title: 4D tumor centroid tracking using orthogonal 2D dynamic MRI: implications for radiotherapy planning.
abstract: OBJECTIVE
  Current pretreatment, 4D imaging techniques are suboptimal in that they sample breathing motion over a very limited "snapshot" in time. Heretofore, long-duration, 4D motion characterization for radiotherapy planning, margin optimization, and validation have been impractical for safety reasons, requiring invasive markers imaged under x-ray fluoroscopy. To characterize 3D tumor motion and associated variability over durations more consistent with treatments, the authors have developed a practical dynamic MRI (dMRI) technique employing two orthogonal planes acquired in a continuous, interleaved fashion.
  
  
  METHODS
  2D balanced steady-state free precession MRI was acquired continuously over 9-14 min at approximately 4 Hz in three healthy volunteers using a commercial 1.5 T system; alternating orthogonal imaging planes (sagittal, coronal, sagittal, etc.) were employed. The 2D in-plane pixel resolution was 2 × 2 mm(2) with a 5 mm slice profile. Simultaneous with image acquisition, the authors monitored a 1D surrogate respiratory signal using a device available with the MRI system. 2D template matching-based anatomic feature registration, or tracking, was performed independently in each orientation. 4D feature tracking at the raw frame rate was derived using spline interpolation.
  
  
  RESULTS
  Tracking vascular features in the lung for two volunteers and pancreatic features in one volunteer, the authors have successfully demonstrated this method. Registration error, defined here as the difference between the sagittal and coronal tracking result in the SI direction, ranged from 0.7 to 1.6 mm (1σ) which was less than the acquired image resolution. Although the healthy volunteers were instructed to relax and breathe normally, significantly variable respiration was observed. To demonstrate potential applications of this technique, the authors subsequently explored the intrafraction stability of hypothetical tumoral internal target volumes and 3D spatial probability distribution functions. The surrogate respiratory information allowed the authors to show how this technique can be used to study correlations between internal and external (surrogate) information over these prolonged durations. However, compared against the gold standard of the time stamps in the dMRI frames, the temporal synchronization of the surrogate 1D respiratory information was shown to be likely unreliable.
  
  
  CONCLUSIONS
  The authors have established viability of a novel and practical pretreatment, 4D tumor centroid tracking method employing a commercially available dynamic MRI sequence. Further developments from the vendor are likely needed to provide a reliably synchronized surrogate 1D respiratory signal, which will likely broaden the utility of this method in the pretreatment radiotherapy planning context.
authors.affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21231, USA. tryggestad.erik@mayo.edu
authors.forename: Erik
authors.initials: E
authors.lastname: Tryggestad
authors.forename: Aaron
authors.initials: A
authors.lastname: Flammang
authors.forename: Russell
authors.initials: R
authors.lastname: Hales
authors.forename: Joseph
authors.initials: J
authors.lastname: Herman
authors.forename: Junghoon
authors.initials: J
authors.lastname: Lee
authors.forename: Todd
authors.initials: T
authors.lastname: McNutt
authors.forename: Teboh
authors.initials: T
authors.lastname: Roland
authors.forename: Steven M
authors.initials: SM
authors.lastname: Shea
authors.forename: John
authors.initials: J
authors.lastname: Wong
mesh_terms: D000328:Adult; D056973:Four-Dimensional Computed Tomography; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D009068:Movement; D009369:Neoplasms / Q000000981:diagnostic imaging* / Q000503:physiopathology / Q000532:radiotherapy*; D011336:Probability; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*