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The device is a diagnostic imaging system that combines Positron Emission Tomography (PET) and X-ray Computed Tomography (CT) systems. The CT component produces cross-sectional images of the body by computer reconstruction of X-ray transmission data. The PET component images the distribution of PET radiopharmaceuticals in the patient body. The PET component utilizes CT images for attenuation correction and anatomical reference in the fused PET and CT images.

This device is to be used by a trained health care professional to gather metabolic and functional information from the distribution of the radiopharmaceutical in the body for the assessment of metabolic and physiologic functions. This information can assist in the evaluation, detection, diagnosis, staging, restaging, follow-up, therapeutic planning and therapeutic outcome assessment of (but not limited to) oncological, cardiovascular, neurological diseases and disorders. Additionally, this device can be operated independently as a whole body multi-slice CT scanner.

Cartesion Prime, PCD-1000A, V10.7 system combines a high-end CT and a high-throughput PET designed to acquire CT, PET and fusion images. The high-end CT system is a multi-slice helical CT scanner with a gantry aperture of 780 mm and a maximum scanning field of 700 mm. The highthroughput PET system has a digital PET detector utilizing SIPM sensors with temporal resolution of

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics. Instead, it describes performance improvements and successful testing against standards. However, key performance indicators and improvements mentioned can be synthesized into a pseudo-acceptance table based on comparisons to the predicate device and improved image quality.

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

The document does not specify a patient sample size for the test set. The testing described primarily involves "bench testing." It mentions improvements in image quality (Signal-to-Noise Ratio, noise, contrast, spatial resolution) with various features and functionalities. The data provenance is not explicitly stated as patient data from a specific country or as retrospective/prospective. The description suggests testing was conducted on phantoms or simulated data suitable for bench testing, rather than human subjects.

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

The document does not mention the use of experts to establish ground truth for a test set. This is consistent with the nature of the described "bench testing," which would typically involve objective measurements against known physical standards or simulated conditions, rather than expert interpretation of medical images.

4. Adjudication Method for the Test Set:

No adjudication method is mentioned, as expert interpretation and ground truth establishment (as typically understood in clinical studies) are not described for the test set.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done based on the provided information. The submission focuses on device modifications and performance improvements validated through bench testing, rather than human reader performance studies.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

The testing described appears to be a standalone (algorithm only without human-in-the-loop performance) study, specifically focusing on the technical performance characteristics of the device and its included software features. The document highlights improvements in image quality metrics (SNR, noise, contrast, spatial resolution) directly attributable to the device's algorithms and hardware, without involving human interpretation of the output.

7. Type of Ground Truth Used:

The type of ground truth used appears to be based on objective physical measurements and established imaging science principles relevant to the technical specifications of a PET/CT system. For example, "Signal-to-Noise Ratio," "noise," "contrast," and "spatial resolution" are quantifiable metrics. The improvements observed with CaLM, PSF correction, and gating are against an implicit baseline or ideal performance under controlled bench testing conditions, rather than against clinical outcomes, pathology, or expert consensus on patient cases.

8. Sample Size for the Training Set:

The document does not provide any information regarding a training set size. This indicates that the validation performed for this submission was not based on machine learning model training and evaluation using labeled datasets in the traditional sense, but rather on direct performance testing of the device's imaging capabilities and software features.

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

As no training set is mentioned, the method for establishing its ground truth is not applicable in this context.

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