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The system is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes, including Axial, Cine, Helical (Volumetric), Cardiac, and Gated acquisitions. These images may be obtained either with or without contrast. This device may include signal analysis and display equipment, patient and equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes. Further the images can be post processed to produce additional imaging planes or analysis results.

The system is indicated for head, whole body, cardiac X-ray Computed Tomography applications in patients of all ages.

The device output is a valuable medical tool for the diagnosis of disease, trauma, or abnormality and for planning, guiding, and monitoring therapy.

The Revolution Ascend CT system is head and whole body CT system incorporating the same basic fundamental operating principles as the predicate device. It is composed of a gantry, patient table, operator console, host computer, and power distribution unit (PDU), and interconnecting cables. The system also includes image acquisition and reconstruction hardware/software, general system software, accompanying documents, and associated accessories, interconnections. Its materials and construction are identical to our existing marketed products.

Identical to the predicate, Revolution Ascend generates cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes, including Axial, Cine, Helical (Volumetric), Cardiac, and Gated acquisitions modes. Revolution Ascend's Intended Use and Indications for Use remain identical to those of the predicate device.

Revolution Ascend includes virtually all the available features of the predicate device Revolution Maxima. Compared to the predicate, the changes incorporated into Revolution Ascend are primarily to introduce a widended bore gantry for easy handling of large patient, trauma examinations, interventional procedures and radiotherapy planning, and addition of other existing features already available from GE's other CT systems. These ported features include Auto Pilot workflow enabled by Deep learning based patient Auto Positioning, Intelligent Protocoling enabled by Machine Learning, Smart Plan and Auto Prescription all integrated into the modern software platform and GUI adopted from Revolution CT, and cardiac feature Auto Gating and as well as Interventional feature 3D Guidance.

The provided text describes a 510(k) premarket notification for a Computed Tomography (CT) system, Revolution Ascend, seeking substantial equivalence to a predicate device, Revolution Maxima. This document primarily focuses on demonstrating the new device's equivalence to an already cleared device rather than proving its performance against a new set of clinical acceptance criteria through a standalone study with human readers or specific AI performance metrics.

Therefore, the information required for a comprehensive answer regarding acceptance criteria and a study proving a device meets these criteria (especially for a medical AI/CADe device) is largely not present in this document. The submission is for a new iteration of a CT scanner, not a novel AI-powered diagnostic tool requiring specific clinical performance validation for its AI components against a defined ground truth.

However, I can extract the information that is implicitly or explicitly stated, and highlight where the requested information is absent or not applicable to this type of submission.

Acceptance Criteria and Device Performance (Implicit):

Since this is a 510(k) for substantial equivalence to a predicate CT system, the "acceptance criteria" are primarily that the new device, Revolution Ascend, performs as safely and effectively as the predicate device, Revolution Maxima, and other previously cleared GE CT systems for specific features. The performance is assessed through non-clinical bench testing, image quality (IQ) and dose evaluation using phantoms, and verification/validation testing.

Regarding the Study Proving the Device Meets Acceptance Criteria:

The document describes non-clinical testing for substantial equivalence, not a clinical study designed to prove new performance claims or the efficacy of novel AI features in a clinical setting with human readers.

1. Sample size used for the test set and the data provenance:

   • Test Set Sample Size: No specific number of "cases" or "patients" for a clinical test set is mentioned. The testing involves "standard IQ, QA and ACR phantoms for standard conditions as well as challenging conditions such as with phantoms simulating large patients" and "3D guidance test with phantoms simulating interventional conditions." This indicates laboratory/bench testing using physical phantoms, not a dataset of patient images.
   • Data Provenance: Not applicable as clinical data are not the primary basis for performance evaluation in this submission. The tests are "non-clinical bench test results."

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not applicable. The "ground truth" for non-clinical phantom testing involves established physical properties, measurements, and engineering specifications, not expert clinical interpretation.

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

   • Not applicable as no human interpretation or adjudication of a test set is described.

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, nor is it described. This submission is for a CT system, not an AI/CADe device requiring direct clinical performance evaluation in synergy with human readers. While the device includes "Intelligent Protocoling enabled by Machine Learning" and "Auto Positioning by Deep Learning," these appear to be workflow/control features, not diagnostic AI features needing MRMC studies for reader performance improvement for a 510(k) submission.

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

   • No standalone performance study of a diagnostic algorithm is detailed. The performance assessment is focused on the CT system's image quality and dose output, verified through phantom studies and engineering testing, ensuring it's equivalent to the predicate.

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

   • For the non-clinical testing, the "ground truth" is based on the known physical properties of the phantoms, established metrics for image quality and dose (e.g., in accordance with IEC 61223-3-5), and design specifications. There's no clinical ground truth (e.g., pathology, expert consensus) involved.

7. The sample size for the training set:

   • The document mentions "Intelligent Protocoling enabled by Machine Learning" and "Auto Positioning by Deep Learning." However, it does not provide any details about the training data size, composition, or provenance for these AI features. As these are described as "workflow features" and integral to the CT system's operation (rather than standalone diagnostic AI tools with independent performance claims), such detail is typically not required for a 510(k) of a CT scanner. They are presented as existing, ported features or minor enhancements that don't alter the fundamental operating principles or intended use.

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

   • Not described/provided in the document. (See point 7).

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The GE NM/CT 850 system is a medical tool intended for use by appropriately trained healthcare professionals to aid in detecting, localizing, diagnosing of diseases and in the assessment of organ function of diseases, trauma, abnormalities, and disorders such as, but not limited to, cardiovascular disease, neurological disorders and cancer. The system output can also be used by the physician for staging of tumors; and planning, guiding, and monitoring therapy.

NM System: General Nuclear Medicine imaging procedures for detection of radioisotope tracer uptake in the patient body, using a variety of scanning modes supported by various acquisition types and imaging features designed to enhance image quality. The scanning mode (Static, Multi-gated, Dynamic and Whole body) and tomographic mode (SPECT, Gated SPECT, Whole body SPECT). Imaging modes include single photon, multi peak frame, with data stored frame/list mode. The imaging-enhancement features include assortment of collimators, gating by physiological signals, and real-time automatic body contouring.

CT System: Intended specifically for attenuation correction and anatomical localization.

NM + CT System: Combined, hybrid SPECT and CT protocols, for CT-based SPECT attenuation corrected imaging as well as functional and anatomical mapping imaging (localization, registration, and fusion).

The GE NM/CT 850 system may include signal analysis and display equipment, patient and equipment supports, components and accessories. The system may include digital processing of data and images, including display, quality check, transfer, and processing, to produce images in a variety of trans-axial and reformatted planes. The images can also be post processed to obtain additional images, imaging planes, and uptake quantitation. The system may be used for patients of all ages.

NM/CT 850 does not support standalone CT operation.

The GE NM/CT 860 system is a medical tool intended for use by appropriately trained healthcare professionals to aid in detecting, localizing, diagnosing of diseases and in the assessment of organ function for the evaluation of diseases, trauma, abnormalities, and disorders such as, but not limited to, cardiovascular disease, neurological disorders and cancer. The system output can also be used by the physician for staging of tumors; and planning, guiding, and monitoring therapy.

NM System: General Nuclear Medicine imaging procedures for detection of radioisotope tracer uptake in the patient body, using a variety of scanning modes supported by various acquisition types and imaging features designed to enhance image quality. The scanning mode (Static, Multi-gated, Dynamic and Whole body) and tomographic mode (SPECT, Gated SPECT, Whole body SPECT), Imaging modes include single photon, multi-isotope, and multipeak, with data stored in frame/list mode. The imaging-enhancement features include assortment of collimators, gating by physiological signals, and real-time automatic body contouring.

CT System: produces Cross sectional images of the body by computer reconstruction of X-Ray transmission data taken at different and planes, including Axial. Cine and Helical acquisitions. These images may be obtained with or without contrast. The CT system is indicated for head, whole body and vascular X-Ray Computed Tomography applications

NM + CT System: Combined, hybrid SPECT and CT protocols, for CT-based SPECT attenuation corrected imaging as well as functional and anatomical mapping imaging (localization, registration, and fusion).

The GE NM/CT 860 system may include signal analysis and display equipment, patient and equipment supports, components and accessories. The system may include digital processing of data and images, including display, quality check, transfer, and processing, to produce images in a variety of trans-axial and reformatted planes., The images can also be post processed to obtain additional images, imaging planes, analysis results and uptake quantitation. The system may be used for patients of all ages.

NM/CT 850 and NM/CT 860 consist of 2 back-to-back gantries (i.e. NM gantry carrying 2 nuclear detectors and a CT gantry), patient table, power distribution unit (PDU), operator console with two acquisition systems (i.e. NM and CT) and a digital processing system, interconnecting cables and associated accessories.
NM/CT 850 and NM/CT 860 generate NM images and CT-based attenuation correction and anatomical localization data for SPECT imaging. NM/CT 860 also generates diagnostic CT images. The NM images are generated through computer reconstruction of data acquired by a Nal-based dual detector NM system that uses a variety of planar and tomographic acquisition types. The CT images are generated by computer reconstruction of data acquired using the Revolution ACTs CT system.

The provided document is a 510(k) Pre-market Notification for the GE Healthcare NM/CT 850 and NM/CT 860 devices, which are SPECT/CT systems. The purpose of this document is to demonstrate "substantial equivalence" to existing predicate devices, rather than establishing de novo acceptance criteria and then proving the device meets them through a study.

Instead, the submission outlines non-clinical testing performed to demonstrate that the modifications to the predicate device (Discovery NM/CT 670) maintain equivalent functionality and performance. The modifications primarily involve replacing the CT subsystem with GE's 8-slice Revolution ACTs, incremental NM image quality enhancement, and the addition of a Smart Console.

Therefore, the information requested in your prompt regarding acceptance criteria and a study to prove they are met in the traditional sense of a new device validation might not be directly applicable or explicitly stated as such in this 510(k) summary. The document emphasizes testing demonstrating equivalence to predicate devices, not setting new benchmarks.

However, I can extract the relevant information about the non-clinical testing conducted to support the claim of substantial equivalence, which serves a similar purpose in the context of this regulatory submission.

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not present a formal table of "acceptance criteria" for the entire device in the way one might expect for a novel AI device or a new product with entirely new performance claims. Instead, it describes "performance metrics/claims" that were tested to demonstrate substantial equivalence to predicate devices. The listed performance metrics from the "Summary of Additional Testing: Non-Clinical Testing" section are:

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

• Test Set Sample Size: The document refers to "a variety of test methods and phantoms" for non-clinical testing. For the lesion detectability and dose/time reduction evaluations, a phantom was used. No information about a "test set" of clinical data (patients/images) is provided, as the testing was non-clinical.
• Data Provenance: The data provenance is from non-clinical phantom testing conducted by GE Healthcare. This is not retrospective or prospective clinical data from human subjects. The country of origin of the data is not explicitly stated but is implied to be internal testing at GE Medical Systems Israel or other GE Healthcare facilities.

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

Not applicable in the context of this non-clinical phantom study. The "ground truth" for phantom studies is the known physical properties and configurations of the phantom itself. For the lesion detectability evaluation, while a model observer was correlated with "an average human observer," no specific number or qualifications of human experts establishing ground truth for a clinical test set are mentioned, as no clinical test set was used for this part of the evaluation.

4. Adjudication Method for the Test Set:

Not applicable, as the "test set" comprised phantoms with known configurations, not clinical cases requiring expert adjudication.

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

No. The document explicitly states: "Given the above information and the type and scope of changes, particularly that the NM imaging component is identical to the predicate, and the CT component is virtually identical to the Revolution ACTs reference device, clinical testing is not needed to demonstrate substantial equivalence." This indicates that an MRMC study was not performed.

6. If a Standalone Performance Study (algorithm only without human-in-the-loop performance) was done:

Yes, in essence. The non-clinical testing, particularly the use of the Channelized Hotelling Model Observer (CHO) for lesion detectability and dose/time reduction, represents a form of standalone (algorithm/system-only) performance evaluation using objective metrics on phantom data. The CHO model is an objective performance metric that predicts how well a human observer would perform.

7. The Type of Ground Truth Used:

For the non-clinical testing, the ground truth was based on the known physical properties and configurations of the phantoms used to simulate various imaging conditions and lesions.

8. The Sample Size for the Training Set:

Not applicable. This document describes a 510(k) submission for a SPECT/CT imaging device, not an AI algorithm that requires a "training set" in the machine learning sense. The "Smart Console" mentioned is an enhancement to workflow and accessibility, not an AI feature that would typically be trained on a large dataset for diagnostic output.

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

Not applicable, as there was no explicit "training set" for an AI algorithm described in this submission.

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