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New technology provides full HD lesion detection during free breathing exams

Siemens Molecular Imaging announces HD•Chest – a new technology that reduces blur created by respiration during PET / CT studies, at the European Association of Nuclear Medicine congress from October 9-13 in Vienna, Austria. The latest evolution in Siemens high-definition PET technologies, HD•Chest provides full high definition (HD) lesion detection and improved SUV quantification for every PET / CT study, every day.

More than 90 percent of today’s PET / CT studies are whole-body scans that can be used to investigate the presence of small lesions in the chest or upper abdomen. By providing a highly automated, amplitude-based gating technology, HD•Chest images the chest and upper abdomen in high-definition and eliminates the fundamental problems encountered with phase-based 4D gating, which can be disruptive and time consuming. HD•Chest is an innovative combination of hardware and software, that provides an accurate, sharp image as respiratory motion is frozen. It also encourages an easy workflow for the routine evaluation of chest and upper abdomen lesions, providing additional clinical value with every patient study.

“Without disrupting clinical workflow, physicians can gain more accurate information on every patient,” says Britta Fuenfstueck, CEO, Molecular Imaging, Siemens Healthcare. “ Siemens Healthcare  is committed to providing increased diagnostic confidence by providing images with more data and less noise. With HD•Chest, small moving lesions become clearer and more defined; no longer hidden in the blur of respiratory motion.”

Because breathing motion is chaotic, the direction of motion and its magnitude vary from patient to patient. They also vary from session to session for a given patient, and even from moment to moment within the procedure. HD•Chest optimizes each patient’s respiratory curve to automatically produce the highest quality PET image. It intelligently adapts to every patients breathing and automatically selects the optimal data range with the least amount of motion and the highest count statistics.

Source: Siemens Healthcare

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