# K203314: Cartesion Prime (PCD-1000A/3) V10.8

- Pathway: 510(k) (Traditional)
- Applicant: Canon Medical Systems Corporation
- Decided: Apr 23, 2021 after 164 days
- Product code: KPS (System, Tomography, Computed, Emission)
- Device class: 2
- Regulation: 21 CFR 892.1200
- Recalls of this device: 1 (0 Class I)
- Data: FDA decisions to Oct 25, 2026; recalls to Oct 12, 2026

## Lineage
Longest line of descent: 1 generation back to K202349 (2020). 1 ancestor in all.
No later device cites it as a predicate yet.
0 of 2 devices in its family (counting itself) have a Class I recall.

## Predicates on the family tree (from the FDA summary)
- K202349: Cartesion Prime, PCD-1000A, V10.7, Canon Medical Systems Corporation (2020) Summary page 5.

## Recalls of this device
- Nov 11, 2020 · Class II · Z-0142-2022: A software problem has been identified which could result in the diagnostic imaging system not proceeding to the next actual scan even though automatic start of the next scan is specified. This could 

## Indications for use
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, localization, 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. AiCE-i for PET is intended to improve image quality and reduce image noise for FDG whole body data by employing deep learning artificial neural network methods which can explore the statistical properties of the signal and noise of PET data. The AiCE algorithm can be applied to improve image quality and denoising of PET images.

Source page: https://510kreport.com/device/K203314
Methodology: https://510kreport.com/methodology