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The Philips IntelliSite Pathology Solution (PIPS) is an automated digital slide creation, viewing, and management system. The PIPS is intended for in vitro diagnostic use as an aid to the pathologist to review and interpret digital images of surgical pathology slides prepared from formalin-fixed paraffin embedded (FFPE) tissue. The PIPS is not intended for use with frozen section, cytology, or non-FFPE hematopathology specimens.

The PIPS comprises the Image Management System (IMS), the Ultra Fast Scanner (UFS) and display. The PIPS is for creation and viewing of digital images of scanned glass slides that would otherwise be appropriate for manual visualization by conventional light microscopy. It is the responsibility of a qualified pathologist to employ appropriate procedures and safeguards to assure the validity of the interpretation of images obtained using PIPS.

Philips IntelliSite Pathology Solution (PIPS) is an automated digital slide creation, viewing, and management system. PIPS consists of two sub-systems and a display component:

• . Image Management System (IMS)
• Ultra Fast Scanner (UFS)
• . Display

The provided document is a 510(k) Summary for a minor modification to an existing device, the Philips IntelliSite Pathology Solution (PIPS). The modification is a new display panel. Therefore, the information primarily focuses on demonstrating that this new panel does not adversely affect the device's performance compared to the predicate device.

Here's the breakdown of the requested information based on the provided text:

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

The document does not explicitly state "acceptance criteria" in the format of a table with specific numerical thresholds for performance. Instead, it refers to compliance with international and FDA-recognized consensus standards and verification tests. The "reported device performance" is framed as demonstrating similarity to the predicate device and compliance with these standards.

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

The document primarily describes non-clinical performance testing of a new display panel. It does not mention a "test set" in the context of patient data or clinical imaging for diagnostic performance evaluation. The tests performed were on the display itself.

• No information on sample size for a test set of patient data.
• No information on data provenance (country of origin, retrospective/prospective).
• The tests were performed on the hardware (display panel).

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)

This information is not applicable. The study described is not a clinical study on diagnostic accuracy or interpretation where expert ground truth would be established. It is a non-clinical study verifying the technical performance of a hardware component (display).

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

This information is not applicable for the same reason as point 3.

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 was done. The device (Philips IntelliSite Pathology Solution) is a whole slide imaging system, not an AI-assisted diagnostic tool. This submission is for a hardware change (display panel) to an existing cleared device. The document explicitly states: "The proposed device with the new display panel did not require clinical performance data since substantial equivalence to the currently marketed predicate device was demonstrated with the following attributes: - Intended Use / Indications for Use, - Technological characteristics, - Non-clinical performance testing, and - Safety and effectiveness." Therefore, no improvement with AI assistance was measured or is relevant to this specific submission.

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

This is not applicable. The device is a whole slide imaging system, not an algorithm, and this submission concerns a display hardware change.

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

This is not applicable as there was no clinical study involving patient data or diagnostic interpretation for which ground truth would be established. The "ground truth" for the non-clinical tests would be the established technical specifications and performance limits for display devices.

8. The sample size for the training set

This is not applicable. The device is a whole slide imaging system, not an AI/ML algorithm that requires a "training set."

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

This is not applicable for the same reason as point 8.

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