Zixin Deng1, Jianing Pang2, Yi Lao3, Xiaoming Bi4, Guan Wang1, Yuhua Chen1, Matthias Fenchel5, Richard Tuli3, Debiao Li1,6,7, Wensha Yang1,3, Zhaoyang Fan1,6,7. 1. 1 Department of Biomedical Sciences, Biomedical Imaging Research Institute, Cedars Sinai Medical Center , Los Angeles, CA , USA. 2. 2 MR R&D, Siemens Healthineers , Chicago, IL , USA. 3. 3 Department of Radiation Oncology, Cedars Sinai Medical Center , Los Angeles, CA , USA. 4. 4 MR R&D, Siemens Healthineers , Los Angeles, CA , USA. 5. 5 MR R&D, Siemens Healthineers , New York, NY , USA. 6. 6 Department of Bioengineering, University of California , Los Angeles, CA , USA. 7. 7 Department of Medicine, University of California , Los Angeles, CA , USA.
Abstract
METHODS: : Nine patients (seven pancreas, one liver, and one lung) were recruited. 4D-MRI was performed using two prototype k-space sorted techniques, stack-of-stars (SOS) and koosh-ball (KB) acquisitions. Post-processing using MoCoAve was implemented for both methods. Image quality score, apparent SNR (aSNR), sharpness, motion trajectory and standard deviation (σ_GTV) of the gross tumor volumes were compared between original and MoCoAve image sets. RESULTS: : All subjects successfully underwent 4D-MRI scans and MoCoAve was performed on all data sets. Significantly higher image quality scores (2.64 ± 0.39 vs 1.18 ± 0.34, p = 0.001) and aSNR (37.6 ± 15.3 vs 18.1 ± 5.7, p = 0.001) was observed in the MoCoAve images when compared to the original images. High correlation in tumor motion trajectories in the superoinferior direction (SI: 0.91 ± 0.08) and weaker in the anteroposterior (AP: 0.51 ± 0.44) and mediolateral (ML: 0.37 ± 0.23) directions, similar image sharpness (0.367 ± 0.068 vs 0.369 ± 0.072, p = 0.805), and minimal average absolute difference (0.47 ± 0.34 mm) of the motion trajectory profiles was found between the two image sets. The σ_GTV in pancreas patients was significantly (p = 0.039) lower in MoCoAve images (1.48 ± 1.35 cm3) than in the original images (2.17 ± 1.31 cm3). CONCLUSION: : MoCoAve using interphase motion correction and averaging has shown promise as a post-processing method for improving k-space sorted (SOS and KB) 4D-MRI image quality in thoracic and abdominal cancer patients. ADVANCES IN KNOWLEDGE:: The proposed method is an image based post-processing method that could be applied to many k-space sorted 4D-MRI methods for improved image quality and signal-to-noise ratio while preserving image sharpness and respiratory motion fidelity. It is a useful technique for the radiotherapy planning community who are interested in using 4D-MRI but aren't satisfied with their current MR image quality.
METHODS: : Nine patients (seven pancreas, one liver, and one lung) were recruited. 4D-MRI was performed using two prototype k-space sorted techniques, stack-of-stars (SOS) and koosh-ball (KB) acquisitions. Post-processing using MoCoAve was implemented for both methods. Image quality score, apparent SNR (aSNR), sharpness, motion trajectory and standard deviation (σ_GTV) of the gross tumor volumes were compared between original and MoCoAve image sets. RESULTS: : All subjects successfully underwent 4D-MRI scans and MoCoAve was performed on all data sets. Significantly higher image quality scores (2.64 ± 0.39 vs 1.18 ± 0.34, p = 0.001) and aSNR (37.6 ± 15.3 vs 18.1 ± 5.7, p = 0.001) was observed in the MoCoAve images when compared to the original images. High correlation in tumor motion trajectories in the superoinferior direction (SI: 0.91 ± 0.08) and weaker in the anteroposterior (AP: 0.51 ± 0.44) and mediolateral (ML: 0.37 ± 0.23) directions, similar image sharpness (0.367 ± 0.068 vs 0.369 ± 0.072, p = 0.805), and minimal average absolute difference (0.47 ± 0.34 mm) of the motion trajectory profiles was found between the two image sets. The σ_GTV in pancreaspatients was significantly (p = 0.039) lower in MoCoAve images (1.48 ± 1.35 cm3) than in the original images (2.17 ± 1.31 cm3). CONCLUSION: : MoCoAve using interphase motion correction and averaging has shown promise as a post-processing method for improving k-space sorted (SOS and KB) 4D-MRI image quality in thoracic and abdominal cancerpatients. ADVANCES IN KNOWLEDGE:: The proposed method is an image based post-processing method that could be applied to many k-space sorted 4D-MRI methods for improved image quality and signal-to-noise ratio while preserving image sharpness and respiratory motion fidelity. It is a useful technique for the radiotherapy planning community who are interested in using 4D-MRI but aren't satisfied with their current MR image quality.
Authors: W Tyler Watkins; Ruijiang Li; John Lewis; Justin C Park; Ajay Sandhu; Steve B Jiang; William Y Song Journal: Med Phys Date: 2010-06 Impact factor: 4.071
Authors: Julien Dinkel; Christian Hintze; Ralf Tetzlaff; Peter E Huber; Klaus Herfarth; Juergen Debus; Hans U Kauczor; Christian Thieke Journal: Radiother Oncol Date: 2009-04-24 Impact factor: 6.280