PURPOSE: To investigate the feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory. METHODS: Two experiments were designed to investigate the feasibility of using reference image based compressed sensing (RICS) technique in DCE-MRI of the breast. The first experiment examined the capability of RICS to faithfully reconstruct uptake curves using undersampled data sets extracted from fully sampled clinical breast DCE-MRI data. An average approach and an approach using motion estimation and motion compensation (ME/MC) were implemented to obtain reference images and to evaluate their efficacy in reducing motion related effects. The second experiment, an in vitro phantom study, tested the feasibility of RICS for improving temporal resolution without degrading the spatial resolution. RESULTS: For the uptake-curve reconstruction experiment, there was a high correlation between uptake curves reconstructed from fully sampled data by Fourier transform and from undersampled data by RICS, indicating high similarity between them. The mean Pearson correlation coefficients for RICS with the ME/MC approach and RICS with the average approach were 0.977 +/- 0.023 and 0.953 +/- 0.031, respectively. The comparisons of final reconstruction results between RICS with the average approach and RICS with the ME/MC approach suggested that the latter was superior to the former in reducing motion related effects. For the in vitro experiment, compared to the fully sampled method, RICS improved the temporal resolution by an acceleration factor of 10 without degrading the spatial resolution. CONCLUSIONS: The preliminary study demonstrates the feasibility of RICS for faithfully reconstructing uptake curves and improving temporal resolution of breast DCE-MRI without degrading the spatial resolution.
PURPOSE: To investigate the feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory. METHODS: Two experiments were designed to investigate the feasibility of using reference image based compressed sensing (RICS) technique in DCE-MRI of the breast. The first experiment examined the capability of RICS to faithfully reconstruct uptake curves using undersampled data sets extracted from fully sampled clinical breast DCE-MRI data. An average approach and an approach using motion estimation and motion compensation (ME/MC) were implemented to obtain reference images and to evaluate their efficacy in reducing motion related effects. The second experiment, an in vitro phantom study, tested the feasibility of RICS for improving temporal resolution without degrading the spatial resolution. RESULTS: For the uptake-curve reconstruction experiment, there was a high correlation between uptake curves reconstructed from fully sampled data by Fourier transform and from undersampled data by RICS, indicating high similarity between them. The mean Pearson correlation coefficients for RICS with the ME/MC approach and RICS with the average approach were 0.977 +/- 0.023 and 0.953 +/- 0.031, respectively. The comparisons of final reconstruction results between RICS with the average approach and RICS with the ME/MC approach suggested that the latter was superior to the former in reducing motion related effects. For the in vitro experiment, compared to the fully sampled method, RICS improved the temporal resolution by an acceleration factor of 10 without degrading the spatial resolution. CONCLUSIONS: The preliminary study demonstrates the feasibility of RICS for faithfully reconstructing uptake curves and improving temporal resolution of breast DCE-MRI without degrading the spatial resolution.
Authors: Brian M Dale; John A Jesberger; Jonathan S Lewin; Claudia M Hillenbrand; Jeffrey L Duerk Journal: J Magn Reson Imaging Date: 2003-11 Impact factor: 4.813
Authors: Thomas E Yankeelov; Jeffrey J Luci; Martin Lepage; Rui Li; Laura Debusk; P Charles Lin; Ronald R Price; John C Gore Journal: Magn Reson Imaging Date: 2005-05 Impact factor: 2.546
Authors: C K Kuhl; H Bieling; J Gieseke; T Ebel; P Mielcarek; F Far; P Folkers; A Elevelt; H H Schild Journal: Radiology Date: 1997-01 Impact factor: 11.105
Authors: Luminita A Tudorica; Karen Y Oh; Nicole Roy; Mark D Kettler; Yiyi Chen; Stephanie L Hemmingson; Aneela Afzal; John W Grinstead; Gerhard Laub; Xin Li; Wei Huang Journal: Magn Reson Imaging Date: 2012-07-06 Impact factor: 2.546
Authors: Yi Guo; R Marc Lebel; Yinghua Zhu; Sajan Goud Lingala; Mark S Shiroishi; Meng Law; Krishna Nayak Journal: Med Phys Date: 2016-05 Impact factor: 4.071
Authors: Laura Heacock; Yiming Gao; Samantha L Heller; Amy N Melsaether; James S Babb; Tobias K Block; Ricardo Otazo; Sungheon G Kim; Linda Moy Journal: J Magn Reson Imaging Date: 2016-11-17 Impact factor: 4.813