Search Results

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

• AAMI/ANSI ES60601-1 (Medical Electrical Equipment - General Requirements for Basic Safety and Essential Performance)
• IEC 60601-1-2 (Electromagnetic Compatibility)
• IEC 60601-1-6 (Usability)
• IEC 60601-2-37 (Particular requirements for ultrasonic medical diagnostic and monitoring equipment)
• IEC 62133 (Secondary Cells and Batteries Safety)
• IEC 62366 (Application of Usability Engineering)
• ISO 10993-1, -5, -10 (Biological Evaluation - Cytotoxicity, Irritation, Skin Sensitization)
• IEC 62304 (Medical Device Software Life Cycle Processes)
• ISO 14971 (Risk Management)
• NEMA UD 2 (Acoustic Output Measurement Standard)
  Performance: The device has undergone non-clinical testing demonstrating compliance with these safety and performance standards. |

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."

Ask a specific question about this device