Application of super‐resolution track‐density technique: Earlier detection of aging‐related subtle alterations than morphological changes in corpus callosum from normal population?

• Published in: Journal of magnetic resonance imaging Vol. 49; no. 1; pp. 164 - 175
• Main Authors: Wang, Dan, Chen, Yu‐Jie, Li, Yue‐Hua
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.01.2019
• Subjects: Adult; Age; Age Factors; Age groups; Aged; Aging; Algorithms; Anisotropy; Corpus callosum; Corpus Callosum - diagnostic imaging; Data processing; Density measurement; Diffusion Magnetic Resonance Imaging; Diffusion Tensor Imaging; diffusion weighted MRI; Female; fiber density; Field strength; Healthy Volunteers; Humans; Image Processing, Computer-Assisted - methods; Imaging; Imaging, Three-Dimensional; Magnetic resonance imaging; Male; Measurement techniques; Middle Aged; Polynomials; Population (statistical); Regression Analysis; Retrospective Studies; Sex Factors; Statistical analysis; Statistical tests; Variance analysis; voxel‐based analysis; Young Adult; diffusion weighted MRI; aging; corpus callosum; voxel-based analysis; fiber density
• ISSN: 1053-1807; 1522-2586; 1522-2586
• DOI: 10.1002/jmri.26051

Background There are rare quantitative fiber density measurement techniques based on voxel measure changes of each corpus callosum (CC) subsegment with age. Purpose To observe the regularity of corpus callosum development in normal aging from subvoxel to macroscopic volume. Study Type Retrospective. Subjects In all, 131 healthy volunteers divided into six age groups. Field Strength/Sequence 3T MR with 32‐channel head coil T1‐3D and diffusion‐weighted imaging with six b‐values in a 30 directions sequence. Assessment Track‐density imaging (TDI) was used to visualize the complexity and the differences occurring in corpus callosum (CC) with age. TDI were reconstructed with a higher spatial voxel resolution of 0.1 mm subvoxel; TDI values are recognized as a subvoxel metric of real tract density. We reconstructed track density maps by using probabilistic streamline tractography combined with constrained spherical deconvolution. The CC was segmented into five subregions, and TDI, volume, and fractional anisotropy (FA) of each subregion in all the groups were measured using T1W‐3D images and compared. Statistical Test Polynomial regression was done to between age and (CC1, CC2, CC3, CC4, CC5) of TDI/volume/FA. Multiple comparisons test two‐way analysis of variance (ANOVA) were used to compare the differences between different age groups and sex groups in each subregion. Fisher's least significant difference test was used for the correction of the multiple comparisons. Results From the 20–70 age groups, TDI values of CC2, CC3, and CC4 increased until 40 years, when they were highest, and then decreased. CC2 (7.35556, 7.56587, 8.06036, 7.53841, 6.6956, 6.56494), CC3 (7.75372, 8.41447, 9.13178, 8.72605, 7.50106, 5.69513), CC4 (8.63414, 9.1518, 9.22451, 9.03154, 8.11556, 7.1967). There was a significant difference in the CC3 TDI between the 50/60 years groups and the 60/70 years groups (P = 0.03853 and 0.00285, respectively). The volumes of CC2, CC3, and CC4 increased between 30 and 50 years and decreased between 50 and 60 years, CC2 (0.06557, 0.07244, 0.08062, 0.07353, 0.08576, 0.06294), CC3 (0.03421, 0.03867, 0.03891, 0.03916, 0.03058, 0.03658), CC4 (0.0242, 0.01948, 0.02445, 0.02887, 0.01938, 0.01956). FA of CC2, CC3, and CC4 decreased between years 40 and 60.CC2 (0.45981, 0.47392, 0.45654, 0.45702, 0.39982, 0.35767), CC3 (0.4628, 0.49056, 0.49701, 0.46667, 0.44795, 0.36799), CC4 (0.46599, 0.52887, 0.4971, 0.53257, 0.42861, 0.43158). Data Conclusion TDI had high sensitivity for the detection of age‐related CC differences. Level of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:164–175.