Revolution Ascend Sliding
Overview
The Revolution Ascend Sliding is a state-of-the-art Computed Tomography (CT) system manufactured by GE Hangwei Medical Systems Co. It is designed to deliver advanced clinical capabilities and exceptionally efficient workflow, leveraging artificial intelligence (AI) technology. The system features a 75-cm wide gantry opening and a lower table position to comfortably accommodate a broad range of patients, including those with high body mass index (BMI) and trauma cases.
At its core, the Revolution Ascend Sliding integrates AI-based features for an ‘Effortless Workflow,’ which intelligently automates tasks from pre-scan protocoling to post-scan processing. This includes AI-based patient centering via the Xtream camera, automatic selection of scan parameters (Auto prescription), and Auto Positioning technology that uses deep learning algorithms to determine optimal table elevation and cradle movements. For image reconstruction, it utilizes deep learning technologies such as TrueFidelity DL and True Enhance DL, which aim to improve image quality, reduce noise, and enhance sharpness at low radiation doses. The platform is scalable, offering configurations with 20-40 mm detector coverage and 64/128 slices, and can be upgraded over time. It also includes features like motion-artifact reduction for cardiac imaging and SmartMar for metal artifact reduction.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-based Effortless Workflow (automated patient centering, auto prescription, auto positioning)
- Deep learning image reconstruction (TrueFidelity DL, True Enhance DL)
- 75-cm wide gantry opening for patient comfort and accessibility
- Scalable platform with 20-40 mm detector coverage and 64/128 slices
- Low-dose imaging capabilities (ASiR-V, ACB)
- Motion-artifact reduction for cardiac imaging
- Smart Subscription for continuous software upgrades
- Clarity Operator Environment for intuitive control
- Bariatric table option supporting up to 306 kg
- Interventional capabilities including 3D needle guidance tracking
- SmartMar metal artifact reduction algorithm
Use Cases
- Head, whole-body, cardiac, and vascular CT applications
- Diagnosis of disease, trauma, or abnormality
- Planning, guiding, and monitoring therapy
- Interventional radiology procedures
- Radiation oncology planning
- Efficient scanning for high BMI and trauma patients
What Physicians Need to Know
Leverage the 'Effortless Workflow' AI features for automated patient positioning and intelligent protocol suggestions to optimize scan efficiency and consistency. Utilize 'TrueFidelity DL' for high-definition, low-noise images and 'True Enhance DL' for improved contrast in challenging cases, particularly in oncology, to enhance diagnostic confidence. Remember that 'True Enhance DL' provides adjunct information and should be interpreted alongside original images. The system's scalability and Smart Subscription ensure access to the latest AI innovations.
The Revolution Ascend integrates with standard PACS for automated archiving and results sharing. Its compatibility with Blackford's AI orchestration platform and GE HealthCare's True PACS and v7 PACS allows for seamless integration of AI applications into existing reading room workflows, promoting a unified digital ecosystem for advanced imaging and analysis.
Details
| Category | Radiology & Imaging AI |
| Pricing | Unknown |
| Deployment | On-premise (medical device) |
| Compliance | |
| BAA Available | Yes AI-estimated |
| HIPAA Compliant | Yes AI-estimated |
| FDA Status |
1 AI-estimated The Revolution Ascend Sliding (K233749) is a head and whole-body CT system cleared by the FDA on February 22, 2024. It generates cross-sectional images of the body for diagnosis of disease, trauma, or abnormality, and for planning, guiding, and monitoring therapy in patients of all ages, across head, whole body, cardiac, and vascular X-ray Computed Tomography applications. |
| Integrations | |
| EHR | Not specified |
| Specialties | Cardiology, Interventional Radiology, Radiology |
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