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Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows:

For ASU-1003: Fetal, Transvaginal. Mixed mode operation includes B/M-Mode.

For UST-9121: Abdominal. Mixed mode operation includes B/M.

For UST-9124: Fetal, Transvaginal. Mixed mode operation includes B/M.

The transducers are to be used for diagnostic ultrasound imaging in Urological, Abdominal, Intraoperative, Surgical and Endoscopic applications.

Diagnostic Ultrasound Transducers

This document describes a 510(k) premarket notification for diagnostic ultrasound transducers (ASU-1003, UST-9121, UST-9124) manufactured by Aloka Co., Ltd. The submission aims to demonstrate substantial equivalence to previously cleared predicate devices.

The information provided does not contain details about a study conducted to prove the device meets specific acceptance criteria in the way a clinical trial or performance evaluation of an AI/software device would. Instead, this is a regulatory submission for ultrasound transducers, which are hardware components. The "acceptance criteria" here refer to regulatory compliance and demonstrating substantial equivalence to predicate devices, primarily through technical specifications and intended use.

Therefore, many of the requested points regarding acceptance criteria, study design, expert ground truth, and AI performance are not applicable to this document. The document focuses on regulatory classification and comparison to existing products.

Here's an attempt to answer the questions based on the provided text, acknowledging the limitations for an ultrasound transducer submission:

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

For ultrasound transducers, the "acceptance criteria" and "performance" are typically related to their technical specifications (e.g., frequency range, imaging modes, acoustic output) and their equivalence to predicate devices. The document states that the devices are substantially equivalent to their predicates.

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

This document does not describe a clinical study with a test set of patient data. The "test set" in this context would likely refer to engineering tests of the transducers themselves to confirm design specifications and safety, rather than a dataset for evaluating an algorithm's performance on patient data. No sample size, data provenance, or retrospective/prospective nature regarding clinical data are mentioned.

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. The ground truth for this type of device (ultrasound transducer) would be established through engineering specifications, safety standards, and performance evaluation against those standards, not through expert review of clinical images.

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

Not applicable, as this document does not describe a study involving expert adjudication of clinical data.

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 for an ultrasound transducer, not an AI or software device. No MRMC study is mentioned.

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

Not applicable. This is an ultrasound transducer, not an algorithm, so performance is inherently "human-in-the-loop" as it requires a sonographer/clinician.

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

The "ground truth" for this regulatory submission is based on technical specifications, safety standards, and substantial equivalence to legally marketed predicate devices. This includes meeting performance characteristics of the predicates and complying with FDA regulations for diagnostic ultrasound transducers. The FDA's request for a postclearance special report on acoustic output, for instance, implies objective, measurable standards for acoustic power.

8. The sample size for the training set

Not applicable. This is not an AI/ML device requiring a training set.

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

Not applicable. This is not an AI/ML device requiring a training set or ground truth for training.

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The SSD-1000 Diagnostic Ultrasound System and Transducers be used for diagnostic ultrasound imaging in Cardiac, Gynecological, Neurological, Obstetrical, Neonatal, Pediatric, Perinatal, Radiological, Vascular, Urological, Abdominal, Gastrointestinal, Trauma, Surgical and Endoscopic applications. The Aloka SSD-1400 is not indicated for ophthalmic applications.

Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows: (followed by tables listing specific clinical applications and modes of operation for the system and various transducers).

The SSD-1000 makes no changes to the indications for use, the ultrasound generator, transducer(s), controls, and signal processing technologies. There are no new system functions added, significant new clinical information provided or significant claims of added effectiveness. In addition, clinical applications/modes of operation provide no new significant interpretation of predicate device; the SSD-1400.

The Aloka SSD-1000 Diagnostic Ultrasound System provides diagnostic ultrasound imaging and fluid flow analysis for various clinical applications. The study provided does not detail specific quantitative acceptance criteria or a study designed to prove these criteria were met. Instead, the document establishes substantial equivalence to a predicate device (SSD-1400, K972465) by demonstrating that the SSD-1000 makes no changes to the indications for use, ultrasound generator, transducers, controls, and signal processing technologies. No new system functions, significant new clinical information, or claims of added effectiveness are noted.

The acceptance criteria are implicitly based on the substantial equivalence of the new device's capabilities to the cleared predicate device. The performance of the device is reported through a list of clinical applications and modes of operation for which the device and its various transducers are intended.

1. Table of Acceptance Criteria and Reported Device Performance:

Since no specific quantitative acceptance criteria were defined in the provided text, the criteria are implicitly that the device performs equivalently to the predicate device for the listed clinical applications and modes. The reported device performance is the scope of its intended uses.

SSD-1000 Diagnostic Ultrasound System:

Note: 'E' indicates the application/mode was added under Appendix E, signifying it's an intended use derived from equivalence to the predicate device.

Selected Transducers and their Clinical Applications/Modes:
(Example for a few transducers, as the full list is extensive in the original document)

• ASU-35-5 (K983879):

  • Small Organ: P, P
  • Cardiac: P, P

• ASU-35B-5 (Appendix E):

  • Small Organ: E, E
  • Cardiac: E, E

• ASU-1000C-3.5 (Appendix E):

  • Fetal: E, E
  • Abdominal: E, E
  • Transvaginal: E, E

• UST-978-3.5 (Appendix E):

  • Abdominal: E, E
  • Pediatric: E, E

• UST-984P-5 (K983879):

  • Fetal: E, E
  • Transvaginal: E, E

• UST-990-5 (K009793):

  • Fetal: P, P
  • Abdominal: P, P
  • Transvaginal: P, P

• UST-5524-5 (K985879):

  • Small Organ: P, P
  • Peripheral Vascular: P, P

• UST-5534T-7.5 (K003739):

  • Intraoperative: P, P
  • Small Organ: P, P
  • Peripheral Vascular: P, P

• UST-5710-7.5 (K00379):

  • Small Organ: P, P

• UST-5818-5 (Appendix E):

  • Intraoperative: E, E
  • Small Organ: E, E
  • Peripheral Vascular: E, E

• UST-5819T-5 (Appendix E):

  • Abdominal: E, E
  • Intraoperative: E, E
  • Small Organ: E, E

• UST-9101-7.5 (K003739):

  • Abdominal: P, P, P
  • Pediatric: P, P

• UST-9102-3.5 (Appendix E):

  • Abdominal: E, E

• UST-9103-5 (Appendix E):

  • Fetal: E, E
  • Abdominal: E, E
  • Transvaginal: E, E

• UST-9104-5 (Appendix E):

  • Intraoperative: E, E
  • Neonatal Cephalic: E, E, E

• UST-9112-5 (Appendix E):

  • Fetal: E, E
  • Transvaginal: E, E

• UST-9116P-5 (Appendix E):

  • Intraoperative: E, E, E
  • Intraoperative Neurological: E, E, E

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

The provided 510(k) summary does not mention a specific test set or data provenance from a prospective or retrospective study for verifying performance against acceptance criteria. The approval is based on substantial equivalence to a predicate device. A post-market surveillance requirement is mentioned in page 3 of the document, requesting "acoustic output measurements based on production line devices" prior to shipping the first device, but this is related to safety and manufacturing compliance rather than clinical performance evaluation.

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

This information is not provided in the document. The approval is based on substantial equivalence, not on a new clinical study requiring ground truth establishment by experts.

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

No adjudication method is mentioned, as there is no specific test set described in the context of clinical performance evaluation.

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 MRMC comparative effectiveness study is mentioned. This device is a diagnostic ultrasound system, not an AI-powered device, so human reader improvement with AI assistance is not applicable in this context.

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

Not applicable, as this is a medical device for imaging, not an algorithm, and it requires a human operator for its intended use.

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

Not applicable. The filing is based on substantial equivalence to a predicate device, meaning its performance characteristics are deemed equivalent to a device already on the market, rather than requiring new ground truth data for novel claims.

8. The sample size for the training set:

Not applicable, as this is a medical device, not a machine learning algorithm that requires a training set.

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

Not applicable, for the same reason as above.

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