title: Compressed-sensing motion compensation (CosMo): a joint prospective-retrospective respiratory navigator for coronary MRI.
abstract: Prospective right hemidiaphragm navigator (NAV) is commonly used in free-breathing coronary MRI. The NAV results in an increase in acquisition time to allow for resampling of the motion-corrupted k-space data. In this study, we are presenting a joint prospective-retrospective NAV motion compensation algorithm called compressed-sensing motion compensation (CosMo). The inner k-space region is acquired using a prospective NAV; for the outer k-space, a NAV is only used to reject the motion-corrupted data without reacquiring them. Subsequently, those unfilled k-space lines are retrospectively estimated using compressed sensing reconstruction. We imaged right coronary artery in nine healthy adult subjects. An undersampling probability map and sidelobe-to-peak ratio were calculated to study the pattern of undersampling, generated by NAV. Right coronary artery images were then retrospectively reconstructed using compressed-sensing motion compensation for gating windows between 3 and 10 mm and compared with the ones fully acquired within the gating windows. Qualitative imaging score and quantitative vessel sharpness were calculated for each reconstruction. The probability map and sidelobe-to-peak ratio show that the NAV generates a random undersampling k-space pattern. There were no statistically significant differences between the vessel sharpness and subjective score of the two reconstructions. Compressed-sensing motion compensation could be an alternative motion compensation technique for free-breathing coronary MRI that can be used to reduce scan time.
authors.affiliation: Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Mehdi H
authors.initials: MH
authors.lastname: Moghari
authors.forename: Mehmet
authors.initials: M
authors.lastname: Akçakaya
authors.forename: Alan
authors.initials: A
authors.lastname: O'Connor
authors.forename: Tamer A
authors.initials: TA
authors.lastname: Basha
authors.forename: Michele
authors.initials: M
authors.lastname: Casanova
authors.forename: Douglas
authors.initials: D
authors.lastname: Stanton
authors.forename: Lois
authors.initials: L
authors.lastname: Goepfert
authors.forename: Kraig V
authors.initials: KV
authors.lastname: Kissinger
authors.forename: Beth
authors.initials: B
authors.lastname: Goddu
authors.forename: Michael L
authors.initials: ML
authors.lastname: Chuang
authors.forename: Vahid
authors.initials: V
authors.lastname: Tarokh
authors.forename: Warren J
authors.initials: WJ
authors.lastname: Manning
authors.forename: Reza
authors.initials: R
authors.lastname: Nezafat
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D055424:Cardiac-Gated Imaging Techniques / Q000379:methods*; D003331:Coronary Vessels / Q000033:anatomy & histology*; D044962:Data Compression / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008297:Male; D009038:Motion; D015203:Reproducibility of Results; D055425:Respiratory-Gated Imaging Techniques / Q000379:methods*; D012680:Sensitivity and Specificity