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The AblatePal Radiofrequency Ablation System is designed to provide monopolar radiofrequency (RF) energy to be used for coagulation and ablation of soft tissue.

The device is a prescription device.

The AblatePal Radiofrequency Ablation System (subject device) (HFM01-MD2202) is a monopolar radiofrequency (RF) generator with dedicated components and accessories. The generator can be operated in only impedance mode that use various combinations of time, tissue temperature, tissue impedance, and manual control. An interactive touchscreen display allows user input to the generator and displays informational signals and alert messages. Active electrodes are placed in the tissue to deliver RF energy to the tissue to be ablated. Only one electrode can be attached to the generator and can be used individually. During the ablation of tissue, RF current flows from the generator to an active electrode which delivers the current to the patient. The RF current flows from the active electrode through the patient's body tissue to the Neutral Electrode, which recovers the current and returns it to the qenerator. The resistance to the current, provided by the patient's tissue, produces the heat that is necessary for ablation of tissue.

The dedicated system components include:

• o RF Generator, radiofrequency generator
• . Ablation Foot Switch (HFM01-AF0002): Single Foot Switch. Pressing the foot switch that RF Generator starts or stops ablating.
• . Power Control Foot Switch (HFM01-AF0001): Double Foot Switch. Pressing the foot switch to adjust power in whole units of Watts that the RF Generator will deliver during the ablation. The blue foot switch can increase the power, and the yellow foot switch can decrease the power.
• . Power Cord (WS-001H+WS-002): A line cord that provides AC power to the RFA system.
• Electrode Kit (HFM01-AC0001~ HFM01-AC0006), including radiofrequency electrode, inflowo outflow tubing sets and Neutral Electrodes (HFM01-AE0001).

The generator is packaged individually and is always supplied with the accessory items: footswitch and cables. The electrode kit HFM01-AC0001~ HFM01-AC0006 is separately packaged.

The following AblatePal Radiofrequency Ablation System compatible accessories are single use:

• . Electrode Kit (HFM01-AC0001~ HFM01-AC0006), including a radiofrequency electrode, inflow-outflow tubing sets and Neutral Electrodes.

The provided text describes a 510(k) premarket notification for the AblatePal Radiofrequency Ablation System. It details the device, its intended use, comparison to a predicate device, and various performance testing. However, it does not contain a table of numerical acceptance criteria or specific study data demonstrating the device meets those criteria in a quantitative sense.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device (Cool-tip™ RF Ablation System) through bench testing, electrical safety, EMC, and ex-vivo animal testing. The "acceptance criteria" discussed are largely qualitative and relate to conformity with applicable standards and performance parity with the predicate.

Given the information provided, the following points can be extracted or inferred, but a direct answer to all parts of your request for a numerical acceptance criteria table and explicit study details meeting them is not possible from this document.

Summary of Device Acceptance and Study (Based on Provided Text):

The AblatePal Radiofrequency Ablation System aims to demonstrate substantial equivalence to its predicate device (Cool-tip™ RF Ablation System) by showing it performs similarly and meets relevant safety and performance standards. The "acceptance criteria" are implied through conformity to these standards and demonstrated clinical parity.

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

As mentioned, a formal table with quantitative acceptance criteria and reported device performance is not present in the provided text. The document refers to meeting design and performance requirements necessary to prove substantial equivalence and ablation performance design requirements, implying the predicate's performance characteristics serve as a benchmark.

However, some comparative performance specifications are given in the "Comparison of Technological Characteristics with the Predicate Device" table (page 5):

Note: The comparisons state "Accuracy of the subject device is in the range of that of the predicate device" for output frequency. For power output accuracy, the subject device's ±20% is wider than the predicate's ±15%, but the document implies this is acceptable due to overall performance data.

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

• Sample Size for Test Set: The document mentions "soft tissue performance providing a characterization of the AblatePal Radiofrequency Ablation System ablation performance across the complete range of modes, electrodes, and in three tissue types: liver, kidney, and muscle." It also states "Ex-vivo testing conducted demonstrated the histological, thermal and ablative performance." No specific numerical sample sizes (e.g., number of tissues, number of ablation cycles) are provided for these tests.
• Data Provenance:
  • Country of Origin: Not explicitly stated for the testing, but the submitter (Compal Electronics, Inc.) is based in Taipei City, Taiwan (R.O.C.).
  • Retrospective or Prospective: The testing described (bench, ex-vivo animal) is inherently prospective as it's conducted to evaluate the device.

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

• Not Applicable. The described testing largely involves objective measurements of physical and electrical parameters, as well as histological analysis of ablated tissues. These typically do not rely on "expert consensus" in the same way an AI diagnostic imaging device would. Histological analysis would be performed by qualified pathologists, but the number is not specified.

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

• Not Applicable. As the tests are objective measurements and histological assessments, an adjudication method for human readers or interpretations is not relevant to the described studies.

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 is designed for AI-assisted diagnostic tools involving human readers. The AblatePal Radiofrequency Ablation System is an electrosurgical device for tissue ablation, not a diagnostic AI tool. Therefore, such a study was not performed.

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

• Yes, in essence. The "Performance Testing" described (electrical safety, EMC, soft tissue performance, ablation zone dimensions, usability validation, packaging) is primarily a standalone evaluation of the device's technical and physical performance characteristics. The software component, categorized as "Moderate Level of Concern," also underwent standalone system-level software testing.

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

• Reference Standards/Objective Measurements: For electrical and physical properties (impedance, temperature, power output, dimensions), the ground truth is the calibrated measurement and engineering specifications.
• Histology/Pathology: For ex-vivo animal testing, the "histological, thermal and ablative performance" would be assessed against established histological criteria and thermal profiles by qualified professionals (e.g., pathologists).
• Applicable Standards: Compliance with IEC 60601-1, IEC 60601-1-2, and IEC 60601-2-2 serves as a "ground truth" for electrical safety and EMC.

8. The sample size for the training set:

• Not Applicable. This device is not an AI/ML-based system that requires a "training set" in the context of data-driven learning. It's a radiofrequency ablation system that operates based on established physical principles and control algorithms.

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

• Not Applicable. See point 8.

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The Apache Ultrasound System (Model: C62) is intended for diagnostic ultrasound imaging and fluid flow analysis in the following applications: Abdominal, Fetal/Obstetric, Gynecological, Fetal Echo, Musculo-skeletal (conventional), Urology, and Pediatric. The system provides diagnostic ultrasound imaging in B, Color Doppler, and M modes. The clinical environments where the system can be used include physician offices, clinics, and clinical point-of-care for diagnosis of patients except environments where intensity of electromagnetic disturbances is high. The Apache Ultrasound System is a portable ultrasound system intended for use in environments where healthcare is provided by trained healthcare professionals.

The Apache Ultrasound System is a portable color ultrasound imaging system, capable of producing high detail resolution intended for clinical diagnostic imaging applications through wireless communication with an off-the-shelf (OTS) mobile device.

This system is a general purpose, software controlled, diagnostic ultrasound system. Its basic function is to acquire ultrasound data and display the image in B-Mode, M-Mode and Color Doppler or a combination of these modes. The Apache Processes the ultrasound signal and transfers real-time scan image data to the Apache App through the wireless connection with the mobile device. The 64-channel beamforming architecture of the probe maximizes the utility of all imaging transducer elements to enhance the diagnostic utility and confidence provided by the system. The Apache App provides the user interface for mode/setting control and image display, acquisition and storage functions. The Apache App is compatible with Android based mobile devices. Verified devices include Samsung Galaxy S10, Google Pixel 4, HTC U11, and LG G85 ThinQ.

The clinical environments where the system can be used include physician offices, clinics, hospitals, and clinical point-of-care for diagnosis of patients except environments where intensity of electromagnetic disturbances is high.

The Apache Ultrasound System is a portable ultrasound system intended for use in environments where healthcare is provided by trained healthcare professionals.

The provided text describes a 510(k) premarket notification for the "Apache Ultrasound System (Model C62)". This document focuses on demonstrating substantial equivalence to a predicate device, rather than proving that the device meets specific performance acceptance criteria through the kind of studies typically performed for AI/ML-based diagnostic devices (e.g., studies evaluating sensitivity, specificity, or reader performance).

Therefore, many of the requested details regarding acceptance criteria for diagnostic performance and specific study methodologies (like sample sizes for test/training sets, expert adjudication, MRMC studies, standalone performance, and ground truth establishment) are not present in this type of FDA submission.

Instead, this submission primarily relies on:

1. Comparison to a Predicate Device: Demonstrating that the new device has the same intended use, indications for use, and similar technological characteristics as a legally marketed device.
2. Compliance with Non-Clinical Standards: Showing that the device meets established safety and performance standards for ultrasound equipment (e.g., electrical safety, electromagnetic compatibility, acoustic output, usability, biocompatibility, software lifecycle, risk management).

Here's an attempt to answer your questions based only on the provided text, highlighting where information is absent or not applicable to this type of submission:

Acceptance Criteria and Device Performance (as per 510(k) for substantial equivalence)

Since this is a substantial equivalence submission for an ultrasound imaging system, the "acceptance criteria" are primarily related to safety, fundamental performance characteristics, and similarity to the predicate device, rather than diagnostic accuracy metrics of an AI/ML algorithm.

1. Table of Acceptance Criteria and Reported Device Performance

Regarding Specific Diagnostic Performance Studies (AI/ML context):

The provided 510(k) summary is for a general-purpose diagnostic ultrasound system, not an AI/ML diagnostic algorithm. Therefore, many of your questions about diagnostic performance studies (sample size, experts, ground truth, MRMC, standalone performance, training sets) are not applicable to this document because such studies are not typically required for a 510(k) submission for a conventional ultrasound device, especially when claiming substantial equivalence and introducing "no new indications for use, modes, features, or technologies relative to the predicate devices (Clarius Scanner) that require clinical testing."

Here's an explicit breakdown of why these questions cannot be answered from the text:

2. Sample size used for the test set and the data provenance: Not applicable. No diagnostic performance test set described.
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. No diagnostic performance test set described.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. No diagnostic performance test set 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: Not applicable. This is a conventional ultrasound system, not an AI-assisted diagnostic device described in this submission.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is a conventional ultrasound system, not an AI-enabled algorithm with standalone performance metrics.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. No diagnostic performance study for which ground truth would be established is mentioned.
8. The sample size for the training set: Not applicable. There is no mention of an AI/ML model that would require a training set.
9. How the ground truth for the training set was established: Not applicable. There is no mention of an AI/ML model that would require a training set.

Conclusion from the text:

The submission concludes: "The Apache Ultrasound System is substantially equivalent to the predicate device. The Apache Ultrasound System function in a manner similar to and are intended for the same use as the predicate device. Based on the predicate device comparison of indications for use, labeling, acoustic output and general safety and effectiveness information, as well as the non-clinical performance test results, it is concluded that this device is as safe and effective as the predicate device for its intended use and performance, and is substantially equivalent to the predicate device."

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