Aquilion ONE (TSX-308A/3) V1.5 is a whole-body multi-slice helical CT scanner capable of imaging entire organs in a single rotation. It uses AI-powered deep learning reconstruction and noise reduction algorithms to enhance image quality, reduce radiation dose, and minimize artifacts. This helps clinicians obtain clearer diagnostic images for various body regions including the head, chest, abdomen, pelvis, cardiac, extremities, and lungs, supporting better patient diagnosis and treatment planning.
This device is indicated to acquire and display cross sectional volumes of the whole body, to include the head, with the capability to image whole organs in a single rotation. It provides volume sets of the entire organ for specialized studies by qualified physicians. It includes iterative reconstruction algorithms (FIRST), deep learning noise reduction (AiCE), and deep learning reconstruction methods (PIQE, CLEAR Motion) to improve image quality, reduce dose, and reduce motion artifacts.
The device is a whole-body multi-slice helical CT scanner that acquires volumetric data sets through a gantry and couch system. It uses iterative reconstruction (FIRST), deep convolutional neural network (DCNN) based noise reduction (AiCE), deep learning reconstruction (PIQE), and motion correction (CLEAR Motion) algorithms. The spectral imaging system acquires two nearly simultaneous CT images using rapid KV switching for material characterization. These advanced AI algorithms improve image quality, reduce noise and radiation dose, and mitigate motion artifacts.
Performance testing included phantom and clinical image evaluations comparing PIQE Lung and Body Image Quality, Spectral Cardiac Image Quality, and CLEAR Motion performance to predicate devices. Bench tests confirmed equivalent or improved image quality and significant motion artifact reduction. Clinical images reviewed by board-certified radiologists confirmed diagnostic quality. Software verification and validation, risk analysis, and cybersecurity assessments were completed demonstrating safety and effectiveness.
No predicate devices specified
Submission
8/13/2024
FDA Approval
12/23/2024
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