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The Access CT scanner system can be used as a Whole Body (except cardiac) Computed Tomography X-ray System featuring a continuously rotating X-ray tube and detector array with multislice capability up to 6/16 slices simultaneously. The acquired X-ray transmission data is reconstructed by computer into cross-sectional images of the same axial plane taken at different angles. The system is suitable for all patients.

The proposed Access CT is currently available in two system configurations, 6 slices and 16 slices.

The Access CT system is used clinically as a diagnostic patient imaging device that produces images that correspond to tissue density. The quality of the images depends on the level and amount of X-ray energy delivered to the tissue. CT imaging displays both high-density tissue, such as bone, and soft tissue. When interpreted by a trained physician, CT images yield useful diagnostic information. The system is intended for use in the head and whole body.

The main components (detection system, the reconstruction algorithm, and the x-ray system) that are used in the Access CT have the same fundamental design characteristics and are based on comparable technologies as the predicate.

The main system modules and functionalities are:

1. Gantry. The Gantry consists of 4 main internal units:
   a. Stator – a fixed mechanical frame that carries HW and SW.
   b. Rotor – A rotating circular stiff frame that is mounted in and supported by the stator.
   c. X-Ray Tube (XRT) and Generator – fixed to the Rotor frame.
   d. Data Measurement System (DMS) – a detectors array, fixed to the Rotor frame.
2. Patient Support (Couch) – carries the patient in and out through the Gantry bore synchronized with the scan.
3. Console - Containing a Host computer and display that is the primary user interface.

In addition to the above components and the software operating them, each system includes hardware and software for data acquisition, display, manipulation, storage and filming as well as post-processing into views other than the original axial images. Patient supports (positioning aids) are used to position the patient.

Here's an analysis of the provided text regarding the acceptance criteria and study proving the device meets those criteria:

This document is a 510(k) Premarket Notification for the Philips Access CT system. It does not present a clinical study for proving the device meets specific acceptance criteria in the context of diagnostic accuracy or AI performance. Instead, it focuses on demonstrating substantial equivalence to predicate devices based on technical specifications, performance standards, and non-clinical testing.

The "acceptance criteria" here relate to engineering and performance specifications for a CT scanner, rather than diagnostic performance of an AI algorithm. The "study" described is primarily non-clinical verification and validation testing, ensuring the device meets its design requirements and complies with relevant safety and performance standards.

Therefore, many of the requested points regarding AI performance, human-in-the-loop studies, ground truth establishment for AI, and expert adjudication are not applicable to this document as it describes a non-AI medical device (a CT scanner).

Acceptance Criteria and Device Performance (as presented in the document)

The document outlines acceptance criteria as technical specifications that the device must meet to be considered substantially equivalent to predicate devices. The "reported device performance" are the actual specifications of the Access CT that are compared against these criteria and the predicate device's specifications.

1. Table of Acceptance Criteria and Reported Device Performance

The closest representation of "acceptance criteria" and "reported device performance" in this document is found in the "Table 5-1 Design/fundamental scientific technologies Comparison" on page 8. The "Acceptance Criteria" are implicitly the values or characteristics of the "Predicate Device Philips MX 16-slice (K091195)", and the "Reported Device Performance" are the values for the "Proposed Access CT".

The document also compares against two other reference devices (Philips Ingenuity CT and Philips Incisive CT) for specific "clinical features" (Iterative recon, CTC, LNA, iPlanning, Batch image processing (iBatch)), concluding they are "Identical".

Study Details (as presented in the document, primarily non-clinical)

2. Sample Size Used for the Test Set and the Data Provenance

• Test Set Description: The document refers to "Design Verification planning and testing" and "Design validation of user needs and intended use" with "simulated use testing with production equivalent Access CT Systems."
• Sample Size: The document does not specify a sample size in terms of patient data or scanned images for non-clinical verification. It focuses on testing the system's compliance with engineering requirements and standards.
• Data Provenance: The testing was conducted internally by Philips Healthcare (Suzhou) Co., Ltd. in China ("Philips Healthcare (Suzhou) Co., Ltd., No. 258, Zhongyuan Road, Suzhou Industrial Park, Suzhou Jiangsu, CHINA, 215024"). The data stems from design verification and validation activities rather than a clinical study. The type of data is technical performance measurements, rather than patient scans with clinical findings. The document states: "The proposed Access CT System did not require any external clinical site testing."
• Retrospective or Prospective: Not applicable in the context of clinical data. The verification and validation testing would have been "prospective" in the sense that it was planned and executed for the purpose of demonstrating compliance.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

• Not Applicable: This is a submission for a CT scanner itself, not an AI algorithm that requires expert ground truth for diagnostic accuracy. The "ground truth" for the device's performance is adherence to technical specifications and safety standards, as measured by engineering tests.

4. Adjudication Method for the Test Set

• Not Applicable: There is no clinical test set requiring adjudication in this document. Adjudication methods are relevant for clinical studies where multiple human readers interpret medical images or data.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

• No: The document explicitly states: "The proposed Access CT System did not require any external clinical site testing. Clinical evaluation of workflow was conducted via simulated use testing and is accounted for in the Summary of Non-Clinical Testing section of the summary."
• This also means there is no effect size given for human readers improving with AI vs. without AI assistance, as AI assistance is not the subject of this 510(k).

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

• Not Applicable: This device is a CT scanner, not a standalone algorithm.

7. The Type of Ground Truth Used

• For the technical and safety performance of the CT scanner, the "ground truth" is established by international and FDA-recognized consensus standards (listed in the "Summary of Non-Clinical Performance Data" section on pages 4-5) and system design requirements. The device's performance is measured against these established standards and requirements. Examples of standards cited include AAMI / ANSI ES60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-2-44, IEC 62304, IEC 62366-1, ISO14971, NEMA XR 25-2011, NEMA XR 28-2013, and NEMA XR 29-2013.

8. The Sample Size for the Training Set

• Not Applicable: This is not an AI/machine learning device submission. There is no "training set" in the context of model development.

9. How the Ground Truth for the Training Set was Established

• Not Applicable: As there is no training set for an AI model, this question is not relevant to the content of the document.

In summary, the provided document details the 510(k) submission for a CT scanner, demonstrating its substantial equivalence to previously cleared predicate devices through comparisons of technical specifications and compliance with established safety and performance standards via non-clinical verification and validation. It is not an application for an AI-powered diagnostic device, and thus, many of the questions related to AI study design, clinical efficacy, and human reader performance are not addressed.

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