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The FUJIFILM ultrasonic processor SP-900 is intended to be used in combination with FUJIFILM Ultrasonic Probe, video processor, light source, monitor, recorder, and various peripheral devices. The product is intended to provide ultrasonic images of the gastrointestinal tract, biliary and pancreatic ducts and surrounding organs, airways and tracheobronchial tree for observation, recording and to aid in diagnosis during endoscopic evaluation. Modes of Operation: B-mode

This product is a medical ultrasonic probe. It is intended for the observation and diagnosis of the gastrointestinal tract, biliary and pancreatic ducts and surrounding organs, airways and tracheobronchial tree under the management of physicians at medical facilities. Modes of Operation: B-mode

The FUJIFILM Ultrasonic Processor SP-900 and FUJIFILM Ultrasonic Probe PB2020-M2 consists of five components: 1) processor (SP-900), 2) probe (PB2020-M2), 3) control pad (CP-900), 4) scanner (RS-900), and 5) power cord. SP-900 generates ultrasound waves into the body cavity by driving the ultrasonic transducer installed in PB2020-M2, which is inserted through the forceps channel of an endoscope. SP-900 processes the reflected ultrasound signals which PB2020-M2 receives in the body cavity and further converts the processed electrical signals to relay to a monitoring system. SP-900 can acquire and display real-time ultrasound data in B-mode. CP-900 is used to control operational features of SP-900. RS-900 provides the mechanical scanning for acquiring a two-dimensional image. The power cord supplies power to SP-900.

This FDA 510(k) summary describes the substantial equivalence of the FUJIFILM Ultrasonic Processor SP-900 and FUJIFILM Ultrasonic Probe PB2020-M2 to their predicate devices. It focuses on the comparison of technological characteristics and safety testing, rather than an AI/ML-driven device's performance evaluation against specific acceptance criteria related to diagnostic accuracy or clinical outcomes.

Therefore, many of the requested elements for describing "acceptance criteria and the study that proves the device meets the acceptance criteria" for an AI/ML device, such as those related to diagnostic performance (sensitivity, specificity, AUROC), expert ground truth establishment, MRMC studies, and training/test set details, are not applicable to this submission.

This submission is for a medical imaging device (ultrasound processor and probe), not an AI/ML diagnostic or assistive device. The "performance data" section focuses on electrical safety, EMC, biocompatibility, and reprocessing validation, which are standard for such hardware devices to demonstrate safety and effectiveness.

However, I can extract the information that is present and indicate where the requested information is not applicable (N/A) based on the provided document.

Device Name: FUJIFILM Ultrasonic Processor SP-900 and FUJIFILM Ultrasonic Probe PB2020-M2

Device Type: Medical Ultrasonic Processor and Probe

1. Table of Acceptance Criteria and Reported Device Performance

For this type of device (ultrasound hardware), the "acceptance criteria" are related to safety, electrical performance, biocompatibility, and reprocessing effectiveness, not diagnostic accuracy metrics typically seen with AI/ML algorithms. The document asserts that the device meets these criteria through various tests.

2. Sample size(s) used for the test set and the data provenance:
N/A - This document describes validation for hardware components (electrical safety, biocompatibility, reprocessing validation), not performance evaluation on a clinical test dataset for diagnostic accuracy. The "test sets" would refer to components/materials undergoing specific engineering and biological tests, not a dataset of patient images.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
N/A - Ground truth as typically defined for AI/ML diagnostic devices (e.g., expert radiological reads, pathology) is not relevant for the hardware validation tests performed here.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
N/A - Not applicable for hardware validation.

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 is not relevant for this hardware device. It's designed to provide general ultrasonic images, not to assist humans in interpretation in an AI-augmented manner.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
No - This is hardware, not an algorithm, so standalone performance in the sense of an AI model's accuracy is not applicable.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
N/A - "Ground truth" in the diagnostic sense is not used for hardware validation. The "ground truth" for the tests performed effectively comes from established engineering standards (e.g., electrical safety limits, biocompatibility guidelines, successful sterilization parameters).

8. The sample size for the training set:
N/A - The device is hardware; there is no "training set" in the machine learning sense.

9. How the ground truth for the training set was established:
N/A - As there is no training set, this is not applicable.

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