Offering a combination of simplified and personalized scanning for patients at significantly lower lifecycle costs than other dual-source CT systems, the Somatom Pro.Pulse may be a viable option for smaller rural facilities and outpatient imaging centers.
Emphasizing significantly less power consumption than other dual-source computed tomography (CT) devices, the newly launched Somatom Pro.Pulse system may facilitate increased access to this technology at smaller facilities.
Siemens Heathineers, the manufacturer of Somatom Pro.Pulse, said the system can be utilized at up to 20 percent less power consumption than previous iterations of dual-source CT. This increased energy efficiency and an improved cooling system have contributed to significantly reduced lifecycle costs for the Somatom Pro.Pulse, according to the company.
Other advantages with the system include myExam Companion, which facilitates optimal CT scan parameters based on patient data and other considerations, such as breath-hold capabilities and heart rate. Siemens Healthineers said the Somatom Pro.Pulse also features a FAST (fully assisting scanner technologies) 3D camera that allows automated patient positioning. The company added that the system’s use of tin filters preserves low radiation dosing while ensuring optimal image quality.
“With our new advanced dual source CT scanner, we aim to make this high-class technology available to more patients,” noted Philipp Fischer, the head of computed tomography at Siemens Healthineers. “CT exams performed on this system follow an intelligent and intuitive workflow appealing to various levels of experience. This enables standardization and reproducibility for clinicians and thus saves personnel capacities.”
Can CT-Based Deep Learning Bolster Prognostic Assessments of Ground-Glass Nodules?
June 19th 2025Emerging research shows that a multiple time-series deep learning model assessment of CT images provides 20 percent higher sensitivity than a delta radiomic model and 56 percent higher sensitivity than a clinical model for prognostic evaluation of ground-glass nodules.