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The system is intended for use by a qualified physician for diagnostic ultrasound imaging or fluid flow analysis of the human body in Fetal/Obstetric, Gynecological, Abdominal (renal, Gyn/Pelvic), Small Organ (thyroid, breast, testes, etc.), Adult Cephalic, Trans-cranial, Musculoskeletal (conventional & superficial), Cardiac-Adult/Pediatric/Fetal. Transesophageal (Cardiac), Peripheral vascular.

The UF-760AG ultrasound instrument is intended to perform the following diagnostic ultrasound investigations: Imaging (B-mode, 3D/4D, harmonic imaging), Time motion (M-mode), Pulsed wave Doppler (PW Doppler), Continuous wave Doppler (CW Doppler), Power Doppler Tissue Imaging, Color Flow Mapping (CFM) and Color Time Motion (CM)

The UF-760AG ultrasound instrument is intended to perform the following diagnostic ultrasound investigations: Imaging (B-mode, 3D/4D), Time motion (M-mode), Pulsed wave Doppler (PW Doppler), Continuous wave Doppler (CW Doppler), Color Flow Mapping (CFM) and Color Time Motion (CM).

The submission also includes the transducers necessary for these procedures.

The system is a portable unit approximately 14.5" wide, 14.4" deep and 3.9" high equipped with a keyboard control panel, a 15" TFT screen, assorted transducers and image storage or hard-copy devices.

The provided text is a 510(k) summary for the Fukuda Denshi UF-760AG Diagnostic Ultrasound Imaging System. It describes the device, its intended use, and states that clinical tests were not required because the device uses the same technology and principles as existing predicate devices. Therefore, there is no study provided that proves the device meets specific acceptance criteria based on clinical performance.

The document focuses on demonstrating substantial equivalence to already cleared devices based on non-clinical performance and technological characteristics.

Here's an attempt to answer your questions based solely on the information available in the provided text, acknowledging the absence of a clinical performance study:

1. Table of Acceptance Criteria and Reported Device Performance

Since no specific quantitative acceptance criteria or clinical performance metrics are provided, this table cannot be fully populated as you requested for a device performance study. The "performance" described is largely about compliance with safety standards and the device's functional modes.

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

• Sample Size for Test Set: Not applicable. No clinical test set data is described.
• Data Provenance: Not applicable for clinical data. For non-clinical testing, the evaluations were conducted by Fukuda Denshi and independent evaluators. The country of origin for these analyses would be Japan (Fukuda Denshi's location) but is not explicitly stated for individual tests. The testing would be considered prospective for the device's development/verification.

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

• Not applicable. No clinical ground truth establishment is described due to the absence of clinical testing.

4. Adjudication Method for the Test Set

• Not applicable. No clinical test set and thus no adjudication method 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

• Not applicable. This is an ultrasound imaging system, not an AI-assisted diagnostic tool. No MRMC study was performed or mentioned.

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

• Not applicable. This is not an algorithmic diagnostic device, but a medical imaging system.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc)

• Not applicable for clinical ground truth. The "ground truth" for the non-clinical performance would be the specifications and requirements defined by the various safety and performance standards (e.g., meeting specific acoustic output limits, ensuring biocompatibility, electrical safety parameters).

8. The Sample Size for the Training Set

• Not applicable. This is not an AI/machine learning device that requires a training set in the conventional sense. The "training" for a device like this would involve design and engineering processes, validation against specifications, and quality controls without explicit data training sets.

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

• Not applicable for the same reasons as point 8.

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Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows: Fetal, Abdominal, Pediatric, Small organs (Thyroid, Breast, Testicle), Adult Cephalic, Cardiac, Transesophageal, Transvaginal, Peripheral Vascular, Musculo-skeletal Conventional, Musculo-skeletal Superficial.
Mode of Operation: A, B, M, PW D, CW D, Color Doppler, Amplitude Doppler, Combined (B + M, B + PWD, Color Doppler + PWD, Amplitude Doppler + PWD).

The UF-870AG is an ultrasound instrument intended to perform the following diagnostic ultrasound investigations: Imaging (B-mode), Time motion (M-mode), Pulsed wave Doppler (PW Doppler), Continuous wave Doppler (CW Doppler), Color Flow Mapping (CFM) and Color Time motion (CM mode). The submission also includes the transducers necessary for these procedures. The system is a mobile console approximately 19" wide, 31" deep and 53-57" high equipped with a keyboard control panal, a large TFT screen, assorted transducers and image storage or hard-copy devices.

This document is a 510(k) premarket notification for the Fukuda Denshi UF-870AG Diagnostic Ultrasound System. It details the device's intended use and claims substantial equivalence to predicate devices, therefore, it does not contain a study and acceptance criteria proving device performance in the way a clinical trial or performance study would for a novel device.

Here's an analysis of the provided information:

1. Table of acceptance criteria and reported device performance:

This section is not applicable as the document is a 510(k) submission asserting substantial equivalence, not a performance study with acceptance criteria and measured performance metrics for a novel AI device. The "performance data" mentioned refers to non-clinical tests for safety and conformance with standards, not performance metrics of an AI algorithm against a specific ground truth.

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

This is not applicable. The submission states: "Clinical tests: Since the UF-870AG uses the same technology and principles as existing E. devices, clinical tests are not required." Therefore, there is no test set, no sample size, and no data provenance from a clinical study for performance evaluation.

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

This is not applicable as no clinical tests were performed to establish a ground truth for a test set.

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

This is not applicable as no clinical tests were performed.

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 is not applicable. The device is an ultrasound imaging system, not an AI-assisted diagnostic tool for which MRMC studies are typically conducted to evaluate reader performance.

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

This is not applicable. The device is a traditional ultrasound system, not an AI algorithm.

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

This is not applicable as no clinical performance studies requiring ground truth were conducted for this 510(k) submission.

8. The sample size for the training set:

This is not applicable. The UF-870AG is a conventional medical diagnostic ultrasound imaging system; it does not utilize AI algorithms that require a training set in the context of machine learning.

9. How the ground truth for the training set was established:
This is not applicable. As it's not an AI device, there's no training set or ground truth in that context.

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