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The iLab™ Ultrasound Imaging System is intended for ultrasound examinations of intravascular pathology. Intravascular ultrasound is indicated in patients who are candidates for transluminal interventional procedures such as angioplasty and atherectomy.

The iLab™ Ultrasound Imaging System is designed for real-time viewing of intravascular anatomies and is intended to be a basic diagnostic tool for imaging and evaluation of patients who are candidates for transluminal procedures. The iLab™ System consists of two compact PC units (one for Image Processing and one for Data Acquisition), up to two displays (one primary and an optional secondary). The iLab System imaging and processing PC are used during an intravascular procedure, at the end of the IVUS procedure, the processing PC supports the archiving of the images obtained during the procedure. The iLab System processing PC converts the native iLab images into DICOM format images prior to archiving to removal media such as a CD, DVD or removable hard disk cartridge. Images can also be archived to a DICOM network server. The iLab™ System is available in two configurations: a Cart-based Configuration and an Installed Configuration.

The document provided is a 510(k) Summary for the Boston Scientific iLab™ Ultrasound Imaging System. It describes the device, its intended use, and comparison to a predicate device. The document details various non-clinical testing performed, including software and hardware verification and validation efforts. However, it does not contain any information about clinical studies with human participants, expert review of data, or establishment of ground truth in the way typically expected for AI/ML device evaluations.

The testing described is primarily focused on engineering verification and validation of the system's components and software against predefined requirements, rather than a performance study involving a test set with established ground truth.

Therefore, many of the requested elements for acceptance criteria and study details cannot be extracted from this document, as they are not relevant to the type of submission provided.

Here's a breakdown of what can be inferred or explicitly stated based on the provided text, and what cannot:

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

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

• Sample Size for Test Set: Not applicable. The document describes software verification and validation, and hardware testing, not a clinical performance study with a "test set" in the context of patient data.
• Data Provenance: Not applicable for a clinical test set. The verification and validation involved "multiple configurations of PC systems" and "production equivalent" systems. On-site validation was planned for "3 or more customer sites."

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)

• Number of Experts: Not applicable. No clinical expert review process is described for establishing ground truth for a test set.
• Qualifications of Experts: Not applicable. The "software validation effort will be performed by testers with iLab clinical experience," but these are testers for engineering validation, not clinical experts establishing ground truth for a performance study.

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

• Adjudication Method: Not applicable. No clinical test set or adjudication process 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

• MRMC Study: No. This document describes a traditional 510(k) for an ultrasound imaging system update, not an AI/ML device requiring an MRMC study.

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

• Standalone Performance: Not applicable. This is an ultrasound imaging system, not an algorithm-only device. The testing focuses on the system's functional integrity.

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

• Type of Ground Truth: Not applicable. The "ground truth" in this context refers to the system meeting its engineering specifications and requirements, as outlined in "Software Requirements Specifications" and "Product and Marketing requirements." No clinical "ground truth" (e.g., pathology, outcomes) for diagnostic accuracy is mentioned.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. This is not an AI/ML device that requires a training set in that context.

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

• Training Set Ground Truth: Not applicable.

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