Search Results

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.

Ask a specific question about this device

This device is a diagnostic imaging system for that combines Positron Emission Tomography (PET) and X-ray Computed Tomography (CT) systems. The CT subsystem produces cross-sectional images of the body by computer reconstruction of x-ray transmission data. The PET subsystem produces images of the distribution of PET radiopharmaceuticals in the patient body (specific radiopharmaceuticals are used for whole body, brain, heart and other organ imaging). CT data is applied to the PET data for attenuation correction. The PET subsystem also provides for list mode, dynamic, and gated acquisitions. This system is intended for patients of all ages.

Image processing and display workstations provide software applications to process, analyze, display, quantify and interpret medical images/data.

The PET and CT images may be registered and displayed in a "fused" (overlaid in the same spatial orientation) format to provide combined metabolic and anatomical data at different angles. Trained professionals use the images in:
· The evaluation, detection and diagnosis of lesions, disease and organ function such as but not limited to cancer, cardiovascular disease, and neurological disorders.
· The detection, localization, and staging of tumors and diagnosing cancer patients.
· Radiation therapy treatment planning and interventional radiology procedures.

The system includes software that provides a quantified analysis of regional cerebral activity from PET images.

Cardiac imaging software provides functionality for the quantification of cardiology images and data sets including but not limited to myocardial perfusion for the display of wall motion and quantification of left-ventricular function parameters from gated myocardial perfusion studies and for the 3D alignment of coronary artery images from CT coronary angiography onto the myocardium.

Both subsystems (PET and CT) can also be operated independently as fully functional, diagnostic imaging systems including application of the CT scanner as a radiation therapy simulation scanner.

This scanner is also 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 proposed Ingenuity TF is an integrated diagnostic imaging system that combines Positron Emission Tomography (PET) and X-ray Computed Tomography (CT). PET uses radiopharmaceuticals to obtain images by measuring the internal distribution of radioactivity within head, body and total body. PET technology enables the practitioner to reconstruct high-resolution, three-dimensional images of biochemical and metabolic processes of organs within the body. The Ingenuity TF utilized Time-of-Flight (ToF) technology for the PET reconstruction. CT is a medical imaging technique that uses Xrays to obtain cross-sectional images of the head or body. The system utilizes the CT technology to obtain anatomic images of the human body and PET technology to obtain functional images of the human body. The CT component can be utilized by clinicians for lung cancer screening. As such, lung cancer screening has been added to the Ingenuity TF intended use. The integration of the anatomical data from CT with the metabolic data from PET gives clinicians the visual information necessary to define the severity, as well as the extent, of the disease. The major subsystems of the PET/CT include the PET image reconstruction subsystem, the PET Data Acquisition subsystem, the CT Image reconstruction subsystem, the CT acquisition subsystem, the PET Gantry, the CT Gantry and the patient table. The system is suitable for all patients, infant through adult.

Here's a summary of the acceptance criteria and study information for the Ingenuity TF device based on the provided text, focusing on what is and isn't available for each point:

1. Table of Acceptance Criteria and Reported Device Performance

The provided FDA 510(k) summary does not include a direct table of specific acceptance criteria (performance metrics with pass/fail thresholds) and corresponding reported performance for the Ingenuity TF. Instead, it states that:

• Acceptance Criteria (Implicit): The device was designed to meet "established design input requirements," "user needs and intended use," and comply with "FDA recognized consensus standards."
• Reported Performance (General): Design Verification activities "demonstrate the Ingenuity TF meets the established design input requirements." "Design Validation of user needs and intended use was conducted via simulated use testing." "Traceability from requirements to test plans to test results confirmed... that design requirements were met."

The document focuses on demonstrating substantial equivalence to a predicate device rather than providing quantitative performance against specific acceptance criteria for standalone performance.

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

This information is not provided in the document. The text mentions "simulated use testing" and "clinical workflow validation," but does not specify the sample size of cases or the provenance (country, retrospective/prospective) of any test data.

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

This information is not provided. If an expert panel was used for simulated use testing or clinical workflow validation, their number and qualifications are not detailed.

4. Adjudication Method for the Test Set

This information is not provided.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not conducted for the Ingenuity TF. The document explicitly states: "The Ingenuity TF did not require clinical study since substantial equivalence to the primary currently marketed and predicate device was demonstrated with the following attributes: Intended Use; Technological characteristics; Non-clinical performance testing; and Safety and effectiveness." Therefore, an effect size of human readers' improvement with AI vs. without AI assistance is not reported.

6. Standalone Performance Study

A standalone performance study (i.e., algorithm only without human-in-the-loop performance) was not explicitly detailed as a separate clinical study. The device itself is a diagnostic imaging system (a PET/CT scanner), not an AI algorithm intended for standalone interpretation. Performance was assessed through non-clinical testing and comparison to a predicate device. The "Image Quality verification" mentioned under non-clinical testing would involve evaluating the image output itself, which is a form of standalone evaluation of the device's output quality.

7. Type of Ground Truth Used

For the non-clinical and simulated use testing mentioned, the type of "ground truth" would likely involve:

• Established Design Input Requirements: Compliance with specified technical and functional requirements.
• User Needs and Intended Use: Verified through simulated use.
• Consensus Standards: Compliance with international safety and performance standards (e.g., NEMA NU 2:2012 for PET performance, IEC 60601 series).

For any "Image Quality verification," ground truth might be derived from phantom studies with known properties or comparison against highly detailed reference images, but this is not explicitly stated. The document doesn't mention pathology, expert consensus on clinical cases, or outcomes data as direct ground truth for device acceptance.

8. Sample Size for the Training Set

The document does not mention a training set sample size. This device is a PET/CT scanner, not an AI model that undergoes a typical training phase with a dedicated dataset. While it incorporates "software that provides a quantified analysis," the development of this software (its training, if any, for specific analytical tasks) is not detailed.

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

Since there is no mention of a training set for the device itself (as it's a hardware imaging system with integrated software), the method for establishing ground truth for a training set is not applicable/not provided.

Ask a specific question about this device