title: Respiratory motion compensation for simultaneous PET/MR based on highly undersampled MR data.
abstract: OBJECTIVE
  Positron emission tomography (PET) of the thorax region is impaired by respiratory patient motion. To account for motion, the authors propose a new method for PET/magnetic resonance (MR) respiratory motion compensation (MoCo), which uses highly undersampled MR data with acquisition times as short as 1 min/bed.
  
  
  METHODS
  The proposed PET/MR MoCo method (4D jMoCo PET) uses radial MR data to estimate the respiratory patient motion employing MR joint motion estimation and image reconstruction with temporal median filtering. Resulting motion vector fields are incorporated into the system matrix of the PET reconstruction. The proposed approach is evaluated for the thorax region utilizing a PET/MR simulation with 1 min MR acquisition time and simultaneous PET/MR measurements of six patients with MR acquisition times of 1 and 5 min and radial undersampling factors of 11.2 and 2.2, respectively. Reconstruction results are compared to 3D PET, 4D gated PET and a standard MoCo method (4D sMoCo PET), which performs iterative image reconstruction and motion estimation sequentially. Quantitative analysis comprises the parameters SUVmean, SUVmax, full width at half-maximum/lesion volume, contrast and signal-to-noise ratio.
  
  
  RESULTS
  For simulated PET data, our quantitative analysis shows that the proposed 4D jMoCo PET approach with temporal filtering achieves the best quantification accuracy of all tested reconstruction methods with a mean absolute deviation of 2.3% when compared to the ground truth. For measured PET patient data, the mean absolute deviation of 4D jMoCo PET using a 1 min MR acquisition for motion estimation is 2.1% relative to the 5 min MR acquisition. This demonstrates a robust behavior even in case of strong undersampling at MR acquisition times as short as 1 min. In contrast, 4D sMoCo PET shows considerable reduction of quantification accuracy for the 1 min MR acquisition time. Relative to 3D PET, the proposed 4D jMoCo PET approach with temporal filtering yields an average increase of SUVmean, SUVmax, and contrast of 29.9% and 13.8% for simulated and measured PET data, respectively.
  
  
  CONCLUSIONS
  Employing artifact-robust motion estimation enables PET/MR respiratory MoCo with MR acquisition times as short as 1 min/bed improving PET image quality and quantification accuracy.
authors.affiliation: Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Rank
authors.affiliation: Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
authors.forename: Thorsten
authors.initials: T
authors.lastname: Heußer
authors.affiliation: Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany and Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, 123 Old Brompton Road, London SW7 3RP, United Kingdom.
authors.forename: Andreas
authors.initials: A
authors.lastname: Wetscherek
authors.affiliation: Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
authors.forename: Martin T
authors.initials: MT
authors.lastname: Freitag
authors.affiliation: Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
authors.forename: Oliver
authors.initials: O
authors.lastname: Sedlaczek
authors.affiliation: Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
authors.forename: Heinz-Peter
authors.initials: HP
authors.lastname: Schlemmer
authors.affiliation: Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
authors.forename: Marc
authors.initials: M
authors.lastname: Kachelrieß
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016477:Artifacts; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009068:Movement; D064847:Multimodal Imaging; D049268:Positron-Emission Tomography; D012119:Respiration; D059629:Signal-To-Noise Ratio