Cartesion Prime (PCD-1000A/3) V10.15

The Cartesion Prime (PCD-1000A/3) V10.15 is a hybrid PET/CT imaging system designed to provide comprehensive diagnostic information by imaging radiopharmaceutical distribution for metabolic and functional assessment, and X-ray transmission for anatomical detail. It enhances PET image quality through AiCE-i deep learning reconstruction for FDG data and incorporates a Deviceless PET Respiratory-gating system to mitigate motion artifacts by generating gating signals directly from PET data.

The Cartesion Prime (PCD-1000A/3) V10.15 is a diagnostic imaging system that integrates Positron Emission Tomography (PET) and X-ray Computed Tomography (CT) functionalities. The PET component visualizes the distribution of administered radiopharmaceuticals to gather metabolic and functional information for assessing physiologic functions, while the CT component provides cross-sectional anatomical images used for attenuation correction and anatomical reference in fused PET/CT images. This system is intended for use by trained healthcare professionals to aid in the evaluation, detection, localization, diagnosis, staging, restaging, follow-up, therapeutic planning, and therapeutic outcome assessment for a range of conditions, including oncological, cardiovascular, and neurological diseases. The device can also operate as a standalone whole-body multi-slice CT scanner. This version introduces two key technological advancements: AiCE-i for PET and a Deviceless PET Respiratory-gating system. AiCE-i for PET employs deep learning artificial neural network methods to enhance image quality and reduce noise in FDG whole-body PET data by analyzing the statistical properties of the signal and noise. The Deviceless PET Respiratory-gating system automatically generates a gating signal from list-mode PET data to reconstruct motion-corrected PET images, particularly beneficial for lesions in the thorax, abdomen, and pelvis affected by respiratory motion. Bench testing demonstrated that this deviceless system improves quantitative parameters like SUV accuracy and tumor volume compared to device-based gating. Clinical image review by experienced physicians confirmed that images acquired using the deviceless gating system were of diagnostic quality, performing as well as or better than non-gated or device-based gated images.

AI Regulatory Concerns

Powered by

Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. What is the quantifiable improvement in lesion detectability and standardized uptake value (SUV) accuracy when using the AiCE-i deep learning algorithm for PET, particularly for small or low-contrast lesions, compared to conventional reconstruction methods across various radiopharmaceuticals beyond FDG?; How does the Deviceless PET Respiratory-gating system algorithm differentiate between patient respiratory motion and other physiological movements, and what is its robustness across a spectrum of breathing patterns and patient conditions (e.g., arrhythmias, involuntary movements)?; What are the specific performance metrics (e.g., reduction in motion artifacts, improvement in spatial resolution) of the Deviceless PET Respiratory-gating system in imaging lesions in the thorax, abdomen, and pelvis, and how do these compare across different patient ages, body habitus, and disease types?; Are there any specific clinical scenarios or patient populations where the combination of AiCE-i and the Deviceless PET Respiratory-gating system demonstrates a synergistic effect on diagnostic accuracy or changes in therapeutic planning compared to using each technology independently?; What is the typical processing time added by the AiCE-i algorithm and the Deviceless PET Respiratory-gating system to the overall image reconstruction workflow, and how might this impact clinical throughput?