High-Definition PET/CT Reduces Blur, Improves Standardized Uptake Values

A new technology that reduces blur created by respiration during positron emission tomography/computed tomography (PET/CT) studies provides full high definition (HD) lesion detection and improved standardized uptake value (SUV) quantification for every PET/CT image in a study.

The latest evolution in Siemens Healthcare (Erlangen, Germany) high-definition PET technologies, HD-Chest, was presented at the European Association of Nuclear Medicine congress from October 9-13, 2010, in Vienna, Austria.

More than 90% 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 four dimensional (4D) gating, which can be disruptive and time consuming. HD-Chest is a novel 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,” stated Britta Fuenfstueck, CEO, Molecular Imaging, Siemens Healthcare. "Siemens 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 a very high 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.

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