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SU‐E‐J‐238: First‐Order Approximation of Time‐Resolved 4DMRI From Cine 2DMRI and Respiratory‐Correlated 4DMRI
Author(s) -
Li G,
Wei J,
Tyagi N,
Hunt M,
Deasy J
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4924324
Subject(s) - interpolation (computer graphics) , sagittal plane , nuclear medicine , mathematics , linear interpolation , exhalation , voxel , volume (thermodynamics) , digital radiography , lung volumes , computer science , medicine , physics , computer vision , mathematical analysis , image (mathematics) , radiography , lung , radiology , quantum mechanics , polynomial
Purpose: Cine 2DMRI is useful in MR‐guided radiotherapy but it lacks volumetric information. We explore the feasibility of estimating timeresolved (TR) 4DMRI based on cine 2DMRI and respiratory‐correlated (RC) 4DMRI though simulation. Methods: We hypothesize that a volumetric image during free breathing can be approximated by interpolation among 3DMRI image sets generated from a RC‐4DMRI. Two patients’ RC‐4DMRI with 4 or 5 phases were used to generate additional 3DMRI by interpolation. For each patient, six libraries were created to have total 5‐to‐35 3DMRI images by 0–6 equi‐spaced tri‐linear interpolation between adjacent and full‐inhalation/full‐exhalation phases. Sagittal cine 2DMRI were generated from reference 3DMRIs created from separate, unique interpolations from the original RC‐4DMRI. To test if accurate 3DMRI could be generated through rigid registration of the cine 2DMRI to the 3DMRI libraries, each sagittal 2DMRI was registered to sagittal cuts in the same location in the 3DMRI within each library to identify the two best matches: one with greater lung volume and one with smaller. A final interpolation between the corresponding 3DMRI was then performed to produce the first‐order‐approximation (FOA) 3DMRI. The quality and performance of the FOA as a function of library size was assessed using both the difference in lung volume and average voxel intensity between the FOA and the reference 3DMRI. Results: The discrepancy between the FOA and reference 3DMRI decreases as the library size increases. The 3D lung volume difference decreases from 5–15% to 1–2% as the library size increases from 5 to 35 image sets. The average difference in lung voxel intensity decreases from 7–8 to 5–6 with the lung intensity being 0–135. Conclusion: This study indicates that the quality of FOA 3DMRI improves with increasing 3DMRI library size. On‐going investigations will test this approach using actual cine 2DMRI and introduce a higher order approximation for improvements. This study is in part supported by NIH (U54CA137788 and U54CA132378).