PURPOSE: Amplified magnetic resonance imaging (aMRI) was recently introduced as a new brain motion detection and visualization method. The original aMRI approach used a video-processing algorithm, Eulerian video magnification (EVM), to amplify cardio-ballistic motion in retrospectively cardiac-gated MRI data. Here, we strive to improve aMRI by incorporating a phase-based motion amplification algorithm. METHODS: Phase-based aMRI was developed and tested for correct implementation and ability to amplify sub-voxel motions using digital phantom simulations. The image quality of phase-based aMRI was compared with EVM-based aMRI in healthy volunteers at 3T, and its amplified motion characteristics were compared with phase-contrast MRI. Data were also acquired on a patient with Chiari I malformation, and qualitative displacement maps were produced using free form deformation (FFD) of the aMRI output. RESULTS: Phantom simulations showed that phase-based aMRI has a linear dependence of amplified displacement on true displacement. Amplification was independent of temporal frequency, varying phantom intensity, Rician noise, and partial volume effect. Phase-based aMRI supported larger amplification factors than EVM-based aMRI and was less sensitive to noise and artifacts. Abnormal biomechanics were seen on FFD maps of the Chiari I malformation patient. CONCLUSION: Phase-based aMRI might be used in the future for quantitative analysis of minute changes in brain motion and may reveal subtle physiological variations of the brain as a result of pathology using processing of the fundamental harmonic or by selectively varying temporal harmonics. Preliminary data shows the potential of phase-based aMRI to qualitatively assess abnormal biomechanics in Chiari I malformation.
PURPOSE: Amplified magnetic resonance imaging (aMRI) was recently introduced as a new brain motion detection and visualization method. The original aMRI approach used a video-processing algorithm, Eulerian video magnification (EVM), to amplify cardio-ballistic motion in retrospectively cardiac-gated MRI data. Here, we strive to improve aMRI by incorporating a phase-based motion amplification algorithm. METHODS: Phase-based aMRI was developed and tested for correct implementation and ability to amplify sub-voxel motions using digital phantom simulations. The image quality of phase-based aMRI was compared with EVM-based aMRI in healthy volunteers at 3T, and its amplified motion characteristics were compared with phase-contrast MRI. Data were also acquired on a patient with Chiari I malformation, and qualitative displacement maps were produced using free form deformation (FFD) of the aMRI output. RESULTS: Phantom simulations showed that phase-based aMRI has a linear dependence of amplified displacement on true displacement. Amplification was independent of temporal frequency, varying phantom intensity, Rician noise, and partial volume effect. Phase-based aMRI supported larger amplification factors than EVM-based aMRI and was less sensitive to noise and artifacts. Abnormal biomechanics were seen on FFD maps of the Chiari I malformationpatient. CONCLUSION: Phase-based aMRI might be used in the future for quantitative analysis of minute changes in brain motion and may reveal subtle physiological variations of the brain as a result of pathology using processing of the fundamental harmonic or by selectively varying temporal harmonics. Preliminary data shows the potential of phase-based aMRI to qualitatively assess abnormal biomechanics in Chiari I malformation.
Authors: S Yamada; K Tsuchiya; W G Bradley; M Law; M L Winkler; M T Borzage; M Miyazaki; E J Kelly; J G McComb Journal: AJNR Am J Neuroradiol Date: 2014-07-10 Impact factor: 3.825
Authors: Roberta Sclocco; Ronald G Garcia; Norman W Kettner; Kylie Isenburg; Harrison P Fisher; Catherine S Hubbard; Ilknur Ay; Jonathan R Polimeni; Jill Goldstein; Nikos Makris; Nicola Toschi; Riccardo Barbieri; Vitaly Napadow Journal: Brain Stimul Date: 2019-02-10 Impact factor: 8.955
Authors: Blaise Simplice Talla Nwotchouang; Maggie S Eppelheimer; Soroush Heidari Pahlavian; Jack W Barrow; Daniel L Barrow; Deqiang Qiu; Philip A Allen; John N Oshinski; Rouzbeh Amini; Francis Loth Journal: Ann Biomed Eng Date: 2021-01-04 Impact factor: 4.219
Authors: Maria Eleni Karakatsani; Antonios N Pouliopoulos; Michael Liu; Sachin R Jambawalikar; Elisa E Konofagou Journal: IEEE Trans Biomed Eng Date: 2021-07-16 Impact factor: 4.756