Table 1.
Comparison of SE-DWI and Segmented-EPI DWI.
Fig 1.
Schematic diagram of segmented-EPI DWI.
Segmentation of the echo train is required to reduce off-resonance artefacts. The time between two 90° excitation pulses is the repetition time (TR) and the time from the first 90° excitation pulse to the central echo acquisition is the average echo time (TE). Δ is the separation time between the two applications of diffusion-encoding gradient pulses and δ refers to the duration of the diffusion-encoding gradient. RF (radiofrequency), Gz (slice gradient), Gy (phase gradient), and Gx (readout gradient).
Fig 2.
The method of zero-filling and partial Fourier transform.
This diagram shows the combination of zero filling and partial Fourier transformation and how they are applied to fill k-space. Zero filling reduces the echo train length and consequently avoids acquisition at late echo period with significant signal decay. Use of this partial Fourier transformation reduces the experiment time by 30%. Dashed lines represent K-space lines, which were not acquired by the combined zero-fill and partial Fourier accelerated acquisition.
Fig 3.
Schematic ROI representations for the measurement of DTI parameters acquired from 2D segmented-EPI DWI in vivo.
ROI were drawn manually on FA maps of each individual mouse. This image sequence represents rostral (top left) to caudal (bottom right) brain slices. The following structures were analysed: Rt (green) and Lt (brown) optic nerve (ON), forceps minor corpus callosum (fmi) (navy), rostral corpus callosum (R-cc) (red), middle corpus callosum (M-cc) (green), external capsule (ec) (yellow), fimbria (fi) (dark blue), internal capsule (ic) (green), caudal corpus callosum (C-cc) (blue), Rt (navy) and Lt (pink) optic tract (opt), Rt (brown) and Lt (red) cerebral peduncle (cp) and forceps major corpus callosum (fmj) (dark red).
Fig 4.
FA map comparison between in vivo and in situ segmented EPI-DWI, and in situ SE-DWI.
Rostral to caudal brain slices of FA maps reconstructed form in vivo segmented EPI-DWI (A), in situ segmented-EPI DWI (B) and in situ SE-DWI (C) acquired at 0.6 mm slice thickness. Distortion artefacts observed in in vivo and in situ segmented EPI-DWI are shown with red arrows.
Table 2.
Comparison of SE-DWI and Segmented-EPI DWI.
Fig 5.
Illustration of signal loss due to motion in in vivo segmented EPI DWI.
(A) b0 image, (B) and (C) DWI images, all are from the same slice position but were acquired in the presence of minimal (A, B) and excessive motion (C).
Fig 6.
Optimization of ETL segmentation to reduce image artefacts.
The FA map from 4-segment EPI-DWI (C) shows less susceptibility to motion artefacts and structure displacement compared the maps reconstructed from 10 and 8-segment ETL (A and B, respectively). This can be observed in the anterior cingulate cortex adjacent to the corpus callosum.
Fig 7.
Examples of the DTI derived parameters of the level of the mid-brain structures from in vivo 2D EPI DWI at 16.4 T.
(A) FA, (B) MD, (C) AD and (D) RD maps.
Fig 8.
Example of FA colour map of mouse brain from in vivo 2D EPI DWI data.
Left top to right bottom represent rostral to caudal brain anatomical level, the following directional colour encoding is used: red = medial-lateral, green = rostral-caudal, blue = dorsal-ventral.
Fig 9.
FA maps of the optic nerves from in vivo 2D EPI DWI data.
Images were reproducible across six mice (M1-M6) and were less susceptible to motion artefacts with reduced partial volume effects in comparison to the SE-DWI experiment. The ROI analysis used only 3–4 voxels in the centre of the nerve to reduce partial volume effects. The optic nerves are the two hyperintense structures inside the yellow box.
Fig 10.
ROI analysis of DTI parameters.
(A) FA, (B) MD, (C) AD, and (D) RD calculated from 6 adult wild-type C57BL/6 male mice imaged using in vivo segmented 2D DWI-EPI. Data are presented as mean ± standard deviation.