Data-driven respiratory gating for ventilation/perfusion lung scan.
Journal
The quarterly journal of nuclear medicine and molecular imaging : official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology (IAR), [and] Section of the Society of...
ISSN: 1827-1936
Titre abrégé: Q J Nucl Med Mol Imaging
Pays: Italy
ID NLM: 101213861
Informations de publication
Date de publication:
Dec 2019
Dec 2019
Historique:
pubmed:
8
2
2018
medline:
28
4
2020
entrez:
8
2
2018
Statut:
ppublish
Résumé
Ventilation/perfusion lung scan is subject to blur due to respiratory motion whether with planar acquisition or single photon emission computed tomography (SPECT). We propose a data-driven gating method for extracting different respiratory phases from lung scan list-mode or dynamic data. The algorithm derives a surrogate respiratory signal from an automatically detected diaphragmatic region of interest. The time activity curve generated is then filtered using a Savitzky-Golay filter. We tested this method on an oscillating phantom in order to evaluate motion blur decrease and on one lung SPECT. Our algorithm reduced motion blur on phantom acquisition: mean full width at half maximum 8.1 pixels on non-gated acquisition versus 5.3 pixels on gated acquisition and 4.1 pixels on reference image. Automated detection of the diaphragmatic region and time-activity curves generation were successful on patient acquisition. This algorithm is compatible with a clinical use considering its runtime. Further studies will be needed in order to validate this method.
Sections du résumé
BACKGROUND
BACKGROUND
Ventilation/perfusion lung scan is subject to blur due to respiratory motion whether with planar acquisition or single photon emission computed tomography (SPECT). We propose a data-driven gating method for extracting different respiratory phases from lung scan list-mode or dynamic data.
METHODS
METHODS
The algorithm derives a surrogate respiratory signal from an automatically detected diaphragmatic region of interest. The time activity curve generated is then filtered using a Savitzky-Golay filter. We tested this method on an oscillating phantom in order to evaluate motion blur decrease and on one lung SPECT.
RESULTS
RESULTS
Our algorithm reduced motion blur on phantom acquisition: mean full width at half maximum 8.1 pixels on non-gated acquisition versus 5.3 pixels on gated acquisition and 4.1 pixels on reference image. Automated detection of the diaphragmatic region and time-activity curves generation were successful on patient acquisition.
CONCLUSIONS
CONCLUSIONS
This algorithm is compatible with a clinical use considering its runtime. Further studies will be needed in order to validate this method.
Identifiants
pubmed: 29409314
pii: S1824-4785.18.03002-9
doi: 10.23736/S1824-4785.18.03002-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM