/accuracy thresholds. The studies described are primarily verification and validation (V&V) testing to ensure the device performs as intended and is safe and effective compared to its predicate.

Therefore, the interpretation below will focus on understanding the "acceptance criteria" through the lens of substantial equivalence and the "study" as the non-clinical testing performed for this purpose.

1. Table of Acceptance Criteria and Reported Device Performance

As noted, the document doesn't provide a typical table of acceptance criteria with numerical targets (e.g., sensitivity, specificity, accuracy). Instead, the "acceptance criteria" are implied by compliance with recognized standards and successful completion of various V&V tests, demonstrating that the device functions correctly and safely. The "reported device performance" is the successful completion of these tests.

Regarding the remaining requested information, it's important to understand that this document describes a hardware/software medical device (a Heart-Lung Machine) and not an AI/ML diagnostic or prognostic algorithm. Therefore, many of the requested fields are not applicable or cannot be answered from the provided text because they relate specifically to AI/ML performance evaluation.

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

• Not Applicable / Not Provided: The nature of the testing (electrical safety, EMC, mechanical, software V&V) does not typically involve "test sets" of patient data or data provenance in the way an AI/ML diagnostic device would. These tests are performed on the device itself or its components. The document does not specify sample sizes for these engineering tests (e.g., how many units were tested for electrical safety).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not Applicable: This type of medical device (Heart-Lung Machine) does not involve establishing ground truth from expert interpretation in the context of diagnostic or prognostic tasks. The "ground truth" for its performance is determined by meeting engineering specifications and safety standards.

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

• Not Applicable: Adjudication methods are relevant for resolving discrepancies in expert interpretations of data, typically in AI/ML performance studies. This is not described for the V&V testing of a Heart-Lung Machine.

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, a MRMC study was not done. This is a non-AI/ML device. The "multi reader multi case" paradigm and "human readers improve with AI" concepts are not applicable to the S5 System as described.

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

• Not Applicable / Not Relevant in the AI/ML sense: The device is a standalone hardware/software system designed to perform its functions. The V&V testing assesses its performance in this standalone capacity. However, this is not equivalent to a "standalone" AI algorithm performance evaluation, as it's an operational medical device with human interaction as part of its intended use.

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

• Engineering Specifications and Recognized Standards: The "ground truth" for the device's performance is compliance with established engineering specifications, design requirements, and recognized international standards (e.g., IEC 60601 series, IEC 62366-1, IEC 62304, ISO 14971) for safety and effectiveness.

8. The sample size for the training set

• Not Applicable: This device is not an AI/ML system that uses a "training set" of data.

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

• Not Applicable: This device is not an AI/ML system that uses a "training set" of data.

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The Century Perfusion System is intended to be used during cardiopulmonary bypass for procedures lasting six (6) hours or less.

The Century Perfusion System is a modular system, like the Stöckert S5 System, consisting of a console base with peristaltic pumps, monitors, displays, controls, and user interfaces.

The provided text describes a 510(k) premarket notification for the Century Perfusion System, demonstrating its substantial equivalence to predicate devices (Stöckert S5 System and COBE Century Perfusion Pump). The document primarily focuses on engineering specifications, comparisons, and adherence to various medical device standards. It does not contain information about acceptance criteria or a study proving device performance in the context of AI/ML-driven medical devices, as the Century Perfusion System is a mechanical pump and not an AI/ML device.

Therefore, I cannot provide the requested information regarding:

• A table of acceptance criteria and reported device performance (in the context of AI/ML).
• Sample size used for the test set and data provenance.
• Number of experts used to establish ground truth and their qualifications.
• Adjudication method for the test set.
• Multi-reader multi-case (MRMC) comparative effectiveness study and effect size.
• Stand-alone (algorithm only) performance.
• Type of ground truth used (expert consensus, pathology, outcomes data, etc.).
• Sample size for the training set.
• How the ground truth for the training set was established.

The document states: "No clinical tests performed." and details non-clinical tests to prove safety and effectiveness through compliance with standards like IEC 60601-1, IEC 62366-1, ISO 14971, etc. It also discusses software validation for the device's control system, but this is for a general software safety classification (Class C) and not for AI/ML performance.

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The Quantum Smart Occluder is indicated for use as an accessory with the Quantum Pump Console for up to 6 hours in the extracorporeal circulation of blood for cardiopulmonary bypass procedures, when used by a qualified medical professional who is experienced in the operation of this or similar equipment.

The Quantum Smart Occluder is a clamping system for the occlusion of both arterial and venous blood lines. The Quantum Smart Occluder is designed to work with the Quantum Pump Manager software application, as part of the Quantum Pump Console (K173834). The operation of the Quantum Smart Occluder is managed from the Quantum Workstation (K163657).

The Quantum Smart Occluder has the availability for 5 sensor attachments:

• . 2 Flow Sensors
• 2 Pressure Sensors
• 1 Level Sensor .

These sensors are identical with the use of the same sensor PCB boards previously cleared with the Quantum Diagnostic Module (K173591) and Quantum Ventilation Module (K181942). These sensor connections can be used in conjunction with the sensor connections used on the Quantum Diagnostic Module (K173591) or Quantum Ventilation Module (K181942) to provide additional readings. Or used solely on the Quantum Smart Occluder to reduce the amount of cabling that is attached to the Quantum Pump Console (K173834).

This document is a 510(k) summary for the Quantum Smart Occluder. It describes a medical device, its intended use, and compares it to predicate devices to establish substantial equivalence. The document does not contain information related to specific acceptance criteria or a study proving that the device meets those criteria, particularly in the context of an AI/ML device.

The Quantum Smart Occluder is a mechanical device (an electronic tube clamp) that is an accessory to a cardiopulmonary bypass system. The performance data mentioned relates to non-clinical testing of electrical safety, EMC, electrosurgery interference, hardware, and software verification/validation. This is standard for a non-AI/ML medical device.

Therefore, I cannot provide the requested information from this document. The questions you've asked are typically relevant for AI/ML-driven devices where performance is measured against clinical ground truth and involves statistical analysis of algorithm output. This document describes a traditional medical device submission.

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The Quantum Pump Console is indicated for use for up to 6 hours in cardiopulmonary bypass procedures, when used by a qualified medical professional who is experienced in the operation of this or similar equipment.

The Quantum Pump Console is a configurable heart-lung machine consisting of various components controlled by a central workstation. The system is intended to be used in any surgery in which the patient's blood is being oxygenated extracorporeally. The modular system consists of a frame, power supply with battery backup, roller pumps, pump control module, diagnostic module and a central workstation with the user interface.

The roller pumps are available in three sizes (4", 6" and 8") and can be controlled via a centralized interface on the Quantum Workstation touchscreen or through the Quantum Pump Console, which contains five knobs and displays in one integrated console.

This document is a 510(k) summary for the Quantum Pump Console, a heart-lung machine. It determines substantial equivalence to a predicate device, the Stöckert S5 System.

Here's an analysis of the provided information regarding acceptance criteria and supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding device performance for a specific clinical or diagnostic task in the way one might expect for an AI/ML diagnostic device. Instead, the "acceptance criteria" are implied by the demonstration of "substantial equivalence" to a predicate device.

The performance data presented is primarily focused on non-clinical testing to ensure the device performs safely and effectively in its intended function, similar to the predicate.

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

This document does not describe a "test set" in the context of clinical data for AI/ML performance. The testing performed is physical/electrical/software verification and validation of the device itself.

• Sample Size for Test Set: Not applicable in the context of clinical/diagnostic performance testing using patient data. The testing involved verification and validation activities on the device hardware and software.
• Data Provenance: Not applicable for patient data. The non-clinical tests were likely conducted in a laboratory or manufacturing setting.

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

Not applicable. The ground truth for the non-clinical tests is based on engineering specifications, regulatory standards, and expected device behavior, rather than expert interpretation of patient data.

4. Adjudication Method for the Test Set

Not applicable. The non-clinical tests involve objective measurements against predefined specifications, not expert adjudication of ambiguous cases.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No MRMC comparative effectiveness study was performed or described. This is not an AI-assisted diagnostic device, but a medical device (heart-lung machine console) where the focus is on its physical and software functionality and safety compared to a predicate.

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

This question is not applicable. The Quantum Pump Console is not an algorithm-only device. It's a hardware system with integrated software, intended to be operated by a qualified medical professional. Its performance is always with a human-in-the-loop.

7. The Type of Ground Truth Used

The "ground truth" for the non-clinical tests would be:

• Engineering specifications and design requirements: For hardware and software functionality.
• Regulatory standards: For electrical safety, EMC, and other performance characteristics.
• Predicate device's known performance characteristics: To establish equivalence in pump speed, accuracy, and overall operational principles.

8. The Sample Size for the Training Set

Not applicable. This device does not use machine learning in a way that requires a "training set" of patient data.

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

Not applicable, as no training set (in the context of AI/ML) was used.

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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 Terumo CVS supplied components to define and configure a heart-lung system to meet individual institution requirements.

The System 1 components are listed below.

• · System 1 Base:
  • Chassis platform Provides operating power and back up battery power for all o system components (100/120V or 220/240V)
  • Central Control Monitor (CCM) A touch screen display used for o configuration and control of system components
  • o Two roller pump hand cranks and hand crank bracket
• · Pump(s) and pump mounting hardware Up to eight pumps can be used with System 1, including the following:
  • 6' Roller Pump O
  • o 4" Roller Pump
  • Centrifugal Control Unit with Centrifugal Drive Motor (up to 2) O
• Pods
  • Air Bubble Detection Pod Used to detect air bubbles in the extracorporeal O circuit, in conjunction with the air sensor
  • o Level Detection Pod Used to monitor liquid levels within a hard shell reservoir.
  • O Pressure Pod - Used to monitor the pressure in the extracorporeal circuit
  • Temperature Pod Used to monitor the temperature in the extracorporeal O circuit and / or the patient
  • Flowmeter Pod Used to monitor flow volume and generate an alarm if O backflow is detected
• Venous Line Occluder Pod Used with the Occluder Head to provide a O computer controlled tube clamping mechanism to regulate flow in the venous line
• Interface Pods to enable data transfer between cardiac monitoring and data o display systems (i.e., Terumo CDI™ 500 Monitor, and TLink™ Data Management System)
• · Electronic Patient Gas System (EPGS) Provides control and monitoring of the gas output to the oxygenator
• Flexible Lamps (15 inch or 33 inch) for local illumination
• · Mounting hardware (e.g., center poles, crossbars, and brackets)

The provided text describes a 510(k) premarket notification for the Terumo Advanced Perfusion System 1, which involves software modifications to an existing device. It discusses software verification and validation, and design validation testing, but does not provide explicit acceptance criteria or detailed study results in the format requested.

Here's an analysis based on the information provided and what is missing:

The document states: "Software verification and validation testing were conducted and discussion of the these activities (i.e. protocols, acceptance criteria, and test results) at the unit, integration, and system level are included as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices."". However, the actual acceptance criteria and test results are not included in the provided text.

Similarly, for design validation: "Design validation testing was conducted and demonstrates that the System 1 performs within the defined design input requirements for the proposed modifications. The following testing was performed on the subject device: . Simulated use case testing . Validation of the Instructions For Use changes". Again, the specific acceptance criteria and detailed results are not provided.

Therefore, I cannot populate the table and answer all questions directly from the given text.

Based on the available information, here's what can be extracted and what remains unknown:

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

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

• Test set sample size: Not specified in the provided text.
• Data provenance: Not specified (e.g., country of origin, retrospective/prospective). The studies are internal manufacturer testing.

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

• Number of experts: Not specified.
• Qualifications of experts: Not specified. The document mentions "qualified medical professional who is experienced in the operation of this or similar equipment" for the device's use, which might imply involvement in validating the simulated use cases, but this is an inference, not a direct statement about ground truth establishment.

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

• Adjudication method: Not specified.

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

• MRMC study: No. This device is a heart-lung machine console, not an AI diagnostic tool involving human readers.
• Effect size: Not applicable.

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

• Not applicable in the context of an "algorithm only" device in this submission. The software modifications are for a console that operates a heart-lung machine; its performance is intrinsically linked to the machine's function.

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

• For the software verification and validation, and design validation, the "ground truth" would likely be adherence to defined software requirements, design input requirements, and successful operation during simulated use testing. Specific "ground truth" types like pathology or outcomes data are not relevant for this type of device modification.

8. The sample size for the training set

• Not applicable. This is not a machine learning/AI model that requires a training set in the conventional sense. The "training" here would refer to the software development and testing cycles.

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

• Not applicable for the reasons stated in point 8.

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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 Terumo CVS supplied components to define and configure a heart-lung system to meet individual institution requirements.

The System 1 components are listed below.

• · System 1 Base:
  • Chassis platform Provides operating power and back up battery power for all o system components (100/120V or 220/240V)
  • Central Control Monitor (CCM) A touch screen display used for o configuration and control of system components
  • o Two roller pump hand cranks and hand crank bracket
• Pump(s) and pump mounting hardware Up to eight pumps can be used with System 1, including the following:
  • 6'' Roller Pump O
  • o 4" Roller Pump
  • Centrifugal Control Unit with Centrifugal Drive Motor (up to 2) O
• Pods
  • Air Bubble Detection Pod Used to detect air bubbles in the extracorporeal O circuit, in conjunction with the air sensor
  • o Level Detection Pod Used to monitor liquid levels within a hard shell reservoir.
  • O Pressure Pod - Used to monitor the pressure in the extracorporeal circuit
  • Temperature Pod Used to monitor the temperature in the extracorporeal O circuit and / or the patient
  • Flowmeter Pod Used to monitor flow volume and generate an alarm if O backflow is detected
• Venous Line Occluder Pod Used with the Occluder Head to provide a o computer controlled tube clamping mechanism to regulate flow in the venous line
• Interface Pods to enable data transfer between cardiac monitoring and data o display systems (i.e., Terumo CDI™ 500 Monitor, and TLink™ Data Management System)
• · Electronic Gas Blender Provides control and monitoring of the gas output to the oxygenator
• Flexible Lamps (15 inch or 33 inch) for local illumination
• · Mounting hardware (e.g., center poles, crossbars, and brackets)

This document describes a 510(k) premarket notification for the Terumo® Advanced Perfusion System 1, focusing on modifications to the device. Please note that this submission primarily addresses engineering modifications (hardware and software) to an existing device and therefore does not include information typically found in studies for a novel AI device, such as training sets, ground truth establishment for AI, expert adjudication methods, or MRMC studies.

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

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly listed in a detailed table format within the document. However, the performance data section indicates that the device was evaluated against existing safety and performance standards for medical devices. The reported device performance is that it complies with these standards.

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

The document does not specify a distinct "test set" in the context of an AI/ML model for which a sample size or data provenance would be relevant. The testing performed was on the modified System 1 device itself.

• Sample Size for Test Set: Not applicable in the context of an AI/ML test set. The entire modified device was subjected to testing.
• Data Provenance: Not applicable. The testing relates to the function of hardware and software modifications of the device, not analysis of external data.

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

Not applicable. This submission is for engineering modifications to a medical device, not an AI/ML model that requires human expert annotation for ground truth.

4. Adjudication Method for the Test Set

Not applicable. No expert adjudication method is mentioned as the testing performed was focused on device functionality and compliance with engineering standards.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, If So, What Was the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

No. An MRMC study was not conducted or mentioned, as this submission is not for an AI-assisted diagnostic or therapeutic device.

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

Not applicable. The device is not an algorithm-only product. It is a cardio-pulmonary bypass machine. Software verification and validation were performed on the embedded software within the device, which is an integral part of its function, not a standalone algorithm.

7. The Type of Ground Truth Used

The "ground truth" in this context refers to the defined engineering specifications and regulatory standards that the device performance was measured against.

• Type of Ground Truth: Engineering specifications for hardware and software functionality, and compliance with recognized Consensus Standards (IEC 60601-1, IEC 60601-1-2) and FDA guidance for software in medical devices.

8. The Sample Size for the Training Set

Not applicable. There is no mention of a "training set" in the context of an AI/ML model. The software modifications were developed and verified, but this is distinct from training an AI model on a dataset.

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

Not applicable. As there is no AI/ML training set, the establishment of ground truth for such a set is not relevant to this submission.

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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 heartlung 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 Terumo CVS supplied components to define and configure a heart-lung system to meet individual institution requirements.

The System 1 components are listed below.

• · System 1 Base:
  • Chassis platform Provides operating power and back up battery power for all O system components (100/120V or 220/240V)
  • Central Control Monitor (CCM) A touch screen display used for O configuration and control of system components
  • Two roller pump hand cranks and hand crank bracket O
• · Pump(s) and pump mounting hardware Up to eight pumps can be used with System 1, including the following:
  • 6" Roller Pump O
  • 4" Roller Pump o
  • Centrifugal Control Unit with Centrifugal Drive Motor (up to 2) O
• Pods
  • Air Bubble Detection Pod Used to detect air bubbles in the extracorporeal O circuit, in conjunction with the air sensor
  • Level Detection Pod Used to monitor liquid levels within a hard shell o reservoir.
  • Pressure Pod Used to monitor the pressure in the extracorporeal circuit O
  • Temperature Pod Used to monitor the temperature in the extracorporeal O circuit and / or the patient
  • Flowmeter Pod Used to monitor flow volume and generate an alarm if O backflow is detected
• Venous Line Occluder Pod Used with the Occluder Head to provide a O computer controlled tube clamping mechanism to regulate flow in the venous line
  • Interface Pods to enable data transfer between cardiac monitoring and data o display systems (e.g., Terumo CDI™ 100 Monitor, CDI™ 500 Monitor, and TLink™ Data Management System)
• · Electronic Gas Blender Provides control and monitoring of the gas output to the oxygenator
• Flexible Lamps (15 inch or 33 inch) for local illumination
• · Mounting hardware (e.g., center poles, crossbars, and brackets)

This document pertains to the resubmission of the Terumo Advanced Perfusion System 1 (K153376) due to a hardware modification. As such, the information provided focuses on the substantial equivalence to a previously cleared device (K151349) rather than a full de novo acceptance criteria study for a new device. Therefore, many of the typical study details for an AI/algorithm-based device are not applicable or not provided in this regulatory document.

However, based on the provided text, I can infer and extract the following:

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

Explanation: The primary goal of the hardware modification was to address a potential issue with the On/Off switch that could lead to power loss. The "acceptance criteria" here is implicitly that the modification successfully resolves this issue. The "reported device performance" directly states that the modification achieves this.

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

• Sample Size for Test Set: Not specified. The document states "successful design verification and validation testing," but does not provide details on the number of units or test scenarios used.
• Data Provenance: Not specified. Given this is a hardware modification for an existing device, it's likely testing was conducted internally by the manufacturer, Terumo Cardiovascular Systems Corporation, based in Ann Arbor, Michigan, USA. The nature of testing points to prospective testing of the modified hardware.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

• Number of Experts: Not applicable. This is a hardware modification of a medical device, not an AI/algorithm-based diagnostic or prognostic tool that relies on expert interpretation for ground truth. The "ground truth" here is the functional performance of the hardware.
• Qualifications of Experts: Not applicable in the context of expert review for ground truth as described for AI/algorithm studies. The testing would have been performed by engineers and quality assurance personnel.

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

• Adjudication Method: Not applicable. This is not a study requiring adjudication of interpretations from multiple experts. The "ground truth" is determined by successful functional testing of the hardware.

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

• MRMC Study: No. This document describes a hardware modification to an existing heart-lung machine console, not an AI-assisted diagnostic or therapeutic device. Therefore, a MRMC comparative effectiveness study involving human readers and AI assistance is not relevant and was not conducted.

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

• Standalone Performance Study: Not applicable. This device is a console that requires human operation ("when used by a qualified medical professional who is experienced in the operation of this or similar equipment"). It is not an algorithm that performs a function independently.

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

• Type of Ground Truth: The "ground truth" for this hardware modification is the demonstrable stable and reliable operation of the On/Off switch and the prevention of inadvertent power loss, as confirmed by design verification and validation testing. This would involve functional tests, electrical safety tests, and potentially stress tests to ensure the new component meets its intended performance specifications.

8. The sample size for the training set:

• Sample Size for Training Set: Not applicable. This device is a hardware system, not an AI/machine learning algorithm that requires a training set.

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

• How Ground Truth for Training Set was Established: Not applicable, as there is no training set for this hardware device.

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