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- Alamidi, Daniel, et al.
(författare)
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Variable Flip Angle 3D Ultrashort Echo Time (UTE) T-1 Mapping of Mouse Lung: A Repeatability Assessment
- 2018
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Ingår i: Journal of Magnetic Resonance Imaging. - : Wiley. - 1053-1807 .- 1522-2586. ; 48:3, s. 846-852
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Tidskriftsartikel (refereegranskat)abstract
- Background: Lung T-1 is a potential translational biomarker of lung disease. The precision and repeatability of variable flip angle (VFA) T-1 mapping using modern 3D ultrashort echo time (UTE) imaging of the whole lung needs to be established before it can be used to assess response to disease and therapy. Purpose: To evaluate the feasibility of regional lung T-1 quantification with VFA 3D-UTE and to investigate long-and short-term T-1 repeatability in the lungs of naive mice. Field strength/Sequence: 3D free-breathing radial UTE (8 mu s) at 4.7T. Assessment: VFA 3D-UTE T-1 calculations were validated against T-1 values measured with inversion recovery (IR) in phantoms. Lung T-1 and proton density (S-0) measurements of whole lung and muscle were repeated five times over 1 month in free-breathing naive mice. Two consecutive T-1 measurements were performed during one of the imaging sessions. Statistical Tests: Agreement in T-1 between VFA 3D-UTE and IR in phantoms was assessed using Bland-Altman and Pearson's correlation analysis. The T-1 repeatability in mice was evaluated using coefficient of variation (CV), repeated-measures analysis of variance (ANOVA), and paired t-test. Results: Good T-1 agreement between the VFA 3D-UTE and IR methods was found in phantoms. T-1 in lung and muscle showed a 5% and 3% CV (1255 +/- 63 msec and 1432 +/- 42 msec, respectively, mean +/- SD) with no changes in T-1 or S-0 over a month. Consecutive measurements resulted in an increase of 2% in both lung T-1 and S-0. Data Conclusion: VFA 3D-UTE shows promise as a reliable T-1 mapping method that enables full lung coverage, high signal-to-noise ratio (similar to 25), and spatial resolution (300 mu m) in freely breathing animals. The precision of the VFA 3D-UTE method will enable better design and powering of studies.
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| 3. |
- McClymont, D., et al.
(författare)
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Fully Automatic Lesion Segmentation in Breast MRI Using Mean-Shift and Graph-Cuts on a Region Adjacency Graph
- 2014
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Ingår i: Journal of Magnetic Resonance Imaging. - : Wiley. - 1053-1807 .- 1522-2586. ; 39:4, s. 795-804
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Tidskriftsartikel (refereegranskat)abstract
- PurposeTo present and evaluate a fully automatic method for segmentation (i.e., detection and delineation) of suspicious tissue in breast MRI. Materials and MethodsThe method, based on mean-shift clustering and graph-cuts on a region adjacency graph, was developed and its parameters tuned using multimodal (T1, T2, DCE-MRI) clinical breast MRI data from 35 subjects (training data). It was then tested using two data sets. Test set 1 comprises data for 85 subjects (93 lesions) acquired using the same protocol and scanner system used to acquire the training data. Test set 2 comprises data for eight subjects (nine lesions) acquired using a similar protocol but a different vendor's scanner system. Each lesion was manually delineated in three-dimensions by an experienced breast radiographer to establish segmentation ground truth. The regions of interest identified by the method were compared with the ground truth and the detection and delineation accuracies quantitatively evaluated. ResultsOne hundred percent of the lesions were detected with a mean of 4.5 1.2 false positives per subject. This false-positive rate is nearly 50% better than previously reported for a fully automatic breast lesion detection system. The median Dice coefficient for Test set 1 was 0.76 (interquartile range, 0.17), and 0.75 (interquartile range, 0.16) for Test set 2. ConclusionThe results demonstrate the efficacy and accuracy of the proposed method as well as its potential for direct application across different MRI systems. It is (to the authors' knowledge) the first fully automatic method for breast lesion detection and delineation in breast MRI. J. Magn. Reson. Imaging 2014;39:795-804. (c) 2013 Wiley Periodicals, Inc.
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