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The Terumo® Advanced Perfusion System 1 is indicated for up to 6 hours of use in extracorporeal circulation of blood for arterial perfusion, regional perfusion, and cardiopulmonary bypass procedures only, and intended to be used by a qualified perfusionist who is experienced in the operation of Sarns™ brand or similar equipment.

The centrifuqal pump is indicated for use in cardiopulmonary bypass procedures only.

The Terumo® Advanced Perfusion Svstem 1 is a highly configurable 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. Within reason, the system should allow users to define and configure a system to meet their individual requirements, and as needed, adapt the configuration as their needs change. The basic Terumo® Advanced Perfusion System 1 consists of a Chassis platform which provides operating power and battery back-up power for all other devices of the system that enable, facilitate or improve the intended use of the product and integrated functions, the Central Control Monitor which through its software and display touch screen facilitates the configuration and control of all other components, the Air Bubble Detect Module which is used to detect gross air bubbles in the arterial line of the perfusion circuit with the Terumo® Air Sensor, and the Level Detect Module which is used to monitor blood levels within a hard shell reservoir with the Terumo® Level Sensors. The following modules may also be used to enhance the abilities of the Terumo® Advanced Perfusion System 1: Temperature Module, Pressure Module, Flowmeter Module, Occluder Module, RS-232 Interface Module, RS-485 Interface Module, CDI™ 100 Interface Module, CDI™ 500 Interface Module, 6" diamter race Roller Pump, 4" diameter race Roller Pump, Centrifuqal Control Module, and a 33" or 15" Lamp. This design allows perfusionists to select the number and types of the accessory devices needed to control and monitor patient perfusion during cardiopulmonary bypass.

The provided document is a 510(k) summary for the Terumo® Advanced Perfusion System 1. It details the device's description, indications for use, and a comparison to predicate devices, along with a statement about performance testing. However, it does not include specific quantitative acceptance criteria or detailed results from a study proving the device meets those criteria.

The document states: "The performance characteristics of the Terumo® Advanced Perfusion System 1 were exhaustively tested and compared with the performance characteristics of the currently marketed Sarns™ 8000 Modular Perfusion System, Sarns™9000 Heart-Lung Console, Sarns™ 8000 Roller Pump, Sarns™ 9000 Universal Roller Pump, Flow Sensor Centrifugal Control Module, and Delphin II/Stand-Alone Centrifugal Module. All new and existing performance characteristics of the Terumo® Advanced Perfusion System 1 have been validated."

And "The Terumo® Advanced Perfusion System 1 perform as intended according to its performance specifications. The Terumo® Advanced Perfusion System 1 is substantially equivalent to its predicated devices."

This indicates that internal performance specifications were used as acceptance criteria, and testing was conducted to demonstrate substantial equivalence to predicate devices. However, the specific metrics, thresholds, and study designs are not disclosed in this summary.

Therefore, based on the provided text, I cannot complete a table of acceptance criteria with reported device performance, nor can I provide answers to most of the specific questions regarding the study design (sample size, ground truth, experts, adjudication, MRMC, or standalone performance).

The document focuses on demonstrating substantial equivalence to existing devices rather than providing detailed quantitative efficacy data that would be typical for an AI/ML diagnostic device with clear performance metrics.

Here's what can be extracted and what cannot be from the provided document:

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

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

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective). The testing appears to be non-clinical, likely laboratory-based, comparing performance to predicate devices.

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/Not specified. This is a medical device (perfusion system), not an AI/ML diagnostic requiring expert ground truth in the same way. The "ground truth" would be established by engineering specifications and direct measurement/testing.
• Qualifications of Experts: Not applicable/Not specified.

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

• Adjudication Method: Not applicable/Not specified. This type of adjudication is typically for subjective interpretations, which isn't directly relevant to the performance testing of a perfusion system described here.

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 is not an AI/ML diagnostic requiring human reader interpretation. The device is for "extracorporeal circulation of blood" and operated by a "qualified perfusionist."
• Effect Size: Not applicable.

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

• Standalone Performance: Not applicable as an AI/ML algorithm. The device itself is a system with components, and its "standalone" performance would refer to its functional operation as designed, independent of human interaction beyond normal operation by a perfusionist. The document states its performance was "exhaustively tested."

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

• Type of Ground Truth: For this type of medical device, the "ground truth" for performance testing would be established by engineering specifications, direct physical measurements, and comparison to the known performance of predicate devices under controlled conditions. It's not based on expert consensus, pathology, or outcomes data in the way an AI diagnostic would be.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This device is not an AI/ML algorithm that requires a "training set." Its design and functionality are based on established engineering principles and existing technologies.

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

• Ground Truth for Training Set: Not applicable. There is no AI/ML training set mentioned or implied for this device.

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The Sarns 8000 Cardioplegia Monitor is indicated to measure extracorporeal line pressure and signal when the pressure exceeds the operator-set limit. either providing an alert or triggering an alarm which stops the cardioplegia pump only. The monitor also measures temperatures of the patient or extracorporeal circuit, counts the time during and between cardiopleqia doses, and tracks the volume of cardioplegia delivered.

The Sarns 8000 Cardioplegia Monitor is only compatible with the Sarns 8000 Modular Perfusion System. The Sarns 8000 Cardioplegia Monitor can display two pressures and three temperatures from attached probes. The pressure has alert and alarm levels which are set by the operator. The Sarns 8000 Cardioplegia Monitor also has a timer for use in tracking the time during and between doses of cardioplegia. With the new added features, it also displays the volume of cardioplegia delivered to the patient. The Sarns 8000 Cardioplegia Monitor communicates with the Sarns 8000 Roller Pump for obtaining volume information and to stop the roller pump (designated for cardioplegia delivery) during a pressure alarm condition if set by the operator to do so. The Sarns 8000 Cardioplegia Monitor also communicates with the Sarns 8000 Data Communications Module for purposes of data acquisition.

The provided text is a 510(k) summary for the Sarns 8000 Cardioplegia Monitor and does not describe acceptance criteria, performance data, or a study that typically involves AI or human interpretation elements. The device is a monitor for extracorporeal line pressure, temperature, time, and cardioplegia volume, and the document focuses on its substantial equivalence to predicate devices and software modifications.

Therefore, many of the requested items (e.g., sample size for test/training sets, experts for ground truth, adjudication methods, MRMC studies, standalone performance, type of ground truth for AI, etc.) are not applicable to the information provided in this regulatory submission.

However, based on the nonclinical performance section, we can infer some information that partially addresses your request, specifically point a.

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

Based on the "Nonclinical Performance" and "Conclusions from Nonclinical Tests" sections, the implied acceptance criterion is that the device functions as intended according to its performance specification.

The following points cannot be answered from the provided text as they relate to AI/machine learning studies or clinical trials, which were not part of this device's submission or testing.

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

• Not applicable; no "test set" in the context of AI/ML or clinical data is mentioned. The testing was nonclinical and focused on software validation.

c. 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; no expert-established ground truth is mentioned. The "ground truth" for this device would be its engineering specifications and correct functional operation.

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

• Not applicable; no adjudication method is mentioned as this was a nonclinical software validation.

e. 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; no MRMC study, human readers, or AI assistance is mentioned.

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

• Not applicable; no standalone algorithm performance in the context of AI is mentioned. The device itself is an "algorithm only" device in a sense, as it performs its functions without direct human intervention once parameters are set, but this is not typically what is meant by "standalone performance" in AI contexts.

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

• The "ground truth" for this device's performance would be engineering and software validation against pre-defined functional specifications.

h. The sample size for the training set

• Not applicable; no training set (in the context of AI/ML) is mentioned.

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

• Not applicable; no training set is mentioned.

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