Influence of temporal regularization and radial undersampling factor on compressed sensing reconstruction in dynamic contrast enhanced MRI of the breast.
| Publication Type | Academic Article |
| Authors | Kim S, Feng L, Grimm R, Freed M, Block K, Sodickson D, Moy L, Otazo R |
| Journal | J Magn Reson Imaging |
| Volume | 43 |
| Issue | 1 |
| Pagination | 261-9 |
| Date Published | 06/01/2015 |
| ISSN | 1522-2586 |
| Keywords | Artifacts, Breast Neoplasms, Data Compression, Image Enhancement, Magnetic Resonance Imaging |
| Abstract | BACKGROUND: To evaluate the influence of temporal sparsity regularization and radial undersampling on compressed sensing reconstruction of dynamic contrast-enhanced (DCE) MRI, using the iterative Golden-angle RAdial Sparse Parallel (iGRASP) MRI technique in the setting of breast cancer evaluation. METHODS: DCE-MRI examinations of the breast (n = 7) were conducted using iGRASP at 3 Tesla. Images were reconstructed with five different radial undersampling schemes corresponding to temporal resolutions between 2 and 13.4 s/frame and with four different weights for temporal sparsity regularization (λ = 0.1, 0.5, 2, and 6 times of noise level). Image similarity to time-averaged reference images was assessed by two breast radiologists and using quantitative metrics. Temporal similarity was measured in terms of wash-in slope and contrast kinetic model parameters. RESULTS: iGRASP images reconstructed with λ = 2 and 5.1 s/frame had significantly (P < 0.05) higher similarity to time-averaged reference images than the images with other reconstruction parameters (mutual information (MI) >5%), in agreement with the assessment of two breast radiologists. Higher undersampling (temporal resolution < 5.1 s/frame) required stronger temporal sparsity regularization (λ ≥ 2) to remove streaking aliasing artifacts (MI > 23% between λ = 2 and 0.5). The difference between the kinetic-model transfer rates of benign and malignant groups decreased as temporal resolution decreased (82% between 2 and 13.4 s/frame). CONCLUSION: This study demonstrates objective spatial and temporal similarity measures can be used to assess the influence of sparsity constraint and undersampling in compressed sensing DCE-MRI and also shows that the iGRASP method provides the flexibility of optimizing these reconstruction parameters in the postprocessing stage using the same acquired data. |
| DOI | 10.1002/jmri.24961 |
| PubMed ID | 26032976 |
| PubMed Central ID | PMC4666836 |