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Gus Iversen, Editor in Chief | December 04, 2024
Siemens Healthineers introduced its Biograph One PET/MR scanner at the RSNA meeting, showcasing its potential to enhance personalized medicine through integrated diagnostic and therapeutic capabilities and emphasizing its potential in theranostics.
“Modern imaging systems offer high precision in visualizing pathological changes and make a crucial contribution to diagnosing life-threatening and complex diseases such as cancer and neurological disorders,” said Andreas Schneck, head of magnetic resonance imaging at Siemens Healthineers. “PET/MR can be valuable for tracking disease progression and evaluating treatment effectiveness, fostering individualized and adaptable therapies.”
The scanner is built on Siemens Healthineers’ Magnetom Vida 3 Tesla MR platform and incorporates a digital PET detector using lutetium oxyorthosilicate crystals, based on Biograph Vision technology. The design aims to deliver high spatial resolution and ultrafast time-of-flight imaging, reducing acquisition times and enabling flexible dose administration.
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Biograph One includes a 35-cm axial field-of-view PET detector, reducing the need for multiple bed positions in whole-body scans. This feature is particularly useful in oncology, allowing simultaneous imaging of brain tumors and lymph node metastases. AI-driven tools like Deep Resolve further accelerate image reconstruction, supporting both 2D and 3D imaging for a wider range of clinical applications.
“PET/MR in neurology and neuro-oncology is in high demand from referring clinicians and patients alike for the logistic convenience and the possibility of combining a high-quality molecular and anatomical examination," said Dr. Ian Law, professor, senior consultant, Rigshospitalet Copenhagen. "We are excited about the ambitious technology in PET/MR Biograph One and the possible impact on our diagnostic workflow and abilities to expand into new diagnostic fields.”
Additionally, the myExam Companion intelligent user interface integrates automation and AI to streamline radiology workflows, aiming to reduce patient slot times by half.
