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The Allura Xper R9 series (within the limits of the used Operating Room table) are intended for use to perform: · Image guidance in diagnostic, interventional and minimally invasive surgery procedures for the following clinical application areas: vascular, non-vascular, cardiovascular and neuro procedures. · Cardiac imaging applications including diagnostics, interventional and minimally invasive surgery procedures. Additionally: · The Allura Xper R9 series can be used in a hybrid Operating Room. • The Allura Xper R9 series contain a number of features to support a flexible and patient centric procedural workflow.

The Allura Xper R9 is classified as an interventional fluoroscopic X-ray system. The primary performance characteristics of the Allura Xper R9 interventional fluoroscopic X-ray system include: - Real-time image visualization of patient anatomy during procedures ● - Imaging techniques and tools to assist interventional procedures - Post processing functions after interventional procedures ● - Storage of reference/control images for patient records ● - . Compatibility to images of other modalities via DICOM - Built in radiation safety controls ● This array of functions offers the physician the imaging information needed to perform minimally invasive interventional procedures. The Allura Xper R9 is available in a comparable set of configurations for monoplane models as the currently marketed and predicate devices Allura Xper R9. Configurations are composed of detector type. (monoplane) geometry, table type and available image processing. The monoplane (single C-arm) systems are categorized into X-ray systems and the configurations are differentiated by the following features: - . 12 inch Flat detector (FD12) - 15 inch Flat detector (FD15) - 20 inch Flat detector (FD20) . Additionally, identical to the predicate devices, all configurations of the Allura Xper R9 are compatible for use in a hybrid operating room when supplied with a compatible operating room table, and can be optionally equipped with the ClarityIQ image processing algorithms.

The provided document is a 510(k) premarket notification for the Philips Medical Systems Nederland B.V. Allura Xper R9, an image-intensified fluoroscopic x-ray system. It describes the device, its indications for use, and a comparison to a predicate device.

However, the document states explicitly that "The Allura Xper R9 did not require clinical study data" (Page 7). This means the submission does not contain information about a study proving the device meets specific acceptance criteria based on clinical performance.

Therefore, I cannot provide the requested information about acceptance criteria or a study proving the device meets them from this document. The submission relies on demonstrating substantial equivalence to a predicate device through non-clinical performance testing and technological similarity rather than a clinical study.

Here's a breakdown of why the requested information cannot be fully provided:

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

• Not available in the document. The document states that clinical study data was not required. It relies on non-clinical performance testing and compliance with standards. No specific acceptance criteria or reported device performance from a clinical study are presented.

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

• Not applicable. No clinical test set or data provenance is mentioned as no clinical study was performed.

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. No clinical study was performed requiring ground truth established by experts.

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

• Not applicable. No clinical study was performed requiring adjudication.

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 available. The device is an X-ray system, not an AI-assisted diagnostic tool for human readers. 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 a hardware imaging system, not an algorithm being assessed for standalone performance.

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

• Not applicable. No clinical study was performed requiring ground truth.

8. The sample size for the training set

• Not available/Applicable. The document does not describe a machine learning model or an algorithm that requires a training set in the context of clinical performance. The "2D Quantitative Analysis software" is mentioned as unchanged from a reference device and its details are not provided in terms of training.

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

• Not available/Applicable. As no training set or clinical ground truth is described, this information cannot be provided.

In summary: The provided FDA 510(k) clearance letter and summary for the Allura Xper R9 demonstrate substantial equivalence based on non-clinical performance testing, technological characteristics, and compliance with recognized standards. It explicitly states that "The Allura Xper R9 did not require clinical study data." Therefore, the detailed information requested about acceptance criteria and clinical study results is not present in this document.

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The Allura Xper R9 series (within the limits of the used Operating Room table) are intended for use to perform: · Image guidance in diagnostic, interventional and minimally invasive surgery procedures for the following clinical application areas: vascular, non-vascular, cardiovascular and neuro procedures. · Cardiac imaging applications including diagnostics, interventional and minimally invasive surgery procedures. Additionally: · The Allura Xper R9 series can be used in a hybrid Operating Room. · The Allura Xper R9 series contain a number of features to support a flexible and patient centric procedural workflow.

The Allura Xper R9 is classified as an interventional fluoroscopic X-ray system. The primary performance characteristics of the Allura Xper R9 interventional fluoroscopic X-ray system include: - Real-time image visualization of patient anatomy during procedures - Imaging techniques and tools to assist interventional procedures - Post processing functions after interventional procedures ● - Storage of reference/control images for patient records ● - Compatibility to images of other modalities via DICOM ● - . Built in radiation safety controls This array of functions offers the physician the imaging information needed to perform minimally invasive interventional procedures. The Allura Xper R9 is available in a comparable set of configurations for monoplane models as the currently marketed and predicate devices Allura Xper FD series / Allura Xper OR Table series R8.2.1. Configurations are composed of detector type, (monoplane) geometry, table type and available image processing. The monoplane (single C-arm) systems are categorized into X-ray systems and the configurations are differentiated by the following features: - . 12 inch Flat detector (FD12) - 15 inch Flat detector (FD15) ● - 20 inch Flat detector (FD20) . Additionally, identical to the predicate devices, all configurations of the Allura Xper R9 are compatible for use in a hybrid operating room when supplied with a compatible operating room table, and can be optionally equipped with the ClarityIQ image processing algorithms.

The provided document is a 510(k) summary for the Philips Medical Systems Nederland BV Allura Xper R9, an image-intensified fluoroscopic x-ray system. The document focuses on demonstrating substantial equivalence to a predicate device (Allura Xper FD series / Allura Xper OR Table series R8.2.1) rather than presenting a study to prove a device meets specific acceptance criteria based on its own reported performance.

Therefore, many of the requested elements (acceptance criteria table, sample size for test set, data provenance, number of experts, adjudication method, MRMC study, standalone performance, training set size, training set ground truth) are not detailed or applicable in the context of this 510(k) submission, which is primarily a comparative assessment.

However, I can extract the relevant information that is present:

Acceptance Criteria and Reported Device Performance

The core "acceptance criteria" in this context is substantial equivalence to the predicate device, specifically in terms of:

1. Indications for Use: The modified device (Allura Xper R9) must have the same indications for use as the predicate.
2. Technological Characteristics: Despite modifications, the fundamental scientific technology must be the same, and changes must not raise new questions of safety or effectiveness.
3. Safety and Effectiveness: Performance testing (non-clinical) must demonstrate that the device is as safe and effective as the predicate device.

The "reported device performance" is a demonstration of this substantial equivalence.

Other requested information:

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

   • Not specified for non-clinical performance tests. The document refers to "software verification testing," "non-clinical validation testing," and "imaging performance metrics" but does not detail sample sizes, data provenance (e.g., country), or whether it was retrospective/prospective outside of referring to "sample clinical images" which were not required for substantial equivalence.

2. 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 specified for the non-clinical performance tests that established substantial equivalence. The document mentions "Signed statements from a board certified radiologist demonstrate that sample clinical images are of adequate quality for use in diagnostic and interventional procedures." This was additional evidence, not the primary means of establishing substantial equivalence for the device's technical aspects.

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

   • Not specified. The non-clinical tests relate to engineering and technical performance (software verification, compliance with standards, imaging performance metrics). Expert adjudication in the traditional sense for diagnostic accuracy is not mentioned as a primary method for demonstrating substantial equivalence.

4. 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 study was done or reported. This device is an X-ray imaging system, not an AI-powered diagnostic tool. The submission is a 510(k) for an updated fluoroscopic X-ray system, demonstrating equivalence to an existing one.

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

   • Not applicable in the context of a general fluoroscopic X-ray system. The "standalone" performance here refers to the system's ability to capture and process images according to its specifications and regulatory standards. The non-clinical performance testing (software verification, imaging performance) served this purpose.

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

   • For the non-clinical performance tests, "ground truth" was established by compliance with recognized international standards (IEC, ISO), FDA guidance documents, and engineering specifications. For example, "Results demonstrated that all executed tests were passed" for software verification. "Equivalent imaging performance" was measured against the predicate device based on metrics outlined in specific FDA guidance.

7. The sample size for the training set

   • Not applicable. This submission is for an imaging device, not an AI/machine learning algorithm requiring a "training set."

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

   • Not applicable, as there is no training set for this type of device.

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