title: Ultrafast 3D balanced steady-state free precession MRI of the lung: Assessment of anatomic details in comparison to low-dose CT.
abstract: OBJECTIVE
  To evaluate the anatomical details offered by a new single breath-hold ultrafast 3D balanced steady-state free precession (uf-bSSFP) sequence in comparison to low-dose chest computed tomography (CT).
  
  
  METHODS
  This was an Institutional Review Board (IRB)-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant prospective study. A total of 20 consecutive patients enrolled in a lung cancer screening trial underwent same-day low-dose chest CT and 1.5T MRI. The presence of pulmonary nodules and anatomical details on 1.9 mm isotropic uf-bSSFP images was compared to 2 mm lung window reconstructions by two readers. The number of branching points on six predefined pulmonary arteries and the distance between the most peripheral visible vessel segment to the pleural surface on thin slices and 50 mm maximum intensity projections (MIP) were assessed. Image quality and sharpness of the pulmonary vasculature were rated on a 5-point scale.
  
  
  RESULTS
  The uf-bSSFP detection rate of pulmonary nodules (32 nodules visible on CT and MRI, median diameter 3.9 mm) was 45.5% with 21 false-positive findings (pooled data of both readers). Uf-bSSFP detected 71.2% of branching points visible on CT data. The mean distance between peripheral vasculature and pleural surface was 13.0 ± 4.2 mm (MRI) versus 8.5 ± 3.3 mm (CT) on thin slices and 8.6 ± 3.9 mm (MRI) versus 4.6 ± 2.5 mm (CT) on MIPs. Median image quality and sharpness were rated 4 each.
  
  
  CONCLUSIONS
  Although CT is superior to MRI, uf-bSSFP imaging provides good anatomical details with sufficient image quality and sharpness obtainable in a single breath-hold covering the entire chest.
authors.affiliation: Cardiothoracic Section, Department of Radiology and Nuclear Medicine, University Hospital Basel, Switzerland.
authors.forename: Tobias
authors.initials: T
authors.lastname: Heye
authors.affiliation: Cardiothoracic Section, Department of Radiology and Nuclear Medicine, University Hospital Basel, Switzerland.
authors.forename: Gregor
authors.initials: G
authors.lastname: Sommer
authors.affiliation: Swiss National Insurance Fund SUVA, Luzern, Switzerland.
authors.forename: David
authors.initials: D
authors.lastname: Miedinger
authors.affiliation: Cardiothoracic Section, Department of Radiology and Nuclear Medicine, University Hospital Basel, Switzerland.
authors.forename: Jens
authors.initials: J
authors.lastname: Bremerich
authors.affiliation: MR Physics, Department of Radiology and Nuclear Medicine, University Hospital Basel, Switzerland.
authors.forename: Oliver
authors.initials: O
authors.lastname: Bieri
mesh_terms: D000368:Aged; D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008168:Lung / Q000000981:diagnostic imaging* / Q000473:pathology*; D008175:Lung Neoplasms / Q000175:diagnosis / Q000000981:diagnostic imaging* / Q000473:pathology*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D011651:Pulmonary Artery / Q000473:pathology; D011857:Radiographic Image Interpretation, Computer-Assisted; D012119:Respiration; D003074:Solitary Pulmonary Nodule / Q000175:diagnosis / Q000000981:diagnostic imaging / Q000473:pathology; D014057:Tomography, X-Ray Computed
keywords: CT; MRI; anatomical details; chest; pulmonary nodules