Table 1 Assessment of the influence of the diffusion tensor imaging (DTI) dataset on measurements of image quality, i.e. signal-to-noise (SNR) ratio, contrast-to-noise ratios (CNR) and minimal angles separating the diffusion encoding vectors.

From: High B-value diffusion tensor imaging for early detection of hippocampal microstructural alteration in a mouse model of multiple sclerosis

Measurements

Datasets

F-value

Size effect

P-value

Post-hoc tests adjusted P-value

B0

B1000-12Dir

B1000-22Dir

B2700-12Dir

B2700-22Dir

B2700-43Dir

B1000-12Dir vs. B2700-12Dir

B1000-22Dir vs. B2700-22Dir

Minimum angle (°)

–

38.4 ± 10.2

29.3 ± 10.1

38.1 ± 5.4

24.5 ± 7.5

20 ± 4.7

58.03§

0.510

 < 0.0001***

1

0.0728

SNR in hippocampus

79.5 ± 7.7

47.2 ± 3.7

47.2 ± 3.6

25 ± 1.8

24.7 ± 1.9

25.1 ± 1.9

2008.17

0.961

 < 0.0001***

 < 0.0001***

 < 0.0001***

CNR in hippocampus

–

–

1.4 ± 0.5

1.7 ± 1.2

1.7 ± 0.8

1.6 ± 0.5

2.47

0.021

0.1040

–

–

CNR in ML

–

–

1.5 ± 0.5

1.8 ± 1.3

1.9 ± 1

1.8 ± 0.6

3.78

0.031

0.0340*

–

0.0110*

CNR in SLM

–

–

1.3 ± 0.4

1.7 ± 1.2

1.6 ± 0.8

1.4 ± 0.5

4.59

0.049

0.2047

–

–

CNR in SR

–

–

1.3 ± 0.5

1.5 ± 1

1.4 ± 0.6

1.4 ± 0.5

0.824

0.007

0.4230

–

–

  1. Measurements in each dataset are expressed as mean ± standard deviation. F-values and P-values correspond to one-way repeated measures analysis of variance, except for the minimal angle (§) which corresponds to Kruskal–Wallis test (non-parametric, non repeated test). The CNRs for the B1000-12Dir was incalculable according to the FSL “Eddy” script.
  2. *P < 0.05; **P < 0.005; ***P < 0.001.
  3. B b-value, Dir number of diffusion gradient directions, ML molecular layer, SLM stratum lacunosum moleculare, SR stratum radiatum.
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