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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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The Philips CT Big Bore is a Computed Tomography X-Ray System intended to produce images of the head and body by computer reconstruction of x-ray transmission data taken at different angles and planes. These devices may include signal analysis and display equipment, patient and equipments and accessories. These systems are indicated for head and whole body X-ray Computed Tomography applications in oncology, vascular and cardiology, for patients of all ages.

These scanners are intended to be used for diagnostic imaging and for low dose CT lung cancer screening for the early detection of lung nodules that may represent cancer*. The screening must be performed within the established inclusion criteria of programs / protocols that have been approved and published by either a governmental body or professional medical society.

• Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

The Philips CT Big Bore is currently available in two system configurations, the Oncology configuration and the Radiology (Base) configuration.

The main components (detection system, the reconstruction algorithm, and the x-ray system) that are used in the Philips CT Big Bore 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 detector 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 A two part subsystem containing a Host computer and display that is the primary user interface and the Common Image Reconstruction System (CIRS) - a dedicated, powerful image reconstruction computer

In addition to the above components and the software operating them, each system includes workstation 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.

This document describes the Philips CT Big Bore, a Computed Tomography X-Ray System. The submission focuses on demonstrating substantial equivalence to a predicate device rather than a standalone clinical efficacy study with acceptance criteria in the typical sense of a diagnostic AI product. Therefore, much of the requested information regarding clinical studies and expert review for ground truth is not directly applicable in the same way.

However, based on the provided text, we can infer and extract the following:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are framed in terms of achieving similar or improved performance compared to the predicate device and meeting established industry standards for CT systems. The reported device performance is primarily a comparison to the predicate device's specifications and measurements on phantoms.

2. Sample Size for Test Set and Data Provenance

The document does not explicitly state a "test set" in the context of an AI/algorithm-driven diagnostic study. Instead, it refers to "bench testing included basic CT performance tests on phantoms" and "Sample clinical images were provided with this submission, which were reviewed and evaluated by radiologists."

• Sample Size for Test Set: Not specified for clinical images. For bench testing, it refers to "phantoms."
• Data Provenance: Not specified for the "sample clinical images." Given the context of a 510(k) for a hardware device, it's highly likely these were internal and possibly from a variety of sources. It's not stated whether they were retrospective or prospective.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: "radiologists" (plural, but exact number not specified).
• Qualifications of Experts: Only "radiologists" are mentioned. No details on years of experience or subspecialty.

4. Adjudication Method for Test Set

• Adjudication Method: Not specified. The document states, "All images were evaluated to have good image quality," suggesting a qualitative assessment rather than a structured adjudication process for a specific diagnostic task.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• MRMC Study: No, a typical MRMC comparative effectiveness study was not performed as described. This submission is for a CT scanner itself, not an AI-assisted interpretation tool where human readers' performance with and without AI would be compared.
• Effect Size of Human Readers with AI vs. without AI: Not applicable, as this was not an AI-assistance study.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: No, this was not a standalone algorithm performance study. The submission is for a complete CT imaging system. The performance metrics reported are for the overall system, not an isolated algorithm. The document mentions "optional software algorithm called WARP or DAS" for increasing slice count, and features like "iDose4" (an extension of DoseRight) and "FDOM, 3D-DOM" for dose modulation, but their standalone performance is not detailed in terms of a clinical study.

7. Type of Ground Truth Used

• Type of Ground Truth: For the "sample clinical images," the ground truth seems to be expert opinion / qualitative assessment by radiologists that the image quality was "good." For the technical performance parameters (MTF, CTDIvol, CT number accuracy, Noise, Slice Thickness), the ground truth was derived from physical phantom measurements against established technical specifications.

8. Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This document describes a CT scanner (hardware and embedded software), not a machine learning model that would have a separate "training set" in the conventional sense. The "training" for the system's development would be through engineering design, iterative testing, and adherence to established physical and software engineering principles.

9. How Ground Truth for the Training Set Was Established

• How Ground Truth for Training Set Was Established: Not applicable. (See point 8). The development of the CT system likely involved extensive engineering design, simulations, and validation against known physical principles and performance targets, which are fundamentally different from establishing ground truth for a machine learning training set.

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