Aquilion Serve SP (TSX-307B/1) V1.3

The Aquilion Serve SP (TSX-307B/1) V1.3 is a whole-body computed tomography system designed to provide high-quality cross-sectional volumetric images with enhanced diagnostic capabilities and reduced radiation dose. It achieves this through a combination of an upgraded X-ray tube and generator, a novel SilverBeam Filter for X-ray beam optimization, and an AI-driven image reconstruction algorithm (AiCE) utilizing Deep Convolutional Neural Networks.

The Aquilion Serve SP (TSX-307B/1) V1.3 is a whole-body multi-slice helical computed tomography (CT) scanner designed to acquire and display cross-sectional volumetric data for a wide range of anatomical regions, including the head. It operates using a gantry, couch, and console for data processing and display, enabling trained physicians to perform specialized studies. Key technological advancements include a higher capacity 7.5 MHU X-ray tube and an increased X-ray generator output (max 72 kW), which distinguish it from its primary predicate device. The system also incorporates AiCE (Advanced Intelligent Clear-IQ Engine), a noise reduction algorithm utilizing Deep Convolutional Neural Network (DCNN) methods to enhance image quality and reduce noise across various applications such as abdominal, pelvic, lung, cardiac, extremities, head, and inner ear imaging. A significant feature of the Aquilion Serve SP is the SilverBeam Filter, a beam-shaping filter that uses silver's photon-attenuating properties to selectively remove low-energy photons, thereby optimizing the X-ray energy spectrum for high-contrast CT applications and facilitating dose reduction. Performance testing using phantoms demonstrated improved or equivalent image quality metrics compared to predicate devices, including Contrast-to-Noise Ratios, CT Number Accuracy, and Modulation Transfer Function. Specific studies confirmed that its Dose Reduction Mode, leveraging the SilverBeam Filter, effectively reduces radiation dose in both head and body scanning modes compared to normal scan protocols.

AI Regulatory Concerns

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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 quantitative range of dose reduction achieved with the SilverBeam Filter in DR-Mode across different anatomical regions (e.g., head vs. body) and patient sizes, beyond the general statement of reduction?; How does the AiCE DCNN algorithm specifically differentiate between noise and fine anatomical details, particularly in low-contrast regions or when imaging pediatric patients?; What are the specific improvements in image quality metrics (e.g., CNR, MTF) observed with the 7.5 MHU X-ray tube and increased generator output compared to the 5.0 MHU tube configuration, and how do these translate to diagnostic confidence?; Are there specific imaging protocols or patient populations where the combination of SilverBeam Filter and AiCE provides the most significant diagnostic advantage over systems lacking these features?; What is the impact of the SilverBeam Filter on the X-ray spectrum, and how does this altered spectrum affect quantitative CT measurements, such as Hounsfield Unit accuracy, for different tissue types?