Ultrasound-based sensors for respiratory motion assessment in multimodality PET imaging

• Published in: Physics in medicine & biology 2022-01, Vol.67 (2), p.2
• Main Authors: Madore, Bruno, Belsley, Gabriela, Cheng, Cheng-Chieh, Preiswerk, Frank, Kijewski, Marie Foley, Wu, Pei-Hsin, Martell, Laurel B, Pluim, Josien P W, Di Carli, Marcelo, Moore, Stephen C
• Format: Article
• Language: English
• Subjects: Humans; image fusion; Motion; motion correction; Multimodal Imaging; Phantoms, Imaging; physiological motion; Positron Emission Tomography Computed Tomography; Positron-Emission Tomography - methods; respiratory gating; sensors; ultrasound-based sensors
• ISSN: 0031-9155; 1361-6560
• DOI: 10.1088/1361-6560/ac4213

Breathing motion can displace internal organs by up to several cm; as such, it is a primary factor limiting image quality in medical imaging. Motion can also complicate matters when trying to fuse images from different modalities, acquired at different locations and/or on different days. Currently available devices for monitoring breathing motion often do so indirectly, by detecting changes in the outline of the torso rather than the internal motion itself, and these devices are often fixed to floors, ceilings or walls, and thus cannot accompany patients from one location to another. We have developed small ultrasound-based sensors, referred to as 'organ configuration motion' (OCM) sensors, that attach to the skin and provide rich motion-sensitive information. In the present work we tested the ability of OCM sensors to enable respiratory gating during PET imaging. A motion phantom involving an FDG solution was assembled, and two cancer patients scheduled for a clinical PET/CT exam were recruited for this study. OCM signals were used to help reconstruct phantom and data into time series of motion-resolved images. As expected, the motion-resolved images captured the underlying motion. In Patient #1, a single large lesion proved to be mostly stationary through the breathing cycle. However, in Patient #2, several small lesions were mobile during breathing, and our proposed new approach captured their breathing-related displacements. In summary, a relatively inexpensive hardware solution was developed here for respiration monitoring. Because the proposed sensors attach to the skin, as opposed to walls or ceilings, they can accompany patients from one procedure to the next, potentially allowing data gathered in different places and at different times to be combined and compared in ways that account for breathing motion.