Yilin Liu1, Xiaodong Zhong2, Brian G Czito3, Manisha Palta3, Mustafa R Bashir4,5, Brian M Dale6, Fang-Fang Yin1,3, Jing Cai1,3. 1. Medical Physics Graduate Program, Duke University, Durham, NC, 27710, USA. 2. MR R&D Collaborations, Siemens Healthcare, Atlanta, GA, 30354, USA. 3. Department of Radiation Oncology, Duke University Medical Center, Durham, NC, 27710, USA. 4. Department of Radiology, Duke University Medical Center, Durham, NC, 27710, USA. 5. Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC, 27710, USA. 6. MR R&D Collaborations, Siemens Healthcare, Cary, NC, 27511, USA.
Abstract
PURPOSE: Diffusion-weighted Magnetic Resonance Imaging (DWI) has been shown to be a powerful tool for cancer detection with high tumor-to-tissue contrast. This study aims to investigate the feasibility of developing a four-dimensional DWI technique (4D-DWI) for imaging respiratory motion for radiation therapy applications. MATERIALS/ METHODS: Image acquisition was performed by repeatedly imaging a volume of interest (VOI) using an interleaved multislice single-shot echo-planar imaging (EPI) 2D-DWI sequence in the axial plane. Each 2D-DWI image was acquired with an intermediately low b-value (b = 500 s/mm2 ) and with diffusion-encoding gradients in x, y, and z diffusion directions. Respiratory motion was simultaneously recorded using a respiratory bellow, and the synchronized respiratory signal was used to retrospectively sort the 2D images to generate 4D-DWI. Cine MRI using steady-state free precession was also acquired as a motion reference. As a preliminary feasibility study, this technique was implemented on a 4D digital human phantom (XCAT) with a simulated pancreas tumor. The respiratory motion of the phantom was controlled by regular sinusoidal motion profile. 4D-DWI tumor motion trajectories were extracted and compared with the input breathing curve. The mean absolute amplitude differences (D) were calculated in superior-inferior (SI) direction and anterior-posterior (AP) direction. The technique was then evaluated on two healthy volunteers. Finally, the effects of 4D-DWI on apparent diffusion coefficient (ADC) measurements were investigated for hypothetical heterogeneous tumors via simulations. RESULTS: Tumor trajectories extracted from XCAT 4D-DWI were consistent with the input signal: the average D value was 1.9 mm (SI) and 0.4 mm (AP). The average D value was 2.6 mm (SI) and 1.7 mm (AP) for the two healthy volunteers. CONCLUSION: A 4D-DWI technique has been developed and evaluated on digital phantom and human subjects. 4D-DWI can lead to more accurate respiratory motion measurement. This has a great potential to improve the visualization and delineation of cancer tumors for radiotherapy.
PURPOSE: Diffusion-weighted Magnetic Resonance Imaging (DWI) has been shown to be a powerful tool for cancer detection with high tumor-to-tissue contrast. This study aims to investigate the feasibility of developing a four-dimensional DWI technique (4D-DWI) for imaging respiratory motion for radiation therapy applications. MATERIALS/ METHODS: Image acquisition was performed by repeatedly imaging a volume of interest (VOI) using an interleaved multislice single-shot echo-planar imaging (EPI) 2D-DWI sequence in the axial plane. Each 2D-DWI image was acquired with an intermediately low b-value (b = 500 s/mm2 ) and with diffusion-encoding gradients in x, y, and z diffusion directions. Respiratory motion was simultaneously recorded using a respiratory bellow, and the synchronized respiratory signal was used to retrospectively sort the 2D images to generate 4D-DWI. Cine MRI using steady-state free precession was also acquired as a motion reference. As a preliminary feasibility study, this technique was implemented on a 4D digital human phantom (XCAT) with a simulated pancreas tumor. The respiratory motion of the phantom was controlled by regular sinusoidal motion profile. 4D-DWI tumor motion trajectories were extracted and compared with the input breathing curve. The mean absolute amplitude differences (D) were calculated in superior-inferior (SI) direction and anterior-posterior (AP) direction. The technique was then evaluated on two healthy volunteers. Finally, the effects of 4D-DWI on apparent diffusion coefficient (ADC) measurements were investigated for hypothetical heterogeneous tumors via simulations. RESULTS:Tumor trajectories extracted from XCAT 4D-DWI were consistent with the input signal: the average D value was 1.9 mm (SI) and 0.4 mm (AP). The average D value was 2.6 mm (SI) and 1.7 mm (AP) for the two healthy volunteers. CONCLUSION: A 4D-DWI technique has been developed and evaluated on digital phantom and human subjects. 4D-DWI can lead to more accurate respiratory motion measurement. This has a great potential to improve the visualization and delineation of cancer tumors for radiotherapy.
Authors: Felix A Breuer; Martin Blaimer; Robin M Heidemann; Matthias F Mueller; Mark A Griswold; Peter M Jakob Journal: Magn Reson Med Date: 2005-03 Impact factor: 4.668
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Authors: Ehsan Abadi; William P Segars; Benjamin M W Tsui; Paul E Kinahan; Nick Bottenus; Alejandro F Frangi; Andrew Maidment; Joseph Lo; Ehsan Samei Journal: J Med Imaging (Bellingham) Date: 2020-04-11