European Radiology Experimental (May 2023)
Improved accuracy and precision of fat-suppressed isotropic 3D T2 mapping MRI of the knee with dictionary fitting and patch-based denoising
Abstract
Abstract Purpose To develop an isotropic three-dimensional (3D) T2 mapping technique for the quantitative assessment of the composition of knee cartilage with high accuracy and precision. Methods A T2-prepared water-selective isotropic 3D gradient-echo pulse sequence was used to generate four images at 3 T. These were used for three T2 map reconstructions: standard images with an analytical T2 fit (AnT2Fit); standard images with a dictionary-based T2 fit (DictT2Fit); and patch-based-denoised images with a dictionary-based T2 fit (DenDictT2Fit). The accuracy of the three techniques was first optimized in a phantom study against spin-echo imaging, after which knee cartilage T2 values and coefficients of variation (CoV) were assessed in ten subjects in order to establish accuracy and precision in vivo. Data given as mean ± standard deviation. Results After optimization in the phantom, whole-knee cartilage T2 values of the healthy volunteers were 26.6 ± 1.6 ms (AnT2Fit), 42.8 ± 1.8 ms (DictT2Fit, p < 0.001 versus AnT2Fit), and 40.4 ± 1.7 ms (DenDictT2Fit, p = 0.009 versus DictT2Fit). The whole-knee T2 CoV reduced from 51.5% ± 5.6% to 30.5 ± 2.4 and finally to 13.1 ± 1.3%, respectively (p < 0.001 between all). The DictT2Fit improved the data reconstruction time: 48.7 ± 11.3 min (AnT2Fit) versus 7.3 ± 0.7 min (DictT2Fit, p < 0.001). Very small focal lesions were observed in maps generated with DenDictT2Fit. Conclusions Improved accuracy and precision for isotropic 3D T2 mapping of knee cartilage were demonstrated by using patch-based image denoising and dictionary-based reconstruction. Key points • Dictionary T2 fitting improves the accuracy of three-dimensional (3D) knee T2 mapping. • Patch-based denoising results in high precision in 3D knee T2 mapping. • Isotropic 3D knee T2 mapping enables the visualization of small anatomical details.
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