Software respiratory gating of positron emission tomography-computed tomography improves pulmonary nodule detection

Morley, Nicholas C.D. ORCID: https://orcid.org/0000-0001-9261-9385, McGowan, Daniel R., Gleeson, Fergus V. and Bradley, Kevin M. ORCID: https://orcid.org/0000-0003-1911-3382 2017. Software respiratory gating of positron emission tomography-computed tomography improves pulmonary nodule detection. American Journal of Respiratory and Critical Care Medicine 195 (2) , pp. 261-262. 10.1164/rccm.201607-1371IM

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Abstract

Pulmonary nodules are blurred by respiratory motion during a fludeoxyglucose F 18 (FDG) positron emission tomography (PET) scan. Current scans have limited ability to assess subcentimeter nodules (1). Devices to mitigate respiratory motion by gating the PET acquisition have achieved limited application. Data-driven gating (DDG) is a novel software technique to detect respiratory motion within PET data, using the static phase for reconstruction, without any additional hardware or radiation dose (2–4). A 60-year-old man underwent FDG imaging to stage colorectal cancer (GE Discovery 690 PET/computed tomography [CT]; GE Healthcare, Milwaukee, WI). On the CT component, a 6-mm pulmonary nodule was identified posteriorly in the right lower lobe (Figure 1A). Using our routine reconstruction (5), this nodule is indistinct from background activity. The greatest Standardized Uptake Value in the volume of interest (SUVmax) is 1.9 and relates to the chest wall (Figure 1B). After retrospective DDG reconstruction, the nodule appears FDG-avid, with SUVmax 2.8 (Figure 1C) now greater than mediastinal blood pool. Uptake within other small pulmonary and hepatic metastases also became more conspicuous, being smaller with increased SUVmax. Although not altering management for this patient, this illustrates that DDG may identify solitary or additional metastases that could benefit patient care. This new technology requires validation, but it promises to enhance the role of FDG PET/CT detection and assessment of small nodules. It could also improve the characterization, quantitative assessment, and risk prediction of larger pulmonary nodules (1).

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Medicine
Publisher:	American Thoracic Society
ISSN:	1073-449X
Last Modified:	01 Apr 2025 15:02
URI:	https://orca.cardiff.ac.uk/id/eprint/132003

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